Transition of the functional brain network related to increasing cognitive demands

Finc, Karolina; Bonna, Kamil; Lewandowska, Monika; Wolak, Tomasz; Nikadon, Jan; Dreszer, Joanna; Duch, Włodzisław; Kühn, Simone

doi:10.1002/hbm.23621

Cited by 90 publications

(94 citation statements)

References 87 publications

(151 reference statements)

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“…5A). Our results are corroborated by recent studies that examined the relationship between cognitive load for the n-back task and network integration using both static [15,[38][39] and time-varying functional connectivity measures [21,30,32,41].…”

Section: Differences In Cognitive Load During the Working Memory Expesupporting

confidence: 89%

Brain network segregation and integration during an epoch-related working memory fMRI experiment

Fransson

Schiffler

Thompson

2018

Preprint

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The characterization of brain subnetwork segregation and integration has previously focused on changes that are detectable at the level of entire sessions or epochs of imaging data. In this study, we applied time-varying functional connectivity analysis together with temporal network theory to calculate point-by-point estimates in subnetwork segregation and integration during an epoch-based (2-back, 0-back, baseline) working memory fMRI experiment as well as during resting-state. This approach allowed us to follow task-related changes in subnetwork segregation and integration at a high temporal resolution. At a global level, the cognitively more taxing 2-back epochs elicited an overall stronger response of integration between subnetworks compared to the 0-back epochs. Moreover, the visual and fronto-parietal subnetworks displayed characteristic and distinct temporal profiles of segregation and integration during the 0-and 2-back epochs. During the interspersed epochs of baseline, many subnetworks, including the default mode, visual, fronto-parietal, cingulo-opercular and dorsal attention subnetworks showed pronounced increases in segregation. Using a drift diffusion model we show that the response time for the 2-back trials are correlated with integration for the fronto-parietal subnetwork and correlated with segregation for the visual subnetwork. Our results elucidate the fastevolving events with regard to subnetwork integration and segregation that occur in an epoch-related task fMRI experiment. Our findings suggest that minute changes in subnetwork integration are of importance for task performance.

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Section: Differences In Cognitive Load During the Working Memory Expesupporting

confidence: 89%

Brain network segregation and integration during an epoch-related working memory fMRI experiment

Fransson

Schiffler

Thompson

2018

Preprint

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“…In other words, the conscious stage accommodates, or receives signals from transient actors (of various sensory modalities, e.g., auditory, tactile, and visual) that are guided by a) priority maps and context setting about the self, world, and others (e.g., Zelinsky and Bisley, 2015 ; Trask et al, 2016 ) that may over time become unconscious, and (b) by an unconscious audience (self-precepts, automatisms, memories, and language). Recent functional connectivity analyses (e.g., hub detection and network-based statistics) have provided support for the Global Workspace Theory, demonstrating how functional networks in the brain reorganize according to higher cognitive loads, particularly during the n -back WM task ( Finc et al, 2017 ). In particular, it appears that network modularity decreases as cognitive load (on the n -back WM task) increases; specifically, far-reaching network hubs increase but local hubs decrease in conjunction with greater global connectivity with the DMN ( Finc et al, 2017 ).…”

Section: Theories Of Working Memory and Cognitive Control In The Healmentioning

confidence: 99%

The Role of Working Memory for Cognitive Control in Anorexia Nervosa versus Substance Use Disorder

et al. 2017

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Prefrontal cortex executive functions, such as working memory (WM) interact with limbic processes to foster impulse control. Such an interaction is referred to in a growing body of publications by terms such as cognitive control, cognitive inhibition, affect regulation, self-regulation, top-down control, and cognitive–emotion interaction. The rising trend of research into cognitive control of impulsivity, using various related terms reflects the importance of research into impulse control, as failure to employ cognitions optimally may eventually result in mental disorder. Against this background, we take a novel approach using an impulse control spectrum model – where anorexia nervosa (AN) and substance use disorder (SUD) are at opposite extremes – to examine the role of WM for cognitive control. With this aim, we first summarize WM processes in the healthy brain in order to frame a systematic review of the neuropsychological, neural and genetic findings of AN and SUD. In our systematic review of WM/cognitive control, we found n = 15 studies of AN with a total of n = 582 AN and n = 365 HC participants; and n = 93 studies of SUD with n = 9106 SUD and n = 3028 HC participants. In particular, we consider how WM load/capacity may support the neural process of excessive epistemic foraging (cognitive sampling of the environment to test predictions about the world) in AN that reduces distraction from salient stimuli. We also consider the link between WM and cognitive control in people with SUD who are prone to ‘jumping to conclusions’ and reduced epistemic foraging. Finally, in light of our review, we consider WM training as a novel research tool and an adjunct to enhance treatment that improves cognitive control of impulsivity.

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“…These dynamic fluctuations have been associated with consciousness (Barttfeld et al, 2015;Godwin et al, 2015), learning (Bassett et al, 2011), behavioral responses, and cognitive functions (Cole et al, 2014;Shine et al, 2016), as well as neurodegenerative disorders (Rashid et al, 2016;Zhang et al, 2016). For instance, the integration between specific communities (or modules) of the brain has been shown to increase during a cognitive task (Braun et al, 2015;Finc et al, 2017), and dynamic changes of brain network modular organization have been associated with learning success (Bassett et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Using Low-Dimensional Manifolds to Map Relationships Between Dynamic Brain Networks

Bahrami

Lyday

Casanova

et al. 2019

Front. Hum. Neurosci.

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As the field of dynamic brain networks continues to expand, new methods are needed to allow for optimal handling and understanding of this explosion in data. We propose here a novel approach that embeds dynamic brain networks onto a two-dimensional (2D) manifold based on similarities and differences in network organization. Each brain network is represented as a single point on the low dimensional manifold with networks of similar topology being located in close proximity. The rich spatio-temporal information has great potential for visualization, analysis, and interpretation of dynamic brain networks. The fact that each network is represented by a single point makes it possible to switch between the low-dimensional space and the full connectivity of any given brain network. Thus, networks in a specific region of the low-dimensional space can be examined to identify network features, such as the location of brain network hubs or the interconnectivity between brain circuits. In this proof-of-concept manuscript, we show that these low dimensional manifolds contain meaningful information, as they were able to successfully discriminate between cognitive tasks and study populations. This work provides evidence that embedding dynamic brain networks onto low dimensional manifolds has the potential to help us better visualize and understand dynamic brain networks with the hope of gaining a deeper understanding of normal and abnormal brain dynamics.

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Transition of the functional brain network related to increasing cognitive demands

Cited by 90 publications

References 87 publications

Brain network segregation and integration during an epoch-related working memory fMRI experiment

Brain network segregation and integration during an epoch-related working memory fMRI experiment

The Role of Working Memory for Cognitive Control in Anorexia Nervosa versus Substance Use Disorder

Using Low-Dimensional Manifolds to Map Relationships Between Dynamic Brain Networks

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