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. Author manuscript; available in PMC: 2022 Feb 1.
Published in final edited form as: Schizophr Res. 2021 Jan 9;228:36–42. doi: 10.1016/j.schres.2020.12.014

Distinct alterations in resting-state electroencephalogram during eyes closed and eyes open and between morning and evening are present in first-episode psychosis patients

Yingyi Zhang a, Alexandra Geyfman a, Brian Coffman a, Kathryn Gill a, Fabio Ferrarelli a,*
PMCID: PMC7987764  NIHMSID: NIHMS1658978  PMID: 33434730

Abstract

Abnormalities in resting-state electroencephalogram (rs-EEG) activity have been previously reported in schizophrenia. While most rs-EEG recordings were performed in patients with chronic schizophrenia during eyes closed (EC), only a handful of studies have investigated rs-EEG activity during both EC and eyes open (EO) conditions. It is also unknown whether EC and EO rs-EEG alterations are present at illness onset, and whether they change during the day. Here, we performed EC and EO rs-EEG recordings in the morning (AM) and evening (PM) in twenty-six first-episode psychosis (FEP) patients and seventeen matched healthy controls (HC). In AM/EC rs-EEG, a widespread reduction was found in low alpha power in FEP relative to HC. In PM/EC, the FEP group demonstrated a trend toward decreased theta power in parietal regions, while decreased high alpha power in frontal and left parietal regions was present during PM/EO. Moreover, reduced low alpha power during AM/EC was associated with worse positive symptoms. Altogether, those findings indicate that rs-EEG alterations are present in FEP patients at illness onset, that they are linked to the severity of their psychosis, and that distinct RS abnormalities can be detected in different conditions of visual alertness and time of the day. Future work should therefore account for those factors, which will help reduce variability of rs-EEG findings across studies and may serve as monitoring biomarkers of illness severity in schizophrenia and related psychotic disorders.

Keywords: Schizophrenia, First-episode psychosis, EEG, Resting-state

1. Introduction

Resting-state electroencephalogram (rs-EEG) recordings are often utilized to investigate spontaneous brain activity (Khanna et al., 2015) . Rs-EEGs are measured during wakefulness while in a relaxed state with the eyes either closed (EC) or open (EO), and offer some advantages compared to EEG recordings collected during behavioral tasks. First, compared to cognitive tasks, rs-EEGs are easy to administer since no cognitive effort is required. This makes them feasible in a wide range of psychiatric populations, including acutely psychotic patients. Second, oscillatory abnormalities observed at rest are more likely to reflect intrinsic defects in underlying cortical neurons, rather than fluctuations in the level of attention or reduced motivation, which represent common confounding factors in schizophrenia (SCZ) and other psychotic patients. Furthermore, the recent availability of high-density (N≥64 channel) EEG systems has allowed for exploring local differences in rs-EEG in EC and EO conditions between patient and control populations in greater detail.

Most rs-EEG studies in SCZ have been conducted during EC, when alpha oscillations are strongest, whereas only a handful of studies have investigated rs-EEG in SCZ during EO, when theta rhythms are most easily observed. Although reduced alpha is the most reported rs-EEG abnormality in SCZ/psychosis, findings have been inconsistently reported and time of day assessment has not been evaluated as a potential source of this variability. Additionally, no study has explored differences in morning (AM) and evening (PM) between psychotic and healthy control (HC) groups (Cajochen et al., 1995). Furthermore, theta activity increases with time spent awake in healthy population, which has not been shown in psychotic patients and may have impact on EEG findings when recordings are conducted at different time of day. Thus, it is important to take into consideration the difference between morning and evening of rs-EEG, besides the difference between EC and EO conditions. Indeed, it has been suggested that EC and EO represent internal processing and external processing, respectively. EC is associated with reduced arousal, reduced activation of autonomic nervous system and an interoceptive state characterized by imagination, while EO reflects increased cortical reactivity and visual information processing (Bellato et al., 2020).

It has been reported that factor analyses applied to spontaneous EEG under eyes-closed condition revealed a lower and a higher alpha band (Lopes da Silva et al., 1997). Additional evidence indicates that lower and higher alpha have their own characteristics and serve different purposes. First, higher alpha frequencies during EO were associated with a decrease in the global signal amplitude accompanied by a substantial increase in vigilance, which was not found in lower alpha (Wong et al., 2016) . Second, lower alpha rhythm event related desynchronization (ERD) reflected general task demands and attentional processes, and showed a widespread movement-type–unspecific desynchronization pattern about similar for finger or foot movement, whereas the higher alpha rhythm ERD showed a more topographically restricted, movement-type–specific pattern, clearly different with finger and foot movement (Pfurtscheller, 2003). Furthermore, contralateral somatosensory alpha ERD significantly correlated with accuracy reaction time, which was stronger in the higher alpha band compared to the lower alpha band (Su et al., 2020).

Alpha activity is generated within the thalamo-cortical system by thalamo-cortical and cortico-thalamic connections. Thus, deficits in rs-EEG alpha, especially during EO when this activity is usually most prominent, point to dysfunctions in thalamo-cortical modules in psychotic patients relative to healthy individuals. These abnormalities can be localized by employing high density (hd)-EEG recordings and are likely to contribute to the neurobiology as well as to some salient clinical features of psychotic disorders (e.g., severity of positive symptoms).

Resting state EEG findings so far in SCZ and psychosis have been variable (Bandyopadhyaya et al., 2011; Begic et al., 2011; Kim et al., 2015), and although this may reflect the heterogeneity of these disorders, it may also be related to differences in resting state condition (EO, EC) and time of the day (AM. PM). Although most EEG recordings were performed in chronic patients, with no RS EC and EO data available for the same group at the beginning of psychosis, fewer studies have investigated and reported RS EC abnormalities in FEP patients (Koenig et al., 2001; Newson and Thiagarajan, 2018; Sponheim et al., 1994). In this study, we accounted for these factors (i.e., resting state condition, time of the day) by performing for the first time EO and EC resting state recordings in the AM and PM in FEP patients, which further helped mitigate other potential confounds like chronic exposure to antipsychotic medications and duration of illness. We also employed hd-EEG recordings to investigate local differences between FEP and HC groups.

2. Methods

2.1. Recruitment

Twenty-six FEP and seventeen HC were recruited for this study. FEP were recruited from the emergency room (ER) at Western Psychiatric Hospital of the University of Pittsburgh Medical Center (UPMC), and through inpatient and outpatient services within and outside of UPMC. Although we made the initial contact with some of the potential participants in the ER, the consenting was obtained in the outpatient setting, where we ensured of the patients’ ability to consent to the study. The consenting and interview were conducted by the Psychosis Recruitment and Assessment Core team independently. All FEP patients were administered the Scale for the Assessment of the Positive and Negative Symptoms (SAPS and SANS), to determine the severity of clinical symptoms (Malla et al., 2016). SAPS score was calculated as the sum of the symptom item scores of the four subscales: hallucinations, delusions, bizarre behavior, and formal thought disorder. SANS score was calculated as the sum of the symptom item scores of the four subscales: affective flattening/blunting, alogia, apathy and asociality. HC were recruited from the local community through physical and online advertisements. More details are shown in the Supplementary document (Supp. Doc). All procedures involving human subjects/patients were approved by the University of Pittsburgh Institutional Review Board, and all participants provided written informed consent prior to completing any of the study procedures.

2.2. Inclusion and exclusion criteria

Inclusion criteria for all participants were: 1) aged 18–40; 2) no major medical or neurological illness affecting CNS function (including pregnancy and head injury); and 3) no DSM-IV intellectual developmental disorder. The Wechsler Abbreviated Scale of Intelligence (WASI) was administered to aid in identifying an intellectual developmental disorder. Inclusion criteria for FEP patients were: 1) experiencing first psychotic episode, defined by report of symptoms and/or history of treatment; 2) had no more than 2 months of lifetime antipsychotic treatment. Inclusion criteria for HC: 1) no history of major psychiatric illness; 2) no treatment with an antipsychotic at any time; 3) no first- degree family history of schizophrenia spectrum disorder and/or mood disorder with psychotic features; 4) no current medication affecting brain structure or function (anti-epilepsy drugs and mood stabilizers). To minimize the occurrence of substance-included psychosis, exclusion criteria for FEP patients included any type of substance use disorder regardless of the relation to psychosis, by conducting screening questions: 1) had a psychotic illness with a temporal relation to a substance use disorder; 2) co-morbidity of DSM-IV psychoactive substance dependence within the past 6 months; 3) substance abuse (other than cannabis and/or alcohol) within the past month.

2.3. Resting-state EEG acquisition

Participants were fitted with a 64-channel high-density electroencephalography net based on the 10-10 system (hd-EEG; Geodesic System 400, Electrical Geodesics Inc., EGI). EEG data were acquired at a sample rate of 250 Hz. Impedances of EEG channels were all under 50kohms and acquisition was vertex referenced. Participants sat comfortably in an armchair and were instructed to relax while rs-EEG recordings were performed. During eyes open recordings, participants were instructed to fixate on a spot on the wall. Two three-minute sessions with eyes open (EO) and two three-minute sessions with closed (EC) were acquired using the following sequence: EO-EC-EO-EC. Evening (PM) rs-EEGs were acquired between 9pm to 12am before bedtime. Overnight sleep EEGs were recorded. Morning (AM) rs-EEGs were acquired between 6am to 9am the next morning after the participants woke up. No caffeine intake was allowed during the whole study procedure. Participants could take their medications on their regular routine. Wakefulness was assessed by research staff, including EEG lab technicians, with extensive experience collecting EEG recordings.

2.4. Resting-state hd-EEG data processing

EEG data were processed in MATLAB (The MathWorks Inc., Natick, MA) for each study subject using custom-made scripts. Signals were down-sampled to 128 Hz and filtered using 2 Hz high-pass and 58 Hz low-pass filters. Noisy segments with large muscle activity or movement artifacts were removed manually by visual inspection of EEG signals throughout the whole recordings. Then channels with an amplitude greater than two standard deviations from the vertex-referenced mean, as well as channels with extremely low amplitude (“flat channels”) were removed. These channels were marked and excluded from statistical analyses. Overall, >80% of the data recorded for each participant and >90% of the channels were retained after this procedure. Data was then re-referenced to the average of all channels. Ocular and muscle movement as well as cardiac signal were removed by means of independent component analysis (ICA; infomax algorithm) using EEGLAB toolbox. Power spectral density (PSD) was computed using Welch’s modified periodogram method in 2-s Hamming windows (50% overlap) in Brainstorm (http://neuroimage.usc.edu/brainstorm). At each electrode, absolute power in the delta (2–4.5 Hz), theta (5–7 Hz), low alpha (7.5–10 Hz), and high alpha (10.5–15 Hz) bands were calculated. Sleep architecture data processing followed the same procedure as in (Kaskie et al., 2019).

2.5. Statistics

To compare demographic characteristics and sleep architecture between FEP patients and HC, χ2 test and Student’s t-tests for independent samples (two tailed) were performed in SPSS. To assess differences in rs-EEG power between FEP patients and HC, channel-wise permutation-based statistics (Student’s t-tests for independent samples, two tailed; 1000 permutations) were conducted. To further compare differences in rs-EEG power between morning and evening within FEP group and HC group, channel-wise permutation-based statistics (paired Student’s t-tests, two tailed were used; 1000 permutations) were conducted. All permutation statistics were performed in Brainstorm, with α=0.05, and controlling for multiple comparisons across channels (correct for signals) using false discovery rate (FDR) correction (q=0.099 to detect trend level effects, and q=0.05 to detect more statistical robust findings) (Benjamini et al., 2001). Averages of rs-EEG power were computed for every channel for each condition (AM /EC, AM/EO, PM/EC, PM/EO) in FEP and HC groups and topographic maps for the two groups were generated and displayed in Brainstorm. Finally, we performed Pearson correlation analyses between the average rs-EEG power within frequency bands/channel clusters (contiguous groups of significant channels) between groups and symptom scores (measured with the SAPS and SANS) as well as medication dose. Correlations between disturbed sleep architectures and disturbed rs-EEGs within frequency bands/channel clusters and clinical symptoms were also performed to explore the impact of sleep disturbance on rs-EEG changes.

3. Results

3.1. Subject characteristics

Table 1 summarizes demographic and clinical characteristics of FEP and HC. There were no significant between-group differences in gender or age. Nineteen FEP patients were minimally treated (<2-month lifetime exposure) with antipsychotic medications, whereas seven were medication-naive at the time of the EEG recordings. Sixteen patients were diagnosed with SCZ, 4 patients were diagnosed with psychosis not otherwise specified, 3 patients were diagnosed with schizoaffective disorder, 2 patients were diagnosed with SCZ with major depressive disorder, and 1 patient was diagnosed with bipolar disorder.

Table 1.

Demographic and clinical characteristics of participants

Characteristics First-episode psychosis (N=26) Healthy controls (N=17) p-values
Gender (male/female) 16/10 13/4 0.343
Age (years, mean ± SD) 23.0 ± 5.7 23.4 ± 4.9 0.892
Taking medications (Na) 19
Daily medication dose CPZb equivalent 242.7 ± 191.5
Antipsychotic type (N) Risperidone 10
Olanzapine 5
Haloperidol 2
Aripiprazole 2
Quetiapine 1
Lurasidone 1
Schizophrenia Schizophrenia 16
subtype (N) Psychosis not otherwise specified 4
Schizoaffective disorder 3
SCZ with major depressive disorder 2
Bipolar disorder 1
SAPSc (mean ± SD)
19.0 ± 11.9
SANSd (mean ± SD)
31.0 ± 7.8
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a

All patients had been treated for less than 2 months at the time of the sleep EEG recordings; two patients were treated with two types of antipsychotic medications.

b

CPZ, chlorpromazine;

c

SAPS, scale for the assessment of the positive symptoms;

d

SANS, scale for the assessment of negative symptoms.

3.2. Sleep architecture parameters

FEP patients had significantly increased sleep latency as well as reduced total sleep time and sleep efficiency compared to HC (Table 2). However, FEP and HC subjects did not differ in time or percentage spent in both non-REM and REM sleep.

Table 2.

Sleep architecture parameters of study groups

Sleep measures First-episode psychosis Healthy controls p-values
Total sleep time (min) 387 ± 88 424 ± 57 0.14
Sleep onset latencya (min) 44 ± 53 15 ± 14 0.04
WASOb (min) 80 ± 58 43 ± 21 0.02
NREM N1 (min, %) 30 ± 18 (8%) 33 ± 14 (8%) 0.64
NREM N2 (min, %) 210 ± 65 (54%) 229 ± 27 (54%) 0.26
NREM N3 (min, %) 66 ± 38 (17%) 79 ± 34 (18%) 0.27
REM (min, %) 81 ± 38 (21%) 84 ± 24 (20%) 0.81
Sleep efficiency (%) 76 ± 15 88 ± 6 0.003
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Measures given as mean ± standard deviation, unless otherwise specified.

a

Sleep onset latency is defined as the time from the beginning of the recording until the first NREM sleep stage 2 epoch.

b

WASO=wake after sleep onset.

3.3. EEG power differences between FEP and HC in the morning and evening during EC and EO

In the morning EC resting state condition, FEP showed a reduction in low alpha EEG power compared to HC (q=0.05). This power reduction was rather diffuse and involved frontal, central, parietal, and occipital regions (Fig. 1A). Average power of all contiguous groups of significant channels were calculated and defined as “AM/EC cluster in low alpha band” for further correlation analysis. There was no significant difference in rs-EEG power between FEP patients and HC in the morning EO resting state, thus there was no data available for relative correlation analysis. Standard deviation topography map of AM/EC condition is shown in Supp. Fig1 A.

Fig. 1. Resting state average EEG power across all channel topographic maps.

Fig. 1.

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A: measured with eyes closed (EC) in the morning (AM). Topographic low alpha band (7.5-10 Hz) EEG power in FEP patients (Left) and HC (Middle). AM/EC spectral power was reduced in FEP patients relative to HC in the EEG low alpha band (p<0.05 FDR). Topographic T statistic maps showed that this power decrease was widespread and involved most of the recorded regions (N=51channels, red area) (Right).

B: measured with eyes closed (EC) in the evening (PM). Topographic theta band (5-7 Hz) EEG power in FEP patients (Left) and HC (Middle). PM/EC spectral powers are in FEP patients relative to HC in the EEG theta band (FDR q<0.099). Topographic T statistic maps revealed that this power reduction was present in parietal regions (N=17 channels, red area) (Right).

C: measured with eyes open (EO) in the evening (PM). Topographic high alpha band (10.5-15 Hz) EEG power of significant electrodes in FEP patients (Left) and HC (Middle). PM/EO spectral powers are in FEP patients relative to HC in the high alpha range (p<0.05 FDR). Topographic T statistic maps revealed that this power reduction was localized in frontal and posterior parietal regions (N=12 channels, red area) (Right).

In the evening EC resting state condition, FEP patients had reduced PM/EC theta band EEG spectral power relative to HC (q=0.099). This power decrease was localized over parietal regions (Fig. 1B). Standard deviation topography map of PM/EC condition is shown in Supp. Fig1 B. Average power of contiguous parietal channels with significance was calculated and defined as “PM/EC cluster in theta band” for further correlation analysis. During the PM/EO condition, we observed significantly reduced high alpha rs-EEG in FEP patients relative to HC (q=0.05). This power reduction localized to frontal and left parietal regions (Fig. 1C). Standard deviation topography map of PM/EO condition is shown in Supp. Fig1 C. Average power of contiguous frontal and parietal channels with significance was calculated and defined as “PM/EO cluster in high alpha band” for further correlation analysis.

There was no significant difference in EEG power between FEP and HC in the following bands and conditions: AM/EC delta, theta and higher alpha bands; PM/EC delta and alpha bands; AM/EO delta, theta and alpha bands; PM/EO delta, theta and lower alpha bands.

3.4. EEG power differences between morning and evening during EC and EO in FEP group and HC group

With eyes closed, there was no significant difference between morning and evening in both groups. However, with eyes open, intra-group analysis showed decreased EEG power in theta band in AM compared to PM, in left frontal, central and left parietal regions in FEP (Supp. Fig 2A). Increased EEG power in high alpha band was detected in HC in AM compared to PM, which was localized in the frontal region (Supp. Fig 2B).

3.5. Associations between waking EEG power and clinical features in FEP patients

Correlation analyses revealed that reduced power in AM/EC cluster in low alpha band was associated with worse positive symptoms assessed with the SAPS (r = −0.438, p = 0.025, Fig. 2), but not with negative symptoms, determined with the SANS. Furthermore, the correlation between reduced alpha power and SAPS was even more significant when we selected the subset of patients diagnosed with SZ (N=20), after removing the six patients diagnosed with SZ and mood disorders (r=−0.5996; p = 0.0052). We also found no significant correlation between EEG power spectral reductions in PM/EC cluster in theta band or PM/EO cluster in high alpha band and either SAPS or SANS scores (Supp. Table 1). In addition, EEG power spectral reductions were not related to anti-psychotic medication doses (Supp. Table 2). Finally, EEG power spectral reductions were not related to altered sleep architecture parameters (Supp. Table 3).

Fig. 2.

Fig. 2.

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Average spectral power of morning eyes-closed cluster in low alpha band was associated with higher SAPS scores (worse positive symptoms) in FEP group.

4. Discussion

This is the first study to investigate resting-state wakefulness in different conditions (EC, EO) and at different time of the day (AM, PM) within-subjects employing hd-EEG recordings in first episode psychosis (FEP) patients. Compared to HC, in the morning, FEP patients showed a widespread reduction in the low alpha frequency range during EC rs-EEG. In the evening, the FEP group demonstrated a trend of decreased theta activity in parietal regions during EC rs-EEG, and significant decreased high alpha activity in frontal and left parietal regions during EO rs-EEG. Furthermore, in FEP reduced AM/EC low alpha rs-EEG power was associated with positive symptom severity.

Several studies have investigated rs-EEG during EC in SCZ. A recent review, which included thirty-four EEG studies, reported an increase in delta and theta band EEG power along with a decrease in the alpha power of patients with (mostly chronic) SCZ compared to HC. Alpha band was the most frequently reported in resting-state studies. Significant decreases in absolute power were dominant in the alpha band for psychotic disorders including schizophrenia and OCD (eyes closed), autism and PTSD (eyes open). In contrast, significant increases were dominant in a handful of studies, most frequently when participants had their eyes open, including depression (beta, eyes open and closed), bipolar (alpha and beta, eyes open), and schizophrenia (alpha and beta, eyes open) patients, thus suggesting that eyes open is a more variable condition than eyes closed (Newson and Thiagarajan, 2018). In most rs-EEG studies, however, time of recording has been scantily considered. In the present study, we investigated the effect of time of the day on rs-EEG activity. Striking reduction of EEG power density including the spindle-frequency range (10-15 Hz) during sleep has been shown in neuropsychiatric mice model (Ang et al., 2018). Reduced spindle activity has also been reported in schizophrenia patients and correlated with their performance such as working memory task and may contribute to psychotic symptoms (Buchmann et al., 2014; Ferrarelli et al., 2007; Ferrarelli et al., 2010). Thus, AM and PM rs-EEG differences might be related to sleep spindle deficit in schizophrenia patients and should be specified in rs-EEG recordings.

In previous work, we reported that patients with chronic SCZ had reduced alpha EEG power (10-11 Hz) in frontal and occipital areas relative to healthy controls during EC rs-EEG (Goldstein et al., 2015). Here, we found the AM/EC alpha reduction was in 7.5-10 Hz. This difference could be related to the large inter-individual variability in schizophrenia patients (e.g., high heterogeneity, a known feature of this disorder) compared to HC. Another possibility is that FEP have more active symptoms than chronic patients (Anticevic et al., 2014), thus they have different EEG presentations. In the present study, we also established that reduced AM/EC alpha power was inversely related to the severity of positive symptoms. We minimized the medication effect and found the reduction in EEG alpha power included a large fronto-parietal region bilaterally. These findings are consistent with data from recent-onset schizophrenia (NRS) patients, which showed reduced alpha power in the left and right frontal regions, which was also reduced at trend level in parieto-occipital regions bilaterally (John et al., 2009), as well as with another study demonstrating RS cortical alpha network abnormalities in first episode schizophrenia spectrum patients (Phalen et al., 2020). Previous work has also revealed disordered EEG source functional connectivity (EEG-SFC) in the eyes closed resting-state condition in schizophrenia. In the alpha band, SCZ showed lower frontal EEG-SFC compared with healthy controls whereas no differences were found between long duration and short duration diseases (Di Lorenzo et al., 2015).

Positive symptoms like hallucinations, paranoia, and delusional thinking are usually observed in SCZ patients, and are particularly prominent in individuals experiencing their first psychotic episode (Ihara et al., 2009). Trouble concentrating is commonly reported in patients with schizophrenia. It has been postulated that less efficient modulation of alpha oscillations is critical for attention deployment and item encoding in schizophrenia (Kustermann et al., 2016). This finding therefore suggests that the EEG alpha band reduction may be implicated in the neurobiology of SCZ and could represent a state biomarker that reflects the severity of psychosis, presumedly impaired attention/concentration. The disconnection hypothesis states that the encoding of uncertainty or precision is important for SCZ, and that the mechanisms underlying psychotic symptoms show a compensatory increase in the precision of prior beliefs (i.e., delusions) relative to the precision of sensory evidence (i.e., hallucinations). Furthermore, there is an association between top-down effects on perceptual inference and symptom severity, suggesting that early psychosis favors prior knowledge over incoming sensory evidence (Friston et al., 2016). Therefore, we assume that the more severe symptoms FEPs experience, the more impaired their false inference is, which could be reflected by a larger AM/EC EEG alpha power reduction.

Our findings point to thalamo-cortical (TC) dysfunction and dysconnectivity. The emergence of high-threshold (HT) bursting and the interconnection of a specialized subset of thalamocortical neurons via gap junctions, generates locally synchronized alpha activity (Hughes and Crunelli, 2005). Notably, the thalamus plays a critical role in generating cortically recorded alpha oscillations, and in previous work we reported marked deficits in sleep spindles, 12-16 Hz NREM sleep oscillations initiated in the thalamus and then relayed and synchronized in the cortex, in patients with SCZ (Buchmann et al., 2014; Ferrarelli et al., 2010). Abnormalities in thalamocortical connectivity has also been reported by several neuroimaging studies, including chronic and early course SCZ (Woodward and Heckers, 2015), as well as by previous work form our group showing reduced TMS-evoked fMRI thalamic response in patients with SCZ relative to HC (Guller et al., 2012). Furthermore, alpha oscillations are generated and modulated by both thalamo-cortical and cortico-thalamic loops, including the pulvinar and the lateral geniculate thalamic nuclei, and recent evidence from intracranial recordings in epileptic patients indicates that alpha rhythm reflects short-range supra-granular feedback, which propagates from higher- to lower-order cortex and cortex to thalamus, thus suggesting how alpha activity could modulate information processing throughout the thalamocortical system (Halgren et al., 2019).

We also found a decrease in the theta band of FEP patients during the evening assessments. An intriguing explanation for this finding is that an increase in theta activity during the daytime is present in HC, but not in FEP patients. In healthy individuals, an increase in wake theta activity (5-9 Hz) occurs throughout the day, followed by more intense sleep because of prolonged wakefulness (Hung et al., 2013). In SCZ patients, on the other hand, this theta activity increase may be altered, leading to theta band power reduction during PM/EC when compared with HC.

Only a handful of studies have investigated RS activity during EO in SCZ. Two elegant EEG studies reported a broadband power increase, from delta to the alpha-beta range, in chronic patients with SCZ relative to HC (Narayanan et al., 2014; Venables et al., 2009). An increase respectively in the delta and in the alpha bands was also reported in first-degree relatives of SCZ probands, based on which it was suggested that those EEG abnormalities may represent endophenotypes for SCZ. Here we found a reduction in those frequency ranges in FEP patients compared to HC. Possible explanations for the discrepancy of those findings are the stage of illness (early vs late) and the effects of long-term medication exposure. Specifically, it could be that a reduction in alpha EEG activity is present at the beginning of illness, which is then followed by a compensatory increase, partly related to antipsychotic medications. In this regard, it was shown that abnormalities in the rs-EEG of early course psychosis patients were elevated in unmedicated patients, and that those alterations decreased in patients who were administered antipsychotic medications (Murphy et al., 2020).

In FEP patients, the EO alpha range reduction was localized in fronto-parietal regions. It has been well established that alpha and beta oscillations, generated by frontoparietal executive control networks, reflect engagement of executive skills including attentional control and the regulation of working memory (Gold et al., 2018). Reduced alpha power during RS EO could therefore reflect a decreased potential to engage attentional resources, whenever needed. A decrease in rs-EEG alpha activity has also been established in autism spectrum disorder (ASD), and for both ASD and healthy children, increased resting alpha levels were associated with greater alpha desynchronization during an attentional task (Keehn et al., 2017). Furthermore, by conducting active attention training technique, researchers were able to enhance alpha activity in healthy individuals (Knowles and Wells, 2018). Given that decreased attention and decline in occupational performance are both core features of SCZ, EEG alpha reduction during EO may represent an important target of treatment in patients with SCZ (Kurachi et al., 2018).

The limitations of this study include the lack of correction for multiple comparisons and the sample size. Future work in larger group of psychotic patients at illness onset is needed to confirm and extend the present findings. Also, while other research groups have investigated low and high alpha frequency bands in humans, the specific alpha ranges selected varied across these EEG studies (Guevara et al., 1995; Tinguely et al., 2006). It would therefore be important to replicate the findings reported here in future work selecting the same frequency bands. Furthermore, longitudinal rs-EEG assessments in FEP psychotic patients will help to better understand the progression of disease, which include establishing whether some of the reported deficits may reflect trait- or state-related biological markers of SCZ and related psychotic disorders. For example, if rs-EEG alterations tend to normalize when positive psychotic symptoms subside, they could represent a (state) biomarker of acute psychosis. It would also be important to investigate whether some of these rs-EEG abnormalities could be used as prognostic and/or predictive indicators of treatment response. Here we found that reduced rs-EEG alpha power correlated with the severity of positive symptoms. Future studies should establish whether higher alpha levels can predict a better treatment response and/or a more favorable prognosis in patients with SCZ, while taking time of the day into consideration. It will also be important to examine whether other clinical symptoms, including those assessing depression severity, are associated with RS alpha or theta band power reduction. In this study we found time of day specific differences between FEP and HC groups for both rs-EEG EC and EC conditions. These findings suggest that time of day contributes to the variability of rs EEG findings in these patients and may contribute to some of the inconsistencies observed in previous studies. Thus, while repeating assessments in the AM and PM would be desirable, future work should at least report time of day of their recordings, which should be considered in interpreting rs-EEG findings.

In sum, by performing hd-EEG recordings during EC and EO, as well as during morning and evening, we established RS alterations in FEP patients, which were distinct both in topography and frequency relative to HC. These findings highlight the importance of accounting for condition and time of the day when assessing RS group differences between healthy and psychiatric populations. They also indicate that rs-EEG alterations are present in psychotic patients at illness onset, and that may serve as monitoring biomarkers of illness severity in patients with SCZ and related psychotic disorders.

Supplementary Material

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Supp. Fig. 1. Resting state EEG standard deviation across all channel topographic maps.

A: measured with eyes closed (EC) in the morning (AM). Topographic low alpha band (7.5-10 Hz) EEG power in FEP patients (Left) and HC (Right).

B: measured with eyes closed (EC) in the evening (PM). Topographic theta band (5-7 Hz) EEG power in FEP patients (Left) and HC (Right).

C: measured with eyes open (EO) in the evening (PM). Topographic high alpha band (10.5-15 Hz) EEG power of significant electrodes in FEP patients (Left) and HC (Right).

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Supp. Fig. 2. Topographic T statistic maps of intra-group analysis between morning and evening.

A: measured with eyes open (EO). In FEP group, the power increase in theta band was localized in left frontal, central and left parietal regions (N=15 channels, red area).

B: measured with eyes open (EO). In HC group, the power decrease in high alpha band was localized in frontal region (N=2 channels, blue area).

Acknowledgements

The authors would like to thank all patients who agreed to participate in our study. We also would like to thank Debra Montrose, Diana Mermon Diana, Elizabeth Radomsky, Kevin Eklund, Alicia Thomas and others at Western Psychiatric Institute and Clinic for recruitment and assessment of participants to our study.

Role of the funding source

This work was supported by The Pittsburgh Foundation Emmerling Rising Star Award in Psychiatric Research (Reference No. FPG00031) and the BRAINS: R01MH113827.

Footnotes

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Conflicts of Interest

All authors declare that they have no conflict of interest.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

1
NIHMS1658978-supplement-1.docx (20.2KB, docx)
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NIHMS1658978-supplement-2.docx (19.4KB, docx)
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NIHMS1658978-supplement-3.docx (20.9KB, docx)
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NIHMS1658978-supplement-4.docx (13.5KB, docx)
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Supp. Fig. 1. Resting state EEG standard deviation across all channel topographic maps.

A: measured with eyes closed (EC) in the morning (AM). Topographic low alpha band (7.5-10 Hz) EEG power in FEP patients (Left) and HC (Right).

B: measured with eyes closed (EC) in the evening (PM). Topographic theta band (5-7 Hz) EEG power in FEP patients (Left) and HC (Right).

C: measured with eyes open (EO) in the evening (PM). Topographic high alpha band (10.5-15 Hz) EEG power of significant electrodes in FEP patients (Left) and HC (Right).

NIHMS1658978-supplement-5.png (907.8KB, png)
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Supp. Fig. 2. Topographic T statistic maps of intra-group analysis between morning and evening.

A: measured with eyes open (EO). In FEP group, the power increase in theta band was localized in left frontal, central and left parietal regions (N=15 channels, red area).

B: measured with eyes open (EO). In HC group, the power decrease in high alpha band was localized in frontal region (N=2 channels, blue area).

NIHMS1658978-supplement-6.png (217.7KB, png)

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