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Action perception as hypothesis testing

View Article: PubMed Central - PubMed

ABSTRACT

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.

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Related in: MedlinePlus

Results of the simulations, arrival time. Every iteration lasts 12 msec. For simplicity, saccades are assumed to have a fixed duration of 16 × 12 = 192 msec. Arrival time is calculated as the difference between the time when the hand (of the actor) and the eye (of the participant) land on the object, as in the original study of Ambrosini et al. (2011). It is negative when the eye lands on the object before the hand. Note that arrival times for the big object (power grasp) are more anticipatory than for the small object (precision grip). This phenomena was also observed in the simulations (compare Fig. 5, Fig. 6).
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fig4: Results of the simulations, arrival time. Every iteration lasts 12 msec. For simplicity, saccades are assumed to have a fixed duration of 16 × 12 = 192 msec. Arrival time is calculated as the difference between the time when the hand (of the actor) and the eye (of the participant) land on the object, as in the original study of Ambrosini et al. (2011). It is negative when the eye lands on the object before the hand. Note that arrival times for the big object (power grasp) are more anticipatory than for the small object (precision grip). This phenomena was also observed in the simulations (compare Fig. 5, Fig. 6).

Mentions: The results of our simulations are remarkably similar to those of the original study (Fig. 4). The key result is a significant advantage for the pre-shape over the no-shape condition, for both power grasp and precision grip. This result stems from the fact that in the pre-shape, information about the actor's goal can be inferred from the hand movement kinematics, enabling an anticipatory saccade to the target to confirm the agent's (or participant's) beliefs.


Action perception as hypothesis testing
Results of the simulations, arrival time. Every iteration lasts 12 msec. For simplicity, saccades are assumed to have a fixed duration of 16 × 12 = 192 msec. Arrival time is calculated as the difference between the time when the hand (of the actor) and the eye (of the participant) land on the object, as in the original study of Ambrosini et al. (2011). It is negative when the eye lands on the object before the hand. Note that arrival times for the big object (power grasp) are more anticipatory than for the small object (precision grip). This phenomena was also observed in the simulations (compare Fig. 5, Fig. 6).
© Copyright Policy - CC BY
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5383736&req=5

fig4: Results of the simulations, arrival time. Every iteration lasts 12 msec. For simplicity, saccades are assumed to have a fixed duration of 16 × 12 = 192 msec. Arrival time is calculated as the difference between the time when the hand (of the actor) and the eye (of the participant) land on the object, as in the original study of Ambrosini et al. (2011). It is negative when the eye lands on the object before the hand. Note that arrival times for the big object (power grasp) are more anticipatory than for the small object (precision grip). This phenomena was also observed in the simulations (compare Fig. 5, Fig. 6).
Mentions: The results of our simulations are remarkably similar to those of the original study (Fig. 4). The key result is a significant advantage for the pre-shape over the no-shape condition, for both power grasp and precision grip. This result stems from the fact that in the pre-shape, information about the actor's goal can be inferred from the hand movement kinematics, enabling an anticipatory saccade to the target to confirm the agent's (or participant's) beliefs.

View Article: PubMed Central - PubMed

ABSTRACT

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.

No MeSH data available.


Related in: MedlinePlus