AIMC Topic: Brain Mapping
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Stimulus Selection Influences Prediction of Individual Phenotypes in Naturalistic Conditions.
Human brain mapping
Feb 15, 2025
While the use of naturalistic stimuli such as movie clips for understanding individual differences and brain-behaviour relationships attracts increasing interest, the influence of stimulus selection remains largely unclear. By using machine learning ...
Frequency-Specific Alternations in the Amplitude of Fluctuations in Tension-Type Headache: A Machine Learning Study.
Journal of neuroscience research
Nov 1, 2024
Brain neural signal at different frequency bands relates to different functions. However, the frequency-specific properties of spontaneous brain activity in tension-type headache (TTH)-the most rampant primary headache-remain largely unknown. We inve...
Unveiling Functional Biomarkers in Schizophrenia: Insights from Region of Interest Analysis Using Machine Learning.
Journal of integrative neuroscience
Sep 24, 2024
BACKGROUND: Schizophrenia is a complex and disabling mental disorder that represents one of the most important challenges for neuroimaging research. There were many attempts to understand these basic mechanisms behind the disorder, yet we know very l...
FMRI Data Analysis Preserving Map Variability Via Unsupervised Object-Centric Learning.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
A novel data-driven functional magnetic resonance imaging (fMRI) data analysis method is proposed using a deep object-centric learning paradigm. The method can faithfully estimate the variabilities in the spatial neural activation maps, which capture...
Deep Residual Neural Networks for Spatial EEG Source Imaging.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
EEG source imaging is an indispensable tool for non-invasive study of brain function. Existing methods mainly directly deal with the EEG inverse problem by imposing prior constraints. However, different brain activation patterns may produce similar p...
Mapping Cognitive Engagement: EEG and Graph Theory Analysis of Brain Region Involvement in Supernumerary Robotic Finger Utilization.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
As the worldwide incidence of stroke increases, supernumerary robotic limbs (SRLs), more specifically supernumerary robotic fingers (SRFs), present a potentially effective solution for enhancing the task related functionality of the upper-limbs of st...
Do we empathize humanoid robots and humans in the same way? Behavioral and multimodal brain imaging investigations.
Cerebral cortex (New York, N.Y. : 1991)
Jun 4, 2024
Humanoid robots have been designed to look more and more like humans to meet social demands. How do people empathize humanoid robots who look the same as but are essentially different from humans? We addressed this issue by examining subjective feeli...
Phase-encoded fMRI tracks down brainstorms of natural language processing with subsecond precision.
Human brain mapping
Feb 1, 2024
Natural language processing unfolds information overtime as spatially separated, multimodal, and interconnected neural processes. Existing noninvasive subtraction-based neuroimaging techniques cannot simultaneously achieve the spatial and temporal re...
Comprehensive exploration of multi-modal and multi-branch imaging markers for autism diagnosis and interpretation: insights from an advanced deep learning model.
Cerebral cortex (New York, N.Y. : 1991)
Jan 31, 2024
Autism spectrum disorder is a complex neurodevelopmental condition with diverse genetic and brain involvement. Despite magnetic resonance imaging advances, autism spectrum disorder diagnosis and understanding its neurogenetic factors remain challengi...
Modeling Brain Representations of Words' Concreteness in Context Using GPT-2 and Human Ratings.
Cognitive science
Dec 1, 2023
The meaning of most words in language depends on their context. Understanding how the human brain extracts contextualized meaning, and identifying where in the brain this takes place, remain important scientific challenges. But technological and comp...
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