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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. Pattern awareness, a continuous-scale score from 100 to 400(based on a clicked icon on the computer screen) as a function ofG, means grouped by stimulus list. Panel B.Pattern awareness score as a function of overall predictivenessproportion, means grouped by stimulus list condition.
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Figure 6: Panel A. Pattern awareness, a continuous-scale score from 100 to 400(based on a clicked icon on the computer screen) as a function ofG, means grouped by stimulus list. Panel B.Pattern awareness score as a function of overall predictivenessproportion, means grouped by stimulus list condition.

Mentions: Participants who deemed the sequences to be more patterned tended to be theones who had training sequences of higher G,r = .41, p < .0001. Higher explicit awareness ofpattern related to greater test match to the training sequences,r = .47, p < .0001, and greaterpredictive behavior in the final 12 trials, r = .51,p < .0001. We ran a separate regression analysis totest for the relationship between prediction and explicit awareness whilecontrolling for other variables, because prediction on the last 12 trialsrelated significantly to these as well. First, we used theG score of a training sequence to predict perception ofexplicit awareness, and saved the residuals. When theGscore was factored out of explicit awareness in this way,predictive tendencies still significantly accounted for what was left overin those residuals, r = .27, p = .005. Thereverse is not true: Once prediction behavior is taken out of explicitawareness, G score is no longer significantly related tothese residuals, r = .08, p = .4,suggesting that prediction mediates between a sequence’s regularityand explicit awareness. We chose to use participants’ test sequencegeneration’s match to training as an additional measure of explicitawareness, and both prediction and test recall correlated with explicitawareness, even when controlling for each other, rs >.25, ps < .005. The relationship between awarenessscore, and G, and predictiveness, is shown in Figure 6.


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

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

Panel A. Pattern awareness, a continuous-scale score from 100 to 400(based on a clicked icon on the computer screen) as a function ofG, means grouped by stimulus list. Panel B.Pattern awareness score as a function of overall predictivenessproportion, means grouped by stimulus list condition.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 6: Panel A. Pattern awareness, a continuous-scale score from 100 to 400(based on a clicked icon on the computer screen) as a function ofG, means grouped by stimulus list. Panel B.Pattern awareness score as a function of overall predictivenessproportion, means grouped by stimulus list condition.
Mentions: Participants who deemed the sequences to be more patterned tended to be theones who had training sequences of higher G,r = .41, p < .0001. Higher explicit awareness ofpattern related to greater test match to the training sequences,r = .47, p < .0001, and greaterpredictive behavior in the final 12 trials, r = .51,p < .0001. We ran a separate regression analysis totest for the relationship between prediction and explicit awareness whilecontrolling for other variables, because prediction on the last 12 trialsrelated significantly to these as well. First, we used theG score of a training sequence to predict perception ofexplicit awareness, and saved the residuals. When theGscore was factored out of explicit awareness in this way,predictive tendencies still significantly accounted for what was left overin those residuals, r = .27, p = .005. Thereverse is not true: Once prediction behavior is taken out of explicitawareness, G score is no longer significantly related tothese residuals, r = .08, p = .4,suggesting that prediction mediates between a sequence’s regularityand explicit awareness. We chose to use participants’ test sequencegeneration’s match to training as an additional measure of explicitawareness, and both prediction and test recall correlated with explicitawareness, even when controlling for each other, rs >.25, ps < .005. The relationship between awarenessscore, and G, and predictiveness, is shown in Figure 6.

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.