AIMC Topic: Brain Mapping
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Analysis of Factors Affecting Cranial Nerve Function of Patients With Vascular Mild Cognitive Impairment Through Functional Magnetic Resonance Imaging Under Artificial Intelligence Environment.
Frontiers in public health
Mar 25, 2022
The study aimed to explore the risk factors of effects of patients with vascular mild cognitive impairment (VaMCI) through functional magnetic resonance imaging (fMRI). In this study, 62 patients were selected from the department of neurology, admitt...
Brain Decoding Using fMRI Images for Multiple Subjects through Deep Learning.
Computational and mathematical methods in medicine
Mar 1, 2022
Substantial information related to human cerebral conditions can be decoded through various noninvasive evaluating techniques like fMRI. Exploration of the neuronal activity of the human brain can divulge the thoughts of a person like what the subjec...
Abnormal Degree Centrality as a Potential Imaging Biomarker for Right Temporal Lobe Epilepsy: A Resting-state Functional Magnetic Resonance Imaging Study and Support Vector Machine Analysis.
Neuroscience
Feb 11, 2022
Previous studies have reported altered neuroimaging features in right temporal lobe epilepsy (rTLE). However, the alterations in degree centrality (DC) as a diagnostic method for rTLE have not been reported. Therefore, we aimed to explore abnormaliti...
A data-driven deep learning pipeline for quantitative susceptibility mapping (QSM).
Magnetic resonance imaging
Feb 3, 2022
PURPOSE: This study developed a data-driven optimization to improve the accuracy of deep learning QSM quantification.
Constructing neural network models from brain data reveals representational transformations linked to adaptive behavior.
Nature communications
Feb 3, 2022
The human ability to adaptively implement a wide variety of tasks is thought to emerge from the dynamic transformation of cognitive information. We hypothesized that these transformations are implemented via conjunctive activations in "conjunction hu...
A self-supervised domain-general learning framework for human ventral stream representation.
Nature communications
Jan 25, 2022
Anterior regions of the ventral visual stream encode substantial information about object categories. Are top-down category-level forces critical for arriving at this representation, or can this representation be formed purely through domain-general ...
Individualized spatial network predictions using Siamese convolutional neural networks: A resting-state fMRI study of over 11,000 unaffected individuals.
PloS one
Jan 21, 2022
Individuals can be characterized in a population according to their brain measurements and activity, given the inter-subject variability in brain anatomy, structure-function relationships, or life experience. Many neuroimaging studies have demonstrat...
Functional cortical localization of tongue movements using corticokinematic coherence with a deep learning-assisted motion capture system.
Scientific reports
Jan 10, 2022
Corticokinematic coherence (CKC) between magnetoencephalographic and movement signals using an accelerometer is useful for the functional localization of the primary sensorimotor cortex (SM1). However, it is difficult to determine the tongue CKC beca...
Hyperrealistic neural decoding for reconstructing faces from fMRI activations via the GAN latent space.
Scientific reports
Jan 7, 2022
Neural decoding can be conceptualized as the problem of mapping brain responses back to sensory stimuli via a feature space. We introduce (i) a novel experimental paradigm that uses well-controlled yet highly naturalistic stimuli with a priori known ...
Structural and functional brain networks of individual differences in trait anger and anger control: An unsupervised machine learning study.
The European journal of neuroscience
Dec 27, 2021
The ability to experience, use and eventually control anger is crucial to maintain well-being and build healthy relationships. Despite its relevance, the neural mechanisms behind individual differences in experiencing and controlling anger are poorly...
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