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Prediction during statistical learning, and implications for the implicit/explicit divide.

Dale R, Duran ND, Morehead JR - Adv Cogn Psychol (2012)

Bottom Line: We offer a novel experimental context to explore prediction, and report results from a simple sequential learning task designed to promote predictive behaviors in participants as they responded to a short sequence of simple stimulus events.Analysis of computer-mouse trajectories revealed that (a) participants almost always anticipate events in some manner, (b) participants exhibit two stable patterns of behavior, either reacting to vs. predicting future events, (c) the extent to which participants predict relates to performance on a recall test, and (d) explicit reports of perceiving patterns in the brief sequence correlates with extent of prediction.We end with a discussion of implicit and explicit statistical learning and of the role prediction may play in both kinds of learning.

View Article: PubMed Central - PubMed

ABSTRACT
Accounts of statistical learning, both implicit and explicit, often invoke predictive processes as central to learning, yet practically all experiments employ non-predictive measures during training. We argue that the common theoretical assumption of anticipation and prediction needs clearer, more direct evidence for it during learning. We offer a novel experimental context to explore prediction, and report results from a simple sequential learning task designed to promote predictive behaviors in participants as they responded to a short sequence of simple stimulus events. Predictive tendencies in participants were measured using their computer mouse, the trajectories of which served as a means of tapping into predictive behavior while participants were exposed to very short and simple sequences of events. A total of 143 participants were randomly assigned to stimulus sequences along a continuum of regularity. Analysis of computer-mouse trajectories revealed that (a) participants almost always anticipate events in some manner, (b) participants exhibit two stable patterns of behavior, either reacting to vs. predicting future events, (c) the extent to which participants predict relates to performance on a recall test, and (d) explicit reports of perceiving patterns in the brief sequence correlates with extent of prediction. We end with a discussion of implicit and explicit statistical learning and of the role prediction may play in both kinds of learning.

No MeSH data available.


Panel A. Stimuli locations on computer screen. Panel B. Exampleregion for reactive and predictive movements when mouse position isrecorded after disappearance of stimulus t-1 and atthe onset of stimulus t (750 ms lapsed). Panel C.Hypothetical trajectory examples for illustration ofpredictive/reactive categories during the 750-ms inter-stimulusinterval. (Note that open circles reflect no stimuli on the screen,but indicate stimulus t andt-1.)
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Figure 1: Panel A. Stimuli locations on computer screen. Panel B. Exampleregion for reactive and predictive movements when mouse position isrecorded after disappearance of stimulus t-1 and atthe onset of stimulus t (750 ms lapsed). Panel C.Hypothetical trajectory examples for illustration ofpredictive/reactive categories during the 750-ms inter-stimulusinterval. (Note that open circles reflect no stimuli on the screen,but indicate stimulus t andt-1.)

Mentions: The interface was programmed using Adobe Flash, in which the computer-mousecursor could be accessed for its x and y coordinates at a rate ofapproximately 40 Hz. The interface occupied a 500-by-500-pixel region withinthe users’ Internet browser (see Figure1, Panel A).Target stimuli were 35-pixel-diameter black circlesthat appeared individually during training, arrayed in a 2 × 2 grid.Participants used only their computer pointer to interact with theinterface.


Prediction during statistical learning, and implications for the implicit/explicit divide.

Dale R, Duran ND, Morehead JR - Adv Cogn Psychol (2012)

Panel A. Stimuli locations on computer screen. Panel B. Exampleregion for reactive and predictive movements when mouse position isrecorded after disappearance of stimulus t-1 and atthe onset of stimulus t (750 ms lapsed). Panel C.Hypothetical trajectory examples for illustration ofpredictive/reactive categories during the 750-ms inter-stimulusinterval. (Note that open circles reflect no stimuli on the screen,but indicate stimulus t andt-1.)
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3376885&req=5

Figure 1: Panel A. Stimuli locations on computer screen. Panel B. Exampleregion for reactive and predictive movements when mouse position isrecorded after disappearance of stimulus t-1 and atthe onset of stimulus t (750 ms lapsed). Panel C.Hypothetical trajectory examples for illustration ofpredictive/reactive categories during the 750-ms inter-stimulusinterval. (Note that open circles reflect no stimuli on the screen,but indicate stimulus t andt-1.)
Mentions: The interface was programmed using Adobe Flash, in which the computer-mousecursor could be accessed for its x and y coordinates at a rate ofapproximately 40 Hz. The interface occupied a 500-by-500-pixel region withinthe users’ Internet browser (see Figure1, Panel A).Target stimuli were 35-pixel-diameter black circlesthat appeared individually during training, arrayed in a 2 × 2 grid.Participants used only their computer pointer to interact with theinterface.

Bottom Line: We offer a novel experimental context to explore prediction, and report results from a simple sequential learning task designed to promote predictive behaviors in participants as they responded to a short sequence of simple stimulus events.Analysis of computer-mouse trajectories revealed that (a) participants almost always anticipate events in some manner, (b) participants exhibit two stable patterns of behavior, either reacting to vs. predicting future events, (c) the extent to which participants predict relates to performance on a recall test, and (d) explicit reports of perceiving patterns in the brief sequence correlates with extent of prediction.We end with a discussion of implicit and explicit statistical learning and of the role prediction may play in both kinds of learning.

View Article: PubMed Central - PubMed

ABSTRACT
Accounts of statistical learning, both implicit and explicit, often invoke predictive processes as central to learning, yet practically all experiments employ non-predictive measures during training. We argue that the common theoretical assumption of anticipation and prediction needs clearer, more direct evidence for it during learning. We offer a novel experimental context to explore prediction, and report results from a simple sequential learning task designed to promote predictive behaviors in participants as they responded to a short sequence of simple stimulus events. Predictive tendencies in participants were measured using their computer mouse, the trajectories of which served as a means of tapping into predictive behavior while participants were exposed to very short and simple sequences of events. A total of 143 participants were randomly assigned to stimulus sequences along a continuum of regularity. Analysis of computer-mouse trajectories revealed that (a) participants almost always anticipate events in some manner, (b) participants exhibit two stable patterns of behavior, either reacting to vs. predicting future events, (c) the extent to which participants predict relates to performance on a recall test, and (d) explicit reports of perceiving patterns in the brief sequence correlates with extent of prediction. We end with a discussion of implicit and explicit statistical learning and of the role prediction may play in both kinds of learning.

No MeSH data available.