The Task Pre-Configuration Is Associated With Cognitive Performance Evidence From the Brain Synchrony

Xiang, Jie; Fan, Chanjuan; Wei, Jing; Li, Ying; Wang, Bin; Niu, Yan; Yang, Lan; Lv, Jiaqi; Cui, Xiaohong

doi:10.3389/fncom.2022.883660

Cited by 2 publications

(2 citation statements)

References 57 publications

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“…One avenue to explore this theory has been to examine the consistency of sFC between resting-state (during no task) and task-states. This reveals the phenomenon of “update efficiency”, where g positively associates with less required connectivity reconfiguration, aligning with the neural efficiency hypothesis (Schultz and Cole, 2016; Thiele et al, 2022; Xiang et al, 2022).…”

Section: Introductionsupporting

confidence: 79%

“…State 1, characterized by uniform phase direction and highest frequency and target transition probability, has been interpreted as a meta-stable state that individuals tend to return to after engaging "cognitive-processing" states (Cabral et al, 2017;Vohryzek et al, 2020). Lower transition distance between State 1 and other states was associated with higher g. Prior work also demonstrates that update efficiency -similarity between resting-state and task-states -relates to higher cognitive performance (Schultz and Cole, 2016;Thiele et al, 2022;Xiang et al, 2022).…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Higher general intelligence is linked to stable, efficient, and typical dynamic functional brain connectivity patterns

Ng¹,

Yu²,

Feusner³

et al. 2023

Preprint

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The capacity of the brain to adaptively and flexibly reconfigure into different network connectivity patterns may underlie general cognitive ability, or g. Network reconfiguration can be captured via assessments of dynamic connectivity (dFC), which quantifies dominant temporally recurrent connectivity patterns, or “states”, common across the population. While standard dynamic measures focus on quantifying relative time spent within states, or the probability transitioning between states, these metrics fail to capture variability between individuals present in connectivity patterns across states. Here, we provide individualized assessments of connectivity flexibility and stability over time by considering within-state pattern stability, the difference in patterns across state transitions, and how well a given state represents the “typical” state in a particular individual. We leveraged resting-state fMRI data from the large-scale Human Connectome Project and data-driven multivariate Partial Least Squares Correlation to examine emergent relationships between dynamic network properties and cognition. We found that higher g was associated with maintaining distinct states over other states, efficient reconfiguration (i.e., less pattern change during common small-magnitude state transitions such as a state to itself, and greater pattern change among rare transitions between very different states), and less reconfiguration away from population-typical patterns. These results demonstrate that higher cognitive abilities are associated with greater state-specific stability, greater connectivity differences when transitioning between distinct states, and reconfiguration into more typical, potentially optimal, connectivity patterns within states. This suggests a link between general cognition and the efficiency of reconfiguration connectivity patterns into stable, well-defined, and typical network states.Significance StatementCognitive performance can be summarized by a general capability - “g”. g has been associated with academic and professional achievement and is critical in a world where higher-order cognition is increasingly necessary to excel. Attempts to improve g are hampered by a lack of mechanistic understanding. A recent theory suggests that the capacity to reconfigure brain connectivity drives g. We investigate metrics which characterize switches in recurring dominant connectivity patterns and propose novel metrics which investigate connectivity changes during the switches and connectivity pattern deviation from the population. Our findings suggest that g is associated with the maintenance of special patterns, greater pattern changes when necessary, and having population-typical patterns. This advances our understanding of g and informs future interventions.

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Section: Introductionsupporting

confidence: 79%

Section: Discussionmentioning

confidence: 99%

Higher general intelligence is linked to stable, efficient, and typical dynamic functional brain connectivity patterns

Ng¹,

Yu²,

Feusner³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

Higher general intelligence is associated with stable, efficient, and typical dynamic functional brain connectivity patterns

Ng,

Yu,

Feusner

et al. 2024

Imaging Neuroscience

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General intelligence, referred to as g, is hypothesized to emerge from the capacity to dynamically and adaptively reorganize macroscale brain connectivity. Temporal reconfiguration can be assessed using dynamic functional connectivity (dFC), which captures the propensity of brain connectivity to transition between a recurring repertoire of distinct states. Conventional dFC metrics commonly focus on categorical state switching frequencies which do not fully assess individual variation in continuous connectivity reconfiguration. Here, we supplement frequency measures by quantifying within-state connectivity consistency, dissimilarity between connectivity across states, and conformity of individual connectivity to group-average state connectivity. We utilized resting-state functional magnetic resonance imaging (fMRI) data from the large-scale Human Connectome Project and applied data-driven multivariate Partial Least Squares Correlation to explore emergent associations between dynamic network properties and cognitive ability. Our findings reveal a positive association between g and the stable maintenance of states characterized by distinct connectivity between higher-order networks, efficient reconfiguration (i.e., minimal connectivity changes during transitions between similar states, large connectivity changes between dissimilar states), and ability to sustain connectivity close to group-average state connectivity. This hints at fundamental properties of brain–behavior organization, suggesting that general cognitive processing capacity may be supported by the ability to efficiently reconfigure between stable and population-typical connectivity patterns.

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The Task Pre-Configuration Is Associated With Cognitive Performance Evidence From the Brain Synchrony

Cited by 2 publications

References 57 publications

Higher general intelligence is linked to stable, efficient, and typical dynamic functional brain connectivity patterns

Higher general intelligence is linked to stable, efficient, and typical dynamic functional brain connectivity patterns

Higher general intelligence is associated with stable, efficient, and typical dynamic functional brain connectivity patterns

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