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. 2010 Aug 16;480(2):143-7.
doi: 10.1016/j.neulet.2010.06.027. Epub 2010 Jun 16.

Feeling for space or for time: task-dependent modulation of the cortical representation of identical vibrotactile stimuli

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Feeling for space or for time: task-dependent modulation of the cortical representation of identical vibrotactile stimuli

Ben Godde et al. Neurosci Lett. .

Abstract

Using functional MRI we examined the task-dependency of brain activation patterns evoked by vibrotactile stimulation. For this purpose, we measured activations after identical stimulation of the fingers of the right hand in three different task conditions: passive attention, localization of the vibrations, and discrimination of temporal noise within the vibrations. Further, we investigated whether, regardless of task demands, the characteristics of the vibrations - periodic versus noisy - had an effect on brain topography. Vibrotactile processing was associated with activation in a variety of cortical areas including contralateral primary somatosensory cortex (SI), bilateral posterior parietal cortex, parietal operculum (second somatosensory cortex, SII), insula, and superior temporal gyrus, as well as ipsilateral middle temporal gyrus, precentral, and middle frontal gyrus. However, identical stimuli evoked different brain activity patterns in different task conditions: significantly stronger activity in the hand representation of SI was found for stimulus localization than for noise detection. In contrast, significantly higher activation for noise detection than for finger localization was found in the thalamus. Activation tended to be lower for noisy stimuli in both hemispheres. Significant stimulus-related differences, however, could be found only in the contralateral postcentral and parietal cortex, particularly during noise discrimination. In summary, in response to vibrotactile stimulation, the level of activation in processing circuits ranging across thalamus and many cortical regions is dictated by the perceptual operation carried out on the vibration. We speculate that different nodes in the network carry signals that can be optimally decoded for either spatial or temporal information and that the degree of activation reflects those nodes' relative contributions to the decoding process.

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