Connectome-based individualized prediction of loneliness

Chunliang Feng, Li Wang, Ting Li, Pengfei Xu*

*Corresponding author for this work

    Research output: Contribution to journalArticleAcademicpeer-review

    12 Citations (Scopus)
    106 Downloads (Pure)

    Abstract

    Loneliness is an increasingly prevalent condition linking with enhanced morbidity and premature mortality. Despite recent proposal on medicalization of loneliness, so far no effort has been made to establish a model capable of predicting loneliness at the individual level. Here, we applied a machine-learning approach to decode loneliness from whole-brain resting-state functional connectivity (RSFC). The relationship between whole-brain RSFC and loneliness was examined in a linear predictive model. The results revealed that individual loneliness could be predicted by within- and between-network connectivity of prefrontal, limbic and temporal systems, which are involved in cognitive control, emotional processing and social perceptions and communications, respectively. Key nodes that contributed to the prediction model comprised regions previously implicated in loneliness, including the dorsolateral prefrontal cortex, lateral orbital frontal cortex, ventromedial prefrontal cortex, caudate, amygdala and temporal regions. Our findings also demonstrated that both loneliness and associated neural substrates are modulated by levels of neuroticism and extraversion. The current data-driven approach provides the first evidence on the predictive brain features of loneliness based on organizations of intrinsic brain networks. Our work represents initial efforts in the direction of making individualized prediction of loneliness that could be useful for diagnosis, prognosis and treatment.

    Original languageEnglish
    Pages (from-to)353-365
    Number of pages13
    JournalSocial Cognitive and Affective Neuroscience
    Volume14
    Issue number4
    DOIs
    Publication statusPublished - Apr-2019

    Keywords

    • loneliness
    • connectome-based predictive modeling
    • resting-state functional connectivity
    • PERCEIVED SOCIAL-ISOLATION
    • CROSS-LAGGED ANALYSES
    • RESTING-STATE
    • FUNCTIONAL CONNECTIVITY
    • ENVIRONMENTAL CONTRIBUTIONS
    • HUMAN BRAIN
    • NETWORK
    • SELF
    • ATTENTION
    • CORTEX

    Cite this