ArticleNeuron2021
High-order interactions explain the collective behavior of cortical populations in executive but not sensory areas.
Article in Neuron, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 23 citations in OpenAlex.
- Charting higher-order models of brain function beyond pairwise interactions.Nature communications · 2026Article
- Population-level encoding of task information is stronger in the adolescent compared to adult frontal cortex.Developmental cognitive neuroscience · 2026Article
- From microstates to macroscales: A Critical Review of Maximum Entropy Modeling and Energy Landscape Analysis in functional MRI.Research square · 2025Article
- Higher-order and distributed synergistic functional interactions encode information gain in goal-directed learning.Nature communications · 2025Article
- Higher-order connectomics of human brain function reveals local topological signatures of task decoding, individual identification, and behavior.Nature communications · 2024Article
- Functional Hypergraphs of Stock Markets.Entropy (Basel, Switzerland) · 2024Article
- The quality and complexity of pairwise maximum entropy models for large cortical populations.PLoS computational biology · 2024Article
- Uncovering hidden network architecture from spiking activities using an exact statistical input-output relation of neurons.Communications biology · 2023Article
- The structures and functions of correlations in neural population codes.Nature reviews. Neuroscience · 2022Review
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
Abstract
One influential view in neuroscience is that pairwise cell interactions explain the firing patterns of large populations. Despite its prevalence, this view originates from studies in the retina and visual cortex of anesthetized animals. Whether pairwise interactions predict the firing patterns of neurons across multiple brain areas in behaving animals remains unknown. Here, we performed multi-area electrical recordings to find that 2nd-order interactions explain a high fraction of entropy of the population response in macaque cortical areas V1 and V4. Surprisingly, despite the brain-state modulation of neuronal responses, the model based on pairwise interactions captured ∼90% of the spiking activity structure during wakefulness and sleep. However, regardless of brain state, pairwise interactions fail to explain experimentally observed entropy in neural populations from the prefrontal cortex. Thus, while simple pairwise interactions explain the collective behavior of visual cortical networks across brain states, explaining the population dynamics in downstream areas involves higher-order interactions.
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Registered trials
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