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A Primer of Signal Detection Theory.
... Behavioral performance was tracked across texture discrimination sessions by computing multiple behaviorally-related parameters including Hit Rate, FA Rate, Sensitivity (d') and Bias. 171 For the fiber photometry cohort, the 405nm and 470nm LEDs provided constant illumination throughout all trials. For the JAWS cohort, LED photoinactivation occurred at a trial probability of 0.50 for every session from the start of the Learning until the end of the Expert phase. ...
... Behavioral performance was tracked across texture discrimination sessions by computing multiple behaviorally-related parameters including Hit Rate, FA Rate, Sensitivity (d') and Bias. 171 ...
... The FA Rate formula is similar to the Hit Rate formula except it replaces Hit with FA and Miss with CR: [FA / (FA + CR)]. Sensitivity illustrates the ability to discriminate between the signal (Go texture) and the noise (NoGo texture), and it is derived from signal detection theory.171 It is calculated as follows: [normalized inverse (Hit Rate) -normalized inverse (FA Rate)]. ...
The posterior medial (POm) thalamus is heavily interconnected with sensory and motor circuitry and is likely involved in behavioral modulation and sensorimotor integration. POm provides axonal projections to the dorsal striatum, a hotspot of sensorimotor processing, yet the role of POm-striatal projections has remained undetermined. Using optogenetics with slice electrophysiology, we found that POm provides robust synaptic input to direct and indirect pathway striatal spiny projection neurons (D1- and D2-SPNs, respectively) and parvalbumin-expressing fast spiking interneurons (PVs). During the performance of a whisker-based tactile discrimination task, POm-striatal projections displayed learning-related activation correlating with anticipatory, but not reward-related, pupil dilation. Inhibition of POm-striatal axons across learning caused slower reaction times and an increase in the number of training sessions for expert performance. Our data indicate that POm-striatal inputs provide a behaviorally relevant arousal-related signal, which may prime striatal circuitry for efficient integration of subsequent choice-related inputs.
... This literature reports that the precision and differentiation of one's own emotional experiences and visual representations Keating, Ichijo, & Cook, 2023;Keating & Cook, pre-print;Keating, Kraaijkamp, & Cook, pre-print) may contribute to the ability to recognise the emotions of others. Indeed, this literature has its roots in signal detection theory (see McNicol, 2005), where it is argued that a 'signal' distribution and a 'noise' distribution that are imprecise (i.e., wide) and indistinct (i.e., overlapping) provide a low sensitivity to discriminate between the 'signal' and 'noise'. Thus, one might predict that an individual who produces imprecise (i.e., inconsistent) angry facial expressions, which are indistinguishable from their sad expressions, may struggle to discriminate other people's angry and sad expressions (perhaps because it is difficult to determine whether others' expressions match their own for anger or for sadness). ...
... We did not make any formal predictions regarding the magnitude of activation of facial landmarks since this evidence was highly mixed (e.g., Faso et al., 2015;Grossman et al., 2013;Lampi et al., 2023;Legiša, Messinger, Kermol, & Marlier, 2013;Loveland et al., 1994;Mathersul, McDonald, & Rushby, 2013;Oberman, Winkielman, & Ramachandran, 2009;Stagg et al., 2013;Yoshimura et al., 2015), and potentially confounded by alexithymia (see Trevisan, Bowering, &Birmingham, 2016 andKeating &Cook, 2020). Finally, in line with signal detection theory (McNicol, 2005) and previous findings (e.g., Keating, Ichijo & Cook, 2023;Keating & Cook, pre-print;Keating, Kraaijkamp & Cook, pre-print), we predicted that the precision and differentiation of participants' own productions would contribute to their ability to recognise others' facial expressions. ...
... Further work is necessary to unpack whether this information about own expressions relates to stored visual representations (e.g., from watching one's own expressions in the mirror) or stored motoric representations. Furthermore, our results show the utility of considering approaches like signal detection theory (SDT; see McNicol, 2005) in the emotion recognition field. That is, we found that precision, an important concept in SDT, is also important with respect to emotion recognition: precise (i.e., consistent or reliable) productions of facial expressions facilitate enhanced emotion recognition. ...
Preliminary studies are suggestive of differences in facial expressions between autistic and non-autistic individuals. However, it is unclear what specifically is different, whether such differences remain after controlling for facial morphology and alexithymia, and whether production differences relate to perception differences. Therefore, here we aimed to 1) compare the jerk and activation profiles for autistic and non-autistic expressions, after controlling for facial morphology and alexithymia, and 2) explore whether differences therein predicted differences in emotion recognition. To fulfil these aims, we employed facial motion capture to record 2,448 posed and 2,448 spoken expressions of anger, happiness, and sadness from 25 autistic and 26 matched non-autistic adults. Participants also completed a dynamic emotion recognition task. We found that the autistic participants relied more on the mouth, and less on the eyebrows, to signal anger than their non-autistic counterparts. For happiness, the autistic participants showed activity patterns suggestive of a less exaggerated smile that also did not “reach the eyes”. For sadness, the autistic participants tended to produce a downturned expression by raising their upper lip more than their non-autistic peers. Alexithymia predicted less differentiated angry and happy expressions, and lower precision (i.e., consistency) for spoken expressions. For non-autistic individuals, those who produced precise spoken expressions had greater emotion recognition accuracy. No production-related factors contributed to autistic emotion recognition. These results have significant implications for understanding the aetiology of the emotion recognition difficulties documented in various clinical conditions.
... (ix) Frequency bands distribution: the frequency content of the COP signal is studied by incorporating amplitudes within frequency bands in order to characterize the preferential involvement of specific neuronal loops in postural regulation [71][72][73][74]. Three frequency bands are usually considered: low frequencies (0-0.02/0.5 Hz) which mostly account for visuovestibular regulation, medium frequencies (0.2/0.5-2 Hz) for cerebellar participation, and high frequencies for proprioceptive participation (>2 Hz), the limits of these bands being different according to the authors [66,71]. ...
... Waddington and Adams [70] applied signal detection theory (SDT) [71][72][73] to deal with noise-associated uncertainty in making judgments about ankle movements and positions. To do this, participants are required on any one trial to make an absolute judgment regarding one of five possible ankle movements. ...
... To do this, participants are required on any one trial to make an absolute judgment regarding one of five possible ankle movements. Nonparametric SDT Receiver Operating Characteristic (ROC) analysis [73] is then used to compare responses to pairs of ankle movements. The area under the ROC curve (AUC) [73] is used as the measurement of ankle proprioceptive sensitivity, representing a participant's ability to discriminate between the five ankle movements [7]. ...
This special issue deals with the different techniques of rehabilitation and improvement of postural function
... Pain discriminability was quantified mainly using a nonparametric measure from SDT, i.e., the area under the receiver operating characteristic (ROC) curve (AUC) ( Figure 1E; see STAR Methods for details on calculating AUC values). 27 As in many classic behavioral pain studies, 1-3,28 we adopted a rating design in terms of SDT, where participants simply rate the pain intensity of each stimulus on a numerical rating scale (NRS), and every rating on the NRS is regarded as an implicit criterion that participants hold. 29,30 We explored EEG responses correlated with pain discriminability using Dataset 1, replicated them in Datasets 2 and 3, and tested whether they are pain selective using all datasets with non-painful stimuli. ...
... 8,28,76 Importantly, we did not use the typical SDT design in which participants are required to identify one of two alternative stimuli (e.g., the stronger stimuli of two intensities). 27 Rather, we used a rating design in the framework of SDT, 27 which is particularly suitable for computing AUC values 29 and has been used extensively in many classic pain behavioral studies. [1][2][3]28 In the rating design, 1-3,28 participants report how painful a pain stimulus is on a numerical rating scale. ...
... 8,28,76 Importantly, we did not use the typical SDT design in which participants are required to identify one of two alternative stimuli (e.g., the stronger stimuli of two intensities). 27 Rather, we used a rating design in the framework of SDT, 27 which is particularly suitable for computing AUC values 29 and has been used extensively in many classic pain behavioral studies. [1][2][3]28 In the rating design, 1-3,28 participants report how painful a pain stimulus is on a numerical rating scale. ...
Neural indicators of pain discriminability have far-reaching theoretical and clinical implications but have been largely overlooked previously. Here, to directly identify the neural basis of pain discriminability, we apply signal detection theory to three EEG (Datasets 1–3, total N = 366) and two fMRI (Datasets 4–5, total N = 399) datasets where participants receive transient stimuli of four sensory modalities (pain, touch, audition, and vision) and two intensities (high and low) and report perceptual ratings. Datasets 1 and 4 are used for exploration and others for validation. We find that most pain-evoked EEG and fMRI brain responses robustly encode pain discriminability, which is well replicated in validation datasets. The neural indicators are also pain selective since they cannot track tactile, auditory, or visual discriminability, even though perceptual ratings and sensory discriminability are well matched between modalities. Overall, we provide compelling evidence that pain-evoked brain responses can serve as replicable and selective neural indicators of pain discriminability.
... In any such task, perceptual judgments are determined by two theoretically independent factors: (1) the observer's ability to discriminate differences in stimulus intensity (perceptual sensitivity), and (2) the observer's general tendency to make higher or lower ratings (response bias). Methods based on signal detection theory (SDT) allow the separate estimation of sensitivity and response bias (McNicol, 1972(McNicol, /2005. ...
... In any such task, perceptual judgments are determined by two theoretically independent factors: (1) the observer's ability to discriminate differences in stimulus intensity (perceptual sensitivity), and (2) the observer's general tendency to make higher or lower ratings (response bias). Methods based on signal detection theory (SDT) allow the separate estimation of sensitivity and response bias (McNicol, 1972(McNicol, /2005. ...
... It is also possible to be differentially sensitive while showing the same degree of response bias, making discriminability and response bias conceptually independent (see Supplemental Figure S1). SDT methods can be generalized to situations with more than two categories of stimuli and continuous rating scales (McNicol, 1972(McNicol, /2005, as in the present study. ...
Despite growing evidence that psychopathy entails reduced emotional processing, the relationship between psychopathic traits and third-person pain perception is poorly understood. This study directly examined perception of others' pain in a sample of male and female students (N = 105) who completed the Self-Report Psychopathy scale (SRP-III) and the Toronto Empathy Questionnaire (TEQ). Participants watched a video of 60 one-second clips of other people experiencing pain. Following each clip, participants rated the perceived level of pain intensity and pain unpleasantness. Psychopathic traits were unrelated to response bias, suggesting that individuals high in psychopathic traits were no more or less likely to impute pain to others. However, higher levels of psychopathic traits, particularly callous affect and antisocial behavior, were associated with a decreased ability to discriminate others' pain. Sensitivity and response bias were unrelated to TEQ scores. These findings provide novel insights into the influence of psychopathic traits on emotional processing.
... To quantify participants' recognition accuracy, d-prime McNicol, 2005) was calculated based on performance during the recognition testing phase of the outdoor scene task. Performance was grouped according to participants' old/new responses, where the number of hits (old images correctly identified as 'old') and false alarms (new images incorrectly judged as 'old') were calculated per image position/condition (predictable A, B, C, D, and unpredictable Z), across participants. ...
... This involved adding 0.5 to the number of false alarms and hits for these subjects, per image position/condition, and adding 1 to the number of distractor and target trials. Once this adjustment was made, d' scores for each image type (predictable 'A', 'B', 'C', 'D' and unpredictable 'Z' images) were then calculated using the psycho package (Makowski, 2018) in R version 4.3.1, which subtracts the z-score of the false alarm rate from the z-score of the hit rate (McNicol, 2005). Note that it was not possible to obtain d' scores for each image position for images in the unpredictable 'Z' condition. ...
Prediction and memory are strongly intertwined, with predictions relying on memory retrieval, whilst also influencing memory encoding. However, it is unclear how prediction errors during learning, as measured by the N400 event-related potential (ERP), influence explicit memory performance, and how individual neural factors may modulate this relationship. The current study sought to investigate the effect of prediction and individual neural variability on memory processing, whilst exploring the N400 as a prediction error signal in a context extending beyond language. Participants (N = 48, females = 33) completed a study-test paradigm where they first viewed predictable and unpredictable four-item ′ABCD′ sequences of outdoor scene images, whilst their brain activity was recorded using electroencephalography (EEG). Subsequently, their memory for the images was tested, and N400 patterns during learning were compared with memory outcomes. Strikingly, greater N400 amplitudes during learning were associated with enhanced memory at test for individuals with low versus high individual alpha frequencies (IAFs). This indicates that IAF may influence stimulus precision weightings and the extent to which prediction errors drive memory encoding. Memory was also strongest for predictable images in the ′B′ position, suggesting that when processing longer sequences, the brain may prioritise the data deemed most informative for predictive model updating. Ultimately, the results provide novel insight into the effect of prediction on memory, by highlighting the role of inter-subject variability, whilst shedding light on the accumulation of predictions across sequences.
... A', a nonparametric equivalent to d', was used to combine hits and false positives in these experiments (McNicol, 1972;Norman, 1964;Rae, 1976;Valentine & Bruce, 1986). A' allows sensitivity to be calculated from a single pair of hit and false-alarm rates using a graphical method to approximate the area under the receiver operating characteristic (ROC) curve. ...
... An A' of 0.50 corresponds to chance performance and an A' of 1 to perfect performance. A' tends to be right skewed and is therefore transformed using 2[arc-(A 7 )] prior to ANOVA (McNicol, 1972). Although sin response latencies were recorded, they are not reported, as the large number of errors meant that there were not enough correct responses to give meaningful averages. ...
A series of experiments is reported that investigated the effects of variations in lighting and viewpoint on the recognition and matching of facial surfaces. In matching tasks, changing lighting reduced performance, as did changing view, but changing both did not further reduce performance. There were also differences between top and bottom lighting. Recognizing familiar surfaces and matching across changes in viewpoint were more accurate when lighting was from above than when it was from below the heads, and matching between different directions of top lighting was more accurate than between different directions of bottom lighting. Top lighting also benefited matching between views of unfamiliar objects (amoebae), though this benefit was not found for inverted faces. The results are difficult to explain if edge- or image-based representations mediate face processing and seem more consistent with an account in which lighting from above helps the derivation of 3-dimensional shape.
... n )/on , the standard definition, and d\ = (u, o -y, n )/a o , which is the intercept of the z-ROC equation, z h = (a n /a o )Zf a + (|x o -|x n )/a o . Note that either can serve as a d' measure (e.g., McNicol, 1972). ...
... Subjects were required to make a recognition response on a 6-point scale with values ranging from very sure old (6) to very sure new (1). The response probabilities in each confidence category were used to construct the z-ROC curve by calculating cumulative probabilities successively from the right-hand side of the distribution and then plotting the z transforms of the hit cumulative values versus the z transforms of the false-alarm cumulative values (see McNicol, 1972). ...
The experiments presented in this article examined the slope of the z-ROC (receiver-operating characteristic) function for recognition memory. The slope was examined as a function of strength and the variables study time, list length, word frequency, and category membership. For normal distributions of familiarity, the slope of the z-ROC is the ratio of the new-item to old-item standard deviations. R. Ratcliff, C.-F. Sheu, and S. D. Gronlund (1992) found that the slope was constant within standard error as a function of strength of encoding, which is inconsistent with the predictions of the global memory models. The results presented here extend this finding: The slope was constant as a functions of strength of encoding, list length, and the number of related items from a category in the study list. Word frequency did affect the slope, but within a frequency class the slope was constant as a function of strength. The implications of these data for the global memory models, the attention likelihood model, and variants of these models are discussed.
... The particular measure of recognition sensitivity used was the area under the MOC curve, P(A), computed for each subject according to procedures described by McNicol (1972). This measure approximates the more common d' and is used when one is unwilling to assume normal distributions and equal variances for the old and new items. ...
... B, a nonparametric measure of response bias, was also computed according to procedures described by McNicol (1972). This measure reflects the average criterion that is used to respond to the recognition test items. ...
We conducted three experiments to examine the effects of information about a speaker's status on memory for the assertiveness of his or her remarks. Subjects either read (Experiments 1 and 2) or listened to a conversation (Experiment 3) and were later tested for their memory of the target speaker's remarks with either a recognition (Experiment l) or a recall procedure (Experiments 2 and 3). In all experiments the target speaker's ostensible status was manipulated. In Experiment 1, subjects who believed the speaker was high in status were less able later to distinguish between remarks from the conversation and assertive paraphrases of those remarks. This result was replicated in Experiment 2, but only when the status information was provided before subjects read the conversation and not when the information was provided after the conversation had been read. Experiment 2's results eliminate a reconstructive memory interpretation and suggest that information about a speaker's status affects the encoding of remarks. Experiment 3 examined this effect in a more ecologically representative context.
... Recent work has highlighted that a person's internal templates-that is the way one pictures emotional expressions in the "minds' eye" (also known as a visual representations of emotion; see Ref. [12][13][14][15][16] )-are important contributors to emotion recognition accuracy 17 . Signal detection theory (see Ref. 18 ) tells us that at least two properties of visual representations should predict emotion recognition accuracy: precision and differentiation. That is, a 'signal' distribution and a 'noise' distribution that are both imprecise (wide) and indistinct (overlapping) provide low sensitivity to discriminate between 'signal' and 'noise' . ...
... This is particularly plausible given that (non-autistic) individuals with less differentiated experiences of emotion typically have less differentiated visual representations too 17 . As mentioned previously, since overlapping 'signal' and 'noise' distributions may make it difficult to discriminate the 'signal' from the 'noise' 18 , it may be that difficulties differentiating visual representations are responsible for emotion recognition differences in autism. However, research has not yet tested this idea. ...
To date, studies have not yet established the mechanisms underpinning differences in autistic and non-autistic emotion recognition. The current study first investigated whether autistic and non-autistic adults differed in terms of the precision and/or differentiation of their visual emotion representations and their general matching abilities, and second, explored whether differences therein were related to challenges in accurately recognizing emotional expressions. To fulfil these aims, 45 autistic and 45 non-autistic individuals completed three tasks employing dynamic point light displays of emotional facial expressions. We identified that autistic individuals had more precise visual emotion representations than their non-autistic counterparts, however, this did not confer any benefit for their emotion recognition. Whilst for non-autistic people, non-verbal reasoning and the interaction between precision of emotion representations and matching ability predicted emotion recognition, no variables contributed to autistic emotion recognition. These findings raise the possibility that autistic individuals are less guided by their emotion representations, thus lending support to Bayesian accounts of autism.
... Participant old/new responses were used to calculate response accuracy metrics McNicol, 2005) for both veridical and associative memories for both IR and DR tasks, as adapted from signal detection theory (McNicol, 2005). d' was calculated using the package Psycho (Makowski, 2018) implemented in R version 3.6.1 (R Core Team, 2021). ...
... Participant old/new responses were used to calculate response accuracy metrics McNicol, 2005) for both veridical and associative memories for both IR and DR tasks, as adapted from signal detection theory (McNicol, 2005). d' was calculated using the package Psycho (Makowski, 2018) implemented in R version 3.6.1 (R Core Team, 2021). ...
Relatively little is known regarding the interaction between encoding-related neural activity and sleep-based memory consolidation. One suggestion is that a function of encoding-related theta power may be to “tag” memories for subsequent processing during sleep. This study aimed to extend previous work on the relationships between sleep spindles, slow oscillation-spindle coupling, and task-related theta activity with a combined Deese-Roediger-McDermott (DRM) and nap paradigm. This allowed us to examine the influence of task- and sleep-related oscillatory activity on the recognition of both encoded list words and associative theme words. Thirty-three participants (29 females, mean age = 23.2 years) learned and recognised DRM lists separated by either a 2 h wake or sleep period. Mixed-effects modelling revealed the sleep condition endorsed more associative theme words and fewer list words in comparison to the wake group. Encoding-related theta power was also found to influence sleep spindle density, and this interaction was predictive of memory outcomes. The influence of encoding-related theta was specific to sleep spindle density, and did not appear to influence the strength of slow oscillation-spindle coupling as it relates to memory outcomes. The finding of interactions between wakeful and sleep oscillatory-related activity in promoting memory and learning has important implications for theoretical models of sleep-based memory consolidation.
... When the stimulus is SN, the participant's response is a hit if the signal reaches a threshold, and a miss if the signal fails to reach the threshold. In the scenario where the stimulus is N, it means the signal remains below the threshold (resulting in a correct rejection) but there exists the potential for the signal to breach the threshold, leading to a false alarm [46]. The SDT has been used in information processing [22,23]. ...
... For instance, one could extend SDT by introducing a nonlinear representation of the stimulus. Moreover, one could assume that the noise in SDT comes from a logistic rather than a Gaussian distribution, so the cumulative Gaussian curves become logistic curves 74,76,77 . ...
Logistic classification is a simple way to make choices based on a set of factors: give each factor a weight, sum them, and use the result to set the log odds of a random draw. This operation is known to describe human and animal choices based on value (economic decisions). There is increasing evidence that it also describes choices based on sensory inputs (perceptual decisions). Here I briefly review this evidence and I fit data from multiple studies in multiple species to show that logistic classification can describe a variety of choices. These include sensory choices influenced by stimuli of other modalities (multisensory integration) or by non-sensory factors such as value and recent history. Logistic classification is the optimal strategy if factors are independent of each other, and a useful heuristic in other conditions. Using it to describe sensory choices is useful to characterize brain function and the effects of brain inactivations.
... This technical outline can enable us to understand signal detection theory in simple terms (see McNicol, 2005). Sensitivity is suggested to be an unbiased assessment of the correct responses in a perceptual task. ...
Signal detection theory (SDT) is a multi-component ratio method for assessing perceptual performance. It can be applied in backward masking, such as the presentation of a brief target image followed by a noise image that can render a target imperceptible. Previously, we implemented a methodology for backward masking that included individualized thresholds to achieve unconscious presentations and involved dedicated SDT-component analyses. We showed that a specific SDT-component, namely, false positives, such as erroneously reporting that an arousing facial stimulus was presented, involved increases in physiological and emotional responses. In this manuscript, we explored this effect outside our individual-thresholds paradigm. For the first time in relevant research, we recruited participants using trial-contour power calculations for false positive responses. We presented emotional faces for 16.67 ms masked with noise images for 116.67 ms. We showed that false-positive responses for emotional faces were characterised by pre-trial arousal, and post-trial arousal increases, and high emotional and confidence ratings. These outcomes were most pronounced for the misperception of fearful faces. Based on these findings, we discussed the possibility of a mechanism for partial self-encapsulated emotional-experiential apperception. We emphasised the possibility of a fear primacy socio-emotional response module during combined visual ambiguity and high psychophysiological arousal.
... To extract the finger discrimination sensitivity (sensitivity of one finger being correctly discriminated from other fingers), we applied signal detection theory and calculated the d-prime as bias-free index of discrimination sensitivity 129,130 by computing the amount of times a specific finger was touched and detected (hit), or was not touched but falsely detected (false alarm). Hits and false alarms were first converted to z-scores before subtracting false alarms from hits. ...
The segregation of processes into cortical layers is a convergent feature in animal evolution. However, it remains unclear how changes in the cortical layer architecture affect sensory system function and dysfunction. To address this, we conducted layer-specific in-vivo 7T-MRI of the primary somatosensory cortex in younger and older adults and in an adult with congenital arm loss. Input layer IV was enlarged and more myelinated in older adults, which drove extended sensory input signals, whereas with congenital arm loss, input layer IV contralateral to the missing limb had shrunk. Age-related cortical thinning was driven by deep layers, and accompanied by altered functional modulation and behavioral readouts. Neuronal calcium imaging and histology across aging mice revealed altered excitatory/inhibitory balance, with deep-layer cell loss and overall increased parvalbumin cell density as potential neural underpinnings. Therefore, the segregation of processes into cortical layers has a unique age-related profile.
... 163 This approach can alleviate the potential misleading inferences of a high-dimensional structure based on its low-dimensional projection that the traditional research has risked committing. 164 Combining this more representative sample of dynamic facial movement patterns and psychophysical tasks, such as signal detection theory 165 and reverse correlation, 166 167 In a similar vein, a face is perceived to belong to someone with high competence if the face is accompanied by richer than poorer clothes. 168 To address this limitation, recent research has incorporated dynamic facial movement and naturalistic face images as stimuli to study the perception of affective states 163,169 and social traits. ...
Faces are among the most important visual stimuli that humans perceive in everyday life. While extensive literature has examined emotional processing and social evaluations of faces, most studies have examined either topic using unimodal approaches. In this review, we promote the use of multimodal cognitive neuroscience approaches to study these processes, using two lines of research as examples: ambiguity in facial expressions of emotion and social trait judgment of faces. In the first set of studies, we identified an event‐related potential that signals emotion ambiguity using electroencephalography and we found convergent neural responses to emotion ambiguity using functional neuroimaging and single‐neuron recordings. In the second set of studies, we discuss how different neuroimaging and personality‐dimensional approaches together provide new insights into social trait judgments of faces. In both sets of studies, we provide an in‐depth comparison between neurotypicals and people with autism spectrum disorder. We offer a computational account for the behavioral and neural markers of the different facial processing between the two groups. Finally, we suggest new practices for studying the emotional processing and social evaluations of faces. All data discussed in the case studies of this review are publicly available.
... Observers must examine those cues and decide whether to treat a persona as a human or a bot, considering the costs and benefits of correct and incorrect decisions. Signal detection theory (SDT) formalizes such tasks in terms of two components: (a) sensitivity, reflecting how well an observer can distinguish the two possible states; and (b) criterion, reflecting the observer's preferences for making correct judgments and avoiding incorrect ones (Green & Swets, 1966;Macmillan & Creelman, 2004;McNicol, 2005;Stanislaw & Todorov, 1999). These factors apply whether human observers or machine learning algorithms are the detectors (Batailler et al., 2022). ...
Objective
We test the effects of three aids on individuals’ ability to detect social bots among Twitter personas: a bot indicator score, a training video, and a warning.
Background
Detecting social bots can prevent online deception. We use a simulated social media task to evaluate three aids.
Method
Lay participants judged whether each of 60 Twitter personas was a human or social bot in a simulated online environment, using agreement between three machine learning algorithms to estimate the probability of each persona being a bot. Experiment 1 compared a control group and two intervention groups, one provided a bot indicator score for each tweet; the other provided a warning about social bots. Experiment 2 compared a control group and two intervention groups, one receiving the bot indicator scores and the other a training video, focused on heuristics for identifying social bots.
Results
The bot indicator score intervention improved predictive performance and reduced overconfidence in both experiments. The training video was also effective, although somewhat less so. The warning had no effect. Participants rarely reported willingness to share content for a persona that they labeled as a bot, even when they agreed with it.
Conclusions
Informative interventions improved social bot detection; warning alone did not.
Application
We offer an experimental testbed and methodology that can be used to evaluate and refine interventions designed to reduce vulnerability to social bots. We show the value of two interventions that could be applied in many settings.
... In the presence of intrusive noise, it may be useful to refer to Signal Detection Theory (SDT), which is applicable to sensory stimuli, including auditory stimuli [29][30][31]. ...
In forensic acoustics, a possible area of analysis is represented by unwanted sound that is perceived as a source of intrusion or disturbance within a certain auditory context. This context is defined as the “auditory scene” and refers to the set of sounds present in a specific environment. The presence of unwanted sounds in the auditory scene can cause a wide range of negative effects, including disturbance, discomfort, moral or immoral harm, and other types of negative impacts on the health and well-being of individuals exposed to noise. In 2022, the technical specification UNI/TS 11844:2022 dedicated to the measurement and analysis of intrusive noise was published. The standard introduces the concept of intrusive noise and defines its calculation methods based on environmental measurements. The purposes of this technical specification is to provide an objective support to methods already in used in acoustic disputes, where the assessment of the annoyance of a noise is often a subjective evaluation of the technician. This work delves into application to some real cases, identifying the potentiality and limits of the standardized method.
... Participants were asked to do a yes-no recognition test. The proportions of correct and incorrect answers were transformed into d' (a standard measurement for recognition; McNicol, 1972). ...
Sex differences favoring women have been found in a number of studies of episodic memory. This study examined sex differences in verbal, nonverbal, and visuospatial episodic memory tasks. Results showed that although women performed at a higher level on a composite verbal and nonverbal episodic memory score, men performed at a higher level on a composite score of episodic memory tasks requiring visuospatial processing. Thus, men can use their superior visuospatial abilities to excel in highly visuospatial episodic memory tasks, whereas women seem to excel in episodic memory tasks in which a verbalization of the material is possible.
... These data were transformed to a" and LX estimates by reference to the formulas and table of Hochhaus (1972). To obtain a more homogeneous distribution, L a values were subjected to a logarithmic transformation: logio LV (McNicol, 1972). Mean values and standard errors for d' and logio L a are shown in Table 3. One-way analyses of variance performed on both d' and transformed L x scores for the five groups yielded nonsignificant diagnosis factors. ...
Examined 2 differing explanations of schizophrenic processing deficit, J. Chapman and A. McGhie's (1962) and A. J. Yates's (see PA, Vol 41:10769). 32 18-46 yr old schizophrenics, classified on the acute-chronic and paranoid-nonparanoid dimensions, and 8 17-45 yr old neurotics were tested on 2 dichotic listening tasks. One task gave reaction time measures of processing speed at 3 rates of stimulus presentation; the other assessed stimulus detection and channel selectivity using theory of signal detection methods. Results support Yates and indicate that schizophrenics can attend successfully to 1 of 2 competing channels. Neither reduced sensory sensitivity nor response bias appeared to affect the performance of any group of Ss. Slowness of processing was a deficit characteristic of chronic, particularly nonparanoid, schizophrenics, although the factors responsible for this slowness remain a matter for empirical investigation. (25 ref)
... They are deduced from recognition data. The relation of the underlying distributions to the data obtained from standard recognition tests-yes/no, confidence rating, forced choice-is given in detail by Glanzer and Adams (1985) and others (Egan, 1975;Green & Swets, 1966;McNicol, 1972). Some possible distributions for two classes of stimuli, when one is more accurately recognized than the other, are shown in Figure 1. ...
The mirror effect is a regularity in recognition memory that requires reexamination of current views of memory. Five experiments that further support and extend the generality of the mirror effect are reported. The first two experiments vary word frequency. The third and fourth vary both word frequency and concreteness. The fifth experiment varies word frequency, concreteness, and the subject’s operations on the words. The experiments furnish data on the stability of the effect, its relation to response times, its extension to multiple mirror effects, and its extension beyond stimulus variables to operation variables. A theory of the effect and predictions that derive from the theory are presented.
... Information availability may be modified by habitat conditions (Weissburg et al., 2014), therefore we might expect neophobic responses in prey to be shaped by environmental conditions. This interference may be attributed to environmental 'noise', which has often been defined as background patterns or stimuli which interfere with the detection or response to cues of interest and which can occur in several modalities (Brumm, 2013;Koops, 1998;McNicol, 2004). However, noise may also be described as any unwanted or unintended additions to information, including distortions or transmission errors, which generate greater uncertainty (Shannon, 1948). ...
In response to uncertain risks, prey may rely on neophobic phenotypes to reduce the costs associated with the lack of information regarding local conditions. Neophobia has been shown to be driven by information reliability, ambient risk and predator diversity, all of which shape uncertainty of risk. We similarly expect environmental conditions to shape uncertainty by interfering with information availability. In order to test how environmental variables might shape neophobic responses in Trinidadian guppies ( Poecilia reticulata ), we conducted an in situ field experiment of two high‐predation risk guppy populations designed to determine how the ‘average’ and ‘variance’ of several environmental factors might influence the neophobic response to novel predator models and/or novel foraging patches. Our results suggest neophobia is shaped by water velocity, microhabitat complexity, pool width and depth, as well as substrate diversity and heterogeneity. Moreover, we found differential effects of the ‘average’ and ‘variance’ environmental variables on food‐ and predator‐related neophobia. Our study highlights that assessment of neophobic drivers should consider predation risk, various microhabitat conditions and neophobia being tested. Neophobic phenotypes are expected to increase the probability of prey survival and reproductive success (i.e. fitness), and are therefore likely linked to population health and species survival. Understanding the drivers and consequences of uncertainty of risk is an increasingly pressing issue, as ecological uncertainty increases with the combined effects of climate change, anthropogenic disturbances and invasive species.
... In the presence of intrusive noise it may be useful to refer to the theory of the "Signal Detection Theory, SDT", applicable to sensory stimuli, including auditory stimuli [24][25][26]. ...
In forensic acoustics, a possible area of analysis is represented by unwanted sound that 1 is perceived as a source of intrusion or disturbance within a certain auditory context. This context 2 is defined as the "auditory scene" and refers to the set of sounds present in a specific environment. 3 The presence of unwanted sounds in the auditory scene can cause a wide range of negative effects, 4 including disturbance, discomfort, moral or immoral harm, and other types of negative impact on the 5 health and well-being of individuals exposed to noise. In 2022, the technical specification UNI/TS 6 11844:2022 dedicated to the measurement and analysis of intrusive noise was published. The standard 7 introduces the concept of intrusive noise and defines its calculation methods based on environmental 8 measurements. The purposes of this technical specification is to provide an objective support to 9 methods already in used in acoustic disputes, where the assessment of the annoyance of a noise is 10 often a subjective evaluation of the technician. This work delves into the application to some real 11 cases, identifying the potentiality and the limits of the standardized method.
... Taken together, these results support the notion of distinct neural representations for all three motion directions ( Figure 3D). To quantify the degree of separation between distributions, we derived receiver-operating-characteristic (McNicol, 2005) curves per participant. Figure 3E shows the grand-average ROC curves for discriminating between the average and the left component motion direction (teal curve in Figure 3E), and between the average of the right component motion (read curve in Figure 3E). ...
The ability to make accurate and timely decisions, such as judging when it is safe to cross
the road, is the foundation of adaptive behaviour. While the computational and neural
processes supporting simple decisions on isolated stimuli have been well characterised, in
the real-world decision-making often requires integration of discrete sensory events over
time and space. When crossing the road, for example, the locations and speeds of several
cars must be considered. It remains unclear how such integrative perceptual decisions are
regulated computationally. Here we used psychophysics, electroencephalography and
computational modelling to understand how the human brain combines visual motion
signals across space. We directly tested competing predictions arising from influential serial
and parallel accounts of visual processing. Using a biologically plausible model of motion
filtering, we find evidence in favour of parallel integration as the fundamental
computational mechanism regulating integrated perceptual decisions.
... If individuals adopt a more liberal response criterion, they are biased towards reporting that the signal is present, and conversely, if they adopt a stricter response criterion, they are biased towards reporting that the signal is absent. (MacMillan & Creelman, 1990;McNicol, 2005;Stanislaw & Todorov, 1999). As can be seen from above, SDT generally recognizes and differentiates two aspects of an individual's performance in a discrimination situation, namely the objective sensibility and the subjective judgment criterion (Krantz, 1969;Rotello et al., 2008). ...
It has been previously found that individuals with internet gaming disorder (IGD) have a negative bias in recognizing facial micro-expressions (MEs). However, the underlying psychological mechanisms of this negative bias remain unknown. According to the signal detection theory (SDT), sensitivity to and response criterion for facial expressions may contribute to the explanation of this negative bias. Specifically, sensitivity (d′) reflects an individual’s ability to detect a given emotional expression and a higher sensitivity indicates a better ability to detect a given emotional expression. Response criterion (c) reflects an individual’s tendency to judge any given facial expression as a particular emotion and a lower response criterion indicates a stronger tendency to judge a facial expression as a particular emotion. It is unclear whether this negative bias in individuals with IGD is primarily due to a lower response criterion for negative MEs or to a higher sensitivity to such MEs. Thus, we used SDT and the Japanese and Caucasian Brief Affect Recognition Test to measure sensitivity to and response criterion for happy and angry MEs with an intensity of 30%, 50% or 70% among 60 individuals with IGD and 60 healthy controls. The results were as follows: (1) Compared with healthy individuals, individuals with IGD had a higher sensitivity (d′) to angry MEs than to happy MEs at the 50% (η² = 0.05) and 70% intensities (η² = 0.11). (2) Compared with healthy individuals, individuals with IGD had a lower response criterion (c) for angry MEs than for happy MEs (η² = 0.29). These results suggest that the negative bias in ME recognition among individuals with IGD may stem from both their higher sensitivity to negative MEs (than to positive MEs) and their lower response criterion for negative MEs (than for positive MEs).
... The parameter value that optimized the method's accuracy on the training set was 7. We then evaluated the method's performance with the chosen parameter value on the test set. We measured the method performance using four standard metrics from signal detection theory: accuracy, precision, recall, and F1 score (McNicol, 2005). A method's precision is the proportion of strategies discovered by our method that correspond to the ground truth strategies, whereas recall defines the proportion of the total number of the ground truth strategies our method discovers. ...
Scientific discovery concerns finding patterns in data and creating insightful hypotheses that explain these patterns. Traditionally, each step of this process required human ingenuity. But the galloping development of computer chips and advances in artificial intelligence (AI) make it increasingly more feasible to automate some parts of scientific discovery. Understanding human planning is one of the fields in which AI has not yet been utilized. State-of-the-art methods for discovering new planning strategies still rely on manual data analysis. Data about the process of human planning is often used to group similar behaviors together. Researchers then use this data to formulate verbal descriptions of the strategies which might underlie those groups of behaviors. In this work, we leverage AI to automate these two steps of scientific discovery. We introduce a method for automatic discovery and description of human planning strategies from process-tracing data collected with the Mouselab-MDP paradigm. Our method utilizes a new algorithm, called Human-Interpret, that performs imitation learning to describe sequences of planning operations in terms of a procedural formula and then translates that formula to natural language. We test our method on a benchmark data set that researchers have previously scrutinized manually. We find that the descriptions of human planning strategies that we obtain automatically are about as understandable as human-generated descriptions. They also cover a substantial proportion of relevant types of human planning strategies that had been discovered manually. Our method saves scientists' time and effort, as all the reasoning about human planning is done automatically. This might make it feasible to more rapidly scale up the search for yet undiscovered cognitive strategies that people use for planning and decision-making to many new decision environments, populations, tasks, and domains. Given these results, we believe that the presented work may accelerate scientific discovery in psychology, and due to its generality, extend to problems from other fields.
... The basic concept of the EI is as follows. The 2 × 2 contingency table (Figure 1) categorises all the outcomes as per the standard theory of signal detection [5] as: true positives (TP) or hits; true negatives (TN) or correct rejections; false positives (FP) or false hits; and false negatives (FN) or misses. From these four cells, two conditions or relations between the index test and the reference standard may be distinguished: consistency, or matching, of outcomes (+/+ or True Positive and −/− or True Negative); and contradiction, or mismatching (+/− or False Positive and −/+ or False Negative). ...
Many metrics exist for the evaluation of binary classifiers, all with their particular advantages and shortcomings. Recently, an “Efficiency Index” (EI) for the evaluation of classifiers has been proposed, based on the consistency (or matching) and contradiction (or mismatching) of outcomes. This metric and its confidence intervals are easy to calculate from the base data in a 2 × 2 contingency table, and their values can be qualitatively and semi-quantitatively categorised. For medical tests, in which context the Efficiency Index was originally proposed, it facilitates the communication of risk (of the correct diagnosis versus misdiagnosis) to both clinicians and patients. Variants of the Efficiency Index (balanced, unbiased) which take into account disease prevalence and test cut-offs have also been described. The objectives of the current paper were firstly to extend the EI construct to other formulations (balanced level, quality), and secondly to explore the utility of the EI and all four of its variants when applied to the dataset of a large prospective test accuracy study of a cognitive screening instrument. This showed that the balanced level, quality, and unbiased formulations of the EI are more stringent measures.
... The 2x2 contingency table (Figure 1) categorises all outcomes as per standard theory of signal detection [5] as: true positives (TP) or hits; true negatives (TN) or correct rejections; false positives (FP) or false hits; and false negatives (FN) or misses. From these four cells, two conditions or relations between the index test and the reference standard may be distinguished: consistency, or matching, of outcomes (+/+ or True Positive, and -/-or True Negative); and contradiction, or mismatching (+/-or False Positive, and -/+ or False Negative). ...
Many metrics exist for the evaluation of binary classifiers, all with their particular advantages and shortcomings. Recently an “Efficiency Index” for the evaluation of classifiers has been proposed, based on the consistency, or matching, and contradiction, or mismatching, of outcomes. This metric and its confidence intervals are easy to calculate from base data in a 2x2 contingency table, and values can be qualitatively and semi-quantitatively categorised. For medical tests, in which context the Efficiency Index was originally proposed, it facilitates communication of risk (of correct diagnosis versus misdiagnosis) to both clinicians and patients. Variants of the efficiency index (balanced, unbiased) which take into account disease prevalence and test cut-offs have also been described. The objectives of the current paper were firstly to extend the EI construct to other formulations (balanced level, quality) and secondly to explore the utility of EI and all four of its variants when applied to the dataset of a large prospective test accuracy study of a cognitive screening instrument. This showed that the balanced level, quality, and unbiased formulations of EI are more stringent measures.
... Sensors were evaluated based on several properties (Extended Data Table 1 and Supplementary Table 1): baseline brightness (F 0 ); fluorescence change (ΔF/F 0 = (F − F 0 )/F 0 ) in response to a single AP (1AP ΔF/F 0 ); fluorescence response to a saturating high-frequency train of 160 APs (reflective of total dynamic range); SNR quantified as the sensitivity index d′ (ref. 26 ) and kinetics (half-rise time (t 1/2,rise ) and t 1/2,decay ). Sensors based on DAPKP showed fast half-decay time and high sensitivity compared with jGCaMP7f, but with slow half-rise times. ...
Calcium imaging with protein-based indicators1,2 is widely used to follow neural activity in intact nervous systems, but current protein sensors report neural activity at timescales much slower than electrical signalling and are limited by trade-offs between sensitivity and kinetics. Here we used large-scale screening and structure-guided mutagenesis to develop and optimize several fast and sensitive GCaMP-type indicators3–8. The resulting ‘jGCaMP8’ sensors, based on the calcium-binding protein calmodulin and a fragment of endothelial nitric oxide synthase, have ultra-fast kinetics (half-rise times of 2 ms) and the highest sensitivity for neural activity reported for a protein-based calcium sensor. jGCaMP8 sensors will allow tracking of large populations of neurons on timescales relevant to neural computation.
... Here, the presented image pairs contain a baseline image to which the other image is compared. The thresholds are estimated by fitting the psychometric function, a maximumlikelihood estimator based on signal detection theory (McNicol, 2005), to the averaged 2AFC task responses. A lesser known purpose of the 2AFC task, as in the present work, is to detect perceptual differences. ...
Objective
The present work explores how the horizontal viewing angle of a virtual character’s face influences perceptions of credibility and approachability.
Background
When encountering virtual characters, people rely both on credibility and approachability judgments to form a first impression of the depicted virtual character. Research shows that certain perceptions are preferred either on frontal or tilted faces, but not how approachability or credibility judgments relate to horizontal viewing angles in finer granularity between 0° and 45°.
Method
52 participants performed a two-alternative forced choice (2AFC) task rating 240 pairwise comparisons of 20 virtual character faces shown in four horizontal viewing angles (0°, 15°, 30°, and 45°) on approachability and credibility. They also rated scales on individual differences based on the BIS-BAS framework (behavioral inhibition system, drive, and reward responsiveness), self-esteem, and personality traits (neuroticism, loneliness).
Results
Both approachability and credibility were negatively related to the horizontal viewing angle, but the negative relationship was less pronounced for approachability. Notably, 15° tilted faces were associated with higher approachability than frontal faces by people scoring high in reward responsiveness, drive, and self-esteem, and scoring low in neuroticism and loneliness.
Conclusion
Our findings highlight the conditions under which showing a virtual character’s face is preferred in a horizontally 15° tilted over a frontal position.
Application
The differential impact of the horizontal viewing angle on approachability and credibility should be considered when displaying virtual character faces.
... Technological capabilities of MPS to be further developed include a variety of models of increasing architectural complexity for different stages of drug/chemical development, representation of healthy and diseased populations by a personalized multiverse of possible futures, platform standardization, increase in throughput, validation against human in vivo outcomes, incor- 3. Increasing combination of high-throughput and high-content analyses. 4. Improved data mining, e.g., applying signal detection theory (McNicol, 2016) or Dempster-Shafer theory 59 , a combination of evidence obtained from multiple sources, and the modeling of conflict between them. 5. Explainable AI, i.e., the emerging use of tools and frameworks to help understand and interpret predictions made by machine learning models. Currently, these come with lower accuracy of prediction, but this will be a matter of time only. ...
Four decades of the Human Genome Project and its consequences have shown how the entrepreneurial state, through significant investment into science, can drive scientific progress and advance biomedicine. A certain fraction of diseases can now be explained as caused by genetics, and a more significant fraction as impacted by genetics. Besides another fraction caused by pathogens, the third and probably largest impactor is exposure, i.e., the many physicochemical and lifestyle factors. This article makes the case that it is time to start a Human Exposome Project, which systematically explores and catalogs the exposure side of human health and disease. The envisioned Human Exposome Project needs to be more than a scaled exposomics approach, aiming to assess the totality of relevant exposures through ~omics of human body fluids and forming exposure hypotheses. Exposomics is increasingly complemented by exposure science and biomonitoring to measure exposure, mechanistic understanding, human-relevant microphysiological systems, big data, and artificial intelligence (AI) to mine these data and integrate pieces of evidence. The potential impact of AI on a possible Human Exposome Project is so substantial that we should speak of exposome intelligence (EI) because this allows us to expand our limited current knowledge to the big unknown unknowns of threats to human health.
... A related question concerns the extent to which metrics were useful in identifying participants classified as improved or unimproved in QoL, i.e. their accuracy when making this discrimination. ROC curves were generated for each metric in detecting the QoL binary outcome and standard signal detection methods applied to quantify overall performance (AUC), sensitivity (accuracy in detecting QoL improvement), and specificity (accuracy in detecting lack of QoL improvement) (Green & Swets, 1966;McNicol, 2004;Stanislaw & Todorov, 1999). AUC provides an index of the overall performance in distinguishing the groups, where values of 0.5 indicate chance performance and values of 1.0 correspond to errorless detection (Hajian-Tilaki, 2013). ...
Background:
In difficult-to-treat depression (DTD) the outcome metrics historically used to evaluate treatment effectiveness may be suboptimal. Metrics based on remission status and on single end-point (SEP) assessment may be problematic given infrequent symptom remission, temporal instability, and poor durability of benefit in DTD.
Methods:
Self-report and clinician assessment of depression symptom severity were regularly obtained over a 2-year period in a chronic and highly treatment-resistant registry sample (N = 406) receiving treatment as usual, with or without vagus nerve stimulation. Twenty alternative metrics for characterizing symptomatic improvement were evaluated, contrasting SEP metrics with integrative (INT) metrics that aggregated information over time. Metrics were compared in effect size and discriminating power when contrasting groups that did (N = 153) and did not (N = 253) achieve a threshold level of improvement in end-point quality-of-life (QoL) scores, and in their association with continuous QoL scores.
Results:
Metrics based on remission status had smaller effect size and poorer discrimination of the binary QoL outcome and weaker associations with the continuous end-point QoL scores than metrics based on partial response or response. The metrics with the strongest performance characteristics were the SEP measure of percentage change in symptom severity and the INT metric quantifying the proportion of the observation period in partial response or better. Both metrics contributed independent variance when predicting end-point QoL scores.
Conclusions:
Revision is needed in the metrics used to quantify symptomatic change in DTD with consideration of INT time-based measures as primary or secondary outcomes. Metrics based on remission status may not be useful.
... Specifically, num_leaves and max_depth were set to 15 and 4, respectively, both L1 and L2 regularisation terms were set to 1.0 and other parameters were set to default values [37]. The performance of the established classifier was evaluated by typical indicators including precision, recall, their harmonic mean value F1-score and Area Under Curve (AUC) [38]. The value of these indicators ranges from 0 to 1, and a higher value generally means a better classification capability of the classifier. ...
Few existing research studies have explored the relationship of road section level, local area level and vehicle level risks within the highway traffic safety system, which can be important to the formation of an effective risk event prediction. This paper proposes a framework of multi-level risks described by a set of carefully selected or designed indicators. The interrelationship among these latent multi-level risks and their observable indicators are explored based on vehicle trajectory data using the structural equation model (SEM). The results show that there exists significant positive correlation between the latent risk constructs that each have adequate convergent validity, and it is difficult to completely separate the local traffic level risk from both the road section level risk and vehicle level risk. The local and road level indicators are also found to be of more importance when risk prediction time gets earlier based on feature importance scoring of the LightGBM. The proposed conceptual multi-level indicator based latent risk framework generally fits with the observed results and emphasises the importance of including multi-level indicators for risk event prediction in the future.
... Models were fit to a random sample of 80% of the data (1814 for the analysis of topics discussed, 1972 for the device demonstrations), and accuracy for predicting the remaining 20% was assessed by calculating the area under the receiver operating characteristic curve, which represents the trade-off between false-positive and true-positive classifications for a range of thresholds on the response probabilities estimated by the regression (ranging from 0 to 1). 31 To visualize differences in trends for patients of different ages, we grouped patients into five age groups. Because there is no uniform standard for age groups in low vision, we base these cohorts on the Medical Subject Heading dictionary (https://www.ncbi. ...
Significance:
Understanding longitudinal changes in why individuals frequent low vision clinics is crucial for ensuring that patient care keeps current with changing technology and changing lifestyles. Among other findings, our results suggest that reading remains a prevailing patient complaint, with shifting priorities towards technology-related topics.
Purpose:
To understand changes in patient priorities and patient care in low vision over the past decade.
Methods:
We conducted a retrospective study of exam records (2009-2019, 3470 exams) from two United States low vision clinics. Automated word searches summarized two properties of the records: topics discussed during the case history and types of rehabilitative devices assessed. Logistic regression was used to model effects of exam year, patient age, patient gender, and level of visual impairment.
Results:
Collapsing across all years, the most common topic discussed was reading (78%), followed by light-related topics (71%) and technology (59%). While the odds of discussing reading trended downward over the decade (odds ratio = 0.57; p = 0.026), technology, social interaction, mobility, and driving trended upward (odds ratios = 4.53, 3.31, 2.71, 1.95; all ps < 0.001). The most frequently assessed devices were tinted lenses (95%). Over time, video magnifier and spectacle assessments trended downward (odds ratios = 0.64, 0.72; p = 0.004, 0.035), while assessments of other optical aids increased. The data indicate several consistent differences amongst patient demographics.
Conclusions:
Reading is likely to remain a prevailing patient complaint, but an increase in technology-related topics suggests shifting priorities, particularly in younger demographics. "Low tech" optical aids have remained prominent in low vision care even as "high tech" assistive devices in the marketplace continue to advance.
... Out of 261 effect sizes on discriminability in the current database, 82.4% used d' family (Swets, 1973; e.g., d', da, or log-liner d'), 17.2% used A' family (Pollack & Norman, 1964; e.g., A', Ag, or Az), and the remaining 0.4% used Pr (Kikutani, 2018). Out of 73 effect sizes on criterion in the current database, 63.0% used c (Swets, 1973), 23.3% used B'' family (Grier, 1971; e.g., B'', or B''D), 11.0% used β family (McNicol, 1972; e.g., β, or log β), and the remaining 2.7% used other indices (e.g., Br). Because researchers were less likely to analyze participants' criterion than accuracy performance (e.g., discriminability, hit and false alarm rates) in facial identification studies, the total number of effect sizes on criterion was relatively smaller than that on discriminability. ...
The current research conducted a three-level meta-analysis with a total of 159 journal articles on the other-race bias in facial identification, which had been published between 1969 and 2021. The effect size analysis yielded moderate pooled effect sizes of the other-race bias on face identification—people showed higher hit rates and discriminability, lower false alarm rates, and more stringent criteria for own-race faces than for other-race faces. Results from the sensitivity analysis and publication bias analysis also supported the robustness of the other-race bias. In moderation analyses, participant race (White vs. non-White) and retention interval between the study and test phases produced stable moderating effects on estimates of the other-race bias. Despite an increase in racial diversity for decades in our society, the current meta-analysis still demonstrated robust effects of the other-race bias in facial identification, replicating findings from the previous meta-analyses.
... We obtained a score that ranges from −1 (i.e., worst performance: 30/30 FP and 0/15 Hits) to +1 (i.e., best performance: 15/15 Hits and 0/30 FP). We decided to use this measure instead of the procedure proposed by other authors (McNicol, 1972;Gainotti, Marra, & Villa, 2001), based on the signal detection theory (Parks, 1966). ...
Objective
The Rey Auditory Verbal Learning Test (RAVLT) is a widely used verbal memory measure that provides scores for different aspects of memory. It involves repeated auditory presentation and recall of a 15-item word list (List A) followed by presentation and recall of a distractor list (List B) and then un-cued immediate and delayed recalls (at 15 min and 1 week) of List A as well as recognition testing. Aims of this study are to provide Italian normative data for certain RAVLT Scores and Composite Indices to improve the diagnostic accuracy of the test in clinical settings and to provide further evidence on how RAVLT can differentiate different amnesia profiles due to focal lesions.
Methods
We enrolled 440 healthy participants and RAVLT Single Scores and Composite Indices have been analyzed by means of multiple regression to verify the influence of age, education, and gender.
Results
We computed the best linear models with RAVLT Single Scores and Composite Indices, as dependent variables, and the most suitable transformation of independent variables. By reversing the signs of the regression coefficients, the adjustment factors for each level of age and, if needed, education and gender have been computed and the adjusted scores have been standardized into Equivalent Scores.
Conclusion
Using these standardized measures, we differentiate three profiles of amnesia due to selective hippocampal sclerosis with severe encoding deficit, fornix lesions with source memory problems, and temporal lobe epilepsy with consolidation failure.
... The advantage of the measure A' is that it is easily interpreted as percent correct, but it has also some disadvantages (i.e., is not distribution free and is not independent of bias) (Pastore et al., 2003). McNicol (1972) and several years later Snodgrass and Corwin (1988) reached the same conclusion, indicating that, "if there is a bias in either direction, A' will underestimate the sensitivity". Thus, readers and researchers should be aware of this limitation. ...
Objective: This study investigated the effect of the spatial disorientation (SD) events on an attentive blank stare in the cockpit scene and demonstrated how much the flight task and visual delayed discrimination task were competing for the pilots’ attention.
Background: SD in flight is the leading cause of human error-related aircraft accidents in the military, general and commercial aviation, and has been an unsolved problem since the inception of flight. In-flight safety research, visually scanning cockpit instruments,
and detecting changes are critical countermeasures against SD.
Method: Thirty male military pilots were performing a dual-task involving piloting a flight simulator and visual change detection, while eye movements were obtained using an eye tracker.
Results: Pilots made more flight errors and spent less time gazing at the area of change in SD-conflict than in non-conflict flights. The vestibular origin SD-conflict led not only to deteriorated piloting and visual scanning but also to problems coordinating overt and covert attention, resulting in lower noticeability of visual changes despite gazing at them.
Conclusion: Our study shows that looking at a given area in space is not a sufficient condition for effective covert attention allocation and the correct response to a visual stimulus. It seems to be important to make pilots aware of this during SD training.
Application: To reduce change blindness, some strategies, such as reducing the number of secondary tasks is extremely valuable. Particular efforts should also be focused on improving the design of the aircraft cockpit by increasing the conspicuousness of
critical information.
... In cognitive psychology, it is used to detect perception thresholds or evaluate the psychological differentiation of stimulus variation. Applying signal detection theory (McNicol, 2005), the underlying model identifies the detection thresholds of perceived stimuli in a 2AFC task by fitting the so-called psychometric function, a maximum-likelihood estimator, to the averaged 2AFC task responses. In such applications, the presented image pairs contain a baseline image (image without any effect) to which the other image is compared. ...
The present work compares the two-alternative forced choice (2AFC) task to rating scales for measuring aesthetic perception of neural style transfer-generated images and investigates whether and to what extent the 2AFC task extracts clearer and more differentiated patterns of aesthetic preferences. To this aim, 8250 pairwise comparisons of 75 neural style transfer-generated images, varied in five parameter configurations, were measured by the 2AFC task and compared with rating scales. Statistical and qualitative results demonstrated higher precision of the 2AFC task over rating scales in detecting three different aesthetic preference patterns: (a) convergence (number of iterations), (b) an inverted U-shape (learning rate), and (c) a double peak (content-style ratio). Important for practitioners, finding such aesthetically optimal parameter configurations with the 2AFC task enables the reproducibility of aesthetic outcomes by the neural style transfer algorithm, which saves time and computational cost, and yields new insights about parameter-dependent aesthetic preferences. © 2022 The Author(s). Published with license by Taylor & Francis Group, LLC.
... At the same time, noisy samples may also appear in small-scale data sets when the task of sample labeling is very difficult, or the opinions of the labeling personnel are different. In the case of manually labeling RSIs, it is difficult to avoid noisy labels in the training data set [139]. At present, the main sources of noisy labels can be classified into four types: 1) The lack of contextual information of ground objects in low-resolution RSIs leads to the low confidence of labels; 2) Errors caused by the negligence of labeling personnel; 3) Ambiguity caused by multi-source labeling; 4) Ambiguity caused by data encoding [136], [140]. ...
In recent years, supervised learning has been widely used in various tasks of optical remote sensing image understanding, including remote sensing image classification, pixel-wise segmentation, change detection, and object detection. The methods based on supervised learning need a large amount of high-quality training data and their performance highly depends on the quality of the labels. However, in practical remote sensing applications, it is often expensive and time-consuming to obtain large-scale data sets with high-quality labels, which leads to a lack of sufficient supervised information. In some cases, only coarse-grained labels can be obtained, resulting in the lack of exact supervision. In addition, the supervised information obtained manually may be wrong, resulting in a lack of accurate supervision. Therefore, remote sensing image understanding often faces the problems of incomplete, inexact, and inaccurate supervised information, which will affect the breadth and depth of remote sensing applications. In order to solve the above-mentioned problems, researchers have explored various tasks in remote sensing image understanding under weak supervision. This paper summarizes the research progress of weakly supervised learning in the field of remote sensing, including three typical weakly supervised paradigms: 1) Incomplete supervision, where only a subset of training data is labeled; 2) Inexact supervision, where only coarse-grained labels of training data are given; 3) Inaccurate supervision, where the labels given are not always true on the ground.
... This procedure cuts data collection time approximately in half by using an adaptive tracking paradigm in which the tones presented are absolute threshold measures comparable to the ones found when using a two-interval forced-choice procedure that controls for response bias [12]. While the use of different psychometric methods has been known to affect measurements, both procedures employed by Ries & DiGiovanni [11,12] were designed to target the same psychometric point of performance of 75% correct [7,25,26]. ...
Background
The study investigated the cause of varying estimates of frequency difference limens (DLs) in delayed comparison tasks involving pitch retention in auditory working memory (AWM). Using procedures adapted from the method of constant stimuli (MCS) and the single-interval adjustment matrix (SIAM), we sought to determine via 3 experiments whether the disparity in frequency DLs obtained using each procedure was due to the method of measurement (Experiment 1), the response format (Experiment 2), or performance feedback (Experiment 3).
Material and methods
Five adults (ages 21 to 38 years) with hearing within normal limits participated in Experiments 1 and 2, and seven adults (ages 20 to 30 years) with hearing within normal limits participated in Experiment 3. Delayed comparison tasks were used to evaluate frequency DLs under SIAM and MCS.
Results
Our preliminary results suggest that DL values for pitch discrimination are more influenced by response format than by the measurement procedure or performance feedback. Regardless of the method used, DL values were greater in the condition containing intervening stimuli compared to the condition lacking intervening stimuli.
Conclusions
Preliminary findings suggest there is consistency in the listener’s adopted criterion (i.e., judgment rationale) across the psychoacoustic methods investigated. Performance measures suggest that SIAM is as accurate as MCS, but it is noteworthy that two SIAM measurement runs using the "same/different" response format is more efficient than four runs with MCS. Future application of the SIAM procedure for measuring DL values might, with larger sample sizes, identify additional factors that contribute to performance and the listener’s adopted criterion, since data collection time is appreciably shorter with SIAM.
... To obtain this, raw data were first entered into a 4 × 4 matrix representing the frequency with which each response was made for each stimulus, to obtain three pairwise Receiver Operating Characteristic (ROC) curves (Macmillan and Creelman 2005). Non-parametric signal detection analysis (McNicol 2005) was then used to produce the mean Area Under the Curve (AUC), calculated using SPSS software v.23. This gave each participant an ankle movement discrimination score, which provides an unbiased estimate of the ability of an individual to discriminate between adjacent pairs of stimuli. ...
Ankle complex proprioception and plantar sole sensitivity have been separately reported to be essential sensory components in balance control among the elderly. However, their inter-relationship is still unknown. Further, although optimal proprioceptive ability has been related to regular physical exercise, the association between physical activity (PA) levels, ankle proprioceptive acuity and plantar cutaneous sensation is unclear. Therefore, this study aims to compare ankle proprioceptive acuity and plantar cutaneous sensitivity scores between groups of older women with different PA levels, and to determine any relationships between plantar sole cutaneous sensitivity, ankle proprioceptive performance and PA levels. 68 older female participants were recruited who were distributed over three PA levels: highly active, moderately active, and inactive. PA level was assessed by the International Physical Activity Questionnaire. Ankle proprioceptive acuity was tested in full weight-bearing stance using the ankle Active Movement Extent Discrimination Apparatus (AMEDA) and plantar cutaneous sensitivity was assessed with the Nylon Semmes–Weinstein monofilaments test. Results showed that ankle proprioceptive acuity scores were strongly positively related to plantar sole sensitivity scores (r = 0.80, p < 0.001; effect size: η2 = 0.715), and both scores correlated with PA level. In conclusion, plantar cutaneous sensitivity and ankle complex proprioception were strongly correlated in older females with different levels of physical activity, suggesting that the former may be an integral part of the latter. Given the previously reported contribution of AMEDA ankle proprioceptive acuity to sport performance level, the health of the plantar sole of the foot may be important as a performance determinant.
Signal Detection Theory (SDT) is a framework used to understand how decisions are made under conditions of uncertainty. It originated in the field of sensory psychology but has since been applied to various fields like cognitive psychology, neuroscience, and also to epidemiology, medical diagnosis, and radar signal processing. SDT also has applications in education, risk assessment, and data analysis in general. Some of the basic concepts and terminology of SDT include the following: signal, noise, hit, miss, false alarm, and correct rejection. The overarching purpose of SDT is to optimize the effectiveness of decision-making under uncertainty (i.e., when signals are weak or when there is a high level of noise). SDT posits that the decision-making process involves comparing sensory input (input data) to a threshold or criterion value. If the input exceeds the threshold, a signal is detected; if a signal does not exceed a decision threshold it is considered noise.
Recent developments in psychophysics termed statistical decision theory (or signal detection theory; SDT) and magnitude estimation (ME) are being applied to an increasing variety of previously recalcitrant problems in clinical psychology and medical decision making. The SDT method separates human decision making into a discrimination accuracy measure and a criterion or bias measure. This characteristic is helpful in analyzing confusing situations such as pain assessment, where any number of procedures or manipulations can affect the S's willingness to report pain, but leave unaffected the detectability of pain-producing stimuli. ME methods applied to personality research do not limit an individual's assessment of his or her personal reactions (e.g., degree of anxiety or intoxication) to a range of categories devised by the experimenter but allow each person to construct as sensitive and unique a scale as is required. These methods also show superior agreement with psychophysiological measures of such factors. It is suggested that ME and SDT represent a significant advance over current practices in terms of their greater objectivity and precision, parsimonious use of a single language for the laboratory and the clinic, and potential for the quantification of subtle covert psychological behaviors. Applications of SDT and ME to the assessment and understanding of pain, anxiety, psychoactive drugs, and medical decision making are described. (97 ref)
The circular diffusion model represents continuous outcome decision making as evidence accumulation by a two-dimensional Wiener process with drift on the interior of a disk, whose radius represents the decision criterion for the task. The hitting point on the circumference of the disk represents the decision outcome and the hitting time represents the decision time. The Girsanov change-of-measure theorem applied to the first-passage time distribution for the Euclidean distance Bessel process yields an explicit expression for the joint distribution of decision outcomes and decision times for the model. A problem with the expression for the joint distribution obtained in this way is that the change-of-measure calculation magnifies numerical noise in the series expression for the Bessel process, which can make the expression unstable at small times when the drift rate or decision criterion is large. We introduce a new method that uses an asymptotic approximation to characterize the Bessel process at short times and the series expression for the large times. The resulting expressions are stable across all parts of the parameter space likely to be of interest in experiments, which greatly simplifies the task of fitting the model to data. The new method applies to the spherical and hyperspherical generalizations of the model and to versions of it in which the drift rates are normally distributed across trials with independent or correlated components.
Background:
Closed-ended rating scales are the most used response format for researchers and clinicians to quantify mental states, whereas in natural contexts people communicate with natural language. The reason for using such scales is that they are typically argued to be more precise in measuring mental constructs; however, the respondents' views as to what best communicates mental states are frequently ignored, which is important for making them comply with assessment.
Methods:
We assessed respondents' (N = 304) degree of depression using rating scales, descriptive words, selected words, and free text responses and probed the respondents for their preferences concerning the response formats across twelve dimensions related to the precision of communicating their mental states and the ease of responding. This was compared with the clinicians' (N = 40) belief of the respondent's view.
Results:
Respondents found free text to be more precise (e.g., precision d' = .88, elaboration d' = 2.0) than rating scales, whereas rating scales were rated as easier to respond to (e.g., easier d' = -.67, faster d' = -1.13). Respondents preferred the free text responses to a greater degree than rating scales compared to clinicians' belief of the respondents' views.
Conclusions:
These findings support previous studies concluding that future assessment of mental health can be aided by computational methods based on text data. Participants prefer an open response format as it allows them to elaborate, be precise, etc., with respect to their mental health issues, although rating scales are viewed as faster and easier.
Signal detection theory is a framework developed in mathematical psychology to explain judgement with perceptual uncertainty, and is used in a variety of fields of psychonomics. It quantifies signal detectability, which is the ability to detect a perceived signal, and response bias, which is the tendency to overestimate or underestimate the existence of a signal. It is essential for applied researchers to understand its mathematical background and theoretical development to date in order to apply the theory properly and productively. However, few comprehensive documents are available that comprehensively describe the theory in Japanese. Therefore, this paper addresses the basic concepts and methods of the theory with related mathematical backgrounds and reviews its recent theoretical developments.
Temporal perception is so profoundly linked to hearing that congenitally and early deaf individuals appear to experience visual temporal impairments. However, most studies investigated visual temporal perception in deaf individuals using static stimuli, while ecological objects with which we interact in everyday life often move across space and time. Given that deafness does not impact spatial metric representations, we hypothesize that, while the temporal perception of static stimuli is altered after early hearing loss, it can be enhanced by providing additional, ecologically relevant information. To evaluate our hypothesis, deaf and hearing participants were tested using an oddball-like visual temporal task. In such a task, participants had to temporally discriminate a Target embedded in a series of static stimuli, whose spatiotemporal structure was dynamically manipulated during the presentation. Our results highlighted that deaf participants could not successfully discriminate the Target’s duration when only temporal information was manipulated, while their temporal sensitivity significantly improved when coherent spatiotemporal information was displayed. Our findings suggest that deaf participants might develop compensatory strategies based on other visual, non-temporal features to estimate external time events.
To address the question which neocortical layers and cell types are important for the perception of a sensory stimulus, we performed multielectrode recordings in the barrel cortex of head-fixed mice performing a single-whisker go/no-go detection task with vibrotactile stimuli of differing intensities. We found that behavioral detection probability decreased gradually over the course of each session, which was well explained by a signal detection theory-based model that posits stable psychometric sensitivity and a variable decision criterion updated after each reinforcement, reflecting decreasing motivation. Analysis of multiunit activity demonstrated highest neurometric sensitivity in layer 4, which was achieved within only 30 ms after stimulus onset. At the level of single neurons, we observed substantial heterogeneity of neurometric sensitivity within and across layers, ranging from nonresponsiveness to approaching or even exceeding psychometric sensitivity. In all cortical layers, putative inhibitory interneurons on average proffered higher neurometric sensitivity than putative excitatory neurons. In infragranular layers, neurons increasing firing rate in response to stimulation featured higher sensitivities than neurons decreasing firing rate. Offline machine-learning-based analysis of videos of behavioral sessions showed that mice performed better when not moving, which at the neuronal level, was reflected by increased stimulus-evoked firing rates.
Research summary
Our article examines the deliberate creation of learning opportunities in the global rollout of innovations. Some firms launch in only a subset of markets at first, with later launches being conditional on debut‐market performance. Such sequencing decreases the downside of potential innovation failure but increases the downside of potential competitive preemption. Consistent with this trade‐off, handset makers during the feature‐phone era sequence rollout more often when innovations are novel. Also consistent is that sequencing seems to respond to firms' past experience with failure and preemption, and that it begins in markets offering strong signals of success and failure—markets with competing innovations and sophisticated consumers, respectively. Our findings contribute to the understanding of entry strategy and opens avenues for researching intentional organizational experimentation.
Managerial summary
Firms can decide whether to launch innovations little by little or everywhere at once. Trial launches allow firms to test commercial viability and react to outcomes before rolling out elsewhere, but risks that competitors get their first. An immediate global launch, by contrast, reduces the scope for competitive preemption but increases the costs of potential failure. Our article uses data from the handset industry to highlight conditions that shape rollout decisions and examine the debut markets sought out for trial launches. Firms tend to trial novel innovations in particular, and their experience with prior misses as well as flops influences their preference. Trial launches often begin in markets with strong competition and discerning consumers, indicating an initial prioritization of learning over monetization. Opportunities for experimentation during market rollout thus ought to feature in strategic considerations of entry timing.
THE THEORY OF SIGNAL DETECTABILITY SUGGESTS VARIABLES WHICH WILL MANIPULATE RESPONSE BIAS. UNDER THE ASSUMPTION THAT S MAXIMIZES EXPECTED VALUE, RESPONSE BIAS WILL CHANGE AS A FUNCTION OF A PRIORI PROBABILITY OF THE SIGNAL. THIS STUDY TESTED THIS HYPOTHESIS WHEN THE CHOICE WAS BETWEEN A TABOO AND NEUTRAL WORD. EACH OF 60 GIRLS WAS GIVEN A PAIR OF WORDS, 1 TABOO AND 1 NEUTRAL, AND WAS INSTRUCTED THAT 1 OF THE 2 WORDS WOULD BE SHOWN. A TABOO WORD, NEUTRAL WORD, OR BLANK WAS PRESENTED ON EACH TRIAL. THE A PRIORI PROBABILITY OF THE TABOO WORD WAS MANIPULATED. THE RESULTS SUPPORT THE ASSUMPTION THAT RESPONSE BIAS (CUTOFF) IS A FUNCTION OF A PRIORI PROBABILITY. UNEXPECTEDLY, TABOO WORDS WERE FOUND TO BE MORE DISCRIMINABLE THAN NEUTRAL WORDS.
This paper is in three major sections. The first provides corrections and additions to existing work on the fitting of receiver operating characteristic (ROC) curves by the method of maximum likelihood. The second compares the predictions of normal and logistic models. The third examines the minimum-logit-chi-square method of parameter estimation in the ROC context.
Conventional least-squares curve fitting procedures are inappropriate for Receiver Operating Characteristic (ROC) plots because both axes represent dependent variables and are both subject to error. A brief review of the problem of interpreting ROC plots is followed by a solution which uses maximum-likelihood estimation of the best fitting straight line derived from a theoretical model which assumes underlying logistic distributions. The logistic is used simply because it is more convenient mathematically than the normal distribution. The normal and logistic models are compared empirically. Two advantages of this estimation procedure are that standard errors for the estimates of the parameters are obtained and there is also a test for goodness-of-fit of the theoretical model. Solutions are given for both yes-no and rating procedures.
This paper investigated a learning model for signal detection which assumes a continuum of sensory states. The model, a generalization of a model originally proposed by Kac (1962, 1969), and selected special cases of this model were evaluated in a 2AFC signal detection task. The general model and its associated special models are quite tractable from the point of view of parameter estimation, and the axioms of the models generate tractable functions for the theoretical probabilities on each trial. Of the special models evaluated, the Kac error-correction model gave the poorest fit on the average.
The basic models of signal detection theory involve the parametric measure,d, generally interpreted as a detectability index. Given two observers, one might wish to know whether their detectability indices are equal or unequal. Gourevitch and Galanter (1967) proposed a large sample statistical test that could be used to test the hypothesis of equald values. In this paper, their large two sample test is extended to aK-sample detection test. If the null hypothesisd
1=d
2=...=d
K
is rejected, one can employ the post hoc confidence interval procedure described in this paper to locate possible statistically significant sources of variance and differences. In addition, it is shown how one can use the Gourevitch and Galanter statistics to testd=0 for a single individual.
A large-sample test for the significance of the difference between two detection data points is developed based upon the assumptions of a one-parameter signal detectability model. In essence, the null hypothesis tested is that two observed data points belong to the samed' function.
The problem of signal detectability treated in this paper is the following: Suppose an observer is given a voltage varying with time during a prescribed observation interval and is asked to decide whether its source is noise or is signal plus noise. What method should the observer use to make this decision, and what receiver is a realization of that method? After giving a discussion of theoretical aspects of this problem, the paper presents specific derivations of the optimum receiver for a number of cases of practical interest. The receiver whose output is the value of the likelihood ratio of the input voltage over the observation interval is the answer to the second question no matter which of the various optimum methods current in the literature is employed including the Neyman - Pearson observer, Siegert's ideal observer, and Woodward and Davies' "observer." An optimum observer required to give a yes or no answer simply chooses an operating level and concludes that the receiver input arose from signal plus noise only when this level is exceeded by the output of his likelihood ratio receiver. Associated with each such operating level are conditional probabilities that the answer is a false alarm and the conditional probability of detection. Graphs of these quantities called receiver operating characteristic, or ROC, curves are convenient for evaluating a receiver. If the detection problem is changed by varying, for example, the signal power, then a family of ROC curves is generated. Such things as betting curves can easily be obtained from such a family. The operating level to be used in a particular situation must be chosen by the observer. His choice will depend on such factors as the permissable false alarm rate, a priori probabilities, and relative importance of errors. With these theoretical aspects serving as an introduction, attention is devoted to the derivation of explicit formulas for likelihood ratio, and for probability of detection and probability -
of false alarm, for a number of particular cases. Stationary, band-limited, white Gaussian noise is assumed. The seven special cases which are presented were chosen from the simplest problems in signal detection which closely represent practical situations. Two of the cases form a basis for the best available approximation to the important problem of finding probability of detection when the starting time of the signal, signal frequency, or both, are unknown. Furthermore, in these two cases uncertainty in the signal can be varied, and a quantitative relationship between uncertainty and ability to detect signals is presented for these two rather general cases. The variety of examples presented should serve to suggest methods for attacking other simple signal detection problems and to give insight into problems too complicated to allow a direct solution.
A table of d' for a model of the unforced choice experiment. Defence Res In Dr Edward's provocative book he attempts to show that practically all aspects of inferential statistics reduce to a consideration of a likelihood function
- M M Taylor
- W C G Fraser
TAYLOR, M. M. and FRASER, W. C. G. (1965). A table of d' for a model of the unforced choice experiment. Defence Res. Med. Lab., Toronto, Canada. Rep. 534. B. J. T. MORGAN Likelihood, by A. W. F. EDWARDS, Cambridge University Press (1972), xvi, 236, ?3.80. In Dr Edward's provocative book he attempts to show that practically all aspects of inferential statistics reduce to a consideration of a likelihood function. While