State and trait components of functional connectivity: Individual differences vary with mental state

Geerligs, Linda; Rubinov, Mikail; Tyler, Lorraine K.; Brayne, Carol; Bullmore, Edward T.; Calder, Andrew C.; Cusack, Rhodri; Dalgleish, Tim; Duncan, John; Henson, Richard N.; Matthews, Fiona E.; Marslen-Wilson, William D.; Rowe, James B.; Shafto, Meredith A.; Campbell, Karen; Cheung, Teresa; Davis, Simon; Kievit, Rogier; McCarrey, Anna; Mustafa, Abdur; Price, Darren; Samu, David; Taylor, Jason R.; Treder, Matthias; Tsvetanov, Kamen; van Belle, Janna; Williams, Nitin; Bates, Lauren; Emery, Tina; Erzinçlioglu, Sharon; Gadie, Andrew; Gerbase, Sofia; Georgieva, Stanimira; Hanley, Claire; Parkin, Beth; Troy, David; Auer, Tibor; Correia, Marta; Gao, Lu; Green, Emma; Henriques, Rafael; Allen, Jodie; Amery, Gillian; Amunts, Liana; Barcroft, Anne; Castle, Amanda; Dias, Cheryl; Dowrick, Jonathan; Fair, Melissa; Fisher, Hayley; Goulding, Anna; Grewal, Adarsh; Hale, Geoff; Hilton, Andrew; Johnson, Frances; Johnston, Patricia; Kavanagh-Williamson, Thea; Kwasniewska, Magdalena; McMinn, Alison; Norma...

Abstract

Resting-state functional connectivity, as measured by functional magnetic resonance imaging (fMRI), is often treated as a trait, used, for example, to draw inferences about individual differences in cognitive function, or differences between healthy or diseased populations. However, functional connectivity can also depend on the individual’s mental state. In the present study, we examined the relative contribution of state and trait components in shaping an individual’s functional architecture. We used fMRI data from a large, population-based human sample (N=587, age 18–88 years), as part of the Cambridge Centre for Aging and Neuroscience (Cam-CAN), which were collected in three mental states: resting, performing a sensorimotor task, and watching a movie. Whereas previous studies have shown commonalities across mental states in the average functional connectivity across individuals, we focused on the effects of states on the pattern of individual differences in functional connectivity. We found that state effects were as important as trait effects in shaping individual functional connectivity patterns, each explaining an approximately equal amount of variance. This was true when we looked at aging, as one specific dimension of individual differences, as well as when we looked at generic aspects of individual variation. These results show that individual differences in functional connectivity consist of state-dependent aspects, as well as more stable, trait-like characteristics. Studying individual differences in functional connectivity across a wider range of mental states will therefore provide a more complete picture of the mechanisms underlying factors such as cognitive ability, aging, and disease.

Citation

Geerligs, L., Rubinov, M., Tyler, L. K., Brayne, C., Bullmore, E. T., Calder, A. C., Cusack, R., Dalgleish, T., Duncan, J., Henson, R. N., Matthews, F. E., Marslen-Wilson, W. D., Rowe, J. B., Shafto, M. A., Campbell, K., Cheung, T., Davis, S., Kievit, R., McCarrey, A., Mustafa, A., …Henson, R. N. (2015). State and trait components of functional connectivity: Individual differences vary with mental state. Journal of Neuroscience, 35(41), 13949-13961. https://doi.org/10.1523/JNEUROSCI.1324-15.2015

• Journal Article Type: Article
• Publication Date: Oct 14, 2015
• Deposit Date: Dec 8, 2023
• Journal: Journal of Neuroscience
• Print ISSN: 0270-6474
• Electronic ISSN: 1529-2401
• Publisher: Society for Neuroscience
• Volume: 35
• Issue: 41
• Pages: 13949-13961
• DOI: https://doi.org/10.1523/JNEUROSCI.1324-15.2015
• Public URL: https://hull-repository.worktribe.com/output/4454037