5 resultados para Psychometric Function

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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The purpose of this clinical trial was to determine the active tactile sensibility of natural teeth and to obtain a statistical analysis method fitting a psychometric function through the observed data points. On 68 complete dentulous test persons (34 males, 34 females, mean age 45.9 ± 16.1 years), one pair of healthy natural teeth each was tested: n = 24 anterior teeth and n = 44 posterior teeth. The computer-assisted, randomized measurement was done by having the subjects bite on thin copper foils of different thickness (5-200 µm) inserted between the teeth. The threshold of active tactile sensibility was defined by the 50% value of correct answers. Additionally, the gradient of the sensibility curve and the support area (90-10% value) as a description of the shape of the sensibility curve were calculated. For modeling the sensibility curve, symmetric and asymmetric functions were used. The mean sensibility threshold was 14.2 ± 12.1 µm. The older the subject, the higher the tactile threshold (r = 0.42, p = 0.0006). The support area was 41.8 ± 43.3 µm. The higher the 50% threshold, the smaller the gradient of the curve and the larger the support area. The curves showing the active tactile sensibility of natural teeth demonstrate a tendency towards asymmetry, so that the active tactile sensibility of natural teeth can mathematically best be described by using the asymmetric Weibull function.

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When tilted sideways participants misperceive the visual vertical assessed by means of a luminous line in otherwise complete dark- ness. A recent modeling approach (De Vrijer et al., 2009) claimed that these typical patterns of errors (known as A- and E-effects) could be explained by as- suming that participants behave in a Bayes optimal manner. In this study, we experimentally manipulate participants’ prior information about body-in-space orientation and measure the effect of this manipulation on the subjective visual vertical (SVV). Specifically, we explore the effects of veridical and misleading instructions about body tilt orientations on the SVV. We used a psychophys- ical 2AFC SVV task at roll tilt angles of 0 degrees, 16 degrees and 4 degrees CW and CCW. Participants were tilted to 4 degrees under different instruction conditions: in one condition, participants received veridical instructions as to their tilt angle, whereas in another condition, participants received the mis- leading instruction that their body position was perfectly upright. Our results indicate systematic differences between the instruction conditions at 4 degrees CW and CCW. Participants did not simply use an ego-centric reference frame in the misleading condition; instead, participants’ estimates of the SVV seem to lie between their head’s Z-axis and the estimate of the SVV as measured in the veridical condition. All participants displayed A-effects at roll tilt an- gles of 16 degrees CW and CCW. We discuss our results in the context of the Bayesian model by De Vrijer et al. (2009), and claim that this pattern of re- sults is consistent with a manipulation of precision of a prior distribution over body-in-space orientations. Furthermore, we introduce a Bayesian Generalized Linear Model for estimating parameters of participants’ psychometric function, which allows us to jointly estimate group level and individual level parameters under all experimental conditions simultaneously, rather than relying on the traditional two-step approach to obtaining group level parameter estimates.

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By means of fixed-links modeling the present study assessed processes involved in visual short-term memory functioning and investigates how these processes are related to intelligence. Using a color change detection task, short-term memory demands increased across three experimental conditions as a function of number of presented stimuli. We measured amount of information retained in visual short-term memory by hit rate as well as speed of visual short-term memory scanning by reaction time. For both measures, fixed-links modeling revealed a constant process reflecting processes irrespective of task manipulation as well as two increasing processes reflecting the increasing short-term memory demands. For visual short-term memory scanning, a negative association between intelligence and the constant process was found but no relationship between intelligence and the increasing processes. Thus, basic processing speed, rather than speed influenced by visual short-term memory demands, differentiates between high- and low-intelligent individuals. Intelligence was positively related to the experimental processes of shortterm memory retention but not to the constant process. In sum, significant associations with intelligence were only obtained when the specific processes of short-term memory were decomposed emphasizing the importance of a thorough assessment of cognitive processes when investigating their relation to intelligence.

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The close association between psychometric intelligence and general discrimination ability (GDA), conceptualized as latent variable derived from performance on different sensory discrimination tasks, is empirically well-established but theoretically widely unclear. The present study contrasted two alternative explanations for this association. The first explanation is based on what Spearman (1904) referred to as a central function underlying this relationship in the sense of the g factor of intelligence and becoming most evident in GDA. In this case, correlations between different aspects of cognitive abilities, such as working memory (WM) capacity, and psychometric intelligence should be mediated by GDA if their correlation is caused by g. Alternatively, the second explanation for the relationship between psychometric intelligence and GDA proceeds from fMRI studies which emphasize the role of WM functioning for sensory discrimination. Given the well-known relationship between WM and psychometric intelligence, the relationship between GDA and psychometric intelligence might be attributed to WM. The present study investigated these two alternative explanations at the level of latent variables. In 197 young adults, a model in which WM mediated the relationship between GDA and psychometric intelligence described the data better than a model in which GDA mediated the relationship between WM and psychometric intelligence. Moreover, GDA failed to explain portions of variance of psychometric intelligence above and beyond WM. These findings clearly support the view that the association between psychometric intelligence and GDA must be understood in terms of WM functioning.

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Numerous studies reported a strong link between working memory capacity (WMC) and fluid intelligence (Gf), although views differ in respect to how close these two constructs are related to each other. In the present study, we used a WMC task with five levels of task demands to assess the relationship between WMC and Gf by means of a new methodological approach referred to as fixed-links modeling. Fixed-links models belong to the family of confirmatory factor analysis (CFA) and are of particular interest for experimental, repeated-measures designs. With this technique, processes systematically varying across task conditions can be disentangled from processes unaffected by the experimental manipulation. Proceeding from the assumption that experimental manipulation in a WMC task leads to increasing demands on WMC, the processes systematically varying across task conditions can be assumed to be WMC-specific. Processes not varying across task conditions, on the other hand, are probably independent of WMC. Fixed-links models allow for representing these two kinds of processes by two independent latent variables. In contrast to traditional CFA where a common latent variable is derived from the different task conditions, fixed-links models facilitate a more precise or purified representation of the WMC-related processes of interest. By using fixed-links modeling to analyze data of 200 participants, we identified a non-experimental latent variable, representing processes that remained constant irrespective of the WMC task conditions, and an experimental latent variable which reflected processes that varied as a function of experimental manipulation. This latter variable represents the increasing demands on WMC and, hence, was considered a purified measure of WMC controlled for the constant processes. Fixed-links modeling showed that both the purified measure of WMC (β = .48) as well as the constant processes involved in the task (β = .45) were related to Gf. Taken together, these two latent variables explained the same portion of variance of Gf as a single latent variable obtained by traditional CFA (β = .65) indicating that traditional CFA causes an overestimation of the effective relationship between WMC and Gf. Thus, fixed-links modeling provides a feasible method for a more valid investigation of the functional relationship between specific constructs.