AIMC Topic: Neurons

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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...
Neural Networks, Computer Computer Simulation Animals Humans Nerve Net Primary Visual Cortex Action Potentials Neuronal Plasticity Neurons Models, Neurological Synapses
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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...
Action Potentials Neurons Stochastic Processes Neural Networks, Computer Learning Humans Models, Neurological
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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...
Poisson Distribution Humans Neurons Membrane Potentials Animals Neural Networks, Computer Models, Neurological Algorithms Action Potentials
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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...
Animals Models, Neurological Action Potentials Astrocytes Neurons Nerve Net Humans Neural Networks, Computer
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Learning in Wilson-Cowan Model for Metapopulation.

Neural computation Mar 18, 2025
The Wilson-Cowan model for metapopulation, a neural mass network model, treats different subcortical regions of the brain as connected nodes, with connections representing various types of structural, functional, or effective neuronal connectivity be...
Models, Neurological Algorithms Neurons Humans Brain Nerve Net Neural Networks, Computer Learning
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Active Inference and Intentional Behavior.

Neural computation Mar 18, 2025
Recent advances in theoretical biology suggest that key definitions of basal cognition and sentient behavior may arise as emergent properties of in vitro cell cultures and neuronal networks. Such neuronal networks reorganize activity to demonstrate s...
Models, Neurological Neurons Intention Computer Simulation Animals Cognition Nerve Net Behavior Humans Neural Networks, Computer Machine Learning
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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...
Decision Making Reaction Time Neurons Models, Neurological Action Potentials Humans Neural Networks, Computer Animals
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Improving Recall in Sparse Associative Memories That Use Neurogenesis.

Neural computation Feb 14, 2025
The creation of future low-power neuromorphic solutions requires specialist spiking neural network (SNN) algorithms that are optimized for neuromorphic settings. One such algorithmic challenge is the ability to recall learned patterns from their nois...
Humans Neural Networks, Computer Algorithms Animals Models, Neurological Neurons Memory Association Learning Neurogenesis Mental Recall
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Contrastive Neuron Pruning for Backdoor Defense.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society Jan 1, 2025
Recent studies have revealed that deep neural networks (DNNs) are susceptible to backdoor attacks, in which attackers insert a pre-defined backdoor into a DNN model by poisoning a few training samples. A small subset of neurons in DNN is responsible ...
Image Processing, Computer-Assisted Neurons Humans Algorithms Neural Networks, Computer Animals Deep Learning
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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...
Humans Epilepsy Neural Networks, Computer Nonlinear Dynamics Models, Neurological Seizures Nerve Net Action Potentials Neurons Algorithms Amygdala Electroencephalography Computer Simulation
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