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Stefan Kiebel

Publications and source records attributed to Stefan Kiebel.

2 recordsLinked to original sources

Visuomotor control within a distributed parieto-frontal network.

The aim of this functional magnetic resonance imaging study was to investigate differences in visuomotor control with increasing task complexity. Twelve right-handed volunteers were asked to perform their signature under different degrees of visual control: internally generated movement with closed eyes, signing with open eyes, tracking the line of the projected signature forwards, and tracking the line of the projected signature backwards. There was a gradual onset and disappearance of activation within a distributed network. Parietal, lateral and medial frontal brain areas were activated during all conditions, confirming the involvement of a parieto-frontal system. The weight of activation shifted with increasing task complexity. Internally generated movements activated predominantly the inferior parietal lobule and the ventral premotor cortex, as well as the rostral cingulate area, pre-supplementary motor area (pre-SMA) and SMA proper. Opening the eyes reduced SMA and cingulate activation and activated increasingly the occipito-parietal areas with higher task complexity. Visually guided movements produced an activation predominantly in the superior parietal lobule and dorsal premotor cortex. This study bridges human activation studies with the results of neurophysiological studies with monkeys. It confirms a gradual transition of visuomotor control with increasing task complexity within a distributed parieto-frontal network.

Adult↗

Anatomically informed basis functions in multisubject studies.

We describe the use of anatomically informed basis functions (AIBF) in the analysis of multisubject functional imaging studies. AIBF are used to specify an anatomically informed spatial model that embodies anatomical knowledge for the statistical analysis of neuroimaging data. In a previous communication, we showed how AIBF can be used to incorporate prior anatomical constraints in single subject functional magnetic resonance image (fMRI) analyses to augment their anatomical precision. In this paper, we extend AIBF such that it can be applied to multisubject studies using fMRI or PET. The key concept is that, after spatial normalization, a canonical cortical surface can be used to generate a forward model of signal sources for all subjects. By estimating the hemodynamic signal in this canonical AIBF-space and then projecting it back into the voxel-space, one effectively extracts functional activity that is smooth, within and only within, the cortical sheet while attenuating other components unrelated to the physiological process of interest. The ensuing procedure can be considered as a highly non-stationary, anisotropic anatomically informed [de]convolution or smoothing. It is shown that this procedure offers various advantages compared to existing conventional methods for the analysis of multisubject studies, in particular it is more sensitive to underlying activations.

Algorithms↗