AIMC Topic: Brain

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BrainLossNet: a fast, accurate and robust method to estimate brain volume loss from longitudinal MRI.

International journal of computer assisted radiology and surgery
PURPOSE: MRI-derived brain volume loss (BVL) is widely used as neurodegeneration marker. SIENA is state-of-the-art for BVL measurement, but limited by long computation time. Here we propose "BrainLossNet", a convolutional neural network (CNN)-based m...

EEG emotion recognition based on data-driven signal auto-segmentation and feature fusion.

Journal of affective disorders
Pattern recognition based on network connections has recently been applied to the brain-computer interface (BCI) research, offering new ideas for emotion recognition using Electroencephalogram (EEG) signal. However unified standards are currently lac...

Brain-computer interfaces inspired spiking neural network model for depression stage identification.

Journal of neuroscience methods
BACKGROUND: Depression is a global mental disorder, and traditional diagnostic methods mainly rely on scales and subjective evaluations by doctors, which cannot effectively identify symptoms and even carry the risk of misdiagnosis. Brain-Computer Int...

Microstate-based brain network dynamics distinguishing temporal lobe epilepsy patients: A machine learning approach.

NeuroImage
Temporal lobe epilepsy (TLE) stands as the predominant adult focal epilepsy syndrome, characterized by dysfunctional intrinsic brain dynamics. However, the precise mechanisms underlying seizures in these patients remain elusive. Our study encompassed...

Autism spectrum disorders detection based on multi-task transformer neural network.

BMC neuroscience
Autism Spectrum Disorders (ASD) are neurodevelopmental disorders that cause people difficulties in social interaction and communication. Identifying ASD patients based on resting-state functional magnetic resonance imaging (rs-fMRI) data is a promisi...

An optimized EEGNet decoder for decoding motor image of four class fingers flexion.

Brain research
As a cutting-edge technology of connecting biological brain and external devices, brain-computer interface (BCI) exhibits promising applications on extensive fields such as medical and military. As for the disable individuals with four limbs losing t...

Discovering the gene-brain-behavior link in autism via generative machine learning.

Science advances
Autism is traditionally diagnosed behaviorally but has a strong genetic basis. A genetics-first approach could transform understanding and treatment of autism. However, isolating the gene-brain-behavior relationship from confounding sources of variab...

Visualization of incrementally learned projection trajectories for longitudinal data.

Scientific reports
Longitudinal studies that continuously generate data enable the capture of temporal variations in experimentally observed parameters, facilitating the interpretation of results in a time-aware manner. We propose IL-VIS (incrementally learned visualiz...

Individual Prediction of Electric Field Induced by Deep-Brain Magnetic Stimulation With CNN-Transformer.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Deep-brain Magnetic Stimulation (DMS) can improve the symptoms caused by Alzheimer's disease by inducing rhythmic electric field in the deep brain, and the induced electric field is rhythm-dependent. However, calculating the induced electric field re...