Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Brief Communication
  • Published:

Association between real-world experiential diversity and positive affect relates to hippocampal–striatal functional connectivity

Nature Neuroscience volume 23, pages 800–804 (2020)Cite this article

Subjects

Abstract

Experiential diversity promotes well-being in animal models. Here, using geolocation tracking, experience sampling and neuroimaging, we found that daily variability in physical location was associated with increased positive affect in humans. This effect was stronger for individuals who exhibited greater functional coupling of the hippocampus and striatum. These results link diversity in real-world daily experiences to fluctuations in positive affect and identify a hippocampal–striatal circuit associated with this bidirectional relationship.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Geolocation tracking in New York and Miami.
Fig. 2: Physical location transformed into sociodemographic feature space.
Fig. 3: Entropy–affect association is linked to hippocampal–ventral striatal connectivity.

Similar content being viewed by others

Data availability

The raw geolocation datasets generated and/or analyzed during this study are not publicly available due to the inherently identifiable nature of geolocation data, but they are available from the corresponding authors on reasonable request. The processed data necessary to reproduce the central findings in the manuscript are available at http://github.com/manateelab/NatNeuro/.

Code availability

Custom R scripts were used to analyze and plot all data. The main analysis code was used to calculate the mean and standard deviation for RE. Code is available online at http://github.com/manateelab/NatNeuro/.

References

  1. Tost, H., Champagne, F. A. & Meyer-Lindenberg, A. Environmental influence in the brain, human welfare and mental health. Nat. Neurosci. 18, 1421–1431 (2015).

    Article  CAS  Google Scholar 

  2. Marashi, V., Barnekow, A., Ossendorf, E. & Sachser, N. Effects of different forms of environmental enrichment on behavioral, endocrinological, and immunological parameters in male mice. Horm. Behav. 43, 281–292 (2003).

    Article  CAS  Google Scholar 

  3. Laviola, G. et al. Beneficial effects of enriched environment on adolescent rats from stressed pregnancies. Eur. J. Neurosci. 20, 1655–1664 (2004).

    Article  Google Scholar 

  4. Brydges, N. M., Leach, M., Nicol, K., Wright, R. & Bateson, M. Environmental enrichment induces optimistic cognitive bias in rats. Anim. Behav. 81, 169–175 (2011).

    Article  Google Scholar 

  5. Fox, N. A., Henderson, H. A., Marshall, P. J., Nichols, K. E. & Ghera, M. M. Behavioral inhibition: linking biology and behavior within a developmental framework. Annu. Rev. Psychol. 56, 235–262 (2005).

    Article  Google Scholar 

  6. Fredrickson, B. L. The broaden-and-build theory of positive emotions. Philos. Trans. R. Soc. Lond. B Biol. Sci. 359, 1367–1377 (2004).

    Article  Google Scholar 

  7. van Praag, H., Kempermann, G. & Gage, F. H. Neural consequences of environmental enrichment. Nat. Rev. Neurosci. 1, 191–198 (2000).

    Article  Google Scholar 

  8. Walsh, R. N. & Cummins, R. A. Mechanisms mediating the production of environmentally induced brain changes. Psychol. Bull. 82, 986–1000 (1975).

    Article  CAS  Google Scholar 

  9. Lisman, J. E. & Grace, A. A. The hippocampal–VTA loop: controlling the entry of information into long-term memory. Neuron 46, 703–713 (2005).

    Article  CAS  Google Scholar 

  10. Düzel, E., Bunzeck, N., Guitart-Masip, M. & Düzel, S. Novelty-related motivation of anticipation and exploration by dopamine (NOMAD): implications for healthy aging. Neurosci. Biobehav. Rev. 34, 660–669 (2010).

    Article  Google Scholar 

  11. Bevins, R. A. & Bardo, M. T. Conditioned increase in place preference by access to novel objects: antagonism by MK-801. Behav. Brain Res. 99, 53–60 (1999).

    Article  CAS  Google Scholar 

  12. Haber, S. N. & Knutson, B. The reward circuit: linking primate anatomy and human imaging. Neuropsychopharmacology 35, 4–26 (2010).

    Article  Google Scholar 

  13. Berlyne, D. E. Novelty, complexity, and hedonic value. Percept. Psychophys. 8, 279–286 (1970).

    Article  Google Scholar 

  14. Freund, J. et al. Emergence of individuality in genetically identical mice. Science 340, 756–759 (2013).

    Article  CAS  Google Scholar 

  15. Garland, E. L. et al. Upward spirals of positive emotions counter downward spirals of negativity: insights from the broaden-and-build theory and affective neuroscience on the treatment of emotion dysfunctions and deficits in psychopathology. Clin. Psychol. Rev. 30, 849–864 (2010).

    Article  Google Scholar 

  16. Sjulson, L., Peyrache, A., Cumpelik, A., Cassataro, D. & Buzsáki, G. Cocaine place conditioning strengthens location-specific hippocampal coupling to the nucleus accumbens. Neuron 98, 926–934 (2018).

  17. Cohen, M. X., Schoene-Bake, J.-C., Elger, C. E. & Weber, B. Connectivity-based segregation of the human striatum predicts personality characteristics. Nat. Neurosci. 12, 32–34 (2009).

    Article  CAS  Google Scholar 

  18. Kühn, S. et al. In search of features that constitute an “enriched environment” in humans: associations between geographical properties and brain structure. Sci. Rep. 7, 11920 (2017).

  19. Schooler, C. Psychological effects of complex environments during the life span: a review and theory. J. Intell. 8, 259–281 (1984).

    Google Scholar 

  20. Schwanen, T., Kwan, M.-P. & Ren, F. How fixed is fixed? Gendered rigidity of space–time constraints and geographies of everyday activities. Geoforum 39, 2109–2121 (2008).

    Article  Google Scholar 

  21. Beck, A.T. & Steer, R.A. BDI, Beck Depression Inventory Manual (The Psychological Corporation, Harcourt Brace Jovanovich, 1987).

  22. Spielberger, C.D. State–Trait Anxiety Inventory for adults http://ubir.buffalo.edu/xmlui/handle/10477/1873 (1983).

  23. Watson, D. & Clark, L.A. The PANAS-X: Manual for the Positive and Negative Affect Schedule–Expanded Form (University of Iowa, 1999).

  24. Freund, J. et al. Association between exploratory activity and social individuality in genetically identical mice living in the same enriched environment. Neuroscience 309, 140–152 (2015).

    Article  CAS  Google Scholar 

  25. Pinheiro, J., Bates, D., DebRoy, S. & Sarkar, D. nlme: linear and nonlinear mixed effects models. R package version 3.1-117 http://cran.r-project.org/package=nlme (2014).

  26. Akaike, H. A new look at the statistical model identification. IEEE Transactions on Automatic Control 19, 716–723 (1974).

    Article  Google Scholar 

  27. Revelle, W. An overview of the psych package, http://cran.r-project.org/web/packages/psych/index.html (2018).

  28. Satterthwaite, T. D. et al. Impact of in-scanner head motion on multiple measures of functional connectivity: relevance for studies of neurodevelopment in youth. Neuroimage 60, 623–632 (2012).

    Article  Google Scholar 

  29. Satterthwaite, T. D. et al. An improved framework for confound regression and filtering for control of motion artifact in the preprocessing of resting-state functional connectivity data. Neuroimage 64, 240–256 (2013).

    Article  Google Scholar 

  30. Power, J. D., Barnes, K. A., Snyder, A. Z., Schlaggar, B. L. & Petersen, S. E. Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. Neuroimage 59, 2142–2154 (2012).

    Article  Google Scholar 

  31. Power, J.D. et al. Methods to detect, characterize, and remove motion artifact in resting state fMRI. Neuroimage 84, 32–41. (2014).

  32. Kebets, V. et al. Somatosensory–motor dysconnectivity spans multiple transdiagnostic dimensions of psychopathology. Biol. Psychiatry 86, 779–791 (2019)

  33. Buckner, R. L., Andrews-Hanna, J. R. & Schacter, D. L. The brain’s default network: anatomy, function, and relevance to disease. Ann. N Y Acad. Sci. 1124, 1–38 (2008).

    Article  Google Scholar 

  34. Desikan, R. S. et al. An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage 31, 968–980 (2006).

    Article  Google Scholar 

  35. Tost, H. et al. Neural correlates of individual differences in affective benefit of real-life urban green space exposure. Nat. Neurosci. 22, 1389–1393 (2019).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

C.A.H. was supported in part by a Klingenstein–Simons Fellowship Award, an NSF Career Award (1654393), a Jacobs Foundation Early Career Fellowship and the NYU Vulnerable Brain Project. A.S.H. was supported by a John Templeton Award and NIH grants 3R01CA206456-03S1 and 1R01AG051346-01. We thank N. Bryce and L. Hunter for assistance with data collection.

Author information

Authors and Affiliations

  1. Department of Psychology, University of Miami, Coral Gables, FL, USA

    Aaron S. Heller, C. E. Chiemeka Ezie, Travis R. Reneau, Lara M. Baez & Conor J. Gibbons

  2. Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA

    Tracey C. Shi

  3. Department of Psychology, New York University, New York, NY, USA

    Tracey C. Shi & Catherine A. Hartley

  4. School of Medicine, New York University, New York, NY, USA

    C. E. Chiemeka Ezie

  5. New York University Center for Neural Science and Langone Health Neuroscience Institute, New York, NY, USA

    Catherine A. Hartley

Authors
  1. Aaron S. Heller
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Tracey C. Shi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. C. E. Chiemeka Ezie
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Travis R. Reneau
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Lara M. Baez
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Conor J. Gibbons
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Catherine A. Hartley
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

A.S.H. and C.A.H. conceived and designed the study. T.C.S. and C.E.C.E. collected the data. A.S.H., T.C.S., T.R.R., L.M.B., C.J.G. and C.A.H. analyzed the data. A.S.H. and C.A.H. interpreted the data and wrote the manuscript with input from the other authors.

Corresponding authors

Correspondence to Aaron S. Heller or Catherine A. Hartley.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature Neuroscience thanks Ulman Lindenberger, Andreas M. Brandmaier, Tali Sharot and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Positive and negative affect by day of week.

This figure depicts the parameter estimates of the effect of day of week (DOW) on positive and negative affect from linear mixed-effects models that included RE, time of day EMA was collected, distance travelled, mean temperature and precipitation (from the modal location of that day for that participant), and cohort as predictors (n = 122 independent human participants). Of the variables in models, only day of the week was also significantly associated with PA, with PA lower early to mid-week relative to the weekend (F(3834) = 2.8, p = 0.011). Both temperature (B = 0.062, t(3835) = 2.585, p = 0.01) and day of the week (F(3835) = 3.0, p = 0.006) were significantly associated with negative affect, which was greater on higher temperature days and in the early to mid-week relative to the weekend. Error bars represent standard error of parameter estimate.

Supplementary information

Supplementary Information

Supplementary Appendix 1, Supplementary Tables 1–5, Supplementary Figs. 1–7 and Supplementary Notes 1–3.

Reporting Summary

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Heller, A.S., Shi, T.C., Ezie, C.E.C. et al. Association between real-world experiential diversity and positive affect relates to hippocampal–striatal functional connectivity. Nat Neurosci 23, 800–804 (2020). https://doi.org/10.1038/s41593-020-0636-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41593-020-0636-4

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing