A review of gamma oscillations in healthy subjects and in cognitive impairment

International Journal of Psychophysiology 90 (2013) 99–117

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International Journal of Psychophysiology journal homepage: www.elsevier.com/locate/ijpsycho

Review

A review of gamma oscillations in healthy subjects and in cognitive impairment Erol Başar ⁎ Istanbul Kultur University, Brain Dynamics, Cognition and Complex Systems Research Center, Istanbul, Turkey

a r t i c l e

i n f o

Article history: Received 3 April 2013 Received in revised form 2 July 2013 Accepted 17 July 2013 Available online 23 July 2013 Keywords: Gamma oscillations Cognition Bipolar disorders Schizophrenia Memory

a b s t r a c t This review describes a wide range of functional correlates of gamma oscillations in whole-brain work, in neuroethology, sensory–cognitive dynamics, emotion, and cognitive impairment. This survey opens a new window towards understanding the brain's gamma activity. Gamma responses are selectively distributed in the whole brain, and do not reflect only a unique, specific function of the nervous system. Sensory responses from cortex, thalamus, hippocampus, and reticular formations in animal and human brains, and also cognitive responses, were described by several authors. According to reviewed results, it becomes obvious that cognitive disorders, and medication—which influence the transmitter release—change entirely the understanding of the big picture in cognitive processes. Gamma activity is evoked or induced by different sensory stimuli or cognitive tasks. Thus, it is argued that gamma-band synchronization is an elementary and fundamental process in whole-brain operation. In conclusion, reasoning and suggestions for understanding gamma activity are highlighted. © 2013 Elsevier B.V. All rights reserved.

1. Introduction This review aims to encompass a wide range of results on gamma oscillations in whole-brain work, in neuroethology, sensory–cognitive dynamics, emotion, and cognitive impairment. A review of such a broad spectrum of data is a difficult mission; however, the trial is important for opening new avenues in understanding brain gamma activity. Neuronal gamma-band oscillations, which can be recorded in many cortical and sub-cortical areas in the mammalian brain and in invertebrate ganglia, are evoked or induced by different stimuli or tasks. Many different gamma-band oscillatory processes are involved in diverse functions (Herrmann et al., 2004). Further, there are several views related to the role of gamma activity in the communication processing of the brain. These results often lead to controversies. The present review argues that gamma-band activation is a fundamental process that serves as an elementary operator of brain function and communication. It was previously proposed that gamma band activities are selectively distributed in the brain, and do not reflect a specific function in the nervous system (Başar-Eroglu et al., 1992). In recent decades, several reviews were published that supported this conclusion (Fries, 2009; Herrmann et al., 2004; Uhlhaas and Singer, 2006). An extended discussion on gamma activity in cognitive impairment was included in recent conference proceedings under the umbrella of the World Federation on Clinical Neurophysiology (Başar et al., 2013). ⁎ Tel.: +90 212 498 43 92; fax: +90 212 498 45 46. E-mail address: [email protected]. 0167-8760/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.ijpsycho.2013.07.005

The empirical background of the gamma band dates back to Adrian (1942), who reported that the application of odorous substances to the olfactory mucosa of the hedgehog induced trains of sinusoidal oscillations within the 30 to 60-Hz range. The studies on the 40-Hz oscillation passed a total of seven phases initiated by Adrian (1942) in the first phase. According to Lavin et al. (1959) and Hernandez-Peon et al. (1960), 40-Hz activity was not restricted to olfactory stimuli, but could be elicited by a wide range of other conditions. The second phase took place between 1960 and 1980, and was characterized by the works of Freeman (1975), Başar et al. (1975a,b,c) and Sheer (1976), in which a variety of functions were ascribed to the gamma oscillations. Başar and Özesmi (1972) introduced the term ‘gamma-response’ to describe hippocampal gamma-range activity to external stimuli in cats. Enhanced gamma activity was especially seen in structures that were able to fire spontaneously in this mode (‘gamma resonance’). In addition, 40-Hz oscillatory responses were also observed in humans (Sheer, 1989; Başar et al., 1976; Galambos et al., 1981). Further studies found gamma-range activities associated with visual (Eckhorn et al., 1988; Gray et al., 1989) and olfactory (Freeman, 1975, 1979) sensation. For a comprehensive review, see Başar-Eroglu et al. (1996b) and Başar (1999). The third phase started with the work of Galambos et al. (1981). This work led to investigations concerning the sensory and cognitive correlates of the gamma oscillation, primarily in humans. The fourth phase is shaped by the fundamental works of Eckhorn et al. (1988), and Gray and Singer (1989), which led to investigations of 40-Hz at the cellular level.

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The fifth phase is marked by the heterogeneity of approaches and techniques applied with the aim of fully describing gamma. During this fifth phase, Galambos (1992) suggested classifying various findings of gamma-band activities measured in different species using a categorical system, in a workshop in New York (See Galambos, 1992), as follows: 1. The spontaneous gamma-activity, i.e., a fraction of the total EEG energy at any given moment without intentional stimulation (Başar and Özesmi, 1972; Sheer, 1976). 2. The induced gamma-activity, i.e., activity initiated by—but not tightly coupled to—a stimulus (Adrian, 1942; Freeman, 1975; Freeman and Skarda, 1981). 3. The evoked gamma-activity, which is both elicited by and strictly timelocked to a stimulus. Numerous examples have been studied in different brain regions of human and cat models. 4. The emitted gamma-activity, i.e., activity that is not bound to a stimulus but rather to an internal process; demonstrated, for instance, by the use of the ‘omitted stimulus’ paradigm in non-mammalian vertebrates like fish (Bullock et al., 1990) or mammals like cat (Başar-Eroglu and Başar, 1991). From the late 1990s to the present, a sixth phase is observed, during which research on gamma activity increased significantly, prompted by interest in the effects of neurotransmitters (Traub et al., 2003; Whittington et al., 1995, 2000). Further, several studies suggested that 40-Hz oscillatory activity is not restricted to sensory processing, but can also be modulated or triggered by cognitive processes (Tiitinen et al., 1993; Pulvermuller et al., 1995; Tallon-Baudry et al., 1998). Başar et al. (1995) argued that gamma responses occur throughout the brain, i.e., in a selectively distributed way, as correlates of brain functions, which can be sensory and cognitive in origin. The seventh phase began in the 2000s, and is shaped by strategies on cognitive gamma responses, and also by increasing numbers of studies on cognitive impairment.

is usually made between ‘evoked’ and ‘induced’ oscillations (BaşarEroglu et al., 1996b). If an oscillation appears with the same latency and phase after each stimulus, it is considered evoked activity, which is usually the case for early gamma activity before 150 ms after stimulus presentation (peak latencies are typically around 50 ms for auditory and around 100 ms for visual stimuli) (see also Figs. 1, 3A,B). Herrmann et al. (2004) also indicated that if the oscillation varies in either latency or phase from trial to trial, it is called induced activity. This is typically the case for the late gamma activity which occurs 200–300 ms after stimulus presentation and later (see also Section 3.2.2 and Fig. 3A). Gamma activity appears in a wide frequency band, between about 30 and 80 Hz. Evoked responses often oscillate around 40 Hz, whereas induced responses might also reveal higher frequencies. Computation of the average potentials across many experimental trials, as it is usually employs electrophysiology to yield the event-related potential, whereas evoked oscillations are summed because they are phase-locked to stimulation. Induced activity, on the other hand, almost cancels out completely in the averaged event-related potential. It should be noted that induced oscillations are highly reduced in the averaged curves but never cancelled out if the number of epochs do not attain high trials (see example in Fig. 3A). To the noteworthy classification by Herrmann et al. (2004), we also add event-related oscillations. In this case, the stimulations include a task, such as the target signal in P300 oddball paradigm. The empirical findings on the gamma band may be roughly classified into sensory (or obligatory) versus cognitive gamma responses.

2. Natural frequencies of the brain. Superposition of oscillations The functional significance of oscillatory neural activity begins to emerge from the analysis of responses to well-defined events (eventrelated oscillations, phase- or time-locked to a sensory or cognitive event). Among other approaches, it is possible to investigate such oscillations by frequency domain analysis of event-related potential (ERP), based on the following hypothesis: The EEG consists of the activity of an ensemble of generators producing rhythmic activity in several frequency ranges. These oscillators are usually active in a random way. However, by application of sensory stimulation, these generators are coupled and act together in a coherent way. This synchronization and enhancement of EEG activity give rise to “evoked” or “induced” rhythms. Evoked potentials, representing ensembles of neural population responses, were considered to be a result of the transition from a disordered to an ordered state. The compound ERP manifests a superposition of evoked oscillations in the EEG frequencies, ranging from delta to gamma (“natural frequencies of the brain” such as alpha: 8–13 Hz, theta: 3.5–7 Hz, delta: 0.5–3.5 Hz and gamma: 30–70 Hz). See further publications by Başar (1980), Yordanova and Kolev (1998), and Klimesch et al. (1997); see reports in Başar and Bullock (1992), Gurtubay et al. (2004), and Buszaky (2006).

3. Gamma oscillations: functional multiplicity Herrmann et al. (2004) distinguish the evoked gamma and induced gamma oscillations as follows: Oscillations in the brain can either occur spontaneously, that is, without relation to external stimuli, or they can be related to the processing of stimuli. In the latter case, a distinction

Fig. 1. (A) Spontaneous and evoked electrical activity recorded from the human vertex (Cz-electrode). The curve was evaluated by averaging 40 single, unselected sweeps (digital filter applied: pass-band filter of 1–200 Hz); (B) averaged EEG-EP of illustration (A), filtered using a 30–50 Hz pass-band filter; (C) spontaneous and evoked electrical activity recorded from the human vertex (Cz-electrode). The curve was evaluated by averaging 40 single, selected sweeps with large 40-Hz enhancement; selection criterion was X N 1.8; (D) averaged EEG-EP of illustration (C), filtered using a 30–50 Hz pass-band filter; (E) spontaneous and evoked electrical activity recorded from the human vertex. The curve was evaluated by averaging 40 single, selected sweeps without 40-Hz enhancement; selection criterion: enhancement factor X b 1.2; (F) averaged EEG-EP of illustration (E), filtered using a 30–50 Hz passband filter. (Bottom) The solid curve is that shown in (E); the dotted curve is (A), which here is filtered 30–50 Hz stop-band filters (modified from Başar et al., 1987).

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3.1. Sensory responses Some examples of sensory functions are: (1) A phase-locked gamma oscillation is also a component of the human auditory and visual response, as Figs. 1 and 2 show. (2) A strategy involving the application of six cognitive paradigms showed that the 40-Hz response in the 100 ms following stimulations has a sensory origin. It is independent of cognitive tasks (Karakas and Başar, 1998) (Fig. 2). (3) The auditory MEG gamma response is similar to human EEG responses, with a close relationship to the middle latency auditory evoked response similar to Fig. 1 (Pantev et al., 1991). (4) Several authors demonstrated auditory and visual response from cortex, thalamus, hippocampus, and reticular formation of the cat brain in the first 150 ms following stimulation (Demiralp et al., 1996). 3.2. Cognitive processes 3.2.1. Binding problem 1. Most prominent examples related to cognitive processes are oscillatory responses in the frequency range of 40–60 Hz, occurring in synchrony within a functional column in the cat visual cortex (Gray

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and Singer, 1989). These authors proposed that these results reflect a mechanism of feature-linking in the visual cortex (Eckhorn et al., 1988). This is related to the ‘binding problem’: how is the spatially distributed but temporally coherent electrical activity from a large number of elementary neural components integrated to functional activity? The binding theory does not fully explain the ‘ubiquity of gamma rhythms’ (Desmedt and Tomberg, 1994; Schürmann et al., 1997). In this respect, it may be helpful to consider further studies of gamma oscillations, partly going back to Lord Adrian (1942). While the interpretations differ, the empirical findings may be roughly classified into sensory or obligatory versus cognitive gamma responses. Concerning the former category, auditory and visual gamma responses are selectively distributed in different cortical and subcortical structures. They are phase-locked stable components of EPs in cortex, hippocampus, brain stem, and cerebellum of cats, that occur 100 ms after sensory stimulation, with a second window of approximately 300 ms latency (Başar, 1980, 1999; Schürmann et al., 1997). 2. The binding theory was supported by several authors, especially by Tallon-Baudry et al. (1996). Presentation of coherent versus noncoherent visual stimuli triggers an early phase-locked 40-Hz component, maximal at electrodes Cz–C4, which does not vary with stimulation type. A second 40-Hz component appears around 280 ms. This is not phase-locked to stimulus onset, and is stronger in response to a coherent stimulus. Tallon-Baudry et al. (1996) suggest that this

Fig. 2. Topography of the grand averages of filtered (28–46 Hz) EEG-ERPs from the target stimuli of the oddball paradigm (modified from Karakas and Başar, 1998; International Journal of Psychophysiology 31, 13–31).

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Fig. 3. A: Event-related potentials of the lower pyramidal layer (CA3) of hippocampus (one cat). Top: Single ERP sweeps (epochs) filtered at 30–50 Hz. Middle: Averaged ERP filtered at 30–50 Hz. Bottom: Unfiltered ERP, average of 50 artifact-free epochs (modified from Başar-Eroğlu et al., 1991). OS: The time marker of the omitted stimulation. The gamma responses are time-locked to omitted stimulation. B: Grand averages (mean values from 8 cats) of ERPs in various layers of hippocampus. Top: Location of multi-electrode; CA1 and CA3 corresponding to HI1 and HI3/HI4, respectively. Middle: Unfiltered ERPs. Bottom: Filtered ERPs (30–50 Hz; OS: omitted stimulation) (modified from Başar-Eroğlu et al., 1991).

could reflect a mechanism of future binding on the basis of highfrequency oscillations (For the late 40-Hz component, see also Fig. 3A). 3. Attention-related 40-Hz responses were reported in humans, especially over the frontal and central areas (Tiitinen et al., 1993). 4. The spatiotemporal magnetic field pattern of gamma band activity has been interpreted as a coherent rostrocaudal sweep of activity, repeating every 12.5 ms, due to a continuous phase shift over the hemisphere (Llinas and Ribary, 1992). 5. During visual perception of reversible or ambiguous figures, a significant increase of almost 50% in human frontal gamma EEG activity was recorded during states of ‘perceptual switching’ (Başar-Eroglu et al., 1996a). This wide spectrum of experimental data is in accordance with a hypothetical ‘selectively distributed parallel processing gamma system’ with multiple functions. Rather than being highly specific correlates of a single process, gamma oscillations might be important building blocks of electrical activity of the brain. Being related to multiple functions, they are also observed in subcortical structures. Subcortical gamma responses: • Auditory and visual-gamma responses are selectively distributed in different cortical and subcortical structures. They are phase-locked, stable components of EPs measurable in the cortex, hippocampus, brain stem, and cerebellum of cats; they occur about 100 ms after sensory stimulation, with a second occurrence of approximately 300-ms latency (Başar, 1980; Schürmann et al., 1997). • The phenomena of inter-sensory facilitation have been studied extensively, mainly in animal models. It was reported that not only subcortical structures (e.g. superior colliculus) (Meredith and Stein, 1983, 1985; Hartline, 1987) but also higher areas of both archi- and neocortical origin (Wallace et al., 1992; Wallace

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and Stein, 1994; Stein et al., 1993) are involved in processes of multimodal convergence. In unanesthetized rats, gamma oscillations were found in epipial derivations adjacent to somatosensory cortices when afferent information was provided by the vibrissae. It was suggested that synchronized gamma oscillations may play a role in assembling punctate information into a coherent representation of a somatosensory stimulus (Jones and Barth, 1997). The impact of cognitive tasks on the gamma band gained considerable interest during the 1990s. Long-distance synchronization has been suggested as a mechanism for the linkage of spatially-segregated cortical areas (König et al., 1995; R. Traub et al., 1996; Rodriguez et al., 1999). The gamma band activity in an auditory oddball paradigm was analyzed with the wavelet transform. A late oscillatory peak at 37 Hz with latency around 360 ms was observed, appearing only for target stimuli (Gurtubay et al., 2001). A study of the human limbic system also confirmed the synchronization of gamma rhythms during cognitive tasks (Fell et al., 1997). Rodriguez et al. (1999) reported that the process of pattern recognition affects gamma band activity and (independently) phase synchrony, based on whether coherent (‘Mooney’ faces) or non-coherent shapes are presented. The authors argue that the process of perception is reflected mainly in phase synchrony.

3.2.2. Superposition of P300 component with gamma response Several investigations dealt with cognitive processes related to gamma responses, some of which were based on measuring the P300 wave. This positive deflection typically occurs in human ERPs in response to “oddball” stimuli or omitted stimuli, interspersed as “targets” into a series of standard stimuli.

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A P300–40-Hz component has been recorded in the cat hippocampus, reticular formation, and cortex (with omitted auditory stimuli as targets). This response occurs approximately 300 ms after stimulation, being superimposed with a slow wave of 4 Hz illustrated in Fig. 3A (Başar-Eroglu and Başar, 1991). The paradigm used was discussed in the following paragraphs. The chronically implanted, freely-behaving cats heard tones of 2000 Hz and 80 dB with regular intervals over a long period of time. In the second stage of the experiments, every fifth of these tones was omitted. In the course of such experiments, induced 40-Hz oscillations were observed in the cat hippocampus. Fig. 3A shows about 10 single EEG-epochs as responses to omitted stimuli, with a passband of 30–50 Hz. Preliminary data indicate similar P300–40-Hz responses to oddball stimuli in humans (Başar-Eroglu et al., 1992; Gurtubay et al., 2001). However, a suppression of 40-Hz activity after target stimuli has also been reported (Fell et al., 1997). Fig. 3B indicates that such 40-Hz bursts in response to omitted stimuli have maximal responses in the CA3 layer of the hippocampus, and that a slow wave of approximately 4 Hz is superimposed with these gamma responses, occurring 300 ms following the omitted stimuli. This P300–40-Hz response has pure cognitive causality, and possibly corresponds to the induced late-gamma response described by Herrmann et al. (2004). This is an example of analyses including a task, accordingly event-related oscillations and also an example of cognitively-induced gamma rhythms superimposed with a lowfrequency oscillatory response. Several studies using intracranial recordings from the rat brain (Miller, 1991) and from human brain (Dastjerdi et al., 2011) indicated that cortico-cortical interplay occurs after sensory-network and hippocampal–cortical network activation. Using rat intracranial recordings, Miller (1991) estimated a hippocampal–cortical loop time in the range of 120–200 ms post-stimulus. In human intracranial recordings, upon a cognitive task, Dastjerdi et al. (2011) demonstrated the occurrence of a cortical activation in lateral parietal cortex after approximately 300 ms. Taking these intracranial recording findings into consideration, it is reasonable to assume that the beginning of the cortico-cortical interplay starts around 300 ms post-stimulus. No gamma responses are seen at the time of the omitted stimulus, since there is no physical stimulation. Thus, the response at around 250–300 ms is a pure cognitive response. This experiment clearly demonstrates an intracranial cognitive response that occurs at 250–300 ms, most probably following a subcortical interplay in the frontal–parietal–hippocampal circuit.

3.3. Gamma responses selectively distributed in the cortex measured from scalp electrodes Sakowitz et al. (2001) analyzed gamma responses upon bimodal (visual, auditory) stimulation. The grand average of all 15 subjects is shown in Fig. 4. With auditory stimulation, enhancements are visible in central locations, and more poorly defined in the occipital ones. Visual

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stimulation shows enhancements only in C4 and Cz. On the other hand, bimodal stimulation evokes significantly higher enhancements than the other two modalities (also see Fig. 4). These enhancements are distributed diffusely in the surface EEG, being most pronounced at central locations. On this stimulus condition, the pre-stimulus responses reach values up to 9 μV. Although distributed diffusely, bimodal responses are most overt in central electrodes, especially in frontal locations, where enhancements occur exclusively upon bimodal stimulation. The results summarized in Fig. 5 for bipolar stimulation help to demonstrate that elicited gamma responses can be selectively distributed across the whole cortex, depending on the modality of the stimulation. Auditory gamma responses are recorded mostly in the central and frontal areas. Visual gamma responses are recorded mostly in posterior areas.

4. Gamma in vegetative functions and evolution In this section, we briefly discuss two examples of gamma activity that manifest completely different phenomena from sensory–cognitive components described in previous sections. These examples clearly show that gamma activity is also interwoven with vegetative functions, and also that the gamma activity can be activated in different types of neural assemblies, namely in invertebrate ganglia. When an animal inhales a familiar scent, what we call a burst can be seen in each EEG tracing. All the waves from the array of electrodes suddenly become more regular, or ordered, for a few cycles, until the animal exhales. The waves often have a higher amplitude and frequency than they do at other times (Fig. 6). The fact that the bursts represent cooperative, interactive activity is not immediately clear in the EEG plots, because the burst segments differ in shape from trace-to-trace in a simultaneously recorded set. Freeman states that it is not the shape of the carrier wave that reveals the identity of an odor. Indeed, the wave changes every time an animal inhales, even when the same odorant is repeatedly sniffed. The identity of an odorant is reliably discernible only in the bulb-wide spatial pattern of the carrier-wave amplitude (Fig. 6). Additional to the results presented in this review, we also direct the reader to a series of experiments by Bullock's research team in California, and Başar's group in Lübeck, covering comparative research on invertebrates and low vertebrates: Schütt and Başar (1992), Schütt et al. (1992), Başar et al. (1999) and Bullock and Başar (1988) also examined the effect of transmitters such as acetylcholine, dopamine, noradrenalin, and serotonin on the isolated ganglia of Helix pomatia (snail), and showed changes in the oscillatory dynamics of these ganglia. These results were briefly presented in Chapter 10 of Başar (2011). We emphasize two results pertinent to the present review: The application of acetylcholine (ACh) induced a large increase in the theta response in the isolated visceral ganglion. Dopamine induced a crucial change in the oscillatory response, which was recorded in the gamma frequency band following the electrical stimulation in the helix visceral ganglion, as shown in Fig. 7 (modified from Schütt and Başar, 1992), which shows the averaged evoked potentials from an experiment in which 40-Hz activity increases after the administration of dopamine (control, top; with dopamine

Fig. 4. Grand average (n = 15) of gamma band wavelet components. Along the x-axis, 1-second pre- and post-stimuli are plotted, with y-values in arbitrary units. (A) Auditory-evoked potentials, (B) visually-evoked potentials, and (C) bisensory-evoked potentials (modified from Sakowitz et al., 2001).

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Fig. 5. Comparison of pre- and post-stimuli maximum coefficients for each electrode and modality. Y-values in arbitrary units (mean and standard error). Single graphs represent (from top to bottom) frontal, centro-temporal, parietal, and occipital electrode rows (modified from Sakowitz et al., 2001).

(10− 2 M), bottom; wide-band filtered 1–250 Hz, left; pass-band filtered from 30 to 70 Hz, right). On the left side of Fig. 7, the evoked potentials of the helix are shown in a wide frequency band. On the right, the filtered evoked potential in the frequency window of 30–70 Hz is illustrated. After the administration of dopamine, the gamma evoked response reached values of more than 200% in comparison to the control response. The basic results obtained from the study of invertebrate ganglia, indicating increased activity in the 40-Hz range after the application of dopamine, allows the tentative assumption that the gamma increase induced by dopamine is a universal process recorded in most low-level species. Section 7 of this review includes results demonstrating that patients with schizophrenia show increased gamma activity when treated with dopamine. It would therefore be interesting to examine patients before and after application of dopamine. Additionally, light-induced gamma responses have been observed in arthropods (Kirschfield, 1992).

Fig. 6. Simultaneous recordings from the olfactory bulb (A), front (B), and rear (C) parts of a cat's olfactory cortex. These show low-frequency waves interrupted by “bursts”—high-amplitude, high-frequency oscillations that are generated when odors are perceived. The average amplitude of a burst is some 100 μV. Each lasts a fraction of a second, for the interval between inhalation and exhalation (modified from Freeman, 1991; with permission).

4.1. Interim conclusion: multiple functions in the gamma band and selective distribution The wide spectrum of experimental data being presented is in accordance with a hypothetical “selectively distributed parallel processing gamma system” with multiple functions. Rather than being highly specific correlates of a single process, gamma oscillations might be important building blocks of electrical activity of the brain. Being related to multiple functions, they may (i) occur in different and distant structures, (ii) act in parallel, and (iii) show phase locking, time locking, or weak time locking. Notably, simple electrical stimulation of isolated invertebrate ganglia evokes gamma oscillations (in the absence of perceptual binding or higher cognitive processes). In conclusion, gamma oscillations possibly represent a universal code of CNS communication. 5. Gamma activity in recognition of faces and facial expressions In the analysis of electrophysiology of facial percepts, the experimenter is confronted with face processing, which comprises (i) perceptual and memory processes required for the recognition of complex stimulation as a face, (ii) the identification of the particular face in view, and (iii) the analysis of its facial expression (McCarthy, 2000). In addition to the processes pointed out, the valence and the arousal dimensions that the subjects express are the prominent characteristics of facial expression analyses. Başar-Eroglu et al. (1996a) reported increased gamma response to ambiguous stimulation. During the repeated presentation of familiar stimuli, the induced gamma band responses were reported to be decreased (Wiggs and Martin, 1998; Gruber and Muller, 2006). On the other hand, induced gamma band enhancements were reported during the representation of unfamiliar stimuli (Fiebach et al., 2005; Gruber and Muller, 2005, 2006; Henson et al., 2000).

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Fig. 7. Averaged evoked potentials from an experiment in which 40-Hz activity increases after dopamine: control, top; with dopamine (10−2 M), bottom; wide-band filtered from 1 to 250 Hz, left; pass-band filtered from 30 to 70 Hz. right. Modified from Schütt and Başar (1992).

Later, a research group also showed greater gamma activity for faces compared to non-face stimuli (Zion-Golumbic et al., 2008). Stronger induced-gamma response to famous faces than non-famous faces was also reported (Zion-Golumbic et al., 2010). On the other hand, in a MEG study, Dobel et al. (2011) reported that unknown faces elicited stronger gamma response than familiar faces. Engell and McCarthy (2010) directly recorded field potentials from the cortical surface while the subjects selectively attended to images of faces or houses. These authors reported that face-specific gamma activity was strongly modulated by selective attention. The changes in gamma activity during recognition of faces in different groups were also analyzed in recent studies. Dobel et al. (2011) showed that persons suffering from prosopagnosia displayed less induced gamma activity in comparison to healthy subjects. Lee et al. (2010) reported that gamma band activity was significantly lower in the schizophrenia patients than in the normal controls at around 700–800 ms at FCz electrode. These authors also analyzed gamma phase synchrony in schizophrenia patients in comparison to healthy subjects during face recognition, and reported lower phase-synchronization at 200–300 ms in schizophrenia patients than in normal controls. Matsumoto et al. (2006) showed that gamma band activity was higher in nonalexithymic subjects in comparison to alexithymic subjects. Accordingly, the abovementioned studies showed that gamma band activity is an important component in recognition of faces and facial expressions. 6. Neurotransmitters, long-distance and short-distance connectivity The web of neurotransmitters and gamma activity constitutes one of the fundamental topics in the study of oscillatory brain networks and their connectivity. Furthermore, the gamma activity and the connectivity between short-distance and long-distance networks play a major role in brain function. Could the disruption of connectivity in a psychiatric dysfunction—namely bipolar disorder—be a biomarker manifesting the major contribution of neurotransmitter gamma to connectivity between long-distance neural networks? The present section deals with the greatly reduced connectivity within the gamma band in bipolar disorder patients. Regardless of the clinical importance of this connectivity-failure, these results are mostly important for enlightening of basic functions of gamma activity. Therefore, this section jointly analyzes neurotransmitter effects in physiology, cognitive impairment, and long-distance coherence. 6.1. Fundamental comments on neurotransmitters and gamma activity According to R.D. Traub et al. (1996), in vitro models of gamma oscillations demonstrate two forms of oscillations: (a) one occurring

transiently, and driven by discrete afferent input; and (b) the other occurring persistently, in response to activation of excitatory metabotropic receptors. The mechanism underlying persistent gamma oscillations has been suggested to involve gap-junctional communication between the axons of principal neurons, but the precise relationship between this neuronal activity and the gamma oscillation has remained elusive. According to their results, R.D. Traub et al. (1996) assumed that high-frequency oscillations occurred as a consequence of random activity within the axonal plexus. The authors further discuss that interneurons provide a mechanism by which this random activity is both amplified and organized into a coherent network rhythm. It was long thought that a given neuron released only one kind of neurotransmitter, but today, many experiments have shown that a single neuron can produce several different neurotransmitters. Başar (2011, Chapter 3) discussed the best-known transmitters that are involved in functions such as causing blood vessels to contract and the heart rate to increase. Norepinephrine plays a role in mood disorders such as manic depression. GABA (gamma-aminobutyric acid) is an inhibitory neurotransmitter that is widely distributed in the neurons of the cortex. GABA contributes to motor control, vision and many other cortical functions. GABAergic interneurons, which are the core component of cortico-limbic circuitry, were found to be defective in the cerebral cortex of bipolar patients (Benes and Berretta, 2001). GABA spreads in neural networks involved in cognitive and emotional processing, and modulates noradrenergic, dopaminergic and serotonergic local neural circuitry (Brambilla et al., 2003). Several studies revealed low plasma (Berettini et al., 1983; Kaiya et al., 1982) or cortical GABA activity (Bhagwagar et al., 2007), or altered genetic expression of GABA (Guidotti et al., 2000; Heckers et al., 2002) in bipolar disorder. Low GABA activity was thought to be a genetically determined trait creating a vulnerability that, with the contribution of environmental factors, can lead to the development of either mania or depression. It is also important to note that GABAergic activity is reciprocally regulated by dopamine, the hyperactivity of which also plays a role in mania (Yatham et al., 2002). Alterations in the modulation of the dopamine system may trigger the appearance of a defective GABA system (Benes and Berretta, 2001). It is important to emphasize the web of theta activity in the GABAergic and cholinergic inputs from the septum. In vivo studies suggest that the hippocampal theta rhythm depends on GABAergic and cholinergic inputs from the septum (Brazhnik and Fox, 1997; Stewart and Fox, 1990), and requires an intact hippocampal CA3 region (Wiig et al., 1994). The cholinergic inputs to the hippocampus are distributed on both the pyramidal and interneuronal cells (Frotscher and Leranth, 1985), while the GABAergic inputs selectively contact the

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hippocampal inter-neurons (Freund and Antal, 1988). Recent in vitro work on septo-hippocampal cocultures showed that CA3, but not CA1, exhibited theta-like oscillations driven by septal muscarinic synaptic inputs (Fischer et al., 1999). This suggests that the hippocampus is locally capable of regulating the frequency of theta, independent of the septal inputs. Other studies have shown that theta episodes recorded in the hippocampus can be elicited by the stimulation of hypothalamo-septal fibers (Smythe et al., 1991), the stimulation of the reticular formation (Kirk and McNaughton, 1993; Vertes, 1982), or by the hippocampal infusion of carbachol after posterior hypothalamic inactivation (Oddie et al., 1994). In the present section, the potential of GABA in bipolar patients will be emphasized. Also included is a discussion of the action of valproate, which is an effective antimanic agent (Bowden, 2003). There is some evidence to support the role of valproate in elevating the levels of GABA within the brain (O'Donnell et al., 2003). Valproate was shown to augment the ability of atypical antipsychotic medications to increase dopamine (DA) and acetylcholine (Ach) efflux in the rat hippocampus and medial prefrontal cortex (Huang et al., 2006). It was also shown to lead to a significant reduction in presynaptic dopamine function in manic patients. This was thought to be related to improvement in manic symptoms (Yatham et al., 2002), since it regulates cell survival pathways such as the cAMP-responsive element binding protein (CREB), brain derived neurotrophic factor (BDNF), bcl-2 and mitogenactivated protein kinases (MAP), which may underlie its neuroprotective and neurotrophic effects (Özerdem et al., 2008; Xiaohua et al., 2002; Löscher, 2002). GABAergic interneurons and pyramidal cells were found to build and maintain complex interconnections that lead to large-scale network oscillations, such as theta, gamma (40–100 Hz), and ultrafast (200 Hz) frequency bands (Benes and Berretta, 2001). Glutamate is a major excitatory neurotransmitter that is associated with learning and memory, and is also thought to be associated with Alzheimer's disease, whose first symptoms include memory malfunctions. GABA and glutamate as neurotransmitters are used by more than 80% of the neurons in the brain, and constitute the most important inhibition. The glutamate action, together with GABA and dopamine, will be presented in Section 9.

With the concept of brain oscillations, the role of temporal and spatial coherence also gained considerable importance (Grossberg, 1999; Mountcastle, 1998). Integrative activity is a function of the coherences between spatial locations of the brain; these coherences vary according to the type of sensory and or cognitive event, and possibly the state of consciousness of the species. Early findings of our research groups (Başar, 1980) demonstrated coherences over long distances in alpha, beta, theta and delta frequency ranges in structures such as sensory cortices, hippocampus and the brain stem of both freely-moving awake cats and sleeping cats. Following sensory stimulation, varying degrees of coherences—thus interactions—were obtained between recordings of the various structures (Başar, 1980; Kocsis et al., 2001; Schürmann et al., 2000). Results pertaining to “varying degrees of coherence” lead to the concept of selectively coherent neural populations. Thus, distributed neural populations cooperate or drive each other, or are driven by general command mechanisms in the EEG frequency channels (Başar, 1980; Haenschel et al., 2000; Kocsis et al., 2001; Schürmann et al., 2000).

6.3. Increase of gamma connectivity during cognitive processing There are few publications showing the significant increase of coherences in all EEG frequency channels during application of cognitive stimulation in comparison to coherences upon pure sensory stimuli (see for example Güntekin and Başar, 2010). In Fig. 8A and B of the following section, these differences are implicitly shown. These results will be described together, in comparative analysis of gamma connectivity and the influence of neurotransmitters.

6.2. Selectively distributed and selectively coherent oscillatory networks in the brain A fundamental unsolved problem in neuroscience concerns the manner in which the vast array of parallel processing occurring in the brain at any given time, respectively the diverse neural activities, is bound together or integrated (Haig et al., 2000). For instance a visual image of an object contains a collection of features that must be identified and segregated from those comprising other objects. Generally, it is assumed that different features of the image are processed by different areas of the brain. How then is the spatially-distributed processing related to one percept integrated? This process is known as the binding problem (Singer and Gray, 1995). The description of integration needs morphological and functional interrelation within defined durations in the time space; the degree of interaction between two signals can be measured by coherence (von Stein and Sarnthein, 2000). Coherence is a statistical measure; the value of coherence depends on the amount of repeated correlations between events in the frequency domain. The phase relationship between the two signals is less relevant; however, it must be stable. Since the signal at each electrode site mostly reflects the network activity under the electrode, coherence between two electrodes should measure interactions between two neural populations. The statistical nature of coherence helps to unravel them from noise if they repeat consistently (von Stein and Sarnthein, 2000). If two brain locations are coherent, one of the locations drives the other, or they reciprocally cooperate; they may also be coherently activated by a common driver (Bullock and McClune, 1989).

Fig. 8. Mean Z values for sensory evoked (A), and target (B) coherence in response to visual stimuli at all electrode pairs. “★” sign represents p b 0.05 (modified from Özerdem et al., 2011).

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6.4. Decrease of event-related gamma coherence in euthymic bipolar patients

6.6. The association between gamma oscillations and GABA/glutamate neurotransmission

Özerdem et al. (2011) studied the cortico-cortical connectivity by examining sensory-evoked coherence and event-related coherence values for the gamma frequency band during simple light stimulation, and visual oddball paradigm in euthymic drug-free patients. The study group consisted of 20 drug-free euthymic bipolar patients and 20 sexand age-matched healthy controls. Groups were compared for the coherence values of the left (F3-T3, F3-TP7, F3-P3, F3-O1) and right (F4-T4, F4-TP8, F4-P4, F4-O2) intra-hemispheric electrode pairs, and showed significantly diminished bilateral long-distance gamma coherence between frontal and temporal, as well as between frontal and temporo-parietal regions, compared to healthy controls. Fig. 8A and B shows the grand averages of visual sensory and visual event-related coherence in gamma frequency (28–48 Hz) band in response to simple light and to target stimuli respectively between the right (F4-T8) and left (F3-T7) fronto-temporal electrode pairs in euthymic bipolar patients (n = 20) compared with healthy controls (n = 20) (Özerdem et al., 2011). No significant reduction in sensory-evoked coherence was recorded in the patient group compared to the healthy controls (Fig. 8A). In contrast, the decrease in “event-related coherence (target stimulation)” differed topologically and ranged between 29% (right fronto-temporal location) and 44% (left fronto-temporo-parietal location) as shown in Fig. 8B. Gamma oscillations were suggested to have a gating effect on the incoming information within the temporal domain, thus facilitating the synchronization of spatially-separate brain regions, and leading to long-term changes in the strength of synaptic connectivity between areas (Whittington et al., 2000). Taken together, disruption of “longrange gamma coherence” in untreated manic patients may represent the underlying mechanism of the well-documented neuro-cognitive dysfunction in bipolar illness (Martinez-Aran et al., 2004). According to Whittington et al. (2000), for an agent to manipulate fast oscillations, a population of interconnected inhibitory cells and sufficient postsynaptic GABAergic response are necessary. It has also been proposed that the generation and maintenance of gamma band oscillation depend on the presence of sufficient GABA (Traub et al., 2003). Disruption in the right fronto-temporal gamma coherence in mania may be indicative of insufficient GABA transmission; improvement with valproate, an agent with well-known GABAergic effects, confirms this suggestion as being applicable in bipolar disorder.

Synchronous neural gamma oscillations are critical for corticocortical communication and the large-scale integration of distributed sets of neurons for integrated cognitive functioning (Rodriguez et al., 1999). Gamma oscillations originate within networks of inhibitory GABAergic interneurons (Gray and McCormick, 1996). This causes a membrane-potential oscillation in long-axoned projection neurons, such as pyramidal cells in the neocortex, hippocampus and thalamocortical neurons, to provide communication between spatially separate sites, and also control brain function. Gamma oscillations are known to have a network-inhibitory effect, and were proposed to be driven by metabotropic glutamate receptor activation (Whittington et al., 1995). GABAergic modulation is required for synchronization of glutamatergic firing (Whittington et al., 2000). Taken together, there is an interplay between the GABA/glutamate system and the gamma oscillations. Bipolar disorder is known to include low GABA activity (Petty, 1995) and abnormalities affecting GABA-related inhibitory neurotransmission (Levinson et al., 2007; Benes and Berretta, 2001). In a multidimensional model of electrical signals by Başar and Güntekin (2008), the interplay between a given neuropathology and different neurotransmitter systems can be displayed in oscillatory activity by application of several different input modalities such as visual, auditory, somatosensory, cognitive and emotional. In accordance with this model, any dysfunction in neuronal synchronization caused by any such dysfunctional neurotransmitter system as the GABA/glutamate system may be related to cognitive and affective integration deficits, such as those seen in bipolar disorder. Oscillatory responses to both target and non-target stimuli are manifestations of working memory processes. Therefore, the coherence decrease in response to both types of stimuli indicates inadequate connectivity between different parts of the brain during a cognitive process, in comparison to pure sensory signal processing. 6.7. Gamma event-related coherence remains unchanged in Alzheimer's patients Fig. 9 shows mean z coherence values for the gamma frequency range upon application of “simple light” stimuli for all electrodes. The significant differences observed between healthy subjects and Alzheimer's disease patients for delta, theta and alpha frequency ranges were not

6.5. What does the coherence change in pathology mean? According to the results in Fig. 8, patients showed bilaterallydiminished long-distance gamma coherence between frontal and temporal, as well as frontal and temporo-parietal regions, compared to healthy controls. However, no significant sensory-evoked coherence reduction was recorded in the patient group compared to the healthy controls. The coherence decrease in response to both stimuli suggests inadequate connectivity between different parts of the brain under cognitive load. The occurrence of large coherence decreases only under cognitive load, but not in response to simple sensory stimuli (Özerdem et al., 2011) is a major finding with regard to the welldocumented cognitive dysfunction across all states of bipolar disorder (Martinez-Aran et al., 2004). Based on previous magnetic resonance imaging studies, where structural abnormalities were displayed in the prefrontal cortex, medial temporal lobe and sub-cortical structures in bipolar disorder, Strakowski et al. (2005) suggested a diminished prefrontal modulation of subcortical and medial temporal structures within the anterior limbic network (e.g., amygdala, anterior striatum and thalamus) for bipolar disorder. Supportive of this, Chepenik et al. (2010) reported reduced negative correlation between ventral prefrontal cortex (vPFC) and amygdala in bipolar patients compared to healthy controls.

Fig. 9. Mean Z values of healthy control (red), untreated AD (green) and treated AD (blue) subjects for gamma frequency range upon simple light stimuli (“*” sign represents p b 0.01).

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observed for the gamma frequency range upon application of a cognitive paradigm (Fig. 10). When compared to healthy subjects, the Alzheimer's disease subjects had higher gamma response coherences upon application of “simple light” in a small number of electrode pairs (Fig. 9). Fig. 10 shows mean z coherence values. The comparison of result of Alzheimer's disease and bipolar disorder patients shows the effect of neurotransmitter GABA in long-distance gamma coherence. In Alzheimer's disease there are clear reductions in event related coherences in alpha, theta and delta frequency bands (Başar et al., 2010). 7. A review of gamma activity in cognitive impairment 7.1. Steady-state auditory/visual evoked oscillations in schizophrenia patients Several paradigms are used in studies of evoked/event-related oscillations in schizophrenia. One of the most commonly used is the auditory or visual steady-state paradigm (Brenner et al., 2009). Most auditory steady-state studies used 40-Hz auditory tones, for which schizophrenia patients showed reduced power in 40-Hz responses to 40-Hz auditory tones. Furthermore, schizophrenia patients showed reduction in phaselocking factor (PLF) across trials for 40-Hz response to 40-Hz auditory tones (Brenner et al., 2003; Light et al., 2006; Hamm et al., 2011; Kwon et al., 1999; Krishnan et al., 2009; Maharajh et al., 2010; Mulert et al., 2011; Spencer et al., 2008b, 2009; Teale et al., 2008; Vierling-Claassen et al., 2008; Wilson et al., 2008). Kwon et al. (1999) demonstrated that schizophrenia patients had selectively-reduced averaged evoked-EEG power in response to 40-Hz auditory stimulation, but normal power responses to 20-Hz and 30-Hz stimulation. Brenner et al. (2003) subsequently analyzed auditory steady-state responses (ASSR) in a combined group of 21 subjects with schizophrenia or schizoaffective disorder, 11 subjects with schizotypal personality disorder, and 22 non-psychiatric comparison subjects. The authors reported that the schizophrenia and schizoaffective disorder groups exhibited decreased power compared to the schizotypal personality disorder and non-psychiatric comparison groups. Accordingly, the authors concluded that deficit may reflect less efficient local neural synchronization to external stimuli in the sensory cortex or in thalamic-sensory oscillations.

Fig. 10. Mean Z values of healthy control (red), untreated Alzheimer's disease (green) and treated Alzheimer's disease (blue) subjects for gamma frequency range upon target stimuli.

Light et al. (2006) analyzed schizophrenia patients (n = 100) and non-psychiatric subjects (n = 80) undergoing auditory steady-state event-related potential testing. They also found that patients had reductions in both evoked power and phase-synchronization in response to 30-Hz and 40-Hz stimulation, but a normal response to 20-Hz stimulation. Light et al. (2006) concluded that schizophrenia patients have frequency-specific deficits in the generation and maintenance of coherent gamma-range oscillations, reflecting a fundamental degradation of the basic integrated neural network activity. Spencer et al. (2008b) included 16 first-episode schizophrenia patients, 16 first-episode affective disorder patients (13 with bipolar disorder), and 33 healthy control subjects. The study used 20-, 30-, and 40-Hz binaural click trains as stimuli, and analyzed ASSR phase-locking and evoked power. It was reported that, at 40-Hz stimulation, schizophrenia patients and affective disorder patients had significantly reduced phaselocking compared with healthy control subjects. This deficit was more pronounced over the left hemisphere in schizophrenia patients. Evoked power at 40 Hz was also reduced in the patients compared with healthy controls. At 30-Hz stimulation, phase locking and evoked power were reduced in both patient groups. The 20-Hz ASSR did not differ between groups, but phase locking and evoked power of the 40-Hz harmonic of the 20-Hz ASSR were reduced in both schizophrenia patients and affective disorder patients. Phase-locking of this 40-Hz harmonic was correlated with total positive symptoms in schizophrenia patients. Spencer et al. (2009) further analyzed 40-Hz auditory steady-state responses in schizophrenia patients. These authors examined whether the 40-Hz auditory ASSR generated in the left primary auditory cortex was positively correlated with auditory hallucination symptoms in schizophrenia. They reported that left-hemisphere-source phaselocking factor in schizophrenia was positively correlated with auditory hallucination symptoms, and was modulated by delta phase. Accordingly, the results of Spencer et al. (2008b, 2009) and of other groups (Teale et al., 2008; Oribe et al., 2010) suggest that the reduction in 40-Hz auditory steady-state evoked power of schizophrenia subjects may be more pronounced for the left hemisphere generators. Oribe et al. (2010) reported that schizophrenia subjects showed delayed evoked neural oscillations and phase-locking to speech sounds, specifically in the left hemisphere. Studies analyzing steady-state responses indicate reduction of gamma response oscillations not only in EEG but also in MEG. Teale et al. (2008) analyzed magnetoencephalographic (MEG) recordings to estimate the phase and amplitude behavior of sources in primary auditory cortex in both hemispheres of schizophrenic and comparison subjects. These authors evaluated both ipsi- and contralateral cases using a driving (40-Hz modulated, 1 kHz carrier) and a non-driving (1 kHz tone) stimulus. Schizophrenic subjects showed reduced phaselocking factor and evoked source strength for contralateral generators responding to the driving stimulus in both hemispheres. For the pure tone stimulus, only the left hemisphere phase-locking factors in the transient window were reduced. In contrast, subjects with schizophrenia exhibited higher induced 40-Hz power in response to both stimulus types, consistent with the reduced phase-locking factor findings. Maharajh et al. (2010) used whole-head magnetoencephalography (MEG) to detect ASSR from both hemispheres in schizophrenia patients and control counterparts. The results indicated reduced phase-synchronization of the ASSR and the stimulus reference signal in schizophrenia patients compared to control subjects, in addition to reduced inter-hemispheric phase-synchronization between contralateral and ipsilateral hemispheric responses in schizophrenia patients. In a recent paper, Hamm et al. (2011) demonstrated that schizophrenia patients had reduced MEG gamma response to 40-Hz stimuli in the right hemisphere. Furthermore, schizophrenia showed normal beta range ASSRs (20 Hz) but reduced gamma range entrainment bilaterally at the harmonic (40 Hz). Wilson et al. (2008) had also reported that gamma power was significantly weaker, and peaked later, in adolescents with psychosis relative to their normally-developing peers. However, it

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should be noted that not all the patients in their study were schizophrenia patients. The authors used a mixed subject group with psychosis (3 patients diagnosed with schizoaffective disorder, 3 with bipolar I disorder, and 4 schizophrenia patients). Although most studies on auditory steady-state stimuli indicated reduced gamma responses, Hong et al. (2004) reported some contradictory results. These authors tested a group of first-degree relatives of schizophrenic probands with schizophrenia spectrum personality symptoms, and a group of schizophrenic patients, to examine whether individuals with increased tendency towards schizophrenia have reduced gamma synchronization. These authors reported that relatives with schizophrenic spectrum personality symptoms had reduced power at 40-Hz synchronization compared to normal controls. Previous findings of reduced steady-state gamma band synchronization in schizophrenic patients were not directly replicated in their study. Patients as a group did not significantly differ from controls, but patients taking new-generation antipsychotics had significantly enhanced 40-Hz synchronization compared to patients taking conventional antipsychotics. Riečanský et al. (2010) analyzed phase-locking of neural responses in schizophrenia upon application of steady-state gamma-frequency (40 Hz) photic stimulation. Compared with healthy control subjects, patients showed higher phase-locking of early evoked activity in the gamma band (36–44 Hz) over the posterior cortex, but lower phaselocking in theta (4–8 Hz), alpha (8–13 Hz), and beta (13–24 Hz) frequencies over the anterior cortex. Among the visual steady-state studies in schizophrenia, only Krishnan et al. (2005) and Riečanský et al. (2010) employed a frequency higher than 30 Hz. Krishnan et al. (2005) reported no significant difference between patients and healthy subjects upon application of photic driving at 40-Hz photic stimuli. However, Riečanský et al. (2010) indicated that, compared with healthy control subjects, patients showed higher phase-locking of early evoked activity in the gamma band (36–44 Hz) over the posterior cortex. In their study, Riečanský et al. (2010) suggested that this difference was due to the different methodologies used in these two different studies. In the study of Riečanský et al. (2010), significant group differences were observed only within a short time period following the onset of visual stimulation, whereas Krishnan et al. (2005) did not analyze the temporal dynamics of the evoked oscillations.

7.2. Somatosensory/auditory/visual sensory evoked oscillations in schizophrenia patients Başar-Eroğlu et al. (2011) investigated gamma oscillations during auditory sensory processing, and reported that averaged gamma response did not differ between schizophrenia and healthy controls. However, at the single-trial level, auditory stimuli elicited higher gamma responses at both anterior and occipital sites in patients with schizophrenia compared to controls. Başar-Eroglu et al. (2008) used a simple visual evoked potential and a visual oddball paradigm to investigate discrepancies in various frequency components in patients with schizophrenia. They found that patients showed higher alpha poststimulus amplitude enhancement and phase-coupling than healthy controls in the early time windows for all conditions (VEPs, non-target and target) at fronto-central sites, whereas the healthy group only showed this effect over occipital locations. Arnfred et al. (2011) analyzed proprioceptive beta and gamma responses in schizophrenia patients and healthy controls. They demonstrated that, when hand posture was disturbed by increased load, the schizophrenia patients demonstrated generally attenuated amplitude of contra-lateral high-frequency (18–45 Hz) activity in the 40–120 ms latency range. On the other hand, frontal beta activity in the 100–150 ms time period and lower frequency range (14–24 Hz) did not differ across any of the groups.

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7.3. Application of oddball paradigm Haig et al. (2000) examined gamma response amplitudes upon application of auditory oddball stimuli in medicated schizophrenics and healthy controls. Significant differences were observed between groups in the amplitude of the second post-stimulus peak in gamma activity in targets. The results indicated amplitude reduction of gamma response oscillations in schizophrenia patients compared to healthy controls over the left hemisphere in frontal sites, and an increase in right hemisphere and parieto-occipital sites. There were no significant between-group differences in the first gamma peak, which occurred around stimulus onset. Slewa-Younan et al. (2004) reported that chronic schizophrenia subjects showed lower late-gamma phase-synchrony compared to healthy subjects during auditory oddball task processing. This reduction was most apparent in female patients. Furthermore, analysis of early-gamma phase-synchrony indicated that chronic schizophrenia subjects showed lower early-gamma phase-synchrony compared to healthy subjects over the left hemisphere. First-episode female patients showed a faster latency of early gamma activity when compared to male counterparts. This study showed the importance of testing for gender-based differences in subject responses. Gender differences in evoked oscillations exist even in simple visual sensory stimulation in healthy subjects, as reported previously by Güntekin and Başar (2007a). Gender difference in evoked oscillations was also shown in different modalities (Güntekin and Başar, 2007b; Jausovec and Jausovec, 2009a,b, 2010). Comparing chronic schizophrenia patients versus first-episode schizophrenia patients also may provide important findings. Furthermore, several studies demonstrated the importance of including two time periods in the analysis of gamma band (early gamma, late gamma) (Başar-Eroglu et al., 2009; Gallinat et al., 2004; Haig et al., 2000; Lee et al., 2001; Lenz et al., 2011; Slewa-Younan et al., 2004; Symond et al., 2005). Symond et al. (2005) used a conventional auditory oddball paradigm to study 40 first-episode schizophrenia patients and 40 age- and sex-matched healthy controls. The authors then examined the magnitude and latency of both early (gamma-1: 150 ms to 150 ms post-stimulus) and late (gamma-2: 200 ms to 550 ms post-stimulus) synchrony with multiple analysis of variance. First-episode schizophrenia patients showed decreased magnitude and delayed latency for global gamma-1 synchrony in relation to the healthy controls. In contrast, there were no group differences in gamma-2 synchrony. Reinhart et al. (2011) investigated the relationship between prestimulus gamma band activity, reaction times, and P300 amplitude upon application of an auditory oddball paradigm. The authors reported that, in healthy controls, the single-trial pre-stimulus gamma power was positively correlated with reaction times. Furthermore, in healthy controls, average P300 amplitude was positively correlated with average, pre-stimulus gamma power; however, in schizophrenia patients, neither reaction times nor P300 amplitude were related to pre-stimulus gamma power. Accordingly, the authors concluded that their results suggested a breakdown in the preparatory brain state in schizophrenia patients. Başar-Eroğlu et al. (2011) investigated evoked gamma oscillations upon application of auditory oddball paradigm. These authors found that, in patients with schizophrenia, the target detection, compared to passive listening to stimuli, was-related to increased single-trial gamma power at frontal sites. Furthermore, averaged gamma response did not differ between schizophrenia and healthy controls. Accordingly, the authors emphasized the importance of considering single-trail gamma response analysis. Table 1 summarizes the results from studies of gamma frequency band in schizophrenia patients upon application of different stimuli. The results are reviewed in chronological order.

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Table 1 The results of studies of schizophrenia patients in gamma frequency band upon application of different stimuli. The results are reviewed in chronological order. Gamma Kwon et al. (1999) Haig et al. (2000)

Auditory steady-state

Evoked power

Auditory oddball

Amplitude of EROs

Auditory oddball

Evoked power

Auditory steady-state

Evoked power

Visual masking task

Evoked power

Auditory oddball

Phase locking

Auditory oddball

Evoked power (WT)

Hong et al. (2004)

Auditory steady-state

Evoked power

SlewaYounan et al. (2004) Spencer et al. (2004) Johannesen et al. (2005) Wynn et al. (2005) Symond et al. (2005)

Auditory oddball

Phase locking

Gestalt stimuli

Evoked power (WT)

Auditory click

Evoked power

Negative symptoms correlated with decreased gamma responses, whereas a significant increase in gamma amplitudes was observed during positive symptoms such as hallucinations. Reduced gamma power in the response following the first auditory click.

Backward masking task

Evoked power

Patients showed overall lower gamma activity.

Auditory oddball

Synchrony

Stimulus–response compatibility task. Auditory steady-state

Evoked power

Schizophrenia patients showed decreased magnitude and delayed latency for global Gamma-1 (0–150 ms) synchrony in relation to healthy comparison subjects. By contrast, there were no group differences in Gamma-2 (200–550 ms) synchrony. Controls, but not patients, showed increased induced gamma band activity for the incongruent condition. Reduced evoked power and phase-synchronization in response to 30–40-Hz stimulation.

Lee et al. (2001) Brenner et al. (2003) Green et al. (2003) Lee et al. (2003) Gallinat et al. (2004)

Cho et al. (2006) Light et al. (2006) Başar-Eroğlu et al. (2007) Bucci et al. (2007) Ferrarelli et al. (2008) Flynn et al. (2008) Pachou et al. (2008) Roach and Mathalon (2008) Spencer et al. (2008a) Spencer et al., 2008b Teale et al. (2008)

VierlingClaassen et al. (2008) Haenschel et al. (2009) Krishnan et al. (2009) Spencer et al. (2009)

N-back task

Participants underwent three to five TMS/high-density EEG sessions at various TMS doses. Auditory oddball

Evoked power and phase-synchronization EROs amplitude

Gamma power event-related coherence Amplitude, synchronization, and source localization Phase locking

N-back task

Evoked power

Auditory oddball

Phase-locking factor (PLF)

Visual and auditory oddball tasks. Standard stimuli were analyzed 20-, 30-, and 40-Hz binaural click trains

Evoked power phase-locking (WT)

Steady-state auditory tones

Evoked power phase-locking (WT) MEG phase-locking factor; mean evoked- and induced amplitude

Steady-state auditory tones

Evoked power

Working memory task

Evoked and induced power

Steady-state auditory tones from 5 to 50 Hz

Evoked power phase-locking factor

Steady-state auditory tones (40 Hz)

Evoked power phase-locking (WT)

Schizophrenia patients had selectively-reduced averaged evoked-EEG power in response to 40-Hz auditory stimulation. For targets: reduced gamma response at left hemisphere and frontal side; increased gamma response in right hemisphere and parieto-occipital sides. For non-targets: widespread reduction in gamma response. Schizophrenia patients had reduced early evoked gamma amplitude compared to healthy subjects. SZ patients exhibited lower power in response to steady-state auditory stimuli compared to non-psychiatric subjects. Event-related gamma activity concurrent with backward masking reflected increased gamma activity in healthy subjects but not for SZ patients. SZ patients had decreased frontal (Gamma-1: −150–150 ms; Gamma-2: 200–550 ms) and left hemisphere (Gamma-1) synchrony. Increased posterior synchrony (Gamma-2: 200–550 ms). In response to standard stimuli, early evoked gamma-band responses (20–100 ms) did not show significant group differences. Schizophrenic patients showed reduced evoked gammaband responses in a late latency range (220–350 ms), particularly after target stimuli. Patients, as a group, did not significantly differ from controls; patients taking newgeneration antipsychotics had significantly enhanced 40-Hz synchronization compared to patients taking conventional antipsychotics. Chronic schizophrenia subjects showed lower gamma phase synchrony compared to healthy subjects. This reduction was most apparent in chronic female patients.

High-amplitude gamma oscillations remained constant in patients, irrespective of task difficulty. Induced gamma power and event-related coherence was observed in patients with non-deficit schizophrenia, but not in those with deficit schizophrenia. Relative to healthy controls, schizophrenia patients had a marked decrease in evoked gamma oscillations that occurred within the first 100 ms after TMS, particularly in a cluster of electrodes located in a fronto-central region. In first-episode patients, gamma-phase synchrony was generally increased during auditory oddball task processing, especially over left centro-temporal sites in 800 ms post-stimulus time window. Compared to controls, patients showed reduced activity at temporal sites in the gamma band. The results showed prominent gamma band phase-locking at frontal electrodes between 20 and 60 ms following tone onset in healthy controls that was significantly reduced in patients with schizophrenia. Visual-evoked gamma oscillation phase-locking at occipital electrodes was reduced in SZ compared with HC. In contrast, auditory-evoked gamma oscillation phase-locking and evoked power did not differ between groups. At 40-Hz stimulation, SZ patients had significantly reduced phase-locking compared with healthy controls. Evoked power at 40 Hz was also reduced in patients compared with HC. At 30-Hz stimulation, phase-locking and evoked power were reduced in patient groups. Schizophrenic subjects showed reduced phase-locking in both hemispheres. For the pure tone stimulus, only the left hemisphere PLFs in the transient window were reduced. In contrast, subjects with schizophrenia exhibited higher induced 40 Hz power in response to both stimulus types, consistent with the reduced PLF findings. Reduced 40-Hz, but increased 20-Hz response in SZ patients compared to healthy controls.

During the late maintenance period, patients showed an increase in induced gamma band amplitude in response to WM load 2 and failed to sustain induced gamma band activity for the highest WM load. Patients with SZ showed broad band reductions in both PLF and MP. Induced gamma (around 40 Hz) response to unmodulated tone stimuli was also reduced in SZ.

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Table 1 (continued) Gamma

Barr et al. (2010) Leicht et al. (2010) Oribe et al. (2010) Maharajh et al. (2010) White et al. (2010) Başar-Eroğlu et al. (2011)

N-back task

Evoked power

Auditory reaction task.

Evoked power (WT)

Speech sounds and pure tones

MEG Evoked Power (WT)

Steady-state auditory tones (40 Hz)

MEG, source localization, spatial and temporal filtering

Vibrotactile somatosensory task Auditory sensory and auditory oddball

EEG–fMRI evoked power

Hall et al. (2011) Hamm et al. (2011)

Auditory oddball

Evoked power

Steady-state auditory tones

MEG inter-trail phase coherence

Lenz et al. (2011) Mulert et al. (2011)

Auditory oddball

Evoked power (WT)

Steady-state auditory tones

Loreta

Sharma et al. (2011)

Choice-reaction task

Event-related coherence

Evoked power (WT)

PLF and evoked power were reduced in SZ at fronto-central electrodes. Left hemisphere source PLF in SZ was positively correlated with auditory hallucination symptoms, and was modulated by delta phase. SZ patients showed increased evoked frontal gamma oscillatory activity, which was most pronounced in the 3-back compared to healthy subjects. Patients with schizophrenia showed a significant reduction of power and phase-locking of the early auditory-evoked GBR. SZ subjects showed delayed evoked oscillations and phase-locking to speech sounds, specifically in the left hemisphere. Results indicated reduced phase-synchronization of the ASSR and the stimulus reference signal in SZ patients compared to control subjects, in addition to reduced inter-hemispheric phase synchronization between contralateral and ipsilateral hemispheric responses in SZ patients. In the healthy group, but not the patients, significant correlation was observed between the strongest component and evoked gamma power. At the single-trial level, auditory stimuli elicited higher gamma responses at both anterior and occipital sites in patients with schizophrenia compared to controls. In patients with schizophrenia, target detection compared to passive listening to stimuli was-related to increased single-trial gamma power at frontal sites. Reduced event-related gamma power during an auditory oddball task in schizophrenia patients and their unaffected identical twins. Schizophrenia patients had reduced gamma response to 40-Hz stimuli in right hemisphere. SZ showed normal beta range ASSRs (20 Hz) but reduced gamma range entrainment bilaterally at the harmonic (40 Hz). Schizophrenic patients presented decreased gamma power in both deviant and target stimuli compared to healthy participants. The major finding was reduced phase synchronization in schizophrenia only between the left and right primary auditory cortex. A positive correlation between auditory hallucination symptom scores and interhemispheric phase synchronization was present only for primary auditory cortices. Reduced event-related coherence in SZ patients during time intervals (0–250 ms poststimulus).

8. Superposition of delta and gamma event-related oscillations in schizophrenia patients during a complex working memory task Başar-Eroğlu et al. (2007) applied a more differentiated event-related response paradigm in comparison to oddball P300 paradigm. In this paradigm, three tasks with gradually increasing working memory (WM) tasks were applied to healthy subjects and schizophrenia patients. Fig. 11 shows grand-average ERO in the delta frequency range and the gamma-band filtered corresponding oscillatory activities during three experimental tasks in patients and controls. The methods for application of three different tasks and the results related to tasks in healthy subjects have already been published by Schmiedt et al. (2005). The

measurements consisted of three tasks: control task, easy working memory (WM) task, and difficult WM task. In healthy subjects, the gamma amplitude increased gradually from control task to difficult WM task. The event-related gamma activity differed significantly between tasks, indicating higher gamma amplitude values during the hard WM task compared to the control task. The ERPs were not filtered in the delta frequency range. However, even without pass band filtering WM tasks trigger in schizophrenic subjects highly diminished slow oscillatory response in the delta frequency range in comparison to healthy subjects. In contrast, the post-stimulus gamma activity was higher in schizophrenia patients than in healthy subjects, regardless of the task (Fig. 11, lower panel).

Fig. 11. Grand-average event-related oscillations in healthy controls (left upper panel) and in schizophrenia patients (right upper panel) during tasks with varying difficulty in working memory. T = 0 represents the stimulus onset. Lower panel shows grand-average gamma activities corresponding to the upper panel (modified from Başar-Eroğlu et al., 2007).

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Fig. 12. Upper panel represents pre-stimulus RMS gamma values in control subjects and in schizophrenia patients in the three tasks. Lower panel shows post-stimulus maximal gamma amplitudes (modified from Başar-Eroğlu et al., 2007).

These results show increases of evoked and induced changes. Enhanced gamma activities can be observed in both pre- and poststimulus time windows. The results in control subjects further suggest a task-related allocation of attentional processes with increased WM-load. In contrast, the patients did not show a modulation of gamma activity with varying task demands. Fig. 12 represents pre and post stimulus RMS gamma values in control subjects and in schizophrenia patients in the three different tasks with histograms. These results could be interpreted as a consequence of impairment in focused attention. A possible interpretation is that higher gamma activity in patients could be related to cortical hyperexcitability, as suggested by Spencer et al. (2004) and Eichhammer et al. (2004). The strategy referenced in Fig. 11 is important, since the alteration of gamma activity in schizophrenia is not manifested only in reduced gamma responses. However, during a working memory task paradigm, patients showed sustained increased gamma activity, whereas healthy subjects showed differentiation related to the varying difficulty of the working memory task. Most studies on auditory steady-state evoked gamma responses showed reduced gamma response oscillations in schizophrenia patients compared to healthy controls. To our knowledge, there is only one study in which previous findings of reduced steady-state gamma band synchronization in schizophrenic patients were not directly replicated (Hong et al., 2004). On the other hand, event-related gamma responses in schizophrenia patients in comparison to healthy subjects show contradictory results in cognitive paradigms. In auditory oddball paradigms, previous authors mostly evaluated event-related gamma responses in two different time windows (early and late time window). Some studies showed that early evoked gamma-band responses did not show significant group differences. However, schizophrenic patients showed reduced evoked gamma band responses in late latency range (Gallinat et al., 2004;

Haig et al., 2000). Other studies (Lee et al., 2001; Slewa-Younan et al., 2004; Symond et al., 2005; Lenz et al., 2011) reported that schizophrenia subjects showed lower early-gamma phase-synchrony compared to healthy subjects. Some studies reported increased gamma response in schizophrenic subjects compared to healthy controls upon application of an auditory paradigm. Başar-Eroğlu et al. (2011) reported that passive listening to stimuli was related to increased single-trial gamma power at frontal sites. Flynn et al. (2008) reported that, in first-episode patients, gamma phase synchrony was generally increased during auditory oddball task processing, especially over left centro-temporal sites in the 800 ms post-stimulus time window. Further research is needed to make robust conclusions on gamma response in auditory oddball paradigm in schizophrenia. 8.1. Non-gamma frequency responses and connectivities As explained in previous sections, there is an important interplay between transmitters and diseases such as Alzheimer, bipolar disorders, and schizophrenia. In such diseases, the oscillations are impaired or are irregular, because of the reduced release of transmitters such as acetylcholine and GABA. Furthermore, breaks of coherence in the alpha and gamma frequency ranges are also accompanied by various types of pathologies. The whole-brain work is highly altered in cases of cognitive impairment, as manifested by several types of diseases. Fig. 13 describes the changes in oscillatory responses, not only in gamma but also in alpha, beta, theta and delta frequency ranges in Alzheimer and bipolar patients. The illustration includes findings related to patients before and after medication. Fig. 13 is a type of short concluding scheme of limited results; it does not comprehend coherence analyses that open deeper horizons. The most important neurotransmitter in both diseases is briefly explained on the right side of Fig. 13.

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The AD patients were medicated with cholinesterase inhibitor and the bipolar patients with valproate. 9. Reasonings and suggestions for understanding gamma activity Taking into consideration the results discussed in the present review, the following section outlines a chain of “Reasonings and Suggestions”, based on empirical evidence. 1. Gamma activation is a fundamental process (or fundamental operator) in the sensory-cognitive communication and functioning in the whole brain. Further, gamma activity is linked to vegetative functions, as indicated by the work of Freeman. 2. Gamma activity and gamma response are also measured in invertebrate ganglia. 3. Each oscillatory activity represents multiple functions; vice versa, each function is represented by multiple oscillations. 4. Results of bi-sensory stimulation clearly indicate that gamma responses are selectively distributed throughout the cortex, depending on the modality of stimulation. When auditory and visual signals are jointly applied, gamma enhancements are observed in all areas, whereas pure sensory signals elicit responses only in specific sensory areas (Figs. 1–5). 5. Visual event-related coherences are high in comparison to simple visual evoked coherences in healthy subjects (compare Figs. 8–10). This can be interpreted as indicating that, during cognitive processes, long-distance connectivity is increased upon cognitive tasks. Therefore, gamma response coherence can be considered as an important

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manifestation of cognitive information processing in whole-brain work. 6. The observation related to increased long-distance connectivity in the gamma band during cognitive processing versus sensory processing opens a new research avenue for understanding of processes of perception, attention, memory, and learning (Desimone, 1996). The disruption of long-distance connectivity in the gamma band in neuropsychiatric diseases with cognitive impairment will probably elucidate, in future, the functional correlates of gamma activity in differentiated functional research. Gamma connectivity is highly decreased in bipolar disorder, whereas almost no change in gamma connectivity is observed in Alzheimer's disease. 7. Web of oscillations and neurotransmitters in neuro-pathology: The pathological level is emphasized in this review, since it can be extremely influential in modulating brain oscillations—both spontaneous and evoked. Moreover, the medication of patients by means of pharmacological agents containing various types of transmitters can help to reduce pathologies and greatly assist in returning oscillatory responses to near-normal levels (Özerdem et al., 2013; Yener et al., 2007, 2008; Güntekin et al., 2008). Moreover, as the results of Porjesz and Rangaswamy (2007) and Rangaswamy et al. (2002) underline, pathologies, genetic factors, and the application of transmitters all influence the results in such a way that the present knowledge can be extended to the understanding of brain oscillations and cognitive processes. 8. After reviewing the reports cited in the present review, it becomes obvious that pathology (cognitive disorders, diseases) and medication, (which influence the transmitter release) entirely change the

Fig. 13. General remarks and summary of evoked/event-related studies of schizophrenia, bipolar disease and Alzheimer patients.

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understanding and overall picture of the cognitive processes. Medication (modulation of transmitters) can partly reduce the cognitive impairment of patients. Additionally, medication helps to reduce pathological deformation of electrical signals. Oscillations within a unique frequency window must be analyzed jointly with multiple oscillations in order to reliably describe pathological cases. The release of transmitters also selectively influences brain oscillations (see Table 1). To obtain a true picture of the oscillation processes in pathology, the frequency analysis has to be performed separately in medicated and non-medicated patients. As shown by the results in Table 1, it is essential to perform analyses separately, preceding and following medication. An ensemble of parameters as spontaneous gamma, event-related gamma responses and coherences may, in the future, be used as clinical biomarkers of cognitive impairment in schizophrenia, Alzheimer's disease, and bipolar disorders. In turn, results related to the attenuation or disappearance of gamma activity in clinical studies may be useful for topological component analysis of cognitive functions such as working memory, perception, and learning deficits. Emotion and functions related to emotional events play a considerable role in integrative brain function, as described by Le Doux (1999) and Solms and Turnbull (2002). Emotional inputs considerably influence event-related alpha responses. In order to achieve a profound functional analysis by means of oscillations, it is suggested to work—ideally—with a broad strategy incorporating sensory and cognitive stimulations. Measurements with only cognitive load before determining the sensory components may lead to restricted interpretations. All memory processes are interwoven with phyletic memory and perception (Fuster, 1995, 1997; Goldman-Rakic, 1996, etc.). We also have to note that not only the parameters of oscillatory patterns but the selective connectivity of gamma oscillations between various structures of the brain is vital for brain functioning when studying coherences in the healthy adult brain, and in clinical disorders. In earlier conclusions Başar (1980, 1999) and Başar-Eroglu et al. (1996b) used the expression universal operator for gamma activity. Further, gamma, is induced by different stimuli or tasks, and is related to several cognitive functions. Fries (2009) stated that neuronal gamma-band synchronization is found in many cortical areas. According to Fries, it appears as if many different gamma-band synchronization phenomena sub-serve many different functions. Thus, this author also argues that gamma-band synchronization is a fundamental process that sub-serves an elementary operation of cortical computation, which is in accordance with the findings of Başar's group. However, Başar (2006) indicated that gamma band synchronization was also measured in many sub-cortical areas as processing in many cognitive strategies during whole-brain operation.

10. Conclusion It initially appears extremely difficult to derive a reliable general theory of gamma from the various results, models, and hypotheses in the present review. Instead, we propose that it would be more reasonable to present highlights, results, and exclusion principles from the results with the aim of excluding somewhat controversial trends, at least in order to avoid errors. References Adrian, E.D., 1942. Olfactory reactions in the brain of the hedgehog. The Journal of Physiology 101, 459–473. Arnfred, S.M., Morup, M., Thalbitzer, J., Jansson, L., Parnas, J., 2011. Attenuation of beta and gamma oscillations in schizophrenia spectrum patients following hand posture perturbation. Psychiatry Research 185 (1–2), 215–224.

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