AIMC Topic: Brain Mapping

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Do Humans and Deep Convolutional Neural Networks Use Visual Information Similarly for the Categorization of Natural Scenes?

Cognitive science Jun 1, 2021
The investigation of visual categorization has recently been aided by the introduction of deep convolutional neural networks (CNNs), which achieve unprecedented accuracy in picture classification after extensive training. Even if the architecture of ...
Brain Animals Brain Mapping Visual Perception Humans Neural Networks, Computer
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DeepMapi: a Fully Automatic Registration Method for Mesoscopic Optical Brain Images Using Convolutional Neural Networks.

Neuroinformatics Apr 1, 2021
The extreme complexity of mammalian brains requires a comprehensive deconstruction of neuroanatomical structures. Scientists normally use a brain stereotactic atlas to determine the locations of neurons and neuronal circuits. However, different brain...
Mice Magnetic Resonance Imaging Mice, Inbred C57BL Brain Mapping Brain Animals Imaging, Three-Dimensional Image Processing, Computer-Assisted Humans Neural Networks, Computer Neuroimaging Research Design Nerve Net Databases, Factual
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An ecologically motivated image dataset for deep learning yields better models of human vision.

Proceedings of the National Academy of Sciences of the United States of America Feb 23, 2021
Deep neural networks provide the current best models of visual information processing in the primate brain. Drawing on work from computer vision, the most commonly used networks are pretrained on data from the ImageNet Large Scale Visual Recognition ...
Ecology Neural Networks, Computer Humans Deep Learning Visual Perception Models, Neurological Pattern Recognition, Visual Brain Mapping Visual Cortex
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Predicting the fMRI Signal Fluctuation with Recurrent Neural Networks Trained on Vascular Network Dynamics.

Cerebral cortex (New York, N.Y. : 1991) Jan 5, 2021
Resting-state functional MRI (rs-fMRI) studies have revealed specific low-frequency hemodynamic signal fluctuations (<0.1 Hz) in the brain, which could be related to neuronal oscillations through the neurovascular coupling mechanism. Given the vascul...
Adult Animals Male Image Processing, Computer-Assisted Neural Networks, Computer Algorithms Female Young Adult Electroencephalography Rest Connectome Cerebrovascular Circulation Rats Magnetic Resonance Imaging Models, Neurological Brain Mapping Humans Blood Vessels Default Mode Network
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Quantitative Assessment of Resting-State for Mild Cognitive Impairment Detection: A Functional Near-Infrared Spectroscopy and Deep Learning Approach.

Journal of Alzheimer's disease : JAD Jan 1, 2021
BACKGROUND: Mild cognitive impairment (MCI) is considered a prodromal stage of Alzheimer's disease. Early diagnosis of MCI can allow for treatment to improve cognitive function and reduce modifiable risk factors.
Support Vector Machine Brain Mapping Discriminant Analysis Feasibility Studies Rest Neuroimaging Neural Pathways Male Spectroscopy, Near-Infrared Deep Learning Cognitive Dysfunction Reproducibility of Results Aged Aged, 80 and over Humans Neural Networks, Computer Machine Learning Algorithms Female
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in the Era of Artificial Intelligence.

Brain connectivity Oct 1, 2020
Neural Pathways Humans Artificial Intelligence Brain Image Processing, Computer-Assisted Brain Mapping Neuroimaging Connectome
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Computational framework for detection of subtypes of neuropsychiatric disorders based on DTI-derived anatomical connectivity.

The neuroradiology journal Oct 1, 2020
Many brain disorders - such as Alzheimer's disease, Parkinson's disease, schizophrenia and autism - are heterogeneous, that is, they may have several subtypes. Traditionally, clinicians have identified subtypes, such as subtypes of psychosis, using c...
Female Adult Male Image Processing, Computer-Assisted Brain Mapping Humans Neuroimaging Neural Pathways Machine Learning Diffusion Tensor Imaging Mental Disorders
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Large-Scale Structural Covariance Networks Predict Age in Middle-to-Late Adulthood: A Novel Brain Aging Biomarker.

Cerebral cortex (New York, N.Y. : 1991) Oct 1, 2020
The aging process is accompanied by changes in the brain's cortex at many levels. There is growing interest in summarizing these complex brain-aging profiles into a single, quantitative index that could serve as a biomarker both for characterizing in...
Male Aging Middle Aged Brain Mapping Female Aged Aged, 80 and over Humans Machine Learning Algorithms Brain
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Evaluating the Sensitivity of Resting-State BOLD Variability to Age and Cognition after Controlling for Motion and Cardiovascular Influences: A Network-Based Approach.

Cerebral cortex (New York, N.Y. : 1991) Oct 1, 2020
Recent functional magnetic resonance imaging (fMRI) studies report that moment-to-moment variability in the BOLD signal is related to differences in age and cognition and, thus, may be sensitive to age-dependent decline. However, head motion and/or c...
Humans Machine Learning Brain Female Motion Aged Body Mass Index Artifacts Magnetic Resonance Imaging Aged, 80 and over Aging Pulse Adult Brain Mapping Middle Aged Male Blood Pressure Image Processing, Computer-Assisted Cognition
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Porthole and Stormcloud: Tools for Visualisation of Spatiotemporal M/EEG Statistics.

Neuroinformatics Jun 1, 2020
Electro- and magneto-encephalography are functional neuroimaging modalities characterised by their ability to quantify dynamic spatiotemporal activity within the brain. However, the visualisation techniques used to illustrate these effects are curren...
Magnetoencephalography Humans Cross-Sectional Studies Machine Learning Brain Mapping Brain Electroencephalography Signal Processing, Computer-Assisted
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