AIMC Topic: Brain

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Predictive uncertainty in deep learning-based MR image reconstruction using deep ensembles: Evaluation on the fastMRI data set.

Magnetic resonance in medicine Jan 28, 2024
PURPOSE: To estimate pixel-wise predictive uncertainty for deep learning-based MR image reconstruction and to examine the impact of domain shifts and architecture robustness.
Humans Algorithms Databases, Factual Brain Deep Learning Magnetic Resonance Imaging Uncertainty Image Processing, Computer-Assisted
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DeepWMH: A deep learning tool for accurate white matter hyperintensity segmentation without requiring manual annotations for training.

Science bulletin Jan 28, 2024
Deep Learning Algorithms Brain White Matter
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Large-Scale Bio-Inspired FPGA Models for Path Planning.

IEEE transactions on biomedical circuits and systems Jan 26, 2024
The hippocampus provides significant inspiration for spatial navigation and memory in both humans and animals. Constructing large-scale spiking neural network (SNN) models based on the biological neural systems is an important approach to comprehend ...
Animals Neurons Algorithms Humans Brain Neural Networks, Computer
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Scalable Multi-Hierarchy Embedded Platform for Neural Population Simulations.

IEEE transactions on biomedical circuits and systems Jan 26, 2024
Brain-inspired structured neural circuits are the cornerstones of both computational and perceived intelligence. Real-time simulations of large-scale high-dimensional neural populations with complex nonlinearities pose a significant challenge. Taking...
Computer Simulation Computer Systems Neurons Neural Networks, Computer Brain
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Using deep learning to quantify neuronal activation from single-cell and spatial transcriptomic data.

Nature communications Jan 26, 2024
Neuronal activity-dependent transcription directs molecular processes that regulate synaptic plasticity, brain circuit development, behavioral adaptation, and long-term memory. Single cell RNA-sequencing technologies (scRNAseq) are rapidly developing...
Neurons Mice Neuronal Plasticity Male Brain Gene Expression Profiling Animals Deep Learning
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Decoding Single and Paired Phonemes Using 7T Functional MRI.

Brain topography Jan 23, 2024
Several studies have shown that mouth movements related to the pronunciation of individual phonemes are represented in the sensorimotor cortex. This would theoretically allow for brain computer interfaces that are capable of decoding continuous speec...
Brain Female Adult Male Young Adult Humans Brain-Computer Interfaces Phonetics Magnetic Resonance Imaging Speech Sensorimotor Cortex Brain Mapping Support Vector Machine
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Rule-based deep learning method for prognosis of neonatal hypoxic-ischemic encephalopathy by using susceptibility weighted image analysis.

Magma (New York, N.Y.) Jan 22, 2024
OBJECTIVE: Susceptibility weighted imaging (SWI) of neonatal hypoxic-ischemic brain injury can provide assistance in the prognosis of neonatal hypoxic-ischemic encephalopathy (HIE). We propose a convolutional neural network model to classify SWI imag...
Datasets as Topic Hypoxia-Ischemia, Brain Child, Preschool Magnetic Resonance Imaging Brain Prognosis Infant, Newborn Deep Learning Humans
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Connectome-based reservoir computing with the conn2res toolbox.

Nature communications Jan 22, 2024
The connection patterns of neural circuits form a complex network. How signaling in these circuits manifests as complex cognition and adaptive behaviour remains the central question in neuroscience. Concomitant advances in connectomics and artificial...
Adaptation, Psychological Cognition Connectome Artificial Intelligence Brain
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Multiple Classification of Brain MRI Autism Spectrum Disorder by Age and Gender Using Deep Learning.

Journal of medical systems Jan 22, 2024
The fact that the rapid and definitive diagnosis of autism cannot be made today and that autism cannot be treated provides an impetus to look into novel technological solutions. To contribute to the resolution of this problem through multiple classif...
Brain Deep Learning Magnetic Resonance Imaging Humans Autism Spectrum Disorder Neuroimaging
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Unsupervised deep learning with convolutional neural networks for static parallel transmit design: A retrospective study.

Magnetic resonance in medicine Jan 21, 2024
PURPOSE: To mitigate inhomogeneity at 7T for multi-channel transmit arrays using unsupervised deep learning with convolutional neural networks (CNNs).
Retrospective Studies Deep Learning Neural Networks, Computer Humans Magnetic Resonance Imaging Brain
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