AIMC Topic: Neuronal Plasticity

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Towards realistic simulation of disease progression in the visual cortex with CNNs.

Scientific reports Feb 19, 2025
Convolutional neural networks (CNNs) and mammalian visual systems share architectural and information processing similarities. We leverage these parallels to develop an in-silico CNN model simulating diseases affecting the visual system. This model a...
Alzheimer Disease Visual Cortex Disease Progression Neuronal Plasticity Models, Neurological Humans Neural Networks, Computer Computer Simulation
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Clinical efficacy of NIBS in enhancing neuroplasticity for stroke recovery.

Journal of neuroscience methods Feb 18, 2025
BACKGROUND: For stroke patients, a therapeutic approach named Non-invasive brain stimulation (NIBS) was applied and it has gained attention. This NIBS approach enhances the neuroplasticity and facilitates in functional Stroke Rehabilitation (SR) thro...
Adult Male Middle Aged Brain Female Aged Stroke Stroke Rehabilitation Transcranial Direct Current Stimulation Transcranial Magnetic Stimulation Treatment Outcome Neuronal Plasticity Recovery of Function Humans Machine Learning
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CDNA-SNN: A New Spiking Neural Network for Pattern Classification Using Neuronal Assemblies.

IEEE transactions on neural networks and learning systems Feb 6, 2025
Spiking neural networks (SNNs) mimic their biological counterparts more closely than their predecessors and are considered the third generation of artificial neural networks. It has been proven that networks of spiking neurons have a higher computati...
Action Potentials Neurons Pattern Recognition, Automated Humans Neuronal Plasticity Models, Neurological Neural Networks, Computer Algorithms
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Memory-Dependent Computation and Learning in Spiking Neural Networks Through Hebbian Plasticity.

IEEE transactions on neural networks and learning systems Feb 6, 2025
Spiking neural networks (SNNs) are the basis for many energy-efficient neuromorphic hardware systems. While there has been substantial progress in SNN research, artificial SNNs still lack many capabilities of their biological counterparts. In biologi...
Humans Neural Networks, Computer Machine Learning Models, Neurological Action Potentials Neurons Memory Computer Simulation Learning Neuronal Plasticity
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The calcitron: A simple neuron model that implements many learning rules via the calcium control hypothesis.

PLoS computational biology Jan 29, 2025
Theoretical neuroscientists and machine learning researchers have proposed a variety of learning rules to enable artificial neural networks to effectively perform both supervised and unsupervised learning tasks. It is not always clear, however, how t...
Synapses Learning Animals Computational Biology Neurons Calcium Neuronal Plasticity Models, Neurological Humans Neural Networks, Computer Machine Learning
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Neural mechanisms of relational learning and fast knowledge reassembly in plastic neural networks.

Nature neuroscience Jan 15, 2025
Humans and animals have a striking ability to learn relationships between items in experience (such as stimuli, objects and events), enabling structured generalization and rapid assimilation of new information. A fundamental type of such relational l...
Models, Neurological Neurons Nerve Net Knowledge Learning Animals Neuronal Plasticity Humans Neural Networks, Computer
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Intrinsic plasticity coding improved spiking actor network for reinforcement learning.

Neural networks : the official journal of the International Neural Network Society Dec 19, 2024
Deep reinforcement learning (DRL) exploits the powerful representational capabilities of deep neural networks (DNNs) and has achieved significant success. However, compared to DNNs, spiking neural networks (SNNs), which operate on binary signals, mor...
Deep Learning Action Potentials Humans Neuronal Plasticity Neurons Neural Networks, Computer Models, Neurological Reinforcement, Psychology Computer Simulation
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Metaplasticity-Enabled Graphene Quantum Dot Devices for Mitigating Catastrophic Forgetting in Artificial Neural Networks.

Advanced materials (Deerfield Beach, Fla.) Dec 8, 2024
The limitations of deep neural networks in continuous learning stem from oversimplifying the complexities of biological neural circuits, often neglecting the dynamic balance between memory stability and learning plasticity. In this study, artificial ...
Quantum Dots Neural Networks, Computer Graphite Deep Learning Neuronal Plasticity
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Stabilizing sequence learning in stochastic spiking networks with GABA-Modulated STDP.

Neural networks : the official journal of the International Neural Network Society Dec 7, 2024
Cortical networks are capable of unsupervised learning and spontaneous replay of complex temporal sequences. Endowing artificial spiking neural networks with similar learning abilities remains a challenge. In particular, it is unresolved how differen...
Neurons gamma-Aminobutyric Acid Stochastic Processes Neuronal Plasticity Models, Neurological Humans Action Potentials Neural Networks, Computer Learning
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Effectiveness of unilateral lower-limb exoskeleton robot on balance and gait recovery and neuroplasticity in patients with subacute stroke: a randomized controlled trial.

Journal of neuroengineering and rehabilitation Dec 5, 2024
BACKGROUND: Impaired balance and gait in stroke survivors are associated with decreased functional independence. This study aimed to evaluate the effectiveness of unilateral lower-limb exoskeleton robot-assisted overground gait training compared with...
Humans Lower Extremity Recovery of Function Female Robotics Stroke Gait Postural Balance Middle Aged Single-Blind Method Aged Treatment Outcome Adult Exoskeleton Device Neuronal Plasticity Male Stroke Rehabilitation Gait Disorders, Neurologic
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