LAUSR

Introduction The use of functional MRI (fMRI) in language research is impaired by acoustic noise produced by the scanner. To reduce scanner noise during stimulus presentation, ‘sparse’ acquisition schemes have been developed in which volume acquisitions are interleaved with periods of silence. This reduces the number of acquired volumes over time. Thus, statistical power must be weighed against scanner time and the subjects distress. To address the limitations of sparse acquisition protocols, clustered sparse acquisition schemes have emerged. Here, we have established a clustered sparse acquisition protocol using simultaneous multisclice imaging acceleration. Methods MRI data were collected using a Philips Ingenia 3T full body scanner. Functional MRI scanning was performed using a standard (simple sparse sampling) versus a clustered sparse acquisition protocol, where three volumes are acquired every twelve seconds (TR = 1200 ms, TE = 30 ms, Flip Angle = 90°, 36 slices, voxel size = 3 × 3 × 3 mm, multiband factor = 2). In this pilot study, five healthy subjects were investigated by (i) a motor (i.e., repetitive thumb, lips and toe movements triggered by a visual cue) and (ii) a language task (i.e., visual object naming), both presented using Psychopy on a screen inside the scanner room. Functional image analysis was performed using SPM12. The three images acquired in one cluster are subject to differing longitudinal magnetization and therefore differing T2 * and T1 effects. To account for this, data were analyzed separately for each time point of acquisition (TPA). The first images from each TPA were realigned to each other, then the remaining images were realigned to the first. Differences in scan intensity were removed by grand mean scaling. A box car function was used. Results Using clustered sparse acquisition, the number of image volumes acquired per event could be increased by factor 3–5. Preliminary results suggest an accordingly significant increase in statistical power, with stronger activations revealed by the clustered sparse sampling protocol for both fMRI paradigms (motor and language task). Strongest activations (local activation maximum) were observed within the primary motor cortex by motor experiment and in the anterior superior temporal gyrus by visual object naming. Conclusion Pilot data acquired using both a motor and a visual object naming task and clustered sparse sampling shows promise for the primary study goal of reducing scan time by increasing statistical power. Such advances are particularly important for clinical applications, given the limited alertness and compliance of patients e.g. before brain tumor resection.