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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
Distributed Representations Enable Robust Multi-Timescale Symbolic Computation in Neuromorphic Hardware
Madison Cotteret, Hugh Greatorex, Alpha Renner +6
Programming recurrent spiking neural networks (RSNNs) to robustly perform multi-timescale computation remains a difficult challenge. To address this, we describe a single-shot weig…
cs.NE2024
TEXEL: A neuromorphic processor with on-chip learning for beyond-CMOS device integration
Hugh Greatorex, Ole Richter, Michele Mastella +10
Recent advances in memory technologies, devices and materials have shown great potential for integration into neuromorphic electronic systems. However, a significant gap remains be…