Ioannis Delis

TL;DR: The data questions the widely held view that 6 facial expression patterns are universal, instead suggesting 4 latent expressive patterns with direct implications for emotion communication, social psychology, cognitive neuroscience, and social robotics.

TL;DR: This paper refers to the hypothesis that the central nervous system generates desired muscle contractions by combining a small number of predefined modules, called muscle synergies, and suggests that synergy extraction methods should explicitly take into account task execution variables.

TL;DR: This method showed that populations of retinal ganglion cells carried information in their spike timing on the ten-milliseconds-scale about spatial details of natural images, and first-spike latencies carried the majority of information provided by the whole spike train about fine-scale image features, and supplied almost as much information about coarse natural image features as firing rates.

TL;DR: A new model is introduced (named space-by-time decomposition) that factorizes muscle activations into concurrent spatial and temporal modules that are compatible with the modules extracted from existing models, such as synchronous synergies and temporal primitives, and generalize time-varying synergies.

TL;DR: A novel computational framework based on single-trial task decoding from muscle synergy activation features finds that time-varying and synchronous synergies with similar number of parameters are equally efficient in task decoding, suggesting that in this experimental paradigm they are equally valid representations of muscle synergies.