3 papers
cs.NE2025
Towards a Comprehensive Theory of Reservoir Computing
Denis Kleyko, Christopher J. Kymn, E. Paxon Frady +2
In reservoir computing, an input sequence is processed by a recurrent neural network, the reservoir, which transforms it into a spatial pattern that a shallow readout network can t…
cs.NE2025
High-resolution spatial memory requires grid-cell-like neural codes
Madison Cotteret, Christopher J. Kymn, Hugh Greatorex +3
Continuous attractor networks (CANs) are widely used to model how the brain temporarily retains continuous behavioural variables via persistent recurrent activity, such as an anima…
cs.NE2025
A Grid Cell-Inspired Structured Vector Algebra for Cognitive Maps
Sven Krausse, Emre Neftci, Friedrich T. Sommer +1
The entorhinal-hippocampal formation is the mammalian brain's navigation system, encoding both physical and abstract spaces via grid cells. This system is well-studied in neuroscie…