Global statistical learning in a visual search task.

Jones, John L.; Kaschak, Michael P.

doi:10.1037/a0026233

Cited by 37 publications

(45 citation statements)

References 33 publications

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“…Our choice to pick two of the word segmentation tasks for this study was driven in part by practical concerns. Limiting the number of word segmentation tasks we employed in the experiment allowed us to assess whether increasing test length would improve SL task reliability and result in correlations between similar SL tasks, while also providing room for us to collect additional measures of interest for an exploratory analysis of the relationship between our SL measures and other cognitive constructs 6 . Because word segmentation tasks typically use a small number of words in their training set, our options for creating a larger set of unique test items were limited.…”

Section: Methodsmentioning

confidence: 99%

“…5 The slight discrepancy between the descriptive statistics reported here and reported within Table 1 for Language 2 2AFC Time 1 (M = 0.56, SD = 0.23) are because the mean and standard deviation here are only for the subset of participants who contributed data for both time points whereas Table 1 reports means and standard deviations for all the participants who contributed data to Time 1. 6 We collected data on a range of cognitive measures (Digit Span, Operation Span, Reading Span, & Nelson Denny Vocabulary Size). Because these measures were…”

Section: Competing Interestsmentioning

confidence: 99%

“…This adaptability plays a role in many domains of formal and informal learning, including language (e.g., [3]), mathematics [4], locomotion (e.g., [5]), and perception (e.g., [6]). Recent linguistic theories suggest that adaptation to probabilistic information characterizes both language acquisition in infancy [7,8,9], and language comprehension and production in adulthood (e.g., [10,11,12]).…”

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Individual Differences in Statistical Learning: Conceptual and Measurement Issues

et al. 2016

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The ability to adapt to statistical structure (often referred to as "statistical learning") has been proposed to play a major role in the acquisition and use of natural languages. Several recent studies have explored the relationship between individual differences in statistical learning and language outcomes. These studies have produced mixed results, with some studies finding a significant relationship between statistical learning and language outcomes, and others finding weak or null results. Furthermore, the few studies that have used multiple measures of statistical learning have reported that they are not correlated (e.g., [1]). The current study assesses the reliability of various measures of auditory statistical segmentation, and their consistency over time. That is, do the generally low correlations observed between measures of statistical learning stem from task demands, the psychometric properties of the measures, or the fact that statistical learning may be a highly fragmented construct? Our results confirm previous reports that individual measures of statistical learning tend not to correlate with each other, and suggest that the somewhat weak reliability of the measures may be an important factor in the low correlations. Our data also suggest that aggregating performance across tasks may be an avenue for improving the reliability of the measures.

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Section: Methodsmentioning

confidence: 99%

Section: Competing Interestsmentioning

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Individual Differences in Statistical Learning: Conceptual and Measurement Issues

et al. 2016

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“…They respond faster to targets appearing in more predictable locations, either because these target locations have higher marginal frequencies (Geng & Behrmann, 2002Jones & Kaschak, 2012) or because they are linked to stronger transition probabilities (Remillard, 2003(Remillard, , 2009). We therefore expected that being able to predict location transitions would serve as an endogenous cue, resulting in increased activity in regions associated with recruitment and directing of spatial attention, specifically the bilateral intraparietal sulcus and the frontal eye fields (see Corbetta &Shulman, 2002, andalso Szczepanski &Kastner, 2013, for recent review).…”

Section: Introductionmentioning

confidence: 99%

Predictability of what or where reduces brain activity, but a bottleneck occurs when both are predictable

Davis

Hasson

2018

NeuroImage

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Detecting regularities in the sensory environment licenses predictions that enable adaptive behaviour. However, it is unclear whether predictions about object category, location, or both dimensions are mediated by overlapping systems, and relatedly, whether constructing predictions about both category and location is associated with processing bottlenecks. To examine this issue, in an fMRI study, we presented participants with image-series in which non-deterministic transition probabilities enabled predictions about either the location of the next image, its semantic category, both dimensions, or neither (the latter forming a "no-regularity" random baseline condition). Speaking to a common system, all three predictable conditions resulted in reduced BOLD activity in four clusters: left rostral anterior cingulate cortex; bilateral putamen, caudate and thalamus; right precentral gyrus, and left visual cortex. Pointing to a processing bottleneck, in some regions, a significant interaction between the two factors was found whereby category-predictable series were associated with lower activity -but only when location regularity was absent. Finally, category regularity decreased activation in areas of the ventral visual stream and semantic areas of lateral temporal cortex, and location regularity decreased activation in a dorsal fronto-parietal cluster, long implicated in the endogenous control of spatial attention. Our findings confirm and expand a role for dACC/dmPFC and striatum in monitoring or responding to uncertainty in the environment and point to a limited capacity bottleneck when multiple predictions are concurrently licensed.

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“…In addition to exogenous and endogenous cues, people are sensitive to the spatial and temporal probabilities that govern target location and presence (Geng & Behrmann, 2002Jones & Kaschak, 2012;Walthew & Gilchrist, 2006). The target location probability denotes a target appearing at one location more often than at other locations and is regarded as an attentional cue that directs spatial attention in a way that cannot be explained within the typical endogenous/exogenous framework (Geng & Behrmann, 2002Zhao, AlAidroos, & Turk-Browne, 2013).…”

Section: Introductionmentioning

confidence: 99%

Selective attention modulates the effect of target location probability on redundant signal processing

Chang

Little

Yang

2016

Atten Percept Psychophys

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We investigated the decision process underlying the detection of targets at multiple locations. In three experiments using the same observers, target location probability and attentional instructions were manipulated. A redundanttarget detection task was conducted in which participants were required to detect a dot presented at one of two locations. When the dot appeared at the two locations with equal frequency (Experiment 1), those participants who were found to have limited to unlimited capacity were shown to adopt a parallel, self-terminating strategy. By contrast, those participants who had supercapacity were shown to process redundant targets in a coactive manner. When targets were presented with unequal probability, two participants adopted a parallel, self-terminating strategy regardless of whether they were informed the target location probability (Experiment 3) or not (Experiment 2). For the remaining two participants, the strategy changed from parallel, self-terminating to serial, selfterminating as a result of the probability instructions. In Experiments 2 and 3, all the participants were of unlimited to limited capacity. Taken together, these results suggest that target location probability differently affects the selection of a decision strategy and highlight the role of controlled attention in selecting a decision strategy.

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Global statistical learning in a visual search task.

Cited by 37 publications

References 33 publications

Individual Differences in Statistical Learning: Conceptual and Measurement Issues

Individual Differences in Statistical Learning: Conceptual and Measurement Issues

Predictability of what or where reduces brain activity, but a bottleneck occurs when both are predictable

Selective attention modulates the effect of target location probability on redundant signal processing

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