Brain function during stages of working memory in schizophrenia and psychotic bipolar disorder

Dense attention network identifies EEG abnormalities during working memory performance of patients with schizophrenia

Introduction

Patients with schizophrenia typically exhibit deficits in working memory (WM) associated with abnormalities in brain activity. Alterations in the encoding, maintenance and retrieval phases of sequential WM tasks are well established. However, due to the heterogeneity of symptoms and complexity of its neurophysiological underpinnings, differential diagnosis remains a challenge. We conducted an electroencephalographic (EEG) study during a visual WM task in fifteen schizophrenia patients and fifteen healthy controls. We hypothesized that EEG abnormalities during the task could be identified, and patients successfully classified by an interpretable machine learning algorithm.

Methods

We tested a custom dense attention network (DAN) machine learning model to discriminate patients from control subjects and compared its performance with simpler and more commonly used machine learning models. Additionally, we analyzed behavioral performance, event-related EEG potentials, and time-frequency representations of the evoked responses to further characterize abnormalities in patients during WM.

Results

The DAN model was significantly accurate in discriminating patients from healthy controls, ACC = 0.69, SD = 0.05. There were no significant differences between groups, conditions, or their interaction in behavioral performance or event-related potentials. However, patients showed significantly lower alpha suppression in the task preparation, memory encoding, maintenance, and retrieval phases F(1,28) = 5.93, p = 0.022, η2 = 0.149. Further analysis revealed that the two highest peaks in the attention value vector of the DAN model overlapped in time with the preparation and memory retrieval phases, as well as with two of the four significant time-frequency ROIs.

Discussion

These results highlight the potential utility of interpretable machine learning algorithms as an aid in diagnosis of schizophrenia and other psychiatric disorders presenting oscillatory abnormalities.

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.

Working memory heterogeneity from age 7 to 11 in children at familial high risk of schizophrenia or bipolar disorder- The Danish High Risk and Resilience Study

BACKGROUND

Despite the genetic overlap between bipolar disorder and schizophrenia, working memory impairments are mainly found in children of parents with schizophrenia. However, working memory impairments are characterized by substantial heterogeneity, and it is unknown how this heterogeneity develops over time. We used a data-driven approach to assess working memory heterogeneity and longitudinal stability in children at familial high risk of schizophrenia (FHR-SZ) or bipolar disorder (FHR-BP).

METHODS

Based on the performances on four working memory tasks by 319 children (FHR-SZ, N = 202, FHR-BP, N = 118) measured at age 7 and 11, latent profile transition analysis was used to test for the presence of subgroups, and the stability of subgroup membership over time. Population-based controls (VIA 7, N = 200, VIA 11, N = 173) were included as a reference group. The working memory subgroups were compared based on caregiver- and teacher ratings of everyday working memory function, and dimensional psychopathology.

RESULTS

A model with three subgroups characterized by different levels of working memory function (an impaired subgroup, a mixed subgroup, and an above average subgroup) best fitted the data. The impaired subgroup had the highest ratings of everyday working memory impairments and psychopathology. Overall, 98 % (N = 314) stayed in the same subgroup from age 7 to 11.

CONCLUSION

Persistent working memory impairments are present in a subset of children at FHR-SZ and FHR-BP throughout middle childhood. Attention should be given to these children, as working memory impairments influence daily life, and may serve as a vulnerability marker of transition to severe mental illness.

Identifying the difference in time perception between major depressive disorder and bipolar depression through a temporal bisection task

BACKGROUND

It is difficult to make a precise diagnosis to distinguish patients with Major Depressive Disorder (MDD) from patients with Bipolar Depressive Disorder (current depressive episode, BD). This study will explore the difference in time perception between MDD and BD using a temporal bisection task.

METHODS

In this temporal bisection task, 30 MDD patients, 30 BD patients, and 30 healthy controls (HC) had to categorize a signal duration, between 400 and 1600 milliseconds (ms), as either short or long. A repeated measurement analysis of variance with 3 (subject type) × 7 (time interval) was performed on the long response ratio with Bonferroni correction for multiple comparisons. Origin software was used to calculate the subjective bisection point (BP), difference limen (DL), and Weber ratio (WR). The Hamilton Depression Rating Scale for depression-17 was used to assess depressive symptoms in the patients.

RESULTS

The data showed that the interaction effect between subject type and duration was significant (F (6,498) = 4.656, p <0.001, η2p = 0.101). At 400 ms, and the long response of the MDD group was greater than HC group (p<0.017, Bonferroni-corrected). At 1200, 1400 and 1600 ms, the long response of BD group is smaller than HC group, (p<0.017, Bonferroni-corrected). The one-way ANOVA revealed significant difference among the HC, MDD and BD groups in the BP values WR values, F(2, 81) = 3.462, p = 0.036 vs. F(2, 81) = 3.311, p = 0.042. Post-hoc tests showed that the value of BP in the MDD group was less than BD group (p = 0.027) and the value of BP in the MDD group was less than HC group (p = 0.027), while there was not significant difference of BP values between BD group and HC group. The WR values in MDD group larger than the HC group (p = 0.022).

LIMITATIONS

Severity of depression not divided and analyzed according to the Hamilton Depression Rating Scale score.

CONCLUSION

The time perception of the MDD and BD groups was different from that of the HC group, they overestimated short time periods. Compared with the BD group, the MDD group had a smaller time bisector, and these patients felt that time passed more slowly. The time sensitivity of MDD group and BD group were less than the HC group. However, there was no statistical difference in time sensitivity between the MDD and BD groups.

Effect of schizophrenia risk gene polymorphisms on cognitive and neural plasticity

A recent Chinese genome-wide association study found evidence for 58 out of the 128 schizophrenia-associated variants previously discovered in Western samples by the Schizophrenia Working Group of the Psychiatric Genomics Consortium (PGC). However, the functional impact of these trans-ancestry genome-wide single-nucleotide polymorphisms (SNPs) is not clear. In the current study, we examined the roles of trans-ancestry SNPs in cognitive and neural plasticity. We first performed a behavioral study of 547 healthy volunteers, who received month-long working memory training, and working memory capability assessment both before and after the training. A separate sample of 101 subjects received the same training and received fMRI scans during a working memory task, both before and after the training. The behavioral study found a significant association between the polygenic risk score (PRS) and behavioral plasticity, with higher schizophrenia risk scores being linked to less plasticity. At the SNP level, rs36068923 showed a significant signal, with the risk allele being associated with less plasticity. The fMRI study further found that the PRS and rs36068923 polymorphism were associated with training-induced changes in striatal activation, with higher PRS and the risk allele of rs36068923 being linked to less brain plasticity. In sum, this study found that a high genetic risk for schizophrenia was associated with less plasticity at both behavioral and neural levels. These results provide new insights into the neural and cognitive mechanisms linking genes to schizophrenia.

Altered frequency-specific/universal amplitude characteristics of spontaneous brain oscillations in patients with bipolar disorder

The human brain is a dynamic system with intrinsic oscillations in spontaneous neural activity. Whether the dynamic characteristics of these spontaneous oscillations are differentially altered across different frequency bands in patients with bipolar disorder (BD) remains unclear. This study recruited 65 patients with BD and 85 healthy controls (HCs). The entire frequency range of resting-state fMRI data was decomposed into four frequency intervals. Two-way repeated-measures ANCOVA was employed to detect frequency-specific/universal alterations in the dynamic oscillation amplitude in BD. The patients were then divided into two subgroups according to their mood states to explore whether these alterations were independent of their mood states. Finally, other window sizes, step sizes, and window types were tested to replicate all analyses. Frequency-specific abnormality of the dynamic oscillation amplitude was detected within the posterior medial parietal cortex (centered at the precuneus extending to the posterior cingulate cortex). This specific profile indicates decreased amplitudes in the lower frequency bands (slow-5/4) and no amplitude changes in the higher frequency bands (slow-3/2) compared with HCs. Frequency-universal abnormalities of the dynamic oscillation amplitude were also detectable, indicating increased amplitudes in the thalamus and left cerebellum anterior lobe but decreased amplitudes in the medial superior frontal gyrus. These alterations were independent of the patients' mood states and replicable across multiple analytic and parametric settings. In short, frequency-specific/universal amplitude characteristics of spontaneous oscillations were observed in patients with BD. These abnormal characteristics have important implications for specific functional changes in BD from multiple frequency and dynamic perspectives.

Combining fMRI and DISC1 gene haplotypes to understand working memory-related brain activity in schizophrenia

The DISC1 gene is one of the most relevant susceptibility genes for psychosis. However, the complex genetic landscape of this locus, which includes protective and risk variants in interaction, may have hindered consistent conclusions on how DISC1 contributes to schizophrenia (SZ) liability. Analysis from haplotype approaches and brain-based phenotypes can contribute to understanding DISC1 role in the neurobiology of this disorder. We assessed the brain correlates of DISC1 haplotypes associated with SZ through a functional neuroimaging genetics approach. First, we tested the association of two DISC1 haplotypes, the HEP1 (rs6675281-1000731-rs999710) and the HEP3 (rs151229-rs3738401), with the risk for SZ in a sample of 138 healthy subjects (HS) and 238 patients. This approach allowed the identification of three haplotypes associated with SZ (HEP1-CTG, HEP3-GA and HEP3-AA). Second, we explored whether these haplotypes exerted differential effects on n-back associated brain activity in a subsample of 70 HS compared to 70 patients (diagnosis × haplotype interaction effect). These analyses evidenced that HEP3-GA and HEP3-AA modulated working memory functional response conditional to the health/disease status in the cuneus, precuneus, middle cingulate cortex and the ventrolateral and dorsolateral prefrontal cortices. Our results are the first to show a diagnosis-based effect of DISC1 haplotypes on working memory-related brain activity, emphasising its role in SZ.

Delay activity during visual working memory: A meta-analysis of 30 fMRI experiments

Visual working memory refers to the temporary maintenance and manipulation of task-related visual information. Recent debate on the underlying neural substrates of visual working memory has focused on the delay period of relevant tasks. Persistent neural activity throughout the delay period has been recognized as a correlate of working memory, yet regions demonstrating sustained hemodynamic responses show inconsistency across individual studies. To develop a more precise understanding of delay-period activations during visual working memory, we conducted a coordinate-based meta-analysis on 30 fMRI experiments involving 515 healthy adults with a mean age of 25.65 years. The main analysis revealed a widespread frontoparietal network associated with delay-period activity, as well as activation in the right inferior temporal cortex. These findings were replicated using different meta-analytical algorithms and were shown to be robust against between-study heterogeneity and publication bias. Further meta-analyses on different subgroups of experiments with specific task demands and stimulus types revealed similar delay-period networks, with activations distributed across the frontal and parietal cortices. The roles of prefrontal regions, posterior parietal regions, and inferior temporal areas are reviewed and discussed in the context of content-specific storage. We conclude that cognitive operations that occur during the unfilled delay period in visual working memory tasks can be flexibly expressed across a frontoparietal-temporal network depending on experimental parameters.

Towards the understanding of state-independent neural traits underlying psychiatric disorders

Hampered by the symptom complexity and diversity, the understanding of fundamental mechanisms underlying psychiatric disorders remains elusive. Traditional neuroscience research focusing on each behavioral domain separately may lack an overarching view of the pathogenesis of an entire disorder, offering limited power to identify core neuropathology that could possibly account for the disorder's various symptoms. The search for neural traits that are robustly present across different brain functional states and disease stages may provide insights into the rudimentary changes beneath manifest clinical phenotypes and thus help penetrate the causal mechanisms underlying a complex disorder. In this review, I briefly summarize previous research on this topic, emphasize how neural traits may help boost the understanding of biological mechanisms underlying psychiatric disorders, and exemplify how the observed traits may aid individualized predictions for diagnosis and prognosis in precision psychiatry, in particular related to schizophrenia. I also discuss a proposed research framework that can be leveraged for future studies on neural traits, as well as considerations for future applications of this nascent research strategy.

Lower functional connectivity of white matter during rest and working memory tasks is associated with cognitive impairments in schizophrenia

BACKGROUND

Schizophrenia can be understood as a disturbance of functional connections within brain networks. However, functional alterations that involve white matter (WM) specifically, or their cognitive correlates, have seldomly been investigated, especially during tasks.

METHODS

Resting state and task fMRI images were acquired on 84 patients and 67 controls. Functional connectivities (FC) between 46 WM bundles and 82 cortical regions were compared between the groups under two conditions (i.e., resting state and during working memory retention period). The FC density of each WM bundle was then compared between groups. Associations of FC with cognitive scores were evaluated.

RESULTS

FC measures were lower in schizophrenia relative to controls for external capsule, cingulum (cingulate and hippocampus), uncinate fasciculus, as well as corpus callosum (genu and body) under the rest or the task condition, and were higher in the posterior corona radiata and posterior thalamic radiation during the task condition. FC for specific WM bundles was correlated with cognitive performance assessed by working memory and processing speed metrics.

CONCLUSIONS

The findings suggest that the functional abnormalities in patients' WM are heterogeneous, possibly reflecting several underlying mechanisms such as structural damage, functional compensation and excessive effort on task, and that WM FC disruption may contribute to the impairments of working memory and processing speed. This is the first report on WM FC abnormalities in schizophrenia relative to controls and their cognitive associates during both rest and task and highlights the need to consider WM functions as components of brain functional networks in schizophrenia.

Dysregulation of Myt1 expression acts as a potential peripheral biomarker for major depressive disorder and bipolar disorder

Major depressive disorder (MDD) and bipolar disorder (BPD) are among the most debilitating mental conditions. Diagnostic criteria for MDD include psychological and physical symptoms, such as low mood and changes in appetite or sleep, respectively. BPD in addition to periods of depression represents episodes of mania or hypomania, and elevation in mood and energy levels are associated with this condition. Dysregulation in adult neurogenesis and myelination have been reported in psychiatric disorders. As a key factor in neurogenesis, it was hypothesized that Myt1 gene expression may be altered in these conditions. Using Real-time PCR, Myt1 expression level in 100 MDD patients and 100 BPD patients, compared with healthy control (HC) individuals was evaluated. Results demonstrate significant downregulation of Myt1 in MDD and BPD. Logistic regression analysis and binary classification evaluation reveal potential risk factor and biomarker characteristics of Myt1, respectively. Moreover, forward and backward digit span results denote a significant reduction in the function of working memory (WM) of MDD and BPD subjects. Correlation analysis revealed a significant association between Myt1 downregulation and WM disruption in the affected individuals. In conclusion, due to its altered role in neurogenesis, downregulation of Myt1 can be associated with the pathology of MDD and BPD.