Neural networks : the official journal of the International Neural Network Society
Dec 27, 2024
Even in the absence of external stimuli, the brain is spontaneously active. Indeed, most cortical activity is internally generated by recurrence. Both theoretical and experimental studies suggest that chaotic dynamics characterize this spontaneous ac...
Neural networks : the official journal of the International Neural Network Society
Dec 26, 2024
In this study, we address the challenge of analyzing electrophysiological measurements in neuronal networks. Our computational model, based on the Reservoir Computing Network (RCN) architecture, deciphers spatio-temporal data obtained from electrophy...
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...
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...
Complex biological systems have evolved to control movement dynamics despite noisy and unpredictable inputs and processing delays that necessitate forward predictions. The staple example in vertebrates is the locomotor control emerging from interacti...
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...
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...
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 ...
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 : 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...