Abstract
Brain activity patterns are highly flexible and often complex, but also highly structured. Here we examined how fundamental properties of brain activity patterns relate to ongoing cognitive processes. To this end, we applied dimensionality reduction algorithms and pattern classifiers to functional neuroimaging data collected as participants listened to a story, temporally scrambled versions of the story, or underwent a resting state scanning session. These experimental conditions were intended to require different depths of processing and inspire different levels of cognitive engagement. We considered two primary aspects of the data. First, we treated the maximum achievable decoding accuracy across participants as an indicator of the “informativeness” of the recorded patterns. Second, we treated the number of features (components) required to achieve a threshold decoding accuracy as a proxy for the “compressibility” of the neural patterns (where fewer components indicate greater compression). Overall, we found that the peak decoding accuracy (achievable without restricting the numbers of features) was highest in the intact (unscrambled) story listening condition. However, the number of features required to achieve comparable classification accuracy was also lowest in the intact story listening condition. Taken together, our work suggests that our brain networks flexibly reconfigure according to ongoing task demands, and that the activity patterns associated with higher-order cognition and high engagement are both more informative and more compressible than the activity patterns associated with lower-order tasks and lower levels of engagement.
Significance Statement How our brains respond to ongoing experiences depends on what we are doing and thinking about, among other factors. To study how brain activity reflects ongoing cognition, we examined two fundamental aspects of brain activity under different cognitive circumstances: informativeness and compressibility. Informativeness refers to the extent to which brain patterns are both temporally specific and consistent across different people. Compressibility refers to how robust the informativeness of brain patterns is to dimensionality reduction. Brain activity evoked by higher-level cognitive tasks are both more informative and more compressible than activity evoked by lower-level tasks. Our findings suggest that our brains flexibly reconfigure themselves to optimize different aspects of how they function according to ongoing cognitive demands.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
We've revised our framing of "informativeness" and "compressibility" to more intuitively distinguish the two concepts. We've also added new analyses of synthetic data and generally strengthened (and added to) our statistical approaches.
Data and code availability
All of the code used to produce the figures and results in this manuscript, along with links to the corresponding data, may be found at github.com/ContextLab/pca paper.
