AIMC Topic: Brain
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Learning sequence attractors in recurrent networks with hidden neurons.
Neural networks : the official journal of the International Neural Network Society
Jun 22, 2024
The brain is targeted for processing temporal sequence information. It remains largely unclear how the brain learns to store and retrieve sequence memories. Here, we study how recurrent networks of binary neurons learn sequence attractors to store pr...
Siamese Graph Convolutional Network quantifies increasing structure-function discrepancy over the cognitive decline continuum.
Computer methods and programs in biomedicine
Jun 22, 2024
BACKGROUND AND OBJECTIVE: Alzheimer's disease dementia (ADD) is well known to induce alterations in both structural and functional brain connectivity. However, reported changes in connectivity are mostly limited to global/local network features, whic...
Assessment of Deep Learning-Based Triage Application for Acute Ischemic Stroke on Brain MRI in the ER.
Academic radiology
Jun 21, 2024
RATIONALE AND OBJECTIVES: To assess a deep learning application (DLA) for acute ischemic stroke (AIS) detection on brain magnetic resonance imaging (MRI) in the emergency room (ER) and the effect of T2-weighted imaging (T2WI) on its performance.
On convergence properties of the brain-state-in-a-convex-domain.
Neural networks : the official journal of the International Neural Network Society
Jun 21, 2024
Convergence in the presence of multiple equilibrium points is one of the most fundamental dynamical properties of a neural network (NN). Goal of the paper is to investigate convergence for the classic Brain-State-in-a-Box (BSB) NN model and some of i...
Spontaneous brain activity in patients with central retinal artery occlusion: a resting-state functional MRI study using machine learning.
Neuroreport
Jun 21, 2024
Central retinal artery occlusion (CRAO) is a serious eye condition that poses a risk to vision, resulting from the blockage of the central retinal artery. Because of the anatomical connection between the ocular artery, which derives from the internal...
Insights into traditional Large Deformation Diffeomorphic Metric Mapping and unsupervised deep-learning for diffeomorphic registration and their evaluation.
Computers in biology and medicine
Jun 21, 2024
This paper explores the connections between traditional Large Deformation Diffeomorphic Metric Mapping methods and unsupervised deep-learning approaches for non-rigid registration, particularly emphasizing diffeomorphic registration. The study provid...
Multivariate modeling and prediction of cerebral physiology in acute traumatic neural injury: A scoping review.
Computers in biology and medicine
Jun 20, 2024
Traumatic brain injury (TBI) poses a significant global public health challenge necessitating a profound understanding of cerebral physiology. The dynamic nature of TBI demands sophisticated methodologies for modeling and predicting cerebral signals ...
The intelligent imaging revolution: artificial intelligence in MRI and MRS acquisition and reconstruction.
Magma (New York, N.Y.)
Jun 20, 2024
Machine learning of dissection photographs and surface scanning for quantitative 3D neuropathology.
eLife
Jun 19, 2024
We present open-source tools for three-dimensional (3D) analysis of photographs of dissected slices of human brains, which are routinely acquired in brain banks but seldom used for quantitative analysis. Our tools can: (1) 3D reconstruct a volume fro...
Super-resolution Deep Learning Reconstruction for 3D Brain MR Imaging: Improvement of Cranial Nerve Depiction and Interobserver Agreement in Evaluations of Neurovascular Conflict.
Academic radiology
Jun 18, 2024
RATIONALE AND OBJECTIVES: To determine if super-resolution deep learning reconstruction (SR-DLR) improves the depiction of cranial nerves and interobserver agreement when assessing neurovascular conflict in 3D fast asymmetric spin echo (3D FASE) brai...
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