bioRxivNeurosciencePreprint
Testing the Vogt-Bailey Index using task-based fMRI across pulse sequence protocols
Kristian GaleaiD, Aitor Alberdi Escudero, Nina Attard-Montalto, Nolan Vella, Robert Elton SmithiD, Christine FarrugiaiD, Paola GaldiiD, Kenneth ScerriiD, Liam ButleriD, Claude Julien BajadaiD
Abstract
Local connectivity analyses in fMRI such as the Vogt-Bailey Index, investigate the prevalence of co-fluctuations in the time-series of adjacent voxels. While there have been in silico assessments of the VB Index, this technique has not yet been assessed in vivo. This study has two aims: first, to assess the VB Index using a task paradigm with well established a priori expectations on the brain region predominantly responsible for executing this task to determine whether the VB Index highlights this area. Second, we investigate if, and how, the spatial resolution of the sequence protocols employed, with their inherent effects on the signal-to-noise ratio, affect the resultant VB maps. A cohort of 10 research volunteers underwent fMRI acquisitions utilising a block design finger tapping experiment. Each volunteer was scanned with three sequence protocols, with all parameters equivalent except for the volume of the voxels. The resulting parametric maps derived using the VB Index were compared with those obtained from the conventional General Linear Model approach. Particular emphasis was placed on the identification of the hand portion of the motor homunculus. Across sequence protocols, the VB Index consistently identified elevated local connectivity in, qualitatively, the same portion of the motor cortex as that yielded by the General Linear Model based on the task paradigm. However, the VB Index also detected elevated local connectivity outside the motor cortex while the General Linear Model results were mostly restricted to the motor cortex. The consistently high VB Index, across sequence protocols, in the cortical region associated with an fMRI task paradigm, despite the approachs agnosticism to that task, provides support for the biological relevance of such local connectivity measures.
- organism: human
- assay: imaging
- research focus: cell type annotation
- research focus: differential expression
- approach: statistical model
- Citations
- 0
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