Precision Functional Mapping of Individual Human Brains

Gordon, Evan M.; Laumann, Timothy O.; Gilmore, Adrian W.; Newbold, Dillan J.; Greene, Deanna J.; Berg, Jeffrey J.; Ortega, Mario; Hoyt, Catherine R.; Gratton, Caterina; Sun, Haoran; Hampton, Jacqueline M.; Coalson, Rebecca S.; Nguyen, Annie; McDermott, Kathleen B.; Shimony, Joshua S.; Snyder, Abraham Z.; Schlaggar, Bradley L.; Petersen, Steven E.; Nelson, Steven M.; Dosenbach, Nico U.F.

doi:10.1016/j.neuron.2017.07.011

Cited by 1,010 publications

(1,298 citation statements)

References 105 publications

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“…Parcellation analyses based on boundary mapping (Cohen et al, 2008; Glasser et al, 2016; Gordon et al, 2016; Gordon, Laumann, Gilmore, et al, 2017; Hirose et al, 2012, 2013, 2016; Laumann et al, 2015; Osada et al, 2017) were applied to the striatum (Figure 1). Each voxel in the striatum of each participant was used as a seed to calculate its correlations with the voxels in the gray matter of the cerebral cortex.…”

Section: Methodsmentioning

confidence: 99%

Striatal subdivisions that coherently interact with multiple cerebrocortical networks

Ogawa

Osada

Tanaka

et al. 2018

Human Brain Mapping

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The striatum constitutes the cortical‐basal ganglia loop and receives input from the cerebral cortex. Previous MRI studies have parcellated the human striatum using clustering analyses of structural/functional connectivity with the cerebral cortex. However, it is currently unclear how the striatal regions functionally interact with the cerebral cortex to organize cortical functions in the temporal domain. In the present human functional MRI study, the striatum was parcellated using boundary mapping analyses to reveal the fine architecture of the striatum by focusing on local gradient of functional connectivity. Boundary mapping analyses revealed approximately 100 subdivisions of the striatum. Many of the striatal subdivisions were functionally connected with specific combinations of cerebrocortical functional networks, such as somato‐motor (SM) and ventral attention (VA) networks. Time‐resolved functional connectivity analyses further revealed coherent interactions of multiple connectivities between each striatal subdivision and the cerebrocortical networks (i.e., a striatal subdivision‐SM connectivity and the same striatal subdivision‐VA connectivity). These results suggest that the striatum contains a large number of subdivisions that mediate functional coupling between specific combinations of cerebrocortical networks.

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Section: Methodsmentioning

confidence: 99%

Striatal subdivisions that coherently interact with multiple cerebrocortical networks

Ogawa

Osada

Tanaka

et al. 2018

Human Brain Mapping

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“…Not only will there be premorbid individual differences in personality and other variables that interact with the effect of a lesion, but (probably in good part due to this) there is also the fact that most patients who have a lesion in one of the regions implicated by Darby et al's (3) analyses (as causally linked to criminal behavior) do not exhibit criminal behavior. It would be of the utmost importance to obtain resting-state fMRI data in criminal lesion cases, such as those described by Darby et al, because it is known that individual functional connectomes not only differ from one another, but also from a group average, such as the one used in their study (14). The most valuable comparisons would then be with two other datasets: with the same individual, but before the lesion (notoriously difficult to obtain since the lesions are generally unpredictable accidents of nature); and with other lesion patients who have damage in the same region, but don't show criminal behavior.…”

Section: Reorganization and Individual Differencesmentioning

confidence: 99%

Searching for the neural causes of criminal behavior

Adolphs

Gläscher

Tranel

2017

Proc. Natl. Acad. Sci. U.S.A.

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All behavior is proximally caused by the brain, but the neural causes of most complex behaviors are still not understood. Much of our ignorance stems from the fact that complex behavior depends on distributed neural control. Unlike a reflex, where the arc from sensation to action can be traced through a few synapses, most volitional behavior involves a dense causal web through which stimuli, memories, beliefs, and other factors exert their effects. Disruption anywhere in this causal web can produce effects that are difficult to trace back to their origin. Against this background, the finding that focal lesions of the ventromedial prefrontal cortex could lead to immoral and even criminal behavior generated considerable surprise and interest (1, 2). While a number of rare cases have now been described in whom a focal lesion caused criminality, these are neither very consistent (the lesions occur in several different anatomical locations) nor at all reliable (only a small fraction of patients, for any lesion location, show criminal behavior). To explain the effects of a lesion on criminal behavior, we need to understand what it is that the lesion does to the rest of the brain, a network-level understanding of lesion effects now provided by the new study of Darby et al. in PNAS (3). A Disconnection ApproachDarby et al. (3) began by searching the literature for cases documenting criminal behavior following a focal brain lesion. They found 17 of these, with lesions predominantly including the prefrontal cortex but also other regions. To estimate the distal effects of such brain damage, lesion network mapping (4) was used, showing which other brain regions, in healthy brains, would normally be functionally connected with the location of the lesion. This approach effectively treats the brain of the lesion patient as equivalent to a healthy brain in which all those regions functionally connected to the lesion site have been instantaneously affected. To do this, Darby et al. (3) leveraged a large reference dataset of restingstate functional MRI (fMRI) data from healthy individuals [from the Brain Genomics Superstruct Project (5)]. From each lesion patient a map was produced showing where, in this resting-state dataset of healthy individuals, the lesion site had strong functional connectivity. Maps of these functionally connected regions were then overlapped across the patients, producing a composite map showing all of the places in a healthy brain that were predicted to be impacted by the lesions. This innovative approach (4, 6) takes seriously the notion of a disconnection syndrome, a term popularized by Norman Geschwind (7) in the 1960s: it is the idea that behavioral impairments can be caused by the disruption of the connections between brain regions rather than by damage to one particular region itself.The composite connectivity map based on positive correlations in the resting-state dataset in fact included many of the regions that, when themselves lesioned, were associated with criminality: the ventromedial and orbi...

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“…Recent cognitive neuroscience research has challenged this assumption (Seghier & Price, ). Several recent studies have shown that between‐person variability is a ubiquitous feature of blood‐oxygenated‐level dependent (BOLD) activation patterns and resting‐state functional connectivity (Finn et al, ; Gordon et al, ; Gratton et al, ; Miller, Donovan, Bennett, Aminoff, & Mayer, ; Rosenberg, Finn, Scheinost, Constable, & Chun, ). In fact, several earlier studies by Miller et al (, , ) found that between‐person differences in whole‐brain BOLD activation patterns persist across differences in task conditions.…”

Section: Introductionmentioning

confidence: 99%

The situation or the person? Individual and task‐evoked differences in BOLD activity

Bolt¹,

Nomi

Bainter

et al. 2019

Human Brain Mapping

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Investigations of between‐person variability are enjoying a recent resurgence in functional magnetic resonance imaging (fMRI) research. Several recent studies have found persistent between‐person differences in blood‐oxygenated‐level dependent (BOLD) activation patterns and resting‐state functional connectivity. Conflicting findings have been reported regarding the extent to which (a) between‐person or (b) within‐person cognitive state differences explain differences in BOLD activation patterns. These discrepancies may arise due to statistical analysis choices, parcellation resolution, and limited sampling of task‐fMRI datasets. We attempt to address these issues in a large‐scale analysis of several task‐fMRI paradigms. Using a novel application of multivariate distance matrix regression, we examine between‐person and task‐condition variability estimates across varying levels of “resolution”, from a coarse region‐of‐interest level to the vertex‐level, and across different distance metrics. These analyses revealed that under most circumstances, differences in task conditions explained a greater amount of variance in activation map differences than between‐person differences. However, this finding was reversed when comparing activation maps at a “high‐resolution” vertex level. More generally, we observed that when moving from “low” to “high” resolutions, the variance explained by between‐person differences increased while variance explained by task conditions decreased. We further analyzed the relationships among subject‐level activation maps across all task‐conditions using an unsupervised clustering approach and identified a superordinate task structure. This structure went beyond conventional task labels and highlighted those experimental manipulations across task conditions that produce contrasting versus similar whole‐brain activation patterns. Overall, these analyses suggest that the question of the subject‐ versus task‐effects on BOLD activation patterns is nontrivial, and depends on the comparison “resolution,” choice of distance metric, and the coding of task‐conditions.

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Precision Functional Mapping of Individual Human Brains

Cited by 1,010 publications

References 105 publications

Striatal subdivisions that coherently interact with multiple cerebrocortical networks

Striatal subdivisions that coherently interact with multiple cerebrocortical networks

Searching for the neural causes of criminal behavior

The situation or the person? Individual and task‐evoked differences in BOLD activity

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