Connecting connectomes to physiology
With the advent of volumetric EM techniques, large connectomic datasets are being created,
providing neuroscience researchers with knowledge about the full connectivity of neural …
providing neuroscience researchers with knowledge about the full connectivity of neural …
Relating network connectivity to dynamics: opportunities and challenges for theoretical neuroscience
C Curto, K Morrison - Current opinion in neurobiology, 2019 - Elsevier
Highlights•Relating network connectivity to dynamics poses a serious theoretical
challenge.•Network science concepts may have limited relevance in a neuroscience …
challenge.•Network science concepts may have limited relevance in a neuroscience …
Republished: Dynamics of stochastic integrate-and-fire networks
GK Ocker - Physical Review X, 2023 - APS
The neural dynamics generating sensory, motor, and cognitive functions are commonly
understood through field theories for neural population activity. Classic neural field theories …
understood through field theories for neural population activity. Classic neural field theories …
Sequential attractors in combinatorial threshold-linear networks
Sequences of neural activity arise in many brain areas, including cortex, hippocampus, and
central pattern generator circuits that underlie rhythmic behaviors like locomotion. While …
central pattern generator circuits that underlie rhythmic behaviors like locomotion. While …
Inferring stochastic low-rank recurrent neural networks from neural data
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 …
neurons to an underlying dynamical system. Models of these neural dynamics should ideally …
Geometric framework to predict structure from function in neural networks
T Biswas, JE Fitzgerald - Physical review research, 2022 - APS
This article is part of the Physical Review Research collection titled Physics of
Neuroscience. Neural computation in biological and artificial networks relies on the …
Neuroscience. Neural computation in biological and artificial networks relies on the …
[HTML][HTML] Core motifs predict dynamic attractors in combinatorial threshold-linear networks
C Parmelee, S Moore, K Morrison, C Curto - PloS one, 2022 - journals.plos.org
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 …
TLNs defined from directed graphs. Like more general TLNs, they display a wide variety of …
[HTML][HTML] Nonlinear stimulus representations in neural circuits with approximate excitatory-inhibitory balance
Balanced excitation and inhibition is widely observed in cortex. How does this balance
shape neural computations and stimulus representations? This question is often studied …
shape neural computations and stimulus representations? This question is often studied …
Constraining computational models using electron microscopy wiring diagrams
A Litwin-Kumar, SC Turaga - Current opinion in neurobiology, 2019 - Elsevier
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 …
of neural circuits or entire brains.•Detailed connectivity data are now being used in the …
Optimal network interventions to control the spreading of oscillations
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 …
phenomena in brain tissue, both healthy and unhealthy. Characterizing how oscillations …