Investigating the contribution of subcortical salience network structures to a measure of social cognition across neurodegenerative diseases
Bibliographic record
Abstract
Abstract Background Social cognition is impacted early in the disease progression of many neurodegenerative diseases (ND). The Salience network (SN) is an intrinsically connected brain network responsible for social cognitive function. Keys hubs of this brain network, the anterior insula (AI) and anterior cingulate cortex (ACC), are reported to incorporate ‘bottom‐up’ signals from subcortical regions such as the amygdala and periaqueductal gray (PAG), but this mechanism and the subcortical contribution to SN connectivity is poorly understood. Our aim was to investigate the contribution of cortical and subcortical structures to SN functional connectivity and to social cognition across NDs. Method 76 participants (21 Alzheimer’s disease, 13 behavioural variant frontotemporal dementia, and 42 Parkinson’s disease) from the Ontario Neurodegenerative Research Initiative (ONDRI) baseline or one‐year follow up visits with resting state fMRI, Montreal Cognitive Assessment (MoCA) total scores, and informant‐reported socioemotional sensitivity scores using the Revised Self‐Monitoring Scale (RSMS) were included (higher score, indicating higher function). All groups were age‐ and sex‐matched. Fisher‐transformed correlation coefficients of functional connectivity from an ROI‐to‐ROI analysis between cortical and subcortical SN ROIs were used to create a mean cortical SN value and mean subcortical SN value to use in linear regression modelling with behavioural scores. Result Mean cortical and subcortical SN connectivity were significantly associated with RSMS total score (b = 2.94, p = 0.041; (b = 3.60, p = 0.014, respectively), independent of cognitive function, with higher connectivity predicting higher score. The interaction between cortical and subcortical connectivity was not significantly associated with RSMS total score. Mean cortical and subcortical connectivity was significantly associated with RSMS‐EX (expressive behaviour of others) and RSMS‐SP (self‐presentation) subscores (b = 1.36, p = 0.049; b = 1.44, p = 0.040; b coef = 1.58, p‐value = 0.033; b coef = 2.15, p‐value = 0.005, respectively). Conclusion Our results indicate a stronger contribution of subcortical structures to social cognition‐related functional connectivity across various neurodegenerative diseases. Despite previous associations with cortical regions, our evidence suggests that alterations in subcortical structures mediate changes in social cognition. Further exploration in larger cohorts is necessary, as impaired social cognition in patients with ND is associated with increased caregiver distress.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".