AIMC Topic: Action Potentials

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Distributed Synaptic Connection Strength Changes Dynamics in a Population Firing Rate Model in Response to Continuous External Stimuli.

Neural computation Apr 17, 2025
Neural network complexity allows for diverse neuronal population dynamics and realizes higherorder brain functions such as cognition and memory. Complexity is enhanced through chemical synapses with exponentially decaying conductance and greater vari...
Animals Neuronal Plasticity Models, Neurological Neural Networks, Computer Computer Simulation Humans Synapses Nerve Net Primary Visual Cortex Action Potentials Neurons
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Elucidating the Theoretical Underpinnings of Surrogate Gradient Learning in Spiking Neural Networks.

Neural computation Apr 17, 2025
Training spiking neural networks to approximate universal functions is essential for studying information processing in the brain and for neuromorphic computing. Yet the binary nature of spikes poses a challenge for direct gradient-based training. Su...
Neurons Stochastic Processes Humans Neural Networks, Computer Models, Neurological Action Potentials Learning
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The Leaky Integrate-and-Fire Neuron Is a Change-Point Detector for Compound Poisson Processes.

Neural computation Apr 17, 2025
Animal nervous systems can detect changes in their environments within hundredths of a second. They do so by discerning abrupt shifts in sensory neural activity. Many neuroscience studies have employed change-point detection (CPD) algorithms to estim...
Humans Neural Networks, Computer Algorithms Poisson Distribution Neurons Membrane Potentials Models, Neurological Action Potentials Animals
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Spiking Neuron-Astrocyte Networks for Image Recognition.

Neural computation Mar 18, 2025
From biological and artificial network perspectives, researchers have started acknowledging astrocytes as computational units mediating neural processes. Here, we propose a novel biologically inspired neuron-astrocyte network model for image recognit...
Astrocytes Neurons Nerve Net Models, Neurological Action Potentials Neural Networks, Computer Animals Humans
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Toward a Free-Response Paradigm of Decision Making in Spiking Neural Networks.

Neural computation Feb 14, 2025
Spiking neural networks (SNNs) have attracted significant interest in the development of brain-inspired computing systems due to their energy efficiency and similarities to biological information processing. In contrast to continuous-valued artificia...
Reaction Time Neurons Models, Neurological Action Potentials Decision Making Neural Networks, Computer Animals Humans
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Intelligent Control to Suppress Epileptic Seizures in the Amygdala: In Silico Investigation Using a Network of Izhikevich Neurons.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Jan 1, 2025
Closed-loop electricalstimulation of brain structures is one of the most promising techniques to suppress epileptic seizures in drug-resistant refractory patients who are also ineligible to ablative neurosurgery. In this work, an intelligent controll...
Neural Networks, Computer Neurons Algorithms Nonlinear Dynamics Action Potentials Humans Amygdala Seizures Nerve Net Electroencephalography Computer Simulation Epilepsy Models, Neurological
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Fault-tolerant neural networks from biological error correction codes.

Physical review. E Nov 1, 2024
It has been an open question in deep learning if fault-tolerant computation is possible: can arbitrarily reliable computation be achieved using only unreliable neurons? In the grid cells of the mammalian cortex, analog error correction codes have bee...
Action Potentials Neurons Neural Networks, Computer Animals Models, Neurological
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Trainable Reference Spikes Improve Temporal Information Processing of SNNs With Supervised Learning.

Neural computation Sep 17, 2024
Spiking neural networks (SNNs) are the next-generation neural networks composed of biologically plausible neurons that communicate through trains of spikes. By modifying the plastic parameters of SNNs, including weights and time delays, SNNs can be t...
Supervised Machine Learning Neural Networks, Computer Time Factors Neurons Humans Models, Neurological Action Potentials
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Inference on the Macroscopic Dynamics of Spiking Neurons.

Neural computation Sep 17, 2024
The process of inference on networks of spiking neurons is essential to decipher the underlying mechanisms of brain computation and function. In this study, we conduct inference on parameters and dynamics of a mean-field approximation, simplifying th...
Humans Animals Models, Neurological Bayes Theorem Neural Networks, Computer Action Potentials Algorithms Neurons
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Comparison of Regression Methods to Predict the First Spike Latency in Response to an External Stimulus in Intracellular Recordings for Cerebellar Cells.

Studies in health technology and informatics Aug 22, 2024
The significance of intracellular recording in neurophysiology is emphasized in this article, with considering the functions of neurons, particularly the role of first spike latency in response to external stimuli. The study employs advanced machine ...
Neurons Cerebellum Machine Learning Action Potentials Models, Neurological Animals Regression Analysis
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