ArticleNeuron2015
Natural grouping of neural responses reveals spatially segregated clusters in prearcuate cortex.
Article in Neuron, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.
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45 citing papers in PubMed.
- Article
- Mapping the computational similarity of individual neurons within large-scale ensemble recordings using the SIMNETS analysis framework.Frontiers in neuroscience · 2025Article
- Orthogonalization of spontaneous and stimulus-driven activity by hierarchical neocortical areal network in primates.Nature communications · 2024Article
- Predicting the effect of micro-stimulation on macaque prefrontal activity based on spontaneous circuit dynamics.Physical review research · 2024Article
- Functional specialization and distributed processing across marmoset lateral prefrontal subregions.Cerebral cortex (New York, N.Y. : 1991) · 2024Article
- Local organization of spatial and shape information in the primate prefrontal cortex.Cerebral cortex (New York, N.Y. : 1991) · 2024Article
- A reservoir of timescales emerges in recurrent circuits with heterogeneous neural assemblies.eLife · 2023Article
- Accounting for Bias in the Estimation ofThe Journal of neuroscience : the official journal of the Society for Neuroscience · 2022Article
- Review
- Priority coding in the visual system.Nature reviews. Neuroscience · 2022Review
- Metastable dynamics of neural circuits and networks.Applied physics reviews · 2022Review
- Article
- Accounting for Biases in the Estimation of Neuronal Signal Correlation.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2021Article
- State-Dependent Regulation of Cortical Processing Speed via Gain Modulation.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2021Article
- Prefrontal cortex represents heuristics that shape choice bias and its integration into future behavior.Current biology : CB · 2021Article
- Dynamic shifts of visual and saccadic signals in prefrontal cortical regions 8Ar and FEF.Journal of neurophysiology · 2020Article
- Statistical methods for dissecting interactions between brain areas.Current opinion in neurobiology · 2020Review
- Stabilization of a brain-computer interface via the alignment of low-dimensional spaces of neural activity.Nature biomedical engineering · 2020Article
- Quantifying Dynamical High-Order Interdependencies From the O-Information: An Application to Neural Spiking Dynamics.Frontiers in physiology · 2020Article
- Plasticity of Persistent Activity and Its Constraints.Frontiers in neural circuits · 2020Review
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6 authors.
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Abstract
A fundamental challenge in studying the frontal lobe is to parcellate this cortex into "natural" functional modules despite the absence of topographic maps, which are so helpful in primary sensory areas. Here we show that unsupervised clustering algorithms, applied to 96-channel array recordings from prearcuate gyrus, reveal spatially segregated subnetworks that remain stable across behavioral contexts. Looking for natural groupings of neurons based on response similarities, we discovered that the recorded area includes at least two spatially segregated subnetworks that differentially represent behavioral choice and reaction time. Importantly, these subnetworks are detectable during different behavioral states and, surprisingly, are defined better by "common noise" than task-evoked responses. Our parcellation process works well on "spontaneous" neural activity, and thus bears strong resemblance to the identification of "resting-state" networks in fMRI data sets. Our results demonstrate a powerful new tool for identifying cortical subnetworks by objective classification of simultaneously recorded electrophysiological activity.
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