ArticleHuman brain mapping2026
Critical-Network Lesion-Symptom Mapping.
Article in Human brain mapping, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Complex datasets used for lesion-symptom mapping (LSM) present serious challenges for interpretable statistical analysis. We introduce Critical Network Lesion-Symptom Mapping (CN-LSM), a neuroanatomical atlas-based method that uses low-dimensional regression models and out-of-sample prediction to identify brain regions that contribute significantly to the prediction of clinical behavioral scores. Rather than focusing on a single most-predictive model, CN-LSM identifies a set of plausible models analyzed as an ensemble. CN-LSM offers three primary advantages over existing approaches: (1) greater robustness to analytical decisions that should be (but often are not) inconsequential to results; (2) holistic quantification of uncertainty across the entire statistical map rather than at individual voxels or regions; and (3) explicit accommodation of multiple plausible explanations, reducing false negatives while preserving stringent control over false positive rates.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.