Emerging evidence suggests that efficient information transfer in neural networks depends crucially upon the balance between excitation and inhibition (E/I-Balance) (Shu et al., 2003; Haider et al., 2006). A shift in E/I-balance towards elevated excitability has been recently implicated in the pathophysiology of schizophrenia (ScZ) (Driesen et al., 2013; Lisman, 2012; Murray et al., 2014; Uhlhaas and Singer, 2012) and could provide a crucial intermediate phenotype that links basic circuit abnormalities with observations from non-invasive neuroimaging. However, it is currently unclear when such abnormalities arise in the course of ScZ and their relationship to clinical and behavioural features associated with the syndrome.

Among the circuit mechanisms that are involved in the maintenance of E/I-balance, parvalbumin-expressing (PV+) γ-Aminobutyric acid (GABA)ergic interneurons are of particular interest (Xue et al., 2014) as inhibition of pyramidal cell activity regulates the output of cell-assemblies and leads to rhythmic fluctuations in excitability or neural oscillations (Sohal et al., 2009; Kopell and LeMasson, 1994). Moreover, there is consistent evidence that α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA)- and N-methyl-D-aspartate Receptor (NMDA-R)-mediated activation of PV+ interneurons is essential for the generation of oscillatory activity (Carlén et al., 2012; Fuchs et al., 2007), especially at gamma-band (30–90 Hz) frequencies. In ScZ, converging evidence from genetics (Pocklington et al., 2015), post-mortem data (Lewis et al., 2012) and brain imaging (Kegeles et al., 2012) have supported the possibility that E/I-balance is disrupted which is consistent with observations from electro/magnetoencephalographical (EEG/MEG)-data that task-related, gamma-band oscillations are reduced (Uhlhaas and Singer, 2010).

One central prediction for a shift in E/I-balance in ScZ towards increased excitability-levels is an increase in spontaneous gamma-band activity and a wealth of evidence from pre-clinical (Yizhar et al., 2011; Kocsis, 2012; Pinault, 2008) as well as data in healthy controls following NMDA-R hypofunctioning (Rivolta et al., 2015; Shaw et al., 2015) highlight that transient increases in excitability are associated with enhanced occurrence of gamma-band power. For example, NMDA-R antagonists have been show to increase spontaneous gamma-band activity in both human (Rivolta et al., 2015) and pre-clinical research (Saunders et al., 2012).

Further support for the E/I-balance hypothesis comes from Magnetic Resonance Spectroscopy (MRS) studies that have investigated alterations in Glutamate and GABA-concentrations across cortical and subcortical areas. A consistent finding is an elevation of Glutamate-levels across illness-stages in ScZ (Merritt et al., 2016) while the evidence for changes in GABA-levels is less consistent (Egerton et al., 2017), supporting the view for a shift towards increased excitability of neural circuits.

To provide further critical support for the E/I-balance hypothesis, we applied an advanced MEG approach to examine resting-state MEG-recordings in participants meeting clinical high-risk criteria (CHR), first-episode (FEP) and chronic ScZ-patients. Currently, there is only limited evidence available from EEG/MEG-recordings in ScZ-patients (Rutter et al., 2009; Andreou et al., 2015; Ramyead et al., 2015), which has tested comprehensively the pattern of spontaneous gamma-band activity across illness-stages. MEG is characterized by an improved signal-to-noise ratio for measurements of high-frequency oscillations compared to EEG (Muthukumaraswamy and Singh, 2013). MEG is also ideally suited for source-reconstruction that allows the identification of the anatomical lay-out of resting-state networks with high spatial resolution.

Accordingly, we focused on the following questions: (1) Are there differences in resting-state gamma-band networks in ScZ and what is the direction of effects across different illness-stages? Previous data highlighted that the signatures of fMRI resting-state networks during early stage psychosis, but not in chronic ScZ, resemble the acute effects of NMDA-R hypofunctioning (Anticevic et al., 2015). In addition, there is evidence that glutamatergic neurotransmission is increased in younger ScZ-patients (Marsman et al., 2013). Accordingly, we predicted that gamma-band activity in CHR and possibly FEP-patients would be upregulated, while in chronic ScZ-patients the opposite pattern would occur. (2) Are gamma-band fluctuations related to clinical symptoms and cognitive deficits in ScZ? Because of the role E/I-balance in shaping information transfer across large-scale networks (Shu et al., 2003; Yizhar et al., 2011), we expected that alterations in gamma-band power would closely correlate with neurocognitive deficits and clinical symptoms across clinical groups. (3) What is the nature of alterations in resting-state gamma-band activity in ScZ? Changes could involve band-limited as opposed to alterations across the entire gamma-band frequency with important implications for the interpretation of these phenomena. And (4) Are alterations in gamma-band power in CHR-participants related to changes in GABA and Glutamate/Glutamine (Glx) concentrations? Based on the relationship between E/I-balance and gamma-band power (Yizhar et al., 2011), we predicted that CHR-participants would be characterized by an altered Glx/GABA-ratio that correlates with increased high-frequency activity.

Emerging evidence suggest that circuit dysfunctions underlying the symptoms and cognitive deficits in ScZ may be caused by an alteration in E/I-balance parameters (Uhlhaas and Singer, 2012; Anticevic et al., 2012). However, direct physiological evidence for this hypothesis from non-invasive electrophysiological and neuroimaging data is so far scarce. The current study addressed this question through the investigation of resting-state gamma-band activity and MRS Glx/GABA levels, two important signatures of E/I-balance (Yizhar et al., 2011; Rowland et al., 2005), across illness stages of ScZ in MEG-data and their relationship to clinical and neuropsychological variables. Recent evidence suggests that early stage psychosis may be characterized by distinct neural signatures compared to chronic ScZ (Anticevic et al., 2015), involving a gradual shift of E/I-balance that implicates elevated glutamatergic neurotransmission at illness-onset.

Consistent with this hypothesis, we observed distinct patterns of resting-state gamma-band power in CHR-, FEP- and chronic ScZ-groups. Specifically, CHR-participants were characterized by increased gamma-band power compared to both FEP and chronic ScZ in a network including frontal and right temporal structures. FEP-patients showed largely reduced 30–90 Hz power over frontal, central and temporal areas but also showed additional increases in visual areas not observed in the chronic ScZ-group.

Importantly, the changes observed in gamma-band power across illness stages covered the entire 30–90 Hz frequency range, except for the CHR group where the increases in spectral power selectively involved the 64–90 Hz frequency band, suggesting that high gamma-band activity may constitute a marker for psychosis-risk. Overall, the pattern of spectral changes is distinct from activity associated with an oscillatory process observed during task-contexts (Hoogenboom et al., 2006; Fries et al., 2008), whereby a circumscribed modulation within a particular frequency is considered to be the hallmark of an oscillation.

The broad-band modulation observed in our data is compatible with the effects of impaired NMDA-R on PV+ cells. Carlén et al. (2012) showed that reduced NMDA-R neurotransmission on PV+ interneurons is associated with increased broad-band gamma-band power at rest while the ability to generate gamma-band oscillations after optogenetic drive of PV-interneurons was reduced. These data thus also replicate the large body of evidence for impaired generation of task-related, band-limited gamma-band oscillations in ScZ (Uhlhaas and Singer, 2010; Thuné et al., 2016), highlighting the crucial importance of impaired E/I-balance for the explanation for alterations in both resting-state as well as task-related gamma-band activity in ScZ.

Elevated excitation due to NMDA-R hypofunctioning has been implicated as a possible mechanism for the emergence of psychosis (Schobel et al., 2013) that could transiently lead to elevated high-frequency activity. This hypothesis is crucially supported by the MRS-data of Glx/GABA concentrations. Specifically, we observed that Glx-levels were elevated while GABA-concentrations were intact in CHR-participants, highlighting that psychosis-risk is intimately related to elevated glutamatergic neurotransmission. This hypothesis is consistent with previous MRS-data of elevated Glx-levels in CHR-participants (de la Fuente-Sandoval et al., 2011; Tandon et al., 2013) and findings in FEP (Kahn and Sommer, 2015).

The current findings critically extend these data by demonstrating that increased Glx-levels extend into visual cortex, which is consistent with evidence that alterations in visual perception may be indicative for transition to ScZ in CHR-participants (Klosterkötter et al., 2001). Moreover, our findings provide the first link between changes in E/I-balance parameters and fluctuations in gamma band power as increased Glx and Glx/GABA ratio correlated significantly with elevated 30-90 Hz activity.

The functional significance of the changes in resting-state gamma-band activity is underlined by the close relations with both neurocognitive and clinical parameters. During normal brain functioning, E/I-balance is fundamental for shaping information transmission of large-scale networks (Yizhar et al., 2011; Saunders et al., 2012). Consistent with this hypothesis, we observed that the degree of reductions in 30–90 Hz gamma-band power in both FEP and chronic ScZ-patients correlated with impairments in cognition and symptoms of emerging psychosis. In the CHR-group, impaired neurocognition correlated with elevated 64–90 Hz power while the presence of attenuated psychotic symptoms showed the opposite relationship. In contrast, deficits in neurocognition in FEP- and chronic ScZ-patients showed a robust correlation with reductions in gamma-band power, highlighting that disruptions in E/I-balance across illness stages in ScZ can potentially account for relations with cognitive impairments.

Robust relationships were observed between reductions in gamma-band power with age, in particular in the chronic ScZ-group. Previous MRI-data has highlighted that reduction in GM could reflect an accelerated aging process in ScZ, possibly related to outcome and medication (Schnack et al., 2016). Accordingly, one scenario is that the reductions in spectral power in chronic ScZ-patients reflect progressive pathophysiological processes that lead to circuit dysfunctions as reflected by an impaired generation of high-frequency activity and pronounced cognitive deficits. Moreover, it is conceivable that anti-psychotic medication may also contribute to the observed reductions in gamma-band power across the illness course as loss of GM has been associated with antipsychotic exposure (Ho et al., 2011) and pre-clinical evidence suggests that antipsychotic medications can reduce gamma-band oscillations (Schulz et al., 2012).

The current data have implications for the interpretation of gamma-band fluctuations and the pathophysiology of ScZ. Spontaneous changes in gamma-band power are representing a distinct aspect of electrophysiological changes typically observed during task-related scenarios that could provide important insights into circuit abnormalities. Thus, increased spiking activity at high frequencies may interfere with the generation of task-related oscillations as has been proposed previously (Hirano et al., 2015). However, we would like to note that contrary to empirical findings, this scenario likely applies primarily to early stage psychosis as chronic ScZ-patients were characterized by reduced gamma-band power.

The study has several limitations. Notably, the current conclusions are based on cross-sectional findings. Accordingly, follow-up data need to determine whether increased resting-state gamma-band power is also predictive for clinical outcomes in CHR-populations. In addition, there were differences in age- and sex-composition across clinical samples. We would like to note that the rescaling procedure employed and matched control participants for the CHR- and FEP-groups highlight that differences in gamma-band power represent the effects of different stages of psychosis. Secondly, it is currently unclear whether the trajectory of changes in spectral power could be influenced by anti-psychotic medication. However, we would like to emphasize that the large majority of CHR-participants and FEP-patients were currently not being treated with antipsychotic medication. Accordingly, it is unlikely that medication effects drove the differences at illness-onset in gamma-power.

Finally, the current study did not examine dynamic aspects of resting-state activity. There is evidence to suggest resting-state networks are not stationary. Accordingly, future studies could examine alterations in micro-states and related phenomena, such as approaches employing a Hidden Markov Model (HMM), to provide further insights into alterations of resting-state activity in ScZ (Rieger et al., 2016; Vidaurre et al., 2018).

A full, anonymized data-set of MRS-recordings plus additional MEG-data from occipital brain regions associated with Figure 5 has been uploaded to Dryad.

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Author details

1. Tineke Grent-'t-Jong

   Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, United Kingdom

   Contribution

   Conceptualization, Software, Formal analysis, Methodology, Writing—original draft, Writing—review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-3177-5346

2. Joachim Gross

   1. Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, United Kingdom
   2. Institute for Biomagnetism and Biosignalanalysis, University of Muenster, Muenster, Germany

   Contribution

   Formal analysis, Funding acquisition, Writing—original draft

   Competing interests

   No competing interests declared

3. Jozien Goense

   Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, United Kingdom

   Contribution

   Formal analysis, Writing—original draft

   Competing interests

   No competing interests declared

4. Michael Wibral

   MEG-Unit, Goethe University, Frankfurt am Main, Germany

   Contribution

   Resources

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-8010-5862

5. Ruchika Gajwani

   Mental Health and Wellbeing, Institute of Health and Wellbeing, University of Glasgow, Glasgow, United Kingdom

   Contribution

   Project administration

   Competing interests

   No competing interests declared

6. Andrew I Gumley

   Mental Health and Wellbeing, Institute of Health and Wellbeing, University of Glasgow, Glasgow, United Kingdom

   Contribution

   Funding acquisition

   Competing interests

   No competing interests declared

7. Stephen M Lawrie

   Department of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom

   Contribution

   Funding acquisition

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-2444-5675

8. Matthias Schwannauer

   Department of Clinical Psychology, University Edinburgh, Edinburgh, United Kingdom

   Contribution

   Funding acquisition

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-4683-2596

9. Frauke Schultze-Lutter

   1. University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
   2. Department of Psychiatry and Psychotherapy, Medical Faculty, Heinrich-Heine-University, Düsseldorf, Germany

   Contribution

   Methodology

   Competing interests

   No competing interests declared

10. Tobias Navarro Schröder

    Kavli Institute for Systems Neuroscience and Centre for Neural Computation, Norwegian University of Science and Technology, Trondheim, Norway

    Contribution

    Project administration

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0001-6498-1846

11. Dagmar Koethe

    1. Department of Psychosomatics and Psychotherapeutic Medicine, Central Institute of Mental health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
    2. Brain and Mind Centre, University of Sydney, Sydney, Australia

    Contribution

    Methodology

    Competing interests

    No competing interests declared

12. F Markus Leweke

    1. Department of Psychosomatics and Psychotherapeutic Medicine, Central Institute of Mental health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
    2. Brain and Mind Centre, University of Sydney, Sydney, Australia
    3. Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany

    Contribution

    Methodology

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-8163-195X

13. Wolf Singer

    1. Department of Neurophysiology, Max Planck Institute for Brain Research, Frankfurt am Main, Germany
    2. Ernst Strüngmann Institute for Neuroscience and the Max Planck Society, Frankfurt am Main, Germany
    3. Frankfurt Institute for Advanced Studies, Frankfurt am Main, Germany

    Contribution

    Project administration

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-8299-2319

14. Peter J Uhlhaas

    Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, United Kingdom

    Contribution

    Conceptualization, Supervision, Funding acquisition, Methodology, Writing—original draft, Project administration, Writing—review and editing

    For correspondence

    peter.uhlhaas@glasgow.ac.uk

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-0892-2224

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