Within and beyond the visual cortex: brain tumors induce highly sensitive plasticity of visual processing in whole-brain neural functional networks.

Vision is a key source of information input for humans, which involves various cognitive functions and a great range of neural networks inside and beyond the visual cortex. There has been increasing observation that the cognitive outcomes after a brain lesion cannot be well predicted by the attributes of the lesion itself but are influenced by the functional network plasticity. However, the mechanisms of impaired or preserved visual cognition have not been probed from direct function-execution conditions and few works have observed it on whole-brain dynamic networks. We used high-resolution electroencephalogram recordings from 25 patients with brain tumors to track the dynamical patterns of functional reorganization in visual processing tasks with multilevel complexity. By comparing with 24 healthy controls, increased cortical responsiveness as functional compensation was identified in the early phase of processing, which was highly localized to the visual cortex and functional networks and less relevant to the tumor position. Besides, a spreading wide enhancement in whole-brain functional connectivity was elicited by the visual word-recognition task. Enhanced early rapid-onset cortical compensation in the local functional networks may contribute to largely preserved basic vision functions, and higher-cognitive tasks are vulnerable to impairment but with high sensitivity of functional plasticity being elicited.

Brain function changes reveal rapid antidepressant effects of nitrous oxide for treatment-resistant depression:Evidence from task-state EEG.

Nitrous oxide has rapid antidepressant effects in patients with treatment-resistant depression (TRD), but its underlying mechanisms of therapeutic actions are not well understood. Moreover, most of the current studies lack objective biological indicators to evaluate the changes of nitrous oxide-induced brain function for TRD. Therefore, this study assessed the effect of nitrous oxide on brain function for TRD based on event-related potential (ERP) components and functional connectivity networks (FCNs) methods. In this randomized, longitudinal, placebo-controlled trial, all TRD participants were divided into two groups to receive either a 1-hour inhalation of nitrous oxide or a placebo treatment, and they took part in the same task-state electroencephalogram (EEG) experiment before and after treatment. The experimental results showed that nitrous oxide improved depressive symptoms better than placebo in terms of 17-Hamilton Depression Rating Scale score (HAMD-17). Statistical analysis based on ERP components showed that nitrous oxide-induced significant differences in amplitude and latency of N1, P1, N2, P2. In addition, increased brain functional connectivity was found after nitrous oxide treatment. And the change of network metrics has a significant correlation with decreased depressive symptoms. These findings may suggest that nitrous oxide improves depression symptoms for TRD by modifying brain function.

Multi-dimensional conditional mutual information with application on the EEG signal analysis for spatial cognitive ability evaluation.

This study aims to explore an effective method to evaluate spatial cognitive ability, which can effectively extract and classify the feature of EEG signals collected from subjects participating in the virtual reality (VR) environment; and evaluate the training effect objectively and quantitatively to ensure the objectivity and accuracy of spatial cognition evaluation, according to the classification results. Therefore, a multi-dimensional conditional mutual information (MCMI) method is proposed, which could calculate the coupling strength of two channels considering the influence of other channels. The coupled characteristics of the multi-frequency combination were transformed into multi-spectral images, and the image data were classified employing the convolutional neural networks (CNN) model. The experimental results showed that the multi-spectral image transform features based on MCMI are better in classification than other methods, and among the classification results of six band combinations, the best classification accuracy of Beta1-Beta2-Gamma combination is 98.3%. The MCMI characteristics on the Beta1-Beta2-Gamma band combination can be a biological marker for the evaluation of spatial cognition. The proposed feature extraction method based on MCMI provides a new perspective for spatial cognitive ability assessment and analysis.