A Python library for deterministic associative memory in AI agents. Status: toy / research memory. Deterministic associative recall for small agent fact stores and learning Modern Hopfield networks.

This study presents a useful approach for revealing large-scale brain attractor dynamics during resting states, task processing, and disease conditions using insights from Hopfield neural networks.

Neurodegenerative disorders, most notably Alzheimer’s disease (AD), are marked by progressive cognitive decline and widespread neuronal loss. A growing body of evidence indicates that synaptic ...

The PyCX project aims to develop an online repository of simple, crude, yet easy-to-understand Python sample codes for dynamic complex systems modeling and simulation, including iterative maps, ...

This is a potentially valuable modeling study on sequence generation in the hippocampus in a variety of behavioral contexts. While the scope of the model is ambitious, its presentation is incomplete ...

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Which learning goals must individual computational elements pursue to contribute to a network-level task solution? This local understanding is missing in both biological, but also artificial neural ...

Training neural networks to perform different tasks is relevant across various disciplines. In particular, Recurrent Neural Networks (RNNs) are of great interest in Computational Neuroscience.