Wilten Nicola

Rapidly Reconfigurable Dynamic Computing in Neural Networks with Fixed Synaptic Connectivity

This paper proposes that neural networks can learn by modulating neuron excitability instead of changing synaptic strengths, enabling task switching and robustness against interference.

Subthreshold Asynchronous States and Computations in Biophysically Detailed Populations of Neurons

The paper demonstrates that computations and asynchronous states can occur in neural networks without spiking through subthreshold voltage fluctuations, using biophysically detailed Hodgkin-Huxley neurons.

Hypothalamic recurrent inhibition regulates functional states of stress effector neurons.

This study identifies recurrent inhibition as a key circuit motif regulating functional states of stress effector neurons through experimental and computational approaches.

Reservoir Computing with Ultra-Sparse Rings

This paper shows that ultra-sparse ring-connected reservoirs can perform complex dynamical systems tasks with linearly scaling parameters.

Versatile Learning without Synaptic Plasticity in a Spiking Neural Network

This paper introduces a spiking neural network framework that learns through bias currents instead of synaptic plasticity, achieving multi-task performance across classification, regression, and dynamical systems mimicry.

Direct Training of Networks of Morris-Lecar Neurons withBackprop

This paper trains biophysically detailed spiking neural networks using Morris-Lecar neurons and differentiable synapses, showing that they can be effectively trained with backpropagation for various tasks.

FORCE trained spiking networks do not benefit from faster learning while parameter matched rate networks do

This paper compares training spiking and rate-based neural networks using FORCE, finding that slower learning rates stabilize performance in spiking networks while faster learning causes instability and uncorrelated solutions.

Contralesional hippocampal spreading depolarization promotes functional recovery after stroke

This study shows that contralesional hippocampal spreading depolarization improves functional recovery after hippocampal stroke in mice.

A somatic afterhyperpolarization is driven by ion channel nodes expressed across a polygonal spectrin cytoskeleton

The paper identifies a structured distribution of CaRyK ion channel clusters aligned with the spectrin cytoskeleton at the soma, contributing to the slow afterhyperpolarization.

A Markovian neural barcode representing mesoscale cortical spatiotemporal dynamics.

The paper introduces a Markovian neural barcode to represent mesoscale cortical dynamics using a Continuous Time Markov Chain model derived from semi-binary non-negative matrix factorization.

The hippocampal theta oscillation may be generated by chimera dynamics

This study proposes that hippocampal theta oscillations arise from chimera dynamics using computational modeling of Kuramoto oscillator networks.

Particle-Swarm Based Modelling Reveals Two Distinct Classes of CRHPVN Neurons

The paper models CRHPVN neurons using a modified AdEx model with PSO, revealing two subtypes with distinct firing dynamics and network-level roles.

Disk-Drive-Like Operations in the Hippocampus

The paper models hippocampal memory operations as a disk-drive system, showing spike sequences and replay dynamics align with disk-drive mechanics.

Does the Zebra Finch Mating Song Circuit Use Spike Times Efficiently?

The paper shows that precise and reliable spike timing in neural circuits improves encoding accuracy more efficiently than rate coding, particularly in larger networks.

The Alzheimer risk factor CD2AP causes dysfunction of the brain vascular network

This study shows that CD2AP loss in brain endothelial cells impairs vascular function and memory in AD models, suggesting therapeutic targeting of CD2AP pathways.

The Dance of the Interneurons: How Inhibition Facilitates Fast Compressible and Reversible Learning in Hippocampus

This paper demonstrates how inhibitory networks in the hippocampus enable fast, compressible, and reversible learning through theta sequences and SPW-R replay.

Neural Sampling Strategies for Visual Stimulus Reconstruction from Two-photon Imaging of Mouse Primary Visual Cortex

This paper reconstructs natural visual stimuli from two-photon calcium imaging of mouse visual cortex by analyzing receptive field density and decoding accuracy.