AIMC Topic: Cerebral Cortex

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Interpretable machine learning approach for neuron-centric analysis of human cortical cytoarchitecture.

Scientific reports Apr 5, 2023
The complexity of the cerebral cortex underlies its function and distinguishes us as humans. Here, we present a principled veridical data science methodology for quantitative histology that shifts focus from image-level investigations towards neuron-...
Image Processing, Computer-Assisted Neurons Cerebral Cortex Humans Machine Learning
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Decoding reappraisal and suppression from neural circuits: A combined supervised and unsupervised machine learning approach.

Cognitive, affective & behavioral neuroscience Mar 28, 2023
Emotion regulation is a core construct of mental health and deficits in emotion regulation abilities lead to psychological disorders. Reappraisal and suppression are two widely studied emotion regulation strategies but, possibly due to methodological...
Anxiety Magnetic Resonance Imaging Humans Brain Cerebral Cortex Emotional Regulation Emotions Unsupervised Machine Learning
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Automatic detection of punctate white matter lesions in infants using deep learning of composite images from two cases.

Scientific reports Mar 17, 2023
Punctate white matter lesions (PWMLs) in infants may be related to neurodevelopmental outcomes based on the location or number of lesions. This study aimed to assess the automatic detectability of PWMLs in infants on deep learning using composite ima...
Humans Cerebral Cortex Magnetic Resonance Imaging Infant White Matter Probability Deep Learning
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iBEAT V2.0: a multisite-applicable, deep learning-based pipeline for infant cerebral cortical surface reconstruction.

Nature protocols Mar 3, 2023
The human cerebral cortex undergoes dramatic and critical development during early postnatal stages. Benefiting from advances in neuroimaging, many infant brain magnetic resonance imaging (MRI) datasets have been collected from multiple imaging sites...
Image Processing, Computer-Assisted Magnetic Resonance Imaging Cerebral Cortex Deep Learning Child Brain Infant Humans
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The identification of interacting brain networks during robot-assisted training with multimodal stimulation.

Journal of neural engineering Jan 18, 2023
Robot-assisted rehabilitation training is an effective way to assist rehabilitation therapy. So far, various robotic devices have been developed for automatic training of central nervous system following injury. Multimodal stimulation such as visual ...
Robotics Arm Upper Extremity Rehabilitation Cerebral Cortex Humans Brain
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Machine learning sequence prioritization for cell type-specific enhancer design.

eLife May 16, 2022
Recent discoveries of extreme cellular diversity in the brain warrant rapid development of technologies to access specific cell populations within heterogeneous tissue. Available approaches for engineering-targeted technologies for new neuron subtype...
Globus Pallidus Parvalbumins Computational Biology Machine Learning Animals Sequence Analysis, DNA Neurons Cerebral Cortex Mice Enhancer Elements, Genetic
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Unsupervised learning of brain state dynamics during emotion imagination using high-density EEG.

NeuroImage Jan 5, 2022
This study applies adaptive mixture independent component analysis (AMICA) to learn a set of ICA models, each optimized by fitting a distributional model for each identified component process while maximizing component process independence within som...
Adult Functional Neuroimaging Unsupervised Machine Learning Electroencephalography Emotions Humans Cerebral Cortex Imagination
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Sequential method for fast neural population activity reconstruction in the cortex from incomplete noisy measurements.

Computers in biology and medicine Dec 7, 2021
During recent years there has been a growing interest in stochastic dynamic neural fields employed for modeling and predictions in biomedical and technical systems. In this paper, given some incomplete noisy data available from sensors, we propose an...
Cerebral Cortex Neural Networks, Computer Algorithms
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A dynamic graph convolutional neural network framework reveals new insights into connectome dysfunctions in ADHD.

NeuroImage Nov 30, 2021
The pathological mechanism of attention deficit hyperactivity disorder (ADHD) is incompletely specified, which leads to difficulty in precise diagnosis. Functional magnetic resonance imaging (fMRI) has emerged as a common neuroimaging technique for s...
Magnetic Resonance Imaging Young Adult Nerve Net Humans Cerebral Cortex Adult Neural Networks, Computer Connectome Attention Deficit Disorder with Hyperactivity
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Unsupervised deep learning identifies semantic disentanglement in single inferotemporal face patch neurons.

Nature communications Nov 9, 2021
In order to better understand how the brain perceives faces, it is important to know what objective drives learning in the ventral visual stream. To answer this question, we model neural responses to faces in the macaque inferotemporal (IT) cortex wi...
Brain Cerebral Cortex Humans Deep Learning Neurons Pattern Recognition, Visual Neural Networks, Computer Semantics Temporal Lobe
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