The suppression of scale-free fMRI brain dynamics across three different sources of effort: aging, task novelty and task difficulty.

Nathan W Churchill,Cheryl Grady,Scott Peltier,Patricia A Reuter-Lorenz,Robyn Spring,Marc G Berman,Stephen C Strother,Mary K Askren,Mi Sook Jung,Bernadine Cimprich

doi:10.1038/srep30895

Abstract

There is growing evidence that fluctuations in brain activity may exhibit scale-free (“fractal”) dynamics. Scale-free signals follow a spectral-power curve of the form P(f ) ∝ f−β, where spectral power decreases in a power-law fashion with increasing frequency. In this study, we demonstrated that fractal scaling of BOLD fMRI signal is consistently suppressed for different sources of cognitive effort. Decreases in the Hurst exponent (H), which quantifies scale-free signal, was related to three different sources of cognitive effort/task engagement: 1) task difficulty, 2) task novelty, and 3) aging effects. These results were consistently observed across multiple datasets and task paradigms. We also demonstrated that estimates of H are robust across a range of time-window sizes. H was also compared to alternative metrics of BOLD variability (SDBOLD) and global connectivity (Gconn), with effort-related decreases in H producing similar decreases in SDBOLD and Gconn. These results indicate a potential global brain phenomenon that unites research from different fields and indicates that fractal scaling may be a highly sensitive metric for indexing cognitive effort/task engagement.

Highlights

Fractalness is a ubiquitous property of nature
To test the hypothesis that H is suppressed for different modulators of cognitive effort, we examined four different datasets: a block-design adaptation of the Trail-Making Test [TMT37], a fast event-related Sustained Attention to Response Task [SART38], an event-related verbal working memory task [VWMT39,40], and a block-design multi-task battery [MTAS25] consisting of different experimental condition blocks
To evaluate the effects of aging on fractal scaling, we compared younger vs. older groups for the SART and TMT tasks (Fig. 5A,B) where median age for the younger subjects was 24 and for older subjects was 68; we looked at fractal scaling as a function of age in Verbal Working Memory Task (VWMT), which included a wide distribution of ages between 36 and 71 years old (Fig. 5C), as a more challenging analysis

Summary

Introduction

Fractalness is a ubiquitous property of nature. This scale invariant, self-similar property is used to describe the growth of trees, the formation of mountains, the branching of blood vessels and the crashing of ocean waves. Neuronal spike trains have a 1/f distribution[13], and electroencephalography (EEG) has a scale-free, broadband signal[1] that is correlated with behavioural measures[2] and frequency-band analyses[3] These properties extend to blood oxygen level dependent functional magnetic resonance imaging (BOLD fMRI), as Van De Ville and colleagues[4] have established that BOLD signal can be modeled as a sum of scale-free EEG “microstates”. Inspired by prior work, which demonstrated that fractal scaling of BOLD signal is increased at rest and modulated by task performance[5,6,7], we hypothesize that fractal scaling decreases globally as a function of cognitive effort. Standard fMRI analysis methods only quantify mean BOLD activity, and treat fluctuations about the mean as noise, neglecting potential effort-related changes in BOLD dynamics

Methods

Results

Conclusion