Fronto-parietal network function during cued visual search in the first-episode schizophrenia spectrum

A new transfer entropy method for measuring directed connectivity from complex-valued fMRI data

Background

Inferring directional connectivity of brain regions from functional magnetic resonance imaging (fMRI) data has been shown to provide additional insights into predicting mental disorders such as schizophrenia. However, existing research has focused on the magnitude data from complex-valued fMRI data without considering the informative phase data, thus ignoring potentially important information.

Methods

We propose a new complex-valued transfer entropy (CTE) method to measure causal links among brain regions in complex-valued fMRI data. We use the transfer entropy to model a general non-linear magnitude-magnitude and phase-phase directed connectivity and utilize partial transfer entropy to measure the complementary phase and magnitude effects on magnitude-phase and phase-magnitude causality. We also define the significance of the causality based on a statistical test and the shuffling strategy of the two complex-valued signals.

Results

Simulated results verified higher accuracy of CTE than four causal analysis methods, including a simplified complex-valued approach and three real-valued approaches. Using experimental fMRI data from schizophrenia and controls, CTE yields results consistent with previous findings but with more significant group differences. The proposed method detects new directed connectivity related to the right frontal parietal regions and achieves 10.2-20.9% higher SVM classification accuracy when inferring directed connectivity using anatomical automatic labeling (AAL) regions as features.

Conclusion

The proposed CTE provides a new general method for fully detecting highly predictive directed connectivity from complex-valued fMRI data, with magnitude-only fMRI data as a specific case.

Neuroimaging features of cognitive impairments in schizophrenia and major depressive disorder

Cognitive dysfunctions are one of the key symptoms of schizophrenia (SZ) and major depressive disorder (MDD), which exist not only during the onset of diseases but also before the onset, even after the remission of psychiatric symptoms. With the development of neuroimaging techniques, these non-invasive approaches provide valuable insights into the underlying pathogenesis of psychiatric disorders and information of cognitive remediation interventions. This review synthesizes existing neuroimaging studies to examine domains of cognitive impairment, particularly processing speed, memory, attention, and executive function in SZ and MDD patients. First, white matter (WM) abnormalities are observed in processing speed deficits in both SZ and MDD, with distinct neuroimaging findings highlighting WM connectivity abnormalities in SZ and WM hyperintensity caused by small vessel disease in MDD. Additionally, the abnormal functions of prefrontal cortex and medial temporal lobe are found in both SZ and MDD patients during various memory tasks, while aberrant amygdala activity potentially contributes to a preference to negative memories in MDD. Furthermore, impaired large-scale networks including frontoparietal network, dorsal attention network, and ventral attention network are related to attention deficits, both in SZ and MDD patients. Finally, abnormal activity and volume of the dorsolateral prefrontal cortex (DLPFC) and abnormal functional connections between the DLPFC and the cerebellum are associated with executive dysfunction in both SZ and MDD. Despite these insights, longitudinal neuroimaging studies are lacking, impeding a comprehensive understanding of cognitive changes and the development of early intervention strategies for SZ and MDD. Addressing this gap is critical for advancing our knowledge and improving patient prognosis.

EEG Network Analysis of Depressive Emotion Interference Spatial Cognition Based on a Simulated Robotic Arm Docking Task

Depressive emotion (DE) refers to clinically relevant depressive symptoms without meeting the diagnostic criteria for depression. Studies have demonstrated that DE can cause spatial cognition impairment. However, the brain network mechanisms underlying DE interference spatial cognition remain unclear. This study aimed to reveal the differences in brain network connections between DE and healthy control (HC) groups during resting state and a spatial cognition task. The longer operation time of the DE group during spatial cognition task indicated DE interference spatial cognition. In the resting state stage, the DE group had weaker network connections in theta and alpha bands than the HC group had. Specifically, the electrodes in parietal regions were hubs of the differential networks, which are related to spatial attention. Moreover, in docking task stages, the left frontoparietal network connections in delta, beta, and gamma bands were stronger in the DE group than those of the HC group. The enhanced left frontoparietal connections in the DE group may be related to brain resource reorganization to compensate for spatial cognition decline and ensure the completion of spatial cognition tasks. Thus, these findings might provide new insights into the neural mechanisms of depressive emotion interference spatial cognition.

Evidence of Neurovascular Water Exchange and Endothelial Vascular Dysfunction in Schizophrenia: An Exploratory Study

BACKGROUND AND HYPOTHESIS

Mounting evidence supports cerebrovascular contributions to schizophrenia spectrum disorder (SSD) but with unknown mechanisms. The blood-brain barrier (BBB) is at the nexus of neural-vascular exchanges, tasked with regulating cerebral homeostasis. BBB abnormalities in SSD, if any, are likely more subtle compared to typical neurological insults and imaging measures that assess large molecule BBB leakage in major neurological events may not be sensitive enough to directly examine BBB abnormalities in SSD.

STUDY DESIGN

We tested the hypothesis that neurovascular water exchange (Kw) measured by non-invasive diffusion-prepared arterial spin label MRI (n = 27 healthy controls [HC], n = 32 SSD) is impaired in SSD and associated with clinical symptoms. Peripheral vascular endothelial health was examined by brachial artery flow-mediated dilation (n = 44 HC, n = 37 SSD) to examine whether centrally measured Kw is related to endothelial functions.

STUDY RESULTS

Whole-brain average Kw was significantly reduced in SSD (P = .007). Exploratory analyses demonstrated neurovascular water exchange reductions in the right parietal lobe, including the supramarginal gyrus (P = .002) and postcentral gyrus (P = .008). Reduced right superior corona radiata (P = .001) and right angular gyrus Kw (P = .006) was associated with negative symptoms. Peripheral endothelial function was also significantly reduced in SSD (P = .0001). Kw in 94% of brain regions in HC positively associated with peripheral endothelial function, which was not observed in SSD, where the correlation was inversed in 52% of brain regions.

CONCLUSIONS

This study provides initial evidence of neurovascular water exchange abnormalities, which appeared clinically associated, especially with negative symptoms, in schizophrenia.

Comparison of brain network between schizophrenia and bipolar disorder: A multimodal MRI analysis of comparative studies

OBJECTIVE

Cognitive impairment is a shared symptom of Schizophrenia (SCZ) and bipolar disorder (BP), but the underlying neural mechanisms for both remain unclear. We aimed to identify abnormalities in the structural and functional brain network of patients with SCZ and BP.

METHODS

The study included 69 patients with SCZ, 40 with BP, and 63 healthy controls (HC). After neurocognitive function assessment, resting-state functional magnetic resonance imaging and diffusion tensor imaging were acquired respectively. We compared the network of structural connectivity (SC) and functional connectivity (FC) among the three groups and performed graph theoretical analyses. The SC-FC coupling was calculated, and the correlations between the cognitive function scores and network properties were ascertained.

RESULTS

The BP group showed significantly higher indicators in subnetworks and graph theory analysis than SCZ and HC. Several brain regions, such as the inferior parietal lobe, exhibited differences among all pairwise comparisons and showed significant correlations with cognitive scores in both SCZ and BP. SC-FC coupling did not significantly differ between the three groups but showed close associations with clinical performance. Interestingly, the direction of correlations between the network properties and cognition tends to present the opposite between SCZ and BP, especially regarding the working memory, attention, and language sections.

CONCLUSIONS

The FC and SC network of the SCZ group appeared more inefficient and disconnected than BP. The network demonstrated to be closely but differently associated with cognitive function at both local and global levels, indicating the potentially separated pathologies of cognition deficits in SCZ and BP.

Load-dependent functional connectivity deficits during visual working memory in first-episode psychosis

INTRODUCTION

Aberrant network connectivity is a core deficit in schizophrenia and may underlie many of its associated cognitive deficits. Previous work in first-episode schizophrenia spectrum illness (FESz) suggests preservation of working memory network function during low-load conditions with dysfunction emerging as task complexity increases. This study assessed visual network connectivity and its contribution to load-dependent working memory impairments.

METHODS

Magnetoencephalography was recorded from 35 FESz and 28 matched controls (HC) during a lateralized change detection task. Impaired alpha desynchronization was previously identified within bilateral dorsal occipital (Occ) regions. Here, whole-brain alpha-band connectivity was examined using phase-locking (PLV) and bilateral Occ as connectivity seeds. Load effects on connectivity were assessed across participants, and PLV modulation within networks was compared between groups.

RESULTS

Occ exhibited significant load modulated connectivity with six regions (FDR-corrected). HC exhibited PLV enhancement with load in all connections. FESz failed to show PLV modulation between right Occ and left inferior frontal gyrus, lateral occipito-temporal sulcus, and anterior intermediate parietal sulcus. Smaller PLVs in all three network connections during both memory load conditions were associated with increased reality distortion in FESz (FDR-corrected.) CONCLUSION: Examination of functional connectivity across the visual working memory network in FESz revealed an inability to enhance communication between perceptual and executive networks in response to increasing cognitive demands. Furthermore, the degree of network communication impairment was associated with positive symptoms. These findings provide insights into the nature of brain dysconnectivity and its contribution to symptoms in early psychosis and identify potential targets for future interventions.

Decreased resting-state neural signal in the left angular gyrus as a potential neuroimaging biomarker of schizophrenia: An amplitude of low-frequency fluctuation and support vector machine analysis

Objective

Schizophrenia (SCH) is primarily diagnosed based on specific clinical symptoms, with the lack of any objective SCH-related biomarkers often resulting in patient misdiagnosis and the underdiagnosis of this condition. This study was developed to assess the utility of amplitude of low-frequency fluctuation (ALFF) values analyzed via support vector machine (SVM) methods as a means of diagnosing SCH.

Methods

In total, 131 SCH patients and 128 age- and gender-matched healthy control (HC) individuals underwent resting-state functional magnetic resonance imaging (rs-fMRI), with the resultant data then being analyzed using ALFF values and SVM methods.

Results

Relative to HC individuals, patients with SCH exhibited ALFF reductions in the left angular gyrus (AG), fusiform gyrus, anterior cingulate cortex (ACC), right cerebellum, bilateral middle temporal gyrus (MTG), and precuneus (PCu) regions. No SCH patient brain regions exhibited significant increases in ALFF relative to HC individuals. SVM results indicated that reductions in ALFF values in the bilateral PCu can be used to effectively differentiate between SCH patients and HCs with respective accuracy, sensitivity, and specificity values of 73.36, 91.60, and 54.69%.

Conclusion

These data indicate that SCH patients may exhibit characteristic reductions in regional brain activity, with decreased ALFF values of the bilateral PCu potentially offering value as a candidate biomarker capable of distinguishing between SCH patients and HCs.

Early visual processing and adaptation as markers of disease, not vulnerability: EEG evidence from 22q11.2 deletion syndrome, a population at high risk for schizophrenia

We investigated visual processing and adaptation in 22q11.2 deletion syndrome (22q11.2DS), a condition characterized by an increased risk for schizophrenia. Visual processing differences have been described in schizophrenia but remain understudied early in the disease course. Electrophysiology was recorded during a visual adaptation task with different interstimulus intervals to investigate visual processing and adaptation in 22q11.2DS (with (22q+) and without (22q−) psychotic symptoms), compared to control and idiopathic schizophrenia groups. Analyses focused on early windows of visual processing. While increased amplitudes were observed in 22q11.2DS in an earlier time window (90–140 ms), decreased responses were seen later (165–205 ms) in schizophrenia and 22q+. 22q11.2DS, and particularly 22q−, presented increased adaptation effects. We argue that while amplitude and adaptation in the earlier time window may reflect specific neurogenetic aspects associated with a deletion in chromosome 22, amplitude in the later window may be a marker of the presence of psychosis and/or of its chronicity/severity.