Elsevier

Schizophrenia Research

Volume 208, June 2019, Pages 293-299
Schizophrenia Research

Frontal slow wave resting EEG power is higher in individuals at Ultra High Risk for psychosis than in healthy controls but is not associated with negative symptoms or functioning

https://doi.org/10.1016/j.schres.2019.01.039Get rights and content

Abstract

Decreased brain activity in the frontal region, as indicated by increased slow wave EEG power measured by electrodes place on the skull over this area, in association with negative symptoms has previously been shown to distinguish ultra-high risk (UHR) individuals who later transitioned to psychosis (UHR-P) from those who did not transition (UHR-NP). The aims of the current study were to: 1) replicate these results and 2) investigate whether similar association between increased frontal slow wave activity and functioning shows any value in the prediction of transition to psychosis in UHR individuals. The brain activity, recorded using EEG, of 44 UHR individuals and 38 healthy controls was included in the analyses. Symptom severity was assessed in UHR participants and functioning was measured in both groups. The power in the theta frequency band in the frontal region of UHR individuals was higher than in controls. However, there was no difference between the UHR-P and the UHR-NP groups, and no change in slow frequency power following transition to psychosis. The correlation between delta frequency power and negative symptoms previously observed was not present in our UHR cohort, and there was no association between frontal delta or theta and functioning in either group. Increased delta power was rather correlated with depressive symptoms in the UHR group. Future research will be needed to better understand when, in the course of the illness, does the slow wave activity in the frontal area becomes impaired.

Introduction

Psychosis can result in lifelong functional impairments and comorbidities. Schizophrenia, one of the most common psychotic disorders, is strongly associated with poor executive functioning (Martin et al., 2015) and functional impairments (Green, 1996). Early intervention in psychosis is crucial, as deterioration can occur very aggressively in the early phases of the illness (Birchwood et al., 1998; McGorry et al., 2008). Decreased duration of untreated psychosis is associated with better outcomes, i.e., symptomatic and functional remission and better quality of life (Jaracz et al., 2015). Therefore it is important to identify individuals as early as possible in the course of the illness in order to minimize the duration of untreated attenuated psychotic symptoms, maximize therapeutic engagement and treatment, and potentially prevent or delay the onset of psychosis. The importance of identifying individuals in the pre-psychotic phase led to the development of a set of criteria to identify those individuals deemed at increased risk for psychosis or ultra-high risk (UHR) for psychosis.

Transition rates can be as high as 36% after three years (Fusar-Poli et al., 2013) and individuals can transition up to ten years after having been identified as UHR (Nelson et al., 2013). Although these rates seem to be decreasing (Nelson et al., 2013; Yung et al., 2007), early identification and intervention remains a principal goal in clinical practice. It is essential to improve the identification of UHR individuals to further enhance the close-in strategy aimed at detecting true positives in the UHR cohorts. The identification of endo-phenotypes or physiological biomarkers that are specific to UHR individuals could improve the predictive power needed in the field of early intervention.

The reduction in executive functioning in the frontal region is a well-documented phenomenon in schizophrenia (see reviews: Boutros et al., 2008b; Galderisi et al., 2009), first-episode psychosis (Harris et al., 2006) and UHR (Lavoie et al., 2012) and could be caused by structural brain abnormalities and/or hypometabolism in the frontal lobe. Particularly in individuals with chronic schizophrenia there is reduction of cortical thickness in the bilateral ventromedial prefrontal cortices (Zhang et al., 2015) and hypometabolism in the right dorsolateral prefrontal cortex (Wolkin et al., 1992). Significant decrease in grey matter, white matter and cerebrospinal fluid in the frontal region has all been observed in first-episode schizophrenia as compared to healthy controls (Asami et al., 2012). Similar anatomical changes in the brain can also be seen before the onset of psychosis. Indeed, reduction of grey matter in the frontal region has been found prior to onset of frank psychotic symptoms in individuals with prodromal psychotic symptoms (Pantelis et al., 2003). Frontal hypometabolism in schizophrenia has been associated with negative symptoms (Wolkin et al., 1992), cognitive deficits (Karbasforoushan et al., 2015) and functional deficits (Tully et al., 2014).

However, these frontal deficits are not unique to psychosis and are present in other psychiatric illnesses such as in anxiety (Park et al., 2016) and depression (Tomioka et al., 2015). Therefore, it is worthwhile investigating these frontal deficits in more detail, particularly in terms of their possible relationship with increased risk of transition to psychosis in the UHR population.

Most studies have used positron emission tomography or functional magnetic resonance imaging to investigate deficits in frontal activity. However, electroencephalography (EEG) may present a more convenient way to evaluate frontal deficits. Indeed, measurement of resting brain activity using EEG has shown, with fairly high consistency, that the amount of slow wave activity (delta or theta waves) in the frontal region is increased in schizophrenia. Slow wave power has been correlated with reduced blood flow and glucose utilization, and is therefore thought to reflect reduced functioning in the frontal area (Guich et al., 1989; Ingvar et al., 1976).

In UHR individuals, increased slow wave activity has been shown to predict transition to psychosis in UHR individuals in one study (van Tricht et al., 2014), but not in others (Lavoie et al., 2012). Increased frontal slow wave activity has also been associated with negative symptoms (Lavoie et al., 2012; Zimmermann et al., 2010), i.e., more severe negative symptoms was correlated with increased frontal delta power in UHR individuals who later transitioned to psychosis (UHR-P), but not in those who did not transition (UHR-NT; Lavoie et al., 2012; Zimmermann et al., 2010). Those results are in line with studies in chronic schizophrenia which have constantly shown that increased slow wave activity is correlated with negative symptoms (Gattaz et al., 1992; Guenther et al., 1988; Harris et al., 1999). More recently, increased slow wave activity in the frontal region has been associated with functional outcome in schizophrenia (Chen et al., 2016). To date, there has been no research on the association between slow wave activity and functioning, which is characteristically impaired in the UHR group.

The aims of the present study were to 1) replicate the results obtained by Lavoie et al. (2012), i.e., identify an association between increased slow wave activity in the frontal region and negative symptoms in UHR-P individuals; 2) investigate whether a similar association between increased frontal slow wave activity and poor functioning can predict transition to psychosis in UHR individuals. Our UHR population was first compared against a healthy control group in order to determine whether our UHR population showed abnormally increased frontal delta and/or theta power.

Section snippets

Study setting

Participants were recruited from a larger pool of participants who consented to participate in the Neurapro study, a randomized controlled trial of Omega-3 fatty acids in UHR (McGorry et al., 2017). The trial's methodology has been described in detail elsewhere (Markulev et al., 2015). Full clinical assessment, including an interview with the Comprehensive Assessment of At-Risk Mental States (CAARMS; Yung et al., 2005) to determine UHR status, and EEG recordings were conducted prior to the

Characterization of UHR participants compared to a healthy control group

The data from eight controls and three UHR participants had to be excluded due to poor quality and, as a consequence, the number of participants in each group was 38 and 44, respectively.

Table 1 shows that the control and UHR groups did not differ in terms of their age and gender distribution. As expected, healthy controls scored significantly higher on all four functioning scales, namely the SOFAS, both global functioning scale and the AQoL. 46.5% of UHR participants were on antidepressant

Discussion

In the present study, an increase in the theta EEG power in the frontal region of UHR participants was measured compared to controls. However, there was no difference between groups in the delta EEG power. There was no significant difference between the UHR-P and the UHR-NP groups in slow wave power in the frontal right area. While our results showed a significant positive correlation between delta power and depressive symptoms in the UHR group, the association between delta frequency power and

Conclusion

Our results showed increased power in the theta band in the frontal region of UHR individuals compared to controls, but not in the delta band. Increased slow wave activity is commonly observed in psychosis, particularly in the later stages of the illness. To our knowledge, this was the first study to look at the association between frontal slow wave activity and functioning in a UHR population. Our results showed no association between functioning and the slow wave power in the frontal region

Conflict of interest

The authors have no conflict of interest to declare.

Acknowledgements

We thank all of the participants and their families.

Contributions

SL designed the study, wrote the protocol and performed the statistical analyses. MS and BJ processed the data, MS drafted the manuscript. AA performed the EEG recordings. HPY gave critical advice on the statistical analyses. All authors critically reviewed the manuscript.

Role of the funding source

This work was supported by an Early Career Research grant from the University of Melbourne (SL) and a NARSAD grant (17537; TW). The Neurapro study was supported by grant 07TGF-1102 from the Stanley Medical Research Institute, grant 566529 from the NHMRC Australia Program and a grant from the Colonial Foundation. BN was supported by NARSAD Independent Investigator Grant from the Brain & Behavior Research Foundation (23199) and TW was supported by Career Development Fellowship from the NHMRC

References (58)

  • M.X. Huang et al.

    An automatic MEG low-frequency source imaging approach for detecting injuries in mild and moderate TBI patients with blast and non-blast causes

    NeuroImage

    (2012)
  • D.H. Ingvar et al.

    Correlation between dominant EEG frequency, cerebral oxygen uptake and blood flow

    Electroencephalogr. Clin. Neurophysiol.

    (1976)
  • K. Jaracz et al.

    Psychosocial functioning in relation to symptomatic remission: a longitudinal study of first episode schizophrenia

    Eur. Psychiatry

    (2015)
  • J.W. Kam et al.

    Resting state EEG power and coherence abnormalities in bipolar disorder and schizophrenia

    J. Psychiatr. Res.

    (2013)
  • W. Klimesch et al.

    A short review of slow phase synchronization and memory: evidence for control processes in different memory systems?

    Brain Res.

    (2008)
  • S. Lavoie et al.

    Frontal delta power associated with negative symptoms in ultra-high risk individuals who transitioned to psychosis

    Schizophr. Res.

    (2012)
  • S. Lavoie et al.

    Impaired mismatch negativity to frequency deviants in individuals at ultra-high risk for psychosis, and preliminary evidence for further impairment with transition to psychosis

    Schizophr. Res.

    (2018)
  • C. Pantelis et al.

    Neuroanatomical abnormalities before and after onset of psychosis: a cross-sectional and longitudinal MRI comparison

    Lancet

    (2003)
  • S. Ranlund et al.

    Resting EEG in psychosis and at-risk populations—a possible endophenotype?

    Schizophr. Res.

    (2014)
  • S.R. Sponheim et al.

    Clinical and biological concomitants of resting state EEG power abnormalities in schizophrenia

    Biol. Psychiatry

    (2000)
  • L.M. Tully et al.

    Impaired cognitive control mediates the relationship between cortical thickness of the superior frontal gyrus and role functioning in schizophrenia

    Schizophr. Res.

    (2014)
  • M.J. van Tricht et al.

    Can quantitative EEG measures predict clinical outcome in subjects at Clinical High Risk for psychosis? A prospective multicenter study

    Schizophr. Res.

    (2014)
  • A. Yung et al.

    Risk factors for psychosis in an ultra high-risk group: psychopathology and clinical features

    Schizophr. Res.

    (2004)
  • R. Zimmermann et al.

    EEG spectral power and negative symptoms in at-risk individuals predict transition to psychosis

    Schizophr. Res.

    (2010)
  • N.C. Andreasen

    Negative symptoms in schizophrenia. Definition and reliability

    Arch. Gen. Psychiatry

    (1982)
  • A. Auther et al.

    Global Functioning: Social Scale (GF: Social)

    (2006)
  • M. Birchwood et al.

    Early intervention in psychosis. The critical period hypothesis

    Br. J. Psychiatry

    (1998)
  • Y.H. Chen et al.

    Frontal slow-wave activity as a predictor of negative symptoms, cognition and functional capacity in schizophrenia

    Br. J. Psychiatry

    (2016)
  • P. Fusar-Poli et al.

    At risk for schizophrenic or affective psychoses? A meta-analysis of DSM/ICD diagnostic outcomes in individuals at high clinical risk

    Schizophr. Bull.

    (2013)
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