# From the statistics of connectivity to the statistics of spike times in neuronal networks

@article{Ocker2017FromTS, title={From the statistics of connectivity to the statistics of spike times in neuronal networks}, author={Gabriel Koch Ocker and Yu Hu and Michael A. Buice and Brent Doiron and Kre{\vs}imir Josi{\'c} and Robert Rosenbaum and Eric Shea-Brown}, journal={Current Opinion in Neurobiology}, year={2017}, volume={46}, pages={109-119} }

An essential step toward understanding neural circuits is linking their structure and their dynamics. In general, this relationship can be almost arbitrarily complex. Recent theoretical work has, however, begun to identify some broad principles underlying collective spiking activity in neural circuits. The first is that local features of network connectivity can be surprisingly effective in predicting global statistics of activity across a network. The second is that, for the important case of…

## 36 Citations

Dimensionality in recurrent spiking networks: global trends in activity and local origins in connectivity

- Computer SciencebioRxiv
- 2018

Here, a set of principles are derived that inform how the connectivity of a spiking neural network determines the dimensionality of the activity that it produces, and how stimuli and intrinsic connectivity interact in shaping the overall dimension of a network’s response.

Correlated states in balanced neuronal networks.

- Biology, Computer SciencePhysical review. E
- 2019

An in-depth analysis of the resulting "correlated state" in balanced networks is provided and it is shown that, unlike the asynchronous state, it produces a tight excitatory-inhibitory balance consistent with in vivo cortical recordings.

Cyclic transitions between higher order motifs underlie sustained activity in asynchronous sparse recurrent networks

- BiologybioRxiv
- 2019

A mechanistic link between activity propagation and higher-order motifs at the level of individual neurons and across networks is demonstrated and generalizability to other weakly and sparsely connected networks is predicted.

The correlated state in balanced neuronal networks

- Biology, Computer SciencebioRxiv
- 2018

This work provides an in-depth analysis of the resulting “correlated state” in balanced networks and shows that, unlike the asynchronous state of previous work, it produces a tight excitatory-inhibitory balance consistent with in vivo cortical recordings.

Internally generated population activity in cortical networks hinders information transmission

- BiologybioRxiv
- 2020

This work studies information transfer in networks of spatially ordered spiking neuron models with strong excitatory and inhibitory interactions, capable of producing rich population-wide neuronal variability, and shows that the spatial structure of feedforward and recurrent connectivity are critical determinants for population code performance.

Cyclic transitions between higher order motifs underlie sustained asynchronous spiking in sparse recurrent networks

- Computer SciencePLoS Comput. Biol.
- 2020

The results point to the crucial role of excitatory higher-order patterns in sustaining asynchronous activity in sparse recurrent networks and provide a possible explanation why such connectivity and activity patterns have been prominently reported in neocortex.

Uncovering Network Architecture Using an Exact Statistical Input-Output Relation of a Neuron Model

- Computer SciencebioRxiv
- 2018

A mathematical framework that connects biophysical properties of individual neurons with neural population activity is developed and allows us to explore biophysical mechanisms of neural information processing from their population activity.

Strong coupling and local control of dimensionality across brain areas

- Biology, Computer SciencebioRxiv
- 2020

The result suggests that areas across the brain operate in a strongly coupled regime where dimensionality is under sensitive control by net connectivity strength; moreover, it is shown how thisNet connectivity strength is regulated by local connectivity features, or synaptic motifs.

Variability of collective dynamics in random tree networks of strongly-coupled stochastic excitable elements

- Computer SciencebioRxiv
- 2018

The collective dynamics of strongly diffusively coupled excitable elements on small random tree networks are studied and it is shown that in the physiologically relevant case of strong coupling the variability of collective response is determined by the joint probability distribution of the total number of leaves and nodes.

Variability of collective dynamics in random tree networks of strongly coupled stochastic excitable elements

- Computer SciencePhysical Review E
- 2018

The collective dynamics of strongly diffusively coupled excitable elements on small random tree networks are studied and it is shown that in the physiologically relevant case of strong coupling the variability of collective response is determined by the joint probability distribution of the total number of leaves and nodes.

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