Review of Schizophrenia Research Using MEG

  • Donald C. RojasEmail author
Living reference work entry


Schizophrenia is a severe form of mental illness characterized by hallucinations, delusions, changes in affect, and serious cognitive and social dysfunction. MEG has made contributions to our understanding of the disorder in many areas, although the most significant contributions have been in four areas. First, MEG has suggested that schizophrenia may be characterized by alteration in cerebral lateralization, particularly in auditory evoked responses. Second, auditory evoked responses suggest significant impairment in early auditory perceptual processes. Third, in one of these sensory deficits in particular, the underlying source configuration of sensory gating abnormalities has provided us with information about the localization of the deficit that was not apparent from EEG studies. Finally, spectrotemporal abnormalities are evident in the disorder, particularly for low-frequency oscillations, and MEG has contributed to our understanding of the regional distribution of those anomalies. These and other interesting, but less well-characterized electrophysiological phenomena studied using MEG methods in schizophrenia and related psychopathologies are reviewed in this chapter.


Schizophrenia Bipolar disorder Psychosis Cerebral asymmetry Sensory gating Delta Alpha Beta Gamma M100 M50 

1 Introduction to Schizophrenia

Schizophrenia is a serious mental disorder characterized behaviorally by symptoms indicating a disconnection from reality as well as significant cognitive and social disability. Although it had been previously described, the Swiss psychiatrist Eugen Bleuler first named the disorder schizophrenia in 1911 (Bleuler 1911), the Greek origin of the word schizophrenia denoting “split mind.” Bleuler’s use of this term was meant to suggest a split from reality in the affected individual rather than a split in personalities, as is often unfortunately assumed among laypersons when thinking about the meaning of the disorder’s name. Schizophrenia has a worldwide prevalence of 1% (Gottesman 1991), which makes it more prevalent than other nervous system disorders such as Alzheimer’s disease, multiple sclerosis, and Parkinson’s disease.

Symptoms in schizophrenia are commonly divided into positive and negative symptoms. The positive symptoms of schizophrenia, those typically not present in healthy individuals, include hallucinations and delusions, disorganized behavior, and disorganized or illogical speech. Negative symptoms, which are those in which there is an absence of a normal behavior, include flattened affect, alogia, and avolition. These symptoms are codified in the Diagnostic and Statistical Manual of Mental Disorders, fourth edition (American Psychiatric Association 1994), and International Classification of Diseases, version 10 (World Health Organization 1992).

The etiology of schizophrenia is not well understood despite years of dedicated research into the underlying biological and environmental contributions. It is clear that schizophrenia has a significant genetic component, evidenced by twin studies demonstrating 50% concordance in monozygotic twins and 17% concordance in dizygotic twins (Gottesman 1991). Although there are a number of mutations that convey risk for the disorder, there are few if any genes with large effects identified. Schizophrenia may be a complex polygenic disorder with many risk genes of small effect and/or a collection of disorders with shared symptomatology but distinct etiologies perhaps with convergence on particular molecular pathways (Gejman et al. 2011). There are also clearly associated environmental factors, including season of birth effects, perinatal/obstetric risks, and associations with viral infection during pregnancy (Tsuang 2000).

Schizophrenia treatment remains essentially unchanged over the past 30 years of drug development. The revolution of the first generation of antipsychotic medications in the 1970s was followed by a subsequent development of so-called second generation, or atypical, antipsychotic medications. Despite differences in receptor affinity profiles, particularly with respect to serotoninergic, 5-HT2A-receptor antagonism, a common mechanism for clinical efficacy shared by all currently approved antipsychotic medications is antagonism of the D2 dopamine receptor. Despite early marketing claims, modern studies have failed to find significant differences in efficacy between first- and second-generation drugs (Lieberman and Stroup 2011), and there has been a call to abandon the terminology altogether (Tyrer and Kendall 2009). Although such medications are generally effective for treatment of positive symptoms in the disorder, few if any have shown promise in treating the cognitive deficits and negative symptoms, which is important since they are more closely associated with prognosis (Rabinowitz et al. 2012; Green 2006). Thus, the search for effective pharmacological and behavioral treatments in schizophrenia has shifted toward cognitive disability.

2 Historical Overview of MEG Applications in Schizophrenia Research

The first MEG paper published on schizophrenia was in 1988 (Reite et al. 1988), which focused on localization of the M50 auditory evoked magnetic field component in six men with schizophrenia. A single-channel, second-order gradiometer was used, combined with simultaneous EEG recordings from the scalp vertex. Mapping the topography of the field distribution, which took several days of work for each subject, was accomplished by employing a grid outlined on a swim cap and 28–43 serially repeated measurements of 128 trials per location with the gradiometer positioned over each grid point. There was no comparison group in the study, so it served primarily as a proof of concept study that MEG could be applied to a severely impaired patient population. The first published paper with a direct comparison between schizophrenia patients and a control group appeared the following year, in 1989, from the same group (Reite et al. 1989). Somewhat surprisingly, the observations from these earlier MEG technologies have generally replicated using more modern methods and machines (see Sect. 3.1).

From those earlier studies, MEG publications on schizophrenia slowly increased in the 1990s and are currently showing a strong increasing trend (see Fig. 1), probably reflecting the wider installed MEG system base as well as the relative ease of conducting whole head, high-density MEG recordings, compared to the earlier days of limited channel arrays. The increase in publications using MEG also seems to track the larger overall trend of increasing numbers of published papers in schizophrenia.
Fig. 1

Studies published by year involving schizophrenia and MEG. A search of PubMed using the terms “magnetoencephalography,” “MEG,” “neuromagnetism,” or “neuromagnetic” and “schizophrenia,” “schizoaffective disorder,” “hallucinations,” or “psychosis” was performed (line labeled MEG + schizophrenia). This was compared to all schizophrenia publications over the same time period

3 Evoked Magnetic Fields in Schizophrenia

3.1 Cerebral Lateralization of the Location of Auditory and Somatosensory Evoked Fields

Some of the earliest studies employing MEG in schizophrenia focused on an asymmetry between the left and right hemisphere location of the auditory components of the evoked response. The M100 (also termed the N100 m) is generated within the auditory cortices on the supratemporal plane (Pantev et al. 1998; Reite et al. 1994), and its location is generally relatively more anterior in the right compared to the left hemisphere (Nakasato et al. 1995; Mäkelä et al. 2004). Reite et al. (1989) reported in a preliminary study of six male patients and six controls that the schizophrenia group exhibited reduced interhemispheric asymmetry compared to controls. Although the original study used repeated measurements of a single-channel MEG instrument, the finding has been replicated using larger array devices, both by the original research group and independently by other investigators using different MEG devices (Tiihonen et al. 1998; Rojas et al. 2002; Rockstroh et al. 2001; Edgar et al. 2006; Reite et al. 1997). Reduced M100 asymmetry has been compared directly between patients with schizophrenia and those with schizoaffective disorder, with both patient groups exhibiting reduced asymmetry compared to controls, but these groups were not significantly different from each other (Teale et al. 2000).

Two studies have compared reduced M100 location asymmetry in schizophrenia directly to samples of persons with dyslexia, a developmental disorder defined by reading disability (Edgar et al. 2006; Heim et al. 2004). In both studies, reduced anterior-posterior asymmetry in both clinical groups was reported relative to control samples, suggesting that the asymmetry reduction might reflect a non-specific neurodevelopmental biomarker. Supportive of this interpretation, reduced asymmetry has also been observed in other neurodevelopmental disorders, including fragile X syndrome (Rojas et al. 2001) and autism (Rojas et al. 2008; Schmidt et al. 2009).

It has also been suggested that the reduced asymmetry in schizophrenia may be a finding specific to males (Reite et al. 1997; Rojas et al. 1997). However, other investigators examining gender differences have not observed changes in location in schizophrenia but have noted gender specific alterations in M100 dipole orientation instead (Hajek et al. 1997a,b). Gender differences, if any, may be important in schizophrenia because of the observation of later onset and possibly less severe psychopathology in women with the disorder (Goldstein 1988; Aleman et al. 2003).

The abnormality in asymmetry is not limited to source locations based on the M100 or even to auditory evoked field locations. The very first schizophrenia paper published suggested reduced asymmetry of the location of the auditory M50 source (Reite et al. 1988), and more recently there has been evidence published that the auditory-steady state source also exhibits this phenomenon in schizophrenia patients (Teale et al. 2003). Outside of the auditory cortex, reduced location asymmetry of the somatosensory M20 and M50 components has been described in schizoaffective disorder and schizophrenia, respectively (Reite et al. 1999b, 2003).

Reduced laterality of the location of auditory and somatosensory responses has also been examined in two studies of early-onset psychotic disorders including schizophrenia. Wilson et al. (2008) did not find significant differences in lateralization of the auditory steady-state response in children and adolescents with a heterogeneous sample of various early-onset psychoses. In a separate study, however, somatosensory M50 dipole location asymmetry was found to be reduced in study of children ages 8–16 years with various early-onset psychotic disorders including schizophrenia, mood disorders with psychotic features, and psychosis NOS (Wilson et al. 2007). In that study, the location asymmetry for the M50 dipole was left more anterior than right hemisphere for both groups, but this left to right shift was reduced in the psychotic group. Although the increased symptomatic heterogeneity in combined psychotic disorder samples may lead to increased variability in sources, a study in bipolar disorder, directly comparing currently euthymic patient samples with and without a history of psychosis, found that reversed somatosensory M20 anterior-posterior localization was specific to the patients with a positive history psychosis, operationally defined as a history of hallucination and/or delusions (Reite et al. 1999a). In contrast to healthy control subjects and nonpsychotic bipolar groups, both of which exhibited right hemisphere locations anterior to the left hemisphere locations, the psychotic bipolar group exhibited right hemisphere M20 locations posterior to the ones in the left hemisphere. This suggests that the dimension of psychosis rather than the specificity of the diagnosis is a key factor. The developmental trajectory of location lateralization for auditory and somatosensory cortices has not yet been studied, however, and more evidence is needed to define both the development and the symptom dimension associations. No studies have yet reported significant correlations between various symptoms of schizophrenia/psychosis and location asymmetry. Reduced M100 amplitude asymmetry to monaural stimulation, between the contralateral and ipsilateral responses, has also been reported (Rockstroh et al. 1998).

Evidence of altered cerebral lateralization in location of auditory and somatosensory function from MEG is part of a larger literature on changes in structural and functional lateralization in schizophrenia. For example, a meta-analysis of various aspects of lateralization in the schizophrenia indicates increased odds ratio of non-right-handedness, increased odds of reduced right-ear advantage in dichotic listening to consonant-vowel sounds, and increased odds of reduced asymmetry of brain structure in schizophrenia, especially in temporal lobe/Sylvian fissure regions, compared to controls (Sommer et al. 2001). It should be noted, however, that abnormality of the localization of function does not necessarily imply an underlying structural abnormality. In one study comparing locations of the auditory M100 to the location of Heschl’s gyrus, asymmetry (right anterior to left) in the location of Heschl’s gyrus was observed in both schizophrenia and control samples (Rojas et al. 1997). Although there were no significant differences between groups in anterior-posterior position of the structure, M100 location asymmetry was significantly different between groups (Rojas et al. 1997). MEG information on location of function may be additive, rather than simply a reflection of an underlying anatomical difference.

3.2 MEG Studies of Auditory Processing

Deficient auditory processing is consistently observed in behavioral studies of schizophrenia. Frequency-matching performance, for example, is commonly reported to be worse in subjects with schizophrenia than in comparison groups (Holcomb et al. 1995; Rabinowicz et al. 2000; Javitt et al. 2000). There is an extensive body of EEG and MEG research on impairment of the mismatch negativity (MMN) in schizophrenia (reviewed in Naatanen and Kähkönen 2009). Similar to the widely replicated reduction in MMN observed in schizophrenia patients using EEG, MEG studies of the magnetic analog (variously termed MMNm or MMF) have also revealed smaller mismatch responses in patients (Kircher et al. 2004; Kreitschmann-Andermahr et al. 1999; Pekkonen et al. 2002; Kasai et al. 2003; Jordanov et al. 2011).

Some MEG studies, however, have tended to capitalize more on source localization strategies than EEG studies, and some interesting results have emerged. Kircher et al. (2004) reported that for duration mismatch responses, schizophrenia patients were significantly less right lateralized compared to healthy controls. Pekkonen et al. (2002) found that while patients with schizophrenia had significantly reduced MMNm amplitudes in both hemispheres compared to control subjects, MMNm latency was only significantly delayed in the left hemisphere. Simple dipole analyses of MMNm, however, may not be as likely to succeed for individual patients with schizophrenia as with healthy control subjects, probably due to a reduction in signal strength in the patient group (Yamasue et al. 2004; Ahveninen et al. 2006). To avoid this, one study fixed the dipole location for the MMNm using a priori information on the location of the primary auditory cortex (Thonnessen et al. 2008). In this latter study, MEG and EEG mismatch responses were directly compared using the fixed dipole locations, and MEG sources outperformed the EEG sources in terms of significant group differences across a number of experimental manipulations (Thonnessen et al. 2008). In a recent study, Dima et al. (2012) examined connectivity and MMNm in schizophrenia, employing a dynamic causal modeling (Friston et al. 2003) approach to fixed dipole locations within primary auditory, secondary auditory, and inferior frontal cortices. Dima et al. (2012) reported an abnormal reversal of connectivity (i.e., reversal of information directional flow) between frontal and superior temporal sources during the MMNm. Whereas healthy individuals exhibited the predicted negative modulation of temporal lobe from frontal lobe (i.e., bottom up rather than top down), schizophrenia patients exhibited greater bottom-up modulation from the temporal lobe to frontal lobe.

MMNm studies have also been published concerning risk for schizophrenia and its genetics. Shin et al. (2009) studied 16 individuals at high risk for schizophrenia based on the presence of attenuated symptoms (i.e., the schizophrenia prodrome) and found that MMNm dipole amplitude was reduced in the right hemisphere and latency was prolonged, relative to 18 healthy controls. Ahveninen et al. (2006) examined MMN and MMNm in a twin design, including monozygotic twins discordant for schizophrenia (N = 10 pairs) and dizygotic twins discordant for schizophrenia (N = 13 pairs) as well as control MZ and DZ twin pairs. Although the EEG MMN component was significantly reduced in the schizophrenia patients and their unaffected twins, the MEG MMNm did not exhibit significant differences between groups, in contrast to the more recent study of Thonnessen et al. (2008), described above. Both EEG and MEG responses exhibited genetic influence relative to the degree of relatedness to schizophrenia (Ahveninen et al. 2006).

Aside from the MMNm component, other evoked magnetic components have been studied with respect to sensory representations and processing in schizophrenia. Two studies have examined tonotopy, or the spatial mapping of frequency to the auditory cortex, using the auditory M100 response (Rosburg et al. 2000b; Rojas et al. 2002). Both found evidence of frequency effects on M100 dipole location for healthy controls, similar to other MEG studies published using only healthy samples (Romani et al. 1982; Pantev et al. 1995). Although both studies also reported differences in the patient group, the specifics differed between studies. Rosburg et al. (2000b) reported frequency-dependent differences in location in the anterior-posterior coordinate, which were slightly greater in patients than controls in the right hemisphere but much greater in controls than in patients in the left hemisphere. In contrast, Rojas et al. (2002) found frequency differences in location on the medial-lateral coordinate for the M100, as well as a reduction in this difference, in both hemispheres, in patients with schizophrenia. Relative to the head coordinate systems used, Heschl’s gyrus, the nominal structural correlate of the primary auditory cortex, has an oblique angle. Frequency gradients along it may be anterior-posterior, medial-lateral, or both, depending on the specific anatomy. Future comparisons may benefit from an accounting of this variability by expressing location coordinates within an anatomically derived framework (Jordanov et al. 2010).

In addition to dipole location, several studies have examined auditory evoked field latency and amplitude in schizophrenia under various experimental manipulations. M100 amplitude is known to exhibit stimulus-specific refractoriness and habituation to repeated stimulation (Hari et al. 1982). Rosburg et al. (2000a) did not find differences in this behavior in 20 patients with schizophrenia when comparing latency and amplitude of the M100 to repeated stimulation over several trial blocks. Overall both controls and schizophrenia patients showed increased latency and decreased amplitude of the M100 as trial blocks increased. There was, however, a significantly higher degree of habituation in a small subgroup of patients taking clozapine, the dose of which correlated with amplitude habituation. As pointed out by the authors, clozapine may be more effective than other antipsychotics at relieving a deficit in rapid habituation termed sensory gating in schizophrenia (Adler et al. 2004). Yet another study used M100 refractory behavior to examine frequency-specific tuning of the M100 and found reduced frequency specificity of the habituation in M100 amplitude in schizophrenia patients (Rojas et al. 2007). Additional reported findings indicating an impairment of early auditory processes include earlier M50 responses (Pekkonen et al. 1999) and reduced amplitude of the M100 (Kreitschmann-Andermahr et al. 1999; Rojas et al. 2007; Edgar et al. 2012). Reduced M100 amplitude appears to be associated with thinner underlying auditory cortex, both in persons with schizophrenia (Edgar et al. 2012) and in subjects at high risk for the disorder based on having a first-degree relative and/or prodromal symptoms (Shin et al. 2012).

3.3 Sensory Gating

One of the most widely replicated and highly studied EEG evoked potential findings in schizophrenia is the so-called sensory gating deficit (Adler et al. 1982). Normally studied using the EEG auditory P50 response to closely spaced paired clicks, healthy individuals tend to exhibit reduced amplitude to the second click (i.e., gating), while individuals with schizophrenia do not exhibit suppression of the second click response amplitude (Patterson et al. 2008). It is sometimes observed that reduced amplitudes of responses to the first, rather than the second click, explain the usual gating ratio for P50 and M50-based sensory gating impairment in schizophrenia (Blumenfeld and Clementz 2001). Impaired sensory gating has been linked to mutations of the cholinergic alpha-7 receptor (CHRNA7) on chromosome 15 (Freedman et al. 2003).

MEG studies have added useful information to this extensive literature. EEG researchers commonly measure P50 sensory gating at vertex (Cz), referenced to linked mastoids or ears, and therefore have no information about lateralization of the response. Thoma et al. (2003) first reported that the sensory gating deficit appeared to be lateralized to auditory M50 sources in the left hemisphere. The left, but not right hemisphere gating in MEG, was correlated to the vertex P50 gating response. The lateralized left hemisphere M50 gating deficit correlates with negative symptoms (Thoma et al. 2005), attention and working memory deficits (Thoma et al. 2003; Smith et al. 2010), and long-term memory (Smith et al. 2010). A recent study also extended the MEG sensory gating deficit for the M50 to human voices rather than clicks, finding that the left-lateralized deficit was associated with auditory hallucinations (Hirano et al. 2010). Simulations of changes in dipole location, orientation, and interhemispheric latency differences have shown that source configuration is important to consider in sensory gating studies in schizophrenia (Edgar et al. 2003). Indeed, source modeling of the M50 response has also been shown to improve the reliability of sensory gating measures, compared to Cz-only EEG approaches (Lu et al. 2007). An MEG study that did not examine sensory gating per se found that M50 responses had higher signal-to-noise ratios than P50 responses, suggesting another potential advantage to MEG (Thonnessen et al. 2008).

One MEG study examined the proportion of variance in the vertex EEG explained by bilateral auditory dipoles modeled using MEG data. Huang et al. (2003) found that dipoles in the left and right auditory cortices account for approximately 97% of the variance in healthy individuals observed at a vertex EEG electrode for the time period including the P50 responses, but a smaller amount, 86%, in persons with schizophrenia. In that study, the residual variance waveform for the dipole had a peak frequency of 40 Hz, suggesting unaccounted for variance in the gamma band in schizophrenia subjects. Indeed, an early combined EEG and MEG sensory gating paper suggested that the gating effect was stronger for gamma-band signals overlapping the P50/M50 response temporally (Clementz et al. 1997). Other spectrally focused MEG studies of sensory gating have implicated theta, alpha, and beta abnormalities as well (Edgar et al. 2008; Ho et al. 2008; Popov et al. 2011).

Gating is not specific to the auditory M50 response. The M100 response also exhibits reduced amplitude to the second of two paired sounds, although historically this has been considered in the context of refractoriness or habituation (see Sect. 3.2). Hanlon et al. (2005a) reported M100 gating deficits in schizophrenia, in addition to the M50-based deficit. The M100, unlike the M50, showed bilateral deficits in the patients. One MEG study examining M100 suppression effects in schizophrenia found that when using monaural stimulation, instead of the usual binaural stimuli, ipsilateral but not contralateral response gating was worse in patients compared to controls (Blumenfeld and Clementz 1999). Similarly, Dale et al. (2010) found that M100 response suppression to the second of two closely spaced syllables was impaired in schizophrenia. Another study examined the generality of sensory gating deficits across sensory modalities in 27 patients with schizophrenia and 21 control subjects (Edgar et al. 2005). Deficits were replicated for the auditory M50 gating response, but were not present in the somatosensory system using the M20 response to median nerve stimulation. The lack of somatosensory gating deficit in schizophrenia does not imply an intact somatosensory system, however, as another MEG study found abnormalities in evoked responses to median nerve stimulation in schizophrenia in the context of a somatosensory oddball task (Huang et al. 2010). Additionally, a follow-up study of secondary somatosensory cortical responses (the M20 is generated in primary somatosensory cortex) found evidence for gating deficits in these later responses in patients with schizophrenia (Thoma et al. 2007).

As with the M100 response, M50 and gating measures derived from it are correlated with structural changes in the brain in schizophrenia. An early study reported that M50 gating was negatively correlated with anterior hippocampal volumes in a hemisphere-specific manner, such that gating in the left correlated with left hippocampus and gating in the right correlated with right hippocampus (Thoma et al. 2008). This is an important observation given the putative role for the hippocampus in some models of sensory gating and the general lack of imaging evidence for a hippocampal generator. Other experimental paradigms more specific to hippocampal function have revealed hippocampal deficits in schizophrenia using MEG (Hanlon et al. 2005b, 2011). In addition, Thoma et al. (2004) also found that thinner auditory cortex in schizophrenia subjects was associated with reduced sensory gating of the M50.

Finally, there are two additional points worth considering for MEG measures of sensory gating in schizophrenia. The first is that while most studies do in fact replicate the alteration in response to amplitude ratios between first and second stimuli, regardless of whether the specific change is to the first or the second stimulus, at least one study using first-episode, medicated schizophrenia subjects did not find evidence for sensory gating impairment in schizophrenia (Bachmann et al. 2010). A significant number of patients, however, were taking clozapine, which in separate studies has been shown to improve sensory gating in schizophrenia, unlike other antipsychotic medications (Adler et al. 2004). Last, MEG-based sensory gating may be a schizophrenia biomarker amenable to inclusion in clinical trials. Popov et al. (2012) reported preliminary evidence of normalization of M50 and gamma-band measures of sensory gating in a sample of schizophrenia patients assigned to a 4-week cognitive remediation intervention.

3.4 Affect Processing in Schizophrenia

More recently, schizophrenia researchers have been focused on impairments in social cognition in the disorder, and it has long been known that schizophrenia patients have reduced affective expression. Several MEG studies have examined aspects of affect processing in the disorder. Streit et al. (2001) examined visual evoked magnetic fields to standardized pictures of facial affect in patients with schizophrenia (N = 15) and control subjects (N = 12). They reported reduced activations in brain regions including the inferior prefrontal, temporal, parietal, and occipital cortices in the schizophrenia group. Inferior prefrontal and fusiform gyrus activity was correlated with behavioral categorization of emotional faces, which was worse in the schizophrenia subjects. A follow-on study of the same dataset examined interregional connectivity using mutual information metrics (Ioannides et al. 2004), observing that schizophrenia subjects had generally weaker linkages between regions involved in the task, including a missing link between right amygdala and primary/secondary visual cortices. Another MEG study employed stimuli from the International Affective Picture System (IAPS) and found that the schizophrenia patients (N = 12) exhibited lower response differences between emotional and neutral stimuli in frontal and posterior regions of the brain (Rockstroh et al. 2006). They also observed a shift in schizophrenia patients toward emotional valence responsiveness toward the right, rather than left, hemisphere, compared to healthy control subjects. In a separate study involving only neutral-face perception, patients with schizophrenia exhibited significantly greater right hemisphere activation than left, compared to control subjects (Lopez-Ibor et al. 2008). A final MEG study involved a heterogeneous sample of patients including schizophrenia (N = 15), depression (N = 19), drug addiction (N = 10), and borderline personality disorder (N = 6), as well as healthy controls (Weber et al. 2009). This study, which also employed emotional and neutral pictures from the IAPS, examined the impact of early life stress on affective processing by focusing on the visual early posterior negativity (EPN) between 160 and 210 ms. They reported that the EPN response was smaller overall in patients with borderline personality and depression than in schizophrenia patients. They also reported, however, that schizophrenia patients had reduced EPN sensitivity to arousing stimuli. Overall, early life stress was negatively correlated with EPN responses.

4 Spontaneous MEG in Schizophrenia

4.1 Abnormal Slow-Wave Activity

Several studies have examined spontaneous low-frequency oscillatory signals in resting MEG recordings from schizophrenia patients. Canive et al. (1996) were the first to report the presence of abnormal slow waves in a small sample of schizophrenia subjects using MEG, reporting the presence of the activity in 4 unmedicated patients out of 11 studied. Fehr et al. (2001) reported increased slow-wave activity (delta and theta band), measured via dipole densities, that tended to cluster in frontal and temporal regions of the cortex in schizophrenia patients. In a follow-on study by the same group that compared different mental states (mental arithmetic and imagery) to rest, schizophrenia patients (N = 30) exhibited higher densities of slow wave related to dipoles compared to controls (N = 17) in the temporal and parietal regions. Dipole density was correlated with a measure of negative symptoms in the patient group (Fehr et al. 2003). Another MEG research group replicated the increased slow wave result in schizophrenia patients, but reported a relationship between dipole density and both positive and negative symptoms in their sample (Sperling et al. 2002, 2003).

Three studies have examined the effects of medication on abnormal slow-wave activity in schizophrenia patients. In a cross-sectional comparison, Fehr et al. (2003) reported that dipole density measure did not differ between medicated and unmedicated patients, in contrast to the earlier report from Canive et al. (1996), who reported that abnormal slow-wave activity found in unmedicated patients was not present in the same subjects after antipsychotic medication for 8 weeks. Studies of medication effects within the context of repeated measurements on patients in a controlled trial are more convincing than cross-sectional comparisons. One such study by Sperling et al. (2002) demonstrated that treatment with clozapine or haloperidol had no effect on slow-wave density, which also contrasted with the Canive et al. (1996) report. Both medication trials had low numbers of patients, however, and a larger trial would be needed to provide a definitive answer to whether antipsychotic medications reduce slow-wave dipole density in schizophrenia.

The specificity of increased focal slow-wave activity in schizophrenia has also been examined in MEG studies. Wienbruch et al. (2003) published data from 25 patients with schizophrenia compared to 27 with major depressive disorder and 18 healthy controls. While the schizophrenia patients exhibited the same pattern of increased delta/theta density in frontal regions compared to controls, there was a significant reduction in slow-wave activity in the depression sample, relative to both the schizophrenia and control groups. A more recent examination by investigators from the same group confirmed these findings. In a very large sample of 76 schizophrenia/schizoaffective disorder patients, compared to 116 healthy subjects and 42 with mood or somatoform disorders, elevation in slow-wave activity was seen in the schizophrenia sample but not in a group comprised of mood and somatoform disorders (Rockstroh et al. 2007). In the Rockstroh et al. (2007) study, the mood/somatoform disorder patient group had fewer slow-wave dipoles than either the schizophrenia or healthy control groups. Interestingly, however, in both diagnostic groups, there was a relationship between affective symptoms and slow-wave activity, the specifics of which differed by diagnosis; in the schizophrenia sample, affective flattening and slow-wave activity were positively correlated, while in the mood/somatoform group, higher depression scores were associated with fewer frontal slow waves. This last point is intriguing given the authors’ choice to combine schizoaffective patients with the schizophrenia patients in the analyses, since major mood symptoms, including major depressive and/or manic episodes, are more characteristic of the former group. The number of schizoaffective patients was too small in the Rockstroh et al. (2007) sample, but in future studies, it would be worth characterizing slow-wave activity and symptom relationships separately for schizophrenia and schizoaffective patients, with a goal of further subtyping the schizoaffective sample by history of depression and mania (i.e., depressive vs. bipolar subtype in the DSM-IV system).

4.2 Other Spectral, Connectivity, and Complexity Studies of Spontaneous MEG in Schizophrenia

Aside from the abnormal slow-wave studies in schizophrenia, there are a smaller number of papers that have examined spontaneous signals in higher frequency bands. Activity in the alpha (8–12 Hz), beta (12–30 Hz), and gamma (30 Hz and higher) bands has been examined. Sperling et al. (1999, 2002), using the same dipole density methods employed in the delta/theta studies described above, also reported higher density for beta activity in schizophrenia patients, although no significant differences in the alpha band were noted. A recent eyes-closed resting state MEG study by Hinkley et al. (2011) of 30 patients and 15 controls replicated the lack of group difference in alpha power. In this study, connectivity analyses using coherence in the alpha band were conducted in source space after reconstruction using a beamforming approach. Decreased connectivity in left dorsolateral prefrontal cortex and right superior temporal cortex was seen in the patient group relative to controls. Prefrontal connectivity was inversely related to negative symptoms, such that low connectivity predicted higher symptoms (Hinkley et al. 2011). In a sensor-level analysis of spontaneous activity during rest and a mental arithmetic task, Kissler et al. (2000) found reduced task-related increases in low-gamma (30–45 Hz) power in left frontal regions of schizophrenia patients and also significantly reduced high gamma (60–71 Hz) across both task conditions in the patient group. Another study employing beamforming source reconstructions examined changes in a wide range of frequencies from delta to very high gamma (80–150 Hz) in a study of 38 patients, 38 unaffected siblings, and 38 healthy controls (Rutter et al. 2009). Reduced gamma, particularly between 30 and 70 Hz, was observed in the schizophrenia group within a large cluster centered primarily in the precuneus region of the medial occipitoparietal cortex. Unaffected siblings demonstrated a similar reduction suggestive of a possible heritable contribution to the deficit. Although the schizophrenia sample was medicated, the presence of the gamma-band deficit in the unaffected and unmedicated relatives suggests that medication does not explain the observation.

Two additional studies deserving mention in this section did not examine the relative spectral power in different bandwidths directly. Fernandez et al. (2011) calculated a measure of signal complexity (Lempel-Ziv complexity) on MEG signals, in sensor space, that is an approximation of the number of frequency components comprising the signal measured. In this study, 15 patients and 15 control subjects were studied, and the authors reported that the complexity measure was positively correlated with age in controls, but negatively correlated with age in the schizophrenia subjects. This was interpreted as possible evidence for a neurodegenerative process in schizophrenia, although the cross-sectional design was recognized as a limitation in this respect. Longitudinal studies employing complexity measures, as well as more traditional spectral and connectivity metrics, could help answer the controversial question of whether schizophrenia is a neurodegenerative disorder. In an earlier MEG study of complexity using a single-channel gradiometer system and a different metric involving nonlinearity dimensionality, it was reported that schizophrenia subjects also had lower complexity than healthy controls (Kotini and Anninos 2002).

4.3 Spectral Findings Associated with Hallucinations in Schizophrenia

Tiihonen et al. (1992) first described latency delays in auditory evoked fields during the hallucinating state in two patients with schizophrenia. Subsequent MEG studies, however, have concerned themselves with spectral content rather than evoked effects. One study employing the dipole density methodology described above reported an increase in beta-band dipole density (12–30 Hz) in the left auditory cortex of a single patient compared to a reference group of 13 healthy controls (Ropohl et al. 2004). It was unclear in this study to what extent the recordings were concomitant with the hallucinations, and there was no comparison of the activity in periods of hallucination and no hallucination. A group study involving eight hallucinating and eight non-hallucinating patients reported significantly greater beta-band dipole density in the hallucinating patients in the superior temporal region of both hemispheres (Reulbach et al. 2007). Although Reulbach et al. did have patients indicate periods of hallucination with button-presses, there is no direct, within-group comparison of the hallucinating versus non-hallucinating state in that study (Reulbach et al. 2007). In another N = 1 study, Ishii et al. (2000) did examine hallucinating versus non-hallucinating periods in a patient, observing that theta-band activity increased during periods of hallucination. Using a frequency-based beamforming approach, these bursts associated with the hallucinations were localized to posterior, superior temporal areas of the left hemisphere. In a recent study involving 12 hallucinating patients (10 with schizophrenia), van Lutterveld et al. (2012) had the participants indicate periods of auditory hallucination with button-presses. They examined oscillatory activity associated with precise timing to the button press in order to estimate changes related to the onset of hallucinations in the patients. Beamformer images were formed for delta, theta, alpha, and beta bands and compared between hallucinating and non-hallucinating segments. During hallucinations, compared to non-hallucination time periods, patients exhibited reduced alpha power in right inferior frontal gyrus and decreases in beta power in the left middle and superior temporal gyrus region. Just prior to the onset of auditory hallucinations, a significant increase in theta power was observed in the hippocampal-amygdala region. No changes in delta were observed. These findings, taken together, suggest that auditory-verbal regions of the cerebral cortex and subcortical regions including the hippocampus are involved in auditory hallucinations, consistent with a larger literature on hallucinations using PET and fMRI methods (see meta-analysis of Jardri 2011). Future studies should continue to explore possible event-related oscillatory state changes associated with hallucinations to separate hallucination mechanisms from internally driven auditory-verbal perceptual activation, if possible. For interested readers, a more comprehensive review of spontaneous MEG findings in schizophrenia can be found in a recent paper by Siekmeier and Stufflebeam (2010).

5 Event-Related Spectral Perturbance (ERSP) in Schizophrenia

In the previous section, we reviewed MEG studies primarily concerned with so-called resting state or spontaneous oscillations in schizophrenia. Since the brain is never truly at rest, these studies are in effect examining patients’ brain activity during periods of free association or stream of consciousness, in the absence of defined external stimulation. Next, MEG studies of neuromagnetic oscillations during the performance of various tasks are considered. Such studies can be grouped under the term event-related spectral perturbances (Makeig et al. 2004). Studies involving both event-related desynchronization (ERD) and event-related synchronization (ERS) are reviewed in this section.

5.1 Alpha Band and Working Memory

Several MEG studies have considered alpha-band ERD during performance of working memory tasks in schizophrenia. MEG has been used extensively to examine working memory in healthy individuals, primarily focusing on theta and alpha band oscillations (Kaufman et al. 1992; Jensen and Tesche 2002; Jensen et al. 2002; Rojas et al. 2000; Bonnefond and Jensen 2012). In the first such study in schizophrenia, Reite et al. (1996) found that during an auditory Sternberg working memory task, schizophrenia participants exhibited reduced left hemisphere duration of alpha suppression (ERD) elicited by memory probe items. No differences were observed in the right hemisphere. This study was inherently limited in spatial coverage by the use of a seven-channel gradiometer system, but was prepositioned over the M100 posterior field maximum so that signals might be nominally interpreted as having a temporal lobe origin. Two recent studies using large array systems have been published, however, using a visual rather than auditory Sternberg working memory task. Canuet et al. (2010, 2011) have published two studies involving individuals with schizophrenia and chronic interictal psychosis or schizophrenia-like psychosis of epilepsy (SLPE). Controversy exists in terms of whether these patient groups can be considered distinct, either etiology- or nosology-wise (Sachdev 1998). During the retention interval of the task, alpha ERD and ERS were observed in both groups as well as in healthy controls and nonpsychotic epilepsy patients. Schizophrenia and SLPE subjects, however, had greater ERD in right dorsolateral prefrontal cortex (DLPFC) compared to healthy controls and nonpsychotic epilepsy patients (Canuet et al. 2010). Subjects with SLPE and schizophrenia were not directly compared. Higher DLPFC activation may indicate relatively higher working memory loading (i.e., difficulty) for the two psychotic clinical groups, as working memory is particularly impaired in persons with schizophrenia compared across neuropsychological domains (Barch and Ceaser 2012; Forbes et al. 2009). A follow-on study involving patients in the SLPE group from the earlier study showed correlations between DLPFC ERD and symptoms of disorganization (Canuet et al. 2011). Finally, Ince et al. (2008, 2009) have used support vector machine classification of working memory task performance in a schizophrenia study to attempt diagnostic classification. Spectral analysis of the selected classifier features indicated the best classification was obtained in lower frequencies, including delta, theta, and alpha.

Several additional studies of alpha ERSP have been published that do not concern working memory directly. A study of visual steady-state responses using stimulation frequencies between 8 and 10.5 Hz found reduced alpha power entrainment across temporal, parietal, and occipital, but not frontal sensors (Koudabashi et al. 2004). Koh et al. (2011) studied alpha ERD and selective attention during an auditory oddball task in 10 people with schizophrenia, 17 individuals at higher genetic and/or symptomatic risk for developing schizophrenia, and 18 healthy controls. Alpha ERD to tones (targets and standards were not separated) was reduced in the schizophrenia and high-risk groups relative to control subjects. Source localization was not employed in this study, but the sensors chosen for statistical analysis were parieto-occipital. A separate auditory oddball study observed that rather than showing differences in ERD, schizophrenia patients had reduced ERS between 700 and 1500 ms poststimulus, compared to controls (Fujimoto et al. 2012). In this study, which did localize the ERS/ERD sources, the alpha ERD activity was localized to occipital and parietal regions. Finally, one study examined alpha reactivity to eyes open and closed in an event-related manner (Ikezawa et al. 2011). They found that the posterior-dominant alpha rhythm ERS on eye-closed events was smaller in the schizophrenia subjects, with source localization suggesting the significant difference was in left posterior temporal cortex. Earlier conceptualizations of the functional significance of alpha synchrony were that it reflected a sort of passive cortical idling rhythm when the cortex was unoccupied by sensory information (Pfurtscheller et al. 1996). More recent evidence, however, suggests that it is associated with top-down, active inhibition of sensory processing in various regions of the cortex in which it is expressed (Klimesch et al. 2007; Bonnefond and Jensen 2012). Thus, differences in alpha synchronization in schizophrenia may reflect inhibitory dysfunction in the disorder, for which there is considerable evidence in the disorder (Lewis et al. 2005).

5.2 Beta Band

In the same auditory oddball study that found alpha ERS differences (see Sect. 5.1), Fujimoto et al. (2012) described alterations in beta band in schizophrenia. Significant decreases in beta ERS between 500 and 750 ms were noted in the schizophrenia subjects in occipital cortex, while decreases between 750 and 1500 ms were evident in right frontal and anterior cingulate cortex. Beta ERD was significantly increased in patients in right frontal, temporal, and parietal cortices, compared to healthy controls.

With respect to working memory, beta has been explored using graph theoretical measures to examine network efficiency in schizophrenia (Bassett et al. 2009). In an interesting comparison between 28 people with schizophrenia and 29 controls, graph measures were assessed in an n-back working memory task. Findings of the study included significantly lower cost efficiency, but higher global efficiency in the schizophrenia group in the beta band during the task. This suggests a shift in the schizophrenia group toward a more random network wiring rather than a typical small-world network. The authors noted, however, that efficiency was highly correlated with performance and that when performance differences between groups were accounted for, differences in efficiency remained but were less significant (Bassett et al. 2009). Using a different method, support vector machine classification, Ince et al. (2009) found discriminant features in beta band (as well as lower frequencies) in a Sternberg working memory task.

Wilson et al. (2009) examined beta ERSP to tactile stimulation of the fingertip in a mixed group of children and adolescents with psychoses including schizophrenia, compared to healthy controls. Beta ERD was significantly higher in the psychotic group in motor-related regions of the brain including the cerebellum and precentral gyrus. In a separate study with a similar group of patients, beta ERD/ERS was examined during performance of a simple, visually cued unimanual finger flexion task (Wilson et al. 2011). Beta-band differences in premovement ERD, as well as post-movement ERS (also known as the post-movement beta-rebound), were observed. Patients exhibited higher beta ERD in precentral and cerebellar regions, similar to the findings of the tactile stimulation study. Beta ERS, however, was reduced in patients within the cerebellum, supplementary motor cortex, and parietal lobe. Motor coordination deficits are one of the few early life predictors of later psychotic disorder onset (Isohanni et al. 2001), and beta abnormalities may reflect early abnormalities in motor circuitry. One recent MEG study has suggested a relationship between the post-movement beta rebound and GABA concentration in the somatomotor region (Gaetz et al. 2011). GABAergic dysfunction is one of the hottest topics in schizophrenia (Benes 2012; Lewis et al. 2012).

Apart from its potential relationship with GABAergic dysfunction, motor beta rhythms may be related to mirror neuron activity, which are neurons that respond to action observation and are theoretically important to social disability in schizophrenia. The beta rhythm has been shown to be reactive to action observations in addition to actual movements (Muthukumaraswamy and Johnson 2004). Schurmann et al. (2007) studied beta-rhythm reactivity to action observation in 11 twin pairs discordant for schizophrenia. They reported that the post-movement beta rebound was reduced to both action execution and observation in the twins with schizophrenia compared to the twins without the disorder, suggesting that the beta effect, while not specific to action observation, may be important for accurate internal representation of the actions of others (i.e., theory of mind).

5.3 Gamma Band

Interest in gamma-band oscillations (30–150 Hz) in schizophrenia is very high and relates to the observation that gamma-band activity is highly dependent on inhibitory neurotransmission mediated by GABAergic neurons (Lewis et al. 2005; Uhlhaas 2011). The circuitry for gamma-band generation in the cortex and hippocampus is reasonably well characterized and represents the interaction of pyramidal glutamatergic inputs to fast-spiking GABAergic interneurons that recurrently inhibit the pyramidal cells (Bartos et al. 2007; Hájos and Paulsen 2009). It should be noted that this relationship, between GABA and gamma, is not unique to gamma oscillations, because there is evidence for GABAergic involvement in lower frequencies (e.g., beta band) as well (Vierling-Claassen et al. 2008; Porjesz et al. 2002). Gamma-band abnormalities have received more attention in this respect, however.

Reduced auditory gamma-band activity in schizophrenia was first noted using EEG and has been widely replicated (Kwon et al. 1999; Koenig et al. 2012; Brenner et al. 2009) and is also present in first-degree unaffected relatives (Hong et al. 2004). Auditory stimuli produce two types of gamma-band responses. An early, obligatory transient gamma-band response is seen in typically developing individuals to all types of sound stimuli within the first 30–80 ms poststimulus (Pantev et al. 1991). When stimuli are modulated in amplitude, either as part of a train of clicks or by amplitude modulation, a later auditory steady-state response (aSSR), beginning around 100 ms, is produced at or near the frequency of modulation, peaking around 40 Hz modulatory rates (Hari et al. 1989). Both types of responses are highly phase-locked in typically developing individuals. The aSSR reduction has been extended to magnetic responses in children and adults with schizophrenia (Teale et al. 2008; Maharajh et al. 2010; Wilson et al. 2008; Vierling-Claassen et al. 2008). Reductions in neuromagnetic aSSR have also been shown to be specific to frequency of stimulation. Tsuchimoto et al. (2011) found that 40 and 80 Hz stimulation rates elicited evidence of reduced bilateral auditory power and phase-locking in schizophrenia, but not stimulation at 20 and 30 Hz. This finding was partly replicated by Hamm et al. (2011), who found reduced power at 80 Hz rates in both hemispheres, but only in the right hemisphere at 40 Hz. Auditory steady-state magnetic responses are typically larger in the right than in the left hemispheres (Ross et al. 2005). In an interesting preliminary study that needs replication in a larger sample, schizoaffective disordered patients (N = 8) had higher 40 Hz aSSR responses in the right hemisphere compared to control subjects, while schizophrenia patients exhibited a bilateral reduction in 40 Hz aSSR power and phase-locking (Reite et al. 2010). Replication of this would be important because many studies combine schizoaffective and schizophrenia groups, although there is some evidence to suggest the two are distinct clinical entities (Abrams et al. 2008).

Transient magnetic gamma-band responses (tGBR) have also been reported as reduced in schizophrenia. Hirano et al. (2008) found reduced evoked tGBR power and phase-locking, as well as longer tGBR peak latency to speech, but not non-speech sounds in the left hemisphere of persons with schizophrenia (N = 20) compared to healthy controls (N = 23). Teale et al. (2008) reported a trend for reduced pure tone phase-locking of the tGBR specific to the left hemisphere, but no differences in evoked power. In the first study of tGBR in MEG published, Clementz et al. (1997) reported a significant reduction in tGBR suppression in schizophrenia subjects in the context of a classic P50/M50 sensory gating paradigm (discussed previously in Sect. 3.3).

6 Future Directions

Despite having made substantial contribution to our knowledge of the electrophysiology of schizophrenia, more MEG research is still needed. MEG remains advantageous for examining the relatively unexplored area between the spatial resolving power of fMRI and the vast EEG literature in schizophrenia with poor spatial resolution. In particular, combining the strength of high sensor density and/or source analytic techniques with modern connectivity approaches such as mutual information (Ioannides et al. 2004), graph theory (Bassett et al. 2009), and causal modeling (Dima et al. 2012) is of high importance given the significant overall interest in the field about brain network-level impairments in the disorder. The use of machine learning and multivariate classification methods is also potentially important (Ince et al. 2009) and could be used to identify subtle risk factors and applied to populations at high risk for developing schizophrenia. With respect to the latter point, more work with unaffected first-degree relatives is recommended (Rutter et al. 2009), both to identify heritable risk factors and to protect the interpretation of findings against medication confounds. Finally, a comment should be made about finding solutions to a significant barrier to MEG research in schizophrenia, which is the relative difficulty of conducting large, multi-site clinical trials due to the relatively low installed user base and differences in technology employed between sites. Efforts to measure and reduce differences between different MEG sites would allow MEG to participate as a technology in future large-scale behavioral and pharmacological intervention trials, as well as providing the means to incorporate large samples in general into new and interesting research studies.


  1. Abrams DJ, Rojas DC, Arciniegas DB (2008) Is schizoaffective disorder a distinct categorical diagnosis? A critical review of the literature. Neuropsychiatr Dis Treat 4(6):1089–1109CrossRefGoogle Scholar
  2. Adler LE et al.(1982) Neurophysiological evidence for a defect in neuronal mechanisms involved in sensory gating in schizophrenia. Biol Psychiatry 17(6):639–654Google Scholar
  3. Adler LE et al.(2004) Varied effects of atypical neuroleptics on P50 auditory gating in schizophrenia patients. Am J Psychiatry 161(10):1822–1828CrossRefGoogle Scholar
  4. Ahveninen J et al.(2006) Inherited auditory-cortical dysfunction in twin pairs discordant for schizophrenia. Biol Psychiatry 60(6):612–620CrossRefGoogle Scholar
  5. Aleman A, Kahn RS, Selten J-P (2003) Sex differences in the risk of schizophrenia: evidence from meta-analysis. Arch Gen Psychiatry 60(6):565–571CrossRefGoogle Scholar
  6. American Psychiatric Association (1994) Diagnostic and statistical manual of mental disorders, 4th edn. American Psychiatric Association, Washington, DCGoogle Scholar
  7. Bachmann S et al.(2010) MEG does not reveal impaired sensory gating in first-episode schizophrenia. Schizophr Res 121(1–3):131–138CrossRefGoogle Scholar
  8. Barch DMD, Ceaser AA (2012) Cognition in schizophrenia: core psychological and neural mechanisms. Trends Cogn Sci 16(1):8CrossRefGoogle Scholar
  9. Bartos M, Vida I, Jonas P (2007) Synaptic mechanisms of synchronized gamma oscillations in inhibitory interneuron networks. Nat Rev Neurosci 8(1):45–56CrossRefGoogle Scholar
  10. Bassett DS et al.(2009) Cognitive fitness of cost-efficient brain functional networks. Proc Natl Acad Sci 106(28):11747–11752CrossRefGoogle Scholar
  11. Benes FMF (2012) A new paradigm for understanding gamma-aminobutyric acid cell pathology in schizophrenia? Biol Psychiatry 72(9):712–713CrossRefGoogle Scholar
  12. Bleuler E (1911) Dementia praecox or the group of schizophrenias. International Universities Press, New YorkGoogle Scholar
  13. Blumenfeld LD, Clementz BA (1999) Hemispheric differences on auditory evoked response suppression in schizophrenia. Neuroreport 10(12):2587–2591CrossRefGoogle Scholar
  14. Blumenfeld LD, Clementz BA (2001) Response to the first stimulus determines reduced auditory evoked response suppression in schizophrenia: single trials analysis using MEG. Clin Neurophysiol 112(9):1650–1659CrossRefGoogle Scholar
  15. Bonnefond M, Jensen O (2012) Alpha oscillations serve to protect working memory maintenance against anticipated distracters. Curr Biol 22(20):1969–1974CrossRefGoogle Scholar
  16. Brenner CAC et al.(2009) Steady state responses: electrophysiological assessment of sensory function in schizophrenia. Brain Res Brain Res Rev 35(6):1065–1077Google Scholar
  17. Canive JM et al.(1996) Magnetoencephalographic assessment of spontaneous brain activity in schizophrenia. Psychopharmacol Bull 32(4):741–750Google Scholar
  18. Canuet L et al.(2010) Working memory abnormalities in chronic interictal epileptic psychosis and schizophrenia revealed by magnetoencephalography. Epilepsy Behav 17(1):109–119CrossRefGoogle Scholar
  19. Canuet L et al.(2011) Psychopathology and working memory-induced activation of the prefrontal cortex in schizophrenia-like psychosis of epilepsy: evidence from magnetoencephalography. Psychiatry Clin Neurosci 65(2):183–190CrossRefGoogle Scholar
  20. Clementz BA, Blumenfeld LD, Cobb S (1997) The gamma band response may account for poor P50 suppression in schizophrenia. Neuroreport 8(18):3889–3893CrossRefGoogle Scholar
  21. Dale CL et al.(2010) Timing is everything: neural response dynamics during syllable processing and its relation to higher-order cognition in schizophrenia and healthy comparison subjects. Int J Psychophysiol Off J Int Organ Psychophysiol 75(2):183–193Google Scholar
  22. Dima D et al.(2012) Abnormal intrinsic and extrinsic connectivity within the magnetic mismatch negativity brain network in schizophrenia: a preliminary study. Schizophr Res 135(1–3):23–27CrossRefGoogle Scholar
  23. Edgar JC et al.(2003) Interpreting abnormality: an EEG and MEG study of P50 and the auditory paired-stimulus paradigm. Biol Psychol 65(1):1–20CrossRefGoogle Scholar
  24. Edgar JC et al.(2005) Cross-modal generality of the gating deficit. Psychophysiology 42(3):318–327MathSciNetCrossRefGoogle Scholar
  25. Edgar JC et al.(2006) Reduced auditory M100 asymmetry in schizophrenia and dyslexia: applying a developmental instability approach to assess atypical brain asymmetry. Neuropsychologia 44(2):289–299CrossRefGoogle Scholar
  26. Edgar JC et al.(2008) Superior temporal gyrus spectral abnormalities in schizophrenia. Psychophysiology 45(5):812–824CrossRefGoogle Scholar
  27. Edgar JC et al.(2012) Temporal and frontal cortical thickness associations with M100 auditory activity and attention in healthy controls and individuals with schizophrenia. Schizophr Res 140(1–3):250–257CrossRefGoogle Scholar
  28. Fehr T et al.(2001) Source distribution of neuromagnetic slow waves and MEG-delta activity in schizophrenic patients. Biol Psychiatry 50(2):108–116CrossRefGoogle Scholar
  29. Fehr T et al.(2003) Source distribution of neuromagnetic slow-wave activity in schizophrenic patients–effects of activation. Schizophr Res 63(1–2):63–71CrossRefGoogle Scholar
  30. Fernandez A et al.(2011) Lempel-Ziv complexity in schizophrenia: a MEG study. Clin Neurophysiol 122(11):2227–2235CrossRefGoogle Scholar
  31. Forbes NF et al.(2009) Working memory in schizophrenia: a meta-analysis. Psychol Med 39(6):889–905CrossRefGoogle Scholar
  32. Freedman R et al.(2003) The genetics of sensory gating deficits in schizophrenia. Curr Psychiatry Rep 5(2):155–161CrossRefGoogle Scholar
  33. Friston KJ, Harrison L, Penny W (2003) Dynamic causal modelling. NeuroImage 19(4):1273–1302CrossRefGoogle Scholar
  34. Fujimoto T et al.(2012) Changes in event-related desynchronization and synchronization during the auditory oddball task in schizophrenia patients. Open Neuroimaging J 6:26–36CrossRefGoogle Scholar
  35. Gaetz W et al.(2011) Relating MEG measured motor cortical oscillations to resting γ-aminobutyric acid (GABA) concentration. NeuroImage 55(2):616–621CrossRefGoogle Scholar
  36. Gejman PVP, Sanders ARA, Kendler KSK (2011) Genetics of schizophrenia: new findings and challenges. Genomics Hum Genet 12:121–144CrossRefGoogle Scholar
  37. Goldstein JM (1988) Gender differences in the course of schizophrenia. Am J Psychiatry 145(6):684–689CrossRefGoogle Scholar
  38. Gottesman II (1991) Schizophrenia genesis: the origins of madness. W H Freeman/Times Books/Henry Holt & Co, New YorkGoogle Scholar
  39. Green MF (2006) Cognitive impairment and functional outcome in schizophrenia and bipolar disorder. J Clin Psychiatry 67(10):e12CrossRefGoogle Scholar
  40. Hajek M, Boehle C et al.(1997a) Abnormalities of auditory evoked magnetic fields in the right hemisphere of schizophrenic females. Schizophr Res 24(3):329–332CrossRefGoogle Scholar
  41. Hajek M, Huonker R et al.(1997b) Abnormalities of auditory evoked magnetic fields and structural changes in the left hemisphere of male schizophrenics–a magnetoencephalographic-magnetic resonance imaging study. Biol Psychiatry 42(7):609–616CrossRefGoogle Scholar
  42. Hájos N, Paulsen O (2009) Network mechanisms of gamma oscillations in the CA3 region of the hippocampus. Neural Netw Off J Int Neural Netw Soc 22(8):1113–1119CrossRefGoogle Scholar
  43. Hamm JP et al.(2011) Abnormalities of neuronal oscillations and temporal integration to low- and high-frequency auditory stimulation in schizophrenia. Biol Psychiatry 69(10):989–996CrossRefGoogle Scholar
  44. Hanlon FM, Miller GA et al.(2005a) Distinct M50 and M100 auditory gating deficits in schizophrenia. Psychophysiology 42(4):417–427CrossRefGoogle Scholar
  45. Hanlon FM, Weisend MP et al.(2005b) A specific test of hippocampal deficit in schizophrenia. Behav Neurosci 119(4):863–875CrossRefGoogle Scholar
  46. Hanlon FM et al.(2011) Bilateral hippocampal dysfunction in schizophrenia. NeuroImage 58(4):1158–1168CrossRefGoogle Scholar
  47. Hari RR et al.(1982) Interstimulus interval dependence of the auditory vertex response and its magnetic counterpart: implications for their neural generation. Electroencephalogr Clin Neurophysiol 54(5):561–569CrossRefGoogle Scholar
  48. Hari R, Hämäläinen M, Joutsiniemi SL (1989) Neuromagnetic steady-state responses to auditory stimuli. J Acoust Soc Am 86(3):1033–1039CrossRefGoogle Scholar
  49. Heim S et al.(2004) Cerebral lateralization in schizophrenia and dyslexia: neuromagnetic responses to auditory stimuli. Neuropsychologia 42(5):692–697CrossRefGoogle Scholar
  50. Hinkley LBN et al.(2011) Clinical symptoms and alpha band resting-state functional connectivity imaging in patients with schizophrenia: implications for novel approaches to treatment. Biol Psychiatry 70(12):1134–1142CrossRefGoogle Scholar
  51. Hirano S et al.(2008) Abnormal neural oscillatory activity to speech sounds in schizophrenia: a magnetoencephalography study. J Neurosci Off J Soc Neurosci 28(19):4897–4903CrossRefGoogle Scholar
  52. Hirano Y et al.(2010) Auditory gating deficit to human voices in schizophrenia: a MEG study. Schizophr Res 117(1):61–67CrossRefGoogle Scholar
  53. Ho M-HR et al.(2008) Time-frequency discriminant analysis of MEG signals. NeuroImage 40(1):174–186CrossRefGoogle Scholar
  54. Holcomb HH et al.(1995) Tone discrimination performance in schizophrenic patients and normal volunteers: impact of stimulus presentation levels and frequency differences. Psychiatry Res Neuroimaging 57(1):75–82CrossRefGoogle Scholar
  55. Hong LE et al.(2004) Evoked gamma band synchronization and the liability for schizophrenia. Schizophr Res 70(2–3):293–302CrossRefGoogle Scholar
  56. Huang MX et al.(2003) Predicting EEG responses using MEG sources in superior temporal gyrus reveals source asynchrony in patients with schizophrenia. Clin Neurophysiol 114(5):835–850CrossRefGoogle Scholar
  57. Huang M-X et al.(2010) Somatosensory system deficits in schizophrenia revealed by MEG during a median-nerve oddball task. Brain Topogr 23(1):82–104CrossRefGoogle Scholar
  58. Ikezawa K et al.(2011) Decreased alpha event-related synchronization in the left posterior temporal cortex in schizophrenia: a magnetoencephalography-beamformer study. Neurosci Res 71(3):235–243CrossRefGoogle Scholar
  59. Ince NF et al.(2008) Selection of spectro-temporal patterns in multichannel MEG with support vector machines for schizophrenia classification. In: Conference proceedings: annual international conference of the IEEE engineering in medicine and biology society. IEEE Engineering in Medicine and Biology Society, pp 3554–3557Google Scholar
  60. Ince NF et al.(2009) Classification of schizophrenia with spectro-temporo-spatial MEG patterns in working memory. Clin Neurophysiol 120(6):1123–1134CrossRefGoogle Scholar
  61. Ioannides AA et al.(2004) Real-time neural activity and connectivity in healthy individuals and schizophrenia patients. NeuroImage 23(2):473–482CrossRefGoogle Scholar
  62. Ishii R et al.(2000) Theta rhythm increases in left superior temporal cortex during auditory hallucinations in schizophrenia: a case report. Neuroreport 11(14):3283–3287CrossRefGoogle Scholar
  63. Isohanni M et al.(2001) Early developmental milestones in adult schizophrenia and other psychoses. A 31-year follow-up of the northern Finland 1966 birth cohort. Schizophr Res 52(1–2):1–19CrossRefGoogle Scholar
  64. Jardri (2011) Cortical activations during auditory verbal hallucinations in schizophrenia: a coordinate-based meta-analysis. Am J Psychiatry 168(1):73–81CrossRefGoogle Scholar
  65. Javitt DC, Shelley A, Ritter W (2000) Associated deficits in mismatch negativity generation and tone matching in schizophrenia. Clin Neurophysiol 111(10):1733–1737CrossRefGoogle Scholar
  66. Jensen O, Tesche CD (2002) Frontal theta activity in humans increases with memory load in a working memory task. Eur J Neurosci 15(8):1395–1399CrossRefGoogle Scholar
  67. Jensen O et al.(2002) Oscillations in the alpha band (9–12 Hz) increase with memory load during retention in a short-term memory task. Cereb Cortex (N Y 1991) 12(8):877–882CrossRefGoogle Scholar
  68. Jordanov T et al.(2010) Local Heschl’s gyrus-based coordinate system for intersubject comparison of M50 auditory response modeled by single equivalent current dipole. J Neurosci Methods 192(1):121–126MathSciNetCrossRefGoogle Scholar
  69. Jordanov T et al.(2011) Reduced mismatch negativity and increased variability of brain activity in schizophrenia. Clin Neurophysiol 122(12):2365–2374CrossRefGoogle Scholar
  70. Kasai K et al.(2003) Neuromagnetic correlates of impaired automatic categorical perception of speech sounds in schizophrenia. Schizophr Res 59(2–3):159–172CrossRefGoogle Scholar
  71. Kaufman L et al.(1992) Changes in cortical activity when subjects scan memory for tones. Electroencephalogr Clin Neurophysiol 82(4):266–284MathSciNetCrossRefGoogle Scholar
  72. Kircher TTJ et al.(2004) Mismatch negativity responses in schizophrenia: a combined fMRI and whole-head MEG study. Am J Psychiatry 161(2):294–304CrossRefGoogle Scholar
  73. Kissler J et al.(2000) MEG gamma band activity in schizophrenia patients and healthy subjects in a mental arithmetic task and at rest. Clin Neurophysiol 111(11):2079–2087CrossRefGoogle Scholar
  74. Klimesch WW, Sauseng PP, Hanslmayr SS (2007) EEG alpha oscillations: the inhibition-timing hypothesis. Brain Res Rev 53(1):63–88CrossRefGoogle Scholar
  75. Koenig TT et al.(2012) Is gamma band EEG synchronization reduced during auditory driving in schizophrenia patients with auditory verbal hallucinations? Schizophr Res 141(2–3):266–270CrossRefGoogle Scholar
  76. Koh Y et al.(2011) An MEG study of alpha modulation in patients with schizophrenia and in subjects at high risk of developing psychosis. Schizophr Res 126(1–3):36–42CrossRefGoogle Scholar
  77. Kotini A, Anninos P (2002) Detection of non-linearity in schizophrenic patients using magnetoencephalography. Brain Topogr 15(2):107–113CrossRefGoogle Scholar
  78. Koudabashi A et al.(2004) Spatiotemporal characteristics of MEG and EEG entrainment with photic stimulation in schizophrenia. In: Conference proceedings: annual international conference of the IEEE engineering in medicine and biology society, vol 6. IEEE Engineering in Medicine and Biology Society, pp 4465–4468Google Scholar
  79. Kreitschmann-Andermahr I et al.(1999) Impaired sensory processing in male patients with schizophrenia: a magnetoencephalographic study of auditory mismatch detection. Schizophr Res 35(2):121–129CrossRefGoogle Scholar
  80. Kwon JS et al.(1999) Gamma frequency-range abnormalities to auditory stimulation in schizophrenia. Arch Gen Psychiatry 56(11):1001–1005CrossRefGoogle Scholar
  81. Lewis DA, Hashimoto T, Volk DW (2005) Cortical inhibitory neurons and schizophrenia. Nat Rev Neurosci 6(4):312–324CrossRefGoogle Scholar
  82. Lewis DA et al.(2012) Cortical parvalbumin interneurons and cognitive dysfunction in schizophrenia. Trends Neurosci 35(1):57–67CrossRefGoogle Scholar
  83. Lieberman JA, Stroup TS (2011) The NIMH-CATIE schizophrenia study: what did we learn? Am J Psychiatry 168(8):770–775CrossRefGoogle Scholar
  84. Lopez-Ibor JJ et al.(2008) The perception of emotion-free faces in schizophrenia: a magneto-encephalography study. Schizophr Res 98(1–3):278–286CrossRefGoogle Scholar
  85. Lu BY et al.(2007) Improved test-retest reliability of 50-ms paired-click auditory gating using magnetoencephalography source modeling. Psychophysiology 44(1):86–90CrossRefGoogle Scholar
  86. Maharajh K et al.(2010) Fluctuation of gamma-band phase synchronization within the auditory cortex in schizophrenia. Clin Neurophysiol Off J Int Fed Clin Neurophysiol 121(4):542–548CrossRefGoogle Scholar
  87. Makeig S et al.(2004) Mining event-related brain dynamics. Trends Cogn Sci 8(5):7CrossRefGoogle Scholar
  88. Mäkelä JP et al.(2004) Functional differences between auditory cortices of the two hemispheres revealed by whole-head neuromagnetic recordings. Hum Brain Mapp 1(1):48–56CrossRefGoogle Scholar
  89. Muthukumaraswamy SD, Johnson BW (2004) Primary motor cortex activation during action observation revealed by wavelet analysis of the EEG. Clin Neurophysiol 115(8):1760–1766CrossRefGoogle Scholar
  90. Naatanen R, Kähkönen S (2009) Central auditory dysfunction in schizophrenia as revealed by the mismatch negativity (MMN) and its magnetic equivalent MMNm: a review. Int J Neuropsychopharmacol Off Sci J Collegium Int Neuropsychopharmacologicum (CINP) 12(1):125–135Google Scholar
  91. Nakasato N et al.(1995) Functional localization of bilateral auditory cortices using an MRI-linked whole head magnetoencephalography (MEG) system. Electroencephalogr Clin Neurophysiol 94(3):183–190CrossRefGoogle Scholar
  92. Pantev C et al.(1991) Human auditory evoked gamma-band magnetic fields. Proc Natl Acad Sci 88(20):8996–9000CrossRefGoogle Scholar
  93. Pantev CC et al.(1995) Specific tonotopic organizations of different areas of the human auditory cortex revealed by simultaneous magnetic and electric recordings. Electroencephalogr Clin Neurophysiol 94(1):26–40CrossRefGoogle Scholar
  94. Pantev C et al.(1998) Study of the human auditory cortices using a whole-head magnetometer: left versus right hemisphere and ipsilateral versus contralateral stimulation. Audiol Neuro-Otol 3(2–3):183–190CrossRefGoogle Scholar
  95. Patterson JVJ et al.(2008) P50 sensory gating ratios in schizophrenics and controls: a review and data analysis. Psychiatry Res Neuroimaging 158(2):22Google Scholar
  96. Pekkonen E et al.(1999) Altered parallel auditory processing in schizophrenia patients. Schizophr Bull 25(3):601–607CrossRefGoogle Scholar
  97. Pekkonen E et al.(2002) Impaired temporal lobe processing of preattentive auditory discrimination in schizophrenia. Schizophr Bull 28(3):467–474CrossRefGoogle Scholar
  98. Pfurtscheller GG, Stancák AA, Neuper CC (1996) Event-related synchronization (ERS) in the alpha band–an electrophysiological correlate of cortical idling: a review. Int J Psychophysiol 24(1–2):39–46CrossRefGoogle Scholar
  99. Popov T et al.(2011) Evoked and induced oscillatory activity contributes to abnormal auditory sensory gating in schizophrenia. NeuroImage 56(1):307–314CrossRefGoogle Scholar
  100. Popov T et al.(2012) Adjusting brain dynamics in schizophrenia by means of perceptual and cognitive training García AV (ed). PLoS One 7(7):e39051CrossRefGoogle Scholar
  101. Porjesz B et al.(2002) Linkage disequilibrium between the beta frequency of the human EEG and a GABAA receptor gene locus. Proc Natl Acad Sci 99(6):3729–3733CrossRefGoogle Scholar
  102. Rabinowicz EF et al.(2000) Auditory sensory dysfunction in schizophrenia: imprecision or distractibility? Arch Gen Psychiatry 57(12):1149–1155CrossRefGoogle Scholar
  103. Rabinowitz J et al.(2012) Negative symptoms have greater impact on functioning than positive symptoms in schizophrenia: analysis of CATIE data. Schizophr Res 137(1–3):147–150CrossRefGoogle Scholar
  104. Reite M et al.(1988) Source origin of a 50-ms latency auditory evoked field component in young schizophrenic men. Biol Psychiatry 24(5):495–506CrossRefGoogle Scholar
  105. Reite M et al.(1989) Late auditory magnetic sources may differ in the left hemisphere of schizophrenic patients. A preliminary report. Arch Gen Psychiatry 46(6):565–572CrossRefGoogle Scholar
  106. Reite M et al.(1994) Auditory M100 component 1: relationship to Heschl’s gyri. Brain Res Cogn Brain Res 2(1):13–20CrossRefGoogle Scholar
  107. Reite M et al.(1996) Magnetoencephalographic evidence of abnormal early auditory memory function in schizophrenia. Biol Psychiatry 40(4):299–301CrossRefGoogle Scholar
  108. Reite M et al.(1997) Magnetic source imaging evidence of sex differences in cerebral lateralization in schizophrenia. Arch Gen Psychiatry 54(5):433–440CrossRefGoogle Scholar
  109. Reite M, Teale P, Rojas DC, Arciniegas D et al.(1999a) Bipolar disorder: anomalous brain asymmetry associated with psychosis. Am J Psychiatry 156(8):1159–1163Google Scholar
  110. Reite M, Teale P, Rojas DC, Sheeder J et al.(1999b) Schizoaffective disorder: evidence for reversed cerebral asymmetry. Biol Psychiatry 46(1):133–136CrossRefGoogle Scholar
  111. Reite M et al.(2003) Anomalous somatosensory cortical localization in schizophrenia. Am J Psychiatry 160(12):2148–2153CrossRefGoogle Scholar
  112. Reite M et al.(2010) Schizoaffective disorder – a possible MEG auditory evoked field biomarker. Psychiatry Res Neuroimaging 182(3):284–286CrossRefGoogle Scholar
  113. Reulbach U et al.(2007) Specific and unspecific auditory hallucinations in patients with schizophrenia: a magnetoencephalographic study. Neuropsychobiology 55(2):89–95CrossRefGoogle Scholar
  114. Rockstroh B et al.(1998) Failure of dominant left-hemispheric activation to right-ear stimulation in schizophrenia. Neuroreport 9(17):3819–3822CrossRefGoogle Scholar
  115. Rockstroh B et al.(2001) Altered hemispheric asymmetry of auditory magnetic fields to tones and syllables in schizophrenia. Biol Psychiatry 49(8):694–703CrossRefGoogle Scholar
  116. Rockstroh B et al.(2006) Electromagnetic brain activity evoked by affective stimuli in schizophrenia. Psychophysiology 43(5):431–439CrossRefGoogle Scholar
  117. Rockstroh BS et al.(2007) Abnormal oscillatory brain dynamics in schizophrenia: a sign of deviant communication in neural network? BMC Psychiatry 7:44CrossRefGoogle Scholar
  118. Rojas DC et al.(1997) Sex-specific expression of Heschl’s gyrus functional and structural abnormalities in paranoid schizophrenia. Am J Psychiatry 154(12):1655–1662Google Scholar
  119. Rojas DC et al.(2000) Neuromagnetic alpha suppression during an auditory Sternberg task. Evidence for a serial, self-terminating search of short-term memory. Brain Res Cogn Brain Res 10(1–2):85–89CrossRefGoogle Scholar
  120. Rojas DC et al.(2001) Auditory evoked magnetic fields in adults with fragile X syndrome. Neuroreport 12(11):2573–2576CrossRefGoogle Scholar
  121. Rojas DC et al.(2002) Alterations in tonotopy and auditory cerebral asymmetry in schizophrenia. Biol Psychiatry 52(1):32–39CrossRefGoogle Scholar
  122. Rojas DC et al.(2007) Neuromagnetic evidence of broader auditory cortical tuning in schizophrenia. Schizophr Res 97(1–3):206–214CrossRefGoogle Scholar
  123. Rojas D et al.(2008) Reduced neural synchronization of gamma-band MEG oscillations in first-degree relatives of children with autism. BMC Psychiatry 8(1):66CrossRefGoogle Scholar
  124. Romani GL, Williamson SJ, Kaufman L (1982) Tonotopic organization of the human auditory cortex. Science 216(4552):1339–1340CrossRefGoogle Scholar
  125. Ropohl A et al.(2004) Cortical activity associated with auditory hallucinations. Neuroreport 15(3):523–526CrossRefGoogle Scholar
  126. Rosburg T, Kreitschmann-Andermahr I, Nowak H et al.(2000a) Habituation of the auditory evoked field component N100 m in male patients with schizophrenia. J Psychiatr Res 34(3):245–254CrossRefGoogle Scholar
  127. Rosburg T, Kreitschmann-Andermahr I, Ugur T et al.(2000b) Tonotopy of the auditory-evoked field component N100 m in patients with schizophrenia. J Psychophysiol 14(3):131–141CrossRefGoogle Scholar
  128. Ross B, Herdman AT, Pantev C (2005) Right hemispheric laterality of human 40 Hz auditory steady-state responses. Cereb Cortex (N Y 1991) 15(12):2029–2039CrossRefGoogle Scholar
  129. Rutter L et al.(2009) Magnetoencephalographic gamma power reduction in patients with schizophrenia during resting condition. Hum Brain Mapp 30(10):3254–3264CrossRefGoogle Scholar
  130. Sachdev P (1998) Schizophrenia-like psychosis and epilepsy: the status of the association. Am J Psychiatry 155(3):325–336CrossRefGoogle Scholar
  131. Schmidt GL et al.(2009) Absence of M100 source asymmetry in autism associated with language functioning. Neuroreport 20(11):1037–1041CrossRefGoogle Scholar
  132. Schurmann M et al.(2007) Manifest disease and motor cortex reactivity in twins discordant for schizophrenia. Br J Psychiatry 191:178–179CrossRefGoogle Scholar
  133. Shin KS et al.(2009) Pre-attentive auditory processing in ultra-high-risk for schizophrenia with magnetoencephalography. Biol Psychiatry 65(12):1071–1078CrossRefGoogle Scholar
  134. Shin KS et al.(2012) Neuromagnetic auditory response and its relation to cortical thickness in ultra-high-risk for psychosis. Schizophr Res 140(1–3):93–98CrossRefGoogle Scholar
  135. Siekmeier PJ, Stufflebeam SM (2010) Patterns of spontaneous magnetoencephalographic activity in patients with schizophrenia. J Clin Neurophysiol Off Publ Am Electroencephalogr Soc 27(3):179–190Google Scholar
  136. Smith AK et al.(2010) Cognitive abilities and 50- and 100-ms paired-click processes in schizophrenia. Am J Psychiatry 167(10):1264–1275CrossRefGoogle Scholar
  137. Sommer I et al.(2001) Handedness, language lateralisation and anatomical asymmetry in schizophrenia: meta-analysis. Br J Psychiatry 178:344–351CrossRefGoogle Scholar
  138. Sperling W et al.(1999) Spontaneous slow and fast MEG activity in male schizophrenics treated with clozapine. Psychopharmacology 142(4):375–382CrossRefGoogle Scholar
  139. Sperling W et al.(2002) Spontaneous, slow and fast magnetoencephalographic activity in patients with schizophrenia. Schizophr Res 58(2–3):189–199MathSciNetCrossRefGoogle Scholar
  140. Sperling W, Kornhuber J, Bleich S (2003) Dipole elevations over the temporoparietal brain area are associated with negative symptoms in schizophrenia. Schizophr Res 64(2–3):187–188CrossRefGoogle Scholar
  141. Streit M et al.(2001) Disturbed facial affect recognition in patients with schizophrenia associated with hypoactivity in distributed brain regions: a magnetoencephalographic study. Am J Psychiatry 158(9):1429–1436CrossRefGoogle Scholar
  142. Teale P et al.(2000) Fine structure of the auditory M100 in schizophrenia and schizoaffective disorder. Biol Psychiatry 48(11):1109–1112CrossRefGoogle Scholar
  143. Teale P et al.(2003) Reduced laterality of the source locations for generators of the auditory steady-state field in schizophrenia. Biol Psychiatry 54(11):1149–1153CrossRefGoogle Scholar
  144. Teale P et al.(2008) Cortical source estimates of gamma band amplitude and phase are different in schizophrenia. NeuroImage 42(4):1481–1489CrossRefGoogle Scholar
  145. Thoma RJ et al.(2003) Lateralization of auditory sensory gating and neuropsychological dysfunction in schizophrenia. Am J Psychiatry 160(9):1595–1605CrossRefGoogle Scholar
  146. Thoma RJ et al.(2004) Auditory sensory gating deficit and cortical thickness in schizophrenia. Neurol Clin Neurophysiol NCN 2004:62Google Scholar
  147. Thoma RJ et al.(2005) M50 sensory gating predicts negative symptoms in schizophrenia. Schizophr Res 73(2–3):311–318CrossRefGoogle Scholar
  148. Thoma RJ et al.(2007) Impaired secondary somatosensory gating in patients with schizophrenia. Psychiatry Res 151(3):189–199CrossRefGoogle Scholar
  149. Thoma RJ et al.(2008) Schizophrenia diagnosis and anterior hippocampal volume make separate contributions to sensory gating. Psychophysiology 45(6):926–935CrossRefGoogle Scholar
  150. Thonnessen H et al.(2008) Optimized mismatch negativity paradigm reflects deficits in schizophrenia patients. A combined EEG and MEG study. Biol Psychol 77(2):205–216CrossRefGoogle Scholar
  151. Tiihonen J et al.(1992) Modified activity of the human auditory cortex during auditory hallucinations. Am J Psychiatry 149(2):255–257CrossRefGoogle Scholar
  152. Tiihonen J et al.(1998) Reversal of cerebral asymmetry in schizophrenia measured with magnetoencephalography. Schizophr Res 30(3):209–219MathSciNetCrossRefGoogle Scholar
  153. Tsuang MM (2000) Schizophrenia: genes and environment. Biol Psychiatry 47(3):210–220CrossRefGoogle Scholar
  154. Tsuchimoto R et al.(2011) Reduced high and low frequency gamma synchronization in patients with chronic schizophrenia. Schizophr Res 133(1–3):99–105CrossRefGoogle Scholar
  155. Tyrer P, Kendall T (2009) The spurious advance of antipsychotic drug therapy. Lancet 373(9657):4–5CrossRefGoogle Scholar
  156. Uhlhaas PJ (2011) High-frequency oscillations in schizophrenia. Clin EEG Neurosci Off J EEG Clin Neurosci Soc (ENCS) 42(2):77–82CrossRefGoogle Scholar
  157. van Lutterveld R et al.(2012) Oscillatory cortical network involved in auditory verbal hallucinations in schizophrenia. PLoS One 7(7):e41149CrossRefGoogle Scholar
  158. Vierling-Claassen D et al.(2008) Modeling GABA alterations in schizophrenia: a link between impaired inhibition and altered gamma and beta range auditory entrainment. J Neurophysiol 99(5):2656–2671CrossRefGoogle Scholar
  159. Weber K et al.(2009) Early life stress and psychiatric disorder modulate cortical responses to affective stimuli. Psychophysiology 46(6):1234–1243CrossRefGoogle Scholar
  160. Wienbruch C et al.(2003) Source distribution of neuromagnetic slow wave activity in schizophrenic and depressive patients. Clin Neurophysiol 114(11):2052–2060CrossRefGoogle Scholar
  161. Wilson TW et al.(2007) Aberrant functional organization and maturation in early-onset psychosis: evidence from magnetoencephalography. Psychiatry Res Neuroimaging 156(1):59–67CrossRefGoogle Scholar
  162. Wilson TW et al.(2008) Cortical gamma generators suggest abnormal auditory circuitry in early-onset psychosis. Cereb Cortex (N Y 1991) 18(2):371–378MathSciNetCrossRefGoogle Scholar
  163. Wilson TW et al.(2009) Aberrant high-frequency desynchronization of cerebellar cortices in early-onset psychosis. Psychiatry Res 174(1):47–56MathSciNetCrossRefGoogle Scholar
  164. Wilson TW et al.(2011) Abnormal gamma and beta MEG activity during finger movements in early-onset psychosis. Dev Neuropsychol 36(5):596–613CrossRefGoogle Scholar
  165. World Health Organization (1992) The ICD-10 classification of mental and behavioural disorders: clinical descriptions and diagnostic guidelines. World Health Organization, GenevaGoogle Scholar
  166. Yamasue H et al.(2004) Abnormal association between reduced magnetic mismatch field to speech sounds and smaller left planum temporale volume in schizophrenia. NeuroImage 22(2):720–727CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Colorado State UniversityFort CollinsUSA

Section editors and affiliations

  • Nobukazu Nakasato
    • 1
  1. 1.Department of EpileptologyTohoku University Graduate School of MedicineSendaiJapan

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