Integrative role of attention networks in frequency-dependent modular organization of human brain.

Despite converging evidence of hierarchical organization in the cerebral cortex, with sensory-motor and association regions at opposite ends, the mechanism of such hierarchical interactions remains elusive. This organization was primarily investigated regarding the spatiotemporal dynamics of intrinsic connectivity networks (ICNs). However, more effort is needed to investigate network dynamics in the frequency domain.

Volumetric and functional connectivity changes of the thalamic nuclei in different stages of Alzheimer's disease.

Objective: Memory processes known to be impaired in Alzheimer's disease (AD) are maintained by a large-scale neurocognitive network with subcortical components, including the thalamus. Therefore, we aimed to examine the volumetric and functional changes of the thalamic nuclei at different scales across AD stages.

Methods: MRI data of patients diagnosed with 20 AD dementia (ADD), 30 amnestic mild cognitive impairment (MCI), and 30 subjective cognitive impairment (SCI) were used.

Neural correlates of approach-avoidance behavior in healthy subjects: Effects of low-frequency repetitive transcranial magnetic stimulation (rTMS) over the right dorsolateral prefrontal cortex.

The dorsolateral prefrontal cortex (dlPFC) is implicated in top-down regulation of emotion, but the detailed network mechanisms require further elucidation. To investigate network-level functions of the dlPFC in emotion regulation, this study measured changes in task-based activation, resting-state and task-based functional connectivity (FC) patterns following suppression of dlPFC excitability by 1-Hz repetitive transcranial magnetic stimulation (rTMS). In a sham-controlled within-subject design, 1-Hz active or sham rTMS was applied to the right dlPFC of 19 healthy volunteers during two separate counterbalanced sessions.

Siamese Graph Convolutional Network quantifies increasing structure-function discrepancy over the cognitive decline continuum.

Background And Objective: Alzheimer's disease dementia (ADD) is well known to induce alterations in both structural and functional brain connectivity. However, reported changes in connectivity are mostly limited to global/local network features, which have poor specificity for diagnostic purposes. Following recent advances in machine learning, deep neural networks, particularly Graph Neural Network (GNN) based approaches, have found applications in brain research as well.

Diffusion tensor imaging in photosensitive and nonphotosensitive juvenile myoclonic epilepsy.

Introduction/background: Juvenile myoclonic epilepsy (JME) syndrome is known to cause alterations in brain structure and white matter integrity. The study aimed to determine structural white matter changes in patients with JME and to reveal the differences between the photosensitive (PS) and nonphotosensitive (NPS) subgroups by diffusion tensor imaging (DTI) using the tract-based spatial statistics (TBSS) method.

Methods: This study included data from 16 PS, 15 NPS patients with JME, and 41 healthy participants.