With the advent of volumetric EM techniques, large connectomic datasets are being created,
providing neuroscience researchers with knowledge about the full connectivity of neural …

Highlights•Relating network connectivity to dynamics poses a serious theoretical
challenge.•Network science concepts may have limited relevance in a neuroscience …

The neural dynamics generating sensory, motor, and cognitive functions are commonly
understood through field theories for neural population activity. Classic neural field theories …

Sequences of neural activity arise in many brain areas, including cortex, hippocampus, and
central pattern generator circuits that underlie rhythmic behaviors like locomotion. While …

A central aim in computational neuroscience is to relate the activity of large populations of
neurons to an underlying dynamical system. Models of these neural dynamics should ideally …

This article is part of the Physical Review Research collection titled Physics of
Neuroscience. Neural computation in biological and artificial networks relies on the …

Combinatorial threshold-linear networks (CTLNs) are a special class of inhibition-dominated
TLNs defined from directed graphs. Like more general TLNs, they display a wide variety of …

Balanced excitation and inhibition is widely observed in cortex. How does this balance
shape neural computations and stimulus representations? This question is often studied …

Highlights•Numerous mapping efforts are generating electron-microscopy wiring diagrams
of neural circuits or entire brains.•Detailed connectivity data are now being used in the …

Oscillations are a prominent feature of neuronal activity and are associated with a variety of
phenomena in brain tissue, both healthy and unhealthy. Characterizing how oscillations …