Computational modeling has long been one of the traditional pillars of cognitive science. Unfortunately, the computer models of cognition being developed today have not kept up with the enormous changes that have taken place in computer technology and, especially, in human-computer interfaces. For all intents and purposes, modeling is still done today as it was 25, or even 35, years ago. Everyone still programs in his or her own favorite programming language, source code is rarely made available, accessibility of models (...) to non-programming researchers is essentially non-existent, and even for other modelers, the profusion of source code in a multitude of programming languages, written without programming guidelines, makes it almost impossible to access, check, explore, re-use, or continue to develop. It is high time to change this situation, especially since the tools are now readily available to do so. We propose that the modeling community adopt three simple guidelines that would ensure that computational models would be accessible to the broad range of researchers in cognitive science. We further emphasize the pivotal role that journal editors must play in making computational models accessible to readers of their journals. (shrink)

Adapting gross motor movement to match the tempo of auditory rhythmic stimulation is a complex skill with a long developmental trajectory. Drumming tasks have previously been employed with infants and young children to measure the emergence of rhythmic entrainment, and may provide a tool for identification of those with atypical rhythm perception and production. Here we describe a new protocol for measuring infant rhythmic movement that can be employed at scale. In the current study, 50 two-year-olds drummed along with the (...) audiovisual presentation of four steady rhythms, using videos of isochronous drumming at 400, 500, 600, and 700 ms IOI, and provided their spontaneous motor tempo by drumming in silence. Toddlers’ drumming is observed from video recordings made in participants’ own homes, obtained via the Lookit platform for online infant studies. We use OpenPose deep-learning model to generate wireframe estimates of hand and body location for each video. The vertical displacement of the hand was extracted, and the power and frequency of infants’ rhythmic entrainment quantified using Fast Fourier Transforms. We find evidence for age-appropriate tempo-flexibility in our sample. Our results demonstrate the feasibility of a fully digital approach to measuring rhythmic entrainment from within the participant’s home, from early in development. (shrink)