AIMC Topic: Action Potentials

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Self-Lateral Propagation Elevates Synaptic Modifications in Spiking Neural Networks for the Efficient Spatial and Temporal Classification.

IEEE transactions on neural networks and learning systems Oct 29, 2024
The brain's mystery for efficient and intelligent computation hides in the neuronal encoding, functional circuits, and plasticity principles in natural neural networks. However, many plasticity principles have not been fully incorporated into artific...
Humans Neural Networks, Computer Algorithms Neurons Neuronal Plasticity Synapses Nerve Net Models, Neurological Action Potentials
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Brain-wide neural recordings in mice navigating physical spaces enabled by robotic neural recording headstages.

Nature methods Oct 7, 2024
Technologies that can record neural activity at cellular resolution at multiple spatial and temporal scales are typically much larger than the animals that are being recorded from and are thus limited to recording from head-fixed subjects. Here we ha...
Robotics Neurons Head Brain Mice Animals Action Potentials Male Mice, Inbred C57BL
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Pattern recognition using spiking antiferromagnetic neurons.

Scientific reports Sep 27, 2024
Spintronic devices offer a promising avenue for the development of nanoscale, energy-efficient artificial neurons for neuromorphic computing. It has previously been shown that with antiferromagnetic (AFM) oscillators, ultra-fast spiking artificial ne...
Neurons Pattern Recognition, Automated Algorithms Models, Neurological Action Potentials Humans Neural Networks, Computer Machine Learning
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Neuromorphic intermediate representation: A unified instruction set for interoperable brain-inspired computing.

Nature communications Sep 16, 2024
Spiking neural networks and neuromorphic hardware platforms that simulate neuronal dynamics are getting wide attention and are being applied to many relevant problems using Machine Learning. Despite a well-established mathematical foundation for neur...
Computer Simulation Machine Learning Models, Neurological Software Action Potentials Brain Neurons Humans Neural Networks, Computer
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Deep brain stimulation and lag synchronization in a memristive two-neuron network.

Neural networks : the official journal of the International Neural Network Society Sep 10, 2024
In the pursuit of potential treatments for neurological disorders and the alleviation of patient suffering, deep brain stimulation (DBS) has been utilized to intervene or investigate pathological neural activities. To explore the exact mechanism of h...
Neuronal Plasticity Models, Neurological Humans Synapses Neurons Action Potentials Neural Networks, Computer Deep Brain Stimulation Computer Simulation Nonlinear Dynamics
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A multiscale distributed neural computing model database (NCMD) for neuromorphic architecture.

Neural networks : the official journal of the International Neural Network Society Sep 10, 2024
Distributed neuromorphic architecture is a promising technique for on-chip processing of multiple tasks. Deploying the constructed model in a distributed neuromorphic system, however, remains time-consuming and challenging due to considerations such ...
Brain Neural Networks, Computer Humans Action Potentials Computer Simulation Artificial Intelligence Neurons Models, Neurological Databases, Factual Synapses
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Dissociative and prioritized modeling of behaviorally relevant neural dynamics using recurrent neural networks.

Nature neuroscience Sep 6, 2024
Understanding the dynamical transformation of neural activity to behavior requires new capabilities to nonlinearly model, dissociate and prioritize behaviorally relevant neural dynamics and test hypotheses about the origin of nonlinearity. We present...
Action Potentials Neurons Nonlinear Dynamics Male Models, Neurological Nerve Net Neural Networks, Computer Animals
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Backpropagation-Based Learning Techniques for Deep Spiking Neural Networks: A Survey.

IEEE transactions on neural networks and learning systems Sep 3, 2024
With the adoption of smart systems, artificial neural networks (ANNs) have become ubiquitous. Conventional ANN implementations have high energy consumption, limiting their use in embedded and mobile applications. Spiking neural networks (SNNs) mimic ...
Machine Learning Algorithms Animals Humans Neural Networks, Computer Models, Neurological Deep Learning Action Potentials Image Processing, Computer-Assisted Neurons
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Delay learning based on temporal coding in Spiking Neural Networks.

Neural networks : the official journal of the International Neural Network Society Aug 31, 2024
Spiking Neural Networks (SNNs) hold great potential for mimicking the brain's efficient processing of information. Although biological evidence suggests that precise spike timing is crucial for effective information encoding, contemporary SNN researc...
Humans Models, Neurological Algorithms Learning Neural Networks, Computer Action Potentials Time Factors Neurons
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A Federated Learning Protocol for Spiking Neural Membrane Systems.

International journal of neural systems Aug 30, 2024
Although deep learning models have shown promising results in solving problems related to image recognition or natural language processing, they do not match how the biological brain works. Some of the differences include the amount of energy consume...
Models, Neurological Action Potentials Neurons Algorithms Deep Learning Humans Neural Networks, Computer Machine Learning
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