Do Symptoms Matter? Investigating Symptom-Based Lesion Network Mapping.
Treeratana, S.; Kasemsantitham, A.-A.; Jarukasemkit, S.; Phusuwan, W.; Chokesuwattanaskul, A.; Sriswasdi, S.; Chunharas, C.; Bijsterbosch, J. D.
Show abstract
Lesion network mapping (LNM) is an approach to map focal brain lesions to a common brain network through the use of a reference connectome dataset. Van den Heuvel and colleagues recently showed that results produced by LNM lack disease specificity. Here, we expand on symptom-based LNM (sLNM) -- a variant designed to focus on symptom-specificity, statistical rigor, and clinical utility. We show that sLNM maps from unrelated disorders nonetheless converge toward a common output, confirming a lack of disease specificity similar to LNM. Given this lack of disease specificity, it is puzzling why studies have shown clinical efficacy of sLNM-guided treatment. Our findings suggest that sLNM results converge to the first principal gradient, which describes the brains sensorimotor-association organizational axis that has been linked to development and pathology. Therefore, sLNM maps may be clinically useful because they reflect this fundamental brain organizational axis rather than disease-specific networks. Taken together with the results from van den Heuvel et al, these insights open an important opportunity for integrating findings from sLNM with findings on the sensorimotor-association brain axis.
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