Function-based Intersubject Alignment of Human Cortical Anatomy

Sabuncu, Mert R.; Singer, Benjamin D.; Conroy, Bryan; Bryan, Ronald E.; Ramadge, Peter J.; Haxby, James V.

doi:10.1093/cercor/bhp085

Cited by 154 publications

(155 citation statements)

References 37 publications

(53 reference statements)

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“…This approach is inherently problematic for dealing with regions of high folding variability, especially since the location of the cortical areas and functionally specialized regions vary in relation to gyral and sulcal landmarks. Fortunately, new registration methods have recently emerged that capitalize on functionally relevant features (e.g., myelin maps, fMRI data) in conjunction with shape-based information (Sabuncu et al 2010;Robinson et al 2013). In the examples illustrated below, we capitalize on the Multimodal Surface Matching (MSM) method as applied to HCP and macaque datasets .…”

Section: Convolutions and Folding Variabilitymentioning

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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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: Convolutions and Folding Variabilitymentioning

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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“…6,[d] Many studies have also focused on improving spatial coregistration and thus functional localization or vice versa. [7][8][9] These structural and functional variations are clearly widespread and likely have a complex impact on the resulting functional patterns, motivating a multivariate whole-brain approach.…”

Section: [A]mentioning

confidence: 99%

Spatial Variance in Resting fMRI Networks of Schizophrenia Patients: An Independent Vector Analysis

Gopal

Miller

Andrew

et al. 2015

SCHBUL

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Spatial variability in resting functional MRI (fMRI) brain networks has not been well studied in schizophrenia, a disease known for both neurodevelopmental and widespread anatomic changes. Motivated by abundant evidence of neuroanatomical variability from previous studies of schizophrenia, we draw upon a relatively new approach called independent vector analysis (IVA) to assess this variability in resting fMRI networks. IVA is a blind-source separation algorithm, which segregates fMRI data into temporally coherent but spatially independent networks and has been shown to be especially good at capturing spatial variability among subjects in the extracted networks. We introduce several new ways to quantify differences in variability of IVA-derived networks between schizophrenia patients (SZs = 82) and healthy controls (HCs = 89). Voxelwise amplitude analyses showed significant group differences in the spatial maps of auditory cortex, the basal ganglia, the sensorimotor network, and visual cortex. Tests for differences (HC-SZ) in the spatial variability maps suggest, that at rest, SZs exhibit more activity within externally focused sensory and integrative network and less activity in the default mode network thought to be related to internal reflection. Additionally, tests for difference of variance between groups further emphasize that SZs exhibit greater network variability. These results, consistent with our prediction of increased spatial variability within SZs, enhance our understanding of the disease and suggest that it is not just the amplitude of connectivity that is different in schizophrenia, but also the consistency in spatial connectivity patterns across subjects.

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“…Since other areas such as areas 44 and 45 of Broca's region seem to exhibit a less strong relationship, it would be relevant to address the variable relationship between both aspects of brain organization in a systematic way. However, the degree to which idiosyncrasies and variability should be handled in the spatial mapping between individuals, templates, and the ensuing atlases remains a challenge (Devlin and Poldrack, 2007) for which multi-modal registration algorithms are certainly part of the solution (Sabuncu et al, 2010).…”

Section: Key Challenges For a Multi-modal Human Brain Atlasmentioning

confidence: 99%

Interoperable atlases of the human brain

Amunts

Hawrylycz²,

Essen³

et al. 2014

NeuroImage

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The last two decades have seen an unprecedented development of human brain mapping approaches at various spatial and temporal scales. Together, these have provided a large fundus of information on many different aspects of the human brain including micro-and macrostructural segregation, regional specialization of function, connectivity, and temporal dynamics. Atlases are central in order to integrate such diverse information in a topographically meaningful way. It is noteworthy, that the brain mapping field has been developed along several major lines such as structure vs. function, postmortem vs. in vivo, individual features of the brain vs. population-based aspects, or slow vs. fast dynamics. In order to understand human brain organization, however, it seems inevitable that these different lines are integrated and combined into a multimodal human brain model. To this aim, we held a workshop to determine the constraints of a multi-modal human brain model that are needed to enable (i) an integration of different spatial and temporal scales and data modalities into a common reference system, and (ii) efficient data exchange and analysis. As detailed in this report, to arrive at fully interoperable atlases of the human brain will still require much work at the frontiers of data acquisition, analysis, and representation. Among them, the latter may provide the most challenging task, in particular when it comes to representing features of vastly different scales of space, time and abstraction. The potential benefits of such endeavor, however, clearly outweigh the problems, as only such kind of multi-modal human brain atlas may provide a starting point from which the complex relationships between structure, function, and connectivity may be explored.

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Function-based Intersubject Alignment of Human Cortical Anatomy

Cited by 154 publications

References 37 publications

Parcellations and Connectivity Patterns in Human and Macaque Cerebral Cortex

Parcellations and Connectivity Patterns in Human and Macaque Cerebral Cortex

Spatial Variance in Resting fMRI Networks of Schizophrenia Patients: An Independent Vector Analysis

Interoperable atlases of the human brain

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