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

Fransson, Peter; Schiffler, Björn C.; Thompson, William Hedley

doi:10.1016/j.neuroimage.2018.05.040

Cited by 38 publications

(30 citation statements)

References 59 publications

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“…Second, as a result of the cross-section nature of this study, it is unclear that brain function differences we found are directly caused by Baduk training or they are pre-existing group differences that predict whether or not a person takes up Baduk rather than a result of that training. Third, considering previous studies showing an interaction between resting-state activity and stimulus-induced activity ( Northoff et al, 2010 ; Fransson et al, 2018 ) and significant differences in resting-state activity between experts and novices ( Jung et al, 2013 ; Dong et al, 2014 , 2015 ), it is speculated that different resting-state activity patterns between the two groups may be the foundation for the activity difference during task-state. Further research with both resting-state and task-stat fMRI will help to clarify this issue.…”

Section: Discussionmentioning

confidence: 95%

Beyond Domain-Specific Expertise: Neural Signatures of Face and Spatial Working Memory in Baduk (Go Game) Experts

Jung

Lee

Yoon

et al. 2018

Front. Hum. Neurosci.

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Recent advances of neuroimaging methodology and artificial intelligence have resulted in renewed interest in board games like chess and Baduk (called Go game in the West) and have provided clues as to the mechanisms behind the games. However, an interesting question that remains to be answered is whether the board game expertise as one of cognitive skills goes beyond just being good at the trained game and how it maps on networks associated with cognitive abilities that are not directly trained. To address this issue, we examined functional activity and connectivity in Baduk experts, compared to novices, while performing a visual n-back working memory (WM) task. We found that experts, compared to novices, had greater activation in superior parietal cortex during face WM, though there were no group differences in behavioral performances. Using a data-driven, whole-brain multivariate approach, we also found significant group differences in the multivariate pattern of connectivity in frontal pole and inferior parietal cortex, further showing greater connectivity between frontal and parietal regions and between frontal and temporal regions in experts. Our findings suggest that long-term trained Baduk experts have the reorganization of functional interactions between brain regions even for untrained cognitive ability.

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Section: Discussionmentioning

confidence: 95%

Beyond Domain-Specific Expertise: Neural Signatures of Face and Spatial Working Memory in Baduk (Go Game) Experts

Jung

Lee

Yoon

et al. 2018

Front. Hum. Neurosci.

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“…A novel work suggests, again, a cross-modal recruitment of sensory related short-term memory where visual memory implicated also auditory regions and, vice versa, auditory short-term memory was associated with the activity of the dorsal and ventral visual pathways (Michalka et al, 2015). Moreover, a recent work has shown fast modifications of functional connectomes and remarked the importance of even minute topological changes for the global network capacity to integrate information (Fransson et al, 2018). Eventually, our previous study focused on the alternating dynamics of segregation and integration in a visual working memory task suggested that the interchange of segregation-integration required a quasi-continuous coherent activation of most of the recorded cortical regions resulting in a global complex network orchestration (Zippo et al, 2018).…”

Section: Discussionmentioning

confidence: 96%

Short-Term Classification Learning Promotes Rapid Global Improvements of Information Processing in Human Brain Functional Connectome

Zippo

Castiglioni

Lin

et al. 2020

Front. Hum. Neurosci.

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Classification learning is a preeminent human ability within the animal kingdom but the key mechanisms of brain networks regulating learning remain mostly elusive. Recent neuroimaging advancements have depicted human brain as a complex graph machinery where brain regions are nodes and coherent activities among them represent the functional connections. While long-term motor memories have been found to alter functional connectivity in the resting human brain, a graph topological investigation of the short-time effects of learning are still not widely investigated. For instance, classification learning is known to orchestrate rapid modulation of diverse memory systems like short-term and visual working memories but how the brain functional connectome accommodates such modulations is unclear. We used publicly available repositories (openfmri.org) selecting three experiments, two focused on short-term classification learning along two consecutive runs where learning was promoted by trial-by-trial feedback errors, while a further experiment was used as supplementary control. We analyzed the functional connectivity extracted from BOLD fMRI signals, and estimated the graph information processing in the cerebral networks. The information processing capability, characterized by complex network statistics, significantly improved over runs, together with the subject classification accuracy. Instead, null-learning experiments, where feedbacks came with poor consistency, did not provoke any significant change in the functional connectivity over runs. We propose that learning induces fast modifications in the overall brain network dynamics, definitely ameliorating the shortterm potential of the brain to process and integrate information, a dynamic consistently orchestrated by modulations of the functional connections among specific brain regions.

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“…Every possible state corresponds to one unique point in state-space, and the temporal evolution of the system in state-space traces a path which is called the "state-space trajectory". Here, we apply a dynamical systems perspective to assess how individual brain networks interact with each other across time, all the while the configurations of both intra-and inter-network (in this study, the DMN) connectivity are retained, which is in contrast to previously used reductionist methods of computing network segregation as one single measure averaged across the whole scan (Chan et al, 2014), or as a single time-varying measure (Fransson et al, 2018;Fukushima et al, 2018).…”

Section: Construction Of State-space Trajectories For Network Interacmentioning

confidence: 99%

Dynamic synergetic configurations of resting-state networks in ADHD

Kaboodvand

Iravani

Fransson

2019

Preprint

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Attention deficit hyperactivity disorder (ADHD) is characterized by high distractibility and impaired executive functions. Notably, there is mounting evidence suggesting that ADHD could be regarded as a default mode network (DMN) disorder. In particular, failure in regulating the dynamics of activity and interactions of the DMN and cognitive control networks have been hypothesized as the main source of task interference causing attentional problems. On the other hand, previous studies indicated pronounced fluctuations in the strength of functional connections over time, particularly for the internetwork connections between the DMN and fronto-parietal control networks. Hence, characterization of connectivity disturbances in ADHD disorder requires a thorough assessment of time-varying FCs. In this study, we propose a dynamical systems perspective to assess how the DMN over time recruits different configurations of network segregation and integration. Specifically, we were interested in configurations for which both intra-and inter-network connections are retained, as opposed to commonly used methods which assess network segregation as a single measure. From resting-state fMRI data, we extracted three different stable configurations of FC patterns for the DMN, namely synergies. We provide evidence supporting our hypothesis that the ADHD brain differs in both recruitment rate and the topology of specific synergies between restingstate networks.

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

Cited by 38 publications

References 59 publications

Beyond Domain-Specific Expertise: Neural Signatures of Face and Spatial Working Memory in Baduk (Go Game) Experts

Beyond Domain-Specific Expertise: Neural Signatures of Face and Spatial Working Memory in Baduk (Go Game) Experts

Short-Term Classification Learning Promotes Rapid Global Improvements of Information Processing in Human Brain Functional Connectome

Dynamic synergetic configurations of resting-state networks in ADHD

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