ArticleThe international journal of neuropsychopharmacology2026
Functional inputs to the subgenual cingulate cortex differentiate levels of depressive symptom severity in neurotypical young adults: granger causality and clustering analyses.
Article in The international journal of neuropsychopharmacology, 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
- Update of
Authors and funding
5 authors.
Funding
Abstract
introductionExtant research has implicated functional connectivity of the subgenual anterior cingulate cortex (sgACC) in major depressive disorders or depressive traits in neurotypical populations. However, prior studies have not distinguished the inputs and outputs of the sgACC, and the "diagnostic" accuracy of these connectivity metrics remains elusive.
methodsHere, we analyzed data of 890 neurotypical young adults (459 women, age 22-35) from the Human Connectome Project using Granger causality analyses (GCA) with the sgACC as the seed and 268 regions of interest from the Shen's atlas as targets. Depressive and other comorbid symptoms were assessed using the Adult Self Report. Individual connectivities were assessed with an F test and group results were evaluated with a binomial test, both at a corrected threshold.
resultsWe identified brain regions with significant inputs to and outputs from the sgACC. Clustering analyses of Granger causality inputs, but not Granger causality outputs or resting state connectivity features revealed distinct subject clusters, effectively distinguishing individuals with different levels of depressive symptom severity and those with comorbidities. Specifically, weaker projections from the fronto-parietal and orbitofrontal cortices, anterior insula, temporal cortices, and cerebellum to the sgACC characterized five clusters with low to high scores of depression as well as comorbid internalizing and externalizing problems. Machine learning using a logistic classifier with the significant "GCA-in" features and 5-fold cross-validation achieved 87% accuracy in distinguishing subject clusters, including those with high vs. low depressive symptom severity levels. DISCUSSION: These new findings specify the functional inputs and outputs of the sgACC and highlight an outsized role of sgACC inputs in distinguishing individuals' depressive symptom severity in a neurotypical population.
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.