ArticleNetwork neuroscience (Cambridge, Mass.)2018
Dynamical networks: Finding, measuring, and tracking neural population activity using network science.
Article in Network neuroscience (Cambridge, Mass.), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Spectral dependence as a framework for neural coordination.Current research in neurobiology · 2026Article
- Mecp2 deficiency impairs microscale cortical network topology and dynamics in a Rett syndrome mouse model.bioRxiv : the preprint server for biology · 2025Article
- MEA-NAP: A flexible network analysis pipeline for neuronal 2D and 3D organoid multielectrode recordings.Cell reports methods · 2024Article
- Stimulus type shapes the topology of cellular functional networks in mouse visual cortex.Nature communications · 2024Article
- MEA-NAP compares microscale functional connectivity, topology, and network dynamics in organoid or monolayer neuronal cultures.bioRxiv : the preprint server for biology · 2024Article
- Reward Expectation Reduces Representational Drift in the Hippocampus.bioRxiv : the preprint server for biology · 2023Article
- The Structure of Hippocampal CA1 Interactions Optimizes Spatial Coding across Experience.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023Article
- Article
- Integrating new memories into the hippocampal network activity space.Nature neuroscience · 2021Article
- Extracting single-trial neural interaction using latent dynamical systems model.Molecular brain · 2021Article
- Scalable and accurate method for neuronal ensemble detection in spiking neural networks.PloS one · 2021Article
- Nonlinear response characteristics of neural networks and single neurons undergoing optogenetic excitation.Network neuroscience (Cambridge, Mass.) · 2020Article
- Organizing principles of whole-brain functional connectivity in zebrafish larvae.Network neuroscience (Cambridge, Mass.) · 2020Article
- Stability of spontaneous, correlated activity in mouse auditory cortex.PLoS computational biology · 2019Article
- Brain-state invariant thalamo-cortical coordination revealed by non-linear encoders.PLoS computational biology · 2018Article
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1 author.
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Abstract
Systems neuroscience is in a headlong rush to record from as many neurons at the same time as possible. As the brain computes and codes using neuron populations, it is hoped these data will uncover the fundamentals of neural computation. But with hundreds, thousands, or more simultaneously recorded neurons come the inescapable problems of visualizing, describing, and quantifying their interactions. Here I argue that network science provides a set of scalable, analytical tools that already solve these problems. By treating neurons as nodes and their interactions as links, a single network can visualize and describe an arbitrarily large recording. I show that with this description we can quantify the effects of manipulating a neural circuit, track changes in population dynamics over time, and quantitatively define theoretical concepts of neural populations such as cell assemblies. Using network science as a core part of analyzing population recordings will thus provide both qualitative and quantitative advances to our understanding of neural computation.
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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.