Investigating dimensional organization in scripts using the pupillary response

Raisig, Susanne; Welke, Tinka; Hagendorf, Herbert; Meer, Elke van der

doi:10.1111/j.1469-8986.2007.00592.x

Cited by 31 publications

(44 citation statements)

References 33 publications

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“…The correlation between behavioral and pupil dilation data revealed only a significant association between RT and LD for the moderate difficulty condition. Some other pupillometry studies have demonstrated no correlations between ER and pupil dilation; however, most studies have reported a correlation between RTs and LD (e.g., Beatty & Lucero-Wagoner, 2000;Raisig, Welke, Hagendorf, & van der Meer, 2007;Nuthmann & van der Meer, 2005). The partial lack for a missing correlation between RT and LD might be due the procedure on how the maximum pupil dilation was determined in this study.…”

Section: Discussionmentioning

confidence: 61%

“…Specifically, higher activations in the bilateral IPS corresponded to longer LDs in each of the difficulty conditions. Although the LD is a function of PD since the muscles controlling pupil dilation take time to constrict and relax due to information processing (so it takes longer to dilate more) (Loewenfeld, 1993), the PD and LD do not correlate in most of the studies (e.g., Beatty & Lucero-Wagoner, 2000;Raisig, Welke, Hagendorf, & van der Meer, 2007;Steinhauer & Hakerem, 1992). A specification of the LD to cortical activity may be due to the finer time scale of the pupillometry compared to fMRI.…”

Section: Discussionmentioning

confidence: 99%

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Cognitive resource allocation for neural activity underlying mathematical cognition: a multi-method study

Landgraf

Meer

2010

ZDM Mathematics Education

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Mathematical cognition requires the allocation of computation resources, where math-specific computations are assumed to take place in the parietal cortex and math-supportive computations in the frontal cortex. Because the pupil dilation has a higher temporal resolution than functional MRI (fMRI), the study investigated to which extent the pupil dilation can help to identify cognitive resource allocation for neural activity underlying math-specific and math-supportive cognition. Combining pupillometry and event-related fMRI, we administered a multiplication verification paradigm to 15 healthy participants asking them to solve easy, moderate, and difficult multiplication tasks. The results revealed that (1) behavioral and pupil dilation data increased parametrically with task difficulty; (2) mental multiplication with increasing difficulty recruited a fronto-parietal circuit comprising left pre-supplementary motor area, left precentral gyrus, right dorsolateral prefrontal cortex, and bilateral intraparietal sulcus (IPS); and (3) pupil dilation was sensitive to cognitive resource allocation for neural activity underlying math-specific cognition in the bilateral IPS, implicating a strong reliance on numerical quantity processing during multiplication. In conclusion, the pupil dilation could be used in mathematics education as an easily acquired peripheral physiological indicator (without relying on fMRI) that might lead to a better understanding of dynamical changes in learning arithmetic abilities as a function of training, experience, and development. On a broader level, its application allows to obtain useful insights into learning disabilities such as dyscalculia, and further improve rehabilitation programs with appropriate intervention structures.

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Section: Discussionmentioning

confidence: 61%

Section: Discussionmentioning

confidence: 99%

Cognitive resource allocation for neural activity underlying mathematical cognition: a multi-method study

Landgraf

Meer

2010

ZDM Mathematics Education

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“…However, the increase is significantly greater when task demands are high compared to when task demands are low. This is the case when a stimulus is unexpected (Gilzenrat Sit down at Brown et al 1999;Siegle et al 2008) or-as we have shown before-when events violate the temporal order (Raisig et al 2007(Raisig et al , 2010. In this task, when a temporal violation is anticipated, we expect that it is not accompanied by the typical pupillary response that marks increased cognitive effort and resource consumption.…”

Section: Introductionmentioning

confidence: 86%

“…We addressed this question with the triplet-paradigm that we have used in several other studies (Raisig et al 2007(Raisig et al , 2010. In that paradigm, an activity (e.g., going to a restaurant) is presented to activate the component events in long-term memory and produce predictions about the order the events will unfold in.…”

Section: Introductionmentioning

confidence: 99%

The role of temporal properties on the detection of temporal violations: insights from pupillometry

2011

Self Cite

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Scripts store the temporal order of component events of everyday activities as well as the temporal position of the events within the activity (early or late). When confronted with an activity, predictions are generated about how the component events will unfold. Thereby, an error-detection mechanism continuously monitors whether they unfold as anticipated or not in order to reveal errors in the unfolding activity. We investigated whether the temporal position "early" or "late" influenced the detection of errors using the pupillary response as an index of cognitive resource consumption. An event triplet consisting of three events was presented in a chronological or non-chronological temporal order. Crucially, the triplet focused either on the beginning (temporal position "early") or the end (temporal position "late") of an activity. We assumed that these position codes would be used to facilitate error detection when a non-chronological event was presented. Results showed that errors in the temporal order were detected more successfully in early than in late triplets. Results further suggest that strong predictions are formed about how an activity begins. Violations of this prediction must be overcome by zooming into the representation and allocating attention to the temporal position that consumes cognitive resources. Only after zooming in has taken place successfully may the position codes be used to anticipate temporal violations in unfolding event sequences.

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“…The size of the pupil is not only affected by light conditions, but also by cognitive and physical efforts and emotional arousal (Beatty and Kahneman 1966;Granholm and Steinhauer 2004;Hess and Polt 1964;Kahneman and Beatty 1967;Loewenfeld 1993). It has been demonstrated throughout various cognitive domains and across different modalities of stimulus presentation that pupil dilation is greater the more difficult the task is (Hess and Polt 1964;Nuthmann and van der Meer 2005;Raisig, Welke, Hagendorf and van der Meer 2007;Verney, Granholm and Marshall 2004). For instance, Hess and Polt (1964) found that pupillary dilation is higher while solving difficult arithmetical problems, such as 11 9 6, than while solving easy problems, such as 4 9 7.…”

Section: Pupillometry As a Way To Assess Resource Allocationmentioning

confidence: 99%

Mathematical cognition: individual differences in resource allocation

Bornemann

Foth

Horn

et al. 2010

ZDM Mathematics Education

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Individuals scoring higher in tests of general cognitive abilities tend to perform better on novel and familiar mathematical tasks. It has been scarcely investigated how this superior mathematical performance relates to the amount of cognitive resources that is invested to solve a given task. In this study we propose that, on novel tasks, individuals with high cognitive abilities outperform less able individuals, because they allocate a higher amount of resources. On familiar tasks, however, individuals with higher abilities profit from more efficient processes compared to individuals of lower cognitive abilities. We tested this hypothesis by administering to 11th graders a geometric analogy task not practiced at school and an algebraic transformation task comprising operations that are routinely required during mathematical courses. General cognitive abilities were measured with Ravens Advanced Progressive matrices (fluid intelligence), the d2 (focused attention) and KAI-N (working memory capacity). Resource allocation was measured by assessing pupil diameter during the problem-solving process. Performance on both the analogy and the algebra task was correlated with general cognitive abilities, especially fluid intelligence. In line with our assumptions, a positive correlation between fluid intelligence and resource allocation was observed in the novel geometric analogy task, whereas the correlation was not significant in the more familiar algebra task.

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Investigating dimensional organization in scripts using the pupillary response

Cited by 31 publications

References 33 publications

Cognitive resource allocation for neural activity underlying mathematical cognition: a multi-method study

Cognitive resource allocation for neural activity underlying mathematical cognition: a multi-method study

The role of temporal properties on the detection of temporal violations: insights from pupillometry

Mathematical cognition: individual differences in resource allocation

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