Hierarchy of transcriptomic specialization across human cortex captured by structural neuroimaging topography

By J. Burt, Murat Demirtaş, William J. Eckner, Natasha M. Navejar, Jie Lisa Ji, William J. Martin, Alberto Bernacchia, Alan Anticevic, John D. Murray. Nature Neuroscience, 2018

596 citations recorded by the source corpus.

Hierarchy provides a unifying principle for the macroscale organization of anatomical and functional properties across primate cortex, yet microscale bases of specialization across human cortex are poorly understood. Anatomical hierarchy is conventionally informed by invasive tract-tracing measurements, creating a need for a principled proxy measure in humans. Moreover, cortex exhibits marked interareal variation in gene expression, yet organizing principles of cortical transcription remain unclear. We hypothesized that specialization of cortical microcircuitry involves hierarchical gradients of gene expression. We found that a noninvasive neuroimaging measure—MRI-derived T1-weighted/T2-weighted (T1w/T2w) mapping—reliably indexes anatomical hierarchy, and it captures the dominant pattern of transcriptional variation across human cortex. We found hierarchical gradients in expression profiles of genes related to microcircuit function, consistent with monkey microanatomy, and implicated in neuropsychiatric disorders. Our findings identify a hierarchical axis linking cortical transcription and anatomy, along which gradients of microscale properties may contribute to the macroscale specialization of cortical function. Burt et al. analyze patterns of gene expression across human cortex and show expression primarily varies along a sensory-association hierarchy captured by noninvasive neuroimaging, suggesting an organizing principle for microcircuit specialization.

Subfields: Cognitive Neuroscience, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/6b9fcb09ac89f5beb0ebffc5c6b96cd1fbcf74ab

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In Cognitive Neuroscience

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Bratislav Misic

Citations in the corpus

Comparing spatial null models for brain maps (2021, unknown): “…2018 ), receptor densities ( Beliveau et al., 2017; Norgaard et al., 2020; Zilles and Amunts, 2009; Zilles et al., 2004 ), intracortical myelin ( Burt et al., 2018; Whitaker et al., 2016 ), and functional organization ( Bellec et al., 2010; Damoi-seaux et al., 2006; Margulies et al., 2016;…”
neuromaps: structural and functional interpretation of brain maps (2022, methodology): “These maps offer insights into the brain’s structural and functional architecture, including grey matter morphometry [9, 17], myelination [13, 28, 36, 88], gene expression [3, 33], cytoarchitecture [66], metabolism [72], neurotransmitter receptors and transporters [8, 32, 55, 94], laminar differenti”
Mapping neurotransmitter systems to the structural and functional organization of the human neocortex (2021, background): “Indeed, recent work has incorporated microarray gene transcription [17, 47], cell types [4, 109], myelination [24, 25, 53], laminar differentiation [138], and intrinsic dynamics [41, 65, 74, 112] into structural and functional models of the brain.”
Developmental relationships between the human alpha rhythm and intrinsic neural timescales are dependent on neural hierarchy (2025, unknown): “For example, intracortical myelin content is increased near the sensorimotor pole of the S-A axis in adults (33,55,56), matures in a gradient along the S-A axis (22,55,57,58), and exhibits weaker age-related changes in regions near the association pole (55,59).”
Heterochronous laminar maturation in the human prefrontal cortex (2025, unknown): “In particular, the S-A axis was derived by integrating in vivo markers of the cortex’s anatomical 101,102 , functional 103,104 , and evolutionary 105 hierarchies as well as representative hierarchical gradients of spatial feature variation 106 .”