The suppressive influence of SMA on M1 in motor imagery revealed by fMRI and dynamic causal modeling

Kasess, Christian H.; Windischberger, Christian; Cunnington, Ross; Lanzenberger, Rupert; Pezawas, Lukas; Moser, Ewald

doi:10.1016/j.neuroimage.2007.11.040

Cited by 220 publications

(181 citation statements)

References 45 publications

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“…Common to all the model classes, the task input (motor execution or motor imagery) was projected to all the three activated regions. Further support for this hypothesis came from the results of Kasess et al (2008) demonstrating that, SMA and M1 as nodes of an interactive closed-loop control circuit subserving motor task execution should both be modulated by task stimuli (Brigadoi et al, 2012;Kasess et al, 2008). Since the activated regions were detected using a general linear model in which Connections that were constant throughout all models are shown as solid arrows.…”

Section: Dynamical Causal Modeling Analysismentioning

confidence: 95%

“…As a powerful approach to inferring effective connectivity from fMRI data, DCM has increasing applications. The validity of DCM has been evaluated by numerous studies (Bitan et al, 2005;Friston et al, 2003;Kasess et al, 2008;Penny et al, 2004b;Smith et al, 2006;Stephan et al, 2005;Szameitat et al, 2007). DCM uses a bilinear model where the changes in neuronal states over time can be evaluated by the following:…”

Section: Dynamical Causal Modeling Analysismentioning

confidence: 99%

“…As an effective connectivity method, DCM is hypothesis driven and requires a priori model structure definition, for which the connectivity parameters are estimated (Kasess et al, 2008). Totally, five model classes were defined according to previous studies.…”

Section: Dynamical Causal Modeling Analysismentioning

confidence: 99%

“…Importantly, using DCM, Kasess et al (2008) showed that the SMA exerts suppressive influence over contralateral M1 during motor imagery, whereas Grefkes et al (2008) demonstrated the facilitation of SMA on contralateral M1 during motor execution. This alteration of the influence that SMA exerts over contralateral M1 during motor execution and motor imagery conditions implied the different roles of SMA induced by different task conditions.…”

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confidence: 99%

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Differential Contribution of Bilateral Supplementary Motor Area to the Effective Connectivity Networks Induced by Task Conditions Using Dynamic Causal Modeling

et al. 2014

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Functional imaging studies have indicated hemispheric asymmetry of activation in bilateral supplementary motor area (SMA) during unimanual motor tasks. However, the hemispherically special roles of bilateral SMAs on primary motor cortex (M1) in the effective connectivity networks (ECN) during lateralized tasks remain unclear. Aiming to study the differential contribution of bilateral SMAs during the motor execution and motor imagery tasks, and the hemispherically asymmetric patterns of ECN among regions involved, the present study used dynamic causal modeling to analyze the functional magnetic resonance imaging data of the unimanual motor execution/imagery tasks in 12 right-handed subjects. Our results demonstrated that distributions of network parameters underlying motor execution and motor imagery were significantly different. The variation was mainly induced by task condition modulations of intrinsic coupling. Particularly, regardless of the performing hand, the task input modulations of intrinsic coupling from the contralateral SMA to contralateral M1 were positive during motor execution, while varied to be negative during motor imagery. The results suggested that the inhibitive modulation suppressed the overt movement during motor imagery. In addition, the left SMA also helped accomplishing left hand tasks through task input modulation of left SMA/right SMA connection, implying that hemispheric recruitment occurred when performing nondominant hand tasks. The results specified differential and altered contributions of bilateral SMAs to the ECN during unimanual motor execution and motor imagery, and highlighted the contributions induced by the task input of motor execution/imagery.

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Section: Dynamical Causal Modeling Analysismentioning

confidence: 95%

Section: Dynamical Causal Modeling Analysismentioning

confidence: 99%

Section: Dynamical Causal Modeling Analysismentioning

confidence: 99%

mentioning

confidence: 99%

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Differential Contribution of Bilateral Supplementary Motor Area to the Effective Connectivity Networks Induced by Task Conditions Using Dynamic Causal Modeling

et al. 2014

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“…The assessment of effective connectivity measures provides a unique opportunity to determine whether and how activity in different regions within a specific network influences the activity in other regions during a certain task (actually, DCM has been improved for resting-state fMRI data [58] ). DCM has already been applied successfully to test competing hypotheses in the sensory fields of neuroscience, such as to investigate the interhemispheric integration of visual processing [59] , the suppressive influence of the supplementary motor area on primary motor cortex in motor imagery [60] , and somatosensory information processing in primary and secondary somatosensory cortices [61] . In addition, DCM has been successfully applied to more complex cognitive tasks, such as face perception [62] and the cortical interactions related to reading and speech processing [63] .…”

Section: Task-induced Effective Connectivity Network Asmentioning

confidence: 99%

A review of functional magnetic resonance imaging for Brainnetome

Song

Jiang

2012

Neurosci. Bull.

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Abstract:The functional brain network using blood-oxygen-level-dependent (BOLD) functional magnetic resonance imaging (fMRI) has revealed the potentials for probing brain architecture, as well as for identifying clinical biomarkers for brain diseases. In the general context of Brainnetome, this review focuses on the development of approaches for modeling and analyzing functional brain networks with BOLD fMRI. The prospects for these approaches are also discussed.

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A Thalamocortical Mechanism for the Absence of Overt Motor Behavior in Covertly Aware Patients

2015

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IMPORTANCE It is well accepted that a significant number of patients in a vegetative state are covertly aware and capable of following commands by modulating their neural responses in motor imagery tasks despite remaining nonresponsive behaviorally. To date, there have been few attempts to explain this dissociation between preserved covert motor behavior and absent overt motor behavior. OBJECTIVES To investigate the differential neural substrates of overt and covert motor behavior and assess the structural integrity of the underlying networks in behaviorally nonresponsive patients. DESIGN, SETTING, AND PARTICIPANTS A case-control study was conducted at an academic center between February 7, 2012, and November 6, 2014. Data analysis was performed between March 2014 and June 2015. Participants included a convenience sample of 2 patients with severe brain injury: a paradigmatic patient who fulfilled all clinical criteria for the vegetative state but produced repeated evidence of covert awareness (patient 1) and, as a control case, a patient with similar clinical variables but capable of behavioral command following (patient 2). Fifteen volunteers participated in the study as a healthy control group. MAIN OUTCOMES AND MEASURES We used dynamic causal modeling of functional magnetic resonance imaging to compare voluntary motor imagery and motor execution. We then used fiber tractography to assess the structural integrity of the fibers that our functional magnetic resonance imaging study revealed as essential for successful motor execution. RESULTS The functional magnetic resonance imaging study revealed that, in contrast to mental imagery, motor execution was associated with an excitatory coupling between the thalamus and primary motor cortex (Bayesian model selection; winning model Bayes factors >17). Moreover, we detected a selective structural disruption in the fibers connecting these 2 regions in patient 1 (fractional anisotropy, 0.294; P = .047) but not in patient 2 (fractional anisotropy, 0.413; P = .35). CONCLUSIONS AND RELEVANCE These results suggest a possible biomarker for the absence of intentional movement in covertly aware patients (ie, specific damage to motor thalamocortical fibers), highlight the importance of the thalamus for the execution of intentional movements, and may provide a target for restorative therapies in behaviorally nonresponsive patients.

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The suppressive influence of SMA on M1 in motor imagery revealed by fMRI and dynamic causal modeling

Cited by 220 publications

References 45 publications

Differential Contribution of Bilateral Supplementary Motor Area to the Effective Connectivity Networks Induced by Task Conditions Using Dynamic Causal Modeling

Differential Contribution of Bilateral Supplementary Motor Area to the Effective Connectivity Networks Induced by Task Conditions Using Dynamic Causal Modeling

A review of functional magnetic resonance imaging for Brainnetome

A Thalamocortical Mechanism for the Absence of Overt Motor Behavior in Covertly Aware Patients

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