Abstract
The aim of this article is to report on the importance and challenges of a time-resolved and spatio-temporal analysis of fMRI data from complex cognitive processes and associated disorders using a study on developmental dyscalculia (DD). Participants underwent fMRI while judging the incorrectness of multiplication results, and the data were analyzed using a sequence of methods, each of which progressively provided more a detailed picture of the spatio-temporal aspect of this disease. Healthy subjects and subjects with DD performed alike behaviorally, though they exhibited parietal disparities using traditional "voxel-based" group analyses. Further and more detailed differences, however, surfaced with a "time-resolved" examination of the neural responses during the experiment. While performing intergroup comparisons, a third group of subjects with dyslexia but with no arithmetic difficulties was included to test the specificity of the analysis and strengthen the statistical base with overall 58 subjects. Surprisingly, the analysis showed a functional dissimilarity during an initial reading phase for the group of dyslexic but otherwise normal subjects, with respect to controls, though only numerical digits and no alphabetic characters were presented. Thus, our results suggest that "time-resolved multivariate" analysis of complex experimental paradigms has the ability to yield powerful new clinical insights about abnormal brain function. Similarly, a detailed compilation of aberrations in the functional cascade may have much greater potential to delineate the core processing problems in mental disorders.
Original language | English |
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Pages (from-to) | 81-96 |
Number of pages | 16 |
Journal | International Journal of Imaging Systems and Technology |
Volume | 22 |
Issue number | 1 |
DOIs | |
State | Published - Mar 2012 |
Keywords
- developmental dyscalculia
- fMRI
- functional brain mapping
- mental arithmetic
- spatio-temporal analysis
ASJC Scopus subject areas
- Electronic, Optical and Magnetic Materials
- Software
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering