A Weighted and Directed Interareal Connectivity Matrix for Macaque Cerebral Cortex

Markov, Nikola; Ercsey-Ravasz, Mária; Gomes, Ana Rita Ribeiro; Lamy, Camille; Magrou, Loïc; Vezoli, Julien; Misery, Pierre; Falchier, Arnaud; Quilodran, René; Gariel, Marie-Alice; Sallet, Jérôme; Gămănuţ, Răzvan; Huissoud, Cyril; Clavagnier, Simon; Giroud, Pascale; Sappey-Marinier, Dominique; Barone, Pascal; Dehay, Colette; Toroczkai, Zoltán; Knoblauch, Kenneth; Essen, David C. Van; Kennedy, Henry

doi:10.1093/cercor/bhs270

Cited by 817 publications

(1,362 citation statements)

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“…Vincent et al (2007) showed qualitatively that functional connectivity in the anesthetized macaque correlated well with anatomical connectivity when testing a seed region in the vicinity of area LIPv, whereas a seed region centered in area V1 revealed evidence of a combination of direct connections (e.g., with area MT) and indirect connections (e.g., with the horizontal meridian of contralateral area V1, which has no direct interhemispheric connections). A recent study showed a modest (r ¼ 0.35) but highly significant correlation between functional connectivity in the anesthetized macaque and the Markov et al (2012) quantitative parcellated connectivity matrix (Miranda-Dominguez et al 2014). Importantly, the analysis revealed many false negatives (negative functional connectivity, or anti-correlation between areas that are strongly connected anatomically).…”

Section: Functional Connectivity Validation In the Macaquementioning

confidence: 96%

“…Major progress on this front has come from a recent systematic effort from the laboratory of Henry Kennedy, revealing that connectivity profiles are more highly distributed and that connection strengths span a much wider range than previously realized (Knoblauch et al 2015). Using a 91-area cortical parcellation and retrograde tracers injected into 29 cortical areas, Markov et al (2012) determined that each cortical area receives on average inputs from 55 other areas out of a (minimum) 26 and (maximum) 87; when expressed as the fraction of retrogradely labeled neurons, these pathways vary over five orders of magnitude in connection strength (Markov et al 2011(Markov et al , 2012Knoblauch et al 2015). This translates to 1615 inter-areal pathways out of 2610 possible in a 29 Â 91 connectivity matrix.…”

Section: Distributed Cortical Connectivitymentioning

confidence: 99%

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Parcellations and Connectivity Patterns in Human and Macaque Cerebral Cortex

Essen

Donahue

Dierker

et al. 2016

Research and Perspectives in Neurosciences

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To decipher brain function, it is vital to know how the brain is wired. This entails elucidation of brain circuits at multiple scales, including microscopic, mesoscopic, and macroscopic levels. Here, we review recent progress in mapping the macroscopic brain circuits and functional organization of the cerebral cortex in primates-humans and macaque monkeys, in particular. There are many similarities across species in terms of overall patterns of cortical gray matter myelination as well as functional areas that are presumed to be homologous. However, there are also many important species differences, including cortical convolutions that are much more complex and more variable in humans than in monkeys. Our ability to analyze structure and function has benefited from improved methods for intersubject registration that cope with this individual variability. To characterize long-distance connectivity, powerful but indirect methods are now available, including resting-state functional connectivity and diffusion imaging coupled with probabilistic tractography. We illustrate how connectivity inferred from diffusion imaging and tractography can be evaluated in relation to 'ground truth' based on anatomical tracers in the macaque. Interspecies registration between human and macaque cortex based on presumed interspecies homologies demonstrates an impressive degree of areal expansion in regions associated with higher cognitive function.

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Section: Functional Connectivity Validation In the Macaquementioning

confidence: 96%

Section: Distributed Cortical Connectivitymentioning

confidence: 99%

Parcellations and Connectivity Patterns in Human and Macaque Cerebral Cortex

Essen

Donahue

Dierker

et al. 2016

Research and Perspectives in Neurosciences

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show abstract

“…While processing hierarchies are typically described in sensorimotor systems (e.g., [9,10]), they have been proposed to extend to transmodal association areas [8,44,45]. In support of this view, spatial gradients of functional integration ranging from unimodal to transmodal areas have recently been described in the human cortex [35,46].…”

Section: Functional Processing Hierarchiesmentioning

confidence: 99%

“…The location of an area among its neighbors thus provides insight into its microstructural characteristics [6], its connections to other parts of the brain [7], and eventually its position in global processing hierarchies [8]. Consider, for example, the well-researched visual system of the macaque monkey [9,10]. Along the visual hierarchy, low-level visual features are increasingly abstracted and integrated with information from other systems.…”

mentioning

confidence: 99%

Large-Scale Gradients in Human Cortical Organization

Huntenburg

Bazin

Margulies

2018

Trends in Cognitive Sciences

797

811

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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. The Significance of Cortical LocationFor more than a century, neuroscientists have studied the cerebral cortex by delineating individual cortical areas (see Glossary) and mapping their function [1]. This agenda has substantially advanced in recent years, as automated parcellation methods improve and data sets of unprecedented size and quality become available [2][3][4]. Nevertheless, our understanding of how the complex structure of the cerebral cortex emerges and gives rise to its elaborate functions remains fragmentary. To complement the description of individual cortical areas, we propose an inquiry into the significance of their spatial arrangement, asking the basic question: Why are cortical areas located where they are?Early formulations of this question date to theories from classical neuroanatomy [1,[5][6][7]. They state that the spatial layout of cortical areas is not arbitrary, but a consequence of developmental mechanisms, shaped through evolutionary selection. The location of an area among its neighbors thus provides insight into its microstructural characteristics [6], its connections to other parts of the brain [7], and eventually its position in global processing hierarchies [8]. Consider, for example, the well-researched visual system of the macaque monkey [9,10]. Along the visual hierarchy, low-level visual features are increasingly abstracted and integrated with information from other systems. Traditionally, areas are ordered based on their degree of microstructural differentiation, and the classification of their connections as feedforward or feedback [11]. The framework we advocate emphasizes that an area's position in the visual processing hierarchy -and thus many of its microstructural and connectional features -is strongly related to its distance from the primary visual area [12,13].More generally, we propose that the spatial arrangement of areas along a global gradient between sensorimotor and transmodal regions is a key feature of human cortical organization. A gradient is an axis of variance in cortical features, along which areas fall in a spatially continuous order. Areas that resemble each other with respect to the feature of interest occupy similar positions along the gradient. As we will point out, there is a strong relationship between the similarity of two areas -that is, their relative position along the gradient -and their relative position along the cortical surface. This important role of cortical location pro...

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“…Numerous new (and mostly relatively weak) projections were uncovered, and the overall connectivity profile for each area was best approximated by a lognormal distribution (Markov et al 2011), with a few strong projections and a large admixture of medium or weak pathways. Graph analysis provided evidence for a relatively high proportion of unidirectional links (Markov et al 2014), a strong contribution of long-distance projections towards areal specificity (Markov et al 2013a), significant distance-dependence of connection densities (Ercsey-Ravasz et al 2013), and hierarchical arrangement of areas into "counter-streams" (Markov et al 2013b). Several of these characteristic topological features are also found in other mammalian species, e.g., the cat or rodent brain.…”

Section: Macroscalementioning

confidence: 84%