Back to Search Start Over

Loneliness is linked to specific subregional alterations in hippocampus-default network covariation.

Authors :
Zajner C
Spreng RN
Bzdok D
Source :
Journal of neurophysiology [J Neurophysiol] 2021 Dec 01; Vol. 126 (6), pp. 2138-2157. Date of Electronic Publication: 2021 Nov 24.
Publication Year :
2021

Abstract

Social interaction complexity makes humans unique. But in times of social deprivation, this strength risks exposure of important vulnerabilities. Human social neuroscience studies have placed a premium on the default network (DN). In contrast, hippocampus (HC) subfields have been intensely studied in rodents and monkeys. To bridge these two literatures, we here quantified how DN subregions systematically covary with specific HC subfields in the context of subjective social isolation (i.e., loneliness). By codecomposition using structural brain scans of ∼40,000 UK Biobank participants, loneliness was specially linked to midline subregions in the uncovered DN patterns. These association cortex patterns coincided with concomitant HC patterns implicating especially CA1 and molecular layer. These patterns also showed a strong affiliation with the fornix white matter tract and the nucleus accumbens. In addition, separable signatures of structural HC-DN covariation had distinct associations with the genetic predisposition for loneliness at the population level. NEW & NOTEWORTHY The hippocampus and default network have been implicated in rich social interaction. Yet, these allocortical and neocortical neural systems have been interrogated in mostly separate literatures. Here, we conjointly investigate the hippocampus and default network at a subregion level, by capitalizing structural brain scans from ∼40,000 participants. We thus reveal unique insights on the nature of the "lonely brain" by estimating the regimes of covariation between the hippocampus and default network at population scale.

Details

Language :
English
ISSN :
1522-1598
Volume :
126
Issue :
6
Database :
MEDLINE
Journal :
Journal of neurophysiology
Publication Type :
Academic Journal
Accession number :
34817294
Full Text :
https://doi.org/10.1152/jn.00339.2021