Robert Rosenbaum

Functionally similar neurons in mouse visual cortex connect preferentially across layers and areas, including feedback, and feature tuning, not receptive-field position, predicts synapses beyond axon-dendrite proximity.

The paper examines neural activity during a reaching task in macaques and finds that basal ganglia-thalamic communication does not follow standard gating or rebound models.

The paper shows that balanced neural networks can exhibit nonlinear stimulus representations through semi-balanced states caused by multiple stimuli.

This paper develops a theory of plasticity in balanced neural networks, showing how balance is maintained and how correlations affect synaptic weight evolution and learning.

The paper investigates how functional connectivity, synaptic connectivity, and external input variability can be distinguished in neural microcircuits using simulations, analysis, and calcium imaging data.

The paper shows that correlated feedforward input increases correlations in balanced neuronal networks, leading to a correlated state with excitatory-inhibitory balance similar to in vivo recordings.

The paper shows that model cortical networks with physiologically accurate inhibitory coupling generate low-dimensional shared variability, matching in vivo recordings and explaining attentional modulation of variability between brain areas.

The paper identifies an amplification mechanism in cortical circuits caused by local imbalance of excitation and inhibition, which can be quantified by a linear correction to balanced network theory.

The paper links network connectivity statistics to spike time statistics in neuronal networks, showing how local connectivity features predict global activity patterns and how plasticity rules can coevolve connectivity and spiking statistics.