Fine-grained alignment of cortical signals to smartphone touchscreen temporal pattern
Smartphone use varies ranging from rapid, rhythmic tapping (e.g., texting) to slower, irregular scrolling (e.g., browsing), resulting in diverse temporal patterns of inter-touch intervals. The underlying brain processes may dynamically align to these behaviors. We investigated population neural signals captured by using EEG during hour long smartphone use sessions (n = 53 subjects, accumulating 136869 interactions). We grouped the brain signals according to the transition patterns between consecutive touchscreen intervals (next-interval statistics), resulting in a matrix of EEG signals. Using data-driven dimensionality reduction on this matrix, we identified low-dimensional neuro-behavioral clusters that captured brain signal features associated with specific next-interval statistics. These neuro-behavioral clusters were found for diverse cortical locations spanning occipital, parietal and frontal cortices, suggesting a cortex-wide alignment to the next-interval statistics. Notably, these clusters were observed predominantly before rather than after the touchscreen interactions and they varied across individuals, suggesting personalized strategies for planning and executing smartphone use. Our findings indicate that the brain tracks and adapts to the fine-grained temporal patterns in touchscreen behavior, likely to support efficient smartphone interactions. More broadly, this work demonstrates how naturalistic smartphone use can reveal dynamic, individualized cortical adaptations to real-world temporal structure.