Home > Publications database > Using multi-level Bayesian lesion-symptom mapping to probe the body-part-specificity of gesture imitation skills > print

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024 7 _ |a 10.1016/j.neuroimage.2017.08.036
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100 1 _ |a Achilles, Elisabeth
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245 _ _ |a Using multi-level Bayesian lesion-symptom mapping to probe the body-part-specificity of gesture imitation skills
260 _ _ |a Orlando, Fla.
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520 _ _ |a Past attempts to identify the neural substrates of hand and finger imitation skills in the left hemisphere of the brain have yielded inconsistent results. Here, we analyse those associations in a large sample of 257 left hemisphere stroke patients. By introducing novel Bayesian methods, we characterise lesion symptom associations at three levels: the voxel-level, the single-region level (using anatomically defined regions), and the region-pair level. The results are inconsistent across those three levels and we argue that each level of analysis makes assumptions which constrain the results it can produce. Regardless of the inconsistencies across levels, and contrary to past studies which implicated differential neural substrates for hand and finger imitation, we find no consistent voxels or regions, where damage affects one imitation skill and not the other, at any of the three analysis levels. Our novel Bayesian approach indicates that any apparent differences appear to be driven by an increased sensitivity of hand imitation skills to lesions that also impair finger imitation. In our analyses, the results of the highest level of analysis (region-pairs) emphasise a role of the primary somatosensory and motor cortices, and the occipital lobe in imitation. We argue that this emphasis supports an account of both imitation tasks based on direct sensor-motor connections, which throws doubt on past accounts which imply the need for an intermediate (e.g. body-part-coding) system of representation.
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700 1 _ |a Weiss-Blankenhorn, Peter
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700 1 _ |a Fink, Gereon R.
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700 1 _ |a Binder, Ellen
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700 1 _ |a Price, Cathy J.
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700 1 _ |a Hope, Thomas M. H.
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773 _ _ |a 10.1016/j.neuroimage.2017.08.036
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