Presentation Abstract

Program#/Poster#: 550.21/RR21
Presentation Title: Direct comparison of network connectivity revealed by resting-state fMRI and concurrent TMS-fMRI
Location: Halls B-H
Presentation time: Tuesday, Nov 12, 2013, 8:00 AM - 9:00 AM
Topic: ++D.14.c. Cerebellum: Human studies
Authors: *J. M. YAU1, M. B. NEBEL3, J. HUA2, J. E. DESMOND1;
1Neurol., Johns Hopkins Univ., BALTIMORE, MD; 2Russell H. Morgan Dept. of Radiology and Radiological Sci., Johns Hopkins Univ., Baltimore, MD; 3Kennedy Krieger Inst., Baltimore, MD
Abstract: Brain regions collaborate in distributed networks. With resting-state functional connectivity analyses, network architecture is inferred from spatially distributed, coherent low-frequency BOLD fluctuations. Resting-state connectivity patterns tend to conform to anatomical connectivity maps and there is a high correspondence between functional connectivity patterns and task-evoked coactivation patterns revealed by conventional functional neuroimaging. Despite these demonstrations, the direct relationship between correlated spontaneous BOLD fluctuations and acute neural processing remains untested in healthy adults. Because transcranial magnetic stimulation (TMS) can be used to causally evoke neural responses in targeted brain regions and in remote but connected areas, this research tool offers a unique opportunity, when paired with fMRI, to relate rs-fMRI network analysis and dynamic neural processes.
Here, we demonstrate that TMS-evoked BOLD activation patterns closely relate, but are not identical, to resting-state functional connectivity. During each scan session, we first acquired rs-fMRI data from participants, prior to TMS administration in the scanner. While participants remained at rest in concurrent TMS-fMRI scans, we causally evoked distinct and robust BOLD activation patterns with targeted brain stimulation. Using TMS target locations as region-of-interest seeds, we computed seed-based correlation maps with a separate rs-fMRI dataset (Kirby 21; Defining networks using this large and independent dataset enabled us to generate robust statistical masks that we used to query and compare each participant’s rs-fMRI data and concurrent TMS-fMRI data. We found substantial overlap in TMS-evoked BOLD activation patterns and seed-based functional connectivity, providing evidence for the hypothesis that resting-state BOLD fluctuations reflect intrinsic network architecture that supports acute and dynamic neural processing. However, TMS also evoked responses that were distinct from seed-based connectivity patterns indicating that concurrent TMS-fMRI may reveal additional network relationships.
Disclosures:  J.M. Yau: None. M.B. Nebel: None. J. Hua: None. J.E. Desmond: None.
Support: The Johns Hopkins University Brain Science Institute
NIH/NICHD Grant P30HD024061
NIH/NINDS Grant F32NS073371

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