Individual variability in functional connectivity predicts performance of a perceptual task

Baldassarre, Antonello; Lewis, Chris; Committeri, Giorgia; Snyder, Abraham Z.; Romani, Gian Luca; Corbetta, Maurizio

doi:10.1073/pnas.1113148109

Cited by 244 publications

(201 citation statements)

References 51 publications

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“…These changes in rs-FC may reflect intrinsic and stable modifications related to vocabulary learning. This result agrees with previous studies showing that training in specific functions increased FC between local and distant brain areas involved in learning a new task (Lewis et al 2009;Baldassarre et al 2012;Ventura-Campos et al 2013). Therefore spontaneous activity patterns in the rs-fMRI may reflect a priori biases and the individual's propensities as a result of experience (Harmelech and Malach 2013).…”

Section: -Relationship Between Auditory and Motor Regions At Restsupporting

confidence: 92%

“…Previous studies have shown that the intensity of correlations within and between brain areas at rest has behavioral significance (Harmelech and Malach 2013;Guerra-Carrillo et al 2014;Finn et al 2015), and that the resting-state activity may reflect the repeated history of co-activation within or between brain regions, which may in turn be a predictor of individual differences while performing perceptual, intelligence, and memory tasks (Lewis et al 2009;Baldassarre et al 2012;Cole et al 2012;Ventura-Campos et al 2013;Bueichekú et al 2015).…”

Section: Introductionmentioning

confidence: 99%

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The dynamic imprint of word learning on the dorsal language pathway

et al. 2017

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According to Hickok and Poeppel (2007), the acquisition of new vocabulary rests on the dorsal language pathway connecting auditory and motor areas. The present study tested this hypothesis longitudinally by measuring BOLD signal changes during a verbal repetition task and modulation of resting state functional connectivity (rs-FC) in the dorsal stream. Thirty-five healthy participants, divided into trained and control groups, completed fMRI sessions on days 1, 10, and 24. Between days 1 and 10, the trained group learned 84 new pseudowords associated with 84 native words. Task-related fMRI results showed a reduced activity in the IFG and STG while processing the learned vocabulary after training, returning to initial values two weeks later. Moreover, rs-fMRI analysis showed stronger rs-FC between the IFG and STG in the trained group than in the control group after learning, especially on day 24. These neural changes were more evident in participants with a larger vocabulary. Discussion focuses on the prominent role of the dorsal stream in vocabulary acquisition. Even when their meaning was known, newly learned words were again processed through the dorsal stream two weeks after learning, with the increase in rs-FC between auditory and motor areas being a relevant longterm imprint of vocabulary learning.

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Section: -Relationship Between Auditory and Motor Regions At Restsupporting

confidence: 92%

Section: Introductionmentioning

confidence: 99%

The dynamic imprint of word learning on the dorsal language pathway

et al. 2017

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“…Previous studies rated the complexity or novelty of improvised musical [Bengtsson et al, 2007; Villarreal et al, 2013] or literary material [Liu et al, 2012; Shah et al, 2013] and correlated these measures with the amplitude of brain activity. Other studies utilizing sensorimotor tasks [Baldassarre et al, 2012; Koyama et al, 2011] have suggested that performance is strongly associated with functional connections between brain regions. Such relationships have rarely been examined in the domain of creativity before and their interactions with expertise or with different phases of the creative process are unknown.…”

Section: Introductionmentioning

confidence: 99%

Brain activity and connectivity during poetry composition: Toward a multidimensional model of the creative process

Liu

Erkkinen

Healey

et al. 2015

Human Brain Mapping

143

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Creativity, a multifaceted construct, can be studied in various ways, for example, investigating phases of the creative process, quality of the creative product, or the impact of expertise. Previous neuroimaging studies have assessed these individually. Believing that each of these interacting features must be examined simultaneously to develop a comprehensive understanding of creative behavior, we examined poetry composition, assessing process, product, and expertise in a single experiment. Distinct activation patterns were associated with generation and revision, two major phases of the creative process. Medial prefrontal cortex (MPFC) was active during both phases, yet responses in dorsolateral prefrontal and parietal executive systems (DLPFC/IPS) were phase‐dependent, indicating that while motivation remains unchanged, cognitive control is attenuated during generation and re‐engaged during revision. Experts showed significantly stronger deactivation of DLPFC/IPS during generation, suggesting that they may more effectively suspend cognitive control. Importantly however, similar overall patterns were observed in both groups, indicating the same cognitive resources are available to experts and novices alike. Quality of poetry, assessed by an independent panel, was associated with divergent connectivity patterns in experts and novices, centered upon MPFC (for technical facility) and DLPFC/IPS (for innovation), suggesting a mechanism by which experts produce higher quality poetry. Crucially, each of these three key features can be understood in the context of a single neurocognitive model characterized by dynamic interactions between medial prefrontal areas regulating motivation, dorsolateral prefrontal, and parietal areas regulating cognitive control and the association of these regions with language, sensorimotor, limbic, and subcortical areas distributed throughout the brain. Hum Brain Mapp 36:3351–3372, 2015. © 2015 The Authors. Human Brain Mapping Published by Wiley Periodicals, Inc..

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“…6 Furthermore, the coordination of brain activity between disparate brain subnetworks is a dynamic and taskdependent process. [7][8][9][10] Temporal dynamic interactions within brain subnetworks play an important role in supporting brain information processing.…”

Section: Introductionmentioning

confidence: 99%

Spectral properties of the temporal evolution of brain network structure

Wang

Zhang

et al. 2015

Chaos: An Interdisciplinary Journal of Nonlinear Science

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The temporal evolution properties of the brain network are crucial for complex brain processes. In this paper, we investigate the differences in the dynamic brain network during resting and visual stimulation states in a task-positive subnetwork, task-negative subnetwork, and whole-brain network. The dynamic brain network is first constructed from human functional magnetic resonance imaging data based on the sliding window method, and then the eigenvalues corresponding to the network are calculated. We use eigenvalue analysis to analyze the global properties of eigenvalues and the random matrix theory (RMT) method to measure the local properties. For global properties, the shifting of the eigenvalue distribution and the decrease in the largest eigenvalue are linked to visual stimulation in all networks. For local properties, the short-range correlation in eigenvalues as measured by the nearest neighbor spacing distribution is not always sensitive to visual stimulation. However, the long-range correlation in eigenvalues as evaluated by spectral rigidity and number variance not only predicts the universal behavior of the dynamic brain network but also suggests non-consistent changes in different networks. These results demonstrate that the dynamic brain network is more random for the task-positive subnetwork and whole-brain network under visual stimulation but is more regular for the task-negative subnetwork. Our findings provide deeper insight into the importance of spectral properties in the functional brain network, especially the incomparable role of RMT in revealing the intrinsic properties of complex systems. The temporal evolution of brain network structure is crucial to revealing brain functions at different brain states, such as learning, memory, and visual stimulation. The sliding window method is effective for the construction of a dynamic brain network, and complex network analysis has been widely used to characterize these networks. Recently, the spectral property analysis of complex networks has attracted increasing attention based on its ability to measure more intrinsic properties of networks than complex network analysis. In particular, the dynamic brain network constructed from human electroencephalogram (EEG) data has been successfully studied by applying random matrix theory (RMT), which aims to identify the spectral fluctuation properties of networks. However, little is known about the spectral properties of the dynamic brain network based on human functional magnetic resonance imaging (fMRI) data at different brain states, and how spectral properties reflect changes in the dynamic brain network must be explained in greater detail. Here, we addressed these issues and investigated the spectral properties of a dynamic brain network constructed from human fMRI data. We show that the global and local properties of the eigenvalue of the brain network are effective for evaluating the changes in the dynamic brain network caused by visual stimulation. However, the differences between global properties...

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Individual variability in functional connectivity predicts performance of a perceptual task

Cited by 244 publications

References 51 publications

The dynamic imprint of word learning on the dorsal language pathway

The dynamic imprint of word learning on the dorsal language pathway

Brain activity and connectivity during poetry composition: Toward a multidimensional model of the creative process

Spectral properties of the temporal evolution of brain network structure

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