scholarly journals Metastable neural dynamics underlies cognitive performance across multiple behavioural paradigms

2019 ◽  
Author(s):  
Thomas H. Alderson ◽  
Arun L.W. Bokde ◽  
J.A.Scott. Kelso ◽  
Liam Maguire ◽  
Damien Coyle
Keyword(s):  
Cognitive Control ◽  
Cognitive Performance ◽  
Resting State ◽  
Network Architecture ◽  
Large Scale ◽  
Fluid Intelligence ◽  
Coordination Dynamics ◽  
Resting State Networks ◽  
Control Networks ◽  
Local Areas

AbstractDespite resting state networks being associated with a variety of cognitive abilities, it remains unclear how these local areas act in concert to express particular cognitive operations. Theoretical and empirical accounts indicate that large-scale resting state networks reconcile dual tendencies toward integration and segregation by operating in a metastable regime of their coordination dynamics. One proposal is that metastability confers important behavioural qualities by dynamically binding distributed local areas into large-scale neurocognitive entities. We tested this hypothesis by analysing fMRI data in a large cohort of healthy individuals (N=566) and comparing the metastability of the brain’s large-scale resting network architecture at rest and during the performance of several tasks. Task-based reasoning was principally characterised by high metastability in cognitive control networks and low metastability in sensory processing areas. Although metastability between resting state networks increased during task performance, cognitive ability was more closely linked to spontaneous activity. High metastability in the intrinsic connectivity of cognitive control networks was linked to novel problem solving (or fluid intelligence) but was less important in tasks relying on prior experience (or crystallised intelligence). Crucially, subjects with resting architectures similar or ‘pre-configured’ to a task-general arrangement demonstrated superior cognitive performance. Taken together, our findings support a critical linkage between the spontaneous metastability of the large-scale networks of the cerebral cortex and cognition.

scholarly journals Increased amygdala volume and functional connectivity with cognitive control networks in chronic migraine

2020 ◽  
Author(s):  
Danielle D DeSouza ◽  
Samuel R Krimmel ◽  
Bharati M Sanjanwala ◽  
Addie Peretz ◽  
Vinod Menon ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Cognitive Control ◽  
Chronic Migraine ◽  
Resting State ◽  
Large Scale ◽  
Pain Catastrophizing ◽  
Headache Frequency ◽  
Control Networks ◽  
Affective Symptoms ◽  
Amygdala Volume

Objective: To characterize the role of the amygdala in episodic (EM) and chronic (CM) migraine, we evaluated amygdala volumes, functional connectivity (FC), and associations with clinical and affective measures. Methods: Eighty-eight patients (44 with EM and 44 age- and sex-matched patients with CM) completed anatomical and resting-state functional MRI scans. Amygdala volumes and resting-state FC to three core large-scale cognitive control networks (default mode (DMN), salience (SN), central executive (CEN)) were compared between groups. Associations between amygdala volume and FC, measures of headache severity (frequency and intensity), and cognitive-affective measures (depression, anxiety, pain catastrophizing) were evaluated. Results: Compared to EM, patients with CM had larger amygdala volume bilaterally. Headache frequency and intensity were associated with increased left and right amygdala volume, and depression was associated with increased right amygdala volume. Patients with CM also demonstrated increased left amygdala FC with the DMN, which across patients was related to headache frequency. Left amygdala FC to the SN was correlated with headache intensity while right amygdala FC to the CEN was correlated with pain catastrophizing. Conclusion: Our findings reveal increased amygdala volume and FC with large-scale neurocognitive networks in patients with CM compared to EM. Aberrant amygdala volume and FC measures were associated with increased migraine severity, depression, and pain catastrophizing, pointing to a link between emotion and pain in migraine. Our findings provide novel insights into amygdala involvement in chronic migraine and may inform future interventions aimed at preventing the progression of both headache and its negative cognitive-affective symptoms.

scholarly journals Association Between Childhood Anhedonia and Alterations in Large-scale Resting-State Networks and Task-Evoked Activation

2019 ◽  
Vol 76 (6) ◽  
pp. 624 ◽  
Author(s):  
Narun Pornpattananangkul ◽  
Ellen Leibenluft ◽  
Daniel S. Pine ◽  
Argyris Stringaris
Keyword(s):  
Resting State ◽  
Large Scale ◽  
Resting State Networks ◽  
And Task

scholarly journals How the human brain introspects about one’s own episodes of cognitive control

2017 ◽  
Author(s):  
David Soto ◽  
Mona Theodoraki ◽  
Pedro M. Paz-Alonso
Keyword(s):  
Cognitive Control ◽  
Human Brain ◽  
Internal Model ◽  
Large Scale ◽  
Brain Activity ◽  
Temporal Correlation ◽  
Control Networks ◽  
Control Functions ◽  
Cognitive States ◽  
Behavioural Performance

AbstractMetacognition refers to our capacity to reflect upon our experiences, thoughts and actions. Metacognition processes are linked to cognitive control functions that allow keeping our actions on-task. But it is unclear how the human brain builds an internal model of one’s cognition and behaviour. We conducted 2 fMRI experiments in which brain activity was recorded ‘online’ as participants engaged in a memory-guided search task and then later ‘offline’ when participants introspected about their prior experience and cognitive states during performance. In Experiment 1 the memory cues were task-relevant while in Experiment 2 they were irrelevant. Across Experiments, the patterns of brain activity, including frontoparietal regions, were similar during on-task and introspection states. However the connectivity profile amongst frontoparietal areas was distint during introspection and modulated by the relevance of the memory cues. Introspection was also characterized by increased temporal correlation between the default-mode network (DMN), frontoparietal and dorsal attention networks and visual cortex. We suggest that memories of one’s own experience during task performance are encoded in large-scale patterns of brain activity and that coupling between DMN and frontoparietal control networks may be crucial to build an internal model of one’s behavioural performance.

scholarly journals Resting-state fMRI data of awake dogs (Canis familiaris) via group-level independent component analysis reveal multiple, spatially distributed resting-state networks

2018 ◽  
Author(s):  
Dόra Szabό ◽  
Kálmán Czeibert ◽  
Ádám Kettinger ◽  
Márta Gácsi ◽  
Attila Andics ◽  
...  
Keyword(s):  
Independent Component Analysis ◽  
Resting State ◽  
Large Scale ◽  
Functional Organization ◽  
Component Analysis ◽  
Independent Component ◽  
Group Level ◽  
Resting State Networks ◽  
Wide Range ◽  
Spatially Distributed

ABSTRACTResting-state networks are spatially distributed, functionally connected brain regions. Studying these networks gives us information about the large-scale functional organization of the brain and alternations in these networks are considered to play a role in a wide range of neurological conditions and aging. To describe resting-state networks in dogs, we measured 22 awake, unrestrained animals of either sex and carried out group-level spatial independent component analysis to explore whole-brain connectivity patterns. Using resting-state functional magnetic resonance imaging (rs-fMRI), in this exploratory study we found multiple resting-state networks in dogs, which resemble the pattern described in humans. We report the following dog resting-state networks: default mode network (DMN), visual network (VIS), sensorimotor network (SMN), combined auditory (AUD)-saliency (SAL) network and cerebellar network (CER). The DMN, similarly to Primates, but unlike previous studies in dogs, showed antero-posterior connectedness with involvement of hippocampal and lateral temporal regions. The results give us insight into the resting-state networks of awake animals from a taxon beyond rodents through a non-invasive method.

scholarly journals Resting State Networks Related to the Maintenance of Good Cognitive Performance During Healthy Aging

2021 ◽  
Vol 15 ◽  
Author(s):  
Satoshi Maesawa ◽  
Satomi Mizuno ◽  
Epifanio Bagarinao ◽  
Hirohisa Watanabe ◽  
Kazuya Kawabata ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Cognitive Performance ◽  
Negative Correlation ◽  
Resting State ◽  
Healthy Aging ◽  
Cognitive Networks ◽  
Cognitive Test ◽  
Resting State Networks ◽  
Mr Images ◽  
Dual Regression

Purpose: Maintenance of cognitive performance is important for healthy aging. This study aims to elucidate the relationship between brain networks and cognitive function in subjects maintaining relatively good cognitive performance.Methods: A total of 120 subjects, with equal number of participants from each age group between 20 and 70 years, were included in this study. Only participants with Addenbrooke’s Cognitive Examination – Revised (ACE-R) total score greater than 83 were included. Anatomical T1-weighted MR images and resting-state functional MR images (rsfMRIs) were taken from all participants using a 3-tesla MRI scanner. After preprocessing, several factors associated with age including the ACE-R total score, scores of five domains, sub-scores of ACE-R, and brain volumes were tested. Morphometric changes associated with age were analyzed using voxel based morphometry (VBM) and changes in resting state networks (RSNs) were examined using dual regression analysis.Results: Significant negative correlations with age were seen in the total gray matter volume (GMV, r = −0.58), and in the memory, attention, and visuospatial domains. Among the different sub-scores, the score of the delayed recall (DR) showed the highest negative correlation with age (r = −0.55, p < 0.001). In VBM analysis, widespread regions demonstrated negative correlation with age, but none with any of the cognitive scores. Quadratic approximations of cognitive scores as functions of age showed relatively delayed decline compared to total GMV loss. In dual regression analysis, some cognitive networks, including the dorsal default mode network, the lateral dorsal attention network, the right / left executive control network, the posterior salience network, and the language network, did not demonstrate negative correlation with age. Some regions in the sensorimotor networks showed positive correlation with the DR, memory, and fluency scores.Conclusion: Some domains of the cognitive test did not correlate with age, and even the highly correlated sub-scores such as the DR score, showed delayed decline compared to the loss of total GMV. Some RSNs, especially involving cognitive control regions, were relatively maintained with age. Furthermore, the scores of memory, fluency, and the DR were correlated with the within-network functional connectivity values of the sensorimotor network, which supported the importance of exercise for maintenance of cognition.

scholarly journals The human brain’s intrinsic network architecture is organized to represent diverse cognitive task information

2021 ◽  
Author(s):  
Douglas H. Schultz ◽  
Takuya Ito ◽  
Michael W. Cole
Keyword(s):  
Cognitive Control ◽  
Network Architecture ◽  
Cognitive Task ◽  
Global Network ◽  
Connectivity Pattern ◽  
Control Networks ◽  
Domain Generality ◽  
Intrinsic Connectivity ◽  
General Capacity ◽  
Logic Rule

AbstractA set of distributed cognitive control networks are known to contribute to diverse cognitive demands, yet it is unclear how these networks gain this domain-general capacity. We hypothesized that this capacity is largely due to the particular organization of the human brain’s intrinsic network architecture. Specifically, we tested the possibility that each brain region’s domain generality is reflected in its level of global (hub-like) intrinsic connectivity, as well as its particular global connectivity topography. Consistent with prior work, we found that cognitive control networks exhibited domain generality, as they represented diverse task context information covering sensory, motor response, and logic rule domains. Supporting our hypothesis, we found that the level of global intrinsic connectivity (as estimated with task-free fMRI) was correlated with domain generality during tasks. Further, using a novel information fingerprint mapping approach, we found that each brain region’s unique cognitive rule response profile could be predicted based on its unique intrinsic connectivity pattern. Together these results suggest that the human brain’s intrinsic network architecture supports its ability to represent diverse cognitive task information, largely via the placement of cognitive control networks within the brain’s global network organization.

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