AIMC Topic: Brain Mapping
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Spatiotemporal discoordination of brain spontaneous activity in major depressive disorder.
Journal of affective disorders
Aug 16, 2024
BACKGROUND: Major depressive disorder (MDD) is a widespread mental health issue, impacting spatial and temporal aspects of brain activity. The neural mechanisms behind MDD remain unclear. To address this gap, we introduce a novel measure, spatiotempo...
TS-AI: A deep learning pipeline for multimodal subject-specific parcellation with task contrasts synthesis.
Medical image analysis
Aug 8, 2024
Accurate mapping of brain functional subregions at an individual level is crucial. Task-based functional MRI (tfMRI) captures subject-specific activation patterns during various functions and behaviors, facilitating the individual localization of fun...
Convolutional neural networks can identify brain interactions involved in decoding spatial auditory attention.
PLoS computational biology
Aug 8, 2024
Human listeners have the ability to direct their attention to a single speaker in a multi-talker environment. The neural correlates of selective attention can be decoded from a single trial of electroencephalography (EEG) data. In this study, leverag...
Fusing multi-scale functional connectivity patterns via Multi-Branch Vision Transformer (MB-ViT) for macaque brain age prediction.
Neural networks : the official journal of the International Neural Network Society
Aug 3, 2024
Brain age (BA) is defined as a measure of brain maturity and could help characterize both the typical brain development and neuropsychiatric disorders in mammals. Various biological phenotypes have been successfully applied to predict BA of human usi...
Preparatory activity of anterior insula predicts conflict errors: integrating convolutional neural networks and neural mass models.
Scientific reports
Jul 19, 2024
Preparatory brain activity is a cornerstone of proactive cognitive control, a top-down process optimizing attention, perception, and inhibition, fostering cognitive flexibility and adaptive attention control in the human brain. In this study, we prop...
Leveraging Brain Modularity Prior for Interpretable Representation Learning of fMRI.
IEEE transactions on bio-medical engineering
Jul 18, 2024
Resting-state functional magnetic resonance imaging (rs-fMRI) can reflect spontaneous neural activities in the brain and is widely used for brain disorder analysis. Previous studies focus on extracting fMRI representations using machine/deep learning...
7 T and beyond: toward a synergy between fMRI-based presurgical mapping at ultrahigh magnetic fields, AI, and robotic neurosurgery.
European radiology experimental
Jul 1, 2024
Presurgical evaluation with functional magnetic resonance imaging (fMRI) can reduce postsurgical morbidity. Here, we discuss presurgical fMRI mapping at ultra-high magnetic fields (UHF), i.e., ≥ 7 T, in the light of the current growing interest in ar...
Shared functional specialization in transformer-based language models and the human brain.
Nature communications
Jun 29, 2024
When processing language, the brain is thought to deploy specialized computations to construct meaning from complex linguistic structures. Recently, artificial neural networks based on the Transformer architecture have revolutionized the field of nat...
An rs-fMRI based neuroimaging marker for adult absence epilepsy.
Epilepsy research
Jun 28, 2024
OBJECTIVE: Approximately 20-30 % of epilepsy patients exhibit negative findings on routine magnetic resonance imaging, and this condition is known as nonlesional epilepsy. Absence epilepsy (AE) is a prevalent form of nonlesional epilepsy. This study ...
Individual characteristics outperform resting-state fMRI for the prediction of behavioral phenotypes.
Communications biology
Jun 26, 2024
In this study, we aimed to compare imaging-based features of brain function, measured by resting-state fMRI (rsfMRI), with individual characteristics such as age, gender, and total intracranial volume to predict behavioral measures. We developed a ma...
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