Large-Scale Gradients in Human Cortical Organization.

By Julia M. Huntenburg, Pierre-Louis Bazin, Daniel S. Margulies. Trends in Cognitive Sciences, 2018

881 citations recorded by the source corpus.

Recent advances in mapping cortical areas in the human brain provide a basis for investigating the significance of their spatial arrangement. Here we describe a dominant gradient in cortical features that spans between sensorimotor and transmodal areas. We propose that this gradient constitutes a core organizing axis of the human cerebral cortex, and describe an intrinsic coordinate system on its basis. Studying the cortex with respect to these intrinsic dimensions can inform our understanding of how the spectrum of cortical function emerges from structural constraints.

Subfields: Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/6dd28ead479f7c526f2c08e226f09c77b9f986b7

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In Cognitive Neuroscience

Citations in the corpus

neuromaps: structural and functional interpretation of brain maps (2022, background): “Second, given the growing interest in how these system-level maps or “gradients” are related to one another, we sought to assess patterns of relationships among them [37, 69].”
Neurodevelopment of the association cortices: Patterns, mechanisms, and implications for psychopathology (2021, neutral): “Moreover, primary regions are located most distant on the cortex from transmodal association regions that support higher-order psychological, social, and executive functions, with uni- and multi-modal cortices occupying spatially intermediate positions (Huntenburg et al., 2018; Margulies et al., 201”
Generative modeling of brain maps with spatial autocorrelation (2020, neutral): “Recent technological advancements in neuroimaging, large-scale connectomics, and high-throughput transcriptomics have facilitated the discovery of conserved principles of brain organization (Huntenburg et al., 2018; Burt et al., 2018; Fornito et al., 2019).”
BrainSpace: a toolbox for the analysis of macroscale gradients in neuroimaging and connectomics datasets (2019, methodology): “As such, using manifolds as a new coordinate system 34 may complement widely used parcellation approaches 2,42,51 and be can be useful for the compact representation of ﬁ ndings and aid in the interpretation and communication of results.”
Gradients of structure–function tethering across neocortex (2019, neutral): “Recent studies suggest a universal organizational principle whereby brain regions are situated along a continuous gradient or hierarchy, ranging from primary sensory and motor regions to transmodal regions (18, 38).”
Aperiodic neural timescales in prefrontal cortex dilate with increased task abstraction (2025, unknown): “The regions of cortex with the longest timescales are also the regions most closely associated with greater task abstraction (5,12,19,20).”
Cortical functional hierarchy disruption following subcortical stroke (2026, unknown): “Neurobiologically, while FCS reflects the local hubness of specific regions, functional gradients capture the macroscale hierarchy of the whole cortex, which is evolutionarily conserved [30].”
The dominance of large-scale phase dynamics in human cortex, from delta to gamma (2026, unknown): “Another dimension, at approximately twice the SF, is a function of the cortical distance between the primary areas and transmodal areas ( Huntenburg et al., 2018 ).”
Revolutionizing Pediatric Neurophysiology With Magnetoencephalography (2026, unknown): “…building on a model of brain organization that postulates a dominant gradient in cortical features across sensorimotor and transmodal areas (Huntenburg et al. 2018), Mahjoory et al. (2020) used RS MEG recordings ( N = 187 adults) and distributed source localization to show that the…”
Developmental relationships between the human alpha rhythm and intrinsic neural timescales are dependent on neural hierarchy (2025, unknown): “In classic models of neural processing hierarchy, information is first processed in sensorimotor regions then in association regions (15,16), forming what has become known as the sensorimotor-to-association axis (S-A axis, reviewed in 17,18).”