Tracking ongoing cognition in individuals using brief, whole-brain functional connectivity patterns

Gonzalez-Castillo, Javier; Hoy, Colin W.; Handwerker, Daniel A.; Robinson, Meghan E.; Buchanan, Laura C.; Saad, Ziad S.; Bandettini, Peter A.

doi:10.1073/pnas.1501242112

Cited by 335 publications

(388 citation statements)

References 49 publications

(49 reference statements)

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“…Therefore, both residual and resting-state spontaneous correlations largely reflect the intrinsic organization of PFC. Although task-evoked changes in largescale spontaneous correlations are relatively small, they are statistically reliable (12,35) and influence behavior (27,36). Moreover, context-dependent information processing is also supported by dynamic changes in large-scale task-evoked correlations (37)(38)(39).…”

Section: Discussionmentioning

confidence: 99%

Distributed representation of context by intrinsic subnetworks in prefrontal cortex

Waskom

Wagner

2017

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

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Human prefrontal cortex supports goal-directed behavior by representing abstract information about task context. The organizational basis of these context representations, and of representations underlying other higher-order processes, is unknown. Here, we use multivariate decoding and analyses of spontaneous correlations to show that context representations are distributed across subnetworks within prefrontal cortex. Examining targeted prefrontal regions, we found that pairs of voxels with similar context preferences exhibited spontaneous correlations that were approximately twice as large as those between pairs with opposite context preferences. This subnetwork organization was stable across task-engaged and resting states, suggesting that abstract context representations are constrained by an intrinsic functional architecture. These results reveal a principle of fine-scaled functional organization in association cortex.fMRI | resting-state | rule | cognitive control | functional organization T he cerebral cortex exhibits functional organization at multiple spatial scales. At a coarse scale, the cortex is parcellated into functional areas (1, 2) that coordinate as networks through longrange connections (3-5). These areas represent and compute information with functional circuitry that is organized more finely. Some fine-scaled, intrinsic principles have been described in detail, particularly for sensory cortex (6, 7). In contrast, the subregional organization of prefrontal cortex (PFC), which gives rise to higherorder processes, including attention, decision-making, and goaldirected action (8, 9), remains largely uncharacterized. Whether PFC representations are encoded within an equipotential system or constrained by an intrinsic functional architecture is currently unknown.Sensory cortex can be mapped by parametrically varying stimulus attributes and measuring changes in the neural response, but complex and dynamic response properties limit the effectiveness of this approach for mapping PFC and other association regions. An alternate strategy is to leverage spontaneous variability in neural activity. Neural responses to repeated presentations of sensory stimuli, or in the absence of stimulation and explicit task demands, exhibit variability that is attributed to ongoing spontaneous activity (10-13). Traditional analyses consider spontaneous activity to be noise, but there is increasing evidence that shared spontaneous variability is a signature of functional organization (14). Analyses of spontaneous correlations have been used to identify multiple large-scale functional networks (4,5,15) and boundaries between functional areas (2, 16-18) in human and nonhuman primate association cortex. The spontaneous correlation structure also mirrors established fine-scaled principles of functional organization in visual cortex, such as preferences for retinotopic position (19) and stimulus orientation (20). We therefore leveraged spontaneous activity to examine the finescaled functional organization of human PFC.We focus...

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Section: Discussionmentioning

confidence: 99%

Distributed representation of context by intrinsic subnetworks in prefrontal cortex

Waskom

Wagner

2017

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

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“…The resulting atlas probabilistically relates a large number of individual neurons (embedded in functional circuits) to a set of behavioral types. A methodologically related set of approaches uses classifiers, such as decision trees, to decode cognitive states from whole-brain functional connectivity patterns [56,57,58]. Another extension of these machine learning-based techniques involves the use of connectivity patterns to identify individuals, also called “connectotyping” [59,60].…”

Section: From Modular Network To Multivariate Systemsmentioning

confidence: 99%

From regions to connections and networks: new bridges between brain and behavior

Mišić

Sporns

2016

Current Opinion in Neurobiology

224

133

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Connections and interactions among distributed brain areas are increasingly recognized as the basis for cognitive operations and a diverse repertoire of behaviors. Analytic advances have allowed for brain connectivity to be represented and quantified at multiple levels: from single connections to communities and networks. This review traces the trajectory of network neuroscience, focusing on how connectivity patterns can be related to cognition and behavior. As recent initiatives for open science provide access to imaging and phenotypic data with great detail and depth, we argue that approaches capable of directly modeling multivariate relationships between brain and behavior will become increasingly important in the field.

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“…Although the magnitude of these changes is small, it is possible to accurately decode the task state of a participant simply from their FC in a task (Alnaes et al, 2015; Gonzalez-Castillo et al, 2015; Shirer et al, 2012). In addition, task performance is related to these modifications of FC (e.g., (Dwyer et al, 2014; Gonzalez-Castillo et al, 2015; Gordon et al, 2014; Hampson et al, 2010; Kelly et al, 2008)), suggesting that the alterations are relevant to behavior.…”

Section: Introductionmentioning

confidence: 99%

Evidence for Two Independent Factors that Modify Brain Networks to Meet Task Goals

Gratton¹,

Laumann²,

Gordon³

et al. 2016

Cell Reports

151

170

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Summary Humans easily and flexibly complete a wide variety of tasks. To accomplish this feat, the brain appears to subtly adjust stable brain networks. Here we investigate what regional factors underlie these modifications, asking whether networks are altered at (a) regions activated by a given task, or (b) hubs that interconnect different networks. We used fMRI ‘functional connectivity’ (FC) to compare networks during rest and three distinct tasks requiring semantic judgments, mental rotation, and visual coherence. We found that network modifications during these tasks were independently associated with both regional activation and network hubs. Furthermore, active and hub regions were associated with distinct patterns of network modification (differing in their localization, topography of FC changes, and variability across tasks), with activated hubs exhibiting patterns consistent with task control. These findings indicate that task goals modify brain networks through two separate processes, linked to local brain function and network hubs.

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Tracking ongoing cognition in individuals using brief, whole-brain functional connectivity patterns

Cited by 335 publications

References 49 publications

Distributed representation of context by intrinsic subnetworks in prefrontal cortex

Distributed representation of context by intrinsic subnetworks in prefrontal cortex

From regions to connections and networks: new bridges between brain and behavior

Evidence for Two Independent Factors that Modify Brain Networks to Meet Task Goals

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