AIMC Topic: Action Potentials

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Strategies to Decipher Neuron Identity from Extracellular Recordings in Behaving Nonhuman Primates.

The Journal of neuroscience : the official journal of the Society for Neuroscience Aug 6, 2025
Identification of the neuron type is critical when using extracellular recordings in awake, behaving animal subjects to understand computation in neural circuits. Yet, modern recording probes have limited power to resolve neuron identity. Here, we pr...
Pursuit, Smooth Wakefulness Macaca mulatta Male Deep Learning Neurons Cerebellum Action Potentials Animals
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A multisynaptic spiking neuron for simultaneously encoding spatiotemporal dynamics.

Nature communications Aug 4, 2025
Spiking neural networks (SNNs) are biologically more plausible and computationally more powerful than artificial neural networks due to their intrinsic temporal dynamics. However, vanilla spiking neurons struggle to simultaneously encode spatiotempor...
Algorithms Animals Spatio-Temporal Analysis Humans Neural Networks, Computer Neurons Axons Synapses Models, Neurological Action Potentials
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Spiking dynamics of individual neurons reflect changes in the structure and function of neuronal networks.

Nature communications Jul 30, 2025
Brain networks exhibit diverse topological structures to adapt and support brain functions. The changes in neuronal network architecture can lead to alterations in neuronal spiking activity, yet how individual neuronal behavior reflects network struc...
Models, Neurological Humans Action Potentials Brain Nerve Net Animals Neurons Fractals
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Manipulation of neuronal activity by an artificial spiking neural network implemented on a closed-loop brain-computer interface in non-human primates.

Journal of neural engineering Jul 21, 2025
Closed-loop brain-computer interfaces can be used to bridge, modulate, or repair damaged connections within the brain to restore functional deficits. Towards this goal, we demonstrate that small artificial spiking neural networks can be bidirectional...
Neural Networks, Computer Male Action Potentials Animals Motor Cortex Neurons Macaca mulatta Brain-Computer Interfaces
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Variability in reported midpoints of (in)activation of cardiac INa.

The Journal of general physiology Jul 16, 2025
Electrically active cells like cardiomyocytes show variability in their size, shape, and electrical activity. But should we expect variability in the properties of their ionic currents? In this meta-analysis, we gather and visualize measurements of t...
Animals Action Potentials Sodium Humans Myocytes, Cardiac Sodium Channels
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Biologically-informed excitatory and inhibitory ratio for robust spiking neural network training.

Scientific reports Jul 10, 2025
Spiking neural networks drawing inspiration from biological constraints of the brain promise an energy-efficient paradigm for artificial intelligence. However, challenges exist in identifying guiding principles to train these networks in a robust fas...
Animals Models, Neurological Neurons Nerve Net Action Potentials Humans Neural Networks, Computer
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BN-SNN: Spiking neural networks with bistable neurons for object detection.

PloS one Jul 10, 2025
Spiking neural networks (SNNs) are emerging as a promising evolution in neural network paradigms, offering an alternative to conventional convolutional neural networks (CNNs). One of the most effective methods for SNN development is the CNN-to-SNN co...
Algorithms Models, Neurological Action Potentials Humans Neural Networks, Computer Neurons
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Stable recurrent dynamics in heterogeneous neuromorphic computing systems using excitatory and inhibitory plasticity.

Nature communications Jul 1, 2025
Many neural computations emerge from self-sustained patterns of activity in recurrent neural circuits, which rely on balanced excitation and inhibition. Neuromorphic electronic circuits represent a promising approach for implementing the brain's comp...
Nerve Net Models, Neurological Action Potentials Neurons Humans Animals Neural Networks, Computer Neuronal Plasticity Brain
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Neurons throughout the brain embed robust signatures of their anatomical location into spike trains.

eLife Jun 27, 2025
Neurons in the brain are known to encode diverse information through their spiking activity, primarily reflecting external stimuli and internal states. However, whether individual neurons also embed information about their own anatomical location wit...
Mice Models, Neurological Machine Learning Animals Mice, Inbred C57BL Brain Action Potentials Neurons Male
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Predictive learning rules generate a cortical-like replay of probabilistic sensory experiences.

eLife Jun 16, 2025
The brain is thought to construct an optimal internal model representing the probabilistic structure of the environment accurately. Evidence suggests that spontaneous brain activity gives such a model by cycling through activity patterns evoked by pr...
Cerebral Cortex Models, Neurological Learning Macaca mulatta Nerve Net Animals Action Potentials Neurons
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