Fersiynau electronig

Dogfennau

Dangosydd eitem ddigidol (DOI)

Ideal grasping movements should maintain an appropriate probability of success, while controlling movement-related costs, in the presence of varying visual (and motor) uncertainty. It is often assumed that the probability of errors is managed by adjusting a margin for error in hand opening (e.g. opening the hand wider with increased visual uncertainty). This idea is intuitive, but non-trivial. It implies not only that the brain can estimate the amount of uncertainty, but also that it can compute how different possible alterations to the movement will affect the probability of errors—which we term the ‘probability landscape’. Previous work suggests the amount of uncertainty is factored into grasping movements. Our aim was to determine whether grasping movements are also sensitive to the probability landscape. Subjects completed three different grasping tasks, with naturally different probability landscapes, such that appropriate margin-for-error responses to increased uncertainty were qualitatively different (opening the hand wider, the same amount, or less wide). We increased visual uncertainty by blurring vision, and by covering one eye. Movements were performed without visual feedback to isolate uncertainty in the brain’s initial estimate of object properties. Changes to hand opening in response to increased visual uncertainty closely resembled those predicted by the margin-for-error account, suggesting that grasping is sensitive to the probability landscape associated with different tasks. Our findings therefore support the intuitive idea that grasping movements employ a true margin-for-error mechanism, which exerts active control over the probability of errors across changing circumstances.

Allweddeiriau

Iaith wreiddiolSaesneg
Tudalennau (o-i)1063-1075
Nifer y tudalennau13
CyfnodolynExperimental Brain Research
Cyfrol237
Rhif y cyfnodolyn4
Dyddiad ar-lein cynnar12 Chwef 2019
Dynodwyr Gwrthrych Digidol (DOIs)
StatwsCyhoeddwyd - Ebr 2019

Cyfanswm lawlrlwytho

Nid oes data ar gael
Gweld graff cysylltiadau