Action perception as hypothesis testing

We present a novel computational model that describes action perception as an active inferential process that combines motor prediction (the reuse of our own motor system to predict perceived movements) and hypothesis testing (the use of eye movements to disambiguate amongst hypotheses). The system uses a generative model of how (arm and hand) actions are performed to generate hypothesis-specific visual predictions, and directs saccades to the most informative places of the visual scene to test these predictions - and underlying hypotheses. We test the model using eye movement data from a human action observation study. In both the human study and our model, saccades are proactive whenever context affords accurate action prediction; but uncertainty induces a more reactive gaze strategy, via tracking the observed movements. Our model offers a novel perspective on action observation that highlights its active nature based on prediction dynamics and hypothesis testing.

Publication type: 
Articolo
Author or Creator: 
Francesco Donnarumma
Marcello Costantini
Ettore Ambrosini
Karl Friston
Giovanni Pezzulo
Publisher: 
Masson, Milano , Italia
Source: 
Cortex (Online) 89 (2017): 45–60. doi:10.1016/j.cortex.2017.01.016
Date: 
2017
Resource Identifier: 
http://www.cnr.it/prodotto/i/367440
https://dx.doi.org/10.1016/j.cortex.2017.01.016
info:doi:10.1016/j.cortex.2017.01.016
http://www.sciencedirect.com/science/article/pii/S0010945217300308
Language: 
Eng
ISTC Author: 
Giovanni Pezzulo's picture
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