A data-driven network decomposition of the temporal, spatial, and spectral dynamics underpinning visual-verbal working memory processes
The brain dynamics underlying working memory (WM) unroll via transient frequency-specific
large-scale brain networks. This multidimensionality (time, space, and frequency) …
large-scale brain networks. This multidimensionality (time, space, and frequency) …
Classifying and scoring major depressive disorders by residual neural networks on specific frequencies and brain regions
Major Depressive Disorder (MDD)-can be evaluated by advanced neurocomputing and
traditional machine learning techniques. This study aims to develop an automatic system …
traditional machine learning techniques. This study aims to develop an automatic system …
InA: Inhibition Adaption on pre-trained language models
Fine-tuning pre-trained language models (LMs) may not always be the most practical
approach for downstream tasks. While adaptation fine-tuning methods have shown …
approach for downstream tasks. While adaptation fine-tuning methods have shown …
Effects of indoor exposure to low level toluene on neural network alterations during working memory encoding
L Pan, J Liu, C Zhan, X Zhang, M Cui, X Su, Z Wang… - Chemosphere, 2023 - Elsevier
Objective While high concentrations of toluene are known to affect multiple human organ
systems, research concerning the influence of immediate, short-term exposure to toluene …
systems, research concerning the influence of immediate, short-term exposure to toluene …
The role of middle frontal gyrus in working memory retrieval by the effect of target detection tasks: a simultaneous EEG-fMRI study
P Xu, M Wang, T Zhang, J Zhang, Z Jin, L Li - Brain Structure and Function, 2023 - Springer
Maintained working memory (WM) representations have been shown to influence visual
target detection selection, while the effect of the visual target detection process on WM …
target detection selection, while the effect of the visual target detection process on WM …
Csgbbnet: an explainable deep learning framework for Covid-19 detection
The COVID-19 virus has swept the world and brought great impact to various fields, gaining
wide attention from all walks of life since the end of 2019. At present, although the global …
wide attention from all walks of life since the end of 2019. At present, although the global …
Computational modeling of attractor-based neural processes involved in the preparation of voluntary actions
A Hassannejad Nazir, J Hellgren Kotaleski… - Cognitive …, 2023 - Springer
Volition is conceived as a set of orchestrated executive functions, which can be
characterized by features, such as reason-based and goal-directedness, driven by …
characterized by features, such as reason-based and goal-directedness, driven by …
Dynamic changes of brain networks during working memory tasks in schizophrenia
R Yao, J Xue, P Yang, Q Wang, P Gao, X Yang… - Neuroscience, 2021 - Elsevier
Electroencephalograph (EEG) signals and graph theory measures have been widely used
to characterize the brain functional networks of healthy individuals and patients by …
to characterize the brain functional networks of healthy individuals and patients by …
Fast asymptotic algorithm for real-time causal connectivity analysis of multivariate systems and signals
The purpose of this work is to optimize the current state-of-the-art asymptotic algorithm of
connectivity Granger-causality measures in the frequency-domain, such as the Directed …
connectivity Granger-causality measures in the frequency-domain, such as the Directed …
Resonating with the World: Thinking Critically about Brain Criticality in Consciousness and Cognition
G Leisman, P Koch - Information, 2024 - mdpi.com
Aim: Biofields combine many physiological levels, both spatially and temporally. These
biofields reflect naturally resonant forms of synaptic energy reflected in growing and …
biofields reflect naturally resonant forms of synaptic energy reflected in growing and …