Limits...
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. Distance (in pixels and as a function of sequenceregularity, G) to next stimuli after 750-ms lapsebetween disappearance of previous stimuli and onset of next stimuli.Panel B. Distance from previous stimuli after 750-ms lapse.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC3376885&req=5

Figure 2: Panel A. Distance (in pixels and as a function of sequenceregularity, G) to next stimuli after 750-ms lapsebetween disappearance of previous stimuli and onset of next stimuli.Panel B. Distance from previous stimuli after 750-ms lapse.

Mentions: The overall extent to which participants moved the mouse cursor towards thenext target prior to the target’s appearance was strongly related tothe regularity of the grammar. This is shown in Panel A of Figure 2. Using the same model asdescribed above, G highly significantly predicted initialdistance to next. Each .1 increase in G on average led toabout a 25-pixel closer initial position to the next target,F(1, 139) = 125.7, p < .0001. Ingeneral, each subsequent trial reduced initial position by about 1 pixel,F(1, 6351) = 174.2, p < .0001, butthis depended upon G, indicated by a significantinteraction term, F(1, 6351) = 161.2, p< .0001. In other words, high-G values (i.e., greaterregularity) had a larger drop in initial position across trials compared tosequences with low-G values.


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

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

Panel A. Distance (in pixels and as a function of sequenceregularity, G) to next stimuli after 750-ms lapsebetween disappearance of previous stimuli and onset of next stimuli.Panel B. Distance from previous stimuli after 750-ms lapse.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 2: Panel A. Distance (in pixels and as a function of sequenceregularity, G) to next stimuli after 750-ms lapsebetween disappearance of previous stimuli and onset of next stimuli.Panel B. Distance from previous stimuli after 750-ms lapse.
Mentions: The overall extent to which participants moved the mouse cursor towards thenext target prior to the target’s appearance was strongly related tothe regularity of the grammar. This is shown in Panel A of Figure 2. Using the same model asdescribed above, G highly significantly predicted initialdistance to next. Each .1 increase in G on average led toabout a 25-pixel closer initial position to the next target,F(1, 139) = 125.7, p < .0001. Ingeneral, each subsequent trial reduced initial position by about 1 pixel,F(1, 6351) = 174.2, p < .0001, butthis depended upon G, indicated by a significantinteraction term, F(1, 6351) = 161.2, p< .0001. In other words, high-G values (i.e., greaterregularity) had a larger drop in initial position across trials compared tosequences with low-G values.

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.