Bias and learning in temporal binding: Intervals between actions and outcomes are compressed by prior bias

Consciousness and Cognition 22 (4):1174-1180 (2013)
  Copy   BIBTEX

Abstract

It has consistently been shown that agents judge the intervals between their actions and outcomes as compressed in time, an effect named intentional binding. In the present work, we investigated whether this effect is result of prior bias volunteers have about the timing of the consequences of their actions, or if it is due to learning that occurs during the experimental session. Volunteers made temporal estimates of the interval between their action and target onset , or between two events . Our results show that temporal estimates become shorter throughout each experimental block in both conditions. Moreover, we found that observers judged intervals between action and outcomes as shorter even in very early trials of each block. To quantify the decrease of temporal judgments in experimental blocks, exponential functions were fitted to participants’ temporal judgments. The fitted parameters suggest that observers had different prior biases as to intervals between events in which action was involved. These findings suggest that prior bias might play a more important role in this effect than calibration-type learning processes

Links

PhilArchive



    Upload a copy of this work     Papers currently archived: 93,296

External links

Setup an account with your affiliations in order to access resources via your University's proxy server

Through your library

Similar books and articles

Intentions and expectations in temporal binding.Kai Engbert & Andreas Wohlschläger - 2007 - Consciousness and Cognition 16 (2):255-264.
Temporal binding and the perception/cognition boundary.Christoph Hoerl - 2019 - In Adrian Bardon, Valtteri Arstila, Sean Power & Argiro Vatakis (eds.), The Illusions of Time: Philosophical and Psychological Essays on Timing and Time Perception. Palgrave Macmillan. pp. 275-287.

Analytics

Added to PP
2013-12-15

Downloads
15 (#976,359)

6 months
29 (#110,451)

Historical graph of downloads
How can I increase my downloads?