Lifespan Neural Dynamics Group

Head: Douglas D. Garrett

The Lifespan Neural Dynamics Group (LNDG) seeks to establish the importance of moment-to-moment neural variability as a crucial “signal” in cognitive neuroscience, a body of work we recently summarized in an opinion in Neuron (Waschke et al., 2021).

Three noteworthy studies represent crucial steps for the LNDG in 2021-22. First, we provided the first longitudinal evidence linking compression of BOLD variability, older age, and decline in cognitive performance across multiple cognitive domains over a two-year period (Garrett et al., 2021, Cereb Cortex). We showed that the fronto-striato-thalamic system emerged as a core neural substrate for change-change coupling among brain signal variability, age, and cognition. The presence of such associations within a narrow two-year window bolsters the promise of signal variability as a sensitive probe for studying age-graded changes in human cognition. Second, our multi-modal study of the neural bases of perceptual uncertainty was published (Kosciessa et al., 2021, Nat Comms). We showed that greater uncertainty lowered evidence accumulation for individual stimulus features, shifted cortex from a rhythmic to an asynchronous/excited regime, and heightened neuromodulatory arousal. Crucially, this constellation of within-person effects was dominantly reflected in the uncertainty-driven upregulation of thalamic activity, a region that may play a central role in how the brain modulates neural excitability under uncertainty.

Third, we applied several approaches my group has developed in the domain of psychiatric treatment prediction (Månsson, Waschke et al., 2021, Biol Psychiatry). 45 patients with social anxiety disorder were scanned twice (11 weeks apart) using task-based and resting-state fMRI to capture neural variability. Task-based signal variability was the strongest predictor of treatment outcome (nine weeks later), outperforming self-reports, resting-state variability, and mean-based measures of neural activity. Notably, task-based signal variability showed excellent test-retest reliability (ICC = 0.80), despite being measured in less than 3 minutes. We thus found novel evidence that BOLD variability may serve as a highly efficient prognostic indicator of clinical outcome.

Finally, ongoing work continues to integrate scientists on the London side of the Centre. For example, LNDG PhD student Liliana Polanski continues to work closely with Magda Dubois (PhD student) and Tobias Hauser (PI) on the neural bases of the explore-exploit tradeoff. LNDG PhD student Alexander Skowron also has established a formal collaboration with Steve Fleming (PI) and his group to integrate metacognitive approaches into Alex’s latent state learning paradigms. We will continue to further establish collaborations between the Berlin and London Centre sites throughout 2022.  

Key publications

1. Månsson, K.N.T., Waschke, L., Manzourid, A., Furmark, T., Fischer, H., & Garrett, D.D. (2022). Moment-to-moment brain signal variability reliably predicts psychiatric treatment outcome. Biological Psychiatry. https://www.biologicalpsychiatryjournal.com/article/S0006-3223(21)01664-4/fulltext
2. Garrett, D.D., Skowron, A., Wiegert, S., Adolf, J., Dahle, C.L., Lindenberger, U., & Raz, N. (2021). Lost dynamics and the dynamics of loss: Longitudinal compression of brain signal variability is coupled with declines in functional integration and cognitive performance. Cerebral Cortex, 31, 5239–5252. https://academic.oup.com/cercor/article/31/11/5239/6326759
3. Kosciessa, J.Q., Lindenberger, U., & Garrett, D.D. (2021). Thalamocortical excitability adjustments guide human perception under uncertainty. Nature Communications, 12:2430. https://www.nature.com/articles/s41467-021-22511-7
4. Waschke, L., Kloosterman, N., *Obleser, J., & *Garrett, D.D. (2021). Behaviour needs neural variability. Neuron, 109, 1-16. https://www.cell.com/neuron/pdf/S0896-6273(21)00045-3.pdf