scholarly journals Cognitive task information is transferred between brain regions via resting-state network topology

2017 ◽  
Author(s):  
Takuya Ito ◽  
Kaustubh R. Kulkarni ◽  
Douglas H. Schultz ◽  
Ravi D. Mill ◽  
Richard H. Chen ◽  
...  
Keyword(s):  
Network Topology ◽  
Resting State ◽  
Cognitive Abilities ◽  
Information Transfer ◽  
Large Scale ◽  
Cognitive Task ◽  
Network Connectivity ◽  
Brain Regions ◽  
Task Rule ◽  
Resting State Network

AbstractResting-state network connectivity has been associated with a variety of cognitive abilities, yet it remains unclear how these connectivity properties might contribute to the neurocognitive computations underlying these abilities. We developed a new approach – information transfer mapping – to test the hypothesis that resting-state functional network topology describes the computational mappings between brain regions that carry cognitive task information. Here we report that the transfer of diverse, task-rule information in distributed brain regions can be predicted based on estimated activity flow through resting-state network connections. Further, we find that these task-rule information transfers are coordinated by global hub regions within cognitive control networks. Activity flow over resting-state connections thus provides a large-scale network mechanism for cognitive task information transfer and global information coordination in the human brain, demonstrating the cognitive relevance of resting-state network topology.

scholarly journals Cognitive task information is transferred between brain regions via resting-state network topology

2017 ◽  
Vol 8 (1) ◽  
Author(s):  
Takuya Ito ◽  
Kaustubh R. Kulkarni ◽  
Douglas H. Schultz ◽  
Ravi D. Mill ◽  
Richard H. Chen ◽  
...  
Keyword(s):  
Network Topology ◽  
Resting State ◽  
Cognitive Task ◽  
Brain Regions ◽  
Resting State Network

scholarly journals Effects of dopamine agonist treatment on resting-state network connectivity in Parkinson’s disease

2020 ◽  
Author(s):  
David M. Cole ◽  
Bahram Mohammadi ◽  
Maria Milenkova ◽  
Katja Kollewe ◽  
Christoph Schrader ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Decision Making ◽  
Parkinson's Disease ◽  
Basal Ganglia ◽  
Dopamine Agonist ◽  
Resting State ◽  
Large Scale ◽  
Network Connectivity ◽  
Resting State Network ◽  
Large Scale Networks

ABSTRACTDopamine agonist (DA) medications commonly used to treat, or ‘normalise’, motor symptoms of Parkinson’s disease (PD) may lead to cognitive-neuropsychiatric side effects, such as increased impulsivity in decision-making. Subject-dependent variation in the neural response to dopamine modulation within cortico-basal ganglia circuitry is thought to play a key role in these latter, non-motor DA effects. This neuroimaging study combined resting-state functional magnetic resonance imaging (fMRI) with DA modification in patients with idiopathic PD, investigating whether brain ‘resting-state network’ (RSN) functional connectivity metrics identify disease-relevant effects of dopamine on systems-level neural processing. By comparing patients both ‘On’ and ‘Off’ their DA medications with age-matched, un-medicated healthy control subjects (HCs), we identified multiple non-normalising DA effects on frontal and basal ganglia RSN cortico-subcortical connectivity patterns in PD. Only a single isolated, potentially ‘normalising’, DA effect on RSN connectivity in sensori-motor systems was observed, within cerebro-cerebellar neurocircuitry. Impulsivity in reward-based decision-making was positively correlated with ventral striatal connectivity within basal ganglia circuitry in HCs, but not in PD patients. Overall, we provide brain systems-level evidence for anomalous DA effects in PD on large-scale networks supporting cognition and motivated behaviour. Moreover, findings suggest that dysfunctional striatal and basal ganglia signalling patterns in PD are compensated for by increased recruitment of other cortico-subcortical and cerebro-cerebellar systems.

Activity flow over resting-state networks shapes cognitive task activations

2016 ◽  
Author(s):  
Michael W. Cole ◽  
Takuya Ito ◽  
Danielle S. Bassett ◽  
Douglas H. Schultz
Keyword(s):  
Resting State ◽  
Large Scale ◽  
Cognitive Task ◽  
Brain Regions ◽  
Resting State Networks ◽  
Resting State Functional Connectivity ◽  
Activation Patterns ◽  
Distributed Processes ◽  
Evoked Activity ◽  
Task Activation

AbstractResting-state functional connectivity (FC) has helped reveal the intrinsic network organization of the human brain, yet its relevance to cognitive task activations has been unclear. Uncertainty remains despite evidence that resting-state FC patterns are highly similar to cognitive task activation patterns. Identifying the distributed processes that shape localized cognitive task activations may help reveal why resting-stateFC is so strongly related to cognitive task activations. We found that estimating task-evoked activity flow (the spread of activation amplitudes) over resting-state FC networks allows prediction of cognitive task activations in a large-scale neural network model. Applying this insight to empirical functional MRI data, we found that cognitive task activations can be predicted in held-out brain regions (and held-out individuals via estimated activity flow over resting-state FC networks. This suggests that task-evoked activity flow over intrinsic networks is a large-scale mechanism explaining the relevance of resting-state FC to cognitive task activations.

Revisiting default mode network function in major depression: evidence for disrupted subsystem connectivity

2013 ◽  
Vol 44 (10) ◽  
pp. 2041-2051 ◽  
Author(s):  
F. Sambataro ◽  
N. D. Wolf ◽  
M. Pennuto ◽  
N. Vasic ◽  
R. C. Wolf
Keyword(s):  
Default Mode Network ◽  
Resting State ◽  
Large Scale ◽  
Critical Role ◽  
Low Frequency ◽  
Network Connectivity ◽  
Brain Regions ◽  
Default Mode ◽  
Network Function ◽  
Functional Relevance

BackgroundMajor depressive disorder (MDD) is characterized by alterations in brain function that are identifiable also during the brain's ‘resting state’. One functional network that is disrupted in this disorder is the default mode network (DMN), a set of large-scale connected brain regions that oscillate with low-frequency fluctuations and are more active during rest relative to a goal-directed task. Recent studies support the idea that the DMN is not a unitary system, but rather is composed of smaller and distinct functional subsystems that interact with each other. The functional relevance of these subsystems in depression, however, is unclear.MethodHere, we investigated the functional connectivity of distinct DMN subsystems and their interplay in depression using resting-state functional magnetic resonance imaging.ResultsWe show that patients with MDD exhibit increased within-network connectivity in posterior, ventral and core DMN subsystems along with reduced interplay from the anterior to the ventral DMN subsystems.ConclusionsThese data suggest that MDD is characterized by alterations of subsystems within the DMN as well as of their interactions. Our findings highlight a critical role of DMN circuitry in the pathophysiology of MDD, thus suggesting these subsystems as potential therapeutic targets.

scholarly journals Functional network topology of the right insula affects emotion dysregulation in hyperactive-impulsive attention-deficit/hyperactivity disorder

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Tammo Viering ◽  
Pieter J. Hoekstra ◽  
Alexandra Philipsen ◽  
Jilly Naaijen ◽  
Andrea Dietrich ◽  
...  
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
Network Topology ◽  
Resting State ◽  
Latent Variable ◽  
Emotion Dysregulation ◽  
Adult Adhd ◽  
Brain Regions ◽  
Graph Analysis ◽  
Hyperactivity Disorder ◽  
The Right

AbstractEmotion dysregulation is common in attention-deficit/hyperactivity disorder (ADHD). It is highly prevalent in young adult ADHD and related to reduced well-being and social impairments. Neuroimaging studies reported neural activity changes in ADHD in brain regions associated with emotion processing and regulation. It is however unknown whether deficits in emotion regulation relate to changes in functional brain network topology in these regions. We used a combination of graph analysis and structural equation modelling (SEM) to analyze resting-state functional connectivity in 147 well-characterized young adults with ADHD and age-matched healthy controls from the NeuroIMAGE database. Emotion dysregulation was gauged with four scales obtained from questionnaires and operationalized through a latent variable derived from SEM. Graph analysis was applied to resting-state data and network topology measures were entered into SEM models to identify brain regions whose local network integration and connectedness differed between subjects and was associated with emotion dysregulation. The latent variable of emotion dysregulation was characterized by scales gauging emotional distress, emotional symptoms, conduct symptoms, and emotional lability. In individuals with ADHD characterized by prominent hyperactivity-impulsivity, the latent emotion dysregulation variable was related to an increased clustering and local efficiency of the right insula. Thus, in the presence of hyperactivity-impulsivity, clustered network formation of the right insula may underpin emotion dysregulation in young adult ADHD.

scholarly journals Cognitive impairment and resting-state network connectivity in Parkinson's disease

2014 ◽  
Vol 36 (1) ◽  
pp. 199-212 ◽  
Author(s):  
Hugo-Cesar Baggio ◽  
Bàrbara Segura ◽  
Roser Sala-Llonch ◽  
Maria-José Marti ◽  
Francesc Valldeoriola ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cognitive Impairment ◽  
Resting State ◽  
Network Connectivity ◽  
Resting State Network

scholarly journals Stroke-related alterations in inter-areal communication revealed via Granger causality analysis

2021 ◽  
Author(s):  
Michele Allegra ◽  
Chiara Favaretto ◽  
Nicholas Metcalf ◽  
Maurizio Corbetta ◽  
Andrea Brovelli
Keyword(s):  
Functional Connectivity ◽  
Granger Causality ◽  
Resting State ◽  
Information Transfer ◽  
Large Scale ◽  
Functional Organization ◽  
Information Flows ◽  
Causality Analysis ◽  
Stroke Patients ◽  
Granger Causality Analysis

ABSTRACTNeuroimaging and neurological studies suggest that stroke is a brain network syndrome. While causing local ischemia and cell damage at the site of injury, stroke strongly perturbs the functional organization of brain networks at large. Critically, functional connectivity abnormalities parallel both behavioral deficits and functional recovery across different cognitive domains. However, the reasons for such relations remain poorly understood. Here, we tested the hypothesis that alterations in inter-areal communication underlie stroke-related modulations in functional connectivity (FC). To this aim, we used resting-state fMRI and Granger causality analysis to quantify information transfer between brain areas and its alteration in stroke. Two main large-scale anomalies were observed in stroke patients. First, inter-hemispheric information transfer was strongly decreased with respect to healthy controls. Second, information transfer within the affected hemisphere, and from the affected to the intact hemisphere was reduced. Both anomalies were more prominent in resting-state networks related to attention and language, and they were correlated with impaired performance in several behavioral domains. Overall, our results support the hypothesis that stroke perturbs inter-areal communication within and across hemispheres, and suggest novel therapeutic approaches aimed at restoring normal information flow.SIGNIFICANCE STATEMENTA thorough understanding of how stroke perturbs brain function is needed to improve recovery from the severe neurological syndromes affecting stroke patients. Previous resting-state neuroimaging studies suggested that interaction between hemispheres decreases after stroke, while interaction between areas of the same hemisphere increases. Here, we used Granger causality to reconstruct information flows in the brain at rest, and analyze how stroke perturbs them. We showed that stroke causes a global reduction of inter-hemispheric communication, and an imbalance between the intact and the affected hemisphere: information flows within and from the latter are impaired. Our results may inform the design of stimulation therapies to restore the functional balance lost after stroke.

Abstract W P29: Tissue Plasminogen Activator Mediated Reperfusion, and Subsequent Improvement in Resting State Connectivity Correlates with Functional Outcome in Acute Ischemic Stroke Patients

Stroke ◽  
2015 ◽  
Vol 46 (suppl_1) ◽  
Author(s):  
Souvik Sen ◽  
Johann Fridriksson ◽  
Taylor Hanayik ◽  
Christopher Rorden ◽  
Isabel Hubbard ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Functional Connectivity ◽  
Functional Outcome ◽  
Resting State ◽  
Network Connectivity ◽  
Stroke Patients ◽  
Post Stroke ◽  
Resting State Network ◽  
Tissue Plasminogen

Background: Intravenous Tissue Plasminogen Activator (TPA) is the only FDA approved medical therapy for acute ischemic stroke (AIS). Prior study suggests that early recanalization is associated with better stroke outcome. Our aim was to correlate task-negative and task-positive (TN/TP) resting state network activity with tissue perfusion and functional outcome, in stroke patients who received TPA. Method: AIS patients were consented and underwent NIH stroke scale (NIHSS) assessment and magnetic resonance imaging (MRI) scans during TPA infusion (baseline) and six hours post stroke. The MRI sequences include contrast-enhanced perfusion weighted image (PWI) and resting state Blood Oxygen Level-Dependent or BOLD (RSB) images acquired using a Siemens Treo 3T MRI scanner. Additionally, the RSB scan and the NIHSS were obtained at a 30-day follow up visit. Results: Fourteen patients (mean age ± SD=63 ±14, 50% male, 50% white, 43% black and 7% others) who qualified for TPA completed the study at baseline and 6 hours post stroke. Of these, 6 patients had valid follow up data at 30 days. Three patients without cerebral ischemia were excluded. A paired samples t-test comparing baseline and 6h post stroke showed a significantly improved TP network t(10)= -4.24 p< 0.05. The resting network connectivity improved from 6 hours post stroke to 30-days follow up, t(5)= -5.35 p< 0.01. Similarly, NIHSS, at 6h post stroke t(10)= 3.62 p< 0.01 and at 30-days follow up t(5)= -3.4 p< 0.01 were significantly better than the NIHSS at baseline. The 6-hours post-stroke perfusion correlated with the resting network connectivity in both the damaged (r=-0.56 p= 0.07) and intact hemispheres (r= -0.57 p= 0.06). Differences in functional connectivity and NIHSS scores from baseline to 6 h were positively correlated (r= 0.56 p=0.07). Conclusion: In this pilot study we found that TPA led to changes in MRI based resting state networks and associated functional outcome. Correlations were found between perfusion, functional connectivity and NIHSS. This suggests that the improvement of resting state network means improved efficiency of brain activity indicated by functional outcome and may be a potential predictive MRI biomarker for TPA response. A larger study is needed to verify this finding.

scholarly journals Altered topology of large-scale structural brain networks in chronic stroke

2019 ◽  
Vol 1 (1) ◽  
Author(s):  
Bastian Cheng ◽  
Eckhard Schlemm ◽  
Robert Schulz ◽  
Marlene Boenstrup ◽  
Arnaud Messé ◽  
...  
Keyword(s):  
Information Transfer ◽  
Large Scale ◽  
Neuronal Degeneration ◽  
Brain Networks ◽  
Brain Regions ◽  
Local Network ◽  
Structural Connectome ◽  
The Impact ◽  
Structural Brain ◽  
Topological Changes

Abstract Beyond disruption of neuronal pathways, focal stroke lesions induce structural disintegration of distant, yet connected brain regions via retrograde neuronal degeneration. Stroke lesions alter functional brain connectivity and topology in large-scale brain networks. These changes are associated with the degree of clinical impairment and recovery. In contrast, changes of large scale, structural brain networks after stroke are less well reported. We therefore aimed to analyse the impact of focal lesions on the structural connectome after stroke based on data from diffusion-weighted imaging and probabilistic fibre tracking. In total, 17 patients (mean age 64.5 ± 8.4 years) with upper limb motor deficits in the chronic stage after stroke and 21 healthy participants (mean age 64.9 ± 10.3 years) were included. Clinical deficits were evaluated by grip strength and the upper extremity Fugl-Meyer assessment. We calculated global and local graph theoretical measures to characterize topological changes in the structural connectome. Results from our analysis demonstrated significant alterations of network topology in both ipsi- and contralesional, primarily unaffected, hemispheres after stroke. Global efficiency was significantly lower in stroke connectomes as an indicator of overall reduced capacity for information transfer between distant brain areas. Furthermore, topology of structural connectomes was shifted toward a higher degree of segregation as indicated by significantly higher values of global clustering and modularity. On a level of local network parameters, these effects were most pronounced in a subnetwork of cortico-subcortical brain regions involved in motor control. Structural changes were not significantly associated with clinical measures. We propose that the observed network changes in our patients are best explained by the disruption of inter- and intrahemispheric, long white matter fibre tracts connecting distant brain regions. Our results add novel insights on topological changes of structural large-scale brain networks in the ipsi- and contralesional hemisphere after stroke.

scholarly journals Effects of Cognitive Training in Mild Cognitive Impairmentmeasured by Resting State Functional Imaging

2020 ◽  
Vol 10 (11) ◽  
pp. 175
Author(s):  
Seungho Kim ◽  
Eunhee Park ◽  
Hyunsil Cha ◽  
Jae-Chang Jung ◽  
Tae-Du Jung ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Training Program ◽  
Cognitive Training ◽  
Resting State ◽  
Cognitive Abilities ◽  
Motor Coordination ◽  
Network Connectivity ◽  
Functional Magnetic Resonance ◽  
Function Test ◽  
The Brain

Mild cognitive impairment (MCI) is defined as an intermediate state of cognitive alteration between normal aging and dementia. In this study, we performed a functional network connectivity analysis using resting-state functional magnetic resonance imaging to investigate the association between changes in functional connectivity in the brain and the improvement in cognitive abilities after cognitive training. A computerized cognitive training program was used to improve the abilities of fifteen participants with MCI. The cognitive training program (Comcog), which consists of three weekly sessions totaling 90 min, was conducted with all participants over six weeks. The cognitive abilities before (pre-Comcog) and after (post-Comcog) the cognitive training process were measured using a neurocognitive function test. After the Comcog, the participants enhanced their visual and verbal memories, attention, and visuo-motor coordination. The functional connectivity between cingulo-opercular (CON) and default mode (DMN) showed significant improvements after Comcog training. Therefore, our study suggests that cognitive training may improve the cognitive abilities of participants. This improvement was associated with an increase in the functional connectivity between DMN and CON. The increase in functional connectivity after cognitive training was specifically associated with overall cognitive functions, including executive, memory, decision-making, and motivational functions.

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