FMRI Characterization of Acute and Chronic Pain Models in Mice Lacking Nociceptor-Specific Sodium Channel NAV 1.7

Research Collection

Doctoral Thesis

Author(s): Ielacqua, Giovanna D.

Publication Date: 2018

Permanent Link: https://doi.org/10.3929/ethz-b-000273852

Rights / License: In Copyright - Non-Commercial Use Permitted

This page was generated automatically upon download from the ETH Zurich Research Collection. For more information please consult the Terms of use.

ETH Library DISS. ETH N° 25097

FMRI CHARACTERIZATION OF ACUTE AND CHRONIC PAIN MODELS IN MICE LACKING NOCICEPTOR- SPECIFIC SODIUM CHANNEL NAV 1.7

A thesis submitted to attain the degree of

DOCTOR OF SCIENCES of ETH ZURICH

(Dr. sc. ETH Zurich)

presented by

GIOVANNA DILETTA IELACQUA

Dr. Med. Vet, University of Turin, Italy

born on 03.11.1987

citizen of Italy

accepted on the recommendation of

Prof. Markus Rudin, examiner

Prof. Hanns Ulrich Zeilhofer, co-examiner

2018

“If we knew what it was we were doing, it would not be called research, would it?”

Albert Einstein

Contents Summary ...... 6

Sommario ...... 8

1. Chapter - Introduction ...... 10

1.1. Neuroimaging ...... 11

1.1.1. History of neuroimaging ...... 11

1.2. MRI ...... 13

1.2.1. History ...... 13

1.2.2 Principles of NMR and MRI ...... 14

1.2.3. Functional MRI (fMRI) ...... 19

1.2.4. rs-fMRI, applications and pitfalls ...... 21

1.3. Pain ...... 23

1.3.1. Definitions and classification ...... 23

1.3.2. Nociception and nociceptors ...... 25

1.3.3. Pain pathways ...... 27

1.3.4. Therapy: past, present, future ...... 29

1.4. Aim of the thesis ...... 32

1.5. References ...... 34

2. Chapter - Investigating the specificity of functional MRI readouts in mice and rats ...... 40

Abstract ...... 41

2.1. Introduction ...... 41

2.2. Materials and methods...... 44

2.2.1. Animals ...... 44

2.2.2. Data Acquisition ...... 45

2.2.3. Data Analysis ...... 47

2.3. Results ...... 48

2.4. Discussion and conclusions ...... 54

2.5. References ...... 59

3. Chapter - Characterization of the response to acute and neuropathic pain in a mouse model of pain insensitivity ...... 64

Abstract ...... 66

3.1. Introduction ...... 66

3.2. Materials and methods...... 69

3.2.1. Animals ...... 69

3.2.2. Data acquisition ...... 71

3.2.3. SNI surgery ...... 72

3.2.4. Behavioural tests ...... 73

3.2.5. Data Analysis ...... 74

3.3. Results ...... 75

3.4. Discussion and conclusions ...... 82

3.5. References ...... 88

4. Chapter - Discussion and conclusions ...... 93

4.1. Suitability of se-fMRI protocols in rodents ...... 94

4.2. Models of insensitivity to pain: why they can help to understand pain processing 97

4.3. Is Nav 1.7 a suitable pharmaceutical target for pain-relief? ...... 100

4.4. References ...... 102

Acknowledgements ...... 107

List of publications ...... 109

Conference proceedings ...... 110

Curriculum Vitae ...... 112

Summary

Functional MRI (fMRI) is an imaging method which has acquired increasing attention over the past decades both in the clinic as well in the pharmacological development and in basic research. Neuroimaging, specifically focusing on brain structure and functions, is a field that is constantly developing in order to improve not only the diagnosis of neurological diseases, but their progresses and regresses as well. fMRI involves a big effort in data acquisition because of its costs, the intrinsic practical acquisition challenges and data analysis which is strictly related to the applications thus being applied in humans or laboratory animals.

So far protocols for task or stimulus-evoked fMRI (se-fMRI) performed in rodents have, on one hand, been demonstrated to be extremely useful in the study of animal models of human diseases, but on the other have proven to be less sensitive and less specific in the study of animal physiology. In the present PhD thesis I aimed to evaluate the suitability of fMRI methods and stimulation paradigms previously established and commonly accepted by scientific community, to study sensory and pain processing in mice as well as in rats.

The three main challenges we targeted were:

I) The variety of stimulation paradigms that have been used in the rodents fMRI domain allows us to extensively study brain functions, however at the same time it creates confounds in regards to specificity of the detected signal, the blood oxygen level-dependent signal (BOLD);

II) The species used for se-fMRI experiments are of critical importance concerning the interpretation of the fMRI readouts and they need to be fully characterized in order to provide meaningful information for potential human applications;

III) Rodent pain models are essential to comprehend how pain develops and how it is centrally processed. Genetically modified mouse models of impaired nociception can help us understanding which pain pathways are involved in specific types of pain and can potentially provide us novel targets for pain treatment. In regards to this last point we decided to focus our research on the examination of a mouse model of congenital pain insensitivity which specifically carries a loss-of-function mutation in the NaV1.7 channel, which is a subtype of sodium voltage-gated channels, involved in the generation of action potentials in nociceptors and their conduction from the periphery to the central nervous system. The fMRI

6 characterization of such a model could give us a significant help in the evaluation of the BOLD response to peripheral nociceptive inputs and provide new insights in the research of novel pharmacological pain targets.

Additionally we investigated if and how a model of neuropathic pain, the spared nerve injury (SNI), can impact se-fMRI results and functional connectivity in this nociception-impaired mouse strain when compared to non-impaired littermates

Sommario

La risonanza magnetica funzionale, RMF o più comunemente fMRI (Functional Magnetic Resonance Imaging), è una modalità di diagnostica per immagini che ha acquisito nelle ultime decadi una crescente importanza in diversi settori, dalla clinica allo sviluppo di composti farmaceutici, fino alla ricerca di base. Il neuroimaging, tra le tecniche di diagnostica per immagini si specializza nello studio della struttura e delle funzioni del cervello ed è una branca scientifica in costante sviluppo, che si prefigge di migliorare la diagnosi di patologie neurologiche e di monitorare la progressione o l’eventuale regressione di tali patologie. La RMF comporta un grande sforzo nell'acquisizione dei dati, a causa sia dei suoi costi sia delle intrinseche difficoltà pratiche di esecuzione. Inoltre, l’analisi dei dati è un punto di cruciale importanza poiché strettamente correlata alle applicazioni cliniche che sono quindi trasferite nella medicina umana che in quella degli animali da laboratorio.

Finora i protocolli per la risonanza magnetica funzionale acquisiti durante l’esecuzione di uno specifico compito o task (task-RMf) su roditori hanno dimostrato di essere da un lato estremamente utili per studiare modelli animali di malattie umane, ma dall'altro lato meno sensibili e specifici per studiare la fisiologia animale. Nella presente tesi di dottorato abbiamo valutato l'idoneità dei metodi di MRf e dei paradigmi di stimolazione comunemente accettati nella comunità scientifica per studiare l'elaborazione centrale dello stimolo sensoriale e del dolore nei topi e nei ratti.

Le principali problematiche sulle quali questa tesi si concentra possono essere riassunte in tre punti: I) la varietà di paradigmi di stimolazione che sono stati utilizzati nel campo della RMf dei roditori, da un lato permette di studiare estensivamente le funzioni cerebrali, ma dall'altro crea confusione nei riguardi della specificità del segnale rilevato, il quale dipende dall’effetto BOLD (Blood oxygen level-dependent), ovvero dal contenuto di ossigeno presente nel sangue; II) le specie utilizzate per gli esperimenti di task-RMf sono di importanza critica per quanto riguarda l'interpretazione dei risultati di RMF e devono essere più accuratamente caratterizzate al fine di fornire informazioni significative per le potenziali applicazioni in campo umano; III) i modelli di dolore eseguiti sui roditori sono essenziali per comprendere come si sviluppi il dolore e come la processazione dello stimolo dolorifico avvenga a livello centrale.

I modelli murini di alterazione della nocicezione, in altre parole modelli murini geneticamente modificati, possono aiutare a capire quali circuiti neuronali del dolore siano coinvolti nella processazione di tipi specifici di dolore e possono fornire nuovi bersagli per il trattamento farmacologico del dolore. Riguardo quest'ultimo punto, nella presente tesi abbiamo deciso di focalizzare la nostra ricerca sull'esame di un modello murino di insensibilità al dolore causata da una particolare mutazione, la quale comporta una perdita di funzione del canale NaV 1.7, un sottotipo di canale transmembrana dipendente dal voltaggio del Sodio. Questi nocicettori sono coinvolti nella generazione e conduzione di stimoli dolorifici dalla periferia al sistema nervoso centrale. La caratterizzazione di tale modello tramite RMf è in grado di fornire un aiuto rilevante nella valutazione dell’effetto BOLD in risposta agli input nocicettivi periferici, e fornire nuovi spunti nella ricerca di nuovi target farmacologici per la cura del dolore.

Inoltre abbiamo esaminato se e in che entità la lesione del nervo peroneale comune e tibiale (spared nerve injury, SNI), un modello di dolore neuropatico, possa avere un impatto sui risultati di task-RMf e di connettività funzionale in questo particolare modello murino di nocicezione alterata.

1. Chapter - Introduction

Chapter I: Introduction

1.1. Neuroimaging

1.1.1. History of neuroimaging

Neuroimaging is a branch of imaging that comprises all the imaging techniques, which are able to visualize directly or indirectly the structure or/and the function or the nervous system. Ideally these methods should be non-invasive, have high sensitivity, and be temporally and spatially accurate. In order to find in the history of imaging the very first method to image brain function, we should go back to the last decades of 19th century, when Angelo Mosso, an Italian neuroscientist, developed the first system to indirectly image human brain activity by recording the pulsation of the human cortex in patients with skull defects (Sandrone et al., 2014; Sandrone et al., 2012). His “human circulation balance” system allowed to measure changes in cerebral blood flow upon physical and emotional activity: by converting brain pulsations into plethysmographic waves he could quantify the magnitude of the blood volume changes. He observed that patients engaged in mathematical calculation had increased brain pulsations. This rather simple observation led him to conclude that mental activity is profoundly associated to alterations in cerebral blood flow (CBF), in other words a functional measurement that could be consider the ancestor of functional magnetic resonance imaging (fMRI) concepts. Unfortunately, Mosso’s method required a sort of skull window, present in some patient with skull defects, similar to the situation in neonates displaying fontanelles, i.e. areas in which the skull is not yet completely closed prior to the completion of skull ossification.

Mosso’s work remained largely unknown and walking through the history of neuroimaging we find Walter Dandy, who in 1918 first published a peculiar brain imaging method called pneumoencephalography (PEG), a rather invasive technique that takes advantage of the contrast created by the air inflated into the spinal canal upon a lumbar spinal puncture to replace the cerebrospinal fluid (CSF) in order to visualize the ventricular system on X-ray images. This replacement exploited the contrast in X-ray images between air filled (the ventricles) and water containing structures (brain tissue). Although consistently severe side effects such as headache, neck stiffness, pyrexia, vomiting, tachycardia and abnormal

Chapter I: Introduction neurological signs have been observed even long after the imaging procedures, PEG surprisingly found its way into the clinical practice until the 1970s (Hsu et al., 2009; White et al., 1973).

Another popular technique, considerably safer than PEG, is cerebral angiography, first described and performed in the late 1920s by the Portuguese neuroscientist Egas Moniz (Artico et al., 2017; Flores, 1954; Petit-Dutaillis, 1954). This technique consists in the catheterization of a peripheral artery (commonly the femoral artery) and propagation of the infusion line to the carotid artery, where an X-ray contrast agent (CA), a iodinated compound is administered. Similarly to PEG, contrast between vascular structures containing the highly scattering contrast agent and the surrounding brain tissue is enhanced enabling the disentification of cerebral vessels. In the case of cerebral angiography many consecutives X- ray images are acquired and the architecture, structure and function of blood vessels as well as tumor masses could be evaluated.

In the early 1970s the Nobel prize laureates Allan McLeod Cormack and Sir Godfrey Newbold Hounsfield conceived (independently of each other though complementary in their approaches) the first X-ray computed tomography system. Hounsfield essentially applied Cormack's theoretical calculations into a clinical application simply known today as computed tomography (CT) (Beckmann, 2006; Hounsfield, 1973). Their discoveries also allowed the development of the back-projection image reconstruction method, which is the fundamental reconstruction method used today for CT, single-photon emission computed tomography (SPECT), positron-emission tomography (PET), as well as for some magnetic resonance imaging (MRI) methods. Shortly after the CT discovery also SPECT and PET came to life, techniques allowing imaging of organs function using radioisotopes emitting gamma photons either by direct nuclear decay (SPECT) or following the emission of an positron and its annihilation by an electron.

An additional Nobel prize was awarded to the two laureates, Sir Peter Mansfield and Paul Lauterbur, for their contributions to the development of MRI, the method that constitutes the topic of this thesis. In fact the groundbreaking development of MRI occurred in the 1970s and the method reached clinical practice in the 1980s, though was recognized by the prestigious

Chapter I: Introduction

Royal Swedish Academy of Sciences only in 2003, around 30 years after the discoveries of Mansfield and Lauterbur (Hounsfield, 1980; Mansfield and Maudsley, 1977).

Today, MRI has evolved as one of the most important tools in clinical radiology. The method exploits the magnetic properties of matter, for tissue predominantly the properties of the hydrogen nucleus. For this, MRI scanners are equipped with magnets producing a high static magnetic field, magnetic field gradients for encoding for spatial information, and radiofrequency transmitter/receiver for generating detectable signals. Basics of the MRI experiment will be described in more detail in the following section.

1.2. MRI

1.2.1. History

As already introduced in the previous section Sir Peter Mansfield and Paul Lauterbur are considered the pioneers of MR imaging, but to be fair we should go back to the early decades of the 20th century to find a first pioneer of nuclear magnetic resonance, Isidor Isaac Rabi, who received the Nobel prize in Physics in 1944. He demonstrated the nuclear magnetic resonance phenomenon by guiding a molecular beam of lithium atoms through a magnetic field and then irradiating it with radio waves. The lithium nuclei were only affected when irradiated at the proper resonance frequency (Rabi, 1926, 1929; Rabi et al., 1934).

This result was further developed independently by Edward Purcell and Felix Bloch in 1946 leading to the concept of modern nuclear magnetic resonance (NMR) (Bloch, 1946; Purcell et al., 1946) and awarded with the Nobel prize in Physics in 1952.

In the 1960s the Swiss chemist Richard Ernst developed Fourier transform NMR which significantly improved the efficiency of the NMR experiment. He proved that NMR signals can be measured either as the impulse response of the sample to the excitation with a radiofrequency pulse or by directly as a frequency response upon slowly altering the frequency across the spectral range of interest. Yet, the time domain experiment led to a dramatic improvement in sensitivity besides increasing the flexibility of the method (Ernst,

Chapter I: Introduction

1966; Ernst and Anderson, 1966) and today essentially all NMR (and MRI) experiments are carried out in the time domain. He was awarded with the Nobel prize in Chemistry for his contribution in the development of Fourier transform NMR spectroscopy in 1991.

The main contribution of Paul Lauterbur in 1973 was the development of frequency encoding, i.e. the mapping of spatial information onto frequency information by rendering the magnetic field location dependent using magnetic field gradient (Lauterbur, 1973). Sir Peter Mansfield introduced the concept of slide selective excitation, a critical component for tomographic imaging (Mansfield, 1977).

1.2.2 Principles of NMR and MRI

In order to understand MRI, it is essential to discuss the MR phenomenon, every atomic nucleus is composed of protons, positively charged particles, and neutrons, neutral particles with the only exception of hydrogen, that has no neutron. When an atom has an odd number of protons and/or neutrons there is a fundamental nuclear property called nuclear spin. We can picture a spin like a small bar magnet with his two poles. The intrinsic property of the spin makes the given nucleus rotate or better spin around its internal axis of rotation with a given angular momentum and magnetic moment. The hydrogen nucleus is composed of only one proton, and as a consequence possesses a nuclear spin ( = 1/2). Hydrogen is also the most abundant element in the human body. 𝐼𝐼

In the absence of a strong magnetic field, the orientation of the magnetic moments is completely random but when they are placed in a static magnetic field (B0) the spins align along the axis of the applied magnetic field continuing spinning around themselves. Nuclei with =

1/2 placed in a magnetic field can align parallel or antiparallel to the main direction𝐼𝐼 (conventionally the Z axes) of the applied field thus, resulting in two energy states, the energy difference between the two states being

(1) =

∆𝐸𝐸 𝛾𝛾 ∙ ℏ ∙ 𝐵𝐵0

Chapter I: Introduction in which = /2 , being Planck’s constant, and is a nucleus-specific constant called gyromagneticℏ ℎratio𝜋𝜋 ℎ(42.57 MHz/Tesla for protons).𝛾𝛾 The energy difference depends consequently upon the value of B0, and the frequency at which the spins precess around their axes is also proportional to the applied magnetic field and it is called the Larmor frequency described in the below formula:

(2) = = ∆𝐸𝐸 𝜔𝜔0 ℏ 𝛾𝛾 ∙ 𝐵𝐵0

In other words when placed in a strong magnetic field the proton precesses around the z axes at a frequency , the Larmor frequency, which is proportional to the strength of the applied magnetic field; 𝜔𝜔the0 stronger the field the higher the precession frequency.

But how is the resonance phenomenon detected? In order to detect transitions between the two energy states, energy must be supplied with a value that matches the energy difference . In MRI this energy is provided by short radiofrequency (RF) pulse of the proper frequency

∆𝐸𝐸 applied perpendicular to the main field direction, the z axis. The RF pulse (the B1 field ) flips net𝜔𝜔 magnetization or (the difference between all magnetic moments along minus the magnet moments opposite𝑀𝑀0 𝑀𝑀0 to𝑧𝑧 the field axis) away from the z axis towards the xy plane. For a tip angle (α) of 90° the transverse magnetization component reaches its maximum value

(Figure 1.1) 𝑀𝑀𝑥𝑥𝑥𝑥

Figure 1.1: Effect 90° RF pulse applied around the x-axis on a magnetization vector aligned along the static magnetic field . Based on “Introduction to Medical Imaging. Physics, Engineering and Clinical Applications” Cambridge University Press 𝐵𝐵0

Chapter I: Introduction

Following the RF pulse, the transverse component of the magnetization rotating around the z-axis at the Larmor frequency (ω0) induces a voltage in the receiver coil, the NMR signal. The NMR signal decreases due to two distinct mechanism. Fluctuations in the magnetic environment (e.g. due to molecular motion) will lead to fluctuation in the precession frequency of the individual nuclear magnets, which thereby lose phase coherence. This results in a decrease of the transverse signal component ( relaxation). Moreover, as any physical system the spin system will dissipate its excess energy𝑇𝑇2 and return to the equilibrium state with the net magnetization aligned along the main magnetic field. This process is called relaxation. Note that 𝑀𝑀 and0 relaxation are completely independent processes. 𝑇𝑇1 2 2 T1 or spin-lattice relaxation𝑇𝑇 𝑇𝑇affects the longitudinal component of the magnetization, .

During a 90° RF pulse the magnetization is flipped into the transverse plane, hence𝑀𝑀𝑧𝑧 immediately following the pulse = 0. Once the field is switched off, will gradually increase, individual spins will flip𝑀𝑀 back𝑧𝑧 to their lower𝐵𝐵1 state energy dissipating𝑀𝑀𝑧𝑧 their excess energy to the environment (the lattice, hence the name spin-lattice relaxation). The efficiency of the energy transfer depends on the nature of the local environment of the spins. Molecular motion such as overall and internal rotations, vibrations or the presence of paramagnetic centers in the vicinity of the spins will affect their relaxation behavior. The effect of these processes is commonly described by an exponential recovery curve characterized by a rate constant that corresponds to the inverse relaxation time (Figure 1.2).

Figure 1.2: Longitudinal relaxation (or spin-lattice relaxation). T1 values increase with increasing field strength. The recovery curves displayed in the figure correspond to a B0 field of 3T.Different tissues have different T1 value at a specific field strength, which can be exploited to generate contrast in T1 weighted MRI experiments. Taken from http://www.startradiology.com/the-basics/mri-technique/

Chapter I: Introduction

T2 or transverse relaxation or spin-spin relaxation is the decay of the transverse magnetization

(Mxy), which becomes maximal following a a 90° RF pulse. The individual protons precess in a highly synchronous fashion, their motion is in-phase (or ‘phase-coherent’). Yet, in addition to the main magnetic field, the protons also sense the presence of other magnetic nuclei, i.e. the chemical environment, which is of stochastic nature due to random molecular motion. This leads to slight changes in the local magnetic field and, as a result, the precession frequency will slightly vary. Correspondingly, phase coherence is lost, and the precession motion of individual nuclear magnets will get out-of-phase (dephasing). Dephasing leads to an exponential decrease in signal intensity, the rate constant being given by 1/ (Fig.1.3).

2 𝑇𝑇

Figure 1.3: Transversal relaxation. As for the longitudinal one, different tissues have different T2 value that depends on two main factors: the B1 homogeneity and the local variation in magnetic field given by the interaction between different tissues. Taken from http://www.startradiology.com/the-basics/mri-technique/

Apart from field fluctuation induced by molecular tumbling, the magnetic field may also vary due to differences in local magnetic susceptibility among different tissues. These static magnetic field gradients will also affect the resonance frequency experienced by individual spins leading to loss of phase-coherence. This is accounted for by an additional relaxation time , which is given by ∗ 2 𝑇𝑇

(3) = + 1 1 ∗ 𝑇𝑇2 𝑇𝑇2 𝛾𝛾 ∙ ∆𝐵𝐵0

Chapter I: Introduction where for the distribution of across a voxel or a region-of-interest. From the above equation,∆𝐵𝐵 0it becomes obvious that𝐵𝐵 0 . is of relevance as it is the major contrast ∗ ∗ mechanism underlying functional MRI𝑇𝑇2 (fMRI)≤ 𝑇𝑇2 signals,𝑇𝑇2

The MR signal arises from the small electrical current induced in the receiver coil by the precession of the net magnetization during the resonance. This is described by Faraday's law of induction, wherein a changing magnetic field induces a voltage in a nearby conductor, a phenomenon known as electromagnetic induction. The MR signal measured is the so-called free induction decay (FID) and corresponds to the decay of the transverse component at the rate 1/ , which will happen after any flip angle RF pulse that generates a transverse ∗ magnetization𝑇𝑇2 component (i.e. sin 0). 𝛼𝛼

In order to derive spatial information𝛼𝛼 ≠ about the object scanned, MRI uses magnetic field gradients in the three dimensions (x, y and z). These additional magnetic fields are designed such that the magnetic field changes in a linear manner along a spatial coordinate. For example, for the -coordinate we may write:

𝑥𝑥

(4) ( ) = +

𝐵𝐵 𝑥𝑥 𝐵𝐵0 𝐺𝐺𝑥𝑥 ∙ 𝑥𝑥 where indicates the gradient amplitude, i.e. the slope of the dependence. As a result, the resonance𝐺𝐺𝑥𝑥 frequency becomes dependent on the location, i.e.

(5) ( ) = ( + )

𝜔𝜔 𝑥𝑥 𝛾𝛾 ∙ 𝐵𝐵0 𝐺𝐺𝑥𝑥 ∙ 𝑥𝑥 i.e. spatial information has been translated into frequency information (frequency encoding). By encoding in three direction the signal contributions can unambiguously assigned to a location (x,y,z) in physical space. It is important to mention that the gradients system does not influence the static magnetic field in the isocenter of the magnet, where the field is constant as B0. In an MRI experiment, magnetic field gradient are transiently switched on characteristic

Chapter I: Introduction for the type of experiment. As an example, we describe the echo planar imaging (EPI) pulse sequence, which is the workhorse for fMRI experiments

EPI is one of the fastest acquisition method in MRI which allows the acquisition of one slice in 50-100ms which makes this sequence suitable to detect functional changes. Instead of measuring just one echo after each excitation pulse, it is possible to acquire many echoes after the application of a RF pulse, this happens as long as the precessing magnetization in the xy plane has not decayed away and it can be sampled with a frequency encoding gradient. In the context of this thesis gradient echo EPI (GE-EPI) was always used for fMRI data acquisition: the sequence is characterized by an excitation pulse, a single RF pulse (α), which is typically <90° with no preparation causing this sequence to be T2* weighted. At the same time a slice- selective gradient on the z-axes is switched on, this causes a dephasing of the spins, which is why a rephasing gradient in the opposite direction needs to follow. Successively a phase encoding gradient along the y-axes is applied and on the x-axes a frequency encoding gradient preceded by a dephasing one is applied. During the frequency encoding gradient the spins rephase, creating the actual signal which is ultimately detected by the RF receiver.

The use of a small flip angle allows a large amount of longitudinal magnetization to remain and to be available for the next repetition. This is why GE-EPI sequences allow us to have very short repetition time (TR).

1.2.3. Functional MRI (fMRI)

To understand what fMRI exactly measures, few other concepts need to be explained: first of all, brain activity requires energy. As the brain has no or only minimal storage capacity for glucose, its primary source of energy, it depends on a constant supply of both glucose and oxygen via the circulation. Therefore the brain is highly perfused: cerebral blood flow (CBF) measures the amount of blood supplied to the brain in a finite period of time. Changes in brain activity and hence in energy consumption rely on the adaptation of local blood flow by a mechanism called neurovascular coupling. Neurovascular coupling is essentially the

Chapter I: Introduction relationship between local neural activity and subsequent changes in local cerebral blood flow (Attwell and Laughlin, 2001; Girouard and Iadecola, 2006; Iadecola and Nedergaard, 2007).

The first fMRI experiment was conducted with the help of an external contrast agent (CA), the first pass effect of the bolus injection could demonstrate changes in cortical perfusion upon visual stimulation (Belliveau et al., 1990). This method based on the administration of an exogenous CA injection was soon substitute by another one based on an endogenous CA: our own blood, or more precisely its oxygen content.

The magnetic properties and structure of hemoglobin, oxyhemoglobin and deoxyhemoglobin were firstly described in 1936 by Pauling (Pauling and Coryell, 1936). While oxyhemoglobin is diamagnetic, deoxyhemoglobin is paramagnetic and hence an intrinsic MRI CA. Ogawa was the first to report in the early 1990s that the MRI signal depends on the oxygenation status of the blood, yielding so-called blood oxygen level dependent (BOLD) contrast. The presence of paramagnetic deoxyhemoglobin in a vessel produces local magnetic field gradients around vascular structures thereby leading to faster dephasing of the signal arising from water protons surrounding a vessel (decrease in ). These alterations in are captured in so-called ∗ ∗ gradient-echo (GE) imaging sequences including𝑇𝑇2 the EPI sequence.𝑇𝑇 .2

The mechanism can be described keeping in mind that the only source of energy of brain cells both at rest (basal metabolism) and during activity is the oxidation of glucose. Because brain heavily depends on a constant supply of glucose and oxygen via the capillary bed, the demand for energy substrates is warranted by local increases in CBF and associated increases in cerebral blood volume (CBV). As oxygen extraction becomes less efficient at higher flow rates (Buxton, 2012; Buxton and Frank, 1997; Buxton et al., 1998) local CBF increases leads to a relative increase in the amount of oxygenated hemoglobin in venous blood (Fig 1.4). This excess of oxyhemoglobin causes a change in the ratio of oxy- to deoxygenated hemoglobin, thereby leading to an local increase in , the BOLD signal, It is important to realize that ∗ functional MRI does not represent a𝑇𝑇 2direct measurement of brain activity, but the quantification of activity-associated hemodynamic changes.

Chapter I: Introduction

Figure 1.4 Physiology of the origin of BOLD contrast. Upon increase in neuronal activity the oxygen metabolism locally increase, in parallel but not proportionally the blood supply rises, consequently there is a mismatch between the oxygenated hemoglobin (Oxy-Hb) provided and the Oxy-Hb effectively used, thus leading to a change in the ratio Oxy to deoxy-Hb in favor of the oxygenated form of hemoglobin, resulting in a change in magnetic susceptibility, the main source of signal in fMRI experiment.

1.2.4. rs-fMRI, applications and pitfalls

As understandable, potential application of fMRI are innumerable; the first fMRI experiment could detect neuronal activity in the visual cortex upon photic (flickering light) stimulation (Belliveau et al., 1990). Apart from activation of the primary visual cortex in response to visual stimulation, fMRI activity patterns have been identified for a wide variety of possible paradigms such as cognitive processing of motion, patterns, colors, object recognition, but also sounds, memory, and many others. These experiments constitute so-called task- or stimulus-evoked fMRI (se-fMRI)

Beyond se-fMRI, there is also the possibility to study the BOLD signal at rest, without imposing any kind of task, because of the presence of spontaneous neuronal activity even in the absence of an external stimulus. This branch of fMRI is called resting-state fMRI (rs-fMRI) and investigates the temporal correlation of spontaneous BOLD signal fluctuations at rest across different areas of the brain.

This type of analysis reveals information on the brain’s functional organization, i.e. the intrinsic brain networks. The assumption that brain functional networks are sensitive to pathologies involving the CNS such as depression, neurodegeneration, autism, other psychiatric disorders or even chronic pain states, has prompted a wide range of experimental an clinical studies using rs-fMRI.

Chapter I: Introduction

It is important to notice that due to its hemodynamic nature the rs-fMRI data are prone to confounding contributions from factors not related to brain activity; these include overall motion of the subject head movements, respiratory motion, pulsation due to the cardiac cycle (Birn et al., 2006; Chang and Glover, 2009; Van Dijk et al., 2012). All the methodological strategies (in the data acquisition as well in the analysis) to get rid of these aforementioned confounds could be even considered as a separate science. More focus to rs- and se-fMRI experiments in mice and rats will be given in chapter II.

Chapter I: Introduction

1.3. Pain

1.3.1. Definitions and classification

Pain is according to the international association for the study of pain (IASP) an “unpleasant sensory and emotional experience associated with actual or potential tissue damage, or described in terms of such damage” (Bonica, 1979). Thus, by definition, pain is not a disease per se and also a highly subjective phenomenon. It is difficult to quantify pain, especially when the subject, be it a human, a pet or a laboratory animal, cannot report its perception.

Pain could be classified in many different ways: the most common, yet still the most debatable, is the distinction based on the duration: acute and chronic pain. We can define pain as being acute when it lasts as long as the noxious stimulus or the underlying tissue damage persists. Yet, certain pathologies or diseases can persist for years and, hence, by definition cannot be considered as acute. Accordingly, chronic pain has been defined as a pain state that persists past the normal healing time (Bonica, 1953). This definition was extended by Treede (RD., 2013), who added that chronic pain lacks the acute warning function of physiological nociception. Nowadays the most commonly accepted pragmatic definition of chronic pain is pain that persists longer than 12 weeks since the onset (Merskey H, 1994).

Apart from the definitions based on the duration it is should be clear that pain is one of the most efficient forms of protection of our body from potential serious injuries. Feeling pain drives us to withdraw our hand from fire and alerts us when something in our body is not functioning properly. For example, abdominal pain could represent for instance a serious pathological event such as the rupture of an abdominal organ, a potential peritonitis, or a simpler indigestion. In both cases the warning sign may lead us to further investigating on the causes.

As I just mentioned abdominal pain, we can also classify pain based on the location: somatic pain when joints, bones, muscles and any superficial structures are involved or visceral pain when it originates from an organ/structure sited in one of the body cavities; the latter can be further specified into thoracic, pelvic, or abdominal pain.

Chapter I: Introduction

Based on its etiology, three main categories can be distinguished: nociceptive, inflammatory or pathological pain (Woolf, 2010).

Nociceptive pain represents the feeling associated with the detection of potentially tissue- damaging noxious stimuli and is a purely protective mechanism. This type of pain is typically acute, it occurs when we feel something too hot or too sharp for instance. It is called nociceptive because it is essentially the perception and consequent processing of an intense noxious stimulus.

Inflammatory pain shares with the nociceptive pain a certain protective function, but occurs when there is tissue damage, which lasts longer than the actual noxious stimulation. In other words the feeling we have when we touch a flame is termed nociceptive pain, but if we actually burn our hand, the pain we will feel until the skin and/or underlying tissues are healed is called inflammatory pain. As the name says, inflammatory pain occurs when inflammation is taking place. In a first phase following the injury, macrophages, mast cells, neutrophils and other immune system cellular components release potent endogenous analgesics, by which pain is temporarily suppressed, the most potent one being β-endorphin. This opioid binds to the opioid receptors of the nerve end terminals and inhibits pain perception, causing transient analgesia. However, in a subsequent phase the release of inflammatory mediators from damaged cells such as ions (K+, H+), bradykinin, histamine, 5‐hydroxytryptamine (5‐HT), ATP and nitric oxide (Kidd and Urban, 2001) activate directly or indirectly peripheral nociceptors and nociceptive pathways leading to spontaneous pain. This type of pain can cause also a peripheral sensitization, in which the aforementioned inflammatory mediators sensitize nerves endings bringing their membrane potential closer to the depolarization threshold (Bolay and Moskowitz, 2002). This mechanism leads then to feel pain also when a stimulus that does not normally provoke pain is applied, in other words it causes allodynia.

Pathological pain is a disease state of the nervous system. It can occur when there is a direct damage to the somatosensory nervous system and in this case we will talk of neuropathic pain. Even in conditions, in which there is no actual tissue damage or inflammation, peripheral and central nociception amplification may occur (dysfunctional pain) in the absence of a stimulus. It is caused by altered expression and trafficking of receptors and ion channels, by a change in their depolarization threshold, by growth of collateral axons in the peripheral

Chapter I: Introduction nociception. Central adaptations may include altered synaptic connectivity or changes in central nociceptive circuits (Costigan et al., 2009).

1.3.2. Nociception and nociceptors

I already introduced the concept of nociception, which according to the IASP is the neural process of encoding noxious stimuli. Nociception does not necessarily involve a painful sensation, though it can give rise to a cardiovascular response such as an increase in heart rate or a muscular reflex. The first essential components of nociception are nociceptors. These are high-threshold sensory receptors of the peripheral somatosensory nervous system (PNS) capable of transducing and encoding noxious stimuli. They are specialized neurons with a peripheral axon and terminal responding to the stimulus, and a central branch carrying the information into the CNS. The noxious information is carried to the CNS by two different types of nerve fibers (axons): A and C-fibers; these axons connect peripheral organs to the spinal cord (CNS), and they differ in diameter and in the thickness of the myelin layer that surrounds them. C-fibers are between 0.2 to 1.5 µm thick. As they are not myelinated, the velocity in the action potential conduction is rather low (estimated between 0.5 and 2 meters per second). In contrast, A-fibers have a much bigger diameter ranging from 1 to 20 µm and are myelinated. Among the four types of A-fibers (α, β, δ and ɣ), the δ subtype is specifically activated upon noxious stimulation. It conducts the stimulus information to the brain at a speed of 5 to 40 meters per second. Aδ are slightly bigger in diameter than the C-fibers, they can reach 5 µm.

The Aα fibers are responsible for conducting proprioception and motor output, are much faster than the previously mentioned fibers conducting velocities reaching up to 120 m/s. Aβ fibers carry only touch information and proprioceptive inputs, they have conducting velocities ranging from 35 to 90m/s. Aɣ are afferent fibers terminating in the Rexed laminae I and V, they constitute the motor innervation of muscle spindles, their velocity ranges from 4 to 24 m/s.

There is no net distinction in the general function of these sensory fibers. This explains why, when there is an injury, we first experience a sharp localized acute pain (mediated by the fast A-fibers), which rapidly goes away and a few seconds later we feel a more diffuse pain mediated by the slowly conducting C-fibers (Fig. 1.5).

Chapter I: Introduction

Figure 1.5: The biphasic pain conduction behavior: it consists of a sharp immediate sensation (indicated by the sharp tall action potential in the figure) due to the fast myelinated Aδ-fibers, followed by a diffuse burning-like sensation due to the slower unmyelinated C-fibers. The painful sensation is usually a mixed effect of the two types of fibers involved. The combination is illustrated on the bottom panel. Based on (Marchand, 2008)

Nociceptors show a differential response to certain type of stimuli such as heat or cold or mechanical stimulation or even combinations of them (Craig and Bushnell, 1994). In the last decades several receptors specifically sensing noxious stimuli have been identified. Among them, the transient receptor potential channels (TRP) belong to the largest group of receptors activated by acid, eicosanoids, heat, cold and mechanical pressure (Bevan and Andersson, 2009). TRP channels are effective detectors and transducers of pain-causing stimuli. They can be found in the PNS as well as in the CNS, responding to physical and chemical stimuli as well as to mediators of immune system and neuromodulators present in the context of an injury, inflammation and other pathological conditions (Mickle et al., 2016). The mechanisms through which a specific TRP is activated and regulated cannot be reliably predicted. There are channels like TRPV1 (the vanilloid receptor subtype 1), which respond to multiple stimuli ranging from heat to compounds or toxins from plants, pro-inflammatory agents, and exocytosis (Venkatachalam and Montell, 2007). TRP channels are situated at the nerve terminations generate a change in the voltage across the neuronal membrane. Once this potential reaches the nociceptor-specific threshold, the neuron fires, starting the action potential wave that ultimately will lead to pain perception. TRP channels consist of six transmembrane segments, with different degrees of sequence homology among the different

Chapter I: Introduction subtypes, permeable to cations. TRP channels belong to a larger family (superfamily) that includes voltage-gated calcium channels (CaVs), voltage-gated potassium channels (KVs) and sodium channels (NaVs) (Yu et al., 2005). Many of these channels are central to mammalian neuromuscular, cardiovascular, and neural physiology, which makes them attractive targets for novel pharmaceutical compounds that could be used in the treatment of various disorders (England and de Groot, 2009; Perret and Luo, 2009). NaVs constitute a class of voltage-gated channels playing an essential role in the generation and propagation of action potential in sensory neurons. Among them are many subtypes that gained attention in the scientific community as elegant and specific targets for pharmacotherapeutic approaches (Ahuja et al., 2015; Lee et al., 2014; Payne et al., 2015). Among the sodium channels (NaVs), the subtype 1.7 has been extensively studied in human channelopathies (Cox et al., 2006; Fertleman et al., 2006). It is a voltage-gated sodium channel encoded by the SCN9A gene expressed in nociceptive neurons whose cell bodies are located in the dorsal root ganglion (DRG) and trigeminal ganglion, as well as in sympathetic ganglion neurons. More focus to the NaV1.7 channel will be given in chapter III.

1.3.3. Pain pathways

There are two principal ascending pain pathways from the nociceptors to the brain: the neospinothalamic and the paleospinothalamic tracts. In the neospinothalamic pathway, important in the localization of painful and thermal stimuli, the sensory afferent fiber carrying the peripheral information forms a synapse with a second order neuron located in the Rexed's lamina I (the marginal zone) and lamina II (the substantia gelatinosa) in the dorsal horn of the spinal cord, where it releases a number of excitatory neurotransmitters such as glutamate and substance P. The second order neuron decussates along the spinal cord to reach the brainstem nuclei and the anterior (ventral in quadruped animals) nucleus of the thalamus. In the thalamus it forms a synaptic connection to a third order neuron, which projects to the somatosensory areas (S1 and S2) providing information about the location and intensity of the painful stimulus (Basbaum et al., 2009). Thalamus is indeed a major relay unit for sensory information to the cerebral cortex (Sherman and Guillery, 1996). Other projection neurons, which convey the affective component of the pain perception (paleospinothalamic) are mostly

Chapter I: Introduction carrying information from C-fibers. They project to the cingulate and insular cortices via the amygdala or to the periaqueductal gray (PAG), which is an important structure of the descending feedback systems.

Two main theories exist for the modulatory pain system or inhibition of pain: the gate control theory firstly proposed by Melzack and Wall in 1965 (Melzack and Wall, 1965) and the more recent descending inhibition (Akil and Liebeskind, 1975; Gebhart, 2004).

The gate control theory describes a pain inhibition process or better a modulation of nociception taking place at the spinal cord level: Aβ fiber activation, mainly resulting from tactile stimuli activate inhibitory interneurons in the dorsal horn of the spinal cord. This results in an inhibitory effect on the pain signal conducted by the C-fibers. This explains why we find relief in rubbing for instance our hand after a painful punch: the tactile stimuli “close” the gate to ascending nociceptive pathways, and therefore pain perception. GABAergic inhibitory interneurons are densely distributed in the superficial dorsal horn and are at the basis of the gate control theory of pain (Basbaum et al., 2009). The gate theory is the rationale for the idea behind the use of transcutaneous electrical nerve stimulation (TENS) for pain relief: TENS uses low-voltage electrical current for pain suppression.

Aδ- and C- ascending pain fibers, reach the brain via the spinothalamic tract through the spinal cord innervating the Rexed laminae I and II. From lamina II, nociceptive neurons connect via a synapse to neurons in the laminae IV and VII, which have opiate receptors (target sites for endogenous opioids such as the endorphins and enkephalins) at their presynaptic ends which upon activation produce hyperpolarization resulting in the inhibition of neuronal firing and release of substance P. This circuit involves the periaqueductal gray (PAG), the locus coeruleus (LC) and the raphe nuclei, essentials in the inhibition of incoming pain information.

The RVM rostral ventromedial medulla and PAG form the basic structures of the descending system: descending control arises from cerebral structures like the anterior cingulate cortex (ACC), the dorsomedial nucleus of the hypothalamus (DMH), the amygdala (Amy) and medial prefrontal cortex (MPC); it receives inputs from the aforementioned structures and projects to the RVM, which ultimately sends its output to the dorsal horn laminae (Fig 1.6). This system

Chapter I: Introduction is also the main target of many analgesic drugs such as opioids and cyclooxygenase inhibitors (Leith et al., 2014).

Figure 1.6. Graphic representation of the PAG-RVM pain modulatory system ACC= anterior cingulate cortex, DMH= dorsomedial nucleus of the hypothalamus, Amy= amygdala, MPC= medial prefrontal cortex, PAG= periaqueductal gray, RVM= rostral ventromedial medulla, DRt= dorsal reticular nucleus, VLM= ventrolateral medulla. Taken from (Heinricher et al., 2009) 1.3.4. Therapy: past, present, future

Already in the ancient age it was not uncommon to treat pain. Hippocrates, the famous Greek physician, who lived between 460 - 370 B.C., used to prescribe willow bark and leaves, especially during childbirth to alleviate pain. His prescription was definitely not without a rationale: willow belongs to the Salix plant genus, which contains a form of salicylic acid, the active component of aspirin.

In ancient Egypt, the use of electric eels on patients was common. The reason why a low voltage electrical current causes pain relief in suffering patients has been already described in the previous section. It is the basic concept behind TENS.

Pain relief in the 19th and 20th century consisted of treatment with opiates, alcohol and cocaine. Even Coca-Cola was initially conceived as a pain-killer, as in fact it contained cocaine. During a state of unconsciousness there is no pain experience, hence anesthesia was consider a mean of pain relief even when using drastic methods such as letting the patient pass out by either hammering on his head, having him or her inhaled gas from a stove, or by compressing the carotid artery. Obviously such treatments involved a non-negligible risk for adverse effects.

Chapter I: Introduction

Nowadays we can certainly rely on many different pain management options, not only by pharmacological interventions, but also by physical (TENS, acupuncture, light therapy) and psychological (hypnosis, meditation) alternatives. Focusing on the pharmacological therapies there are two available options: non-opioid analgesics in combination with adjuvant medication and opioid analgesics (Tayeb et al., 2016). In the first group, we find non-steroidal anti-inflammatory drugs (NSAIDs) and acetaminophen, antiepileptic drugs, antidepressants and local and regional anesthetics such as lidocaine. Opioids are usually indicated for the relief of moderate to severe pain; nonetheless they always carry the risk for misuse, abuse, addiction, overdose and even death (Cheatle, 2015; Oderda et al., 2015; Vowles et al., 2015).

Apart from the misuse risk and side effects, both opioids and NSAIDs share as common feature that they are multi-action drugs not certainly designed to alleviate a specific type of pain but rather to fight the response of the organism to pain. NSAIDs are anti-inflammatory drugs, they do act on the immune system cascade inhibiting the activity of cyclooxygenase enzymes (COX- 1 and/or COX-2), which catalyze the formation of prostaglandins (the E2 for instance is responsible for the increase in neuron firing in the hypothalamus, the center of thermoregulation, causing therefore fever (Aronoff and Neilson, 2001)) and thromboxane from arachidonic acid. Current pain therapy is mainly centered on few classes of pharmaceuticals, and these pharmacological treatments may lack efficacy against different types of pain but they have systematic effects on the immune system and/or important side- effects.

The main challenge of future therapeutic approaches is to identify novel, more specific targets for pain relief. Given the variety of forms of pain, it appears plausible that different pharmaceutical interventions may be required for treating the different pain phenotypes.

In this frame, peripheral and central nociceptor-specific channels could be sophisticated and powerful options to develop analgesic drugs. In the past few years a number of powerful TRP- antagonists have been advanced into clinical trials for the treatment of different types of pain such as inflammatory, neuropathic and visceral pain (Brederson et al., 2013; Levine and Alessandri-Haber, 2007). Promising analgesic effects have been shown; yet, for the first generation of TRP-antagonist drugs, unwanted side effects have been observed (hyperthermia and impaired noxious heat sensation). Also, NaV antagonists are currently being evaluated as

Chapter I: Introduction targets for pain relief, many studies already showed the effective analgesic effects upon the antagonization of these nociceptors (Bang et al., 2018; Pertovaara, 2017; Yang et al., 2018).

Chapter I: Introduction

1.4. Aim of the thesis

Expenses on pain treatment, and in particular on chronic pain, and the loss in workforce associated to it, have become a major costs factor in our healthcare system. The economic importance and the impact that pain has on every day’s life underline the need of an ongoing research in this field. In order to better understand the genesis and evolution of pain and to investigate pain perception and processing, a range of studies are currently being performed in both humans and animals with the main goal of elucidating new targets for anti-nociceptive medication and developing more customized therapies for each type of pain and even individual.

FMRI is nowadays widely used as a non-invasive method for studying areas of neural activity in the CNS and appears to be suitable for practical use in pain research. The hope is to identify brain signatures characteristic for a given pain state that would constitute a more objective readout of pain sensation than the patient’s report that will be inevitably affected by the patient’s previous experiences, cognitive processes and emotional state. Such information should contribute to rationalize mechanisms underlying the physiopathology of pain and development novel therapeutic interventions.

The overall goal of this PhD thesis was to evaluate the suitability of fMRI methods and stimulation paradigms established in our laboratory in the course of the past decade to study sensory and pain processing in mice as well as in rats; the specific goals of the projects were:

• to test the suitability of established innocuous and noxious peripheral stimulation paradigms for fMRI studies and to elucidate the specificity of the fMRI response during sensory and painful stimulation in mice and rats; • to investigate the signature of somatosensory neuronal and vascular responses to peripheral sensory input in rodents using fMRI readouts; • to investigate the stimulus evoked fMRI (se-fMRI) response with three different stimulation paradigms (electrical, chemical and thermal stimulation of the mouse paw) in C57Bl6 mice and in mice lacking the nociceptor-specific sodium channel, NaV 1.7 both under control and chronic pain conditions; • to investigate using rs-fMRI the changes in functional connectivity (FC) in NaV 1.7 deficient mice under chronic pain conditions.

Chapter I: Introduction

Chapter II specifically focuses on the first two goals, in order to elucidate the suitability of se- fMRI protocols under different conditions, experiments have been performed both in mice and rats to elucidate potential species-related differences regarding the specificity of the fMRI response.

Chapter III examines the role of NaV1.7 channel by comparing fMRI data obtained in NaV 1.7 knock out (KO) mouse strain, a model for pain insensitivity, with those obtained in wild-type littermates. For the characterization of the KO mouse line, both se-fMRI (to analyze the differences in the processing of a peripheral stimulus) and rs-fMRI (to analyze for differences in intrinsic brain networks) have been used. In a second step, the two readouts were used to investigate differences in FC between NaV1.7 KO and wildtype mice following spared nerve injury (SNI) as model for persistent nociceptive input.

Chapter IV, critically reviews the findings of this PhD thesis projects and ends with an outlook on role of fMRI with regard to the development of novel therapeutic concepts for the treatment of pain.

Chapter I: Introduction

1.5. References

Ahuja, S., Mukund, S., Deng, L., Khakh, K., Chang, E., Ho, H., Shriver, S., Young, C., Lin, S., Johnson, J.P., Jr., Wu, P., Li, J., Coons, M., Tam, C., Brillantes, B., Sampang, H., Mortara, K., Bowman, K.K., Clark, K.R., Estevez, A., Xie, Z., Verschoof, H., Grimwood, M., Dehnhardt, C., Andrez, J.C., Focken, T., Sutherlin, D.P., Safina, B.S., Starovasnik, M.A., Ortwine, D.F., Franke, Y., Cohen, C.J., Hackos, D.H., Koth, C.M., Payandeh, J., 2015. Structural basis of Nav1.7 inhibition by an isoform-selective small-molecule antagonist. Science 350, aac5464.

Akil, H., Liebeskind, J.C., 1975. Monoaminergic mechanisms of stimulation-produced analgesia. Brain Res 94, 279-296.

Aronoff, D.M., Neilson, E.G., 2001. Antipyretics: Mechanisms of action and clinical use in fever suppression. American Journal of Medicine 111, 304-315.

Artico, M., Spoletini, M., Fumagalli, L., Biagioni, F., Ryskalin, L., Fornai, F., Salvati, M., Frati, A., Pastore, F.S., Taurone, S., 2017. Egas Moniz: 90 Years (1927-2017) from Cerebral Angiography. Front Neuroanat 11, 81.

Attwell, D., Laughlin, S.B., 2001. An energy budget for signaling in the grey matter of the brain. Journal of Cerebral Blood Flow and Metabolism 21, 1133-1145.

Bang, S., Yoo, J., Gong, X., Liu, D., Han, Q., Luo, X., Chang, W., Chen, G., Im, S.T., Kim, Y.H., Strong, J.A., Zhang, M.Z., Zhang, J.M., Lee, S.Y., Ji, R.R., 2018. Differential Inhibition of Nav1.7 and Neuropathic Pain by Hybridoma-Produced and Recombinant Monoclonal Antibodies that Target Nav1.7 : Differential activities of Nav1.7-targeting monoclonal antibodies. Neurosci Bull 34, 22-41.

Basbaum, A.I., Bautista, D.M., Scherrer, G., Julius, D., 2009. Cellular and Molecular Mechanisms of Pain. Cell 139, 267-284.

Beckmann, E.C., 2006. CT scanning the early days. Br J Radiol 79, 5-8.

Belliveau, J.W., Rosen, B.R., Kantor, H.L., Rzedzian, R.R., Kennedy, D.N., Mckinstry, R.C., Vevea, J.M., Cohen, M.S., Pykett, I.L., Brady, T.J., 1990. Functional Cerebral Imaging by Susceptibility- Contrast Nmr. Magnetic Resonance in Medicine 14, 538-546.

Bevan, S., Andersson, D.A., 2009. TRP channel antagonists for pain--opportunities beyond TRPV1. Curr Opin Investig Drugs 10, 655-663.

Chapter I: Introduction

Birn, R.M., Diamond, J.B., Smith, M.A., Bandettini, P.A., 2006. Separating respiratory-variation-related neuronal-activity-related fluctuations in fluctuations from fMRI. Neuroimage 31, 1536-1548.

Bloch, F., 1946. Nuclear Induction. Physical Review 70, 460-474.

Bolay, H., Moskowitz, M.A., 2002. Mechanisms of pain modulation in chronic syndromes. Neurology 59, S2-7.

Bonica, J.J., 1953. The management of pain of cancer. J Mich State Med Soc 52, 284-290.

Bonica, J.J., 1979. The need of a taxonomy. Pain 6, 247-248.

Brederson, J.D., Kym, P.R., Szallasi, A., 2013. Targeting TRP channels for pain relief. European Journal of Pharmacology 716, 61-76.

Buxton, R.B., 2012. Dynamic models of BOLD contrast. Neuroimage 62, 953-961.

Buxton, R.B., Frank, L.R., 1997. A model for the coupling between cerebral blood flow and oxygen metabolism during neural stimulation. Journal of Cerebral Blood Flow and Metabolism 17, 64- 72.

Buxton, R.B., Wong, E.C., Frank, L.R., 1998. Dynamics of blood flow and oxygenation changes during brain activation: The balloon model. Magnetic Resonance in Medicine 39, 855-864.

Chang, C., Glover, G.H., 2009. Relationship between respiration, end-tidal CO2, and BOLD signals in resting-state fMRI. Neuroimage 47, 1381-1393.

Cheatle, M.D., 2015. Prescription Opioid Misuse, Abuse, Morbidity, and Mortality: Balancing Effective Pain Management and Safety. Pain Med 16 Suppl 1, S3-8.

Costigan, M., Scholz, J., Woolf, C.J., 2009. Neuropathic Pain: A Maladaptive Response of the Nervous System to Damage. Annual Review of Neuroscience 32, 1-32.

Cox, J.J., Reimann, F., Nicholas, A.K., Thornton, G., Roberts, E., Springell, K., Karbani, G., Jafri, H., Mannan, J., Raashid, Y., Al-Gazali, L., Hamamy, H., Valente, E.M., Gorman, S., Williams, R., McHale, D.P., Wood, J.N., Gribble, F.M., Woods, C.G., 2006. An SCN9A channelopathy causes congenital inability to experience pain. Nature 444, 894-898.

Chapter I: Introduction

Craig, A.D., Bushnell, M.C., 1994. The thermal grill illusion: unmasking the burn of cold pain. Science 265, 252-255.

England, S., de Groot, M.J., 2009. Subtype-selective targeting of voltage-gated sodium channels. Br J Pharmacol 158, 1413-1425.

Ernst, R.R., 1966. Sensitivity Enhancement in Magnetic Resonance. In: Waugh, J.S. (Ed.), Advances in Magnetic and Optical Resonance. Academic Press, pp. 1-135.

Ernst, R.R., Anderson, W.A., 1966. Application of Fourier Transform Spectroscopy to Magnetic Resonance. Review of Scientific Instruments 37, 93-+.

Fertleman, C.R., Baker, M.D., Parker, K.A., Moffatt, S., Elmslie, F.V., Abrahamsen, B., Ostman, J., Klugbauer, N., Wood, J.N., Gardiner, R.M., Rees, M., 2006. SCN9A mutations in paroxysmal extreme pain disorder: allelic variants underlie distinct channel defects and phenotypes. Neuron 52, 767-774.

Flores, A., 1954. [The discoveries of Egas Moniz discussed at the Fifth International Congress of Neurology]. Med Contemp 72, 561-572.

Gebhart, G.F., 2004. Descending modulation of pain. Neuroscience and Biobehavioral Reviews 27, 729- 737.

Girouard, H., Iadecola, C., 2006. Neurovascular coupling in the normal brain and in hypertension, stroke, and Alzheimer disease. Journal of Applied Physiology 100, 328-335.

Heinricher, M.M., Tavares, I., Leith, J.L., Lumb, B.M., 2009. Descending control of nociception: Specificity, recruitment and plasticity. Brain Res Rev 60, 214-225.

Hounsfield, G.N., 1973. Computerized transverse axial scanning (tomography). 1. Description of system. Br J Radiol 46, 1016-1022.

Hounsfield, G.N., 1980. Computed medical imaging. Science 210, 22-28.

Hsu, W., Li, K.W., Bookland, M., Jallo, G.I., 2009. Keyhole to the brain: Walter Dandy and neuroendoscopy. J Neurosurg Pediatr 3, 439-442.

Iadecola, C., Nedergaard, M., 2007. Glial regulation of the cerebral microvasculature. Nature Neuroscience 10, 1369-1376.

Chapter I: Introduction

Kidd, B.L., Urban, L.A., 2001. Mechanisms of inflammatory pain. Br J Anaesth 87, 3-11.

Lauterbur, P.C., 1973. Image Formation by Induced Local Interactions - Examples Employing Nuclear Magnetic-Resonance. Nature 242, 190-191.

Lee, J.H., Park, C.K., Chen, G., Han, Q., Xie, R.G., Liu, T., Ji, R.R., Lee, S.Y., 2014. A monoclonal antibody that targets a NaV1.7 channel voltage sensor for pain and itch relief. Cell 157, 1393-1404.

Leith, J.L., Wilson, A.W., You, H.J., Lumb, B.M., Donaldson, L.F., 2014. Periaqueductal grey cyclooxygenase-dependent facilitation of C-nociceptive drive and encoding in dorsal horn neurons in the rat. Journal of Physiology-London 592, 5093-5107.

Levine, J.D., Alessandri-Haber, N., 2007. TRP channels: Targets for the relief of pain. Biochimica Et Biophysica Acta-Molecular Basis of Disease 1772, 989-1003.

Mansfield, P., 1977. Multi-Planar Image-Formation Using Nmr Spin Echoes. Journal of Physics C-Solid State Physics 10, L55-L58.

Mansfield, P., Maudsley, A.A., 1977. Medical imaging by NMR. Br J Radiol 50, 188-194.

Marchand, S., 2008. The physiology of pain mechanisms: From the periphery to the brain. Rheumatic Disease Clinics of North America 34, 285-309.

Melzack, R., Wall, P.D., 1965. Pain mechanisms: a new theory. Science 150, 971-979.

Merskey H, B.N.n.e.S., 1994. Classification of chronic pain. IASP Press.

Mickle, A.D., Shepherd, A.J., Mohapatra, D.P., 2016. Nociceptive TRP Channels: Sensory Detectors and Transducers in Multiple Pain Pathologies. Pharmaceuticals (Basel) 9.

Oderda, G.M., Lake, J., Rudell, K., Roland, C.L., Masters, E.T., 2015. Economic Burden of Prescription Opioid Misuse and Abuse: A Systematic Review. J Pain Palliat Care Pharmacother 29, 388-400.

Pauling, L., Coryell, C.D., 1936. The magnetic properties and structure of hemoglobin, oxyhemoglobin and carbonmonoxyhemoglobin. Proceedings of the National Academy of Sciences of the United States of America 22, 210-216.

Chapter I: Introduction

Payne, C.E., Brown, A.R., Theile, J.W., Loucif, A.J., Alexandrou, A.J., Fuller, M.D., Mahoney, J.H., Antonio, B.M., Gerlach, A.C., Printzenhoff, D.M., Prime, R.L., Stockbridge, G., Kirkup, A.J., Bannon, A.W., England, S., Chapman, M.L., Bagal, S., Roeloffs, R., Anand, U., Anand, P., Bungay, P.J., Kemp, M., Butt, R.P., Stevens, E.B., 2015. A novel selective and orally bioavailable Nav 1.8 channel blocker, PF-01247324, attenuates nociception and sensory neuron excitability. Br J Pharmacol 172, 2654-2670.

Perret, D., Luo, Z.D., 2009. Targeting voltage-gated calcium channels for neuropathic pain management. Neurotherapeutics 6, 679-692.

Pertovaara, A., 2017. Multi-target treatment of bone cancer pain using synergistic combinations of pharmacological compounds in experimental animals. Scand J Pain 14, 69-70.

Petit-Dutaillis, D., 1954. [Egas Moniz' cerebral angiography]. Med Contemp 72, 573-579.

Purcell, E.M., Torrey, H.C., Pound, R.V., 1946. Resonance Absorption by Nuclear Magnetic Moments in a Solid. Physical Review 69, 37-38.

Rabi, I.I., 1926. Spinning electrons. Nature 118, 228-228.

Rabi, I.I., 1929. Refraction of beams of molecules. Nature 123, 163-164.

Rabi, I.I., Kellogg, J.M.B., Zacharias, J.R., 1934. The magnetic moment of the proton. Physical Review 46, 0157-0163.

RD., T., 2013. Entstehung der Schmerzchronifizierung. Praktische Schmerzmedizin pp 3-13.

Sandrone, S., Bacigaluppi, M., Galloni, M.R., Cappa, S.F., Moro, A., Catani, M., Filippi, M., Monti, M.M., Perani, D., Martino, G., 2014. Weighing brain activity with the balance: Angelo Mosso's original manuscripts come to light. Brain 137, 621-633.

Sandrone, S., Bacigaluppi, M., Galloni, M.R., Martino, G., 2012. Angelo Mosso (1846-1910). J Neurol 259, 2513-2514.

Sherman, S.M., Guillery, R.W., 1996. Functional organization of thalamocortical relays. J Neurophysiol 76, 1367-1395.

Chapter I: Introduction

Tayeb, B.O., Barreiro, A.E., Bradshaw, Y.S., Chui, K.K., Carr, D.B., 2016. Durations of Opioid, Nonopioid Drug, and Behavioral Clinical Trials for Chronic Pain: Adequate or Inadequate? Pain Med 17, 2036-2046.

Van Dijk, K.R.A., Sabuncu, M.R., Buckner, R.L., 2012. The influence of head motion on intrinsic functional connectivity MRI. Neuroimage 59, 431-438.

Venkatachalam, K., Montell, C., 2007. TRP channels. Annu Rev Biochem 76, 387-417.

Vowles, K.E., McEntee, M.L., Julnes, P.S., Frohe, T., Ney, J.P., van der Goes, D.N., 2015. Rates of opioid misuse, abuse, and addiction in chronic pain: a systematic review and data synthesis. Pain 156, 569-576.

White, Y.S., Bell, D.S., Mellick, R., 1973. Sequelae to pneumoencephalography. J Neurol Neurosurg Psychiatry 36, 146-151.

Woolf, C.J., 2010. What is this thing called pain? J Clin Invest 120, 3742-3744.

Yang, Y., Mis, M.A., Estacion, M., Dib-Hajj, S.D., Waxman, S.G., 2018. NaV1.7 as a Pharmacogenomic Target for Pain: Moving Toward Precision Medicine. Trends Pharmacol Sci 39, 258-275.

Yu, F.H., Yarov-Yarovoy, V., Gutman, G.A., Catterall, W.A., 2005. Overview of molecular relationships in the voltage-gated ion channel superfamily. Pharmacol Rev 57, 387-395.

2. Chapter - Investigating the specificity of functional MRI readouts in mice and rats

Chapter II: Investigating the specificity of functional MRI readouts in mice and rats

Abstract

Stimulus-evoked fMRI experiments in mice show widespread hemodynamic responses even after innocuous stimulation, indicating a general arousal response of the animal. Systemic cardiovascular responses to stimuli appear to overrule cerebral hemodynamics and mask specific stimulus-evoked responses. Measurements in rats are less confounded by such impact, resulting in predominantly contralateral activation of cortical somatosensory cortical area involved in processing of the stimulus. In the present study, we characterized fMRI responses in further details and under three different paw stimulation paradigms (electrical, chemical and thermal) in both rats and mice. A better understanding of the interplay between specific and systemic fMRI signal contributions could help enhancing specificity in fMRI.

2.1. Introduction

In the mammalian brain, information is processed by spatially segregated functional units of local neuronal circuits. For example, sensory inputs and motor outputs to distinct body regions are mapped onto somatosensory and motor cortices with relatively little variability across individuals, a feature that has been extensively exploited in functional studies across species to monitor topological reorganization in response to training learning or following an insult. Rodents are of particular interest for such studies given their simple cortical anatomy due to the absence of surface convolutions. A variety of methods have been applied to probe neural activity such as electrophysiological recordings, optical imaging exploiting intrinsic contrast (White et al., 2011) or using either voltage or ion sensitive dyes (Chen et al., 2013; Peron et al., 2015). These readouts are complemented by non-invasive functional neuroimaging techniques including functional magnetic resonance imaging (fMRI) (Adamczak et al., 2010; Ahrens and Dubowitz, 2001). The latter provides indirect measures probing activity related hemodynamic adaptations (changes in blood oxygenation level, BOLD contrast) and therefore relies on the integrity of neurovascular coupling. The indirect nature also renders readouts susceptible to confounds associated with fluctuations in the physiological state of the (Mutschler et al., 2014). Nevertheless, fMRI is attractive as it allows full brain coverage and it is readily translatable to human studies.

Chapter II: Investigating the specificity of functional MRI readouts in mice and rats

Normal brain functional anatomy is assumed to exhibit pronounced lateralization, in other words unilateral peripheral input is processed and projected primarily in the contralateral hemisphere, and findings are supported by compelling evidences from numerous functional imaging studies in mammals including humans (Buckner et al., 1996; Buckner et al., 1998; Poplawsky et al., 2015), as well as from analyses of functional deficits elicited by focal brain lesions (Amyot et al., 2015). fMRI studies in animals involve anaesthesia, which inherently interferes with activity readouts. These effects must be balanced against potential interference of arousal related activity that may occur in response to immobilization or processing of sensory stimuli when using minimal anaesthesia. Arousal related activation would be observed in brain areas that are not primarily involved in processing specific peripheral input. The occurrence of such non-specific fMRI signals has been reported in C57BL/6 mice, which display widespread bilateral BOLD responses to unilateral innocuous and noxious peripheral stimuli irrespective of the type of anaesthesia (Schroeter et al., 2014) and mouse strain used. Even mice lacking interhemispheric connection via the corpus callosum showed significant involvement of the ipsilateral hemisphere (Schroeter et al., 2017). These widespread non-specific responses in mice have been related to arousal effects, which comprise both neurogenic and non- neurogenic components.

In contrast to mice, fMRI responses to peripheral fore- and hindpaw stimulation in rats have been consistently found in the respective contralateral somatosensory cortices as also reported by previous works from our lab (Sydekum et al., 2009; Sydekum et al., 2014). Studies in mice yielded conflicting results: while some groups reported contralateral dominance of the BOLD signal change to unilateral stimulation (Adamczak et al., 2010; Ahrens and Dubowitz, 2001; Nair and Duong, 2004; Nasrallah et al., 2014); our group consistently observed rather widespread bilateral fMRI responses that lacked topological specificity (Bosshard et al., 2010a; Schroeter et al., 2014). These observations triggered a tedious analysis of origins and the compositions of measured stimulus-evoked fMRI signals leading to the conclusion that mouse fMRI data comprise contributions from an arousal response potentially leading to widespread neural activity and hence fMRI responses and/or to stimulus-elicited changes in cardiac output. As neural activity-mediated signals are inherently weak, hemodynamic changes

Chapter II: Investigating the specificity of functional MRI readouts in mice and rats particularly associated with fluctuations in physiological state may overrule cerebral autoregulation and affect fMRI readouts. Consequently, sensory stimulus-evoked fMRI signal changes cannot be taken as a surrogate for neural activity in mice in an unreflected manner. There are also several studies reporting ipsilateral fMRI signals in rats elicited by peripheral stimulation. For example, Maandag and colleagues have associated the occurrence of widespread bilateral cortical BOLD responses to the physiological baseline state as characterized by the cerebral metabolic oxygen consumption (Maandag et al., 2007a). Similarly, noxious stimulation by injecting formalin or capsaicin into the rat hindpaw was shown to prompt widespread BOLD changes involving both hemispheres (Shih et al., 2008; Yee et al., 2016).

Based on these observations in mice and rats we hypothesized that stimulus evoked fMRI signals comprise specific contributions associated with processing of peripheral sensory input, non-specific neurogenic contributions affecting regions not directly involved in processing of peripheral stimuli as well as non-neurogenic contributions due to changes in cardiovascular parameters such as heart rate (HR), blood pressure (BP) and oxygen saturation (pO2) that may overrule cerebrovascular autoregulation and thus leading to changes in the fMRI signal intensity. While experimental evidence suggests that non-specific signal dominate the overall stimulus-evoked response in mice, it appears that in rats specificity is largely retained when using innocuous as well as noxious stimuli.

The objective of the current study was to discriminate specific and non-specific contributions to fMRI signal in rats elicited by peripheral sensory input as a function of nature and strength of stimulus and the site of stimulus administration. We analyzed BOLD fMRI responses across the rat brain for both fore- and hindpaw stimulation using a variety of sensory and nociceptive stimuli (electrical stimulation as well as chemical stimulation with capsaicin). As fore- and hindpaw exhibit different sensitivity to the applied stimuli, this would allow modulating the ratio of specific to non-specific contributions to the overall BOLD response. In addition, we investigated the BOLD fMRI response of the analogous stimuli in mice for a systematic comparison of the two species. The results clearly revealed that in isoflurane anesthetized rats, BOLD signal change in the contralateral cerebral hemisphere largely outweigh the ipsilateral ones; nevertheless, we consistently observe ipsilateral signals as well. On the other

Chapter II: Investigating the specificity of functional MRI readouts in mice and rats hand, isoflurane anesthetized mice showed widespread responses irrespective of stimulus type and strength and irrespective of whether the stimulus was applied to the forepaw or the hindpaw.

2.2. Materials and methods

2.2.1. Animals

The experiments were carried out in compliance with the Swiss law of animal protection and were approved by the Cantonal Veterinary Office (license Nr 242/2014). Female Lewis and Sprague Dawley rats (Janvier, Le Genest-St. Isle, France) and C57BL/6 mice were used in the study, with ages ranging between 12 and 20 weeks at the time point of study, and the body weights between 200 and 250 g for rats and 20 – 23 g for mice. Isoflurane anesthesia (Attane, Minrad, NY, USA) has been used for the experiments. Anesthesia was induced using 4 % isoflurane (Abbott, Cham, Switzerland) in a 4:1 air/oxygen mixture. Animal preparation was performed following standard protocols established in our lab (Grandjean et al., 2014; Schroeter et al., 2014). Upon induction of anesthesia mice and rats were endotracheally intubated and mechanically ventilated (Maraltec, Biel-Benken, Switzerland) with 80 breaths per minute (bpm) for mice and 50 bpm for rats while applying a respiration cycle of 25 % inhalation and 75 % exhalation (MRI-1 Volume Ventilator, CWI Inc., Ardmore, USA) using 1.5 % isoflurane for rats and 1.2% for mice. The tail vein was cannulated for administration of muscle relaxant (Pancuronium Bromide, Sigma-Aldrich) administered as a bolus at a dose of 1 mg/kg followed by an hourly administration of 0.5mg/kg. Body temperature was monitored with a rectal temperature probe (MLT415, ADInstruments) and kept at 36.0 ± 0.5° C using a warm-water circuit integrated into the animal support (Bruker BioSpin). For reproducible positioning, the head of the animals was placed with the incisor teeth secured over a bite bar; Ophthalmic ointment was applied onto the eyes. After MR measurements, animals were placed on a heating mat and anesthesia was maintained at 1-1.2% isoflurane while Pancuronium was metabolized, recovery was assessed by pinching the paws, testing the palpebral reflex and observing the spontaneous breathing acts. After successful recovery the

Chapter II: Investigating the specificity of functional MRI readouts in mice and rats animals were placed back into their home cage. Animal preparation, anesthesia protocols and the fore- and hindpaw stimulation paradigms were identical for the fMRI experiments and for assessment of reflexes and systemic physiological parameters. Every rat fMRI session lasted about three hours consisting of 25 minutes for animal preparation, 20 minutes for preparatory MRI scans, and 2.25h for fMRI data acquisition. For mice the fMRI session time was shortened to a maximum of two hours.

2.2.2. Data Acquisition

MRI/fMRI data were acquired using a Bruker Biospec 94/30 small animal MR system (Bruker BioSpin MRI, Ettlingen, Germany) operating at 400 MHz (9.4 T). For experiments using rats, a radiofrequency cross-coil setup (Bruker BioSpin MRI, Ettlingen, Germany) has been used with a linearly polarized birdcage resonator for signal transmission and a phased-array surface coil for signal reception. For anatomical orientation, images in the sagittal and horizontal direction allowed exact positioning of twelve adjacent coronal slices of thickness of 0.7 mm with the first slice placed 2.3 mm rostral of bregma according to a stereotaxic rat brain atlas (Paxinos and Franklin, 2012). Global 1st order shimming followed by fieldmap-based local shimming (MAPSHIM) was performed to reduce static magnetic field inhomogeneities using previously acquired field maps. BOLD fMRI data were acquired using a gradient-echo echo-planar imaging (GE-EPI) sequence with FOV = 18.5 x 11.4 mm2, Matrix = 80 x 35, yielding an in-plane voxel dimension of 231 x 326 µm2, flip angle = 60°, repetition time TR = 1000 ms, echo time TE = 12 ms, number of averages NA = 1, and 12 slices, giving a temporal resolution of 1 second per image data set. The length of the stimulus evoked fMRI (se-fMRI) paradigms was set to 740 repetitions for electrical, thermal stimulations, and 900 repetitions for the chemical stimulation.

Mice have been studied using a Bruker Biospec 94/30 small animal MR system (Bruker BioSpin MRI, Ettlingen, Germany) operating at 400 MHz (9.4 T). For mice, a four-element receive-only cryogenic phased array coil (Bruker BioSpin AG, Switzerland) was used in combination with a linearly polarized room temperature volume resonator for transmission. The shimming procedure was analogous to the one described for rats. For the fMRI measurements, data

Chapter II: Investigating the specificity of functional MRI readouts in mice and rats were acquired using a GE-EPI sequence with the following parameters: FOV = 16 x 7 mm2 and matrix size = 80 x 35 yielding an in-plane voxel dimension of 200 x 200 µm2, α = 60°, TE/TR = 12/1000 ms, NA = 1, . Twelve adjacent coronal slices with a thickness of 0.5 mm were acquired covering the anatomical regions of primary and secondary somatosensory cortex (S1, S2), primary motor cortex (M1) anterior cingulate cortex (ACC), Insula (Ins), Thalamus (Th) and Caudate Putamen (CPu) ranging from - 0.58 cm to 1.70 cm relatively to the bregma.

For electrical stimulation a pair of needle electrodes (Genuine Grass Instruments, West Warwick, USA) was inserted subcutaneously (s.c.) into the paw with a distance of two millimeters between the needles, and connected to a current stimulus isolator (A365D, World Precision Instruments Inc., Sarasota, USA). Stimulus delivery was controlled with a custom- written LabVIEW software (National Instruments, Austin, USA) and synchronized to the onset of the fMRI imaging sequence. Different amplitudes (2-6 mA for rats and 0.3 to 1.5 for mice) were applied with a pulse duration of 0.5 ms and frequency of 5Hz. The stimulus paradigm consisted of a block design starting with 180 seconds baseline followed by four cycles of 20 seconds stimulus and 120 seconds post-stimulus period. For chemical stimulation, a cannula was inserted s.c. into the paw and two different doses of capsaicin (1 - 2µg dissolved in 10µl of saline for rats and 0.5 - 1µg dissolved in 5µl for mice) have been injected. As innocuous stimulus, 0.9% NaCl solution was injected into the hindpaw (20 µl of injected volume for rats and 10µl for mice). The stimulation paradigm for both stimuli, innocuous and noxious, consisted of a 300 seconds baseline and 600 seconds post-injection signal acquisition. For thermal stimulation, a 22 x 6 mm copper heating plate controlled via a proportional–integral– derivative (PID) controller was attached to the palmar side of the paw. Temperatures of 42°C, which is considered to be the pain threshold temperature in both humans and mice (Cain et al., 2001; Reimann et al., 2016), 44°C and 46°C, considered to be a noxious stimuli, were applied. The block stimulus paradigm was identical to that applied for electrical stimulation: 180 seconds baseline followed by four cycles of 20 seconds stimulus and 120 seconds post- stimulus period. Cardiovascular parameters, such as pulse distention (PD) as measure of blood pressure changes, HR and pO2 were recorded using a fiber optic pulse oxymeter (MouseOx, STARR Life Science, Oakmont, USA) fixed to the shaved flank during electrical stimulation following the same block design applied during the se-fMRI session

Chapter II: Investigating the specificity of functional MRI readouts in mice and rats

2.2.3. Data Analysis

For analysis of the fMRI data, spatial preprocessing was performed in AFNI (http://afni.nimh.nih.gov/) and consisted of the following steps: the first 20 volumes of the data sets were discarded to account for T1 relaxation, the images of each scan were slice-time corrected, motion correction was performed by realigning all scan volumes to the first repetition, and data sets from all animals were co-registered to a template volume. Subsequently, a weak Gaussian blur (FWHM = 0.3mm) was applied. Data were corrected with global signal regression and band pass filtered for a spectral range 0.01 Hz to 0.3 Hz. For se- fMRI, the data were scaled to percentage signal change relative to baseline and detrended by adding polynomials (to the fourth order) as regressors to a general linear model (GLM).

Statistical parametric maps have been generated using a general linear model (GLM) within the SPM Software tool (Statistical Parametric Mapping; www.fil.ion.ucl.ac.uk/spm/). As a model for the stimulus-evoked BOLD response (ΔBOLD) upon stimulation, the SPM basis functions were convolved with the stimulus time course. The beta values of the GLM analysis using the gamma variate as a regressor entered the group statistics (one-sample t-test) for each group of analysis. Maps are shown as color-coded mean beta-values. For the analysis of time courses of ΔBOLD, regions-of-interest (ROIs) were defined according to a stereotaxic rat/mouse brain atlas (Paxinos and Franklin, 2012) for the contralateral (cl) and ipsilateral (il) primary somatosensory forepaw and hindpaw cortices (S1 FP, S1 HP) respectively, using AFNI. The reflex activity upon electrical stimulation of the fore- and hindpaw was rated according to: 0 = no response, 1 = whiskers movement, 2 = sporadic paw withdrawal reflex, 3 = continuous paw withdrawal reflex. Descriptive statistics are given as mean across animals ± standard deviation of the mean (SD). For statistical comparisons, t-tests, ANOVA or Pearson’s correlations were performed, statistical significance was inferred for p<0.05.

Chapter II: Investigating the specificity of functional MRI readouts in mice and rats

2.3. Results

The reflex activity upon electrical stimulation at different current amplitudes did not show any significant difference in the reaction scores between HP and FP stimulation (Figure 1) in both species. In mice we could not detected any significant difference at low nor at high amplitudes with a mean reaction score of 1.167 ± 0.5853 and 1.5 ± 0.441 for HP and FP respectively (p= 0.6533); in rats we observed a similar trend with no significant difference detected: the mean reaction score upon HP stimulation was 1.125 ± 0.7181 and upon FP stimulation 1.5 ± 0.6847 with a non-significant p value of 0.9394 (Figure 1)

Amplitude Significant p - value Mean HP Mean FP

0.4 mA No 0,116 0 0,667

Mouse 0.5 mA No 0,374 0,333 1

0.6 mA No 0,374 2 1,667

0.7 mA No 0,518 2,333 2,667

1 mA No n/a 0 0

2 mA Yes 0,024 0 0,75 Rat 3 mA No 0,320 1,5 2,25

5 mA No n/a 3 3

Figure 1: Reflex activity of anaesthetized mice and rats to electrical paw stimulation as a function of stimulus amplitude. Reaction score measured upon electrical stimulation applied on the FP or HP of anesthetized rats and mice without the administration of a muscle relaxant. The reflex activity upon electrical stimulation was identical under forepaw and hindpaw stimulation at any applied amplitude. Values shown as mean ± SD. Descriptive analysis and statistics are shown in the table below the graph. Statistical significance was determined using the Holm-Sidak method, with alpha = 0.05. Each amplitude was analyzed individually, without assuming a consistent SD.

Chapter II: Investigating the specificity of functional MRI readouts in mice and rats

Effects of electrical stimulation on cardiovascular parameters are depicted in figure 2. Similar measurements have been already acquired and shown under four different anesthesia regimes (Schroeter et al., 2014) in our research group, therefore the measurements have not been repeated: In mice, the heart rate stayed constant within the range 520-530bpm and did not respond to the stimuli. In contrast, both pulse distention and O2 saturation displayed transient increases during stimulus presentation with values returning to baseline quickly after each stimulation period. Cardiovascular parameters of rats responded differently to electrical stimulation: the HR increased by 3 to 5% during stimulation irrespective of the stimulus amplitude, while interestingly there was a decrease in PD values of the order of 10 to 15% during stimulus presentation. Similar to mice, we found a slight increase in rat pO2 upon stimulation. Similar cardiovascular responses have been measured for HP and FP stimulation.

Chapter II: Investigating the specificity of functional MRI readouts in mice and rats

Figure 2 Cardiovascular parameters measured during electrical paw stimulation in mice and rats under different amplitudes. Heart rate (beats per minute, bpm), pulse distention (measured in µm) as measure of blood pressure, and O2 saturation (expressed in %) have been recorded in bench experiments carried out under identical conditions as during the fMRI experiments. Rats have been stimulated with 2, 4 and 7 mA on FP (dashed lines) and HP (full line). A representative mouse has been stimulated with 0.5mA on the forepaw. Values represent mean values.

Chapter II: Investigating the specificity of functional MRI readouts in mice and rats

Se-fMRI data revealed specificity of evoked BOLD signals in rats upon electrical forepaw stimulation irrespective for all stimulation amplitudes tested. The statistical map obtained for a 2mA amplitude stimulus applied to the forepaw displays predominant ∆BOLD responses in the contralateral S1 FP area and thalamus (Th) (Figure 3, top panel). The difference between contra- and ipsilateral S1FP persists upon increasing the stimulus amplitude, even under conditions considered to be noxious, e.g. at 6 mA. Stimulation of the HP revealed the same result, though the difference between contra- and ipsilateral ∆BOLD responses was slightly smaller as was the overall amplitude of the response. Despite the retained specificity of the fMRI response, activity patterns appear more widespread than those observed during FP stimulation (Figure 3, bottom panel). Interestingly, while the S1FP signal amplitude showed a pronounced dependence on the stimulus amplitude, this was less evident for S1HP area (Figure 3, bottom right panel).

Figure 3 Contralateral dominance of BOLD fMRI response in rats following unilateral stimulation of FP and HP. (left) Statistical maps showing activated brain areas during FP (upper panel) and HP (bottom panel). Maps have been thresholded to significance levels p<0.05. (middle) Temporal profile of ∆BOLD signal intensity in the respective somatosensory cortical S1 areas for electrical paw stimulation at 2mA (ipsilateral: blue, contralateral: red). The profiles for the two sides during HP stimulation largely overlap. (right) Maximum ∆BOLD amplitude as a function of the current applied (2, 3, 4, 5 and 6 mA). Values are shown as mean ± SD. S1FP BOLD responses scale with stimulus amplitude, while the BOLD amplitude in the corresponding HP territory did not change upon increase in the current amplitude in the range 2mA < I < 6mA. Paw stimulation evoked a predominantly contralateral response though ipsilateral signals were consistently detected. The difference between contra- and ipsilateral responses was larger for FP than for HP.

Chapter II: Investigating the specificity of functional MRI readouts in mice and rats

In mice electrical FP stimulation elicited a widespread BOLD signal change with no difference in signal amplitudes between contralateral and ipsilateral hemisphere. Also when stimulated at low amplitudes of 0.5mA, identical ∆BOLD responses were recorded in the ipsi- and contralateral S1 areas (Figure 4, top row). Analogous responses have been measured during HP stimulation irrespective of the stimulation amplitude applied (Figure 4, bottom row). The ∆BOLD amplitude measured for HP stimulation is significantly weaker than the response to FP stimulation. Similar to the observation in rats, we found a pronounced dependence of the S1FP ∆BOLD amplitude on the stimulus amplitude, which was much less evident for the S1HP area (Figure 4, max ∆BOLD graphs)..

Figure 4 Widespread BOLD responses to unilateral electrical stimulation of FP and HP in mice. (left) Statistical maps showing activated brain areas during FP (upper panel) and HP (lower panel). Maps have been thresholded to significance levels p<0.05. (middle) Temporal profile of ∆BOLD signal intensity in the respective somatosensory cortical S1 areas for electrical paw stimulation at 0.7mA (ipsilateral: blue, contralateral: red). The profiles for the two sides largely overlap in HP as well as in FP stimulation. (right) Maximum ∆BOLD amplitude as a function of the current applied (0.5, 0.7, 1 and 1.5 mA). Values are shown as mean ± SD. BOLD responses scale with stimulus amplitude, the effect being more pronounced for FP than for HP. There is no statistical significant difference between contra- and ipsilateral BOLD responses.

The non-specific results that have been observed in mice seem to be consistent also when other type of stimulations such as chemical (saline and 0.5µg of Capsaicin) and thermal stimuli (42°, 44° and 46° C) are applied. They all elicited once again a bilateral response (Figure 5) and

Chapter II: Investigating the specificity of functional MRI readouts in mice and rats none of the comparisons between contralateral and ipsilateral BOLD signal change reached statistical significance. Upon noxious chemical stimulation (1 and 2 µg of capsaicin), rats showed a higher ∆BOLD signal increase in the contralateral S1 area of the somatosensory cortex but a consistent ipsilateral contribution has been observed (figure 6).

Figure 5 Sensory stimulation in mice, thermal stimuli at 42°, 44° and 46°C have been applied on the forepaw as well as Saline solution and 0.5µg of capsaicin injected on the palmar side of the forepaw. These different stimuli evoked a bilateral response recorded in the S1 areas on the ipsi and the contralateral side of the somatosensory cortex S1 area. Data shown as mean ± SD. The dashed line indicates the stimulus block design

Figure 6: Chemical noxious stimulation in rats. Two different concentrations, 1 and 2µg of Capsaicin have been injected on the palmar side of the forepaw. These different stimulus concentrations evoked a bilateral but not identical response recorded in the S1 areas on the ipsi and the contralateral side of the somatosensory cortex. Although the ∆BOLD change is higher in the S1 area contralateral to the applied stimulus, the recorded BOLD extracted from the ipsilateral side is robust and consistent. Data shown as mean. The dashed line indicates the stimulus block design.

Chapter II: Investigating the specificity of functional MRI readouts in mice and rats

2.4. Discussion and conclusions

While the availability of numerous genetically modified mouse strains makes fMRI in this species an attractive tool for functional phenotyping, studying brain activity patterns in response to peripheral stimuli using se-fMRI constitutes a challenge. Contradictory results have been reported by different research groups (Adamczak et al., 2010; Heindl-Erdmann et al., 2010), though there were significant differences in data quality that renders comparison difficult. Obviously, se-fMRI data of mice have to be interpreted carefully as physiological and technical confounds may inevitably affect BOLD signal changes measured. As previously discussed (Schlegel et al., 2015; Schroeter et al., 2017; Schroeter et al., 2014) cardiovascular contribution might be the dominating non-neurogenic factor affecting the neurogenic BOLD response. BOLD contrast originates from local increases in CBF to cope with the increased oxygen demand of active brain regions. Yet, changes in peripheral cardiovascular parameters

(HR, BP, pO2), e.g. as the result of an arousal response, may overrule cerebral autoregulation and prompt a generalized CBF response (Schroeter et al., 2017; Schroeter et al., 2014). A recent study has confirmed a close link between arterial blood pressure and unspecific BOLD signal changes upon electrostimulation in mice (Reimann et al., 2018) supporting our hypothesis that BOLD signal increase detected in murine somatosensory areas are prone to confounds imposed by changes in peripheral circulation (Reimann et al., 2018). One would assume that the peripheral (arousal related) response could be modified by modulating the stimulus intensity, though for neither type of the stimuli applied (electrical, thermal, chemical) the non-neurogenic contribution could be reduced to a level that made the overall response specific by reducing the stimulus amplitude to apparently innocuous levels. Only, when analyzing the response to single stimuli, some degree of contralateral dominance has been reported (Schlegel et al., 2015). Alternatively, the peripheral response can be modulated by physiological interventions. Recently, highly specific contralateral BOLD responses have been reported in mice using ketamine-xylazine anesthesia (Kim group 2018, not yet published). In this study the heart rate of the mice was of the order of 200 to 250bpm, way lower than the normal physiological range of 500-600bpm. We may speculate that under these conditions,

Chapter II: Investigating the specificity of functional MRI readouts in mice and rats peripheral contribution overruling the cerebral autoregulation could be largely suppressed maintaining the specificity of neurogenic BOLDS signals.

There is a wealth of literature documenting that in rats fMRI responses elicited by peripheral stimuli are regionally specific and reflect the segregation of functional cerebral anatomy. For example, sensory paw stimulation prompts an increase in the BOLD amplitude in the contralateral somatosensory S1 area reflecting the stimulated paw (Schmid et al., 2016; Shih et al., 2013; Sumiyoshi et al., 2012). Nevertheless, it has been demonstrated that also in rats upon highly noxious unilateral stimulation the fMRI response occurs not only in the somatosensory areas involved in the processing of the applied stimulus, but also in other non- specific brain regions, and the BOLD signal amplitudes correlates well with the increases in mean arterial pressure masking the actual changes in the local field potential reflecting neuronal activity (Jeffrey-Gauthier et al., 2013; Uchida et al., 2017) apparently depending on the type and, in particular, the strength of the applied stimulus.

Anaesthesia intrinsically interferes in any measurement of brain function: In fact, the mode of action and the dose of the anesthetic have been shown to have a profound effect on the extent of stimulus evoked BOLD responses in rats (Maandag et al., 2007b) and mice (Schlegel et al., 2015; Schroeter et al., 2014) as well as on brain functional networks in mice (Grandjean et al., 2014). Widespread BOLD responses have been observed in mice anaesthetized with commonly used agents such as isoflurane, medetomidine, propofol and urethane, though the shape of the hemodynamic response function was found to be compound specific (Schroeter et al., 2014). Variation of stimulus type (electrical, thermal and chemical) and amplitude did not affect the unspecific activation pattern in a qualitative way (figure 5), even when using very mild innocuous stimulation paradigms (current amplitude 0.5mA, paw temperature 42°C, and saline injected s.c.). It has been shown that very weak stimuli such a single electrical pulses have to be administered to preserve topological specificity. This is in contrast with fMRI studies in rats, in which using analogous anesthesia regimes (isoflurane) and stimulation paradigms report fMRI responses reflecting the functional architecture of the brain with specific signal changes in the topological area representing the simulated limb. Nevertheless, also in rat fMRI, signal in the hemisphere ipsilateral to the stimulated limb have been reported, associated with the intrinsic metabolic state of the animals (Maandag et al., 2007b) or when

Chapter II: Investigating the specificity of functional MRI readouts in mice and rats using noxious stimuli (e.g. administration of 1 and 2 µg of capsaicin, Fig. 6). In line with the findings in mice we speculate that the ipsilateral contribution in the latter cases is associated with an arousal-induced neurogenic and non-neurogenic CBF response.

FP and HP exhibit different susceptibility to stimulation. While BOLD responses in the S1FP to electrical stimulation scaled with the stimulus amplitude in mice and to lesser extend also in rats for the stimulus amplitudes used, this dependence was weaker for the S1HP response for both species. The weaker response observed in rats might be related to the use of higher stimulus intensities used in these experiments, i.e. the BOLD response was approaching saturation. Nevertheless, the initial slope ∆BOLD/mA of the FP response is significantly larger in mice than in rats. HP responses were in general weaker than FP response; moreover, we did not observed a difference regarding the two species. This differential BOLD response to FP or HP stimulation might be attributed to the differences in receptor density. In humans the density of sensory receptors and the variety of them is for functional reasons higher on the hands than on the feet (Johansson, 1978; Johansson and Vallbo, 1979), Similar to humans, rodents use their forelimbs for much more complex functions than their hind limbs, which might explain the larger extent of the respective cortical area as well as the higher dynamic range of BOLD responses reflecting overall synaptic activity. Yet, many rodent models of human pathologies, such as models of neuropathic pain (Howard et al., 2005; Kim and Chung, 1992; Ralvenius et al., 2015), are typically performed on the hind limbs for simplicity and better anatomical accessibility, which may limit the sensitivity of the fMRI readouts.. fMRI is an indirect readout of neural activity that depends on a complex neurovascular coupling mechanism an therefore is prone to confounds (Huneau et al., 2015). For example, drug effects on NVC will inevitably alter hemodynamic responses as revealed by anesthetic specific hemodynamic response functions in mice (Schlegel et al., 2015; Schroeter et al., 2014) and rats (Maandag et al., 2007b) as well as the potential interference of the general physiological state or stimulus induced alteration in the physiological state (Schroeter et al., 2014). Correlations of fMRI traces with more immediate readouts of neural activity might allow separating neurogenic from non-neurogenic BOLD signals. For example, it could be also demonstrated that neuronal activity as derived from measurement of Ca2+ influx using fluorescent Ca2+-indicators is tightly related to BOLD fMRI signals in rat S1 upon paw

Chapter II: Investigating the specificity of functional MRI readouts in mice and rats stimulation, though fMRI signals were found to be also affected by astrocyte activity (Schulz et al., 2012). Recently, these methods have been adapted to allow for simultaneous fluorescence/fMRI in mice (Schlegel et al., 2018) .

The cerebral autoregulatory system is responsible to maintain a CBF in the physiological range, buffering potential dangerous fluctuations that might be elicited by strong alterations cardiovascular tone. It has been shown that in rats an arterial blood pressure fluctuation within the range of 60-120 mmHg is efficiently compensated by cerebral autoregulation (Ferrari et al., 2012; Gozzi et al., 2007). This reduces the sensitivity to peripheral fluctuations and facilitates the detection of region specific BOLD response. Yet, in mice, blood pressure changes are tightly related, if not fully overlapping, to the BOLD response detected (Reimann et al., 2018) which might explain the failure of the autoregulation in the suppression of peripheral vascular contribution resulting in widespread brain activation.

In conclusion, se-fMRI signals reflecting central processing of peripheral sensory stimuli are composed of neurogenic and non-neurogenic contributions, the weight of which differs across species. While in rats the hemodynamic response elicited by neural activity in the corresponding functional topological area outweighs any non-neurogenic contributions, this is not the case in mice when using commonly used anesthetics such as isoflurane. In this case, the signal is dominated by a cerebrovascular response most likely caused by changes in peripheral cardiovascular physiology that overrules cerebral autoregulation, leading to widespread BOLD responses. This behavior is observed for different types and amplitudes of stimuli and for different anesthesia protocols. Different strategies are conceivable to overcome this limitation: 1) Use of a weak peripheral stimulus may minimize the systemic response and such retain topological specificity of the stimulus-evoked response. This has been demonstrated when stimulating the paws with individual pulses (Schlegel et al., 2015). When using no stimulus of any kind, i.e. monitoring spontaneous activity in the mouse brain to analyze functional connectivity in the mouse brain, results obtained in mice are fully compatible with results obtained in other species (Grandjean et al., 2014; Jonckers et al., 2011a; Zerbi et al., 2015). 2) The cardiovascular system might be pharmacologically modulated to tamper its susceptibility to changes in the arousal state. A recent study revealed that using an anesthesia regime that induces severe bradycardia allowed retaining the topological

Chapter II: Investigating the specificity of functional MRI readouts in mice and rats specificity of the BOLD signal in response to FP stimulation also in mice (Kim group, 2018 not yet published). 3) The use of non-hemodynamic readouts would eliminate any hemodynamic confounds. Diffusion fMRI has been suggested as an alternative readout, yet the origin of these signals is still a matter of debate and the approach is considerably less straightforward than conventional BOLD fMRI; alternatively, optoacoustic imaging may be used to monitor Ca2+ based neuronal signals under in vivo condition in zebra fish (Dean-Ben et al., 2017). The method could be translated to mice, though it would be invasive and limited to superficial structures. In conclusion the combination of different readouts of neuronal activity may help to disentangle the various contributions relevant for neurovascular coupling and the BOLD signal.

Chapter II: Investigating the specificity of functional MRI readouts in mice and rats

2.5. References

Adamczak, J.M., Farr, T.D., Seehafer, J.U., Kalthoff, D., Hoehn, M., 2010. High field BOLD response to forepaw stimulation in the mouse. Neuroimage 51, 704-712.

Ahrens, E.T., Dubowitz, D.J., 2001. Peripheral somatosensory fMRI in mouse at 11.7 T. NMR Biomed 14, 318-324.

Amyot, F., Arciniegas, D.B., Brazaitis, M.P., Curley, K.C., Diaz-Arrastia, R., Gandjbakhche, A., Herscovitch, P., Hinds, S.R., 2nd, Manley, G.T., Pacifico, A., Razumovsky, A., Riley, J., Salzer, W., Shih, R., Smirniotopoulos, J.G., Stocker, D., 2015. A Review of the Effectiveness of Neuroimaging Modalities for the Detection of Traumatic Brain Injury. J Neurotrauma 32, 1693- 1721.

Bosshard, S.C., Baltes, C., Wyss, M.T., Mueggler, T., Weber, B., Rudin, M., 2010a. Assessment of brain responses to innocuous and noxious electrical forepaw stimulation in mice using BOLD fMRI. Pain 151, 655-663.

Buckner, R.L., Bandettini, P.A., O'Craven, K.M., Savoy, R.L., Petersen, S.E., Raichle, M.E., Rosen, B.R., 1996. Detection of cortical activation during averaged single trials of a cognitive task using functional magnetic resonance imaging. Proc Natl Acad Sci U S A 93, 14878-14883.

Buckner, R.L., Goodman, J., Burock, M., Rotte, M., Koutstaal, W., Schacter, D., Rosen, B., Dale, A.M., 1998. Functional-anatomic correlates of object priming in humans revealed by rapid presentation event-related fMRI. Neuron 20, 285-296.

Cain, D.M., Khasabov, S.G., Simone, D.A., 2001. Response properties of mechanoreceptors and nociceptors in mouse glabrous skin: an in vivo study. J Neurophysiol 85, 1561-1574.

Chen, J.L., Andermann, M.L., Keck, T., Xu, N.L., Ziv, Y., 2013. Imaging neuronal populations in behaving rodents: paradigms for studying neural circuits underlying behavior in the mammalian cortex. J Neurosci 33, 17631-17640.

Dean-Ben, X.L., Gottschalk, S., Sela, G., Shoham, S., Razansky, D., 2017. Functional optoacoustic neuro- tomography of calcium fluxes in adult zebrafish brain in vivo. Optics Letters 42, 959-962.

Ferrari, L., Turrini, G., Crestan, V., Bertani, S., Cristofori, P., Bifone, A., Gozzi, A., 2012. A robust experimental protocol for pharmacological fMRI in rats and mice. J Neurosci Methods 204, 9- 18.

Chapter II: Investigating the specificity of functional MRI readouts in mice and rats

Gozzi, A., Ceolin, L., Schwarz, A., Reese, T., Bertani, S., Crestan, V., Bifone, A., 2007. A multimodality investigation of cerebral hemodynamics and autoregulation in pharmacological MRI. Magn Reson Imaging 25, 826-833.

Grandjean, J., Schroeter, A., Batata, I., Rudin, M., 2014. Optimization of anesthesia protocol for resting- state fMRI in mice based on differential effects of anesthetics on functional connectivity patterns. Neuroimage 102 Pt 2, 838-847.

Heindl-Erdmann, C., Axmann, R., Kreitz, S., Zwerina, J., Penninger, J., Schett, G., Brune, K., Hess, A., 2010. Combining functional magnetic resonance imaging with mouse genomics: new options in pain research. Neuroreport 21, 29-33.

Howard, R.F., Walker, S.M., Mota, P.M., Fitzgerald, M., 2005. The ontogeny of neuropathic pain: Postnatal onset of mechanical allodynia in rat spared nerve injury (SNI) and chronic constriction injury (CCI) models. Pain 115, 382-389.

Huneau, C., Benali, H., Chabriat, H., 2015. Investigating Human Neurovascular Coupling Using Functional Neuroimaging: A Critical Review of Dynamic Models. Frontiers in Neuroscience 9.

Jeffrey-Gauthier, R., Guillemot, J.P., Piche, M., 2013. Neurovascular coupling during nociceptive processing in the primary somatosensory cortex of the rat. Pain 154, 1434-1441.

Johansson, R.S., 1978. Tactile sensibility in the human hand: receptive field characteristics of mechanoreceptive units in the glabrous skin area. J Physiol 281, 101-125.

Johansson, R.S., Vallbo, A.B., 1979. Tactile sensibility in the human hand: relative and absolute densities of four types of mechanoreceptive units in glabrous skin. J Physiol 286, 283-300.

Jonckers, E., Van Audekerke, J., De Visscher, G., Van der Linden, A., Verhoye, M., 2011a. Functional connectivity fMRI of the rodent brain: comparison of functional connectivity networks in rat and mouse. PLoS One 6, e18876.

Kim, S.H., Chung, J.M., 1992. An experimental model for peripheral neuropathy produced by segmental spinal nerve ligation in the rat. Pain 50, 355-363.

Maandag, N.J., Coman, D., Sanganahalli, B.G., Herman, P., Smith, A.J., Blumenfeld, H., Shulman, R.G., Hyder, F., 2007a. Energetics of neuronal signaling and fMRI activity. Proc Natl Acad Sci U S A 104, 20546-20551.

Chapter II: Investigating the specificity of functional MRI readouts in mice and rats

Maandag, N.J.G., Coman, D., Sanganahalli, B.G., Herman, P., Smith, A.J., Blumenfeld, H., Shulman, R.G., Hyder, F., 2007b. Energetics of neuronal signaling and fMRI activity. Proceedings of the National Academy of Sciences of the United States of America 104, 20546-20551.

Mutschler, I., Wieckhorst, B., Meyer, A.H., Schweizer, T., Klarhofer, M., Wilhelm, F.H., Seifritz, E., Ball, T., 2014. Who gets afraid in the MRI-scanner? Neurogenetics of state-anxiety changes during an fMRI experiment. Neurosci Lett 583, 81-86.

Nair, G., Duong, T.Q., 2004. Echo-planar BOLD fMRI of mice on a narrow-bore 9.4 T magnet. Magn Reson Med 52, 430-434.

Nasrallah, F.A., Tay, H.C., Chuang, K.H., 2014. Detection of functional connectivity in the resting mouse brain. Neuroimage 86, 417-424.

Paxinos, G., Franklin, K., 2012. Paxinos and Franklin's the Mouse Brain in Stereotaxic Coordinates 4th Edition. Academic Press Peron, S., Chen, T.W., Svoboda, K., 2015. Comprehensive imaging of cortical networks. Curr Opin Neurobiol 32, 115-123.

Poplawsky, A.J., Fukuda, M., Murphy, M., Kim, S.G., 2015. Layer-Specific fMRI Responses to Excitatory and Inhibitory Neuronal Activities in the Olfactory Bulb. J Neurosci 35, 15263-15275.

Ralvenius, W.T., Benke, D., Acuna, M.A., Rudolph, U., Zeilhofer, H.U., 2015. Analgesia and unwanted benzodiazepine effects in point-mutated mice expressing only one benzodiazepine-sensitive GABAA receptor subtype. Nat Commun 6, 6803.

Reimann, H.M., Hentschel, J., Marek, J., Huelnhagen, T., Todiras, M., Kox, S., Waiczies, S., Hodge, R., Bader, M., Pohlmann, A., Niendorf, T., 2016. Normothermic Mouse Functional MRI of Acute Focal Thermostimulation for Probing Nociception. Sci Rep 6, 17230.

Reimann, H.M., Todiras, M., Hodge, R., Huelnhagen, T., Millward, J.M., Turner, R., Seeliger, E., Bader, M., Pohlmann, A., Niendorf, T., 2018. Somatosensory BOLD fMRI reveals close link between salient blood pressure changes and the murine neuromatrix. Neuroimage 172, 562-574.

Schlegel, F., Schroeter, A., Rudin, M., 2015. The hemodynamic response to somatosensory stimulation in mice depends on the anesthetic used: Implications on analysis of mouse fMRI data. Neuroimage 116, 40-49.

Chapter II: Investigating the specificity of functional MRI readouts in mice and rats

Schlegel, F., Sych, Y., Schroeter, A., Stobart, J., Weber, B., Helmchen, F., Rudin, M., 2018. Fiber-optic implant for simultaneous fluorescence-based Calcium recordings and BOLD fRMI in mice. Nature Protocols.

Schmid, F., Wachsmuth, L., Schwalm, M., Prouvot, P.H., Jubal, E.R., Fois, C., Pramanik, G., Zimmer, C., Faber, C., Stroh, A., 2016. Assessing sensory versus optogenetic network activation by combining (o)fMRI with optical Ca2+ recordings. Journal of Cerebral Blood Flow and Metabolism 36, 1885-1900.

Schroeter, A., Grandjean, J., Schlegel, F., Saab, B.J., Rudin, M., 2017. Contributions of structural connectivity and cerebrovascular parameters to functional magnetic resonance imaging signals in mice at rest and during sensory paw stimulation. J Cereb Blood Flow Metab 37, 2368- 2382.

Schroeter, A., Schlegel, F., Seuwen, A., Grandjean, J., Rudin, M., 2014. Specificity of stimulus-evoked fMRI responses in the mouse: The influence of systemic physiological changes associated with innocuous stimulation under four different anesthetics. Neuroimage 94, 372-384.

Schulz, K., Sydekum, E., Krueppel, R., Engelbrecht, C.J., Schlegel, F., Schroter, A., Rudin, M., Helmchen, F., 2012. Simultaneous BOLD fMRI and fiber-optic calcium recording in rat neocortex. Nat Methods 9, 597-602.

Shih, Y.Y., Chang, C., Chen, J.C., Jaw, F.S., 2008. BOLD fMRI mapping of brain responses to nociceptive stimuli in rats under ketamine anesthesia. Med Eng Phys 30, 953-958.

Shih, Y.Y., Chen, Y.Y., Lai, H.Y., Kao, Y.C., Shyu, B.C., Duong, T.Q., 2013. Ultra high-resolution fMRI and electrophysiology of the rat primary somatosensory cortex. Neuroimage 73, 113-120.

Sumiyoshi, A., Suzuki, H., Ogawa, T., Riera, J.J., Shimokawa, H., Kawashima, R., 2012. Coupling between gamma oscillation and fMRI signal in the rat somatosensory cortex: Its dependence on systemic physiological parameters. Neuroimage 60, 738-746.

Sydekum, E., Baltes, C., Ghosh, A., Mueggler, T., Schwab, M.E., Rudin, M., 2009. Functional reorganization in rat somatosensory cortex assessed by fMRI: Elastic image registration based on structural landmarks in fMRI images and application to spinal cord injured rats. Neuroimage 44, 1345-1354.

Sydekum, E., Ghosh, A., Gullo, M., Baltes, C., Schwab, M., Rudin, M., 2014. Rapid functional reorganization of the forelimb cortical representation after thoracic spinal cord injury in adult rats. Neuroimage 87, 72-79.

Chapter II: Investigating the specificity of functional MRI readouts in mice and rats

Uchida, S., Bois, S., Guillemot, J.P., Leblond, H., Piche, M., 2017. Systemic blood pressure alters cortical blood flow and neurovascular coupling during nociceptive processing in the primary somatosensory cortex of the rat. Neuroscience 343, 250-259.

White, B.R., Bauer, A.Q., Snyder, A.Z., Schlaggar, B.L., Lee, J.M., Culver, J.P., 2011. Imaging of functional connectivity in the mouse brain. PLoS One 6, e16322.

Yee, J.R., Kenkel, W.M., Kulkarni, P., Moore, K., Perkeybile, A.M., Toddes, S., Amacker, J.A., Carter, C.S., Ferris, C.F., 2016. BOLD fMRI in awake prairie voles: A platform for translational social and affective neuroscience. Neuroimage 138, 221-232.

Zerbi, V., Grandjean, J., Rudin, M., Wenderoth, N., 2015. Mapping the mouse brain with rs-fMRI: An optimized pipeline for functional network identification. Neuroimage 123, 11-21.

3. Chapter - Characterization of the response to acute and neuropathic pain in a mouse model of pain insensitivity

Chapter III: Characterization of the response to acute and neuropathic pain in a mouse model of pain insensitivity

“The two enemies of human happiness are pain and boredom”

Arthur Schopenauer

Chapter III: Characterization of the response to acute and neuropathic pain in a mouse model of pain insensitivity Abstract fMRI has been widely used to assess changes in brain activity evoked by innocuous and noxious stimuli. However, stimulus-evoked fMRI measurements in mice have turned out challenging, and it is still under investigation whether and under which conditions stimulus- evoked fMRI applications in mice can lead to reliable readouts. Se-fMRI could be a useful tool to characterize genetically modified mouse strains, such as mice exhibiting altered sensitivity to pain. In this study we could characterize Nav1.7 KO mice with respect to neural processing of three different types of peripheral stimuli and compared to a wildtype control group. We could demonstrate that Nav1.7 KO mice do not display any significant change in ∆BOLD signal upon noxious stimulation. Furthermore, resting-state fMRI revealed that the loss Nav 1.7 channels does not interfere with the physiological development of functional brain networks. Rs-fMRI longitudinal analysis performed during the course of a neuropathic pain model (spared nerve injury) was able to demonstrate the key role of the thalamus in processing nociceptive inputs.

3.1. Introduction

Although not considered a disease or a pathology per se, pain, according to the International association for the study of pain (IASP), is an “unpleasant sensory and emotional experience associated with actual or potential tissue damage, or described in terms of such damage” (Bonica, 1979). In United States only, chronic pain affects approximately 100 million people, many more than any other disease including cancer, diabetes and heart diseases (Institute of Medicine Report from the Committee on Advancing Pain Research, 2011). With increase in life expectancy this number will further increase as pain arises as a consequence of many age- related pathologies. It is the most common cause of long-term disability, and its socio- economic burden is estimated to be between 560$ and 635$. Even though pain is perceived as a negative feeling, it is an essential part of protective mechanisms of the human body, pain perception allows us to withdraw our hands from a burning flame in order to prevent a more serious injury. Pain therapy is and will remain a fundamental part of medical treatments, especially for long-term and terminal patients.

Chapter III: Characterization of the response to acute and neuropathic pain in a mouse model of pain insensitivity

Today, pain is categorized according to the location, duration, etiology and intensity of pain. We discriminate three different types: nociceptive, inflammatory and pathological pain (Woolf, 2010). Nociceptive pain occurs upon stimulation of a sensory nerve fiber when the stimulus intensity exceeds the threshold needed for activating a specific nociceptor. It is a purely protective mechanism elicited by thermal, mechanical and chemical stimuli, typically triggering a withdrawal reflex. There are five phenotypic features of inflammation: heat (calor), pain (dolor), redness (rubor), swelling (tumor) and loss/disturbance of function (functio laesa); Inflammatory pain is primarily caused by the involvement of the immune system: low pH (acidosis), the mechanical pressure produced by the swelling which is caused by the formation of the inflammatory exudate and the inflammatory chemotaxis trigger the nociceptors which are reactive to these specific stimuli. Whenever the nervous system is damaged (neuropathic pain) or responds in an abnormal way to stimuli (dysfunctional pain), we speak of pathological pain.

Current pain therapy is focused on few classes of pharmaceuticals. Depending on the type of pain therapeutic strategies can be divided into two categories: 1) non-opioid analgesics and adjuvant medications and 2) opioids analgesics. Non-opioids drugs include non-steroidal anti- inflammatory drugs (NSAIDs), acetaminophen and related compounds, antiepileptic drugs, antidepressants, and local and regional anesthetics inhibiting signal propagation of action potentials to the CNS. Opioids are centrally active drugs interacting with opioid receptors. They are indicated for treatment of moderate to severe pain. Opioids carry the risk for misuse, abuse, addiction, overdose and even death (Cheatle, 2015; Oderda et al., 2015; Vowles et al., 2015). Even though many non-pharmaceutical treatments are nowadays available, such as psychological approaches, physical rehabilitative approaches and alternative medicines treatments like acupuncture and chiropractic, there is still a consistent need for pharmacological interventions.

Despite of these therapy options, management of patients suffering from a chronic pain condition is insufficient, and more specific or even personalized treatment strategies have become a priority in therapy development. In this context, nociceptors have been identified as attractive targets for pain therapy. Voltage-gated sodium channels (Nav) are a class of voltage-gated channels that play an essential role in the generation and propagation of action

Chapter III: Characterization of the response to acute and neuropathic pain in a mouse model of pain insensitivity potential in sensory neurons. The different subtypes of Nav channels may constitute attractive targets for specific pharmacotherapeutic approaches (Ahuja et al., 2015; Lee et al., 2014; Payne et al., 2015). Among those, Nav1.7 has been extensively characterized in humans channelopathies (Cox et al., 2006; Fertleman et al., 2006). It is a voltage-gated sodium channel encoded by the SCN9A gene and expressed in nociceptors located in neurons of the dorsal root ganglion (DRG) and trigeminal ganglion, as well as in sympathetic ganglion neurons. These receptors are located at nerve terminals. They are sensitive to voltage changes across the neuronal membrane. Once this potential reaches the nociceptor-specific threshold, the channel opens leading to rapid depolarization. The neuron fires, initiating the action potential wave that ultimately will lead to pain perception. The Nav1.7 channel, together with other voltage-gated sodium channels, is responsible for the propagation of the neuronal action potential. Previous studies in mice lacking in Nav1.3, 1.7, 1.8 and 1.9 channels (Minett et al., 2014a; Minett et al., 2014b; Minett et al., 2012) revealed differential behavioral responses under different conditions of chronic pain such as after chronic constriction injury (CCI) of the sciatic nerve, spinal nerve transection (SNT) at the fifth lumbar section, oxyplatin-induced pain, and bone cancer.

Animal models are typically characterized using molecular assays and behavioural tests, while functional magnetic resonance imaging (fMRI), although used in humans, is hardly applied in animal studies (Heindl-Erdmann et al., 2010; Heindl-Erdmann et al., 2017). Nevertheless, the method is attractive also in mice for pain researches allowing deciphering the CNS response to peripheral stimuli using stimulus-evoked fMRI (se-fMRI) or pain-induced alterations in the intrinsic functional architecture of the brain derived from resting-state fMRI (rs-fMRI) data. The objective of the current study was to evaluate the impact of Nav1.7 on central processing of nociceptive input by comparing the fMRI signature observed in NaV1.7 deficient with age- matched littermate mice. We analyzed the processing of acute peripheral stimuli as well as alterations in the intrinsic brain network in the two genotypes both in a pain-naïve state and in a model of neuropathic pain, the spared nerve injury (SNI) model. fMRI data were compared with behavioral readouts. Interestingly we did not find any differences in any of the fMRI between the two genotypes in the pain naïve state despite of significant differences in pain

Chapter III: Characterization of the response to acute and neuropathic pain in a mouse model of pain insensitivity behavior. In mice following SNI, rs-fMRI analysis revealed significant differences in networks involving the thalamus between the two genotypes.

3.2. Materials and methods

3.2.1. Animals

All experimental procedures conformed to the national guidelines of the Swiss Federal Act on Animal Protection and were approved by the Cantonal Veterinary Office of Zurich (licenses ZH243/2014 and ZH190/2015). Animals were housed in a temperature-controlled room in individually ventilated cages (IVC) containing a maximum of five animals under a twelve-hour dark/light cycle. Food and water were provided ad libitum.

Mice (males and females) between 14 and 20 weeks of age were studied. Group sizes are given in Table 1. In order to reduce variability in weight, only female mice of the same age group have been used for the SNI study. SNI mice split in a randomized manner into four groups: wild type sham (n= 8), wild type SNI (n= 10), Nav1.7 Wnt1 sham (n= 8), and Nav 1.7 Wnt1 SNI (n= 10).

Nav1.7 Wild type Advill Electrical 0.7 mA n=10 n=9 Stimulation 1 mA n=10 n=9

1.5 mA n=10 n=9

Thermal 42°C n=8 n=5 Stimulation 45°C n=8 n=5

48°C n=8 n=5

Chemical Capsaicin [0.5µg] n=10 n=6 Stimulation Capsaicin [1µg] n=10 n=6

10 µl Saline n=5 n=3

Table 1: group size for each stimulation type

Chapter III: Characterization of the response to acute and neuropathic pain in a mouse model of pain insensitivity

The Nav 1.7 knockout mouse strains have been provided by the Molecular Nociception Group at UCL London. Mouse lines were generated as previously described by Minett et al. (Minett et al., 2014b; Minett et al., 2012). Conditional Nav 1.7 knockout mouse (KO) strains were generated using the Cre-loxP system: floxed (Scn9a) Nav 1.7 mice were crossed with strains, for which Cre expression is driven by either the Advillin promoter (Nav1.7Advill), expressed in all dorsal root ganglia (DRG) neurons, or alternatively by the Wnt1 promoter (Nav1.7Wnt1) expressed in tissue derived from the neural tube, including sensory and sympathetic neurons (Danielian et al., 1998). The strain Nav1.7fl/fl:Advill was used for the fMRI characterization of the model because the loss of function mutation was restricted only to the DRG neurons and therefore we were able to characterize the model in a more specific manner. Because of the known involvement of the sympathetic system in neuropathic pain model (Minett et al., 2014b) the Nav1.7fl/fl:Wnt1 mice were used in the context of the SNI study

Animal preparation was performed following standard procedures established in our lab (Grandjean et al., 2014; Schroeter et al., 2014). In brief, anesthesia was induced using 4 % isoflurane (Abbott, Cham, Switzerland) in a 4:1 air:oxygen mixture. Mice were endotracheally intubated and mechanically ventilated during MRI measurements with 80 breaths per minute (bpm) using respiratory cycle of 25% inhalation and 75% exhalation (MRI-1 Volume Ventilator, CWI Inc., Ardmore, USA) under 1.2% isoflurane anesthesia. The tail vein was cannulated for administration of muscle relaxant (Pancuronium Bromide, Sigma-Aldrich, Germany) administered as a bolus at a dose of 1 mg/kg. Body temperature was monitored with a rectal temperature probe (MLT415, ADInstruments) and kept constant at 36.5° ± 0.5° C using a warm-water circuit integrated into the animal support (Bruker BioSpin, Ettlingen, Germany). After MR measurements animals were placed on a heating mat and anesthesia was maintained at 1-1.2% isoflurane while Pancuronium was metabolized. Recovery was assessed by pinching the paws, testing the palpebral reflex and observing the spontaneous breathing acts. After recovery the animals were placed back into their home cage.

Chapter III: Characterization of the response to acute and neuropathic pain in a mouse model of pain insensitivity

3.2.2. Data acquisition

Data were acquired with a Bruker Biospec 94/30 small animal MR system (Bruker BioSpin MRI, Ettlingen, Germany) operating at 400MHz (9.4T). For excitation and signal reception, a cryogenic quadrature transmit/receive surface coil was used. Global 1st order shimming followed by fieldmap-based local shimming procedure (MAPSHIM) was performed to reduce static magnetic field, B0 inhomogeneities. fMRI data were acquired using a Gradient Echo Planar Imaging sequence (GE-EPI) with the following parameters: field-of-view (FOV) = 16 x 7 mm2 and matrix size = 80 x 35 yielding an in-plane voxel dimension of 200 µm x 200 µm., Echo Time/Repetition Time (TE/TR) = 12/1000 ms, number of averages = 1, Flip angle α = 60°. Twelve adjacent coronal slices with a thickness of 0.5 mm were acquired covering the anatomical regions of primary and secondary somatosensory cortex (S1, S2), primary motor cortex (M1) anterior cingulate cortex (ACC), Insula (Ins), Thalamus (Th) and Caudate Putamen (CPu) going approximately from - 0.58 cm to 1.70 cm relatively to the Bregma. Animals were stimulated on forepaw (fp) and/or hindpaw (hp) using three different paradigms:

For electrical stimulation a pair of needle electrodes (Genuine Grass Instruments, West Warwick, USA) was inserted s.c. into the paw with a distance of two millimeters between the needles, and connected to a current stimulus isolator (A365D, World Precision Instruments Inc., Sarasota, USA). Stimulus delivery was controlled with a custom-written LabVIEW program (National Instruments, Austin, USA) and synchronized to the fMRI imaging sequence. Different amplitudes (0.5, 1, and 1.5 mA) were applied with a pulse duration of 0.5 ms and frequency of 5Hz. The stimulus paradigm consisted of a block design starting with 180 seconds of baseline followed by four cycles, each consisting of 20 seconds stimulation and 120 seconds post-stimulus/rest period. For chemical stimulation a cannula was inserted subcutaneously (s.c.) into the forepaw. Two different doses of capsaicin (0.5 and 1µg dissolved in 5μl 0.9% saline solution) have been injected. As a control, the hindpaw was stimulated with 10μl of 0.9% NaCl solution in order to have the same proportion volume/paw size as in the forepaw. The stimulation paradigm for both stimuli, capsaicin and saline injection, consisted of a 300 seconds baseline and 600 seconds post-injection signal acquisition. For thermal stimulation, a 22 x 6 mm copper heating plate controlled via a proportional–integral–derivative controller (PID controller) was attached to the palmar side of the forepaw. Different temperatures were

Chapter III: Characterization of the response to acute and neuropathic pain in a mouse model of pain insensitivity applied from 42°C, described as the pain threshold temperature in both humans and mice (Cain et al., 2001; Reimann et al., 2016) to 48°C, considered to be a noxious stimulus. The block stimulus paradigm was identical to the one applied for electrical stimulation: 180 seconds baseline followed by four cycles of 20 seconds stimulation and 120 seconds post-stimulus period.

3.2.3. SNI surgery

For the SNI surgery procedure anesthesia was induced with 4% isoflurane (Abbott, Cham, Switzerland) and maintained at 2% in a 4:1 air/oxygen mixture. The animals were placed on a feedback-controlled heating pad and temperature maintained at 36.5° (Harvard apparatus). Animals were positioned on their right side to expose the left hindpaw, then shaved from the knee to the hip area, and disinfected with a surgical skin preparation alternating for three times 70% ethanol and povidone-iodine solution (Betadine) (Supplementary figure 3.1).

Before starting the surgery, analgesia was ensured with a s.c. injection of 0.1mg/kg b.w. Buprenorphine (Temgesic, Indivior, Switzerland). A ten millimeters incision was performed behind the knee joint (Supplementary Fig. 3.1) parallel to the femur. Carrying out blunt dissection to avoid any muscle lesions and bleedings, the sciatic nerve was exposed and the three nerve branches (sural, tibial and common peroneal) could be identified. Fluids and lidocaine were instilled in the surgical area to prevent dehydration of surrounding tissues. Using a blunt micro hook (Fine Science Tools, Germany), the tibial and common peroneal nerves were lifted, ligated together with a surgical knot using a 6-0 suture and two millimeters of their length were resected. Muscle layers were carefully moved back to their original anatomical position and the wound sutured with non-resorbable surgical suture. After the surgery the animals were placed into a warm box until fully recovered from the anesthesia, they were then transferred back into their home cages. A second intraperitoneal (i.p.) administration of 0.1mg/kg Buprenorphine (Temgesic, Indivior, Switzerland) was given eight hours after surgery completion.

Chapter III: Characterization of the response to acute and neuropathic pain in a mouse model of pain insensitivity

3.2.4. Behavioural tests

A paw withdrawal test was performed to characterize the phenotype of Nav1.7 KO mice. Mice were anesthetized and intubated following the same protocol performed for animal scan preparation except for the administration of muscle relaxant. Animals were then placed on the MR cradle and connected to the ventilator with a 1.2% isoflurane anesthesia and their reaction to electrical hindpaw stimulation scored for three different amplitudes 0.7, 1 and 1.5 mA as described in Table 3.1.

Score Observation 0 no reaction 1 whisker movements 2 sporadic wincing continuous wincing and/or paw 3 withdrawal Table 3.1: Scoring of mice behavioural response electrical stimulation

Von Frey test of tactile stimulation was performed to assess the integrity of sensory perception Nav1.7 KO mice and to monitor the potential development of mechanical allodynia after SNI surgery. Mice were placed on the grid platform for 30 minutes for three non- consecutive days for habituation and 30 minutes prior to the experiment. Each hindpaw was stimulated four times, for a total of eight replicates per mouse and the pressure needed to elicit a paw withdrawal reflex was recorded. Withdrawal test data was statically analyzed with a Mann-Whitney Rank Sum Test.

Chapter III: Characterization of the response to acute and neuropathic pain in a mouse model of pain insensitivity

3.2.5. Data Analysis

Resting-state fMRI data was analyzed as previously described by Buehlmann et al. (Buehlmann et al., 2018). In brief: functional scans were normalized to a MRI template (Australian Mouse Brain Mapping Consortium, http://www.imaging.org.au/AMBMC) using linear affine and non-linear greedy symmetric normalization (SyN) transformation in advanced normalization tools (ANTs V2.1, http://picsl.upenn.edu/software/ants/)

Independent functional components (ICs) were extracted on a subject level using fsl MELODIC (Multivariate Exploratory Linear Optimized Decomposition of Independent Components), the mean EPI image was taken as a reference. Such independent components, also referred to as resting-state networks (RSNs), are highly reproducible across naïve subjects [65] and can be used as a basis to assess the impact of a disease state on BOLD-signal fluctuations within these components. This is referred to as within network or intra-regional functional connectivity and constitutes a completely data-driven approach for analyzing fMRI data. This process includes 0.01Hz high-pass filtering of the 4D dataset, spatial smoothing with a 2x2mm2 kernel and head motion correction using MCFLIRT. Non-physiological contributions to BOLD signal were removed using FIX (FMRIB’s ICAbased Xnoiseifier (Griffanti et al., 2014; Salimi-Khorshidi et al., 2014), v1.06) by an in-house classifier (Zerbi et al., 2015).

For seed-based analysis (SBA), average time series were extracted from anatomically defined seeds and used as a regressor in a general linear model (GLM) analysis. Resulting subject and session level voxel-wise Z-score maps of seed projections were subsequently analyzed within target ROIs using previously described resting state networks or anatomically defined ROIs in a linear mixed model analysis, accounting for multiple comparisons.

Se-fMRI data was first despiked using 3dDespike within the analysis of functional neuroimages software (AFNI, NIH Bethesda, USA). Subsequently, data have been normalized with ANTs (Dunwoody, USA), more specifically affine and greedy non-linear transformation were applied. A first-level single-subject analysis of each se-fMRI time series was performed by means of FMRIB Software Library (FSL, FMRIB, Oxford, UK) (Jenkinson et al., 2012; Woolrich et al., 2009) using the functionality FSL Expert Analysis Tool (FEAT): the first ten volumes were deleted to ensure signal stabilization, high pass filtering was set to 0.01 Hz and spatial

Chapter III: Characterization of the response to acute and neuropathic pain in a mouse model of pain insensitivity smoothing was performed using a 0.3 millimeter kernel size, motion correction FMRIB's Linear Registration Tool (MCFLIRT) was applied, z-threshold was set to 3.1 and p-threshold to 0.05. We then performed a higher-level analysis using a general liner model (fsl_glm) with 5000 permutations for each contrast within randomise (FMRIB Software Library randomise (Winkler et al., 2014)). Threshold-Free Cluster Enhancement and family wise error corrected (FEW- corrected) p-values were obtained.

3.3. Results

Nav1.7 KO mice display significantly reduced nociceptive but normal sensory behavior

Paw withdrawal test showed that the Nav 1.7 KO mice displayed significantly impaired nociception when electrically stimulated with current amplitudes of 0.7 and 1.0 mA amplitudes with p< 0.001 and p= 0.004, respectively (Fig.3.1). At a stimulus amplitude of 1.5mA, responses of Nav1.7 KO mice still tended to be weaker than in wildtype mice, the reduction did not reach statistical significance (p= 0.072). On the other hand, when a sensory tactile stimulation was applied (von Frey test), the sensitivity thresholds needed to elicit a paw withdrawal were similar in the two groups, with values of 2.02 ± 0.36 g for wildtype and 2.21 ± 0.34 g for Nav1.7 KO mice, respectively (unpaired t-test was performed yielding a non- significant p value of 0.88).

Figure 3.1: Effect of Nav1.7 gene deletion on behavioural pain assessment. Comparison of forepaw withdrawal response (left) and Von Frey test (right) in Nav 1.7Advill and WT mice upon electrical stimulation. Nav 1.7Advill mice showed diminished reflex response to low and high intensity stimuli compared to WT mice. Tactile mechanical innocuous stimulation of forepaw produced similar responses in the two groups. Data shown as mean ± STD. **= p- values < 0.001.

Chapter III: Characterization of the response to acute and neuropathic pain in a mouse model of pain insensitivity

Significantly reduced stimulus-induced BOLD fMRI signals in Nav1.7 KO mice reflective of reduced nociceptive input

Genotypic differences in stimulus evoked fMRI responses between Nav1.7 KO mice and their WT littermates were analyzed for three different sensory/nociceptive stimuli. Irrespective of the nature of stimulus used (electrical, thermal, and chemical), a significantly diminished blood-oxygen-level dependent (BOLD) fMRI response was observed in Nav1.7 KO mice as compared to WT mice.

For electrical stimulation the amplitudes of the BOLD responses in the contralateral S1 region of somatosensory cortex of WT mice amounted to 1.78±0.31%, 2.08±0.32%, 2.69±0.34%, whereas in NaV1.7KO mice we detected 0.08±0.167%, 0.66±0.23%, 0.84±0.26% for 0.7, 1 and 1.5 mA respectively. The reductions were statistically significant with p-values of p=0.0002, p=0.0004 and p=0.0003.

While for thermal stimulation the amplitude of the ∆BOLD fMRI response increased as a function of the stimulus amplitude, i.e. the temperature, with values of WT of 1.28±0.38%, 1.37±0.30%, 2.41±0.49% for temperatures of 42°, 45°, and 48 °C, the fMRI response in Nav1,7 mice did hardly change across the temperature range with 0.53±0.36%, 0.17±0.20%, 0.20±0.38%. This translated into a slightly significant difference in the response of the two genotypes at the lowest temperature (p=0.028), while for 45 and 48 significant effects have been found with, p=0.0005 and p=0.0004 respectively. These results are in line with the function of the Nav1.7 channel in the excitation of heat-sensitive nociceptors.

Chemical stimulation mirrored the results obtained for thermal stimulation. Upon injecting saline solution, known to elicit a burning sensation, WT animals showed a significant increase in BOLD signal intensity, which was not observable in Nav1.7 KO mice when comparing the BOLD signal change of KO mice to baseline values (p=0.24). Similarly, in contrast to WT animals, Nav1.7 KO mice hardly responded to the injection of capsaicin, the principal active compound of hot chili peppers. The effect reduction in fMRI response was highly significant with p-values of p=0.0136 and 0.0034 for capsaicin concentrations of 0.5 µg and 1 µg (p=0.0034), respectively (Fig. 3.2).

Chapter III: Characterization of the response to acute and neuropathic pain in a mouse model of pain insensitivity

Figure 3.2: Diminished response to nociceptive input in KO as compared to WT mice. ∆BOLD percentage change upon paw stimulation with three different paradigms and three different strength for each stimulus: electrical stimulation of forepaw at stimulus amplitudes 0.7, 1, and 1.5 mA (top row), thermal stimulation of forepaw with temperature of 42, 45, and 48°C (middle row), and chemical stimulation of hindpaw with saline solution, 0.5, and 1.5 µg capsaicin dissolved in saline (bottom row). Nav1.7 KO mice display a deficit in nociception for all three stimulus types, as revealed by significantly reduced BOLD signal amplitudes. Among the three paradigms, thermal stimulation showed the most pronounced genotype effect in line with the notion that the nociceptor Nav1.7 is responsible for the conduction of action potentials caused by a burning sensation input. Time series have been extracted from normalized and motion corrected data derived the contralateral from S1 ROI. Data are shown as mean BOLD % change ± SD

A subsequent region of interest (ROI) analysis performed for somatosensory cortex S1 forelimb (S1), thalamus (Th), caudate putamen (CPu) and hippocampus (Hip) revealed a widespread bilateral BOLD response in WT animals as previously described by Schroeter et al. (Schroeter et al., 2014) for all types of stimulus applied (Supplementary fig. 3.2).

Chapter III: Characterization of the response to acute and neuropathic pain in a mouse model of pain insensitivity

Knock-out of Nav1.7 channel does not affect intrinsic brain networks

A comparison of functional networks derived from stationary rs-fMRI analysis revealed no significant differences in functional connectivity (FC) between Nav 1.7 KO and WT mice in any of the 17 bilateral networks analyzed (Fig. 3.3 top matrix).

Figure 3.3: Genotype per se does not affect functional networks in brain, but alters networks adaptation following SNI surgery (top panel) Map depicting intrinsic correlation among brain networks in Nav1.7Wnt1 KO mice, (lower triangle of matrix), and WT littermates (upper triangle). The color scale shows the Pearson’s correlation values ranging from r=0 (blue) to r=1 (red). (Bottom panel, left matrix) The matrix displays results of longitudinal connectivity analysis comparing WT-SNI and Wt-Sham groups. In WT-SNI mice, significant increases (or decreases) in connectivity strength in regions typically associated with pain processing such as thalamus (Th), striatum (lStr and vStr), prefrontal cortex (PfC) have been observed as a function of time following SNI, when

Chapter III: Characterization of the response to acute and neuropathic pain in a mouse model of pain insensitivity compared to WT-sham. Colors indicate statistical significance at p<0.05 (yellow) and p<0.01 (red), while blue indicates no significant differences. (Bottom panel, right matrix) Differences in FC between WT-SNI and NaV1.7Wnt1 KO groups. Striking differences have been found in almost all networks involving the thalamus connections, suggesting that this gatekeeper of the pain ascendant pathway is strongly affected in WT mice but not in KO mice. Color coding as in the middle left matrix.

Following spared nerve injury WT mice but not Nav1.7 KO mice develop mechanical allodynia

As expected and previously described (Richner et al., 2011; Shields et al., 2003), WT operated mice (WT-SNI) developed mechanical allodynia after SNI surgery. Dynamic von Frey measurements yielded 2.02 ± 0.28 g that at baseline and decreased to 0.90 ± 0.13 g (p=0.0017) seven days after surgery, notable reduction of 55.5% in the force applied to elicit a paw withdrawal. This force threshold slightly recovered toward baseline values at 21 days after the surgery (1.25 ± 0.24), remaining nevertheless much lower compared to the baseline value with a mean drop of 38%. In contrast, in Nav1.7 KO mice the withdrawal threshold remained unaffected within error limits by the surgical intervention (Fig. 3.4). Withdrawal thresholds in Nav1.7 KO mice were 2.05 ± 0.29 g at baseline, as well as 1.88 ± 0.25 and 1.67 ± 0.36 g at 7 and 21 days following SNI, respectively (p=0.65). The most evident and significant difference between WT and Nav1.7 KO operated groups was observed at day seven (p=0.0028).

Figure 3.4: Spared nerve injury induces mechanical allodynia in WT but not in Nav1.7Wnt KO mice. von Frey test in Nav1.7Wnt1 and WT mice upon tactile mechanical stimulation. Nav1.7Wnt1 mice showed unaltered paw withdrawal response to tactile stimulation as a function of time following SNI. WT-SNI mice showed a consistent and significant increase of sensitivity to tactile innocuous stimulation as revealed by the reduced pressure

Chapter III: Characterization of the response to acute and neuropathic pain in a mouse model of pain insensitivity required to elicit the withdrawal of the operated paw, demonstrating the development of allodynia in SNI- sensitized WT mice. Data shown as percentage deviation from baseline ± SD.

Spared nerve injury did not affect stimulus-evoked fMRI responses in Nav1.7 and WT mice

Stimulus-evoked fMRI performed during all the three time points showed that Nav 1.7 KO mice do not perceive the applied painful input at baseline nor when sensitized with SNI surgery at seven and 21 days after surgery.

Significant differences in thalamic networks between Nav1.7 KO and WT mice following spared nerve injury

Longitudinal analysis of resting state FC in WT-SNI mice showed an increased FC in pain- processing-related regions, such as thalamus, striatum (lateral and ventral) and prefrontal cortex indicating that the SNI model produces FC alterations in the ascending and descending pain pathways as a model of chronic neuropathic pain (Fig. 3.3 middle panel). The comparison between WT-SNI and Nav1.7-SNI mice highlighted a pronounced genotype, affecting essentially all functional connections involving the thalamic network, a major hub in sensory and nociceptive processing which in Nav1.7 KO mice had decreased functional connectivity.

After longitudinal functional connectivity analysis, seed based analysis was performed with the two main nuclei (seeds) placed in the right contralateral and in the left ipsilateral thalamus (rTh and lTh respectively). Interestingly the functional connections showing the highest significance in time course correlations referred to thalamic-striatal and thalamic-amygdallar connectivities, in particular on the contralateral side to the SNI surgery (Fig. 3.5). The thalamic- striatal connection was further investigated with seed-based analysis by placing the seed in either the right thalamus or the left thalamus and targeting the regions of right and left dorsal Striatum respectively (rdStr and ldStr). We observed a remarkable difference between the two connections: the rTh-rdStr connection is more affected by the SNI surgery than the corresponding lTh-ldStr connection in WT mice as compared to the Nav 1.7 KO mice (Fig. 3.6).

Chapter III: Characterization of the response to acute and neuropathic pain in a mouse model of pain insensitivity

Caudal

Rostral

Figure 3.5: Stronger involvement of contralesional thalamic networks. Seed based analysis of rs-fMRI data in NaV1.7Wnt1 KO and WT operated groups using a seeed located in the contralesional right thalamus (hot color scale) and in the ipsilesional left thalamus (cold color scale). Color coded voxels were found to be significant (p<0.05)

Figure 3.6: Differences in thalamic-striatal functional connectivity between WT and Nav1.7 KO mice following unilateral spared nerve injury. Results of seed-based analysis for intra hemispheric thalamic-striatal connectivity revealing target regions in the right dorsal striatum for a seed in the contralesional right thalamus (in yellow) and for the respective ispilesional (left) regions (in purple) The difference in the thalamic-dorsal striatum connection between the WT-SNI and the Nav1.7Wnt1 SNI observed in the thalamus-dorsal striatum connectivity is larger in the contra- than the ipsilesional hemisphere. The figure shows significant differences between the two groups (p<0.05). Both a dorsal view (left) a caudo-ventral view (right) of the mouse brain is shown in order to better appreciate the regions involved.

Chapter III: Characterization of the response to acute and neuropathic pain in a mouse model of pain insensitivity 3.4. Discussion and conclusions

Voltage-gated sodium channels have been shown to play an essential role in painful inputs transmission. In fact, nociceptive signals are propagated from the periphery to the CNS with the essential help of these channels (Erickson et al., 2018; Hund and Mohler, 2014; Kerr et al., 2001; Tomaselli and Farinelli, 2018; Wadhawan et al., 2017). In order to better understand the role of Nav channels in nociception and pain, knowledge on how they affect pain processing in the CNS, and in particular in brain, becomes relevant (Adamczak et al., 2010; Baltes et al., 2011a; Bosshard et al., 2010a; Bosshard et al., 2012; Bosshard et al., 2015; Heindl-Erdmann et al., 2010). Recently it has been reported that despite the fact that humans lacking the NaV1.7 channels do not perceive pain, stimulus evoked fMRI responses were observed in all elements of the pain matrix identified for the general population (Salomons et al., 2016). To investigate effects of Nav1.7 on the fMRI signature in more detail we compared central responses in Nav1.7 KO mice and their wildtype littermates in response to a peripheral stimulus and at rest (spontaneous activity) both in pain-naïve animals and ice following SNI. To the best of our knowledge the only fMRI studies reported to Nav-deficient mice related to the subtype Nav1.8 only (Heindl-Erdmann et al., 2017).

On one hand resting-state fMRI experiments, performed in the absence of a painful condition, could confirm the unaltered functional connectivity patterns in Nav1.7-deficient mice, on the other hand, se-fMRI revealed significantly reduced BOLD fMRI amplitudes in Nav1.7 KO mice compared to WT mice in response to electrical, chemical, but above all thermal painful stimuli as previously shown by Minett et al. (Minett et al., 2014b). The response pattern in WT mice to peripheral input was widespread, indicative of dominating contributions due to peripheral circulation as previously reported (Reimann et al., 2018; Schroeter et al., 2017; Schroeter et al., 2014). Similarly, the reduced fMRI amplitude observed in NaV1.7 KO mice is rather reflective of a reduced arousal response due to reduced nociceptive input. Interestingly, there were no major differences in the spatial extent of the stimulus evoked fMRI signals in the two genotypes.

The successful implementation of the neuropathic pain model of SNI was confirmed by the rs- fMRI readouts: SNI-operated mice showed a clearly altered FC during chronic pain state when compared to sham-operated mice; brain regions fundamentally involved in pain processing

Chapter III: Characterization of the response to acute and neuropathic pain in a mouse model of pain insensitivity such as thalamus, striatum, prefrontal cortex and amygdala (Baliki et al., 2014a; Tracey and Mantyh, 2007) have shown to be largely affected by neuropathic pain development. Furthermore rs-fMRI results showed increased functional connectivity within the right hemisphere (contralateral to the SNI surgery). On the left (ipsilesional) side only marginal (i.e. significant but in less voxels compared to the contralesional side, figure 3.8) differences were found in intra-hemispheric connectivity between SNI and sham operated mice over the three time points examined. This result are in good agreement with what has been observed by Baliki et al. in SNI operated rats (Baliki et al., 2014a). Furthermore rs-fMRI FC correlation values observed over the course of the entire neuropathic pain model showed a trend of decreasing connectivity in the thalamic-striatal and thalamic-prefrontal cortical connections which is clearly observable only in the WT-SNI group (Supplementary 3.3), this result is in line with a previous study with similar experimental design in regards to a bone cancer pain model (Buehlmann et al., 2018).

The thalamus exhibited the strongest changes in functional connectivity between SNI and sham groups with particular changes observed in the thalamic-striatal, thalamic-prefrontal cortex and thalamic-amygdallar connections, all exhibiting decreased functional connectivity in KO mice. Thalamus is in fact a central anatomical and functional gatekeeper via which nociceptive input is processed in the CNS, involved both in the pain ascending and descending pathways (Apkarian et al., 2005). Our results indicate that intra-hemispheric functional connections involving the thalamus are profoundly enhanced in a chronic neuropathic pain state such as elicited by SNI in WT mice. In contrast, thalamic networks were hardly affected in Nav1.7KO mice indicating that the peripheral noxious chronic input is almost completely missing in these genetically modified animals.

Stimulus-evoked fMRI performed during the development of neuropathic pain condition could furthermore demonstrate that Nav 1.7 KO mice do not experience the applied painful thermal input at baseline nor when sensitized with SNI surgery at seven and 21 days after surgery, suggesting an important role of the Nav 1.7 channel also in neuropathic chronic pain state. Yet, again the reduced BOLD fMRI amplitudes indicate rather reduced peripheral signal contribution due to a reduced arousal response than an actual difference in central processing.

Chapter III: Characterization of the response to acute and neuropathic pain in a mouse model of pain insensitivity

Comparing se-fMRI and rs-fMRI results in Nav1.7 KO mice, it appears that se-fMRI rather reflects differences in peripheral input than differences in central processing. The widespread nature of the signal involving both hemispheres in WT and Nav1.7 mice hints at significant systemic hemodynamic contributions due to an arousal response: reduced nociceptive input prompts smaller stimulus-evoked changes in cardiovascular parameters and hence reduced fMRI amplitudes. In contrast, rs-fMRI data are collected in the absence of an external stimulus and, if properly preprocessed, should be largely devoid of confounds due to systemic circulation, i.e. reflect spontaneous neural activity. Rs-fMRI derived functional connectivity analysis revealed significant differences of networks involved in processing of SNI elicited chronic nociceptive input, in particular in networks involving the thalamus. Interestingly, these changes were largely absent in Nav1.7 mice following SNI due absence or much reduced nociceptive input. Hence, rs-fMRI more immediately probes CNS functional adaptations due to the gene deletion than se-fMRI. Further studies in this direction, e.g. on Nav 1.7 nociceptors but also more generally on sodium voltage-gated channels could improve the understanding of pain processing during chronic and acute pain states in rodents and humans, giving new concrete molecular targets for pharmaceutical management of pain.

Chapter III: Characterization of the response to acute and neuropathic pain in a mouse model of pain insensitivity

Supplementary figure 3.1: surgical preparation before resection of the common peroneal and tibial nerves: incision performed caudal to the knee joint (A), blunt dissection was performed to avoid any bleeding (B), localization of the three branches of the sciatic nerve (C) and exposure of common peroneal and tibial nerves (D)

Chapter III: Characterization of the response to acute and neuropathic pain in a mouse model of pain insensitivity Adjusted P Value 0,003093296 0,00212 0,020464681 0,00186 0,052781013 0,00112 0,032783181 0,00087 0,032783181 0,00212 0,00842402 0,00150 0,052781013 0,00212 0,032783181 0,00212 0,042836882 0,020646314 0,384705063 0,176868961 0,042836882 0,099139797 0,389958471 0,389958471 Difference 3,679 4,623 3,365 4,753 2,327 3,773 2,643 3,738 2,077 3,337 2,647 3,19 2,263 2,841 2,656 2,536 3,455 3,444 1,513 2,411 3,372 3,436 1,343 1,339 Mean NaV KO 0,08604 1,551 -0,1726 1,271 0,2206 1,147 0,2079 1,084 0,07687 0,7495 0,1416 0,8107 -0,0004217 0,7463 -0,03931 0,8903 2,066 1,863 1,771 1,821 0,4083 0,3225 0,4178 0,5709 Mean WT 3,765 6,174 3,193 6,024 2,548 4,92 2,851 4,823 2,154 4,087 2,788 4,001 2,263 3,587 2,617 3,426 5,521 5,307 3,284 4,233 3,78 3,759 1,761 1,91 g µ 1 48°C P value 0,000387186 0,00075 0,003440233 0,00037 0,028420841 0,00016 0,006880399 0,00011 0,006644346 0,00053 0,001207799 0,00025 0,026748241 0,00086 0,008115561 0,00066 1.5 mA1.5 0,007121059 0,002604406 0,149460579 0,047495043 0,006234975 0,020664539 0,218948447 0,26879797 Adjusted P Value 0,064067341 0,21337 0,040447086 0,21337 0,040447086 0,21337 0,034352239 0,21337 0,000549275 0,13031 0,007048485 0,21337 0,006486804 0,21337 0,008419916 0,21337 0,001580048 0,000946155 0,001306686 0,001580048 0,001306686 0,001580048 0,001183115 0,001580048 Difference 2,117 2,64 2,656 2,541 2,042 2,177 2,468 2,166 2,524 2,075 2,291 1,937 3,155 1,504 2,569 1,552 4,88 5,306 3,59 4,018 4,258 4,448 3,116 3,183 Mean NaV KO 1,073 0,5484 0,9381 0,671 0,8395 0,3441 0,7644 0,4175 0,3978 -0,1528 0,3005 -0,1121 0,03672 0,04561 0,2821 -0,003464 0,8891 0,7518 0,7793 0,7118 -0,3002 -0,06504 -0,005698 0,1553 Mean WT 3,19 3,189 3,594 3,212 2,882 2,521 3,233 2,583 2,922 1,922 2,591 1,824 3,192 1,549 2,851 1,548 5,769 6,058 4,369 4,73 3,958 4,383 3,11 3,338 g µ 0.5 45°C P value 0,064067341 0,04481 0,013668334 0,03481 0,017976247 0,03614 0,008700963 0,03481 6,86759E-05 0,01730 0,001178212 0,03370 0,000929273 0,05293 0,001689684 0,04943 1 mA 0,000395246 0,000118318 0,0002179 0,000479573 0,000234523 0,000458408 0,000169102 0,001156965 Adjusted P Value 0,808760029 0,54594 0,808760029 0,54594 0,808760029 0,55275 0,808760029 0,55275 0,808760029 0,55275 0,808760029 0,66493 0,808760029 0,66493 0,808760029 0,66493 0,00937583 0,00792502 0,04156582 0,04156582 0,011606724 0,008064851 0,04156582 0,04156582 Difference 2,466 1,787 2,197 1,495 2,079 1,245 1,919 1,134 0,665 0,7149 1,242 0,4295 1,376 0,5099 1,656 0,5184 3,562 3,409 2,141 2,566 2,201 2,517 1,463 1,65 Mean NaV KO -0,00519 0,9689 -0,03706 1,033 0,04679 0,7973 0,2271 0,827 0,8383 0,2303 0,4736 0,4349 0,2224 0,7319 0,1837 0,725 0,528 0,7534 0,4378 0,5652 0,1009 0,2412 0,1736 0,3591 2,46 2,756 Mean WT 2,16 2,527 2,125 2,042 2,146 1,961 1,503 0,9452 1,715 0,8644 1,598 1,242 1,84 1,243 4,09 4,163 2,579 3,132 2,302 2,758 1,637 2,009 0,200549569 42°C P value 0,09398 0,235832297 0,10122 0,186800068 0,12550 0,240833142 0,13369 0,506432696 0,15071 0,316195709 0,38060 0,264952301 0,32615 0,203163919 0,30544 0.7 mA0.7 0,001568778 0,000994079 0,010601361 0,010557472 0,002332198 0,001156124 0,01633077 0,028100205 saline S1_ipsi ROI S1_ipsi S1_contra S1_contra TH_ipsi TH_ipsi TH_contra TH_contra CPu_ipsi CPu_ipsi CPu_contra CPu_contra Hip_ipsi Hip_ipsi Hip_contra Hip_contra S1_ipsi S1_contra TH_ipsi TH_contra CPu_ipsi CPu_contra Hip_ipsi Hip_contra

Supplementary figure 3.2. Statistical values detected in a region of interests analysis in different brain areas: somatosensory S1 area (S1), thalamus (TH), Caudate Putamen (CPu) and Hippocampus (Hip). The data have been extracted in the contralateral and ipsilateral side of the applied stimulus.

Chapter III: Characterization of the response to acute and neuropathic pain in a mouse model of pain insensitivity

Supplementary figure 3.3: rs-fMRI FC correlation values over the three time points. The trend of decreasing connectivity in the thalamic-striatal and thalamic-prefrontal cortical connections is clearly observable only in the WT-SNI group. Data are shown as mean and 95% percentile ± SEM

Chapter III: Characterization of the response to acute and neuropathic pain in a mouse model of pain insensitivity

3.5. References

Adamczak, J.M., Farr, T.D., Seehafer, J.U., Kalthoff, D., Hoehn, M., 2010. High field BOLD response to forepaw stimulation in the mouse. Neuroimage 51, 704-712.

Apkarian, A.V., Bushnell, M.C., Treede, R.D., Zubieta, J.K., 2005. Human brain mechanisms of pain perception and regulation in health and disease. Eur J Pain 9, 463-484.

Baliki, M.N., Chang, P.C., Baria, A.T., Centeno, M.V., Apkarian, A.V., 2014a. Resting-sate functional reorganization of the rat limbic system following neuropathic injury. Sci Rep 4, 6186.

Baltes, C., Bosshard, S., Mueggler, T., Ratering, D., Rudin, M., 2011a. Increased blood oxygen level- dependent (BOLD) sensitivity in the mouse somatosensory cortex during electrical forepaw stimulation using a cryogenic radiofrequency probe. NMR Biomed 24, 439-446.

Bonica, J.J., 1979. The need of a taxonomy. Pain 6, 247-248.

Bosshard, S.C., Grandjean, J., Schroeter, A., Baltes, C., Zeilhofer, H.U., Rudin, M., 2012. Hyperalgesia by low doses of the local anesthetic lidocaine involves cannabinoid signaling: an fMRI study in mice. Pain 153, 1450-1458.

Bosshard, S.C., Stuker, F., von Deuster, C., Schroeter, A., Rudin, M., 2015. BOLD fMRI of C-Fiber Mediated Nociceptive Processing in Mouse Brain in Response to Thermal Stimulation of the Forepaws. PLoS One 10, e0126513.

Chapter III: Characterization of the response to acute and neuropathic pain in a mouse model of pain insensitivity

Buehlmann, D., Grandjean, J., Xandry, J., Rudin, M., 2018. Longitudinal resting-state fMRI in a mouse model of metastatic bone cancer reveals distinct functional reorganizations along a developing chronic pain state. Pain.

Cain, D.M., Khasabov, S.G., Simone, D.A., 2001. Response properties of mechanoreceptors and nociceptors in mouse glabrous skin: an in vivo study. J Neurophysiol 85, 1561-1574.

Cheatle, M.D., 2015. Prescription Opioid Misuse, Abuse, Morbidity, and Mortality: Balancing Effective Pain Management and Safety. Pain Med 16 Suppl 1, S3-8.

Danielian, P.S., Muccino, D., Rowitch, D.H., Michael, S.K., McMahon, A.P., 1998. Modification of gene activity in mouse embryos in utero by a tamoxifen-inducible form of Cre recombinase. Curr Biol 8, 1323-1326.

Erickson, A., Deiteren, A., Harrington, A.M., Garcia-Caraballo, S., Castro, J., Caldwell, A., Grundy, L., Brierley, S.M., 2018. Voltage-gated sodium channels: (NaV )igating the field to determine their contribution to visceral nociception. J Physiol.

Griffanti, L., Salimi-Khorshidi, G., Beckmann, C.F., Auerbach, E.J., Douaud, G., Sexton, C.E., Zsoldos, E., Ebmeier, K.P., Filippini, N., Mackay, C.E., Moeller, S., Xu, J., Yacoub, E., Baselli, G., Ugurbil, K., Miller, K.L., Smith, S.M., 2014. ICA-based artefact removal and accelerated fMRI acquisition for improved resting state network imaging. Neuroimage 95, 232-247.

Chapter III: Characterization of the response to acute and neuropathic pain in a mouse model of pain insensitivity

Heindl-Erdmann, C., Zimmermann, K., Reeh, P., Brune, K., Hess, A., 2017. Activity and connectivity changes of central projection areas revealed by functional magnetic resonance imaging in NaV1.8-deficient mice upon cold signaling. Sci Rep 7, 543.

Hund, T.J., Mohler, P.J., 2014. Nav channel complex heterogeneity: new targets for the treatment of arrhythmia? Circulation 130, 132-134.

Institute of Medicine Report from the Committee on Advancing Pain Research, C., and Education, 2011. Relieving Pain in America: A Blueprint for Transforming Prevention, Care, Education, and Research Relieving Pain in America: A Blueprint for Transforming Prevention, Care, Education, and Research, Washington (DC).

Jenkinson, M., Beckmann, C.F., Behrens, T.E., Woolrich, M.W., Smith, S.M., 2012. Fsl. Neuroimage 62, 782-790.

Kerr, B.J., Souslova, V., McMahon, S.B., Wood, J.N., 2001. A role for the TTX-resistant sodium channel Nav 1.8 in NGF-induced hyperalgesia, but not neuropathic pain. Neuroreport 12, 3077-3080.

Minett, M.S., Eijkelkamp, N., Wood, J.N., 2014a. Significant determinants of mouse pain behaviour. PLoS One 9, e104458.

Minett, M.S., Falk, S., Santana-Varela, S., Bogdanov, Y.D., Nassar, M.A., Heegaard, A.M., Wood, J.N., 2014b. Pain without nociceptors? Nav1.7-independent pain mechanisms. Cell Rep 6, 301-312.

Minett, M.S., Nassar, M.A., Clark, A.K., Passmore, G., Dickenson, A.H., Wang, F., Malcangio, M., Wood, J.N., 2012. Distinct Nav1.7-dependent pain sensations require different sets of sensory and sympathetic neurons. Nat Commun 3, 791.

Oderda, G.M., Lake, J., Rudell, K., Roland, C.L., Masters, E.T., 2015. Economic Burden of Prescription Opioid Misuse and Abuse: A Systematic Review. J Pain Palliat Care Pharmacother 29, 388-400.

Chapter III: Characterization of the response to acute and neuropathic pain in a mouse model of pain insensitivity

channel blocker, PF-01247324, attenuates nociception and sensory neuron excitability. Br J Pharmacol 172, 2654-2670.

Richner, M., Bjerrum, O.J., Nykjaer, A., Vaegter, C.B., 2011. The spared nerve injury (SNI) model of induced mechanical allodynia in mice. J Vis Exp.

Salimi-Khorshidi, G., Douaud, G., Beckmann, C.F., Glasser, M.F., Griffanti, L., Smith, S.M., 2014. Automatic denoising of functional MRI data: combining independent component analysis and hierarchical fusion of classifiers. Neuroimage 90, 449-468.

Salomons, T.V., Iannetti, G.D., Liang, M., Wood, J.N., 2016. The "Pain Matrix" in Pain-Free Individuals. JAMA Neurol 73, 755-756.

Shields, S.D., Eckert, W.A., 3rd, Basbaum, A.I., 2003. Spared nerve injury model of neuropathic pain in the mouse: a behavioral and anatomic analysis. J Pain 4, 465-470.

Tomaselli, G.F., Farinelli, F., 2018. NaV Channels: Assaying Biosynthesis, Trafficking, Function. Methods Mol Biol 1722, 167-184.

Tracey, I., Mantyh, P.W., 2007. The cerebral signature for pain perception and its modulation. Neuron 55, 377-391.

Chapter III: Characterization of the response to acute and neuropathic pain in a mouse model of pain insensitivity

Wadhawan, S., Pant, S., Golhar, R., Kirov, S., Thompson, J., Jacobsen, L., Qureshi, I., Ajroud-Driss, S., Freeman, R., Simpson, D.M., Smith, A.G., Hoke, A., Bristow, L.J., 2017. NaV channel variants in patients with painful and nonpainful peripheral neuropathy. Neurol Genet 3, e207.

Winkler, A.M., Ridgway, G.R., Webster, M.A., Smith, S.M., Nichols, T.E., 2014. Permutation inference for the general linear model. Neuroimage 92, 381-397.

Woolf, C.J., 2010. What is this thing called pain? J Clin Invest 120, 3742-3744.

Woolrich, M.W., Jbabdi, S., Patenaude, B., Chappell, M., Makni, S., Behrens, T., Beckmann, C., Jenkinson, M., Smith, S.M., 2009. Bayesian analysis of neuroimaging data in FSL. Neuroimage 45, S173-186.

Zerbi, V., Grandjean, J., Rudin, M., Wenderoth, N., 2015. Mapping the mouse brain with rs-fMRI: An optimized pipeline for functional network identification. Neuroimage 123, 11-21.

4. Chapter - Discussion and conclusions

Chapter IV: Discussion and conclusions

4.1. Suitability of se-fMRI protocols in rodents

MRI is a non-invasive imaging technique that allows to functionally and structurally study not only somatic and visceral alterations but also brain processing, modifications in functional connectivity and structural changes. Over the last decades functional MRI (fMRI) became very attractive to study human neuro-pathologies; diseases like depression, neurodegeneration (which is also an important feature of Alzheimer’s disease), autism, other psychiatric disorders and chronic pain states are an essential part of today’s medicine and the focus of the development of novel treatments. While structural changes are frequently late markers of the disease process, alterations in tissue, and in particular, brain function may serve as sensitive marker of developing or ongoing disease process.

The use of animal models mimicking aspects of human diseases allows studying pathological transformation at the organism level, i.e. with all regulatory processes in place. Hypothesis- driven models, which frequently involve genetically modified animals are meanwhile established tools for studying mechanistic aspects of the disease process, e.g. for identifying relevant molecular therapy targets, but also for rationalizing phenotypic aspects of a pathology such as Alzheimer’s disease in which alterations in brain processing are reflected by altered functional networks, vascular pathologies, as well as neurodegenerative tissue transformations in humans (Wierenga and Bondi, 2007) as well as in the context of genetically engineered models of cerebral amyloidosis (Grandjean et al., 2016; Klohs et al., 2014).

In the present PhD thesis I focused on investigating to what extent fMRI can be used to assess altered processing of peripheral input and altered brain networks associated with pain. FMRI techniques in rodents have been widely used to study not only pathological states but also physiological brain functions (Baltes et al., 2011b; Bosshard et al., 2010b; Logothetis et al., 2001; Zhao et al., 2005; Zhao et al., 2006). The goals of such studies are to understand the source of the fMRI signal (i.e. to link the fMRI signal to neural activity), to investigate mechanisms of altered neural processing under pathological conditions, and to translate phenotypic readouts to human medicine. The major issue of fMRI being translatable from rodents to humans lays in the fact that experiments are typically carried out under different

Chapter IV: Discussion and conclusions physiological conditions. Firstly, fMRI requires immobilization of the human or the laboratory animal for the duration of data acquisition, which in the case of animals typically requires anaesthesia (Jonckers et al., 2011b; Schroeter et al., 2014). Anaesthesia inevitably interferes with brain function with different anaesthetics having different effects. Depending on the anaesthetic used some brain circuits could be “switched off” or modified (Martin et al., 2006). Apart from its central effects, anaesthesia may influence body temperature, induce respiratory depression thereby altering the partial pressure of blood gases, and affect cardiovascular parameters such as heart rate and arterial blood pressure. Given the nature of the BOLD fMRI signal such peripheral physiological changes may confound or completely mask specific neurogenic signals elicited by peripheral stimuli (Fukuda et al., 2013; Schroeter et al., 2014). Given the potential negative impact of anaesthesia, it may appear logical to perform fMRI on awake animals. Yet, fMRI experiments in awake animals are prone to confounds as well: the animal needs to be immobilized during data acquisition, which despite training is likely to influence the arousal state of the animal an thus its basic physiology. Despite restraining, motion artefacts in fMRI data are likely to occur. Moreover, administering sensory or even nociceptive stimuli to awake animals will constitute a major stress factor. All these changes have a strong impact on the fMRI BOLD response, which is ultimately detected, and hence, the result might indicate fear processing rather than physiological brain processing of innocuous and noxious peripheral stimuli (Berwick et al., 2002; Harris et al., 2015; Lukasik and Gillies, 2003).

In the first part of this PhD thesis we investigated how different stimuli at different amplitudes and strengths influence BOLD response in both rats and mice, the most commonly used laboratory animals for studying human physiological and pathological models. After a systematic review of the main stimulus paradigms that could be found in literature, we observed that electrical stimulation elicited widespread BOLD responses in mouse brain irrespectively of the type and strength of the stimulus. In contrast, in rats BOLD responses to electrical stimulation evoked BOLD changes that displaying a high degree of topological specificity to the somatosensory S1 area contralateral to the stimulus applied even when using high current amplitudes, though some ipsilateral signal changes have been observed as well. Hence, we can conclude that BOLD signal changes in mice to peripheral stimulation are

Chapter IV: Discussion and conclusions dominated by non-neurogenic contributions due to stimulus-associated changes in general cardiovascular parameters (Reimann et al., 2018; Schroeter et al., 2014), while in rat the dominant contribution is of neurogenic origin, reflecting the processing of peripheral input. This might indicate that the mouse is apparently not suited for studying stimulus-evoked brain processing given its susceptibility of getting aroused even in the anesthetized state, though such a statement has to be taken with care. It has been suggested and in part already demonstrated that when using very mild stimuli topological specificity can be retained (Schlegel et al. 2015). Similarly, the influence of peripheral physiology might be minimized by suitable pharmacological interventions.

The flexibility in functional neuroimaging is definitely higher in rats as compared to mice in which non-neurogenic signal contributions typically outweight neurogenic ones. We have also found that in rats and mice fMRI responses to FP stimulation are stronger than when stimulating the HP, which has been attributed to the higher degree of innervation of the FP. The more skilled behaviour of the FP is also reflected by the larger functional topological representation of the respective S1 somatosensory cortical area, i.e. area (S1FP) > area (S1HP). While mice, given the large number of genetically engineered strain available would be highly attractive for functional studies, se-fMRI in mice is subject to severe limitations. A close monitoring of cardiovascular parameters must be performed ideally during the occurrence of the stimulus, to eventually exclude or better regress these changes in the subsequent data analysis. This, of course, assumes that the neurogenic signals are of sufficient signal-to-noise ratio to modulate the unspecific signal contribution. Yet, monitoring cardiovascular parameters, in particular blood pressure, during MRI data acquisition is challenging. ECG and pulse-oxymeter devices suitable for fMRI measurements in rodents are available on the market but they are rarely compatible with se-fMRI experiments when other equipment needs to be used for the stimulus delivery, especially in such small animals like mice. As fMRI experiments are sensitive to cardiovascular physiology including blood oxygenation, it is essential to control and maintain the physiological status of the examined animal throughout the duration of the experiment. Variations in the preparation time across subjects may lead to changes in body temperature, and other general physiological parameters, which might have a strong impact on the data quality and on the amplitude of the ∆BOLD response.

Chapter IV: Discussion and conclusions

Therefore, it is crucial to perform such experiments in a standardized fashion, i.e. stick to a strict timing regime, to maintain variability across subjects minimal. Another important factor is the anaesthesia regime used during se-fMRI experiments: while inhalation-anaesthetic isoflurane is easy to administer and control, it is known to affect the cardiovascular system leading to increased heart rate, and decreased arterial blood pressure; these effects can be explained by a reduction of sympathetic tone that reduces both cardiac output and total peripheral resistance (Constantinides et al., 2011). Changes in cardiovascular tone will affect fMRI signal, hence alternative anaesthetics have been evaluated for rodent fMRI (Jonckers et al., 2014; Low et al., 2016; Petrinovic et al., 2016; Schroeter et al., 2014). None of these anaesthetics has the ideal profile, all have pros and cons; hence the search for an optimal anaesthetic regime for rodents, and in particular for mice, must continue.

4.2. Models of insensitivity to pain: why they can help to understand pain processing

The availability of genetically engineered mouse strains is attractive for investigating the role of specific molecular mediators for a certain pathological condition. We have used mice with a loss of function mutation in Nav 1.7 channels (Minett et al., 2014b; Minett et al., 2012). Voltage-gated sodium channels have been shown to play an essential role in pain perception. In fact, nociception is propagated from the periphery to the CNS with the essential help of these channels (Erickson et al., 2018; Hund and Mohler, 2014; Kerr et al., 2001; Tomaselli and Farinelli, 2018; Wadhawan et al., 2017). In fact, human carriers of such mutations are insensitive to pain, in particular to pain elicited by activation of temperature-sensitive nociceptors (Cox et al., 2006). The analysis of se-fMRI response to electrical, thermal and chemical stimulation revealed that there is a significantly reduced BOLD response in Nav1.7 KO mice reflective of reduced nociceptive input. Despite the reduced fMRI amplitude observed in NaV1.7 KO mice, the BOLD signals are widespread and comprise both hemispheres, which is rather reflective of a reduced arousal response due to reduced nociceptive input. There were no major differences in the spatial extent of the stimulus

Chapter IV: Discussion and conclusions evoked fMRI signals in the two genotypes when acutely stimulated. Moreover, rs-fMRI confirmed that mice lacking NaV1.7 showed no alteration of intrinsic brain networks when compared to WT animals. Hence we may conclude that loss of function mutation of NaV1.7 reduces nociceptive signaling to the CNS but does not affect central processing as such.

The perception of pain is a rather complex process, in which many factors contribute to the pain sensation. Nociceptive input itself is not enough to characterize the response to pain, which varies a lot across subjects. The way pain is perceived depends on cognition, emotional state, previous experiences, and expectations. It has been shown that subjects who have experienced pain previously might perceive pain differently with regard to frequency and intensity compared to naïve subjects. Expectations of pain has been demonstrated to have a fundamental role in both increasing the pain perception, (for instance after experiencing a trauma (2014; Stojanovic et al., 2016)) or decreasing the pain perception because of a positive and optimistic attitude towards the expected pain therapy (Cormier et al., 2016), which even in the absence of an actual treatment (placebo effect) could cause pain relief (Colloca and Grillon, 2014; Evers et al., 2014). This illustrates the complexity of pain assessment and the need for more objective measures of pain though of course cognitive and emotional process will also affect functional neuroimaging readouts. Quantitative assessment of pain is difficult both in humans and in rodents though pain readouts including neuroimaging data in rodents may be less confounded by higher cognitive or emotional factors. For example, rodents are not aware of the potential pain-relieving treatments they are receiving. Therefore, in general, a placebo effect is largely abolished in such rodent pain models. Nevertheless, fMRI responses to innocuous and noxious peripheral stimuli in mice indicate a strong arousal component. A critical aspect is the development of clinically relevant rodent models mimicking different aspects of human pain such as neuropathic or inflammatory pain, which form the basis for mechanistic studies and the development of novel pain therapies.

The conventional methods to evaluate pain in rodents are behavioural tests, which on one side involve highly standardized procedures, but on the other side are extremely influenced by the experimenter. Functional neuroimaging including fMRI may eliminate part of this subjectivity in assessing pain and in humans fMRI has become a common practice to study pain (Bingel and Tracey, 2008; Tracey, 2011). Study on pain under acute and chronic conditions

Chapter IV: Discussion and conclusions has led to a ‘pain fMRI signature’ than comprises anatomical structures such as the, thalamus, the anterior cingulate cortex and the insula, the so-called pain matrix, though recently questions regarding the relevance of this pain matrix have been raised (Salomons et al., 2016). Nevertheless, the extensive use of fMRI in the clinics has stimulated the use of neuroimaging to characterize pain states also in rodents (Thompson and Bushnell, 2012; Zhao et al., 2012; Zhao et al., 2014).

Se-fMRI has been proven to be a useful tool to investigate in pain processing especially in rats, which due their efficient autoregulatory system yield topological specific neurogenic responses to innocuous and noxious stimuli. Rat models have been extensively used to characterize processing in the CNS under acute and chronic pain conditions (Baliki et al., 2014b; Chang et al., 2014; Zhao et al., 2014). While translation to mice would be attractive due to the availability of genetically engineered strain (Heindl-Erdmann et al., 2017), there is the issue of lack in specificity of fMRI signals. Hence, we may conclude that se-fMRI, which is attractive for studying the decoding processing of nociceptive input in rat CNS, is hardly feasible in mice. Conditions, yielding specific BOLD signals in the mouse are either innocuous (low intensity stimulus) or are recorded under non-physiological conditions, which largely decouple the peripheral from central processing.

The alternative for functional studies in mice is rs-fMRI, which measures spontaneous brain activity and, by definition, does not involve any task or stimulus: correspondingly, any stimulus evoked arousal response is avoided. While rs-fMRI is not relevant for studying acute pain processing it might constitute an attractive tool to analyze plastic changes in brain networks due to persistent nociceptive input in a longitudinal manner. This has been recently demonstrated in a mouse model of pain associated with bone metastasis in peripheral long bones (Buehlmann et al., 2018), and also in the current study of SNI elicited neuropathic pain in WT and NaV1.7 KO mice.

Chapter IV: Discussion and conclusions

4.3. Is Nav 1.7 a suitable pharmaceutical target for pain-relief?

The discovery that many subtypes of Nav channels are involved in pain pathways initiated a new era of research for therapeutics targeting these nociceptors. The findings that humans carriers of a loss of Nav1.7 function mutation were pain free but had normal sensory perception, excluding a loss of olfaction, has led to an extended effort to find specific inhibitors of this channel with therapeutic potential (Cardoso and Lewis, 2017; Emery et al., 2016). Nav blockers have been already clinically validated as a therapy for treating neuropathic pain. However, these treatments lack specificity for subtypes of Nav channels and have quite significant CNS and cardiovascular side effects when administered as long-term therapy (Silos- Santiago, 2008) as the Nav1.7 channels are expressed in many different tissues, many potent Nav1.7 blockers have been found to be clinically effective but only relatively weak analgesics and had failed in regards to achieving the same degree of analgesia as congenital Nav 1.7 inactivity (Minett et al., 2015). In contrast, tetrodotoxin-resistant channels (Nav 1.8 and 1.9) are mostly expressed in nociceptive neurons in the dorsal root ganglia (DRGs), where they play a key role in normal and/or pathological pain sensation. Given their CNS specific expression there is a chance that a novel class of analgesics with less systemic side effects might be developed.

Nav blockage on its own may be not sufficient to obtain the desired analgesic effect, other alternatives are currently being studied and it might be useful to consider Nav blockers in combination therapy e.g. with nerve growth factor (NGF) blockers. NGF has been demonstrated to play a key role in peripheral hyperalgesia and inflammation, especially in the treatment of osteoarthritis, inflammatory pain and lower back pain where anti-NGF antibodies have shown an attenuated pain response (Cattaneo, 2010). The anti-NGF monoclonal antibody 911 (muMab 911) has proven to have beneficial effects in osteoarthritis and its preventive usage reduces the number of subchondral osteoclast thus limiting subchondral bone changes (Xu et al., 2016).

Further research focusing on the various subtypes of Nav channels as well as on other targets such as NGF might lead to promising pharmacological developments in pain treatment. Nav

100

Chapter IV: Discussion and conclusions and NGF blockage, alone or even in combination, might be efficient pharmaceutical strategies to ameliorate chronic pain conditions which are an essential part of many diseases. The imaging field and, more specifically from our side, MRI can play a key role in the development of new pharmacological treatments. The suitability of MRI readout to study pain has been demonstrated over the course of the past decades and it serves not only as a screening tool to diagnose pathologies but also as a non-invasive tool to study brain function and its alterations.

101

Chapter IV: Discussion and conclusions

4.4. References

2014. Trauma-Informed Care in Behavioral Health Services, Rockville (MD).

Baliki, M.N., Chang, P.C., Baria, A.T., Centeno, M.V., Apkarian, A.V., 2014b. Resting-sate functional reorganization of the rat limbic system following neuropathic injury. Scientific Reports 4.

Baltes, C., Bosshard, S., Mueggler, T., Ratering, D., Rudin, M., 2011b. Increased blood oxygen level- dependent (BOLD) sensitivity in the mouse somatosensory cortex during electrical forepaw stimulation using a cryogenic radiofrequency probe. Nmr in Biomedicine 24, 439-446.

Berwick, J., Martin, C., Martindale, J., Jones, M., Johnston, D., Zheng, Y., Redgrave, P., Mayhew, J., 2002. Hemodynamic response in the unanesthetized rat: Intrinsic optical imaging and spectroscopy of the barrel cortex. Journal of Cerebral Blood Flow and Metabolism 22, 670-679.

Bingel, U., Tracey, I., 2008. Imaging CNS modulation of pain in humans. Physiology (Bethesda) 23, 371- 380.

Bosshard, S.C., Baltes, C., Wyss, M.T., Mueggler, T., Weber, B., Rudin, M., 2010b. Assessment of brain responses to innocuous and noxious electrical forepaw stimulation in mice using BOLD fMRI. Pain 151, 655-663.

Cardoso, F.C., Lewis, R.J., 2017. Sodium channels and pain: from toxins to therapies. Br J Pharmacol.

Cattaneo, A., 2010. Tanezumab, a recombinant humanized mAb against nerve growth factor for the treatment of acute and chronic pain. Curr Opin Mol Ther 12, 94-106.

Chang, P.C., Pollema-Mays, S.L., Centeno, M.V., Procissi, D., Contini, M., Baria, A.T., Martina, M., Apkarian, A.V., 2014. Role of nucleus accumbens in neuropathic pain: Linked multi-scale evidence in the rat transitioning to neuropathic pain. Pain 155, 1128-1139.

Colloca, L., Grillon, C., 2014. Understanding placebo and nocebo responses for pain management. Curr Pain Headache Rep 18, 419.

Constantinides, C., Mean, R., Janssen, B.J., 2011. Effects of isoflurane anesthesia on the cardiovascular function of the C57BL/6 mouse. Ilar Journal 52, e21-31.

102

Chapter IV: Discussion and conclusions

Cormier, S., Lavigne, G.L., Choiniere, M., Rainville, P., 2016. Expectations predict chronic pain treatment outcomes. Pain 157, 329-338.

Emery, E.C., Luiz, A.P., Wood, J.N., 2016. Nav1.7 and other voltage-gated sodium channels as drug targets for pain relief. Expert Opin Ther Targets 20, 975-983.

Evers, A.W., Bartels, D.J., van Laarhoven, A.I., 2014. Placebo and nocebo effects in itch and pain. Handb Exp Pharmacol 225, 205-214.

Fukuda, M., Vazquez, A.L., Zong, X.P., Kim, S.G., 2013. Effects of the a2-adrenergic receptor agonist dexmedetomidine on neural, vascular and BOLD fMRI responses in the somatosensory cortex. European Journal of Neuroscience 37, 80-95.

Grandjean, J., Derungs, R., Kulic, L., Welt, T., Henkelman, M., Nitsch, R.M., Rudin, M., 2016. Complex interplay between brain function and structure during cerebral amyloidosis in APP transgenic mouse strains revealed by multi-parametric MRI comparison. Neuroimage 134, 1-11.

Harris, A.P., Lennen, R.J., Marshall, I., Jansen, M.A., Pernet, C.R., Brydges, N.M., Duguid, I.C., Holmes, M.C., 2015. Imaging learned fear circuitry in awake mice using fMRI. European Journal of Neuroscience 42, 2125-2134.

Hund, T.J., Mohler, P.J., 2014. Nav channel complex heterogeneity: new targets for the treatment of arrhythmia? Circulation 130, 132-134.

103

Chapter IV: Discussion and conclusions

Jonckers, E., Palacios, R.D.Y., Shah, D., Guglielmetti, C., Verhoye, M., Van der Linden, A., 2014. Different Anesthesia Regimes Modulate the Functional Connectivity Outcome in Mice. Magnetic Resonance in Medicine 72, 1103-1112.

Jonckers, E., Van Audekerke, J., De Visscher, G., Van der Linden, A., Verhoye, M., 2011b. Functional Connectivity fMRI of the Rodent Brain: Comparison of Functional Connectivity Networks in Rat and Mouse. PLoS One 6.

Kerr, B.J., Souslova, V., McMahon, S.B., Wood, J.N., 2001. A role for the TTX-resistant sodium channel Nav 1.8 in NGF-induced hyperalgesia, but not neuropathic pain. Neuroreport 12, 3077-3080.

Klohs, J., Rudin, M., Shimshek, D.R., Beckmann, N., 2014. Imaging of cerebrovascular pathology in animal models of Alzheimer's disease. Frontiers in Aging Neuroscience 6.

Logothetis, N.K., Pauls, J., Augath, M., Trinath, T., Oeltermann, A., 2001. Neurophysiological investigation of the basis of the fMRI signal. Nature 412, 150-157.

Low, L.A., Bauer, L.C., Klaunberg, B.A., 2016. Comparing the Effects of Isoflurane and Alpha Chloralose upon Mouse Physiology. PLoS One 11.

Lukasik, V.M., Gillies, R.J., 2003. Animal anaesthesia for in vivo magnetic resonance. Nmr in Biomedicine 16, 459-467.

Martin, C., Martindale, J., Berwick, J., Mayhew, J., 2006. Investigating neural-hemodynamic coupling and the hemodynamic response function in the awake rat. Neuroimage 32, 33-48.

Minett, M.S., Falk, S., Santana-Varela, S., Bogdanov, Y.D., Nassar, M.A., Heegaard, A.M., Wood, J.N., 2014b. Pain without nociceptors? Nav1.7-independent pain mechanisms. Cell Rep 6, 301-312.

Minett, M.S., Pereira, V., Sikandar, S., Matsuyama, A., Lolignier, S., Kanellopoulos, A.H., Mancini, F., Iannetti, G.D., Bogdanov, Y.D., Santana-Varela, S., Millet, Q., Baskozos, G., MacAllister, R., Cox, J.J., Zhao, J., Wood, J.N., 2015. Endogenous opioids contribute to insensitivity to pain in humans and mice lacking sodium channel Na(v)1.7. Nature Communications 6.

104

Chapter IV: Discussion and conclusions

Petrinovic, M.M., Hankov, G., Schroeter, A., Bruns, A., Rudin, M., von Kienlin, M., Kunnecke, B., Mueggler, T., 2016. A novel anesthesia regime enables neurofunctional studies and imaging genetics across mouse strains. Sci Rep 6, 24523.

Salomons, T.V., Iannetti, G.D., Liang, M., Wood, J.N., 2016. The "Pain Matrix" in Pain-Free Individuals. JAMA Neurol 73, 755-756.

Silos-Santiago, I., 2008. The role of tetrodotoxin-resistant sodium channels in pain states: are they the next target for analgesic drugs? Curr Opin Investig Drugs 9, 83-89.

Stojanovic, M.P., Fonda, J., Fortier, C.B., Higgins, D.M., Rudolph, J.L., Milberg, W.P., McGlinchey, R.E., 2016. Influence of Mild Traumatic Brain Injury (TBI) and Posttraumatic Stress Disorder (PTSD) on Pain Intensity Levels in OEF/OIF/OND Veterans. Pain Med 17, 2017-2025.

Thompson, S.J., Bushnell, M.C., 2012. Rodent functional and anatomical imaging of pain. Neurosci Lett 520, 131-139.

Tomaselli, G.F., Farinelli, F., 2018. NaV Channels: Assaying Biosynthesis, Trafficking, Function. Methods Mol Biol 1722, 167-184.

Tracey, I., 2011. Can neuroimaging studies identify pain endophenotypes in humans? Nat Rev Neurol 7, 173-181.

Wierenga, C.E., Bondi, M.W., 2007. Use of functional magnetic resonance imaging in the early identification of Alzheimer's disease. Neuropsychology Review 17, 127-143.

Xu, L., Nwosu, L.N., Burston, J.J., Millns, P.J., Sagar, D.R., Mapp, P.I., Meesawatsom, P., Li, L., Bennett, A.J., Walsh, D.A., Chapman, V., 2016. The anti-NGF antibody muMab 911 both prevents and

105

Chapter IV: Discussion and conclusions

reverses pain behaviour and subchondral osteoclast numbers in a rat model of osteoarthritis pain. Osteoarthritis and Cartilage 24, 1587-1595.

Zhao, F., Wang, P., Hendrich, K., Kim, S.G., 2005. Spatial specificity of cerebral blood volume-weighted fMRI responses at columnar resolution. Neuroimage 27, 416-424.

Zhao, F., Wang, P., Hendrich, K., Ugurbil, K., Kim, S.G., 2006. Cortical layer-dependent BOLD and CBV responses measured by spin-echo and gradient-echo fMRI: insights into hemodynamic regulation. Neuroimage 30, 1149-1160.

Zhao, F.Q., Welsh, D., Williams, M., Coimbra, A., Urban, M.O., Hargreaves, R., Evelhoch, J., Williams, D.S., 2012. fMRI of pain processing in the brain: A within-animal comparative study of BOLD vs. CBV and noxious electrical vs. noxious mechanical stimulation in rat. Neuroimage 59, 1168- 1179.

Zhao, F.Q., Williams, M., Bowlby, M., Houghton, A., Hargreaves, R., Evelhoch, J., Williams, D.S., 2014. Qualification of fMRI as a biomarker for pain in anesthetized rats by comparison with behavioral response in conscious rats. Neuroimage 84, 724-732.

106

Acknowledgements

This work was strongly influenced by many persons and I would love to spend few words in their regards:

Markus Rudin, thanks for accepting me in your group, you have always been a comprehensive supervisor and your optimism motivated me to stay every day focused and more curious, your patience and swiss kindness made everything look easier also when it was not.

Aileen, thanks for your experience, I learned from you not to trust what I cannot see with my own eyes, Saint Thomas must have been an ancestor of yours, I am sure.

The AICers! all members of the AIC group made my time here great, a special thanks goes to Manoj, Markus, Aline (the author of the famous Hawaiian quote “no waterfalls no toilet”), Patrick, Ramanil, Cath, Jael, Marco D., Karthik (your soul belongs to this group!), Marija and Wuwei who never let me win at the Chinese checkers. Without all of you, life at the AIC would have been dramatically boring.

Valerio, thanks for your statistically significant inputs, your contributions allowed me to boost my skills and create new ones, your critical thinking helped me a lot during the past 4 years and every time I will odor roasted chicken I’ll think of you, I guess you’ve altered my FC.

My Zurich Friends: thanks to Marco B., Davide (a.k.a. Facchions), Francesco, Vale and Niccolo’, the time we’ve spent together gave me a break, it helped me putting all the problems aside and enjoying simple life pleasures.

And now we come to the most personal acknowledgements, those who definitely left a sign on my last years of life and therefore also on this thesis:

Jan, I could probably define you as my professional father or rather big brother (considering your young age :P). I always thought (and I still think) that my interview with you was a catastrophe, but nevertheless I got your trust, and I am thankful for all the time we have spent together in the lab, in the office and moreover in the kitchen, testing and tasting new culinary

protocols, I really appreciated our scientific and non-scientific discussions. Your healthy way of working and thinking is of great inspiration for me.

Cristina and Daniele thanks for being my friends since almost 10 years, thanks to have put your trust in me and Stefano as witnesses of your union, I will miss our cozy nights chatting about anything in front of one of our beloved risottos!

Rosetta, you have been treating me like a daughter without asking anything in return, your presence throughout my swiss journey was of great importance, your unconditional positiveness distracted me and kept me up during hard times.

My mythical buddies, the Moose team, my everyday joy and support: Georges and David you have been two amazing friends to me, I couldn’t ask for better mates to go through our daily life problems and satisfactions; our courses, our road trips, our nights out, our holidays. In other words our friendship is one of the greatest gift I could have hoped to have. Thank you!

My whole family: my parents, my sisters, Luca, Matilde and the little Ludovica; sometimes I have not felt supported, but I nevertheless want to thank all of you, because in one way or another you motivated me in pursuing my goals, and hopefully you could ultimately see that my work is an essential part of my happiness. Dad, thanks for being my first and most likely my greatest fan.

Stefano, I do not have the words to describe how important you have been, we were only two kids when we first met, and I am extremely proud of the two adults we became together, we have had hard times living apart for all these years, but our journey, finally together, is just around the corner, and I couldn’t be happier to begin this new adventure with you.

108

List of publications

• Valerio Zerbi, Giovanna D. Ielacqua , Marija Markicevic, Matthias Haberl , Mark H.Ellisman, Arjun A.Bhaskaran, Andreas Frick, Markus Rudin, Nicole Wenderoth. Dysfunctional Autism risk genes cause circuit-specific connectivity deficits with distinct developmental trajectories. Cerebral cortex 04/2018. DOI:10.1093/cercor/bhy046

• Kristoffer Sahlholm, Giovanna D. Ielacqua, Jinbin Xu, Lynne A Jones, Felix Schlegel, Robert H Mach, Markus Rudin, Aileen Schroeter: The role of beta-arrestin2 in shaping fMRI BOLD responses to dopaminergic stimulation. Psychopharmacology 04/2017; DOI:10.1007/s00213-017-4609-6

• Giovanna D. Ielacqua, Felix Schlegel, Martina Füchtemeier, Jael Xandry, Markus Rudin, Jan Klohs: Magnetic Resonance Q Mapping Reveals a Decrease in Microvessel Density in the arcAβ Mouse Model of Cerebral Amyloidosis. Frontiers in Aging Neuroscience 01/2016; 7(32).DOI:10.3389/fnagi.2015.00241

• Jan Klohs, Andreas Deistung, Giovanna D. Ielacqua, Aline Seuwen, Diana Kindler, Ferdinand Schweser, Markus Vaas, Anja Kipar, Jü Rgen, R Reichenbach, Markus Rudin: Quantitative assessment of microvasculopathy in arcAb mice with USPIO-enhanced gradient echo MRI. Journal of cerebral blood flow and metabolism: official journal of the International Society of Cerebral Blood Flow and Metabolism 12/2015; 36(9). DOI:10.1177/0271678X15621500

• Markus Rempfler, Matthias Schneider, Giovanna D. Ielacqua, Xianghui Xiao, Stuart R. Stock, Jan Klohs, Gábor Székely, Bjoern Andres, Bjoern H. Menze: Reconstructing Cerebrovascular Networks under Local Physiological Constraints by Integer Programming. Medical Image Analysis 04/2015; 25(1). DOI:10.1016/j.media.2015.03.008

• Markus Rempfler, Matthias Schneider, Giovanna D. Ielacqua, Tim Sprenger, Xianghui Xiao, Stuart R. Stock, Jan Klohs, Gábor Székely, Bjoern Andres, Bjoern H. Menze: Rekonstruktion zerebraler Gefässnetzwerke aus in-vivo μMRA mittels physiologischem Vorwissen zur lokalen Gefässgeometrie. Bildverarbeitung für die Medizin 2015, Edited by Handels, Heinz and Deserno, Thomas Martin and Meinzer, Hans-Peter and Tolxdorff, Thomas, 01/2015: pages 161-166; Springer Berlin/Heidelberg. DOI:10.1007/978-3-662-46224-9_29

• David Buehlmann, Giovanna D. Ielacqua, Jael Xandry, Markus Rudin. Preventive administration of anti-NGF treatment effectively suppresses functional connectivity alterations following cancer-induced bone pain in mice (submitted)

109

• Giovanna D. Ielacqua, David Buehlmann, Georges Hankov, Valerio Zerbi, Jael Xandry, Mark Augath, John N. Wood, Schroeter Aileen, Rudin Markus. fMRI characterization of sensory and pain processing in “pain-free” mice (In preparation)

• Ruiqing Ni, Diana Rita Kindler, Marie Rouault, Giovanna D. Ielacqua, Markus Rudin, Jan Klohs. Genetic deletion of the coagulation factor XII mitigates cerebral microbleed load but not hemodynamic dysfunction in the arcAβ mouse model of cerebral amyloidosis. (In preparation)

• Mustafa Çavuşoğlu, Beat Werner, Jia Zhang, Ielacqua Giovanna Diletta, Giovanni Pellegrini, Rea Deborah Signorell, Alexandros Papachristodoulou, Davide Brambilla, Paola Luciani, Patrick Roth, Michael Weller, Markus Rudin, Ernst Martin-Fiori, Jean- Christophe Leroux. Transcranial cavitation control during focused-ultrasound mediated blood-brain-barrier opening. (In preparation)

Conference proceedings

• Georges Hankov, Aline Seuwen, Giovanna D. Ielacqua, Anna Mechling, Eva Mracsko, Andreas Bruns, Basil Künnecke, Markus von Kienlin, Markus Rudin, Thomas Mueggler. Neurochemical signature of the metabolic mechanisms underlying de- & re- myelination in the mouse’s cerebellum. Proc. Intl. Soc. Mag. Reson. Med. 26 (2018) #0924 • David Buehlmann, Giovanna Ielacqua, Jael Xandry, Markus Rudin. Preventive anti-NGF treatment suppresses alterations in functional connectivity imposed by cancer-induced bone pain in mice. Proc. Intl. Soc. Mag. Reson. Med. 26 (2018) #2344 • Giovanna D. Ielacqua,, Aileen Schroeter, Aline Seuwen, David Buehlmann, John N. Wood, and Markus Rudin. fMRI and spectroscopic characterization of sensory and pain processing in “pain-free” mice. Proc. Intl. Soc. Mag. Reson. Med. 25 (2017) #1715 • Georges Hankov, Giovanna D. Ielacqua, Basil Künnecke, Thomas Mueggler, Markus von Kienlin, and Markus Rudin. Poloxamer: a new means to recover functional network information in the rodent’s deep brain structures. Proc. Intl. Soc. Mag. Reson. Med. 25 (2017) #5248 • David Buehlmann, Giovanna D. Ielacqua, Joanes Grandjean, Jael Xandry, and Markus Rudin. Towards specific biomarkers of chronic pain: Modelling behavior readouts of developing pain to resting-state functional connectivity using a developmental trajectory in a mouse model of chronic pain from bone cancer. Proc. Intl. Soc. Mag. Reson. Med. 25 (2017) #1710

110

• Giovanna D. Ielacqua, Aileen Schroeter, David Buehlmann, John N. Wood, Markus Rudin. fMRI characterization of sensory and pain processing in “pain-free” mice. The Challenge of Chronic Pain (2017) • Giovanna D. Ielacqua, Aileen Schroeter, David Bühlmann, Felix Schlegel, John N Wood, and Markus Rudin. fMRI characterization of pain processing in NaV1.7 Wnt1 KO mice. Proc. Intl. Soc. Mag. Reson. Med. 24 (2016) #1740 • David Bühlmann, Joanes Grandjean, Giovanna D. Ielacqua, Jael Xandry, and Markus Rudin. Longitudinal resting-state fMRI and 1H-MRS characterization in the mouse brain during development of a chronic pain state. Proc. Intl. Soc. Mag. Reson. Med. 24 (2016) #3751 • Giovanna D. Ielacqua, Aileen Schroeter, Mark Augath, Felix Schlegel and Markus Rudin. how specific is specific? stimulus-evoked fMRI in rats and mice. Proc. Intl. Soc. Mag. Reson. Med. 23 (2015) #2037 • Giovanna D. Ielacqua, Felix Schlegel, Markus Rudin, Jan Klohs. Age-dependent decrease of capillary density in arcAβ mouse model of cerebral amyloidosis detected with Relaxation Rate Shift Index Q mapping at 9.4T using a Cryoprobe. Proc. Intl. Soc. Mag. Reson. Med. 22 (2014) #2098

111

Curriculum Vitae

Education Jan 2014 – Apr 2018 Ph.D. Student ETH Zurich, Institute for Biomedical Engineering. Zurich, Switzerland June 2012 State Exam Dr. Vet. Med Sep 2006 – Oct 2011 Veterinary Medicine Degree Department of Veterinary Science, University of Turin, Italy Sep 2009 – Sep 2010 Exchange Student Vetsuisse faculty, University of Zurich, Switzerland Sep 2001- Jul 2006 High School “G. Keplero“ Scientific High school, Rome, Italy Jun-Jul 2005 Exchange Student “Egbert- Gymnasium” Humanistisches- neusprachliches Gymnasium. Muensterschwarzach, Germany

Work Experience Sep 2017 – Apr 2018 Head of animal facility ETH Zurich, Institute for Biomedical Engineering. Zurich, Switzerland Management of the animal facility, animal import/export, animal health report Jan 2014 – present Doctoral researcher ETH Zurich, Institute for Biomedical Engineering. Zurich, Switzerland fMRI characterization of pain models in rodents. Se-fMRI, rs-fMRI from acquisition to data analysis Jan 2014 – Sep 2017 Vice Head of animal facility ETH Zurich, Institute for Biomedical Engineering. Zurich, Switzerland Management of the animal facility, animal import/export, animal health report Aug 2012 – Dec 2013 Dr. Vet. Med. ETH Zurich, Institute for Biomedical Engineering. Zurich, Switzerland Vascular Pathology in Alzheimer's Disease. Magnetic resonance angiography (MRA) and perfusion MRI in a mouse model of Alzheimer’s Disease, acquisition and data analysis Jan 2012 – Aug 2012 Veterinarian - Clinic and surgery of small animals Ambulatorio Veterinario Centro. Turin, Italy Oct 2010 – Oct 2011 Vet. Med. Thesis Department of Veterinary Sciences, University of Turin. Turin, Italy Microencapsulated organic acids therapy in Salmonella typhimurium pigs infection. Autopsy, Histopathology, data analysis

Awards Oct 2015 Best Paper Award - Medical Image Analysis - MICCAI 2015 Reconstructing Cerebrovascular Networks under Local Physiological Constraints by Integer Programming. Medical Image Analysis Skills and Activities Skills MRI data acquisition, rodents anesthesia, intubation and cannulation, MR angiography, se-fMRI/rs-fMRI in mice and rats, FSL, AFNI, ITKsnap,

112

neurosurgery (SNI mice), Immunofluorescence, Immunohistochemistry, Neuropathology, Histopathology, Neurobiology and Brain Physiology, Confocal Microscopy, Necropsy, Microsoft Office, Prism, Sigma Plot. Certifications FELASA B certificate - Education and training of persons carrying out animal experiments FELASA C certificate - Education for persons responsible for directing animal experiments/Ausbildung zum Leiter von Tierversuchen.

Teaching duties EXCITE Summer School on Biomedical Engineering (2013 - present) Theory and practice of fMRI experiments in mice and rats. Workshop: Functional MRI in mice: setup, animal preparation and monitoring (Nov 2016/May 2017) Languages Italian (native), English (fluent), German (fluent), French (basic knowledge) Memberships ESMRMB ESMI ISMRM Other Interests I like to travel and take pictures, I have a passion for long distance swimming and l love cooking.

113