Signal detection theory (SDT) has proven to be a robust and useful statistical model for analyzing human performance in detection and decision making tasks. As with many models extensions have been proposed in order capture and represent the real world to a greater degree. Multidimensional Signal Detection Theory (MSDT) has had success in describing and modeling complex signals, signals that are comprised by more than one identifiable component dimension. Fuzzy Signal Detection Theory (FSDT) has had success in modeling and measuring human performance in cases where there exist ambiguity in the signal or response dimension characteristics, through the application of fuzzy set theory to the definition of the performance outcome categories. Multidimensional Fuzzy Signal Detection Theory (MFSDT) was developed to accommodate simultaneously both the multidimensionality of a signal and the fuzzification of outcome categories in order to integrate the two extensions. A series of three studies were performed to develop and test the theory. One study's purpose was to develop and derive multidimensional mapping functions, the aspect of MFSDT where MSDT and FSDT were integrated. Two receiver operating characteristic (ROC) studies were performed, one simulated and one empirical. The results from both ROC analysis indicated that for perceptually separable and perceptually integral complex stimuli that MFDST is a viable methodological approach to analyzing performance of signal detection tasks where there are complex signals with ambiguous signal characteristics.

Understanding eyewitness lineup judgment processes is critical, both from a theoretical standpoint (to better understand human memory) and from a practical one (to prevent wrongful convictions and criminals walking free). Currently, two influential theories attempt to explain lineup decision making: the theory of eyewitness judgment strategies (Lindsay & Wells, 1985), and the signal detection theory-informed diagnostic-feature-detection hypothesis (Wixted & Mickes, 2014). The theory of eyewitness judgment strategies posits that eyewitnesses can adopt either an absolute judgment strategy (base identification decisions only on their memory for the culprit) or a relative judgment strategy (base identification decision on lineup member comparisons). This theory further predicts that relative judgment strategies lead to an increase in false identifications. Contrast this with the diagnostic-feature-detection hypothesis, which predicts that the lineup member comparisons inherent to relative strategies promote greater accuracy. These two theories have been tested indirectly (i.e., via lineup format manipulations tangentially related to the theory), but there is a lack of direct tests. Across two experiments (Ns = 192, 584), we presented participants with simulated crime videos and corresponding lineups, and manipulated judgment strategy using explicit absolute and relative strategy instructions and a novel rank-order manipulation meant to encourage lineup member comparisons. We found no substantial differences in identifications or overall accuracy as a function of instructed strategy. These results are inconsistent with the theory of eyewitness judgment strategies but provide some support for the diagnostic-feature-detection hypothesis. We discuss implications for both theories and future lineup research. / Graduate

Current Signal Detection Theory models of source memory necessitate assumptions about the underlying distributions of source strengths to describe source memory performance. The current experiments applied a modified version of the same-different task in order to plot individual memory stimuli along a controlled dimension of the average frequency of voices. This technique allowed us to determine that subjects were using an independent-observations strategy rather than a differencing strategy when deciding whether two test words were spoken by the same or different female speakers at study. By including two male and two female voices and changing the task distinction from same or different speakers to same or different genders, we predictably switched subjects’ decision strategies. With this new same-different memory design, we are one step closer to ending our reliance on measures that are inferred from data to describe subjects’ source memory performance.

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Empathy and memory are two central aspects that make us human. In the following work, I combined these two areas with genetics and asked how they would interrelate against the background of age. At study, 28 younger and 32 older adults went through an item recognition/source memory paradigm with neutral and emotional (i.e., angry) faces. Dispositional empathy was measured using the Interpersonal Reactivity Index (IRI) and the Empathy Quotient (EQ). Further, 13 single-nucleotide polymorphisms (SNPs) from mainly oxytocin receptors (OXTR) were extracted. Results revealed that older adults had a lower score on the Fantasy dimension of the IRI. Younger and older adults did not differ in hit rate, but older adults showed a higher false alarm rate for neutral source memory. For emotional item recognition, older adults showed a higher liberal response bias whereas, for neutral source memory, younger adults showed a higher conservative response bias. For both memory and empathy, main effects and age interactions were found for OXTR rs237887, rs237897, rs2254298, rs4564970, and rs4686302. These findings illustrated the close interconnectivity of memory, empathy, and genetics over the human life span.

Signal Detection Theory (SDT; Green & Swets, 1966) is a well-established technique to analyze accuracy data in a number of experimental paradigms in psychology, most notably memory and perception, by separating a response bias/criterion from the theoretically bias-free discriminability/sensitivity. As SDT has traditionally been applied, the researcher may be confronted with loss in statistical power and erroneous inferences. A generalized linear mixed-effects modeling (GLMM) approach is presented and advantages with regard to power and precision are demonstrated with an example analysis. Using this approach, a correlation of response bias and sensitivity was detected in the dataset, especially prevalent at the item level, though a correlation between these measures is usually not found to be reported in the memory literature. Directions for future extensions of the method as well as a brief discussion of the correlation between response bias and sensitivity are enclosed. / Graduate / 2019-03-22

Objective: The perceptual mechanisms underlying the development and maintenance of excessive physical symptom reporting (i.e. 'somatisation') are poorly understood. Research with non-clinical participants suggests that high and low symptom reporters perform differently when detecting somatosensory signals and have different false alarm rates in which the presence of a signal is incorrectly reported when no signal is present. High symptom reporters often incorrectly report the presence of a signal particularly when a stimulus in a different sensory modality is presented. Previous research has shown that it may be possible to reduce false alarm rates by perceptual training using bi-modal visuo-tactile stimuli pairing. The current was designed to test this hypothesis. Methods: Seventy non-clinical participants scoring either high or low on the Patient Health Questionnaire (PHQ-15; a measure of somatisation) completed the Somatic Signal Detection Task (SSDT), a novel perceptual paradigm that purports to measure individual differences in somatosensory distortion. Prior to the SSDT, approximately two thirds of the sample completed either a 'weak' or 'strong' perceptual training protocol in which a suprathreshold tactile and visual stimuli were paired either infrequently (25%) or frequently (75%), with the intention of training participants to discriminate tactile signal from noise more effectively. The remaining participants received no perceptual training. Factors known to be strongly associated with somatisation were controlled for. Negative affectivity was controlled for using the State-Trait Anxiety Inventory Trait Version (STAI-T; Spielberger, Gorsuch & Lushene, 1970), somatosensory amplification was controlled for using the Somatosensory Amplification Scale (SSAS; Barsky, Goodson, Lane & Cleary, 1988), the Patient Health Questionnaire (PHQ-9; Kroenke, Spitzer, & Williams, 2001) was used to control for depression and the Health Anxiety Inventory-Short Version (SHAI; Salkovskis, Rimes, Warwick & Clark, 2002) was used to control for hypochondriacal factors with the Patient Health Questionnaire-Generalised Anxiety Disorder (PHQ-GAD-7; Spitzer, Kroenke, Williams & Löwe, 2006) being used to control for anxiety. Results: The high PHQ-15 group reported significantly more false alarms and had a significantly higher response criterion than the low PHQ-15 group in the no perceptual training conditions. The perceptual training reduced the false alarm rate for the high PHQ-15 group but did not alter response criterion. Although the findings were in the predicted direction, neither of these findings reached significance. The effect size indicated that this was due to low power. Conclusions: The findings were suggestive of the effect of perceptual training reducing false alarm rates; however, low power meant that it was impossible to draw firm conclusions. Further research with a larger sample is required.

People’s ability to call an experienced item “old” and a novel item “new” is recognition memory. Recognition memory is usually studied by first asking participants to learn a list of words and then make judgments of old (studied) or new (not studied) for test words. It has long been debated whether the underlying process of recognition memory is continuous or discrete. Two types of models are compared specifically that assume either discrete or continuous information states: the 2-high threshold (2HT) model and the unequal variance signal detection (UVSD) model, respectively. Researchers have used the receiver operation characteristic (ROC) function and response time (RT) data to test between the two models. However, both methods have provided evidence for 2HT and UVSD, and the debate has not come to consensus. In this study, we used an alternative approach to look into this issue. After studying the words, participants first made “old/new” judgment for each single test item. Then, if there were falsely identified items, each of them was randomly paired with a correctly identified word of the same response. Participants were asked to choose the studied word from the word pair. Simulation and experimental results were able to discriminate the 2HT and UVSD model. Experimental results showed that the UVSD model fitted the data better than the 2HT model. The forced-choice test paradigm provided an effective way to test between the 2HT and UVSD models.

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