Neural Noise- Neuroimaging-derived brain maps of general cognitive functioning and neurobiological signatures are reported (Translational Psychiatry, Nature).1
- Relevant for neuroimaging methods and potential targeting; psychiatry/translational focus, tier-2.1 1
Weekly enrichment (2026-07-20)
- The primary study (Translational Psychiatry, 31 Oct 2025; PMID 41173893) meta-analyzed vertex-wise associations between domain-general cognitive functioning (g) and cortical morphometry (volume, surface area, thickness, curvature, sulcal depth) across three cohorts — UK Biobank, Generation Scotland, and the Lothian Birth Cohort 1936 — with a meta-analytic N = 38,379 (age range 44–84 years).2
- g–morphometry associations varied in both magnitude and direction across the cortex (β range −0.12 to 0.17 across measures) and showed good cross-cohort agreement (mean spatial correlation r = 0.57, SD = 0.18).2
- The authors assembled existing and derived new cortical maps of 33 neurobiological characteristics from multiple modalities, including neurotransmitter receptor densities, gene expression, functional connectivity, metabolism, and cytoarchitectural similarity.2
- These 33 profiles spatially covaried along four major dimensions of cortical organization (accounting for 66.1% of the variance), and those dimensions shared spatial patterning with the g-morphometry maps (p_spin < 0.05; |r| range 0.22–0.55).2
- The paper provides an openly accessible compendium of cortex-wide and within-region spatial correlations, offered as a framework for analyzing other behavior–brain MRI associations.2
- Context on structural correlates: in UK Biobank (N = 29,004), age/sex-corrected total brain volume correlated with g at r = 0.276 (95% CI 0.252–0.300), with the largest regional correlates including insula, frontal, temporal, paracingulate and lateral occipital volumes, thalamic volume, and thalamic/association white-matter microstructure.3
- Context on multimodal machine learning: an eLife UK Biobank study (n > 14,000) combined 72 neuroimaging phenotypes across diffusion, resting-state functional, and structural MRI; stacking across modalities captured 48% of the cognition–mental-health covariation, versus 25.5–31.6% within single modalities.4
- BCI/clinical implication: reproducible multimodal brain maps of g offer candidate targets and biomarkers for neuromodulation and could inform decoding or neurofeedback, but effect sizes are modest and the work is observational and psychiatry-focused (tier-2) rather than causal BCI research.24