Denis Turcu

The paper identifies a minimal central pattern generator circuit for fly walking using connectome simulations and experimental validation.

The paper introduces CoSyn-RNN, a continual-learning model inspired by biological neural systems, which maintains performance across tasks through synaptic state protection and context modulation.

The paper introduces a plasticity-switching recurrent neural network (psRNN) that models synaptic state-dependent plasticity and shows it improves learning efficiency in cognitive tasks.

The paper develops an end-to-end model of electrosensation in weakly electric fish, using artificial data to train an ANN that extracts object properties.

This paper demonstrates that sparse RNNs can perform high-capacity classification through distributed computation and resonance amplification of inputs.

YASS sorts spikes from multi-electrode arrays with > 500 electrodes using neural network detection and denoising, parallelized nonparametric Bayesian clustering, and matching-pursuit deconvolution, outperforming manual sorting on primate retina recordings.