Article

Improved inference of latent neural states from calcium imaging data

2025-10-17

Abstract excerpt

Calcium imaging (CI) is a standard method for recording neural population activity, as it enables simultaneous recording of hundreds-to-thousands of individual somatic signals. Accordingly, CI recordings are prime candidates for population-level latent variable analyses, for example, using models such as Gaussian Process Factor Analysis (GPFA), hidden Markov models (HMMs), and latent dynamical systems. However, th...

Topics

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

Identifiers and source

Literature Corpus work: d40b8594-f7c1-527f-96a6-5e66a0da4e76
DOI: 10.1101/2025.10.17.682993

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Improved inference of latent neural states from calcium imaging dataDOI 10.1101/2025.10.17.682993Read

Spatial quantification of the synaptic activity phenotype across large populations of neurons with Markov random fields.Semantic proximity Read

Inferring parameters of pyramidal neuron excitability in mouse models of Alzheimer’s disease using biophysical modeling and deep learningSemantic proximity Read

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

Recurrent Switching Dynamical Systems Models for Multiple Interacting Neural PopulationsSemantic proximity Read

Methods and considerations for estimating parameters in biophysically detailed neural models with simulation based inferenceSemantic proximity Read

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

Reconciling functional differences in populations of neurons recorded with two-photon imaging and electrophysiology.Semantic proximity Read

NEuRT: A Transformer-Based Model for Explainable Neuronal Activity AnalysisSemantic proximity Read

Generating realistic neurophysiological time series with denoising diffusion probabilistic modelsSemantic proximity Read

A dynamic generative model can extract interpretable oscillatory components from multichannel neurophysiological recordingsSemantic proximity Read

Decodanda: a Python toolbox for best-practice decoding and geometric analysis of neural representationsSemantic proximity Read

Simulation-Based Inference for Whole-Brain Network Modeling of Epilepsy using Deep Neural Density EstimatorsSemantic proximity Read