AIMC Topic: Nerve Net

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A multi-domain feature fusion epilepsy seizure detection method based on spike matching and PLV functional networks.

Journal of neural engineering Feb 5, 2025
The identification of spikes, as a typical characteristic wave of epilepsy, is crucial for diagnosing and locating the epileptogenic region. The traditional seizure detection methods lack spike features and have low sample richness. This paper propos...
Humans Epilepsy Seizures Nerve Net Neural Networks, Computer Action Potentials Electroencephalography
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Schizophrenia recognition based on three-dimensional adaptive graph convolutional neural network.

Scientific reports Feb 3, 2025
Previous deep learning-based brain network research has made significant progress in understanding the pathophysiology of schizophrenia. However, it ignores the three-dimensional spatial characteristics of EEG signals and cannot dynamically learn the...
Models, Neurological Electroencephalography Schizophrenia Adult Male Convolutional Neural Networks Nerve Net Graph Neural Networks Humans Algorithms Female
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Hybrid neural networks for continual learning inspired by corticohippocampal circuits.

Nature communications Feb 2, 2025
Current artificial systems suffer from catastrophic forgetting during continual learning, a limitation absent in biological systems. Biological mechanisms leverage the dual representation of specific and generalized memories within corticohippocampal...
Neural Networks, Computer Learning Animals Humans Cerebral Cortex Models, Neurological Nerve Net Neurons Memory Hippocampus
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Temporal pavlovian conditioning of a model spiking neural network for discrimination sequences of short time intervals.

Journal of computational neuroscience Feb 1, 2025
The brain's ability to learn and distinguish rapid sequences of events is essential for timing-dependent tasks, such as those in sports and music. However, the mechanisms underlying this ability remain an active area of research. Here, we present a P...
Time Perception Discrimination, Psychological Neurons Nerve Net Humans Conditioning, Classical Neural Networks, Computer Time Factors Animals Models, Neurological Action Potentials
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DSAM: A deep learning framework for analyzing temporal and spatial dynamics in brain networks.

Medical image analysis Jan 29, 2025
Resting-state functional magnetic resonance imaging (rs-fMRI) is a noninvasive technique pivotal for understanding human neural mechanisms of intricate cognitive processes. Most rs-fMRI studies compute a single static functional connectivity matrix a...
Male Brain Female Deep Learning Adult Magnetic Resonance Imaging Connectome Humans Nerve Net Neural Networks, Computer
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Recurrent neural networks with transient trajectory explain working memory encoding mechanisms.

Communications biology Jan 28, 2025
Whether working memory (WM) is encoded by persistent activity using attractors or by dynamic activity using transient trajectories has been debated for decades in both experimental and modeling studies, and a consensus has not been reached. Even thou...
Memory, Short-Term Nerve Net Recurrent Neural Networks Neural Networks, Computer Humans Animals Models, Neurological
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Identifying multilayer network hub by graph representation learning.

Medical image analysis Jan 16, 2025
The recent advances in neuroimaging technology allow us to understand how the human brain is wired in vivo and how functional activity is synchronized across multiple regions. Growing evidence shows that the complexity of the functional connectivity ...
Brain Mapping Connectome Nerve Net Algorithms Brain Magnetic Resonance Imaging Humans Machine Learning
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Characterizing brain network alterations in cervical spondylotic myelopathy using static and dynamic functional network connectivity and machine learning.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia Jan 16, 2025
BACKGROUND: Cervical spondylotic myelopathy (CSM) is a debilitating condition that affects the cervical spine, leading to neurological impairments. While the neural mechanisms underlying CSM remain poorly understood, changes in brain network connecti...
Humans Machine Learning Brain Cervical Vertebrae Nerve Net Spinal Cord Diseases Spondylosis Male Middle Aged Magnetic Resonance Imaging Female Aged Adult
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Random noise promotes slow heterogeneous synaptic dynamics important for robust working memory computation.

Proceedings of the National Academy of Sciences of the United States of America Jan 16, 2025
Recurrent neural networks (RNNs) based on model neurons that communicate via continuous signals have been widely used to study how cortical neural circuits perform cognitive tasks. Training such networks to perform tasks that require information main...
Neurons Synapses Nerve Net Cognition Models, Neurological Memory, Short-Term Animals Prefrontal Cortex Humans Neural Networks, Computer
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Exploring continual learning strategies in artificial neural networks through graph-based analysis of connectivity: Insights from a brain-inspired perspective.

Neural networks : the official journal of the International Neural Network Society Jan 15, 2025
Artificial Neural Networks (ANNs) aim at mimicking information processing in biological networks. In cognitive neuroscience, graph modeling is a powerful framework widely used to study brain structural and functional connectivity. Yet, the extension ...
Learning Models, Neurological Humans Nerve Net Neural Networks, Computer Brain
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