Neurobiology of Schizophrenia: Search for the Elusive Correlation with Symptoms

In the last half-century, human neuroscience methods provided a way to study schizophrenia in vivo, and established that it is associated with subtle abnormalities in brain structure and function. However, efforts to understand the neurobiological bases of the clinical symptoms that the diagnosis is based on have been largely unsuccessful. In this paper, we provide an overview of the conceptual and methodological obstacles that undermine efforts to link the severity of specific symptoms to specific neurobiological measures. These obstacles include small samples, questionable reliability and validity of measurements, medication confounds, failure to distinguish state and trait effects, correlation–causation ambiguity, and the absence of compelling animal models of specific symptoms to test mechanistic hypotheses derived from brain-symptom correlations. We conclude with recommendations to promote progress in establishing brain-symptom relationships

Test-retest reliability of time-frequency measures of auditory steady-state responses in patients with schizophrenia and healthy controls.

BackgroundAuditory steady-state response (ASSR) paradigms have consistently demonstrated gamma band abnormalities in schizophrenia at a 40-Hz driving frequency with both electroencephalography (EEG) and magnetoencephalography (MEG). Various time-frequency measures have been used to assess the 40-Hz ASSR, including evoked power, single trial total power, phase-locking factor (PLF), and phase-locking angle (PLA). While both EEG and MEG studies have shown power and PLF ASSR measures to exhibit excellent test-retest reliability in healthy adults, the reliability of these measures in patients with schizophrenia has not been determined.MethodsASSRs were obtained by recording EEG data during presentation of repeated 20-Hz, 30-Hz and 40-Hz auditory click trains from nine schizophrenia patients (SZ) and nine healthy controls (HC) tested on two occasions. Similar ASSR data were collected from a separate group of 30 HC on two to three test occasions. A subset of these HC subjects had EEG recordings during two tasks, passively listening and actively attending to click train stimuli. Evoked power, total power, PLF, and PLA were calculated following Morlet wavelet time-frequency decomposition of EEG data and test-retest generalizability (G) coefficients were calculated for each ASSR condition, time-frequency measure, and subject group.ResultsG-coefficients ranged from good to excellent (> 0.6) for most 40-Hz time-frequency measures and participant groups, whereas 20-Hz G-coefficients were much more variable. Importantly, test-retest reliability was excellent for the various 40-Hz ASSR measures in SZ, similar to reliabilities in HC. Active attention to click train stimuli modestly reduced G-coefficients in HC relative to the passive listening condition.DiscussionThe excellent test-retest reliability of 40-Hz ASSR measures replicates previous EEG and MEG studies. PLA, a relatively new time-frequency measure, was shown for the first time to have excellent reliability, comparable to power and PLF measures. Excellent reliability of 40 Hz ASSR measures in SZ supports their use in clinical trials and longitudinal observational studies

Aberrant activity in conceptual networks underlies N400 deficits and unusual thoughts in schizophrenia.

BackgroundThe N400 event-related potential (ERP) is triggered by meaningful stimuli that are incongruous, or unmatched, with their semantic context. Functional magnetic resonance imaging (fMRI) studies have identified brain regions activated by semantic incongruity, but their precise links to the N400 ERP are unclear. In schizophrenia (SZ), N400 amplitude reduction is thought to reflect overly broad associations in semantic networks, but the abnormalities in brain networks underlying deficient N400 remain unknown. We utilized joint independent component analysis (JICA) to link temporal patterns in ERPs to neuroanatomical patterns from fMRI and investigate relationships between N400 amplitude and neuroanatomical activation in SZ patients and healthy controls (HC).MethodsSZ patients (n = 24) and HC participants (n = 25) performed a picture-word matching task, in which words were either matched (APPLE→apple) by preceding pictures, or were unmatched by semantically related (in-category; IC, APPLE→lemon) or unrelated (out of category; OC, APPLE→cow) pictures, in separate ERP and fMRI sessions. A JICA "data fusion" analysis was conducted to identify the fMRI brain regions specifically associated with the ERP N400 component. SZ and HC loading weights were compared and correlations with clinical symptoms were assessed.ResultsJICA identified an ERP-fMRI "fused" component that captured the N400, with loading weights that were reduced in SZ. The JICA map for the IC condition showed peaks of activation in the cingulate, precuneus, bilateral temporal poles and cerebellum, whereas the JICA map from the OC condition was linked primarily to visual cortical activation and the left temporal pole. Among SZ patients, fMRI activity from the IC condition was inversely correlated with unusual thought content.ConclusionsThe neural networks associated with the N400 ERP response to semantic violations depends on conceptual relatedness. These findings are consistent with a distributed network underlying neural responses to semantic incongruity including unimodal visual areas as well as integrative, transmodal areas. Unusual thoughts in SZ may reflect impaired processing in transmodal hub regions such as the precuneus, leading to overly broad semantic associations

Identifying functional network changing patterns in individuals at clinical high-risk for psychosis and patients with early illness schizophrenia: A group ICA study.

Although individuals at clinical high risk (CHR) for psychosis exhibit a psychosis-risk syndrome involving attenuated forms of the positive symptoms typical of schizophrenia (SZ), it remains unclear whether their resting-state brain intrinsic functional networks (INs) show attenuated or qualitatively distinct patterns of functional dysconnectivity relative to SZ patients. Based on resting-state functional magnetic imaging data from 70 healthy controls (HCs), 53 CHR individuals (among which 41 subjects were antipsychotic medication-naive), and 58 early illness SZ (ESZ) patients (among which 53 patients took antipsychotic medication) within five years of illness onset, we estimated subject-specific INs using a novel group information guided independent component analysis (GIG-ICA) and investigated group differences in INs. We found that when compared to HCs, both CHR and ESZ groups showed significant differences, primarily in default mode, salience, auditory-related, visuospatial, sensory-motor, and parietal INs. Our findings suggest that widespread INs were diversely impacted. More than 25% of voxels in the identified significant discriminative regions (obtained using all 19 possible changing patterns excepting the no-difference pattern) from six of the 15 interrogated INs exhibited monotonically decreasing Z-scores (in INs) from the HC to CHR to ESZ, and the related regions included the left lingual gyrus of two vision-related networks, the right postcentral cortex of the visuospatial network, the left thalamus region of the salience network, the left calcarine region of the fronto-occipital network and fronto-parieto-occipital network. Compared to HCs and CHR individuals, ESZ patients showed both increasing and decreasing connectivity, mainly hypo-connectivity involving 15% of the altered voxels from four INs. The left supplementary motor area from the sensory-motor network and the right inferior occipital gyrus in the vision-related network showed a common abnormality in CHR and ESZ groups. Some brain regions also showed a CHR-unique alteration (primarily the CHR-increasing connectivity). In summary, CHR individuals generally showed intermediate connectivity between HCs and ESZ patients across multiple INs, suggesting that some dysconnectivity patterns evident in ESZ predate psychosis in attenuated form during the psychosis risk stage. Hence, these connectivity measures may serve as possible biomarkers to predict schizophrenia progression

Role of N-methyl-D-aspartate receptors in action-based predictive coding deficits in schizophrenia

Published in final edited form as:Biol Psychiatry. 2017 March 15; 81(6): 514–524. doi:10.1016/j.biopsych.2016.06.019.BACKGROUND: Recent theoretical models of schizophrenia posit that dysfunction of the neural mechanisms subserving predictive coding contributes to symptoms and cognitive deficits, and this dysfunction is further posited to result from N-methyl-D-aspartate glutamate receptor (NMDAR) hypofunction. Previously, by examining auditory cortical responses to self-generated speech sounds, we demonstrated that predictive coding during vocalization is disrupted in schizophrenia. To test the hypothesized contribution of NMDAR hypofunction to this disruption, we examined the effects of the NMDAR antagonist, ketamine, on predictive coding during vocalization in healthy volunteers and compared them with the effects of schizophrenia. METHODS: In two separate studies, the N1 component of the event-related potential elicited by speech sounds during vocalization (talk) and passive playback (listen) were compared to assess the degree of N1 suppression during vocalization, a putative measure of auditory predictive coding. In the crossover study, 31 healthy volunteers completed two randomly ordered test days, a saline day and a ketamine day. Event-related potentials during the talk/listen task were obtained before infusion and during infusion on both days, and N1 amplitudes were compared across days. In the case-control study, N1 amplitudes from 34 schizophrenia patients and 33 healthy control volunteers were compared. RESULTS: N1 suppression to self-produced vocalizations was significantly and similarly diminished by ketamine (Cohen’s d = 1.14) and schizophrenia (Cohen’s d = .85). CONCLUSIONS: Disruption of NMDARs causes dysfunction in predictive coding during vocalization in a manner similar to the dysfunction observed in schizophrenia patients, consistent with the theorized contribution of NMDAR hypofunction to predictive coding deficits in schizophrenia.This work was supported by AstraZeneca for an investigator-initiated study (DHM) and the National Institute of Mental Health Grant Nos. R01 MH-58262 (to JMF) and T32 MH089920 (to NSK). JHK was supported by the Yale Center for Clinical Investigation Grant No. UL1RR024139 and the US National Institute on Alcohol Abuse and Alcoholism Grant No. P50AA012879. (AstraZeneca for an investigator-initiated study (DHM); R01 MH-58262 - National Institute of Mental Health; T32 MH089920 - National Institute of Mental Health; UL1RR024139 - Yale Center for Clinical Investigation; P50AA012879 - US National Institute on Alcohol Abuse and Alcoholism)Accepted manuscrip

Neurophysiological Distinction between Schizophrenia and Schizoaffective Disorder

Schizoaffective disorder (SA) is distinguished from schizophrenia (SZ) based on the presence of prominent mood symptoms over the illness course. Despite this clinical distinction, SA and SZ patients are often combined in research studies, in part because data supporting a distinct pathophysiological boundary between the disorders are lacking. Indeed, few studies have addressed whether neurobiological abnormalities associated with SZ, such as the widely replicated reduction and delay of the P300 event-related potential (ERP), are also present in SA. Scalp EEG was acquired from patients with DSM-IV SA (n = 15) or SZ (n = 22), as well as healthy controls (HC; n = 22) to assess the P300 elicited by infrequent target (15%) and task-irrelevant distractor (15%) stimuli in separate auditory and visual ”oddball” tasks. P300 amplitude was reduced and delayed in SZ, relative to HC, consistent with prior studies. These SZ abnormalities did not interact with stimulus type (target vs. task-irrelevant distractor) or modality (auditory vs. visual). Across sensory modality and stimulus type, SA patients exhibited normal P300 amplitudes (significantly larger than SZ patients and indistinguishable from HC). However, P300 latency and reaction time were both equivalently delayed in SZ and SA patients, relative to HC. P300 differences between SA and SZ patients could not be accounted for by variation in symptom severity, socio-economic status, education, or illness duration. Although both groups show similar deficits in processing speed, SA patients do not exhibit the P300 amplitude deficits evident in SZ, consistent with an underlying pathophysiological boundary between these disorders

Reward processing electrophysiology in schizophrenia : effects of age and illness phase

Background: Reward processing abnormalities may underlie characteristic pleasure and motivational impairments in schizophrenia. Some neural measures of reward processing show age-related modulation, highlighting the importance of considering age effects on reward sensitivity. We compared event-related potentials (ERPs) reflecting reward anticipation (stimulus-preceding negativity, SPN) and evaluation (reward positivity, RewP; late positive potential, LPP) across individuals with schizophrenia (SZ) and healthy controls (HC), with an emphasis on examining the effects of chronological age, brain age (i.e., predicted age based on neurobiological measures), and illness phase. Methods: Subjects underwent EEG while completing a slot-machine task for which rewards were not dependent on performance accuracy, speed, or response preparation. Slot-machine task EEG responses were compared between 54 SZ and 54 HC individuals, ages 19 to 65. Reward-related ERPs were analyzed with respect to chronological age, categorically-defined illness phase (early; ESZ versus chronic schizophrenia; CSZ), and were used to model brain age relative to chronological age. Results: Illness phase-focused analyses indicated there were no group differences in average SPN or RewP amplitudes. However, a group x reward outcome interaction revealed that ESZ differed from HC in later outcome processing, reflected by greater LPP responses following loss versus reward (a reversal of the HC pattern). While brain age estimates did not differ among groups, depressive symptoms in SZ were associated with older brain age estimates while controlling for negative symptoms. Conclusions: ESZ and CSZ did not differ from HC in reward anticipation or early outcome processing during a cognitively undemanding reward task, highlighting areas of preserved functioning. However, ESZ showed altered later reward outcome evaluation, pointing to selective reward deficits during the early illness phase of schizophrenia. Further, an association between ERP-derived brain age and depressive symptoms in SZ extends prior findings linking depression with reward-related ERP blunting. Taken together, both illness phase and age may impact reward processing among SZ, and brain aging may offer a promising, novel marker of reward dysfunction that warrants further study

Aberrant Hierarchical Prediction Errors Are Associated With Transition to Psychosis: A Computational Single-Trial Analysis of the Mismatch Negativity

Background: Mismatch negativity reductions are among the most reliable biomarkers for schizophrenia and have been associated with increased risk for conversion to psychosis in individuals who are at clinical high risk for psychosis (CHR-P). Here, we adopted a computational approach to develop a mechanistic model of mismatch negativity reductions in CHR-P individuals and patients early in the course of schizophrenia. // Methods: Electroencephalography was recorded in 38 CHR-P individuals (15 converters), 19 patients early in the course of schizophrenia (≤5 years), and 44 healthy control participants during three different auditory oddball mismatch negativity paradigms including 10% duration, frequency, or double deviants, respectively. We modeled sensory learning with the hierarchical Gaussian filter and extracted precision-weighted prediction error trajectories from the model to assess how the expression of hierarchical prediction errors modulated electroencephalography amplitudes over sensor space and time. // Results: Both low-level sensory and high-level volatility precision-weighted prediction errors were altered in CHR-P individuals and patients early in the course of schizophrenia compared with healthy control participants. Moreover, low-level precision-weighted prediction errors were significantly different in CHR-P individuals who later converted to psychosis compared with nonconverters. // Conclusions: Our results implicate altered processing of hierarchical prediction errors as a computational mechanism in early psychosis consistent with predictive coding accounts of psychosis. This computational model seems to capture pathophysiological mechanisms that are relevant to early psychosis and the risk for future psychosis in CHR-P individuals and may serve as predictive biomarkers and mechanistic targets for the development of novel treatments

A Multi-site Resting State fMRI Study on the Amplitude of Low Frequency Fluctuations in Schizophrenia

Background: This multi-site study compares resting state fMRI amplitude of low frequency fluctuations (ALFF) and fractional ALFF (fALFF) between patients with schizophrenia (SZ) and healthy controls (HC). Methods: Eyes-closed resting fMRI scans (5:38 min; n = 306, 146 SZ) were collected from 6 Siemens 3T scanners and one GE 3T scanner. Imaging data were pre-processed using an SPM pipeline. Power in the low frequency band (0.01–0.08 Hz) was calculated both for the original pre-processed data as well as for the pre-processed data after regressing out the six rigid-body motion parameters, mean white matter (WM) and cerebral spinal fluid (CSF) signals. Both original and regressed ALFF and fALFF measures were modeled with site, diagnosis, age, and diagnosis × age interactions. Results: Regressing out motion and non-gray matter signals significantly decreased fALFF throughout the brain as well as ALFF in the cortical edge, but significantly increased ALFF in subcortical regions. Regression had little effect on site, age, and diagnosis effects on ALFF, other than to reduce diagnosis effects in subcortical regions. There were significant effects of site across the brain in all the analyses, largely due to vendor differences. HC showed greater ALFF in the occipital, posterior parietal, and superior temporal lobe, while SZ showed smaller clusters of greater ALFF in the frontal and temporal/insular regions as well as in the caudate, putamen, and hippocampus. HC showed greater fALFF compared with SZ in all regions, though subcortical differences were only significant for original fALFF. Conclusions: SZ show greater eyes-closed resting state low frequency power in frontal cortex, and less power in posterior lobes than do HC; fALFF, however, is lower in SZ than HC throughout the cortex. These effects are robust to multi-site variability. Regressing out physiological noise signals significantly affects both total and fALFF measures, but does not affect the pattern of case/control differences