AIMC Topic: Brain Mapping
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Perturbing BEAMs: EEG adversarial attack to deep learning models for epilepsy diagnosing.
BMC medical informatics and decision making
Jul 6, 2023
Deep learning models have been widely used in electroencephalogram (EEG) analysis and obtained excellent performance. But the adversarial attack and defense for them should be thoroughly studied before putting them into safety-sensitive use. This wor...
An automatic interpretable deep learning pipeline for accurate Parkinson's disease diagnosis using quantitative susceptibility mapping and T1-weighted images.
Human brain mapping
Jun 19, 2023
Parkinson's disease (PD) diagnosis based on magnetic resonance imaging (MRI) is still challenging clinically. Quantitative susceptibility maps (QSM) can potentially provide underlying pathophysiological information by detecting the iron distribution ...
msQSM: Morphology-based self-supervised deep learning for quantitative susceptibility mapping.
NeuroImage
May 21, 2023
Quantitative susceptibility mapping (QSM) has been applied to the measurement of iron deposition and the auxiliary diagnosis of neurodegenerative disease. There still exists a dipole inversion problem in QSM reconstruction. Recently, deep learning ap...
Deep learning applied to EEG source-data reveals both ventral and dorsal visual stream involvement in holistic processing of social stimuli.
Scientific reports
May 5, 2023
Perception of social stimuli (faces and bodies) relies on "holistic" (i.e., global) mechanisms, as supported by picture-plane inversion: perceiving inverted faces/bodies is harder than perceiving their upright counterpart. Albeit neuroimaging evidenc...
Neurophysiology, Neuropsychology, and Epilepsy, in 2022: Hills We Have Climbed and Hills Ahead. Neurophysiology in epilepsy.
Epilepsy & behavior : E&B
Apr 27, 2023
Since the discovery of the human electroencephalogram (EEG), neurophysiology techniques have become indispensable tools in our armamentarium to localize epileptic seizures. New signal analysis techniques and the prospects of artificial intelligence a...
Structure and function in artificial, zebrafish and human neural networks.
Physics of life reviews
Apr 25, 2023
Network science provides a set of tools for the characterization of the structure and functional behavior of complex systems. Yet a major problem is to quantify how the structural domain is related to the dynamical one. In other words, how the divers...
Data-efficient resting-state functional magnetic resonance imaging brain mapping with deep learning.
Journal of neurosurgery
Apr 14, 2023
OBJECTIVE: Resting-state functional MRI (RS-fMRI) enables the mapping of function within the brain and is emerging as an efficient tool for the presurgical evaluation of eloquent cortex. Models capable of reliable and precise mapping of resting-state...
Benchmarking explanation methods for mental state decoding with deep learning models.
NeuroImage
Apr 13, 2023
Deep learning (DL) models find increasing application in mental state decoding, where researchers seek to understand the mapping between mental states (e.g., experiencing anger or joy) and brain activity by identifying those spatial and temporal feat...
Attention Deficit Hyperactivity Disorder Classification Based on Deep Learning.
IEEE/ACM transactions on computational biology and bioinformatics
Apr 3, 2023
Attention Deficit Hyperactivity Disorder (ADHD) is a type of mental health disorder that can be seen from children to adults and affects patients' normal life. Accurate diagnosis of ADHD as early as possible is very important for the treatment of pat...
Inter-individual deep image reconstruction via hierarchical neural code conversion.
NeuroImage
Mar 11, 2023
The sensory cortex is characterized by general organizational principles such as topography and hierarchy. However, measured brain activity given identical input exhibits substantially different patterns across individuals. Although anatomical and fu...
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