AIMC Topic: Models, Neurological

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STSF: Spiking Time Sparse Feedback Learning for Spiking Neural Networks.

IEEE transactions on neural networks and learning systems Jun 1, 2025
Spiking neural networks (SNNs) are biologically plausible models known for their computational efficiency. A significant advantage of SNNs lies in the binary information transmission through spike trains, eliminating the need for multiplication opera...
Neurons Feedback Animals Time Factors Neuronal Plasticity Models, Neurological Action Potentials Machine Learning Humans Algorithms Neural Networks, Computer Computer Simulation
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Metaplasticity and continual learning: mechanisms subserving brain computer interface proficiency.

Journal of neural engineering May 23, 2025
Brain computer interfaces (BCIs) require substantial cognitive flexibility to optimize control performance. Remarkably, learning this control is rapid, suggesting it might be mediated by neuroplasticity mechanisms operating on very short time scales....
Models, Neurological Male Mice, Inbred C57BL Learning Mice, Transgenic Brain-Computer Interfaces Mice Animals Neuronal Plasticity Optogenetics
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Unsupervised post-training learning in spiking neural networks.

Scientific reports May 21, 2025
The human brain is a dynamic system that is constantly learning. It employs a combination of various learning strategies to facilitate complex learning processes. However, implementing biological learning mechanisms into Spiking Neural Networks (SNNs...
Action Potentials Unsupervised Machine Learning Neurons Synapses Nerve Net Humans Learning Neural Networks, Computer Neuronal Plasticity Brain Models, Neurological
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A multiscale brain emulation-based artificial intelligence framework for dynamic environments.

Scientific reports May 21, 2025
Achieving general artificial intelligence (AGI) has long been a grand challenge in the field of AI, and brain-inspired computing is widely acknowledged as one of the most promising approaches to realize this goal. This paper introduces a novel brain-...
Models, Neurological Neurons Saccades Artificial Intelligence Algorithms Brain Humans
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Neural Code Translation With LIF Neuron Microcircuits.

Neural computation May 14, 2025
Spiking neural networks (SNNs) provide an energy-efficient alternative to traditional artificial neural networks, leveraging diverse neural encoding schemes such as rate, time-to-first-spike (TTFS), and population-based binary codes. Each encoding me...
Humans Neural Networks, Computer Animals Models, Neurological Action Potentials Neurons
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Dynamics and Bifurcation Structure of a Mean-Field Model of Adaptive Exponential Integrate-and-Fire Networks.

Neural computation May 14, 2025
The study of brain activity spans diverse scales and levels of description and requires the development of computational models alongside experimental investigations to explore integrations across scales. The high dimensionality of spiking networks p...
Animals Models, Neurological Action Potentials Neurons Nerve Net Neural Networks, Computer Humans Brain Computer Simulation
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Dynamics of Continuous Attractor Neural Networks With Spike Frequency Adaptation.

Neural computation May 14, 2025
Attractor neural networks consider that neural information is stored as stationary states of a dynamical system formed by a large number of interconnected neurons. The attractor property empowers a neural system to encode information robustly, but it...
Neurons Adaptation, Physiological Animals Models, Neurological Action Potentials Humans Neural Networks, Computer Brain
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Convolutional networks can model the functional modulation of the MEG responses associated with feed-forward processes during visual word recognition.

eLife May 13, 2025
Traditional models of reading lack a realistic simulation of the early visual processing stages, taking input in the form of letter banks and predefined line segments, making them unsuitable for modeling early brain responses. We used variations of t...
Pattern Recognition, Visual Humans Female Neural Networks, Computer Magnetoencephalography Young Adult Brain Male Adult Models, Neurological Reading
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Realistic Subject-Specific Simulation of Resting State Scalp EEG Based on Physiological Model.

Brain topography May 13, 2025
Electroencephalography (EEG) recordings are widely used in neuroscience to identify healthy individual brain rhythms and to detect alterations associated with various brain diseases. However, understanding the cellular origins of scalp EEG signals an...
Computer Simulation Female Adult Humans Brain Rest Brain Waves Scalp Male Models, Neurological Electroencephalography
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The effects of the post-delay epochs on working memory error reduction.

PLoS computational biology May 1, 2025
Accurate retrieval of the maintained information is crucial for working memory. This process primarily occurs during post-delay epochs, when subjects receive cues and generate responses. However, the computational and neural mechanisms that underlie ...
Computational Biology Models, Neurological Memory, Short-Term Humans Neural Networks, Computer Male
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