A. Stasik

The paper applies metamodels to a spiking neural network to approximate its dynamics and invert parameter distributions from simulation outputs.

The paper uses biophysical simulations of mouse primary visual cortex to show that current sinks and sources are shaped by both synaptic weights and dendritic placement, with distinct contributions from thalamocortical inputs and cortical feedback.

This paper introduces RippleNet, a deep LSTM-based model for detecting SPW-R events from LFP data, achieving high precision with minimal manual curation.

The paper introduces BMTK, an open-source software suite for multiscale brain circuit modeling, enabling simulations across different resolution levels with reduced coding requirements.

This paper uses convolutional neural networks to estimate synaptic connection weights in a neuronal network model from local field potential (LFP) signals.