scholarly journals Conditional Granger Causality Analysis of Effective Connectivity during Motor Imagery and Motor Execution in Stroke Patients

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Li Wang ◽  
Jingna Zhang ◽  
Ye Zhang ◽  
Rubing Yan ◽  
Hongliang Liu ◽  
...  
Keyword(s):  
Granger Causality ◽  
Motor Function ◽  
Motor Imagery ◽  
Effective Connectivity ◽  
Causality Analysis ◽  
Motor Execution ◽  
Stroke Patients ◽  
Granger Causality Analysis ◽  
Cortical Motor ◽  
Motor Network

Aims.Motor imagery has emerged as a promising technique for the improvement of motor function following stroke, but the mechanism of functional network reorganization in patients during this process remains unclear. The aim of this study is to evaluate the cortical motor network patterns of effective connectivity in stroke patients.Methods.Ten stroke patients with right hand hemiplegia and ten normal control subjects were recruited. We applied conditional Granger causality analysis (CGCA) to explore and compare the functional connectivity between motor execution and motor imagery.Results.Compared with the normal controls, the patient group showed lower effective connectivity to the primary motor cortex (M1), the premotor cortex (PMC), and the supplementary motor area (SMA) in the damaged hemisphere but stronger effective connectivity to the ipsilesional PMC and M1 in the intact hemisphere during motor execution. There were tighter connections in the cortical motor network in the patients than in the controls during motor imagery, and the patients showed more effective connectivity in the intact hemisphere.Conclusions.The increase in effective connectivity suggests that motor imagery enhances core corticocortical interactions, promotes internal interaction in damaged hemispheres in stroke patients, and may facilitate recovery of motor function.

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.

scholarly journals Multivariate Granger Causality Analysis of Acupuncture Effects in Mild Cognitive Impairment Patients: An fMRI Study

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Shangjie Chen ◽  
Lijun Bai ◽  
Maosheng Xu ◽  
Fang Wang ◽  
Liang Yin ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Granger Causality ◽  
Effective Connectivity ◽  
Brain Networks ◽  
Brain Regions ◽  
Causality Analysis ◽  
Granger Causality Analysis ◽  
Cognitive States ◽  
Dorsolateral Prefrontal

Evidence from clinical reports has indicated that acupuncture has a promising effect on mild cognitive impairment (MCI). However, it is still unknown that by what way acupuncture can modulate brain networks involving the MCI. In the current study, multivariate Granger causality analysis (mGCA) was adopted to compare the interregional effective connectivity of brain networks by varying needling depths (deep acupuncture, DA; superficial acupuncture, SA) and at different cognitive states, which were the MCI and healthy control (HC). Results from DA at KI3 in MCI showed that the dorsolateral prefrontal cortex and hippocampus emerged as central hubs and had significant causal influences with each other, but significant in HC for DA. Moreover, only several brain regions had remarkable causal interactions following SA in MCI and even few brain regions following SA in HC. Our results indicated that acupuncture at KI3 at different cognitive states and with varying needling depths may induce distinct reorganizations of effective connectivities of brain networks, and DA at KI3 in MCI can induce the strongest and more extensive effective connectivities related to the therapeutic effect of acupuncture in MCI. The study demonstrated the relatively functional specificity of acupuncture at KI3 in MCI, and needling depths play an important role in acupuncture treatments.

scholarly journals Asymmetric effective connectivity within frontoparietal motor network underlying motor imagery and motor execution

2020 ◽  
Author(s):  
Takeshi Ogawa ◽  
Hideki Shimobayashi ◽  
Jun-ichiro Hirayama ◽  
Motoaki Kawanabe
Keyword(s):  
Motor Imagery ◽  
Primary Motor Cortex ◽  
Brain Activity ◽  
Effective Connectivity ◽  
Premotor Cortex ◽  
Brain Regions ◽  
Neural Representation ◽  
Motor Execution ◽  
Positive Effects ◽  
Motor Network

AbstractBoth imagery and execution of motor controls consist of interactions within a neuronal network, including frontal motor-related regions and posterior parietal regions. To reveal neural representation in the frontoparietal motor network, several approaches have been proposed: one is decoding of actions/modes related to motor control from the spatial pattern of brain activity; another is to estimate effective connectivity, which means a directed association between two brain regions within motor regions. However, a motor network consisting of multiple brain regions has not been investigated to illustrate network representation depending on motor imagery (MI) or motor execution (ME). Here, we attempted to differentiate the frontoparietal motor-related networks based on the effective connectivity in the MI and ME conditions. We developed a delayed sequential movement and imagery (dSMI) task to evoke brain activity associated with data under ME and MI in functional magnetic resonance imaging (fMRI) scanning. We applied a linear non-Gaussian acyclic causal model to identify effective connectivity among the frontoparietal motor-related brain regions for each condition. We demonstrated higher effective connectivity from the contralateral dorsal premotor cortex (dPMC) to the primary motor cortex (M1) in ME than in MI. We mainly identified significant direct effects of dPMC and ventral premotor cortex (vPMC) to the parietal regions. In particular, connectivity from the dPMC to the superior parietal lobule (SPL) in the same hemisphere showed significant positive effects across all conditions. Instead, interlateral connectivities from vPMC to SPL showed significantly negative effects across all conditions. Finally, we found positive effects from A1 to M1 in the same hemisphere, such as the audio motor pathway. These results indicated that sources of motor command originated from d/vPMC and influenced M1 as achievements of ME and MI, and the parietal regions as integration of somatosensory and visual representation during finger tapping. In addition, sequential sounds may functionally facilitate temporal motor processes.

scholarly journals A failed top-down control from prefrontal cortex to amygdala in generalized anxiety disorder: evidence from resting-state fMRI with Granger causality analysis

2019 ◽  
Author(s):  
Mengshi Dong ◽  
Likun Xia ◽  
Min Lu ◽  
Chao Li ◽  
Ke Xu ◽  
...  
Keyword(s):  
Prefrontal Cortex ◽  
Anxiety Disorder ◽  
Granger Causality ◽  
Generalized Anxiety Disorder ◽  
Resting State ◽  
Effective Connectivity ◽  
Generalized Anxiety ◽  
Causality Analysis ◽  
Top Down ◽  
Granger Causality Analysis

AbstractObjectiveIn generalized anxiety disorder (GAD), abnormal top-down control from prefrontal cortex (PFC) to amygdala is a widely accepted hypothesis through which “emotional dysregulation model” may be explained. However, whether and how the PFC directly exerted abnormal top-down control on amygdala remained largely unknown. We aim to investigate the amygdala-based effective connectivity by using Granger causality analysis (GCA).MethodsThirty-five drug-naive patients with GAD and thirty-six healthy controls (HC) underwent resting-state functional MR imaging. We used seed-based Granger causality analysis to examine the effective connectivity between the bilateral amygdala and the whole brain. The amygdala-based effective connectivity was compared between the two groups.ResultsIn HC, the left middle frontal gyrus exerted inhibitory influence on the right amygdala, while in GAD group, this influence was disrupted (single voxel P < 0.001, Gaussian random field corrected with P < 0.01).ConclusionOur finding might provide new insight into the “insufficient top-down control” hypothesis in GAD.

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