2026-10-12T13:14:31Z https://api.figshare.com/v2/oai

oai:figshare.com:article/34014808 2026-09-28T14:58:59Z category_12 category_15 category_122 category_135 portal_87 item_type_3 month_year_09_2026

Structure-Adaptive E-Value Filter for Detecting Regional Signals in Brain Imaging Jingcheng He (9046971) Hangjin Jiang (10164692) Wenguang Sun (4173823) Cell Biology Neuroscience Mental Health Computational Biology False discovery rate Conformal inference Partial conjunction hypothesis Neuroimaging Cognitive impairment <p>Structural MRI provides a noninvasive view of the neuroanatomical differences associated with cognitive impairment and dementia. Using data from the Alzheimer’s Disease Neuroimaging Initiative, we investigate which anatomical regions exhibit widespread gray-matter differences and how these regional patterns vary across the clinical spectrum. Addressing this goal requires translating spatially dependent voxel-level evidence into regional conclusions while controlling multiplicity across anatomical regions. We propose the Structure-adaptive E-value FilTer (SEFT), which uses flexible working models to construct spatially adaptive voxel-level scores and aggregates them into regional partial-conjunction e-values. When combined with the e-value Benjamini–Hochberg (e-BH) procedure, these e-values provide finite-sample control of the set-wise false discovery rate under arbitrary interregional dependence. The ADNI analysis reveals a coherent neuroanatomical pattern: the exploratory analysis shows that differences between normal cognition and mild cognitive impairment are concentrated in medial-temporal regions, whereas the differences between mild cognitive impairment and dementia extend more broadly into temporal–limbic and posterior association regions. Both patterns largely overlap the normal-cognition–dementia benchmark, identifying a shared anatomical core across the clinical comparisons.</p> 2026-09-28T14:58:59Z Dataset Dataset 10.6084/m9.figshare.34014808.v1 https://figshare.com/articles/dataset/Structure-Adaptive_E-Value_Filter_for_Detecting_Regional_Signals_in_Brain_Imaging/34014808 CC BY 4.0