Article

Recurrent Switching Dynamical Systems Models for Multiple Interacting Neural Populations

2020-10-22

Abstract excerpt

Modern recording techniques can generate large-scale measurements of multiple neural populations over extended time periods. However, it remains a challenge to model non-stationary interactions between high-dimensional populations of neurons. To tackle this challenge, we develop recurrent switching linear dynamical systems models for multiple populations. Here, each high-dimensional neural population is represente...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 78c32678-72c2-5b3d-a727-629701a6db77
DOI: 10.1101/2020.10.21.349282

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Recurrent Switching Dynamical Systems Models for Multiple Interacting Neural PopulationsDOI 10.1101/2020.10.21.349282Read

Deep inverse modeling reveals dynamic-dependent invariances in neural circuit mechanismsSemantic proximity Read

Nonlinear manifolds underlie neural population activity during behaviourSemantic proximity Read

Switching state-space modeling of neural signal dynamicsSemantic proximity Read

Dynamic Models of Neural Population DynamicsSemantic proximity Read

osl-dynamics: A toolbox for modelling fast dynamic brain activitySemantic proximity Read

Improved inference of latent neural states from calcium imaging dataSemantic proximity Read

Multi-dynamic Modelling Reveals Strongly Time-varying Resting fMRI CorrelationsSemantic proximity Read

Effective excitability captures network dynamics across development and phenotypesSemantic proximity Read

iLQR-VAE : control-based learning of input-driven dynamics with applications to neural dataSemantic proximity Read

Biologically plausible learning in a deep recurrent spiking networkSemantic proximity Read

Complex priors and flexible inference in recurrent circuits with dendritic nonlinearitiesSemantic proximity Read

A Canonical Neural Mechanism for Behavioral VariabilitySemantic proximity Read