Application of in Neuropsychiatric Diseases (Supplements to Clinical Neurophysiology, Vol. 62) Editors: E. Bas¸ar, C. Bas¸ar-Erog˘lu, A. O¨ zerdem, P.M. Rossini, G.G. Yener 343 # 2013 Elsevier B.V. All rights reserved

Chapter 20

Brain oscillations as biomarkers in neuropsychiatric disorders: following an interactive panel discussion and synopsis

Go¨ rsev G. Yenera,b,* and Erol Bas¸arb aBrain Dynamics Multidisciplinary Research Center, and Departments of and Neurology, Dokuz Eylu¨l University, Izmir 35340, Turkey bBrain Dynamics, Cognition and Complex Systems Research Center, Istanbul Kultur University, Istanbul 34156, Turkey

ABSTRACT This survey covers the potential use of neurophysiological changes as a biomarker in four neuropsychiatric diseases ( deficit hyperactivity disorder (ADHD), Alzheimer’s disease (AD), bipolar disorder (BD), and (SZ)). Great developments have been made in the search of biomarkers in these disorders, especially in AD. Nevertheless, there is a tremendous need to develop an efficient, low-cost, potentially portable, non-invasive biomarker in the diagnosis, course, or treatment of the above-mentioned disorders. Electrophysiological methods would provide a tool that would reflect functional brain dynamic changes within milliseconds and also may be used as an ensemble of biomarkers that is greatly needed in the evaluation of cognitive changes seen in these disorders. The strategies for measuring cognitive changes include spontaneous (EEG), sensory evoked (SEO), and event-related oscillations (ERO). Further selective connectivity deficit in sensory or cognitive networks is reflected by coherence measurements. Possible candidate biomarkers discussed in an interactive panel can be summarized as follows: for ADHD: (a) elevation of delta and theta, (b) diminished alpha and beta responses in spontaneous EEG; for SZ: (a) decrease of ERO gamma responses, (b) decreased ERO in all other ranges, (c) invariant ERO gamma response in relation to working demand; for euthymic BD: (a) decreased event-related gamma coherence, (b) decreased alpha in ERO and in spontaneous EEG; for manic BD: (a) lower alpha and higher beta in ERO, (b) decreased event-related gamma coherence, (c) lower alpha and beta in ERO after valproate; and for AD: (a) decreased alpha and beta, and increased theta and delta in spontaneous EEG, (b) hyperexcitability of motor cortices as shown by transcortical magnetic stimulation, (c) hyperexcitability of visual sensory cortex as indicated by increased SEO theta responses, (d) lower delta ERO, (e) lower delta, theta, and alpha event-related coherence, (f) higher theta synchrony and higher alpha event-related coherence in cholinergically treated AD subjects. In further research in the search for biomarkers, multimodal methods should be introduced to for validation pur- poses. Also, providing the protocols for standardization and harmonization of user-friendly acquisition or analysis methods that would be applied in larger cohort populations should be used to incorporate these electrophysiologic methods into the clinical criteria. In an extension to conventional anatomical, biochemical and brain imaging biomarkers, the use of neurophysiologic markers may lead to new applications for functional interpretrations and also the possibility to monitor treatments tailored for individuals.

*Correspondence to: Dr. Go¨ rsev G. Yener, M.D., Ph.D., Department of Neurology, Dokuz Eylu¨ l University Medical School, Balc¸ova, Izmir 35340, Turkey. Tel.: þ90 232 412 4050; Fax: þ90 232 277 7721; E-mail: [email protected] 344

KEYWORDS Biomarker; Brain oscillation; Alzheimer’s disease; Bipolar disorder; Schizophrenia; Attention deficit hyperactivity disorder; Event-related; Alpha; Beta; Theta; Gamma; Delta

20.1. Introductory remarks very valuable to develop a low-cost, user-friendly biomarker that can be applied widely to many neu- Publications on cognitive processes by means ropsychiatric disorders. of brain oscillations have increased within the The brain does not respond in a homogenous and literature in the past 20–30 years. standard manner to stimulations. The responses are However, there are relatively few studies related highly dependent on topology, age, states, and to cognitive impairment within the literature, dat- pathology. The spontaneous electroencephalo- ing only from the beginning of the last decade. graphic oscillations, evoked oscillations, event- Accordingly, the trend to use “biomarkers” is rel- related oscillations (EROs) and event-related atively recent. coherences are selectively distributed. Accordingly, The official US National Institutes of Health’s the organizers suggested that new, reliable hypoth- definition of a biomarker is: “a characteristic that eses and biomarkers could be pronounced only after is objectively measured and evaluated as an indi- performing or surveying a wide spectrum of mea- cator of normal biological or pathogenic processes, surements, as described in the following section. or pharmacologic responses to a therapeutic inter- vention.” Biomarkers can provide an objective basis for diagnosis, treatment selection, and out- 20.1.1. Cardinal view on multiple analysis of brain come measures (Fig. 1; Wright et al., 2009). oscillations A conference/workshop related to brain oscilla- tion in neuropsychiatric diseases took place in Istan- It is necessary to emphasize that there are impor- bul in May 2011 as a first conference during which tant functional differences between spontaneous diseases such as Alzheimer’s disease (AD), mild electroencephalography (EEG), sensory evoked cognitive impairment (MCI), schizophrenia (SZ), oscillations (SEOs), and EROs. In the analysis of bipolar disorders (BD), attention deficit hyperactiv- spontaneous EEG, only sporadically changes of ity disorder (ADHD) and their neurophysiologic amplitudes from hidden sources are measured. strategy modalities were jointly referenced and dis- SEOs reflect the property of sensory networks acti- cussed. The present interactive survey is mostly vated by a sensory stimulation. Event-related (or based on the results and closing panel discussion cognitive) oscillations manifest modification of sen- of this conference. It also covers part of discussions, sory and cognitive networks, both triggered by a advice or remarks of lecturers, and important hints cognitive task (Fig. 2). from papers of the present Supplement 62 and also An important brain mechanism underlying cog- relevant knowledge from previous publications. nitive processes is the exchange of information During the panel discussion, Claudio Babiloni between brain areas. The oscillatory analyses of gave an extended and useful synopsis of discus- isolated brain areas are important ( Bas¸ar et al., sions, and Giovanni Frisoni gave important hints 1999), but not sufficient to explain all aspects of and described goals for establishing brain oscilla- information processing within the brain. There- tions as biomarkers in neuropsychiatric disorders fore, in addition to local changes in brain dynam- based on his experience of MRI techniques. Paolo ics, dynamics of connectivity between different M. Rossini stated that in the next 10 years it will be brain areas must be investigated for a description 345

AT-RISK SUBJECTS ASYMPTOMATIC SUBJECTS SYMPTOMATIC SUBJECTS

NO DISEASE ASYMPTOMATIC DISEASE CLINICAL SYMPTOMS

PREVENTION OF RISK EARLY DETECTION & TREATMENT TAILORING TREATMENT

BIOMARKER FOR BIOMARKER FOR BIOMARKER FOR RISK FACTORS SCREENING PROGNOSIS AND TREATMENT MONITORING

Fig. 1. Biomarkers are useful for detecting the risk factors, screening, or treatment monitoring. (Modified from Wright et al., 2009.)

Brain oscillations (delta, theta, alpha, beta, gamma frequency ranges)

Spontaneous EEG Evoked and event-related oscillations

From hidden sources Sensory response Cognitive response

(Spontaneous coherence) (Sensory coherence) (Event-related coherence)

Fig. 2. A schematic presentation of differentiation in brain oscillations. of neurophysiological mechanisms underlying In resting EEG analysis, only sporadically occur- cognitive deficits of neuropsychiatric diseases. ring coherences from hidden sources are mea- Coherence is the synchrony between neuronal sured. Sensory evoked coherences reflect the activities in different parts of the brain. According degree of connectivity (links) between sensory to Bullock et al. (2003), increased coherence networks activated only by a sensory stimulation. between two structures, namely A and B, can be Event-related (or cognitive) coherences manifest caused by the following processes: (1) structures coherent activity of sensory and cognitive net- A and B are driven by the same generator; (2) works triggered by a cognitive task. Accordingly, structures A and B can mutually drive each other; the cognitive response coherences comprehend (3) one of the structures, A or B, drives the other. activation of a greater number of neural networks 346 that are most likely not activated or less activated also possible that neural groups are not separated in the EEG and pure sensory evoked coherences. into different structures but co-exist also in given Therefore, event-related coherences and ERO structures. These are selectively distributed neu- merit special attention in patients with cognitive ron clusters capable of responding to sensory/cog- impairment. In particular, in AD patients with nitive inputs. It is also expected that following strong cognitive impairment, it is relevant to ana- sensory stimulation, cognitive neural clusters lyze whether medical treatment (drug application) would remain silent, whereas a cognitive selectively acts upon sensory and cognitive net- (i.e., target signal in ) would works manifested in topologically different places excite both sensory and cognitive neural clusters. and in different frequency windows. Such an Certainly in the case of cognitive impairment, cog- observation may serve in future to provide a nitive neural clusters would be more affected, in deeper physiological understanding of distributed turn, giving rise to less unclear responses. More- functional networks and, in turn, the possibility of over, reduced response amplitude can result from determination of markers for medical treatment. either non-responding neural units or non-phase- Fig. 3 presents a schema for connectivity underly- locked response activity. ing sensory evoked coherence responses following Fig. 3 illustrates only one local area. However, simple sensory stimuli and event-related coher- isolated brain networks can explain only a limited ence responses following a cognitive task. It is activity. In addition to these local activities, it is not possible to define clear-cut boundaries for important to emphasize the selective connectivity these neural groups that are differentiated upon between neural elements of these networks and, application of sensory stimulation or upon cogni- more important, differential connectivity between tive stimulation. This schema indicates that there distant areas of the brain (e.g., frontal, limbic, and are neural populations, mostly responding to sen- parietal connections) (Fig. 4). In the case of AD, sory signals, and other populations responding to the number of neural clusters responding to cogni- only cognitive stimulation. Further, there is some tive stimulus is greatly reduced. Additionally, we overlap or plasticity among these networks. It is observe a selective connectivity deficit between

Event-relative (cognitive) connections

Sensory-evoked connections

Cognitive structures

Sensory structures

Fig. 3. Neural assemblies involved in sensory and cognitive networks. Cognitive networks (here shown by magenta lines) probably contain sensory neural elements, but also involve additional neural assemblies, as shown by magenta circles. Sensory network elements are illustrated by blue squares and connections by blue lines. It is expected that sen- sory signals trigger activation of sensory areas, whereas cognitive stimulation would evoke both neural groups reacting to sensory and cognitive inputs. 347

with neurotransmitter abnormalities; therefore, if we can construct multi-dimensional profiles and link them with underlying neurotransmitter abnormalities, we can develop individualized treatments. During this interactive discussion, three main questions were discussed.

20.2.1. Question 1: After discussing the electrophysiological details of schizophrenia, AD, BDs, MCI, ADHD, etc., can we develop an Fig. 4. Web of sensory and cognitive networks between ensemble of biomarkers for these disorders, and distant neural networks. what should we be doing to translate those valuable methods into clinical practice? distant neural networks (see Gu¨ntekin et al., 2008; Giovanni Frisoni stated that “the case of Bas¸ar et al., 2010). Alzheimer’s disease (AD) is particularly favorable to develop neurophysiologic markers, because we 20.2. Interactive panel discussion, chaired by have a reasonable hypothesis for the causes.” Go¨ rsev G. Yener and Erol Bas¸ar Current biomarkers have various degrees of validation — a dynamic process that is ongoing. The following section summarizes the interactive Therefore, it is possible to develop neurophysio- panel discussion. logical markers, using the already validated Dean Salisbury stated that psychologists build markers as a proof of convergent validity for diag- models in order to understand complex behaviors. nosis or for disease progression. Future research However, the model must be biologically realistic. on neurophysiological biomarkers should there- Working with patients, neuroscientists look for fore start from the current position, with an exis- abnormalities in the biological system; we there- ting framework and biomarkers against which to fore learn to constrain the model, based on these validate new markers. abnormalities. This provides a greater understand- Markers that were discussed are for diagnosis — ing of how our complex cognition is represented in structural, metabolic, or CSF changes. However, the real brain. However, when we consider the clin- one may also need markers to track disease pro- ical aspects in terms of potential benefits for gression, to check whether a drug is effective. patients, or discuss biomarkers, we need to differ- Some markers may be used for diagnostic and also entiate between the larger class, which are state- tracking purposes, but others may not change dependent and may index a change or current much over time, and so are poor markers to track functioning, and endophenotypes, which are trait disease progression (Fig. 1 and Table 1). related. In future, we aim to define complex endo- AD is more favorable to develop electrophysio- phenotypes using a multi-dimensional approach logical biomarkers. Different degrees of validation across the diagnostic categories; such a multivari- occur for these biomarkers. Structural, metabolic, ateanalysisofpatternsofEROandERPswould and CSF markers (i.e., static) are already available allow classification of different sub-categories for AD. Further, dynamic markers are important within neuropsychiatric disorders. That is the link for tracking or progression of disease or monitoring 348

TABLE 1

BIOLOGICAL MARKERS USED IN ALZHEIMER’S DISEASE AND/OR MILD COGNITIVE IMPAIRMENT, AND THEIR USAGE OR ADVANTAGES

AD markers For diagnosis For progression For drug effects Non-invasiveness Low cost

Amyloid PET þ þ FDG-PET þþ þ þ CSF þ Structural MRI þþ þ Electrophysiology þþ þ þ þ

AD: Alzheimer’s disease; FDG-PET: fluoro deoxy glucose positron emission tomography; CSF: cerebrospinal fluid; MRI: magnetic imaging.

drug effects, since disease-modifying drugs are (a) for diagnosis of a specific disease; being widely studied in AD. In AD, Michael (b) for tracking the disease; Weiner has launched a major project called the (c) for differential diagnosis; Alzheimer’s disease initiative (d) for monitoring effects of medication following (ADNI), to follow patients with cognitive distur- therapy; bances over time (every 6 months, 5 years to date), (e) for allowing therapeutic intervention at the including a number of biomarkers (biological and presymptomatic stage; imaging) (Weiner et al., 2012). The ADNI project (f) for detecting endophenotypes that are trait- has clarified much about the progression of the dis- related; ease. The most obvious proposal would be to add (g) studying at-risk populations to develop an neurophysiological markers and study how they early intervention; change with time and to what extent they agree with (h) identifying subtypes. the other markers (Karow et al., 2010; Polikar et al., 2010; Walhovd et al., 2010; Jack et al., 2011). Many years ago, the biomarker field of AD was similar to 20.2.2. Biomarkers in schizophrenia that of schizophrenia. Table 1 summarizes a few AD biomarkers. According to Ays¸egu¨ lO¨ zerdem, in psychiatry, we Michael Koch commented that biomarkers need biomarkers to differentiate between disor- could open a venue for very early therapeutic ders rather than clearly defining patients from intervention, including some neuropsychiatric dis- healthy controls. This is difficult, given the diag- eases, where the course of progression is not as nostic criteria we are using. However, it may help rapid as in AD or Parkinson’s disease. There is to investigate dimensions: studying schizophrenia widespread agreement that biomarkers must be or bipolar patients together to see how they differ reliable not only in differentiating diseases, but over time, for example, in terms of electrophysio- also in predicting the course of the disease, thereby logical parameters. Another approach for early allowing therapeutic intervention at the pre- diagnosis would be to study the at-risk population symptomatic stage. or their first-degree relatives, to track potential In summary, according to G. Frisoni, M. Koch, electrophysiological characteristics; next focus on D. Salisbury, and A. O¨ zerdem, biomarkers can this issue and associate it with clinical pathology; be classified based on specific functions: then follow up subsequent treatments (see 349

Onitsuka et al., this volume). According to Dan 20.2.2. Question 2: Can we learn about cognitive Mathalon, most of the psychiatric disorders, whose impairments after application just by knowing pathophysiology we still do not know well, have a some dynamic factors that are influenced by the neurodevelopmental basis meaning that we know disease and by looking at the disease itself; can we that things are not normal even before the full devel- learn about these disorders? opment of the disorder is evident. Therefore, bio- markers would allow us to detect risk and to Investigating the pathophysiology of neuropsychi- develop strategies for early intervention, because atric diseases by means of brain oscillations can some intervention strategies may not be effective lead to an understanding of how the brain can be later, beyond this early window of opportunity. so disorganized that it results in this complex system Go¨rsev G. Yener commented on these argum- of symptoms. For many researchers, this could be a ents as follows: “In schizophrenia or mild cognitive more interesting topic than their potential use as impairment (MCI), we may see subtle neurophysio- biomarker as commented by Judith Ford. logical changes or symptoms in the early sub-clinical The following section summarizes the analysis era. The real challenge will be developing electro- presented by Claudio Babiloni during the discus- physiological methods that are inexpensive, non- sion on standardization, harmonization, and contin- invasive and user-friendly. This might help to screen uous dialogue with clinicians which is the new wider populations and to prevent AD progression at frontier for our field. My work and that of several the earliest possible stage. The epidemiological others is to follow the ADNI data collection stan- results indicate that the expansion of AD worldwide dards and to have a common language to organize is increasing every year, and a delay of several years and analyze the data; to link EEG oscillations in in the development of AD would refuse the cost.” resting state in AD with respect to biomarkers, According to G. Frisoni, there is a lack of a according to the most advanced standards by biomarker for the diagnosis of schizophrenia, as it ADNI. is now based on the clinical criteria of the Diagnostic Cognitive neuroscience studies: attention and and Statistical Manual of Mental Disorders (DSM- many other cognitive functions. The field now IV, American Psychiatric Association, 2000). regards the cognitive functions in a refined way Previously, we knew very little about AD, except that focuses on sub-functions and work is ongo- that there were “dementias”; this is gradually broken ing to relate our EEG oscillations to this modern down into more detailed classifications,that mayalso view of our , etc. We have a very be a useful approach in schizophrenia. For example powerful approach to capture the transmission a diagnostic marker to differentiate between of information within the brain at several sites schizophrenia sub-types is needed in that case. according to several oscillatory codes. Transla- Even though BD and schizophrenia are consid- tional studies to align our various EEG markers ered as separate neuropsychiatric entities, they with the concept of markers in the different share several common susceptibility genes and fields of neurological pathologies are extremely overlap in the confirmed linkages (Onitsuka important. Further, if we are able to go beyond et al., in this volume). Altered the limitations of EEG, like low spatial resolu- and can be an index of cognitive tion, we can precisely localize the networks used dysfunction. Studies reported larger neural oscilla- for these oscillations, such as theta networks, tions and increased phase-locking in BD than because there are probably specific networks using healthy controls or schizophrenia. Schizophrenia specific codes or combinations of codes. So we subjects exhibited delayed neural oscillations need neuroimaging to capture, with higher spatial and decreased phase-locking compared with resolution, the cortical and subcortical networks healthy controls. in the brain, and studies with transition models 350 to capture and validate oscillatory phenomena. already been made to base diagnosis and sub- Therefore, a multimodal approach to the study of typing solely on quantified EEG patterns, but clinical and cognitive neuroscience is crucial. An the results were disappointing. Therefore, any pro- important contribution of this conference is to posed approach must be multimodal, but there are demonstrate the progress of several innovative difficulties in reaching agreement. To be practical, multimodal studies (Rossini and Ferreri, this vol- it must be relatively inexpensive, so the use of ume). These multimodal approaches include fMRI or MRI in all cases is questionable; imaging Professor Rossini’s transcortical magnetic stimula- technologies would be used in AD cases, but prac- tion and EEG studies, structural connectivity stud- tical implementation must consider any method’s ies and EEG prepulse inhibition as a model of link inherent financial costs. between brain and peripheral nervous system, and According to Giovanni Frisoni, the progress of neurovegetative response to the brain as described the AD research resulted from the effort to orga- by Bas ¸ar et al. (2010). nize researchers from multiple sites to generate Babiloni does not view EEG alone: the purpose definitive data sets. That facilitated the discovery of his work is not simply collecting EEG data, but of patterns across different imaging modalities, is primarily to dialogue with others, providing to the extent that these patterns are now useful multimodal methods including neuropsychology for clinicians. There are other similar trends that on AD, rather than abstract theories. This is should be encouraged: there are initiatives to con- the real core of the ongoing multi-centerwork duct multi-site collection of schizophrenia data in on EEG to break into the AD frontier and clinically high-risk youths; as a result, large sam- research. ples are rapidly being generated. This addresses a long-standing problem in our field, where the literature is dominated by studies using small sam- 20.2.3. Question 3: Would it be possible to propose ples that fail to be replicated. This problem of rep- some common neurophysiologic grounds? What lication is compounded because our fields examine might be the methodological necessities? conditions that are inherently complex, abnormal, Harmonized spontaneous EEG and a standardized and heterogeneous. In the process of addressing approach to ERP and brain oscillations? this, we must change the process of science. It is not easy to agree on commonly applicable para- Robert Barry found that the proposal is good in digms, but some changes are occurring, where principle, but very difficult to implement in prac- researchers collect data that are beneficial for tice. According to him, it is difficult to find common- the wider research field. Such multi-site, large- alities between researchers investigating differing sample studies will be necessary in order to deliver issues. There may be potential benefits from basic results that are of use to clinicians. resting EEG, functional magnetic resonance imag- Robert Barry provided the following comments: ing (fMRI). However, if one asks what might be “Listening to the presentations, it seems we are an appropriate paradigm, these paradigms each ignoring the state of the patients when they come have different efficiencies in different disorders. to be assessed. Some of the differences in alpha that Therefore, there would be limited efficiency bene- were presented may relate to the fact that patients fits from all researchers attempting to collect data may be highly anxious for a diagnosis or treatment. on everything. So some of the results we are observing are related According to Dean Salisbury, we cannot simply to anxiety, not the disease itself. We should be con- rely on resting EEG. In psychiatry, attempts have sidering universally applicable methods that would 351 screen out some of those issues and lead to more functional coupling of EEG rhythms between cor- robust results. One simple and cheap add-on might tical populations (“functional connectivity”) as a be the use of skin conductors, which showed hugedif- mode to gate the transfer of signals/information ferences between patients and controls in ADHD.” across neural circuits. Evaluation of resting state brain rhythms 20.3. Open discussion enlightens physiological and pathological aging and global cognitive status of the subjects. On 20.3.1. Summary by Claudio Babiloni the one hand, it has been shown that particular resting state alpha rhythms (about 8–10 Hz) are Some speakers presented an intriguing view of the reduced in amplitude in association with brain brain rhythms in the resting state condition. This atrophy and global cognitive status in subjects with condition can be conceptualized as a spontaneous MCI and AD. In the same vein, pathological delta fluctuation in brain along the time axis. rhythms (1–4 Hz) increase as a function of the dis- This apparently simple state of the brain is very ease, at least at group level. The power reduction rich in information about, and the mechanisms of the alpha rhythms along the disease progression of, neural synchronization and coordination within would be slowed by cholinesterase inhibitors cortico-cortical and subcortical–cortical circuits (Donepezil) in AD patients responding to long- modulating the brain arousal time by time. The term therapy of 12 months, suggesting some rela- speakers have shown that specific brain dynamics tionship among resting state alpha rhythms, aging, of the resting stage, the “default” state, express a and integrity of the cholinergic sort of inhibition in the processing of stimuli com- systems. Of note, intriguing analogies between ing from the external world and form a crucial bias AD and major depression are suggested by the in the subsequent response of the brain to external finding of reduced resting state alpha rhythms in stimuli. For example, the specific phase of the patients with depression during asymptomatic brain oscillatory activity in the prestimulus period periods. On the other hand, it has been shown that, can affect the timing of the brain response to a in AD patients, the power of delta rhythms is given external stimulus, the selective involvement abnormal not only in the resting state, but also of the neural networks, and the relative ability of in response to “oddball” target stimuli as a func- these networks to process information in order tion of the treatment with cholinesterase inhibitors to represent events/operative states, and (Yener et al., 2007). Impaired processing of the . “oddball” target stimuli would also be related to It has also been confirmed that brain rhythms at an abnormal coupling of the EEG oscillations particular alpha (about 8–10 Hz) are from delta to alpha frequencies. This is a promis- related to arousal and are modulated in amplitude ing neurophysiological approach to the explora- by caffeine. In the resting state, other brain fre- tion of brain function in developmental age, quencies are able to be associated with the global physiological, and pathological aging, as well as personality of children in the development of psychiatric disorders. state; these preliminary results need to be con- firmed. However, this is a positive indication that several people with different personalities and 20.3.2. Schizophrenia methods of processing information are character- ized by particular features of the neural synchroni- In the workgroup on schizophrenia, several zation in the brain, together with a different speakers reviewed the state of the art in relation 352 to the neurophysiological basis of the generation manipulation, with only slight relationships with of brain gamma (<35 Hz) rhythms. A key role the subjects’ mental state, in agreement with the would be played by fine neural circuits modulated idea that schizophrenia cannot be captured by sim- by agonists and antagonists (i.e., ketamine) of glu- ple pharmacological “challenge” models. How- tamate neurotransmission and NMDA receptors. ever, the general methodological approach based Interesting original evidence has been presented on surrogate EEG endpoints seems to be quite in both human and animal models. promising for drug discovery in schizophrenia. Some interesting evidence has been presented about the relationship between atrophy of the temporal lobe and abnormal EEG oscillations in 20.3.4. Hyperconnectivity oddball paradigms in schizophrenic patients, although some open issues and contrasting results One of the most interesting findings of the schizo- suggest that the variability of the disease endo- phrenia session concerned “hyperconnectivity.” phenotypes may prevent the definition of a com- One of the speakers showed that schizophrenic mon picture about the particular abnormalities patients were characterized by “paradoxical” of the brain synchronization mechanisms in occipital EEG oscillatory responses to auditory schizophrenia. In this regard, the relationship “oddball” targets in two different experiments between features of EEG rhythms and genotyping (Bas¸ ar-Erog˘lu et al., 2011). This is further evident merits specific discussion. Some speakers have that schizophrenia patients can display shown EEG procedures to unveil the relationships maladapted hyper-connectivity; it has been specu- between specific endophenotypes, EEG oscilla- lated that, in these patients, abnormal auditory tory activity, and the progression of schizophrenia. information is distributed and triggers excitation Specifically, there would be some invariant indi- in the occipital visual cortex, possibly producing vidual features of gamma rhythms along the pro- abnormal visual imagery or visual processing. This gression of schizophrenia from the first episode intriguing working hypothesis will need to be onward, and these features appear to be common tested with control experiments in schizophrenic to people of the same family, in terms of determin- patients to evaluate possible relationships ing whether they depend on genetics. This is prom- between the “paradoxical” occipital EEG oscilla- ising for a future classification of patients with tory responses to auditory “oddball” targets different forms of the disease, possibly in relation and structural neuroimaging indexes (i.e., to genetic features. tractography, diffusion tensor imaging).

20.3.3. EEG markers in schizophrenia 20.3.5. Neurotransmitters

Another important input from the schizophrenia The symposium also addressed a new frontier for workgroup was the evaluation of candidate the study of EEG oscillations and neurotrans- EEG markers for schizophrenia (resting state, mitters, namely EEG investigations of BDs. In “oddball,” etc.) in young healthy subjects who this regard, the first preliminary results were underwent to a reversible and innocuous pharma- presented on brain oscillations and major cological procedure to induce some mental states depression. ERO and coherence studies in AD resembling positive schizophrenia symptoms. also showed decreased delta and theta responses The results showed that such a procedure is not and widely diminished cortico-cortical coher- able to induce, “tout court,” the typical EEG pic- ences in alpha, theta, and delta ranges. Among ture of schizophrenia. Only a minority of EEG those parameters, frontal theta phase-locking markers was affected by the experimental and alpha fronto-parietal coherence values were 353 sensitive to medication effects, as reported by have a great tool available, but the cross-talk with Yener and Bas¸ar (2010) and Gu¨ ntekin et al. clinicians is crucial to understand how to apply this (2008). An intense discussion was developed tool. For most clinicians, the neuroscience vocab- about how EEG may help identify the relation- ulary is challenging and, previously, waveforms ship between the neural synchronization mecha- were difficult for physicians to interpret. The great nisms at the basis of transfer of information expansion of neuroimaging within the last year between areas and mood regulation as reflected allows the function to be plotted onto the by the generation of EEG oscillations. anatomy, making it more recognizable for clini- cians. It requires effort from all parties to use the appropriate language to communicate with 20.3.6. General conclusion each other. In AD, the great initiatives are large and multinational. This group should be expanded A general conclusion was that the EEG community to mirror such approaches; if neurophysiology must continue to inform the discussion with clini- enters that mainstream, it could contribute enor- cians about the kind of evidence required to test mously to the understanding of the disease and the particular contribution of EEG oscillatory to patient treatment.” markers for early diagnosis and prognosis, individu- alized management, therapy monitoring, and drug discovery in psychiatric and dementia patients. 20.4. Candidate electrophysiological biomarkers Besides, understanding the brain plasticity and its for several neuropsychiatric disorders underlying functional and structural components hasbeenchallengedbynewneurophysiological 20.4.1. Attention deficit hyperactivity disorder techniques within the past 10 years as summarized (ADHD) by Rossini and Ferreri (this volume). There is a need for a deeper dialogue with cognitive neurosci- ADHD is a condition in which a person (usually a entists using fMRI and transcranial magnetic child) has an unusually high activity level and a stimulation in order to investigate the correlation short attention span. People with the disorder between EEG oscillations and fine brain topogra- may act impulsively and may have learning and phy of hemodynamic responses and excitatory/ behavioral problems. Several reports consistently inhibitory neurotransmitter systems. Furthermore, reported increased gamma oscillatory responses a deeper dialogue is necessary with cognitive (Perez et al., Taylor et al., Yordanova et al., all psychologists involved in the fine modeling of sub- in this volume) and elevation of delta and theta types of attention (i.e., endogenous, reflexive, exog- along with diminished alpha and beta responses enous, orienting, etc.) and memory (i.e., procedural, in spontaneous (resting) EEG (Monastra et al., episodic, semantic), to evolve the experimental 2001; Barry et al., 2003). One of the difficulties designs to be used in our EEG studies. The future with ADHD is a tendency for over-diagnosis. role of EEG oscillations in clinical and cognitive Barry and Clarke (in this volume) suggest the neuroscience depends on this dialogue. The same theta:beta ratio as a potential biomarker for is true for the future of clinical and cognitive ADHD. As they state, it seems to be sensitive to neuroscience itself. Indeed, EEG oscillations are medication, as improved symptoms following the main emerging property of the resting state medication are linked to a reduction in the and working brain. The pathway is still long but theta:beta ratio. An updated general model of quite exciting. coherence anomalies in ADHD children, based After Claudio Babiloni’s summary, Giovanni on Barry and Clarke (this volume), also indicates Frisoni stated that “as a physician, my feeling is a wide range of regional connectivity anomalies in that neuroscientists working on brain oscillations this disorder. 354

20.4.2. Schizophrenia volume), alterations of ASSRs in schizophrenia, schizotypal personality disorder, and first-degree Schizophrenia is a psychotic disorder (or a group relatives of patients with schizophrenia were of disorders) marked by severely impaired think- reported. ASSRs are usually reduced in power ing, emotions, and behaviors. Increased dopami- or phase-locking in patients with schizophrenia nergic activity in the mesolimbic pathway of the following 40-Hz stimulation. Possibly, delayed brain is a consistent finding. The mainstay of treat- phase synchronization and reduction in 40-Hz ment is pharmacotherapy with antipsychotic med- power in schizophrenia could be also considered ications; these primarily work by suppressing as biomarkers. dopamine activity. Previously, Mathalon’s and Ford’s groups Gamma activity induced in response to task- showed that the early evoked gamma band relevant and irrelevant auditory oddball stimuli response to tones is poorly synchronized in schizo- in medicated schizophrenics showed a significant phrenia (Roach and Mathalon, 2008), which is decrease in comparison to controls (Haig et al., consistent with other reports of abnormalities in 2000). Later other reports confirmed the reduced the early auditory gamma oscillatory responses gamma (Wynn et al., 2005; Bas¸ar-Erog˘lu et al., in chronic schizophrenia patients (for a review, 2007; Spencer et al., 2008) independent of medica- see Gandal et al., 2012). Gamma responses of tion (Minzenberg et al., 2010), and also reduction young schizophrenia patients show decreased in delta, theta, and alpha frequency bands (Bas¸ ar- evoked power (Perez et al., this volume) and Erog˘lu et al., 2009) in schizophrenia patients. diminished phase-locking of gamma responses Bas¸ ar-Erog˘lu et al. (2011) indicated an over- (Roach et al., this volume). excitability of neuronal networks in schizophrenia According to Taylor et al. (this volume), it as shown by their findings showing elevated seems likely that the early auditory gamma band gamma responses at both anterior and occipital responses would be reduced in schizophrenia. sites to auditory stimuli. They also showed a less Roach and Mathalon (2008) suggested that - prominent anterior alpha response to simple sen- let parameters might play a role in the detection of sory auditory input, which probably indicates less group differences and reported reduced phase- efficient processing, similar to reduced alpha locking of early auditory gamma band responses responses for non-target stimuli in oddball para- in this disorder. digm in schizophrenia subjects (see Bas¸ar Erog˘lu The relationship between long-range fronto- et al., this volume) posterior connectivity and local brain activity in Herrmann and Demiralp (2005) reviewed the the frontal and posterior areas is investigated by literature on the alterations of gamma oscillations Sharma et al. (this volume). They show that abnor- (between 30 and 80 Hz) during the course of mal functional connectivity in the fronto-posterior neuropsychiatric disorders and based on a study brain network in schizophrenia is not necessarily by Lee et al. (2003). They suggested that in schizo- characterized by a global reduction of connectivity, phrenic patients, negative symptoms correlate but can either be increased (during rest) or with a decrease in gamma responses, whereas a decreased (during cognitive control), depending significant increase in gamma amplitudes is on the stage of the task. The sensory and frontal observed during positive symptoms such as areas of schizophrenia patients showed reduced hallucinations. evoked activity and the posterior association cortex Auditory steady-state response (ASSR) power during later target evaluation and perceptual pro- and phase-locking to gamma range stimulation cesses are more strongly reduced in schizophrenia. were found to be reduced in patients with schizo- Fronto-posterior coherence was reduced in phrenia. In a review by O’Donnell et al. (this patients as early as 100 ms. These results indicate 355 that connectivity disturbances may be a more fun- The results presented by O¨ zerdem et al. (in this damental deficit in schizophrenia and may mani- volume) and by Bas¸ar et al. (2011) suggest that the fest very early during cognitive control. This may crucial decrease of alpha power, the increase of also have an implication for the later local evoked beta activity, the high reduction of long distance activity, where connectivity impairments that visual event-related gamma coherence in manifested earlier could drive impairments in euthymic BD patients are candidate biomarkers the later local activity. in this disease. Hall et al. (2011) examined whether or not gamma band oscillations constitute endo- 20.4.3. Bipolar disorders phenotypes of BD by testing BD patients, mono- zygotic BD twins, unaffected relatives, and BD is not a single disorder, but a category of mood healthy subjects using the auditory oddball task. disorders defined by the presence of one or more Patients with BD exhibited reduced gamma band episodes of abnormally elevated mood, clinically power, whereas these changes were not observed referred to as mania. Individuals who experience in clinically unaffected relatives. Therefore, these manic episodes also commonly experience depres- responses do not appear to be an eligible criterion sive episodes or symptoms, or mixed episodes for endophenotypes of BD (Hall et al., 2011). which present the features of both mania and Oribe et al. (2010) investigated evoked neural depression (Bowden, 2007). The event-related oscillations at 20–45 Hz and found that subjects oscillatory responses in various types of BDs and with BD exhibited greater power in evoked neural their response to valproate were investigated by oscillations in response to speech sounds com- O ¨ zerdem et al. (2008a,b, 2010). In their reports pared to healthy subjects and schizophrenia sub- in 2008a, investigating bipolar manic and jects; and schizophrenia patients exhibited medication-free patients, they reported signifi- delayed evoked neural oscillation peak- and cantly higher occipital beta and lower occipito- phase-locking to speech sounds. Their study frontal alpha EROs than healthy controls. After implied that the evoked neural oscillation to treatment with valproate, alpha ERO responses speech sounds provided a useful index to distin- in BD patients were significantly lower. rBas¸a guish BD from schizophrenia (Onitsuka et al., in et al. (2011) reported the decrease of alpha fre- this volume). quency band both in spontaneous EEG and sen- sory evoked oscillatory responses. This group concluded that alpha response is the universal operator in the brain. Increased occipital beta 20.4.4. Alzheimer’s disease response in mania may be compensatory to the dysfunctional alpha operation. Its reduction after AD is the most common form of dementia, a neu- valproate may be through modulation of gluta- rological disease characterized by loss of mental matergic and GABAergic mechanisms. Their ability severe enough to interfere with normal study on the effects of valproate euthymic and daily activities of living. In the normal aging, a medication-free bipolar patients showed a dimin- reduction in total brain volume is seen; the reduc- ished delta responses ( O¨ zerdem et al., 2008b). tion in the cortical gray matter volume in AD is Later reports by the same research group have more severe than in healthy controls and ranges indicated decreased event-related gamma coher- between 8% and 9% and hippocampal loss is ence both in euthymic BD (O ¨ zerdem et al., 8%, and olfactory/orbitofrontal cortex shows 12– 2011) and manic BD (O ¨ zerdem et al., 2010)as 15% loss. The pattern of cortical atrophy in mild another possible candidate of biomarker. AD is similar to that in prodromal AD, but the loss 356 is more severe in the direct hippocampal pathway improve in AD subjects with cholinergic treat- and sensorimotor, visual, and temporal cortices ment. The most sensible ERO parameters seem (Prestia et al., this volume). These morphometric to be delta and theta oscillatory responses over changes are reflected in many electrophysiological fronto-central regions, and fronto-parietal coher- measurements. In resting EEG studies (Babiloni ences in alpha, theta, and delta frequencies et al., 2011; for a review, see Lizio et al., 2011), (Bas¸ ar et al., 2010; Yener and Bas¸ar, Ch. 16, this when healthy controls, MCI, and AD subjects volume). When electrophysiological markers are were classified according to spectral EEG coher- used in combination with structural MRI, SPECT, ence and other EEG features, the successful dis- and PET markers, a comprehensive data fusion crimination rates of controls from mild AD were analysis may provide a more accurate analysis as 89–45%, from MCI to AD 92–78%, and the taking into account important variables such as conversion of MCI subjects to AD 87–60%. The validity, costs, invasiveness, and availability of most sensible parameters of resting state EEG the procedures in the epidemiological studies were cortical delta/theta and alpha rhythms, (Vecchio et al., this volume). fronto-parietal coherence and computation of A chart summarizing the possible biomarkers the directed transfer function that were abnormal and related neurotransmitters in mentioned in amnesic MCI and AD subjects (Vecchio et al., neuropsychiatric disorders has been shown in this volume). Fig. 5. Event-related oscillations have also shown that mild AD subjects differ from healthy controls. Polikar et al. (2007) used ERO frequency bands 20.4.5. Polymorphism to classify AD and healthy controls by means of an automated program. They found oscillatory The works of Porjesz et al. (2005) and of responses of 1–2 and 2–4 at Pz, and 4–8 Hz at Fz Rangaswamy and Porjesz (2008), related to AD , and 2–4 Hz at Cz were the most valuable classi- and a cholinergic receptor gene (CHRM2), are fiers for AD subjects from healthy controls. By important, since their findings suggest the possible means of these four parameters, they reported a role of CHRM2 in the generation and modulation sensitivity rate of 77% and a specificity rate of of evoked oscillations. Theta and delta EROs 81%. Later studies reported a consistent decrease depend on the level of (muscarinic in fronto-central delta responses upon either activation). M2 receptors inhibit presynaptic visual (Yener et al., 2008) or auditory oddball release of acetylcholine, leading to inhibition of stimulation (Caravaglios et al., 2008; Yener irrelevant networks. Muscarinic receptors are par- et al., 2012). Frontal theta responsiveness has been ticularly concentrated in the forebrain and possibly also reported, either following visual (Yener et al., serve to maintain the effective balance of relevant/ 2007) or auditory oddball (Caravaglios et al., 2010) irrelevant networks, hence, directly influencing paradigm. In their study, Caravaglios et al. (2010) generation (Frodl-Bauch et al., 1999). reported that a decreased theta responsiveness in a According to the work of the Porjesz group late time window later than poststimulus 250 ms. (Begleiter and Porjesz, 2006), the results with the Diminished event-related coherence values have CHRM2 gene and brain oscillations strongly been reported in AD in delta, theta, and alpha support the role of acetylcholine in the generation ranges in fronto-parietal connections. Regarding of (theta oscillations) and in the P300 the medication effects, the alpha event-related component (delta and theta oscillations). The func- coherence ( Gu¨ ntekin et al., 2008) and theta tion of acetylcholine has been demonstrated with phase-locking (Yener et al., 2007) seem to regard to stimulus significance (Perry et al., 1999), 357

UNMEDICATED MEDICATED PATIENT TRANSMITTER θ:β -Increased -Improved Dopamine and θ, δ and ratio in decreased α, β spontaneous ADHD noradrenaline in spontaneous EEG EEG

Low γ ERD in Decreased ERO unmedicated in γ and all other Dopamine and no change frequency bands Schizophrenia after medication (all subjects were medicated)

-Decreased γ ER -Decreased δ GABA coherence ERO after Bipolar Dopamine -Decreased valproate euthymic Glutamate alpha in ERO and in spontaneous EEG

-Lower α and -Lower α and β GABA higher β ERO ERO after Bipolar Dopamine -Decreased γ ER valproate manic Glutamate coherence

-Higher δ, θ and -Higher θ ERO α, β synchrony lower Acetylcholine (spontaneous -Higher α ER Alzheimer EEG) coherence than -Lower δ ERO unmedicated -Lower θ ERO synchrony –Lower α,θ,δ ER coherence

Fig. 5. The possible biomarkers and related neurotransmitters in several neuropsychiatric disorders. selective attention (Mitrofanis and Guillery, 1993), 20.5. Neurotransmitters and experimental studies and P300 generation (Callaway et al., 1983). Thus, genes are important for the expression of 20.5.1. Neurotransmitters the endophenotype (brain oscillations) and help in the identification of genes that increase the pro- It is important to remark that such neurotransmitter- pensity to develop alcohol dependence and related related agents are often used as medication in certain disorders (Begleiter and Porjesz, 2006). From the diseases. It was long thought that a given summary of the research publications of Begleiter released only one kind of neurotransmitter, but and Porjesz and their research teams, it can today many experiments have shown that a single be clearly stated that studies of neuroelectric neuron can produce several different neurotransmit- endophenotypes offer a powerful strategy for ters. Below, four of the best-known transmitters identifying the genes that can create susceptibility that are involved in functions in both the central to develop psychiatric disorders and provide novel and the peripheral nervous systems are described; insights into etiological factors. and neurotransmitters that play a role in major 358 neuropsychiatric disorders mentioned in this volume development of either mania or depression. It is are listed in Fig. 5. also important to note that GABAergic activity Acetylcholine is a widely distributed, excitatory is reciprocally regulated by dopamine, hyperactiv- neurotransmitter that triggers muscle contraction ity of which also plays a role in mania (Yatham and stimulates the excretion of certain hormones. et al., 2002). Alterations in the modulation of In the , it is involved in, for the dopamine system may trigger the appearance example, , attentiveness, anger, and of a defective GABA system (Benes and aggression. Berretta, 2001). It is important to emphasize is a neurotransmitter that is the web of theta activity on the GABAergic important for attentiveness, emotion, sleeping, and cholinergic inputs from the septum. In vivo dreaming, and learning. It is also released as a hor- studies suggest that the hippocampal theta mone into the blood, where it causes blood vessels rhythm depends on GABAergic and cholinergic to contract and the to increase. Norepi- inputs from the septum (Stewart and Fox, 1990; nephrine plays a role in mood disorders such as Brazhnik and Fox, 1997) and requires an intact manic depression. hippocampal CA3 region (Wiig et al., 1994). Dopamine is an inhibitory neurotransmitter The cholinergic inputs to the hippocampus are involved in controlling movement and posture. It distributed on both the pyramidal and interneu- also modulates mood and plays a central role in ronal cells (Frotscher and Le´ra´nth, 1985), while positive reinforcement and dependency. The loss the GABAergic inputs selectively contact the of dopamine in certain parts of the brain causes hippocampal (Freund and Antal, the muscle rigidity typically present in Parkinson’s 1988). Later work in vitro on septo-hippocampal disease. cocultures showed that CA3, but not CA1, GABA (gamma-aminobutyric acid) is an inhib- exhibited theta-like oscillations driven by septal itory neurotransmitter that is widely distributed in muscarinic synaptic inputs (Fischer et al., 1999). the of the cortex. GABA contributes to This suggests that the hippocampus is locally motor control, vision, and many other cortical capable of regulating the frequency of theta, functions. Some drugs that increase the level of independent of the septal inputs. Valproate was GABA in the brain are used to treat shown to augment the ability of atypical antipsy- and to calm the trembling of patients suffering chotic medications to increase dopamine (DA) from Huntington’s disease. GABAergic interneu- and acetylcholine (ACh) efflux in the rat hippo- rons, which are the core component of cortico- campus and medial prefrontal cortex (Huang limbic circuitry, were found to be defective in et al., 2006).Itwasalsoshowntoleadtoasignif- the of bipolar patients (Benes icant reduction in presynaptic dopamine function and Berretta, 2001). GABA spreads in neural net- in manic patients. works involved in cognitive and emotional GABAergic interneurons and pyramidal cells processing and modulates noradrenergic, dopami- were found to build and maintain complex inter- nergic, and serotonergic local neural circuitry connections, which lead to large-scale network (Brambilla et al., 2003). Several studies revealed oscillations, such as theta, gamma (40–100 Hz), low plasma (Kaiya et al., 1982; Berrettini et al., and ultrafast (200 Hz) frequency bands (Benes 1983) or cortical (Bhagwagar et al., 2007) GABA and Berretta, 2001). activity or altered genetic expression of GABA Glutamate is a major excitatory neurotransmit- (Guidotti et al., 2000) in BD. Low GABA activity ter that is associated with learning and memory was thought to be a genetically determined trait and is also thought to be associated with AD, whose creating a vulnerability which, with the contribu- first symptoms include memory malfunctions. tion of environmental factors, can lead to the Neurons that use GABA and glutamate as 359 neurotransmitters are used by more than 80% of schizophrenia patients, but the exact relationship the neurons in the brain and constitute the most between symptoms and reduced PPI is still important inhibition. unclear. Recent findings suggest that the levels of PPI in humans and animals may be predictive of certain cognitive functions. Hence, this simple measure of reflex suppression may be of use for 20.5.2. Animal models and neurotransmitters clinical research and the cannabinoid system will be one promising field of schizophrenia transla- The significance of 40-Hz activity in the of tional research. different mammals has been hypothesized by sev- eral authors (Freeman, 1975; Bas¸ar et al., 1987; 20.6. Essences of the conference: advantages and Eckhorn et al., 1988; Bas¸ar-Erog˘lu and Bas¸ar, efficiency of neurophysiological markers 1991; Kaiser et al., 2008; Lenz et al., 2008)asan important coding channel in processing sensory Following the standard definition, a “biomarker” and cognitive information in neural networks. should differentiate the subject with a certain neu- These results further indicate a widely ranging ropsychiatric disorder from the healthy subject, function of the gamma component among the dif- track the progress of the disorder, or monitor the ferent classes of vertebrates and invertebrates. effects of medication. In the present report, three Bullock and Bas¸ar (1988), Schu ¨ tt et al. (1992), fundamental questions arose in relation to the and Bas¸ar et al. (1999) also examined the effect principal theme of the utility of brain oscillations of transmitters such as acetylcholine, dopamine, as biomarkers. Questions and/or remarks of confer- noradrenalin, and on the isolated gang- ence participants are presented here in order to dis- lia of Helix pomatia (snail) and showed changes in play knowledge related to brain oscillations in the oscillatory dynamics of these ganglia. The different brain diseases. Giovanni Frisoni’s com- application of acetylcholine (ACh) induced a large ments related to the nature and evolution of bio- increase in the theta response in the isolated vis- markers in AD present important criteria for ceral ganglion. Dopamine induced a crucial successful development of electrophysiological bio- change in the oscillatory response, which was markers in addition to structural MRI and bio- recorded in the gamma frequency band following chemical CSF biomarkers. Claudio Babiloni’s the electrical stimulation in the Helix visceral discussion presents a concise overview of the state ganglion. of the art. According to Michael Koch (see in this volume), The advantages of electrophysiological bio- it seems that transmitters and animal models, and markers in comparison to other markers are as also the links between genetics, transmitters, and follows: oscillations, will be very important in the near (1) These methods are non-invasive. future. The challenge is to see whether a research (2) They are inexpensive. group is able to combine these three factors. Koch (3) Neurophysiological measurements enable the states that animal models and endophenotypes of description of brain dynamics. mental disorders are regarded as preclinical (4) These methods analyze a fast activity chain of approaches for understanding the underlying the brain in the range of 0–500 ms. mechanisms of these diseases, and in developing (5) The electrophysiological measurements open drug treatment strategies. A frequently used trans- the possibility to record processes of percep- lational model of sensorimotor gating and its def- tion, attention, decision making, and working icits in some neuropsychiatric disorders is prepulse memory. In other words, it is possible to learn inhibition (PPI) of startle. PPI is reduced in about dynamic brain function. 360

At this stage, it is vital to mention that applications discussed neuropsychiatric diseases, namely, of ensembles of electrophysiological recording ADHD, AD, BD, and schizophrenia. methods and strategies are important in the search We hope that the results of this conference for appropriate biomarkers (Fig. 6). According to will contribute to better translational research. the results in the present volume, both conceptual The most challenging topic would therefore and methodological types of strategies are needed be to develop user-friendly electrophysiological to identify biomarkers. The conceptual strategies methods and a common ground that would allow include (a) differentiation between evoked and discussion between clinicians, electrophysiologists, EROs as they possibly reflect the activities of sen- and other researchers. sory and cognitive networks, respectively; (b) differential connectivity deficit as shown by coher- ence measurements; (c) changes in spontaneous EEG activity; and (d) changes under medication Abbreviations influence. The present report also emphasizes the impor- Ab42 ¼ amyloid beta 42 peptide tance of the link between oscillations and AD ¼ Alzheimer’s disease neurotransmitters (Fig. 5). In this report, we also ADHD ¼ attention deficit hyperactivity disorder indicate the possibility that several findings ADNI ¼ Alzheimer’s disease neuroimaging described in this volume can be proposed as bio- initiative marker candidates. The search of biomarkers is cer- ASSR ¼ auditory steady-state responses tainly not limited to the results of the present issue, BACE ¼ beta-secretase and the reviews of O’Donnell et al., Vecchhio et al., BD ¼ bipolar disorder Yener and Bas¸ar, and Bas¸ar and Gu¨ntekin (all in CSF ¼ cerebrospinal fluid this volume) indicate several other possibilities. EEG ¼ electroencephalography The present volume, Supplements to Clinical ERO ¼ event-related oscillation Neurophysiology, Vol. 62, and the present panel ERP ¼ event-related potential report will likely be most useful in manifesting fMRI ¼ functional magnetic resonance imaging the new strong trend to develop biomarkers FDG-PET ¼ fluoro-deoxy glucose positron emis- related to brain oscillations in at least four sion tomography

THE STRATEGIES FOR ANALYSIS OF BRAIN ACTIVITY

Default brain Evoked brain activity activity

Event-related brain activity

Fig. 6. Analysis of brain includes combinations of default brain activity or evoked brain activity by simple sensory stimuli or event-related brain activity elicited by cognitive tasks. 361

HC ¼ healthy controls sustained attentional processing? Int. J. Psychophysiol.,71 MCI ¼ mild cognitive impairment (1): 75–83. ¼ Bas¸ar-Erog˘lu, C., Mathes, B., Brand, A. and Schmiedt-Fehr, C. MRI magnetic resonance imaging (2011) Occipital gamma response to auditory stimulation in PET ¼ positron emission tomography patients with schizophrenia. Int. J. Psychophysiol., 79(1): 3–8. PLF ¼ phase-locking factor Begleiter, H. and Porjesz, B. (2006) Genetics of ¼ oscillations. Int. J. Psychophysiol., 60(2): 162–171. P-tau phospho-tau protein Benes, F.M. and Berretta, S. (2001) GABAergic interneurons: SZ ¼ schizophrenia implications for understanding schizophrenia and bipolar SEO ¼ sensory evoked oscillation disorder. Neuropsychopharmacology, 25(1): 1–27. TMS ¼ transcranial magnetic stimulation Berrettini, W.H., Nurnberger, J.I., Jr., Hare, T.A., Simmons- Alling, S., Gershon, E.S. and Post, R.M. (1983) Reduced T-tau ¼ total tau protein plasma and CSF gamma-aminobutyric acid in affective illness: effect of lithium carbonate. Biol. Psychiatry, 18(2): 185–194. Bhagwagar, Z., Wylezinska, M., Jezzard, P., Evans, J., Ashworth, F., Sule, A., Matthews, P.M. and Cowen, P.J. (2007) Reduction in occipital cortex gamma-aminobutyric References acid concentrations in medication-free recovered unipolar depressed and bipolar subjects. Biol. Psychiatry, 61(6): 806–812. American Psychiatric Association (2000) Diagnostic and Statis- Bowden, C.L. (2007) Spectrum of effectiveness of valproate in tical Manual of Mental Health Disorders. American Psychiat- neuropsychiatry. Exp. Rev. Neurother., 7(1): 9–16. ric Association, Washington, DC, 980 pp. Brambilla, F., Biggio, G., Pisu, M.G., Bellodi, L., Perna, G., Babiloni, C., Vecchio, F., Lizio, R., Ferri, R., Rodriguez, G., Bogdanovich-Djukic, V., Purdy, R.H. and Serra, M. (2003) Marzano, N., Frisoni, G.B. and Rossini, P.M. (2011) Resting Neurosteroid secretion in panic disorder. Psychiatry Res., state cortical rhythms in mild cognitive impairment and 118(2): 107–116. Alzheimer’s disease: electroencephalographic evidence. Brazhnik, E.S. and Fox, S.E. (1997) Intracellular recordings J. Alzheimers Dis., 26(Suppl. 3): 201–214. from medial septal neurons during hippocampal theta Barry, R.J., Clarke, A.R. and Johnstone, S.J. (2003) A review of rhythm. Exp. Brain Res., 114(3): 442–453. electrophysiology in attention deficit/hyperactivity disorder. Bullock, T.H. and Bas¸ar, E. (1988) Comparison of ongoing I. Qualitative and quantitative electroencephalography. Clin. compound field potentials in the brain of invertebrates and Neurophysiol., 114: 171–183. vertebrates. Brain Res. Rev., 13: 57–75. Bas¸ar, E., Rosen, B., Bas¸ar-Erog˘lu, C. and Greitschus, F. (1987) Bullock, T.H., McClune, M.C. and Enright, J.T. (2003) Are the The associations between 40 Hz EEG and the middle latency electroencephalograms mainly rhythmic? Assessment of peri- response of the auditory . Int. J. Neurosci., odicity in wide-band time series. Neuroscience, 121: 233–252. 33(1–2): 103–117. Callaway, E., Halliday, R. and Herning, R.I. (1983) A compar- Bas¸ar, E., Bas¸ar-Erog˘lu, C., Karakas¸, S. and Schu¨ rmann, M. ison of methods for measuring event-related potentials. Elec- (1999) Are cognitive processes manifested in event-related troencephalogr. Clin. Neurophysiol., 55(2): 227–232. gamma, alpha, theta and delta oscillations in the EEG? Neu- Caravaglios, G., Costanzo, E., Palermo, F. and Muscoso, E.G. rosci. Lett., 259(3): 165–168. (2008) Decreased amplitude of auditory event-related delta Bas¸ar, E., Gu¨ ntekin, B., Tu¨ lay, E. and Yener, G.G. (2010) responses in Alzheimer’s disease. Int. J. Psychophysiol., Evoked and event related coherence of Alzheimer patients 70: 23–32. manifest differentiation of sensory-cognitive networks. Brain Caravaglios, G., Castro, G., Costanzo, E., Di Maria, G., Res., 1357: 79–90. Mancuso, D. and Muscoso, E. (2010) Theta power responses Bas¸ar, E., Gu¨ ntekin, B., Atagu¨ n, I., Turp-Go¨ lbas¸ı, B., Tu¨ lay, E. in mild Alzheimer’s disease during an auditory oddball and O¨ zerdem, A. (2011) Brain’s alpha activity is highly paradigm: lack of theta enhancement during stimulus reduced in euthymic bipolar disorder patients. Cogn. Neuro- processing. J. Neural Transm., 117: 1195–1208. dyn., DOI IO 1007/s11571-011-9172-y. Eckhorn,R.,Bauer,R.,Jordan,W.,Brosch,M.,Kruse,W., Bas¸ar-Erog˘lu, C. and Bas¸ar, E. (1991) A compound P300–40 Munk, M. and Reitboeck, H. (1988) Coherent oscillations: a Hz response of the cat hippocampus. Int. J. Neurosci., mechanism of feature linking in the visual cortex? Multiple elec- 60: 227–237. trode and correlation analyses in the cat. Biol. Cybern., 60(2): Bas¸ar-Erog˘lu, C., Brand, A., Hildebrandt, H., Karolina 121–130. Kedzior, K., Mathes, B. and Schmiedt, C. (2007) Working Fischer, Y., Ga¨hwiler, B.H. and Thompson, S.M. (1999) Activa- memory related gamma oscillations in schizophrenia tion of intrinsic hippocampal theta oscillations by acetylcho- patients. Int. J. Psychophysiol., 64(1): 39–45. line in rat septo-hippocampal cocultures. J. Physiol. (Lond.), Bas¸ar-Erog˘lu, C., Schmiedt-Fehr, C., Mathes, B., 519(2): 405–413. Zimmermann, J. and Brand, A. (2009) Are oscillatory brain Freeman, W.J. (1975) Mass Action in the Nervous System. responses generally reduced in schizophrenia during long Academic Press, New York, pp. 1–507. 362

Freund, T.F. and Antal, M. (1988) GABA-containing neurons contribution to an integrative neuroscience model of schizo- in the septum control inhibitory interneurons in the hippo- phrenia. Brain Res. Rev., 41(1): 57–78. campus. Nature (Lond.), 336(6195): 170–173. Lenz,D.,Jeschke,M.,Schadow,J.,Naue,N.,Ohl,F.W.and Frodl-Bauch, T., Bottlender, R. and Hegerl, U. (1999) Herrmann, C.S. (2008) Human EEG very high frequency Neurochemical substrates and neuroanatomical generators oscillations reflect the number of matches with a template in of the event-related P300. Neuropsychobiology, 40(2): 86–94. auditory short-term memory. Brain Res., 1220: 81–92. Frotscher, M. and Le´ra´nth, C. (1985) Cholinergic innervation of Lizio, R., Vecchio, F., Frisoni, G.B., Ferri, R., Rodriguez, G. the rat hippocampus as revealed by choline acetyltransferase and Babiloni, C. (2011) Electroencephalographic rhythms immunocytochemistry: a combined light and electron in Alzheimer’s disease. Int. J. Alzheimers Dis., 2011: 1–11. microscopic study. J. Comp. Neurol., 239(2): 237–246. (927573. Epub 2011 May 12.) Gandal, M.J., Edgar, J.C., Klook, K. and Siegel, S.J. (2012) Minzenberg, M.J., Firl, A.J., Yoon, J.H., Gomes, G.C., Gamma synchrony: towards a translational biomarker for Reinking, C. and Carter, C.S. (2010) Gamma oscillatory the treatment-resistant symptoms of schizophrenia. Neuro- power is impaired during cognitive control independent of pharmacology, 62(3): 1504–1518. medication status in first-episode schizophrenia. Guidotti, A., Pesold, C. and Costa, E. (2000) New neurochem- Neuropsychopharmacology, 35(13): 2590–2599. ical markers for psychosis: a working hypothesis of their Mitrofanis, J. and Guillery, R.W. (1993) New views of the tha- operation. Neurochem. Res., 25(9–10): 1207–1218. lamic reticular in the adult and the developing brain. Gu¨ntekin, B., Saatc¸i, E. and Yener, G. (2008) Decrease of evoked Trends Neurosci., 16(6): 240–245. delta, theta and alphacoherence inAlzheimerpatientsduringa Monastra, V.J., Lubar, J.F. and Linden, M. (2001) The develop- visual oddball paradigm. Brain Res., 1235: 109–116. ment of a quantitative electroencephalographic scanning Haig, A.R., Gordon, E., De Pascalis, V., Meares, R.A., process for attention deficit-hyperactivity disorder: reliability Bahramali, H. and Harris, A. (2000) Gamma activity in and validity studies. Neuropsychology, 15(1): 136–144. schizophrenia: evidence of impaired network binding? Clin. Oribe, N., Onitsuka, T., Hirano, S., Hirano, Y., Maekawa, T., Neurophysiol., 111(8): 1461–1468. Obayashi, C., Ueno, T., Kasai, K. and Kanba, S. (2010) Differ- Hall, M.H., Spencer, K.M., Schulze, K., McDonald, C., entiation between bipolar disorder and schizophrenia revealed Kalidindi, S., Kravariti, E., Kane, F., Murray, R.M., by neural oscillation to speech sounds: an MEG study. Bipolar Bramon, E., Sham, P. and Rijsdijk, F. (2011) The genetic Disord., 12(8): 804–812. and environmental influences of event-related gamma O¨ zerdem, A., Gu¨ ntekin, B., Tunca, Z. and Bas¸ar, E. (2008a) oscillations on bipolar disorder. Bipolar Disord., 13(3): Brain oscillatory responses in patients with bipolar disorder 260–271. manic episode before and after valproate treatment. Brain Herrmann, C.S. and Demiralp, T. (2005) Human EEG Res., 1235: 98–108. gamma oscillations in neuropsychiatric disorders. Clin. O¨ zerdem, A., Kocaaslan, S., Tunca, Z. and Bas¸ar, E. (2008b) Neurophysiol., 116: 2719–2733. Event related oscillations in euthymic patients with bipolar Huang, M., Li, Z., Ichikawa, J., Dai, J. and Meltzer, H.Y. (2006) disorder. Neurosci. Lett., 444(1): 5–10. Effects of divalproex and atypical antipsychotic drugs on O¨ zerdem, A., Gu¨ ntekin, B., Saatc¸i, E., Tunca, Z. and Bas¸ar, E. dopamine and acetylcholine efflux in rat hippocampus and (2010) Disturbance in long distance gamma coherence in prefrontal cortex. Brain Res., 1099(1): 44–55. bipolar disorder. Prog. Neuropsychopharmacol. Biol. Psychi- Jack, C.R., Jr., Vemuri, P., Wiste, H.J., Weigand, S.D., atry, 34(6): 861–865. Aisen, P.S., Trojanowski, J.Q., Shaw, L.M., Bernstein, M.A., O¨ zerdem, A., Gu¨ ntekin, B., Atagu¨ n, I., Turp, B. and Bas¸ar, E. Petersen, R.C., Weiner, M.W., Knopman, D.S. and the (2011) Reduced long distance gamma (28–48 Hz) coherence Alzheimer’s Disease Neuroimaging Initiative (2011) Evidence in euthymic patients with bipolar disorder. J. Affect. Disord., for ordering of Alzheimer disease biomarkers. Arch. Neurol., 132(3): 325–332. 68(12): 1526–1535. Perry, E., Walker, M., Grace, J. and Perry, R. (1999) Acetylcho- Kaiser, J., Heidegger, T. and Lutzenberger, W. (2008) Behav- line in mind: a neurotransmitter correlate of consciousness? ioral relevance of gamma-band activity for short-term Trends Neurosci., 22(6): 273–280. memory-based auditory decision-making. Eur. J. Neurosci., Polikar, R., Topalis, A., Green, D., Kounios, J. and Clark, C.M. 27(12): 3322–3328. (2007) Comparative multiresolution analysis of ERP Kaiya, H., Namba, M., Yoshida, H. and Nakamura, S. (1982) spectral bands using an ensemble of classifiers approach for Plasma glutamate decarboxylase activity in neuropsychiatry. early diagnosis of Alzheimer’s disease. Comput. Biol. Med., Psychiatry Res., 6(3): 335–343. 37(4): 542–558. Karow, D.S., McEvoy, L.K., Fennema-Notestine, C., Polikar, R., Tilley, C., Hillis, B. and Clark, C.M. (2010) Multi- Hagler, D.J., Jr., Jennings, R.G., Brewer, J.B., Hoh, C.K., modal EEG, MRI and PET data fusion for Alzheimer’s disease Dale, A.M. and the Alzheimer’s Disease Neuroimaging Ini- diagnosis. Proceedings of the IEEE Engineering in Medical tiative (2010) Relative capability of MR imaging and FDG and Biology Society, 2010, pp. 6058–6061. PET to depict changes associated with prodromal and early Porjesz, B., Rangaswamy, M., Kamarajan, C., Jones, K.A., Alzheimer disease. Radiology, 256: 932–942. Padmanabhapillai, A. and Begleiter, H. (2005) The utility Lee, K.H., Williams, L.M., Breakspear, M. and Gordon, E. of neurophysiological markers in the study of alcoholism. (2003) Synchronous gamma activity: a review and Clin. Neurophysiol., 116(5): 993–1018. 363

Rangaswamy, M. and Porjesz, B. (2008) Uncovering genes for neuroimaging initiative: a review of papers published since cognitive (dys)function and predisposition for alcoholism its inception. Alzheimers Dement., 8(1, Suppl.): S1–S68. spectrum disorders: a review of human brain oscillations as (Oct 31 (E pub ahead), PubMed PMID: 22047634.) effective endophenotypes. Brain Res., 1235: 153–171. Wiig, K.A., Heynen, A.J. and Bilkey, D.K. (1994) Effects of Roach, B.J. and Mathalon, D.H. (2008) Event-related EEG kainic acid microinfusions on hippocampal type 2 RSA time-frequency analysis: an overview of measures and an (theta). Brain Res. Bull., 33(6): 727–732. analysis of early gamma band phase locking in schizophrenia. Wright, C.F., Hall, A., Matthews, F.E. and Brayne, C. (2009) Schizophr. Bull., 34(5): 907–926. Biomarkers, dementia, and public health. Ann. N. Y. Acad. Schu¨ tt, A., Bas¸ar, E. and Bullock, T.H. (1992) The effects of Sci., 1180: 11–19. acetylcholine, dopamine and noradrenaline on the visceral Wynn, J.K., Light, G.A., Breitmeyer, B., Nuechterlein, K.H. ganglion of Helix pomatia. II. Stimulus poten- and Green, M.F. (2005) Event-related gamma activity in tials. Comp. Biochem. Physiol. C, 102(1): 169–176. schizophrenia patients during a visual backward-masking Spencer, K.M., Niznikiewicz, M.A., Shenton, M.E. and task. Am. J. Psychiatry, 162(12): 2330–2336. McCarley, R.W. (2008) Sensory-evoked gamma oscillations Yatham, L.N., Liddle, P.F., Lam, R.W., Shiah, I.S., Lane, C., in chronic schizophrenia. Biol. Psychiatry, 63(8): 744–747. Stoessl, A.J., Sossi, V. and Ruth, T.J. (2002) PET study of Stewart, M. and Fox, S.E. (1990) Do septal neurons pace the the effects of valproate on dopamine D(2) receptors in hippocampal theta rhythm? Trends Neurosci., 13(5): neuroleptic- and mood-stabilizer-naive patients with non- 163–168. psychotic mania. Am. J. Psychiatry, 159(10): 1718–1723. Walhovd, K.B., Fjell, A.M., Brewer, J., McEvoy, L.K., Yener, G. and Bas¸ar, E. (2010) Sensory evoked and event Fennema-Notestine, C., Hagler, D.J., Jr., Jennings, R.G., related oscillations in Alzheimer’s disease, a short review. Karow, D., Dale, A.M. and Alzheimer’s Disease Neuroimag- Cogn. Neurodyn., 4: 263–274. ing Initiative (2010) Combining MR imaging, positron- Yener, G., Gu¨ ntekin, B., O¨ niz, A. and Bas¸ar, E. (2007) emission tomography, and CSF biomarkers in the diagnosis Increased frontal phase-locking of event related theta oscil- and prognosis of Alzheimer disease. Am. J. Neuroradiol., lations in Alzheimer patients treated with acetylcholine- 3: 347–354. esterase inhibitors. Int. J. Psychophysiol., 64: 46–52. Weiner, M.W., Veitch, D.P., Aisen, P.S., Beckett, L.A., Yener, G., Gu¨ ntekin, B. and Bas¸ar, E. (2008) Event-related Cairns, N.J., Green, R.C., Harvey, D., Jack, C.R., delta oscillatory responses of Alzheimer patients. Eur. J. Jagust, W., Liu, E., Morris, J.C., Petersen, R.C., Saykin, A.J., Neurol., 15: 540–547. Schmidt, M.E., Shaw, L., Siuciak, J.A., Soares, H., Yener,G.G., Gu¨ ntekin,B., Orken,D.N., Tu¨ lay,E., Forta,H.and Toga, A.W., Trojanowski, J.Q. and Alzheimer’s Disease Bas¸ar, E. (2012) Auditory event related delta responses Neuroimaging Initiative (2011) The Alzheimer’s disease are decreased in Alzheimer’s disease. Behav. Neurol., 24: 1–9.