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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.


The percentage of participants (from all 11 G-scoresequences) that exhibit reactive (proportion prediction = 0) orpredictive (proportion prediction = 1) response modes across48-position sequences divided into eight blocks. (Note that Block 1shows 6 bins because Block 7 contained no participants. This 0 wasincluded in the analysis, however.)
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Figure 3: The percentage of participants (from all 11 G-scoresequences) that exhibit reactive (proportion prediction = 0) orpredictive (proportion prediction = 1) response modes across48-position sequences divided into eight blocks. (Note that Block 1shows 6 bins because Block 7 contained no participants. This 0 wasincluded in the analysis, however.)

Mentions: Simply averaging over participants (as in Figure 2) does not reveal a stark bimodality in predictivetendencies that we observed in our participants. To showcase thisbimodality, we used the previous dependent measure (distance away fromprevious trial) and conducted distribution analyses. In the 48-positiontrials, any individual trial was deemed “predictive” when theinitial distance from previous was 275 pixels or greater (indicatingsubstantial movement away, likely to another target; see Panel B of Figure 1). We calculated the proportionof trials that were predictive in six-trial blocks (giving eight blocks).For any given block for each subject, a proportion score is obtained, lyingbetween 0 and 1, representing the extent to which that block was predictive.A score of 1 on this proportion would indicate that all trials of these 6were predictive. A score of 0 would indicate only reaction: Participantsstayed closer to their initial position prior to the next trial. For eachblock, 1 to 8, a distribution of 143 scores is obtained (see Figure 3).


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

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

The percentage of participants (from all 11 G-scoresequences) that exhibit reactive (proportion prediction = 0) orpredictive (proportion prediction = 1) response modes across48-position sequences divided into eight blocks. (Note that Block 1shows 6 bins because Block 7 contained no participants. This 0 wasincluded in the analysis, however.)
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 3: The percentage of participants (from all 11 G-scoresequences) that exhibit reactive (proportion prediction = 0) orpredictive (proportion prediction = 1) response modes across48-position sequences divided into eight blocks. (Note that Block 1shows 6 bins because Block 7 contained no participants. This 0 wasincluded in the analysis, however.)
Mentions: Simply averaging over participants (as in Figure 2) does not reveal a stark bimodality in predictivetendencies that we observed in our participants. To showcase thisbimodality, we used the previous dependent measure (distance away fromprevious trial) and conducted distribution analyses. In the 48-positiontrials, any individual trial was deemed “predictive” when theinitial distance from previous was 275 pixels or greater (indicatingsubstantial movement away, likely to another target; see Panel B of Figure 1). We calculated the proportionof trials that were predictive in six-trial blocks (giving eight blocks).For any given block for each subject, a proportion score is obtained, lyingbetween 0 and 1, representing the extent to which that block was predictive.A score of 1 on this proportion would indicate that all trials of these 6were predictive. A score of 0 would indicate only reaction: Participantsstayed closer to their initial position prior to the next trial. For eachblock, 1 to 8, a distribution of 143 scores is obtained (see Figure 3).

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.