Dr Douglas Garrett, UCL-MPI

Emerging directions in the study of moment-to-moment brain signal variability: On networks and decisions

The study of moment-to-moment brain signal variability continues to gain momentum in cognitive neuroscience, yet understanding of associated principles and functions remains nascent. Our fMRI/EEG/MEG work suggests that within-person brain signal variability offers highly predictive, complementary, and even orthogonal views of brain function compared to traditional measures, across a host of different rest and parametric task conditions in healthy adults. In the current talk, I will highlight two new directions in this line of research. First, we continue to focus on understanding how “local” variability may reflect functional networks. In particular, we find in multiple fMRI studies that more variable brain signals strongly reflect higher functional network integration (i.e., lower spatio-temporal PCA dimensionality), with the thalamus playing a crucial role. Our most recent parallel EEG/fMRI work further demonstrates that adults with elevated thalamic BOLD variability (and higher network integration) also exhibit a robust posterior alpha signature during a parametric dot motion task, providing first evidence of within-person convergence between fMRI and EEG variability measures. Second, under the working hypothesis that variability of neural activity is a prerequisite for cognitive adaptability, we study the extent to which humans flexibly regulate neural (EEG) variability within-person to maximize reward during decision-making. In recent work, we encouraged participants to use either a “liberal” (by penalizing misses) or “conservative” (by penalizing false alarms) response criterion for reporting perceptual targets. We found that time-series entropy was higher when participants invoked a more liberal response mode, perhaps reflecting the top-down implementation of within-person variability modulation. Strikingly, greater upregulation of entropy in frontal electrodes during the liberal condition (liberal minus conservative) solely predicted more liberal shifts in signal-detection-theoretic criterion. Thus, we argue that those who more flexibly modulate neural variability also more flexibly adjust their behavioural responses to maximize reward. Finally, I will embed these distinct sets of findings within existing and emerging perspectives on the nature and functional consequences of brain signal variability in humans.

Keywords: Lifespan development, brain dynamics, neuromodulation, ageing brain