Lifespan Neural Dynamics Group

The human brain is remarkably dynamic – Why?

Various subdisciplines within neuroscience have long shown that the brain is inherently dynamic and variable across moments at every level of the nervous system. Many researchers have typically conceived of variability as either (a) measurement error or (b) neural “noise,” a nuisance factor that presumably interferes with the efficiency of neural processes. With respect to aging, the concepts of “noisy” and inefficient processing have been discussed since the 1950s (see Garrett, McIntosh, & Grady, 2014), but it is only comparatively recently that directly examining within-subject brain signal variability in vivo has been employed as a means of testing the notion of age-related neural noise. Perhaps surprisingly, neural variability may be highly functional for neural systems, indexing important benefits such as increased dynamic range and systemic flexibility/adaptability (cf. Garrett, Samanez-Larkin et al., 2013). Viewed from this perspective, it is possible to reframe brain aging as a generalized process of increasing system rigidity and loss of dynamic range that manifests in reduced brain signal variability. The Lifespan Neural Dynamics Group (LNDG) tests this conceptualization by examining electroencephalographic (EEG) and functional magnetic resonance imaging (fMRI) brain signal variability and dynamics in relation to lifespan development, cognition, neurochemistry, network dynamics, and brain structure.

Recent Publications

Kloosterman, N. A., de Gee, J. W., Werkle-Bergner, M., Lindenberger, U., Garrett, D. D., & Fahrenfort, J. J. (2019). Humans strategically shift decision bias by flexibly adjusting sensory evidence accumulation in visual cortex. eLife, 8: e37321. https://doi.org/10.7554/eLife.37321

Salami, A., Garrett, D., Wahlin, A., Rieckmann, A., Papenberg, G., Karalija, N., ... Nyberg, L. (2019). Dopamine D2/3 binding potential modulates neural signatures of working memory in a load-dependent fashion. Journal of Neuroscience, 39, 537–547. https://doi.org/10.1523/JNEUROSCI.1493-18.2018

Garrett, D. D., Epp, S. M., Perry, A., & Lindenberger, U. (2018). Local temporal variability reflects functional integration in the human brain. NeuroImage, 183, 776–787. https://doi.org/10.1016/j.neuroimage.2018.08.019

Grady, C. L., & Garrett, D. D. (2018). Brain signal variability is modulated as a function of internal and external demand in younger and older adults. NeuroImage, 169, 510–523. https://doi.org/10.1016/j.neuroimage.2017.12.031

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Key References

Garrett, D. D., Lindenberger, U., Hoge, R., & Gauthier, C. J. (2017). Age differences in brain signal variability are robust to multiple vascular controls. Scientific Reports, 7:10149. https://doi.org/10.1038/s41598-017-09752-7

Grandy, T. H., Garrett, D. D., Schmiedek, F., & Werkle-Bergner, M. (2016). On the estimation of brain signal entropy from sparse neuroimaging data. Scientific Reports, 6:23073. doi: 10.1038/ srep23073

Garrett, D. D., Nagel, I. E., Preuschhof, C., Burzynska, A. Z., Marchner, J., Wiegert, S., ... Lindenberger, U. (2015). Amphetamine modulates brain signal variability and working memory in younger and older adults. Proceedings of the National Academy of Sciences USA, 112, 7593–7598. doi: 10.1073/pnas. 1504090112

Garrett, D. D., McIntosh, A. R., & Grady, C. L. (2014). Brain signal variability is parametrically modifiable. Cerebral Cortex, 24, 2931–2940. doi: 10.1093/ cercor/bht150

Garrett, D. D., Samanez-Larkin, G. R., MacDonald, S. W. S., Lindenberger, U., McIntosh, A. R., & Grady, C. L. (2013). Moment-to-moment brain signal variability: A next frontier in human brain mapping? Neuroscience & Biobehavioral Reviews, 37, 610–624. doi: 10.1016/ j.neubiorev.2013.02.015

Garrett, D. D., Kovacevic, N., McIntosh, A. R., & Grady, C. L. (2013). The modulation of BOLD variability between cognitive states varies by age and processing speed. Cerebral Cortex, 23, 684–693. doi: 10.1093/cercor/ bhs055

Garrett, D. D., Kovacevic, N., McIntosh, A. R., & Grady, C. L. (2011). The importance of being variable. Journal of Neuroscience, 31, 4496–4503. doi: 10.1523/ jneurosci.5641-10.2011

Garrett, D. D., Kovacevic, N., McIntosh, A. R., & Grady, C. L. (2010). Blood oxygen level-dependent signal variability is more than just noise. Journal of Neuroscience, 30, 4914–4921. doi: 10.1523/jneurosci. 5166-09.2010