AIMC Topic: Cerebral Cortex

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Machine learning analysis of cortical activity in visual associative learning tasks with differing stimulus complexity.

Physiology international Feb 27, 2025
Associative learning tests are cognitive assessments that evaluate the ability of individuals to learn and remember relationships between pairs of stimuli. The Rutgers Acquired Equivalence Test (RAET) is an associative learning test that utilizes ima...
Photic Stimulation Visual Perception Association Learning Brain Mapping Electroencephalography Cerebral Cortex Humans Machine Learning Female Young Adult Adult Male
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A simple clustering approach to map the human brain's cortical semantic network organization during task.

NeuroImage Feb 18, 2025
Constructing task-state large-scale brain networks can enhance our understanding of the organization of brain functions during cognitive tasks. The primary goal of brain network partitioning is to cluster functionally homogeneous brain regions. Howev...
Cerebral Cortex Male Nerve Net Cognition Female Magnetic Resonance Imaging Cluster Analysis Humans Young Adult Brain Mapping Brain Adult Semantics
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Exploring hyperelastic material model discovery for human brain cortex: Multivariate analysis vs. artificial neural network approaches.

Journal of the mechanical behavior of biomedical materials Feb 10, 2025
The human brain, characterized by its intricate architecture, exhibits complex mechanical properties that underpin its critical functional capabilities. Traditional computational methods, such as finite element analysis, have been instrumental in unc...
Elasticity Multivariate Analysis Cerebral Cortex Humans Neural Networks, Computer Biomechanical Phenomena Finite Element Analysis
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Geometric deep learning with adaptive full-band spatial diffusion for accurate, efficient, and robust cortical parcellation.

Medical image analysis Feb 8, 2025
Cortical parcellation delineates the cerebral cortex into distinct regions according to their distinctiveness in anatomy and/or function, which is a fundamental preprocess in brain cortex analysis and can influence the accuracy and specificity of sub...
Image Processing, Computer-Assisted Humans Algorithms Cerebral Cortex Adult Deep Learning
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Leveraging Input-Level Feature Deformation With Guided-Attention for Sulcal Labeling.

IEEE transactions on medical imaging Feb 4, 2025
The identification of cortical sulci is key for understanding functional and structural development of the cortex. While large, consistent sulci (or primary/secondary sulci) receive significant attention in most studies, the exploration of smaller an...
Image Processing, Computer-Assisted Humans Neural Networks, Computer Magnetic Resonance Imaging Algorithms Cerebral Cortex
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Hybrid neural networks for continual learning inspired by corticohippocampal circuits.

Nature communications Feb 2, 2025
Current artificial systems suffer from catastrophic forgetting during continual learning, a limitation absent in biological systems. Biological mechanisms leverage the dual representation of specific and generalized memories within corticohippocampal...
Cerebral Cortex Nerve Net Memory Models, Neurological Humans Neurons Neural Networks, Computer Hippocampus Learning Animals
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Decoding cortical folding patterns in marmosets using machine learning and large language model.

NeuroImage Jan 24, 2025
Macroscale neuroimaging results have revealed significant differences in the structural and functional connectivity patterns of gyri and sulci in the primate cerebral cortex. Despite these findings, understanding these differences at the molecular le...
Cerebral Cortex Large Language Models Callithrix Male Machine Learning Transcriptome Language Animals
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A Self-supervised Deep Learning Model for Diagonal Sulcus Detection with Limited Labeled Data.

Neuroinformatics Dec 26, 2024
Sulci are a fundamental part of brain morphology, closely linked to brain function, cognition, and behavior. Tertiary sulci, characterized as the shallowest and smallest subtype, pose a challenging task for detection. The diagonal sulcus (ds), locate...
Humans Magnetic Resonance Imaging Male Supervised Machine Learning Neural Networks, Computer Cerebral Cortex Deep Learning Female Image Processing, Computer-Assisted Adult
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Predicting cortical-thalamic functional connectivity using functional near-infrared spectroscopy and graph convolutional networks.

Scientific reports Nov 30, 2024
Functional near-infrared spectroscopy (fNIRS) measures cortical hemodynamic changes, yet it cannot collect this information from subcortical structures, such as the thalamus, which is involved in several key functional networks. To address this drawb...
Spectroscopy, Near-Infrared Humans Magnetic Resonance Imaging Neural Networks, Computer Brain Injuries Female Cerebral Cortex Machine Learning Young Adult Infant, Newborn Thalamus Adult Male
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The Developing Human Connectome Project: A fast deep learning-based pipeline for neonatal cortical surface reconstruction.

Medical image analysis Nov 26, 2024
The Developing Human Connectome Project (dHCP) aims to explore developmental patterns of the human brain during the perinatal period. An automated processing pipeline has been developed to extract high-quality cortical surfaces from structural brain ...
Infant, Newborn Deep Learning Image Processing, Computer-Assisted Humans Magnetic Resonance Imaging Cerebral Cortex Connectome
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