Unsuccessful reduction of high-frequency alpha activity during cognitive activation in schizophrenia

Differentiation between suicide attempt and suicidal ideation in patients with major depressive disorder using cortical functional network

Studies exploring the neurophysiology of suicide are scarce and the neuropathology of related disorders is poorly understood. This study investigated source-level cortical functional networks using resting-state electroencephalography (EEG) in drug-naïve depressed patients with suicide attempt (SA) and suicidal ideation (SI). EEG was recorded in 55 patients with SA and in 54 patients with SI. Particularly, all patients with SA were evaluated using EEG immediately after their SA (within 7 days). Graph-theory-based source-level weighted functional networks were assessed using strength, clustering coefficient (CC), and path length (PL) in seven frequency bands. Finally, we applied machine learning to differentiate between the two groups using source-level network features. At the global level, patients with SA showed lower strength and CC and higher PL in the high alpha band than those with SI. At the nodal level, compared with patients with SI, patients with SA showed lower high alpha band nodal CCs in most brain regions. The best classification performances for SA and SI showed an accuracy of 73.39%, a sensitivity of 76.36%, and a specificity of 70.37% based on high alpha band network features. Our findings suggest that abnormal high alpha band functional network may reflect the pathophysiological characteristics of suicide and serve as a clinical biomarker for suicide.

Analysis of functional connectivity using machine learning and deep learning in different data modalities from individuals with schizophrenia

Objective. Schizophrenia(SCZ) is a severe mental disorder associated with persistent or recurrent psychosis, hallucinations, delusions, and thought disorders that affect approximately 26 million people worldwide, according to the World Health Organization. Several studies encompass machine learning (ML) and deep learning algorithms to automate the diagnosis of this mental disorder. Others study SCZ brain networks to get new insights into the dynamics of information processing in individuals suffering from the condition. In this paper, we offer a rigorous approach with ML and deep learning techniques for evaluating connectivity matrices and measures of complex networks to establish an automated diagnosis and comprehend the topology and dynamics of brain networks in SCZ individuals.Approach.For this purpose, we employed an functional magnetic resonance imaging (fMRI) and electroencephalogram (EEG) dataset. In addition, we combined EEG measures, i.e. Hjorth mobility and complexity, with complex network measurements to be analyzed in our model for the first time in the literature.Main results.When comparing the SCZ group to the control group, we found a high positive correlation between the left superior parietal lobe and the left motor cortex and a positive correlation between the left dorsal posterior cingulate cortex and the left primary motor. Regarding complex network measures, the diameter, which corresponds to the longest shortest path length in a network, may be regarded as a biomarker because it is the most crucial measure in different data modalities. Furthermore, the SCZ brain networks exhibit less segregation and a lower distribution of information. As a result, EEG measures outperformed complex networks in capturing the brain alterations associated with SCZ.Significance. Our model achieved an area under receiver operating characteristic curve (AUC) of 100% and an accuracy of 98.5% for the fMRI, an AUC of 95%, and an accuracy of 95.4% for the EEG data set. These are excellent classification results. Furthermore, we investigated the impact of specific brain connections and network measures on these results, which helped us better describe changes in the diseased brain.

Alpha Event-Related Desynchronization During Reward Processing in Schizophrenia

BACKGROUND

Alterations in the brain's reward system may underlie motivation and pleasure deficits in schizophrenia (SZ). Neuro-oscillatory desynchronization in the alpha band is thought to direct resource allocation away from the internal state, to prioritize processing salient environmental events, including reward feedback. We hypothesized reduced reward-related alpha event-related desynchronization (ERD) in SZ, consistent with less externally focused processing during reward feedback.

METHODS

Electroencephalography was recorded while participants with SZ (n = 54) and healthy control participants (n = 54) played a simple slot machine task. Total alpha band power (8-14 Hz), a measure of neural oscillation magnitude, was extracted via principal component analysis and compared between groups and reward outcomes. The clinical relevance of hypothesized alpha power alterations was examined by testing associations with negative symptoms within the SZ group and with trait rumination, dimensionally, across groups.

RESULTS

A group × reward outcome interaction (p = .018) was explained by healthy control participants showing significant posterior-occipital alpha power suppression to wins versus losses (p < .001), in contrast to participants with SZ (p > .1). Among participants with SZ, this alpha ERD was unrelated to negative symptoms (p > .1). Across all participants, less alpha ERD to reward outcomes covaried with greater trait rumination for both win (p = .005) and loss (p = .002) outcomes, with no group differences in slope.

CONCLUSIONS

These findings demonstrate alpha ERD alterations in SZ during reward outcome processing. Additionally, higher trait rumination was associated with less alpha ERD during reward feedback, suggesting that individual differences in rumination covary with external attention to reward processing, regardless of reward outcome valence or group membership.

Overcoming Rest-Task Divide-Abnormal Temporospatial Dynamics and Its Cognition in Schizophrenia

Schizophrenia is a complex psychiatric disorder exhibiting alterations in spontaneous and task-related cerebral activity whose relation (termed "state dependence") remains unclear. For unraveling their relationship, we review recent electroencephalographic (and a few functional magnetic resonance imaging) studies in schizophrenia that assess and compare both rest/prestimulus and task states, ie, rest/prestimulus-task modulation. Results report reduced neural differentiation of task-related activity from rest/prestimulus activity across different regions, neural measures, cognitive domains, and imaging modalities. Together, the findings show reduced rest/prestimulus-task modulation, which is mediated by abnormal temporospatial dynamics of the spontaneous activity. Abnormal temporospatial dynamics, in turn, may lead to abnormal prediction, ie, predictive coding, which mediates cognitive changes and psychopathological symptoms, including confusion of internally and externally oriented cognition. In conclusion, reduced rest/prestimulus-task modulation in schizophrenia provides novel insight into the neuronal mechanisms that connect task-related changes to cognitive abnormalities and psychopathological symptoms.

Resting EEG in alpha band predicts individual differences in visual size perception

Human visual size perception results from an interaction of external sensory information and internal state. The cognitive mechanisms involved in the processing of context-dependent visual size perception have been found to be innate in nature to some extent, suggesting that visual size perception might correlate with human intrinsic brain activity. Here we recorded human resting alpha activity (8-12 Hz), which is an inverse indicator of sustained alertness. Moreover, we measured an object's perceived size in a two-alternative forced-choice manner and the Ebbinghaus illusion magnitude which is a classic illustration of context-dependent visual size perception. The results showed that alpha activity along the ventral visual pathway, including left V1, right LOC and bilateral inferior temporal gyrus, negatively correlated with an object's perceived size. Moreover, alpha activity in the left superior temporal gyrus positively correlated with size discrimination threshold and size illusion magnitude. The findings provide clear evidence that human visual size perception scales as a function of intrinsic alertness, with higher alertness linking to larger perceived size of objects and better performance in size discrimination and size illusion tasks, and suggest that individual variation in resting-state brain activity provides a neural explanation for individual variation in cognitive performance of normal participants.

Resting frontal EEG asymmetry and schizotypal traits: a test-retest study

Introduction: Increase in right relative to left frontal electroencephalography (EEG) activity has been observed in patients with schizophrenia, both in cognitive tasks and during rest; and this lateralisation may be related to the severity of schizotypal traits. Methods: We used the Schizotypal Personality Questionnaire (SPQ) to assess schizotypal traits, and examined the correlation between these traits and resting EEG frontal asymmetry (left-right) in 52 college students, as well as the reliability of this correlation over a three-month interval. Results: A higher total score on the SPQ was correlated with reduced asymmetry in different frequency bands: gamma and beta2 frequency bands at baseline, and delta and alpha frequency bands three months later. Additionally, the reduced left relative to right frontal gamma and beta2 asymmetry was correlated with the participants' verbal fluency ability. However, this correlation was no longer statistically significant after the total SPQ score was controlled. Conclusions: These findings suggest that resting frontal EEG asymmetry is correlated with powers in different frequency bands, and may be an endophenotype for schizophrenia spectrum disorders.

Differential changes in visual and auditory event-related oscillations in dementia with Lewy bodies

OBJECTIVE

Aside from the cognitive impairment, patients with dementia with Lewy bodies (DLB) have a high frequency of visual hallucinations and a number of other vision-related symptoms, whereas auditory hallucinations are less frequent. To better understand the differential dysfunction of the visual network in DLB, we compared auditory and visual event-related potentials and oscillations in patients with DLB.

METHODS

Event-related potentials elicited by visual and auditory oddball tasks were recorded in 23 patients with DLB and 22 healthy controls and analyzed in time and time-frequency domain.

RESULTS

DLB patients had decreased theta band activity related to both early sensory and later cognitive processing in the visual, but not in the auditory task. Patients had lower delta and higher alpha and beta bands power related to later cognitive processing in both auditory and visual tasks.

CONCLUSIONS

In DLB visual event-related oscillations are characterized by a decrease in theta and lack of inhibition in alpha bands.

SIGNIFICANCE

Decreased theta and a lack of inhibition in alpha band power might be an oscillatory underpinning of some classical DLB symptoms such as fluctuations in attention and high-level visual disturbances and a potential marker of dysfunction of the visual system in DLB.

The Self and Its Prolonged Intrinsic Neural Timescale in Schizophrenia

Schizophrenia (SCZ) can be characterized as a basic self-disorder that is featured by abnormal temporal integration on phenomenological (experience) and psychological (information processing) levels. Temporal integration on the neuronal level can be measured by the brain's intrinsic neural timescale using the autocorrelation window (ACW) and power-law exponent (PLE). Our goal was to relate intrinsic neural timescales (ACW, PLE), as a proxy of temporal integration on the neuronal level, to temporal integration related to self-disorder on psychological (Enfacement illusion task in electroencephalography) and phenomenological (Examination of Anomalous Self-Experience [EASE]) levels. SCZ participants exhibited prolonged ACW and higher PLE during the self-referential task (Enfacement illusion), but not during the non-self-referential task (auditory oddball). The degree of ACW/PLE change during task relative to rest was significantly reduced in self-referential task in SCZ. A moderation model showed that low and high ACW/PLE exerted differential impact on the relationship of self-disorder (EASE) and negative symptoms (PANSS). In sum, we demonstrate abnormal prolongation in intrinsic neural timescale during self-reference in SCZ including its relation to basic self-disorder and negative symptoms. Our results point to abnormal relation of self and temporal integration at the core of SCZ constituting a "common currency" of neuronal, psychological, and phenomenological levels.

Occipital Alpha Connectivity During Resting-State Electroencephalography in Patients With Ultra-High Risk for Psychosis and Schizophrenia

Schizophrenia patients always show cognitive impairment, which is proved to be related to hypo-connectivity or hyper-connectivity. Further, individuals with an ultra-high risk for psychosis also show abnormal functional connectivity-related cognitive impairment, especially in the alpha rhythm. Thus, the identification of functional networks is essential to our understanding of the disorder. We investigated the resting-state functional connectivity of the alpha rhythm measured by electroencephalography (EEG) to reveal the relation between functional network and clinical symptoms. The participants included 28 patients with first-episode schizophrenia (FES), 28 individuals with ultra-high risk for psychosis (UHR), and 28 healthy controls (HC). After the professional clinical symptoms evaluation, all the participants were instructed to keep eyes closed for 3-min resting-state EEG recording. The 3-min EEG data were segmented into artefact-free epochs (the length was 3 s), and the functional connectivity of the alpha phase was estimated using the phase lag index (PLI), which measures the phase differences of EEG signals. The FES and UHR groups displayed increased resting-state PLI connectivity compared with the HC group [F(2,74) = 10.804, p < 0.001]. Significant increases in the global efficiency, the local efficiency, and the path length were found in the FES and UHR groups compared with those of the HC group. FES and UHR showed an increased degree of connectivity compared with HC. The degree of the left occipital lobe area was higher in the UHR group than in the FES group. The hypothesis of disconnection is confirmed. Furthermore, differences between the UHR and FES group were found, which is valuable for producing clinical significance before the onset of schizophrenia.