ArticleJournal of neurophysiology2017
Inferring neuronal network functional connectivity with directed information.
Article in Journal of neurophysiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Motor priming is associated with widespread recruitment into neural ensembles and more rapid ensemble transitions.iScience · 2026Article
- Maximum likelihood estimation of spatially dependent interactions in large populations of cortical neurons.Frontiers in computational neuroscience · 2025Article
- Modeling multiscale causal interactions between spiking and field potential signals during behavior.Journal of neural engineering · 2022Article
- Neural Estimator of Information for Time-Series Data with Dependency.Entropy (Basel, Switzerland) · 2021Article
- Inferring functional connectivity through graphical directed information.Journal of neural engineering · 2021Article
- Addressing indirect frequency coupling via partial generalized coherence.Scientific reports · 2021Article
- Recent Advances in Electrical Neural Interface Engineering: Minimal Invasiveness, Longevity, and Scalability.Neuron · 2020Review
- Photodiode-Based Optical Imaging for Recording Network Dynamics with Single-Neuron Resolution in Non-Transgenic Invertebrates.Journal of visualized experiments : JoVE · 2020Article
- Inferring neural information flow from spiking data.Computational and structural biotechnology journal · 2020Review
- Reconstructing neuronal circuitry from parallel spike trains.Nature communications · 2019Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A major challenge in neuroscience is to develop effective tools that infer the circuit connectivity from large-scale recordings of neuronal activity patterns. In this study, context tree maximizing (CTM) was used to estimate directed information (DI), which measures causal influences among neural spike trains in order to infer putative synaptic connections. In contrast to existing methods, the method presented here is data driven and can readily identify both linear and nonlinear relations between neurons. This CTM-DI method reliably identified circuit structures underlying simulations of realistic conductance-based networks. It also inferred circuit properties from voltage-sensitive dye recordings of the buccal ganglion of
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.