Calculation of signal detection theory measures

Stanislaw, Harold; Todorov, Natasha

doi:10.3758/bf03207704

Cited by 2,651 publications

(2,330 citation statements)

References 45 publications

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“…Performance was measured with the sensitivity index d' in order to account for any response bias, calculated as d' = z(hits)-z(false alarms). In cases with maximum hits or no false alarms, we adopted the common practice of adding the equivalent of half a trial (0.5/84) to the proportion correct to avoid division by zero (Stanislaw and Todorov 1999). The d' scores within each session were analysed with an independent-samples t-test comparing the 30min and 24hr groups, which was the principal measure of interest.…”

Section: Behavioural Data Analysismentioning

confidence: 99%

Cross-modal transfer of statistical information benefits from sleep

Durrant

Cairney

Lewis

2016

Cortex

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Extracting regularities from a sequence of events is essential for understanding our environment. However, there is no consensus regarding the extent to which such regularities can be generalised beyond the modality of learning. One reason for this could be the variation in consolidation intervals used in different paradigms, also including an opportunity to sleep. Using a novel statistical learning paradigm in which structured information is acquired in the auditory domain and tested in the visual domain over either 30min or 24hr consolidation intervals, we show that cross-modal transfer can occur, but this transfer is only seen in the 24hr group. Importantly, the extent of cross-modal transfer is predicted by the amount of SWS obtained. Additionally, cross-modal transfer is associated with the same pattern of decreasing MTL and increasing striatal involvement which has previously been observed to occur across 24 hours in unimodal statistical learning. We also observed enhanced functional connectivity after 24 hours in a network of areas which have been implicated in cross-modal integration including the precuneus and the middle occipital gyrus. Finally, functional connectivity between the striatum and the precuneus was also enhanced, and this strengthening was predicted by SWS. These results demonstrate that statistical learning can generalise to some extent beyond the modality of acquisition, and together with our previously published unimodal results, support the notion that statistical learning is both domain-general and domain-specific.

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Section: Behavioural Data Analysismentioning

confidence: 99%

Cross-modal transfer of statistical information benefits from sleep

Durrant

Cairney

Lewis

2016

Cortex

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“…This analysis compared test time (baseline, immediate test, and delay test) and tDCS current level (0.1 mA and 2.0 mA) to determine the degree to which response bias changed throughout the task as a function of tDCS. Signal detection (d') scores as well as response bias (β) scores reported in this analysis were calculated based on the hit (correct responses to images containing target objects) and false alarm (incorrect responses to images not containing target objects) rates according to calculations described by Stanislaw and Todorov (1999). Briefly, signal detection (d') is calculated by subtracting the z-normalized false alarm rate from the z-normalized hit rate, while response bias (β) is calculated by raising e to the power of ½ the difference between the squared, z-normalized false alarm rate and the squared, z-normalized hit rate.…”

Section: Discussionmentioning

confidence: 99%

Impact of tDCS on performance and learning of target detection: Interaction with stimulus characteristics and experimental design

et al. 2012

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We have previously found that transcranial direct current stimulation (tDCS) over right inferior frontal cortex (RIFC) enhances performance during learning of a difficult visual target detection task (Clark et al., 2012). In order to examine the cognitive mechanisms of tDCS that lead to enhanced performance, here we analyzed its differential effects on responses to stimuli that varied by repetition and target presence, differences related to expectancy by comparing performance in single-and double-blind task designs, and individual differences in skin stimulation and mood. Participants were trained for 1 h to detect target objects hidden in a complex virtual environment, while anodal tDCS was applied over RIFC at 0.1 mA or 2.0 mA for the first 30 min. Participants were tested immediately before and after training and again 1 h later. Higher tDCS current was associated with increased performance for all test stimuli, but was greatest for repeated test stimuli with the presence of hidden-targets. This finding was replicated in a second set of subjects using a double-blind task design. Accuracy for target detection discrimination sensitivity (d ' ; Z(hits) − Z(false alarms)) was greater for 2.0 mA current (1.77) compared with 0.1 mA (0.95), with no differences in response bias (β). Taken together, these findings indicate that the enhancement of performance with tDCS is sensitive to stimulus repetition and target presence, but not to changes in expectancy, mood, or type of blinded task design. The implications of these findings for understanding the cognitive mechanisms of tDCS are discussed.

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“…D'. Because target accuracy was high across conditions and error rate varied across conditions we calculated d' (Stanislaw & Todorov, 1999) to adjust hits (correct performance on target trials) for false alarms (incorrect performance on non-target trials). The maximum possible d' score was 2.84 (no errors).…”

Section: Working Memory For Manual Gesturesmentioning

confidence: 99%

Working memory for meaningless manual gestures.

Rudner

2015

Canadian Journal of Experimental Psychology / Revue canadienne

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Effects on working memory performance relating to item similarity have been linked to prior categorisation of representations in long-term memory. However, there is evidence from gesture processing that this link may not be obligatory. The present study investigated whether working memory for incidentally generated meaningless manual gestures is influenced by formational similarity and whether this effect is modulated by working-memory load. Results showed that formational similarity did lower performance, demonstrating that similarity effects are not dependent on prior categorisation. However, this effect was only found when working-memory load was low, supporting a flexible resource allocation model according to which it is the quality rather than quantity of working memory representations that determines performance. This interpretation is in line with proposals suggesting language modality specific allocation of resources in working memory.

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Calculation of signal detection theory measures

Cited by 2,651 publications

References 45 publications

Cross-modal transfer of statistical information benefits from sleep

Cross-modal transfer of statistical information benefits from sleep

Impact of tDCS on performance and learning of target detection: Interaction with stimulus characteristics and experimental design

Working memory for meaningless manual gestures.

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