Investigation of effective connectivity in the motor cortex of fMRI data using Granger causality model

2007 ◽  
Author(s):  
Xingchun Wu ◽  
Ni Tang ◽  
Kai Yin ◽  
Xia Wu ◽  
Xiaotong Wen ◽  
...  
Keyword(s):  
Motor Cortex ◽  
Granger Causality ◽  
Effective Connectivity ◽  
Fmri Data ◽  
Causality Model

Kernel Granger Causality Mapping Effective Connectivity on fMRI Data

2009 ◽  
Vol 28 (11) ◽  
pp. 1825-1835 ◽  
Author(s):  
Wei Liao ◽  
D. Marinazzo ◽  
Zhengyong Pan ◽  
Qiyong Gong ◽  
Huafu Chen
Keyword(s):  
Granger Causality ◽  
Effective Connectivity ◽  
Fmri Data

scholarly journals Visual Information Shapes the Dynamics of Corticobasal Ganglia Pathways during Response Selection and Inhibition

2015 ◽  
Vol 27 (7) ◽  
pp. 1344-1359 ◽  
Author(s):  
Sara Jahfari ◽  
Lourens Waldorp ◽  
K. Richard Ridderinkhof ◽  
H. Steven Scholte
Keyword(s):  
Visual Cortex ◽  
Visual Information ◽  
Response Selection ◽  
Selection Process ◽  
Effective Connectivity ◽  
Action Selection ◽  
Visual Input ◽  
Fmri Data ◽  
Response Strategies ◽  
Fast Flow

Action selection often requires the transformation of visual information into motor plans. Preventing premature responses may entail the suppression of visual input and/or of prepared muscle activity. This study examined how the quality of visual information affects frontobasal ganglia (BG) routes associated with response selection and inhibition. Human fMRI data were collected from a stop task with visually degraded or intact face stimuli. During go trials, degraded spatial frequency information reduced the speed of information accumulation and response cautiousness. Effective connectivity analysis of the fMRI data showed action selection to emerge through the classic direct and indirect BG pathways, with inputs deriving form both prefrontal and visual regions. When stimuli were degraded, visual and prefrontal regions processing the stimulus information increased connectivity strengths toward BG, whereas regions evaluating visual scene content or response strategies reduced connectivity toward BG. Response inhibition during stop trials recruited the indirect and hyperdirect BG pathways, with input from visual and prefrontal regions. Importantly, when stimuli were nondegraded and processed fast, the optimal stop model contained additional connections from prefrontal to visual cortex. Individual differences analysis revealed that stronger prefrontal-to-visual connectivity covaried with faster inhibition times. Therefore, prefrontal-to-visual cortex connections appear to suppress the fast flow of visual input for the go task, such that the inhibition process can finish before the selection process. These results indicate response selection and inhibition within the BG to emerge through the interplay of top–down adjustments from prefrontal and bottom–up input from sensory cortex.

Methodological and Technical Issues for Integrating Functional Magnetic Resonance Imaging Data in a Neuronavigational System

Neurosurgery ◽  
2001 ◽  
Vol 49 (5) ◽  
pp. 1145-1157 ◽  
Author(s):  
Franck-Emmanuel Roux ◽  
Danielle Ibarrola ◽  
Michel Tremoulet ◽  
Yves Lazorthes ◽  
Patrice Henry ◽  
...  
Keyword(s):  
Brain Tumor ◽  
Motor Cortex ◽  
Brain Mapping ◽  
Fmri Data ◽  
Electrode Placement ◽  
Cortical Mapping ◽  
Tumor Surgery ◽  
Motor Cortex Stimulation ◽  
Functional Magnetic Resonance ◽  
Brain Tumor Surgery

ABSTRACT OBJECTIVE The aim of this article was to analyze the technical and methodological issues resulting from the use of functional magnetic resonance image (fMRI) data in a frameless stereotactic device for brain tumor or pain surgery (chronic motor cortex stimulation). METHODS A total of 32 candidates, 26 for brain tumor surgery and six chronic motor cortex stimulation, were studied by fMRI scanning (61 procedures) and intraoperative cortical brain mapping under general anesthesia. The fMRI data obtained were analyzed with the Statistical Parametric Mapping 99 software, with an initial analysis threshold corresponding to P < 0.001. Subsequently, the fMRI data were registered in a frameless stereotactic neuronavigational device and correlated to brain mapping. RESULTS Correspondence between fMRI-activated areas and cortical mapping in primary motor areas was good in 28 patients (87%), although fMRI-activated areas were highly dependent on the choice of paradigms and analysis thresholds. Primary sensory- and secondary motor-activated areas were not correlated to cortical brain mapping. Functional mislocalization as a result of insufficient correction of the echo-planar distortion was identified in four patients (13%). Analysis thresholds (from P < 0.0001 to P < 10−12) more restrictive than the initial threshold (P < 0.001) had to be used in 25 of the 28 patients studied, so that fMRI motor data could be matched to cortical mapping spatial data. These analysis thresholds were not predictable preoperatively. Maximal tumor resection was accomplished in all patients with brain tumors. Chronic motor cortex electrode placement was successful in each patient (significant pain relief >50% on the visual analog pain scale). CONCLUSION In brain tumor surgery, fMRI data are helpful in surgical planning and guiding intraoperative brain mapping. The registration of fMRI data in anatomic slices or in the frameless stereotactic neuronavigational device, however, remained a potential source of functional mislocalization. Electrode placement for chronic motor cortex stimulation is a good indication to use fMRI data registered in a neuronavigational system and could replace somatosensory evoked potentials in detection of the central sulcus.

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