Modulations of Insular Projections by Prior Belief Mediate the Precision of Prediction Error During Tactile Learning

Total Page:16

File Type:pdf, Size:1020Kb

Modulations of Insular Projections by Prior Belief Mediate the Precision of Prediction Error During Tactile Learning Research Articles: Behavioral/Cognitive Modulations of insular projections by prior belief mediate the precision of prediction error during tactile learning https://doi.org/10.1523/JNEUROSCI.2904-19.2020 Cite as: J. Neurosci 2020; 10.1523/JNEUROSCI.2904-19.2020 Received: 5 December 2019 Revised: 26 February 2020 Accepted: 27 February 2020 This Early Release article has been peer-reviewed and accepted, but has not been through the composition and copyediting processes. The final version may differ slightly in style or formatting and will contain links to any extended data. Alerts: Sign up at www.jneurosci.org/alerts to receive customized email alerts when the fully formatted version of this article is published. Copyright © 2020 Wang (##) et al. 1 Modulations of insular projections by prior belief mediate the 2 precision of prediction error during tactile learning 3 Bin A. Wang (⦻ᮼ)1,2, Lara Schlaffke1,2, Burkhard Pleger1-3 4 1Department of Neurology, BG University Hospital Bergmannsheil, Ruhr-University Bochum, 5 Bürkle-de-la-Camp Place 1, 44789 Bochum, Germany 2 6 Collaborative Research Centre 874 "Integration and Representation of Sensory Processes", Ruhr 7 University Bochum, Universitätsstraße 150, 44780 Bochum, Germany 8 3Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, 9 Stephanstr. 1a, 04103 Leipzig, Germany Abbreviated title: Insular projections encode precision of prediction Correspondence to: Burkhard Pleger, MD Department of Neurology, BG University Hospital Bergmannsheil Ruhr-University Bochum Bürkle-de-la-Camp Place 1, 44789, Bochum, Germany Phone: +49 (0) 234-302-3551 Fax: +49 (0) 234-302-6888 Email: [email protected] & Bin A. Wang, PhD Department of Neurology, BG University Hospital Bergmannsheil Ruhr-University Bochum Bürkle-de-la-Camp Place 1, 44789, Bochum, Germany Phone: +49 (0) 234-302-3857 Email: [email protected] 10 1 11 Number of pages: 35 12 Number of figures: 7 13 Number of tables: 1 14 Number of words for abstract: 151 15 Number of words for introduction: 558 16 Number of words for discussion: 1301 17 18 19 20 Acknowledgements: 21 This work was supported by the Deutsche Forschungsgemeinschaft (DFG, German 22 Research Foundation): Project number 122679504 - SFB 874 ‘Integration and 23 Representation of Sensory Processes’. 24 Conflict of Interest: 25 The authors declare no competing financial interests. 2 26 Abstract 27 Awareness for surprising sensory events is shaped by their prior belief inferred from past 28 experience. Here, we combined hierarchical Bayesian modeling with fMRI on an 29 associative learning task in 28 male human participants to characterize the effect of the 30 prior belief of tactile events on connections mediating the outcome of perceptual 31 decisions. Activity in anterior insula (AIC), premotor cortex (PMd) and inferior parietal 32 lobule (IPL) were modulated by prior belief on unexpected targets as compared to 33 expected targets. On expected targets, prior belief decreased the connection strength from 34 AIC to IPL, whereas it increased the connection strength from AIC to PMd when targets 35 were unexpected. Individual differences in the modulatory strength of prior belief on 36 insular projections correlated with the precision that increases the influence of prediction 37 errors on belief updating. These results suggest complementary effects of prior belief on 38 insular-frontoparietal projections mediating the precision of prediction during 39 probabilistic tactile learning. 40 41 Key words: hierarchical Bayesian modeling; dynamic causal modeling; functional 42 magnetic resonance imaging; tactile learning; prediction 43 3 44 Significance Statement 45 In a probabilistic environment, the prior belief of sensory events can be inferred from 46 past experiences. How this prior belief modulates effective brain connectivity for 47 updating expectations for future decision-making remains unexplored. Combining 48 hierarchical Bayesian modeling with fMRI, we show that during tactile associative 49 learning, prior expectations modulate connections originating in the anterior insula cortex 50 and targeting salience and attention related frontoparietal areas (i.e., parietal and 51 premotor cortex). These connections seem to be involved in updating evidence based on 52 the precision of ascending inputs to guide future decision-making. 53 4 54 Introduction 55 The expectation for the occurrence of tactile events is modulated by prior experiences 56 (Lovero et al. 2009; van Ede et al. 2010; Van Ede et al. 2014). In a probabilistic 57 environment, prior belief about the causes of relevant stimuli, such as imminent tactile 58 inputs, is continuously updated based on past experiences following the principle of 59 predictive coding (Rao and Ballard 1999) and free energy (Friston and Kiebel 2009). In 60 this framework, bottom-up sensations and top-down predictions are integrated by 61 precision-dependent computational processes, where the precision or confidence 62 increases the influence of ascending prediction error (PE) signals on perceptual inference 63 via post-synaptic gain (i.e., cortical gain control or excitation-inhibition balance) 64 (Feldman and Friston 2010). 65 Awareness of surprising or unexpected tactile sensations is thought to depend on 66 interactions within a hierarchically organized somatosensory system. Somatosensory 67 mismatch negativity, as a PE equivalent, elicited by an unexpected deviant has been 68 shown to follow Bayesian rules (Ostwald et al. 2012; Allen et al. 2016; Fardo et al. 2017). 69 These rules seem to be encoded by recurrent processing loops in a network encompassing 70 primary/secondary somatosensory cortices (S1/S2), inferior frontal cortex and anterior 71 cingulate cortex (Ostwald et al. 2012). Unexpected tactile events particularly increase 72 recurrent connectivity between S1/S2, inferior/middle frontal and inferior parietal regions 73 (Allen et al. 2016; Fardo et al. 2017), while the anterior insular cortex (AIC) seems 74 crucial for the integration of afferent sensory inputs with top-down control arising in the 75 frontal and cingulate cortex (Allen et al. 2016). 5 76 Behavioral performance and neural responses to expected and unexpected outcomes are 77 modulated by prior beliefs about future states of the tactile environment. The degree of 78 anticipation has been shown to improve the precision of tactile sensations (Van Ede et al. 79 2014), whereas uncertainty (Rossi-Pool et al. 2016; Schröder et al. 2019) or the 80 constitutive elements of perceptual inference, i.e., prediction error and precision 81 weighting (Ostwald et al. 2012; Allen et al. 2016; Fardo et al. 2017), are well reflected by 82 neural responses in the insular, cingulate, and premotor cortex. Despite all this evidence, 83 how prior belief regulates effective connectivity in the somatosensory network for future 84 decision-making remains unknown. 85 In an associative learning task, the association strength of the decision and the 86 corresponding feedback is continuously updated on the basis of recent observations. 87 Considerable evidence has shown that this inference can be conceptualized by 88 hierarchical Bayesian modeling (Iglesias et al. 2013; Vossel et al. 2015; Kuhns et al. 89 2017; Weilnhammer et al. 2018). Here, we applied an adapted tactile associative learning 90 task where participants had to learn the changing predictive strength of a sample stimulus 91 in forecasting a subsequently presented target. Trial-wise prior belief about the sample- 92 target contingency were used as modulators of effective connectivity for expected and 93 unexpected targets. 94 We hypothesized to identify a hierarchically organized somatosensory network, 95 consisting of the insular cortex and frontoparietal regions, in which predicted outcomes, 96 i.e., the awareness for expected and unexpected targets, are differentially modulated by 97 prior belief. Since the insular cortex is considered as a core hub regulating the interaction 98 of bodily, attentional, and anticipatory tactile signals (Sridharan et al. 2008; Lovero et al. 6 99 2009; Menon and Uddin 2010; Allen et al. 2016), we further expected that efferent 100 projections originating in the insula may change as a function of prior belief for expected 101 and unexpected targets, which, in turn may signal the precision weighting for belief 102 updating. 103 Materials and Methods 104 Participants 105 We recruited thirty-three healthy male participants (mean age ± SD: 25.1 ± 3.8 years). 106 Only male participants were included to avoid the influences of hormonal fluctuations 107 over the menstrual cycle on learning and associated blood-oxygen-level-dependent 108 (BOLD) signals (Dreher et al. 2007; Sacher et al. 2013; Wetherill et al. 2016). Five 109 participants were excluded due to more than 20% invalid trials (i.e., missed or late 110 response >1300ms) or less than 60% correct responses. Consequently, twenty-eight 111 participants were included for further date analysis (mean age ± SD: 25.3 ± 3.9 years). 112 All participants were right-handed as assessed by the Edinburgh Handedness Inventory 113 (Oldfield 1971) and had normal or corrected to normal vision, no history of 114 psychiatric/neurological disorders or regular medication. The study was approved by the 115 ethics committee of the Ruhr-University Bochum. 116 Tactile stimuli 117 The tactile stimuli were generated and delivered using an MRI-compatible piezoelectric 118 Braille stimulator (Metec, Stuttgart, Germany).
Recommended publications
  • Prefrontal and Posterior Parietal Contributions to the Perceptual Awareness of Touch M
    www.nature.com/scientificreports OPEN Prefrontal and posterior parietal contributions to the perceptual awareness of touch M. Rullmann1,2,5, S. Preusser1,5 & B. Pleger1,3,4* Which brain regions contribute to the perceptual awareness of touch remains largely unclear. We collected structural magnetic resonance imaging scans and neurological examination reports of 70 patients with brain injuries or stroke in S1 extending into adjacent parietal, temporal or pre-/frontal regions. We applied voxel-based lesion-symptom mapping to identify brain areas that overlap with an impaired touch perception (i.e., hypoesthesia). As expected, patients with hypoesthesia (n = 43) presented lesions in all Brodmann areas in S1 on postcentral gyrus (BA 1, 2, 3a, 3b). At the anterior border to BA 3b, we additionally identifed motor area BA 4p in association with hypoesthesia, as well as further ventrally the ventral premotor cortex (BA 6, BA 44), assumed to be involved in whole-body perception. At the posterior border to S1, we found hypoesthesia associated efects in attention-related areas such as the inferior parietal lobe and intraparietal sulcus. Downstream to S1, we replicated previously reported lesion-hypoesthesia associations in the parietal operculum and insular cortex (i.e., ventral pathway of somatosensory processing). The present fndings extend this pathway from S1 to the insular cortex by prefrontal and posterior parietal areas involved in multisensory integration and attention processes. Te primary somatosensory cortex (S1) in monkeys can be divided into four Brodmann areas: (BA) 1, 2, 3a, and 3b. Each BA consists of a somatotopically organized map that subserves distinct somatosensory functions1–3.
    [Show full text]
  • Imaging the Premotor Areas Nathalie Picard* and Peter L Strick†
    663 Imaging the premotor areas Nathalie Picard* and Peter L Strick† Recent imaging studies of motor function provide new insights critically on a clear definition of the location and boundaries into the organization of the premotor areas of the frontal lobe. of these cortical areas. Thus, one focus of our review The pre-supplementary motor area and the rostral portion of synthesizes the new data that is relevant to this issue. the dorsal premotor cortex, the ‘pre-PMd’, are, in many respects, more like prefrontal areas than motor areas. Recent Medial wall data also suggest the existence of separate functional divisions Pre-supplementary motor area and supplementary in the rostral cingulate zone. motor area In monkeys, it is now established that area 6 on the medial Addresses wall of the brain contains two separate areas: the supple- Department of Neurobiology, University of Pittsburgh School of mentary motor area proper (SMA) in the caudal portion of Medicine, W1640 Biomedical Science Tower, 200 Lothrop Street, area 6, and the pre-SMA in the rostral portion (Figure 1a; Pittsburgh, PA 15261, USA reviewed in [2,4]). The SMA and pre-SMA are equivalent *e-mail: [email protected] †e-mail: [email protected] to fields F3 and F6 described by Matelli et al. [5]. In humans, the level of the anterior commissure (VCA line) Current Opinion in Neurobiology 2001, 11:663–672 [6] marks the border between the two areas. The division 0959-4388/01/$ — see front matter of medial area 6 into two distinct fields is based on a © 2001 Elsevier Science Ltd.
    [Show full text]
  • A Practical Review of Functional MRI Anatomy of the Language and Motor Systems
    REVIEW ARTICLE FUNCTIONAL A Practical Review of Functional MRI Anatomy of the Language and Motor Systems X V.B. Hill, X C.Z. Cankurtaran, X B.P. Liu, X T.A. Hijaz, X M. Naidich, X A.J. Nemeth, X J. Gastala, X C. Krumpelman, X E.N. McComb, and X A.W. Korutz ABSTRACT SUMMARY: Functional MR imaging is being performed with increasing frequency in the typical neuroradiology practice; however, many readers of these studies have only a limited knowledge of the functional anatomy of the brain. This text will delineate the locations, anatomic boundaries, and functions of the cortical regions of the brain most commonly encountered in clinical practice—specifically, the regions involved in movement and language. ABBREVIATIONS: FFA ϭ fusiform face area; IPL ϭ inferior parietal lobule; PPC ϭ posterior parietal cortex; SMA ϭ supplementary motor area; VOTC ϭ ventral occipitotemporal cortex his article serves as a review of the functional areas of the brain serving to analyze spatial position and the ventral stream working Tmost commonly mapped during presurgical fMRI studies, to identify what an object is. Influenced by the dorsal and ventral specifically targeting movement and language. We have compiled stream model of vision, Hickok and Poeppel2 hypothesized a sim- what we hope is a useful, easily portable, and concise resource that ilar framework for language. In this model, the ventral stream, or can be accessible to radiologists everywhere. We begin with a re- lexical-semantic system, is involved in sound-to-meaning map- view of the language-processing system. Then we describe the pings associated with language comprehension and semantic ac- gross anatomic boundaries, organization, and function of each cess.
    [Show full text]
  • Neuromodulation: Harnessing Neuroplasticity with Brain Stimulation and Rehabilitation
    Neuromodulation: Harnessing Neuroplasticity with Brain Stimulation and Rehabilitation Presenters: Cecília N. Prudente, PT, MS, PhD1 Bernadette T. Gillick, PT, MS, PhD1 Colum MacKinnon, PhD2 Teresa J.Kimberley, PT, PhD1 1Dept. of Rehabilitation Medicine 2Dept. of Neurology Conflicts of interest TJK: consulting income from MicroTransponder Others: Nothing to declare Learning objectives 1. Be familiar with forms of brain stimulation 2. Be able to identify safety and feasibility of each technique 3. Understand the purposes of using the parameters of brain stimulation 4. Translate brain stimulation research into clinical implications Harnessing neuroplasticity to improve motor function 1. Neuromodulation tools 2. Down-regulation 3. Up-regulation 4. Hijacking neural firing patterns 5. Where are we now, where are we going, and how do we get there? 6. Discussion Harnessing neuroplasticity to improve motor function 1. Neuromodulation tools 2. Down-regulation 3. Up-regulation 4. Hijacking neural firing patterns 5. Where are we now, where are we going, and how do we get there? 6. Discussion What is neuromodulation? http://blog.cambridgeconsultants.com/medical-technology/wp- content/uploads/2014/05/Neuromodulation.jpg Publications per year 1200 1000 800 Neuromodulation 600 Neuromodulation & rehabilitation 400 200 0 2016 1978 1988 1998 2008 Source: Pubmed How to neuromodulate? Healthy state Neuroplasticity Injury Medications Neuromodulation Rehabilitation Neuromodulation tools Why neuromodulate? E I Healthy state : greater excitability : greater inhibition
    [Show full text]
  • A Scoping Review of Neuromodulation Techniques in Neurodegenerative Diseases: a Useful Tool for Clinical Practice?
    medicina Review A Scoping Review of Neuromodulation Techniques in Neurodegenerative Diseases: A Useful Tool for Clinical Practice? Fabio Marson 1,2 , Stefano Lasaponara 3,4 and Marco Cavallo 5,6,* 1 Research Institute for Neuroscience, Education and Didactics, Fondazione Patrizio Paoletti, 06081 Assisi, Italy; [email protected] 2 Department of Human Neuroscience, Sapienza University of Rome, 00185 Rome, Italy 3 Department of Psychology, Sapienza University of Rome, 00185 Rome, Italy; [email protected] 4 Department of Human Sciences, LUMSA University, 00193 Rome, Italy 5 Faculty of Psychology, eCampus University, 22060 Novedrate, Italy 6 Clinical Psychology Service, Saint George Foundation, 12030 Cavallermaggiore, Italy * Correspondence: [email protected]; Tel.: +39-347-830-6430 Abstract: Background and Objectives: Neurodegenerative diseases that typically affect the elderly such as Alzheimer’s disease, Parkinson’s disease and frontotemporal dementia are typically char- acterised by significant cognitive impairment that worsens significantly over time. To date, viable pharmacological options for the cognitive symptoms in these clinical conditions are lacking. In recent years, various studies have employed neuromodulation techniques to try and contrast patients’ decay. Materials and Methods: We conducted an in-depth literature review of the state-of-the-art of the contribution of these techniques across these neurodegenerative diseases. Results: The present review reports that neuromodulation techniques targeting cognitive impairment do not allow to Citation: Marson, F.; Lasaponara, S.; Cavallo, M. A Scoping Review of draw yet any definitive conclusion about their clinical efficacy although preliminary evidence is very Neuromodulation Techniques in encouraging. Conclusions: Further and more robust studies should evaluate the potentialities and Neurodegenerative Diseases: A limitations of the application of these promising therapeutic tools to neurodegenerative diseases.
    [Show full text]
  • Motivational System Modulates Brain Responses During Exploratory Decision‑Making Chia‑Wei Li1, Carol Yeh‑Yun Lin2*, Ting‑Ting Chang3,4, Nai‑Shing Yen3,4 & Danchi Tan5
    www.nature.com/scientificreports OPEN Motivational system modulates brain responses during exploratory decision‑making Chia‑Wei Li1, Carol Yeh‑Yun Lin2*, Ting‑Ting Chang3,4, Nai‑Shing Yen3,4 & Danchi Tan5 Managers face risk in explorative decision‑making and those who are better at such decisions can achieve future viability. To understand what makes a manager efective at explorative decision‑ making requires an analysis of the manager’s motivational characteristics. The behavioral activation/ inhibition system (BAS/BIS), ftting the motivational orientation of “approach” or “avoidance,” can afect individual decision‑making. However, very little is known about the neural correlates of BAS/BIS orientation and their interrelationship with the mental activity during explorative decision‑making. We conducted an fMRI study on 111 potential managers to investigate how the brain responses of explorative decision‑making interact with BAS/BIS. Participants were separated into high‑ and low‑ performance groups based on the median exploration‑score. The low‑performance group showed signifcantly higher BAS than that of the high‑performance group, and its BAS had signifcant negative association with neural networks related to reward‑seeking during explorative decision‑making. Moreover, the BIS of the low‑performance group was negatively correlated with the activation of cerebral regions responding to risk‑choice during explorative decision‑making. Our fnding showed that BAS/BIS was associated with the brain activation during explorative decision‑making only in the low‑performance group. This study contributed to the understanding of the micro‑foundations of strategically relevant decision‑making and has an implication for management development. Organizations need both exploitation and exploration in order to survive and prosper in changing environments1–3.
    [Show full text]
  • Mirror Neurons for Execution, Observation, and Imagery ⁎ Flavia Filimon,A, Jonathan D
    www.elsevier.com/locate/ynimg NeuroImage 37 (2007) 1315–1328 Human cortical representations for reaching: Mirror neurons for execution, observation, and imagery ⁎ Flavia Filimon,a, Jonathan D. Nelson,a,b Donald J. Hagler,a and Martin I. Serenoa aDepartment of Cognitive Science, University of California, San Diego, 9500 Gilman Dr. #0515, La Jolla, CA 92093-0515, USA bComputational Neurobiology Laboratory, Salk Institute, La Jolla, CA, USA Received 5 April 2007; revised 27 May 2007; accepted 8 June 2007 Available online 18 June 2007 We used functional magnetic resonance imaging (fMRI) to map the Electrophysiological studies in macaques have identified several cortical representations of executed reaching, observed reaching, and frontal areas involved in hand action representations (Preuss et al., imagined reaching in humans. Whereas previous studies have mostly 1996; Muakkassa and Strick, 1979; Matelli and Luppino, 2001; examined hand actions related to grasping, hand–object interactions, Rizzolatti et al., 1988). For instance, both dorsal premotor cortex or local finger movements, here we were interested in reaching only (i.e. (PMd, or F2 and F7) and ventral premotor cortex (PMv, or F4 and the transport phase of the hand to a particular location in space), F5) contain arm/hand representations that are specific to certain without grasping. We hypothesized that mirror neuron areas specific to reaching-related representations would be active in all three conditions. motor actions, such as grasping or reaching (Matelli and Luppino, An overlap between executed, observed, and imagined reaching 2001). More specifically, neurons that respond to both hand action activations was found in dorsal premotor cortex as well as in the execution (e.g.
    [Show full text]
  • The Cingulate Cortex and Limbic Systems for Emotion, Action, and Memory
    Brain Structure and Function https://doi.org/10.1007/s00429-019-01945-2 REVIEW The cingulate cortex and limbic systems for emotion, action, and memory Edmund T. Rolls1,2 Received: 19 April 2019 / Accepted: 19 August 2019 © The Author(s) 2019 Abstract Evidence is provided for a new conceptualization of the connectivity and functions of the cingulate cortex in emotion, action, and memory. The anterior cingulate cortex receives information from the orbitofrontal cortex about reward and non-reward outcomes. The posterior cingulate cortex receives spatial and action-related information from parietal cortical areas. It is argued that these inputs allow the cingulate cortex to perform action–outcome learning, with outputs from the midcingulate motor area to premotor areas. In addition, because the anterior cingulate cortex connects rewards to actions, it is involved in emotion; and because the posterior cingulate cortex has outputs to the hippocampal system, it is involved in memory. These apparently multiple diferent functions of the cingulate cortex are related to the place of this proisocortical limbic region in brain connectivity. Keywords Cingulate cortex · Limbic systems · Hippocampus · Orbitofrontal cortex · Emotion · Memory · Depression Introduction: the cingulate cortex and other stream processing areas that decode ‘what’ the stimulus is limbic structures (Rolls 2014b, 2016a, 2019a, b). The hippocampus is a key structure in episodic memory with inputs from the dorsal A key area included by Broca in his limbic lobe (Broca stream cortical areas about space, action, and ‘where’ events 1878) is the cingulate cortex, which hooks around the cor- occur, as well as from the ‘what’ ventral processing stream pus callosum.
    [Show full text]
  • How Does the Brain Produce Movement?
    p CHAPTER 10 How Does the Brain Produce Movement? The Hierarchical Control The Basal Ganglia and of Movement the Cerebellum The Forebrain and Movement Initiation The Basal Ganglia and Movement Force The Brainstem and Species-Typical Movement Focus on Disorders: Tourette’s Syndrome Focus on Disorders: Autism The Cerebellum and Movement Skill The Spinal Cord and Movement Execution Focus on Disorders: Paraplegia The Organization of the Somatosensory System The Organization of the Somatosensory Receptors and Sensory Perception Motor System Dorsal-Root Ganglion Neurons The Motor Cortex The Somatosensory Pathways to the Brain The Corticospinal Tracts Spinal-Cord Responses to Somatosensory Input The Motor Neurons The Vestibular System and Balance The Control of Muscles Exploring the Somatosensory The Motor Cortex and Skilled System Movements The Somatosensory Homunculus Investigating Neural Control of Skilled Movements The Effects of Damage to the Somatosensory Cortex The Control of Skilled Movements in Other Species The Somatosensory Cortex and Complex How Motor Cortex Damage Affects Skilled Movement Movements Kevork Djansezian/AP Photo Micrograph: Dr. David Scott/Phototake 354 I p amala is a female Indian elephant that lives at the In one way, however, Kamala uses this versatile trunk zoo in Calgary, Canada. Her trunk, which is really very unusually for an elephant (Onodera & Hicks, 1999). K just a greatly extended upper lip and nose, con- She is one of only a few elephants in the world that paints sists of about 2000 fused muscles. A pair of nostrils runs its with its trunk (Figure 10-1). Like many artists, she paints length and fingerlike projections are located at its tip.
    [Show full text]
  • Schaer K., Jahn G., Lotze M. (2012) Fmri-Activation During Drawing A
    Behavioural Brain Research 233 (2012) 209–216 Contents lists available at SciVerse ScienceDirect Behavioural Brain Research j ournal homepage: www.elsevier.com/locate/bbr Research report fMRI-activation during drawing a naturalistic or sketchy portrait a b a,∗ K. Schaer ,G.Jahn , M. Lotze a Functional Imaging Unit, Center for Diagnostic Radiology and Neuroradiology, University of Greifswald, Greifswald, Germany b Department of Psychology, University of Greifswald, Greifswald, Germany h i g h l i g h t s We used fMRI to measure 20 naive subjects during drawing a portrait. Participants were able to track their drawing online. We identified three important circuits specific for the process of portrait drawing. Circuits where: face perception, location encoding, and continuous feedback processes. Representations involved: fusiform gyrus, precuneus, parietal sulcus, and cerebellum. a r t i c l e i n f o a b s t r a c t Article history: Neural processes for naturalistic drawing might be discerned into object recognition and analysis, atten- Received 8 March 2012 tion processes guiding eye hand interaction, encoding of visual features in an allocentric reference frame, Received in revised form 3 May 2012 a transfer into the motor command and precise motor guidance with tight sensorimotor feedback. Cere- Accepted 8 May 2012 bral representations in a real life paradigm during naturalistic drawing have sparsely been investigated. Available online 15 May 2012 Using a functional Magnetic Resonance Imaging (fMRI) paradigm we measured 20 naive subjects during drawing a portrait from a frontal face presented as a photograph. Participants were asked to draw the Keywords: portrait in either a naturalistic or a sketchy characteristic way.
    [Show full text]
  • Primary Motor and Sensory Cortical Areas Communicate Via Spatiotemporally Coordinated Networks at Multiple Frequencies
    Primary motor and sensory cortical areas communicate via spatiotemporally coordinated networks at multiple frequencies Fritzie I. Arce-McShanea,1, Callum F. Rossa, Kazutaka Takahashia, Barry J. Sessleb, and Nicholas G. Hatsopoulosa,c,d,1 aDepartment of Organismal Biology and Anatomy, University of Chicago, Chicago, IL 60637; bFaculty of Dentistry, University of Toronto, Toronto, ON M5G 1G6, Canada; cCommittee on Computational Neuroscience, University of Chicago, Chicago, IL 60637; and dCommittee on Neurobiology, University of Chicago, Chicago, IL 60637 Edited by Nancy Kopell, Boston University, Boston, MA, and approved March 9, 2016 (received for review January 22, 2016) Skilled movements rely on sensory information to shape optimal show that interactions between MIo and SIo involve coherent motor responses, for which the sensory and motor cortical areas networks at multiple frequencies. Cortical processes may make are critical. How these areas interact to mediate sensorimotor inte- use of the dynamics of oscillatory rhythms and coherence phase gration is largely unknown. Here, we measure intercortical coherence to coordinate the activation of sensorimotor networks at multiple between the orofacial motor (MIo) and somatosensory (SIo) areas of spatial and temporal scales. cortex as monkeys learn to generate tongue-protrusive force. We report that coherence between MIo and SIo is reciprocal and that Results neuroplastic changes in coherence gradually emerge over a few We trained two naïve monkeys to protrude the tongue onto a days. These functional networks of coherent spiking and local field force transducer and apply isometric force at the level cued by potentials exhibit frequency-specific spatiotemporal properties. target positions shown on a video screen (Fig.
    [Show full text]
  • Area 2 of Primary Somatosensory Cortex Encodes Kinematics of the Whole Arm Raeed H Chowdhury1,2*, Joshua I Glaser3,4,5, Lee E Miller1,6,7,8*
    RESEARCH ARTICLE Area 2 of primary somatosensory cortex encodes kinematics of the whole arm Raeed H Chowdhury1,2*, Joshua I Glaser3,4,5, Lee E Miller1,6,7,8* 1Department of Biomedical Engineering, Northwestern University, Evanston, United States; 2Systems Neuroscience Institute, University of Pittsburgh, Pittsburgh, United States; 3Interdepartmental Neuroscience Program, Northwestern University, Chicago, United States; 4Department of Statistics, Columbia University, New York, United States; 5Zuckerman Mind Brain Behavior Institute, Columbia University, New York, United States; 6Department of Physiology, Northwestern University, Chicago, United States; 7Department of Physical Medicine and Rehabilitation, Northwestern University, Chicago, United States; 8Shirley Ryan AbilityLab, Chicago, United States Abstract Proprioception, the sense of body position, movement, and associated forces, remains poorly understood, despite its critical role in movement. Most studies of area 2, a proprioceptive area of somatosensory cortex, have simply compared neurons’ activities to the movement of the hand through space. Using motion tracking, we sought to elaborate this relationship by characterizing how area 2 activity relates to whole arm movements. We found that a whole-arm model, unlike classic models, successfully predicted how features of neural activity changed as monkeys reached to targets in two workspaces. However, when we then evaluated this whole-arm model across active and passive movements, we found that many neurons did not consistently represent the whole arm over both conditions. These results suggest that 1) neural activity in area 2 includes representation of the whole arm during reaching and 2) many of these neurons represented limb state differently during active and passive movements. *For correspondence: [email protected] (RHC); [email protected] (LEM) Introduction Moving in an uncontrolled environment is a remarkably complex feat.
    [Show full text]