AIMC Topic: Action Potentials

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Linking cellular-level phenomena to brain architecture: the case of spiking cerebellar controllers.

Neural networks : the official journal of the International Neural Network Society Apr 23, 2025
Linking cellular-level phenomena to brain architecture and behavior is a holy grail for theoretical and computational neuroscience. Advances in neuroinformatics have recently allowed scientists to embed spiking neural networks of the cerebellum with ...
Humans Animals Neuronal Plasticity Models, Neurological Neural Networks, Computer Algorithms Learning Cerebellum Nerve Net Action Potentials Neurons
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Heterogeneous quantization regularizes spiking neural network activity.

Scientific reports Apr 23, 2025
The learning and recognition of object features from unregulated input has been a longstanding challenge for artificial intelligence systems. Brains, on the other hand, are adept at learning stable sensory representations given noisy observations, a ...
Neural Networks, Computer Animals Models, Neurological Action Potentials Neurons Nerve Net Humans
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SpikeCLIP: A contrastive language-image pretrained spiking neural network.

Neural networks : the official journal of the International Neural Network Society Apr 19, 2025
Spiking Neural Networks (SNNs) have emerged as a promising alternative to conventional Artificial Neural Networks (ANNs), demonstrating comparable performance in both visual and linguistic tasks while offering the advantage of improved energy efficie...
Neural Networks, Computer Models, Neurological Humans Action Potentials Algorithms Neurons Language
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Toward a Biologically Plausible SNN-Based Associative Memory with Context-Dependent Hebbian Connectivity.

International journal of neural systems Apr 16, 2025
In this paper, we propose a spiking neural network model with Hebbian connectivity for implementing energy-efficient associative memory, whose activity is determined by input stimuli. The model consists of three interacting layers of Hodgkin-Huxley-M...
Humans Neural Networks, Computer Synapses Models, Neurological Memory Action Potentials Association Learning Neurons
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Event-based optical flow on neuromorphic processor: ANN vs. SNN comparison based on activation sparsification.

Neural networks : the official journal of the International Neural Network Society Apr 7, 2025
Spiking neural networks (SNNs) for event-based optical flow are claimed to be computationally more efficient than their artificial neural networks (ANNs) counterparts, but a fair comparison is missing in the literature. In this work, we propose an ev...
Neurons Neural Networks, Computer Algorithms Action Potentials
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ECG-based heart arrhythmia classification using feature engineering and a hybrid stacked machine learning.

BMC cardiovascular disorders Apr 7, 2025
A heart arrhythmia refers to a set of conditions characterized by irregular heart- beats, with an increasing mortality rate in recent years. Regular monitoring is essential for effective management, as early detection and timely treatment greatly imp...
Predictive Value of Tests Signal Processing, Computer-Assisted Arrhythmias, Cardiac Heart Rate Diagnosis, Computer-Assisted Electrocardiography Action Potentials Algorithms Reproducibility of Results Humans Machine Learning
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Finger Vein Recognition Based on Unsupervised Spiking Convolutional Neural Network with Adaptive Firing Threshold.

Sensors (Basel, Switzerland) Apr 3, 2025
Currently, finger vein recognition (FVR) stands as a pioneering biometric technology, with convolutional neural networks (CNNs) and Transformers, among other advanced deep neural networks (DNNs), consistently pushing the boundaries of recognition acc...
Action Potentials Neurons Deep Learning Fingers Convolutional Neural Networks Veins Humans Support Vector Machine Neural Networks, Computer Algorithms
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RRAM-Based Spiking Neural Network With Target-Modulated Spike-Timing-Dependent Plasticity.

IEEE transactions on biomedical circuits and systems Apr 2, 2025
The spiking neural network (SNN) training with spike timing-dependent plasticity (STDP) for image classification usually requires a lot of neurons to extract representative features and(or) needs an external classifier. Conventional bio-inspired lear...
Action Potentials Neurons Algorithms Neuronal Plasticity Models, Neurological Humans Neural Networks, Computer
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GraphDeep-hERG: Graph Neural Network PharmacoAnalytics for Assessing hERG-Related Cardiotoxicity.

Pharmaceutical research Mar 26, 2025
PURPOSE: The human Ether-a-go-go Related-Gene (hERG) encodes rectifying potassium channels that play a significant role during action potential repolarization of cardiomyocytes. Blockade of the hERG channel by off-target drugs can lead to long QT syn...
Deep Learning Ether-A-Go-Go Potassium Channels Humans Graph Neural Networks Potassium Channel Blockers Machine Learning Action Potentials Neural Networks, Computer ERG1 Potassium Channel Algorithms Cardiotoxicity Computer Simulation
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Phase of firing does not reflect temporal order in sequence memory of humans and recurrent neural networks.

Nature neuroscience Mar 24, 2025
The temporal order of a sequence of events has been thought to be reflected in the ordered firing of neurons at different phases of theta oscillations. Here we assess this by measuring single neuron activity (1,420 neurons) and local field potentials...
Theta Rhythm Neural Networks, Computer Recurrent Neural Networks Female Epilepsy Humans Young Adult Memory, Short-Term Nerve Net Adult Neurons Temporal Lobe Male Action Potentials
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