Home alone: A population neuroscience investigation of brain morphology substrates
Bibliographic record
Abstract
As a social species, ready exchange with peers is a pivotal asset - our "social capital". Yet, single-person households have come to pervade metropolitan cities worldwide, with unknown consequences in the long run. Here, we systematically explore the morphological manifestations associated with singular living in ∼40,000 UK Biobank participants. The uncovered population-level signature spotlights the highly associative default mode network, in addition to findings such as in the amygdala central, cortical and corticoamygdaloid nuclei groups, as well as the hippocampal fimbria and dentate gyrus. Both positive effects, equating to greater gray matter volume associated with living alone, and negative effects, which can be interpreted as greater gray matter associations with not living alone, were found across the cortex and subcortical structures Sex-stratified analyses revealed male-specific neural substrates, including somatomotor, saliency and visual systems, while female-specific neural substrates centered on the dorsomedial prefrontal cortex. In line with our demographic profiling results, the discovered neural pattern of living alone is potentially linked to alcohol and tobacco consumption, anxiety, sleep quality as well as daily TV watching. The persistent trend for solitary living will require new answers from public-health decision makers. SIGNIFICANCE STATEMENT: Living alone has profound consequences for mental and physical health. Despite this, there has been a rapid increase in single-person households worldwide, with the long-term consequences yet unknown. In the largest study of its kind, we investigate how the objective lack of everyday social interaction, through living alone, manifests in the brain. Our population neuroscience approach uncovered a gray matter signature that converged on the 'default network', alongside targeted subcortical, sex and demographic profiling analyses. The human urge for social relationships is highlighted by the evolving COVID-19 pandemic. Better understanding of how social isolation relates to the brain will influence health and social policy decision-making of pandemic planning, as well as social interventions in light of global shifts in houseful structures.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".