AIMC Topic: Neurons

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Intrinsic plasticity coding improved spiking actor network for reinforcement learning.

Neural networks : the official journal of the International Neural Network Society Dec 19, 2024
Deep reinforcement learning (DRL) exploits the powerful representational capabilities of deep neural networks (DNNs) and has achieved significant success. However, compared to DNNs, spiking neural networks (SNNs), which operate on binary signals, mor...
Computer Simulation Humans Neurons Neural Networks, Computer Deep Learning Reinforcement, Psychology Neuronal Plasticity Action Potentials Models, Neurological
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Spintronic Artificial Neurons Showing Integrate-and-Fire Behavior with Reliable Cycling Operation.

Nano letters Dec 17, 2024
The rich dynamics of magnetic materials makes them promising candidates for neural networks that, like the brain, take advantage of dynamical behaviors to efficiently compute. Here, we experimentally show that integrate-and-fire neurons can be achiev...
Neurons Neural Networks, Computer Action Potentials
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Enhanced accuracy in first-spike coding using current-based adaptive LIF neuron.

Neural networks : the official journal of the International Neural Network Society Dec 16, 2024
First spike timings are crucial for decision-making in spiking neural networks (SNNs). A recently introduced first-spike (FS) coding method demonstrates comparable accuracy to firing-rate (FR) coding in processing complex temporal information through...
Humans Action Potentials Neural Networks, Computer Neurons Models, Neurological
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Adapting to time: Why nature may have evolved a diverse set of neurons.

PLoS computational biology Dec 13, 2024
Brains have evolved diverse neurons with varying morphologies and dynamics that impact temporal information processing. In contrast, most neural network models use homogeneous units that vary only in spatial parameters (weights and biases). To explor...
Adaptation, Physiological Biological Evolution Neurons Nerve Net Brain Animals Models, Neurological Action Potentials Computational Biology Humans Neural Networks, Computer
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Neural networks with optimized single-neuron adaptation uncover biologically plausible regularization.

PLoS computational biology Dec 13, 2024
Neurons in the brain have rich and adaptive input-output properties. Features such as heterogeneous f-I curves and spike frequency adaptation are known to place single neurons in optimal coding regimes when facing changing stimuli. Yet, it is still u...
Action Potentials Neurons Nerve Net Computational Biology Models, Neurological Adaptation, Physiological Neural Networks, Computer Algorithms Computer Simulation Animals Brain Humans
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Similarity-based context aware continual learning for spiking neural networks.

Neural networks : the official journal of the International Neural Network Society Dec 12, 2024
Biological brains have the capability to adaptively coordinate relevant neuronal populations based on the task context to learn continuously changing tasks in real-world environments. However, existing spiking neural network-based continual learning ...
Action Potentials Algorithms Neurons Learning Humans Models, Neurological Neural Networks, Computer
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Two-Terminal Neuromorphic Devices for Spiking Neural Networks: Neurons, Synapses, and Array Integration.

ACS nano Dec 12, 2024
The ever-increasing volume of complex data poses significant challenges to conventional sequential global processing methods, highlighting their inherent limitations. This computational burden has catalyzed interest in neuromorphic computing, particu...
Humans Neurons Biomimetics Synapses Neural Networks, Computer Action Potentials
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Stabilizing sequence learning in stochastic spiking networks with GABA-Modulated STDP.

Neural networks : the official journal of the International Neural Network Society Dec 7, 2024
Cortical networks are capable of unsupervised learning and spontaneous replay of complex temporal sequences. Endowing artificial spiking neural networks with similar learning abilities remains a challenge. In particular, it is unresolved how differen...
Neural Networks, Computer Learning Neuronal Plasticity Humans Neurons gamma-Aminobutyric Acid Stochastic Processes Models, Neurological Action Potentials
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Temporal spiking generative adversarial networks for heading direction decoding.

Neural networks : the official journal of the International Neural Network Society Dec 5, 2024
The spike-based neuronal responses within the ventral intraparietal area (VIP) exhibit intricate spatial and temporal dynamics in the posterior parietal cortex, presenting decoding challenges such as limited data availability at the biological popula...
Action Potentials Neurons Macaca mulatta Generative Adversarial Networks Parietal Lobe Neural Networks, Computer Animals Models, Neurological
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Low-power and lightweight spiking transformer for EEG-based auditory attention detection.

Neural networks : the official journal of the International Neural Network Society Dec 4, 2024
EEG signal analysis can be used to study brain activity and the function and structure of neural networks, helping to understand neural mechanisms such as cognition, emotion, and behavior. EEG-based auditory attention detection is using EEG signals t...
Acoustic Stimulation Humans Auditory Perception Neural Networks, Computer Neurons Electroencephalography Action Potentials Attention Signal Processing, Computer-Assisted
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