Aberrant brain dynamics in major depressive disorder during working memory task.

Working memory (WM) is a distributed and dynamic process, and WM deficits are recognized as one of the top-ranked endophenotype candidates for major depressive disorders (MDD). However, there is a lack of knowledge of brain temporal-spatial profile of WM deficits in MDD. We used the dynamical degree centrality (dDC) to investigate the whole-brain temporal-spatial profile in 40 MDD and 40 controls during an n-back task with 2 conditions (i.e., '0back' and '2back'). We explored the dDC temporal variability and clustered meta-stable states in 2 groups during different WM conditions. Pearson's correlation analysis was used to evaluate the relationship between the altered dynamics with clinical symptoms and WM performance. Compared with controls, under '2back vs. 0back' contrast, patients showed an elevated dDC variability in wide range of brain regions, including the middle frontal gyrus, orbital part of inferior frontal gyrus (IFGorb), hippocampus, and middle temporal gyrus. Furthermore, the increased dDC variability in the hippocampus and IFGorb correlated with worse WM performance. However, there were no significant group-related differences in the meta-stable states were observed. This study demonstrated the increased WM-related instability (i.e., the elevated dDC variability) was represented in MDD, and enhancing stability may help patients achieve better WM performance.

A connectome-based model of delusion in schizophrenia using functional connectivity under working memory task.

Delusion is an important feature of schizophrenia, which may stem from cognitive biases. Working memory (WM) is the core foundation of cognition, closely related to delusion. However, the knowledge of neural mechanisms underlying the relationship between WM and delusion in schizophrenia is poorly investigated. Two hundred and thirty patients with schizophrenia (dataset 1: n = 130; dataset 2: n = 100) were enrolled and scanned for an N-back WM task. We constructed the WM-related whole-brain functional connectome and conducted Connectome-based Predictive Modelling (CPM) to detect the delusion-related networks and built the correlation model in dataset 1. The correlation between identified networks and delusion severity was tested in a separate, heterogeneous sample of dataset 2 that mainly includes early-onset schizophrenia. The identified delusion-related network has a strong correlation with delusion severity measured by the NO.20 item of SAPS in dataset 1 (r = 0.433, p = 2.7 × 10-7, permutation-p = 0.035), and can be validated in the same dataset by using another delusion measurement, that is, the P1 item of PANSS (r = 0.362, p = 0.0005). It can be validated in another independent dataset 2 (NO.20 item of SAPS for r = 0.31, p = 0.0024, P1 item of PANSS for r = 0.27, p = 0.0074). The delusion-related network comprises the connections between the default mode network (DMN), cingulo-opercular network (CON), salience network (SN), subcortical, sensory-somatomotor network (SMN), and visual networks. We successfully established correlation models of individualized delusion based on the WM-related functional connectome and showed a strong correlation between delusion severity and connections within the DMN, CON, SMN, and subcortical network.

Effects of long-term antipsychotic medication on brain instability in first-episode schizophrenia patients: a resting-state fMRI study.

Early initiation of antipsychotic treatment plays a crucial role in the management of first-episode schizophrenia (FES) patients, significantly improving their prognosis. However, limited attention has been given to the long-term effects of antipsychotic drug therapy on FES patients. In this research, we examined the changes in abnormal brain regions among FES patients undergoing long-term treatment using a dynamic perspective. A total of 98 participants were included in the data analysis, comprising 48 FES patients, 50 healthy controls, 22 patients completed a follow-up period of more than 6 months with qualified data. We processed resting-state fMRI data to calculate coefficient of variation of fractional amplitude of low-frequency fluctuations (CVfALFF), which reflects the brain regional activity stability. Data analysis was performed at baseline and after long-term treatment. We observed that compared with HCs, patients at baseline showed an elevated CVfALFF in the supramarginal gyrus (SMG), parahippocampal gyrus (PHG), caudate, orbital part of inferior frontal gyrus (IOG), insula, and inferior frontal gyrus (IFG). After long-term treatment, the instability in SMG, PHG, caudate, IOG, insula and inferior IFG have ameliorated. Additionally, there was a positive correlation between the decrease in dfALFF in the SMG and the reduction in the SANS total score following long-term treatment. In conclusion, FES patients exhibit unstable regional activity in widespread brain regions at baseline, which can be ameliorated with long-term treatment. Moreover, the extent of amelioration in SMG instability is associated with the amelioration of negative symptoms.

The neural compensation phenomenon in schizophrenia with mild attention deficits during working memory task.

BACKGROUND: Working memory (WM) and attention are essential cognitive processes, and their interplay is critical for efficient information processing. Schizophrenia often exhibits deficits in both WM and attention, contributing to function impairments. This study aims to investigate the neural mechanisms underlying the relationship between WM impairments and attention deficits in schizophrenia. METHODS: We assessed the functional-MRI scans of the 184 schizophrenias with different attention deficits (mild=133; severe=51) and 146 controls during an N-back WM task. We explored their whole-brain functional connectome profile by adopting the voxel-wise degree centrality (DC). Linear analysis was conducted to explore the associations among attention deficit severity, altered DC, and WM performance in patients. RESULTS: We observed that all patients showed decreased DC in the pre-supplementary area (pre-SMA), and posterior cerebellum compared to the controls, and schizophrenia patients with mild attention deficits showed decreased DC in the supramarginal gyrus, insula, and precuneus compared with the other 2 groups. DC values of the detected brain regions displayed U-shaped or inverted U-shaped curves, rather than a linear pattern, in response to increasing attention deficits. The linear analysis indicated that altered DC of the pre-SMA can modulate the relationship between attention deficits and WM performance. CONCLUSION: The U-shaped or inverted U-shaped pattern in response to increasing attention deficits may reflect a compensation mechanism in schizophrenia with mild attention deficits. This notion is also supported by the linear analysis that schizophrenia patients with mild attention deficits can improve their WM performance by increasing the DC value of the pre-SMA.

Modeling and experimental analysis of wire-driven continuum surgical robot.

A new configuration of continuum surgical robot is proposed, whose skeleton is composed of inner and outer layers. The outer layer is composed of miniature rotating modules connected in series and connected by orthogonal hinges, which can ensure the ability to resist unconventional torsion without losing the degree of freedom. The inner layer is a central support column with superelasticity. When bending, its superelasticity can make the overall configuration biased toward constant curvature bending, which is convenient for motion control and according to the new configuration, this paper establishes the kinematics model of the robot. Finally, the motion control experiment of the continuum robot is carried out. After the experiment, the average positioning error of the robot is 2.674 mm, and the average repetitive positioning error is 2.625 mm. Both are less than 2 % of the robot length, verifying the accuracy of the model.