Mechanistic modeling with low-rank recurrent networks uncovers the relationship between network connectivity, neural dynamics, and selection modulation mechanisms in context-dependent computation.
Maximilian Nentwich, Marcin Leszczynski ... Lucas C Parra
A new computational model improves estimation of Granger connectivity by removing spurious effects of external inputs, and estimation of linear encoding models by removing spurious effects of recurrent connections.
Extended multi-attribute attentional drift diffusion model reveals how attentional dynamics and weight shifts lead to less healthy decisions under hunger.
A robust method to infer excitatory and inhibitory synaptic conductances from neuronal recordings reveals functional circuit organization in rhythmic networks.
