Bridging the Gap between Deep Learning and Hypothesis-Driven Analysis via Permutation Testing. (arXiv:2207.14349v1 [cs.LG])

A fundamental approach in neuroscience research is to test hypotheses based
on neuropsychological and behavioral measures, i.e., whether certain factors
(e.g., related to life events) are associated with an outcome (e.g.,
depression). In recent years, deep learning has become a potential alternative
approach for conducting such analyses by predicting an outcome from a
collection of factors and identifying the most "informative" ones driving the
prediction. However, this approach has had limited impact as its findings are
not linked to statistical …

analysis arxiv deep learning gap hypothesis learning lg testing