  The distribution of intervals between human actions such as email posts or
keyboard strokes demonstrates distinct properties at short vs long time scales.
For instance, at long time scales, which are presumably controlled by complex
process such as planning and decision making, it has been shown that those
inter-event intervals follow a scale-invariant (or power-law) distribution. In
contrast, at shorter time-scales - which are governed by different process such
as sensorimotor skill - they do not follow the same distribution and little do
we know how they relate to the scale-invariant pattern. Here, we analyzed 9
millions intervals between smartphone screen touches of 84 individuals which
span several orders of magnitudes (from milliseconds to hours). To capture
these intervals, we extend a priority-based generative model to smartphone
touching events. At short-time scale, the model is governed by refractory
effects, while at longer time scales, the inter-touch intervals are governed by
the priority difference between smartphone tasks and other tasks. The
flexibility of the model allows to capture inter-individual variations at short
and long time scales while its tractability enables efficient model fitting.
According to our model, each individual has a specific power-low exponent which
is tightly related to the effective refractory time constant suggesting that
motor processes which influence the fast actions are related to the higher
cognitive processes governing the longer inter-event intervals.
