Salivation to food cues is typically explained in terms of mere stimulus-response links. However, food cues seem to especially increase salivation when food is attractive, suggesting a more complex psychological process. Adopting a grounded cognition perspective, we suggest that perceiving a food triggers simulations of consuming it, especially when attractive. These simulations then induce salivation, which effectively prepares the body for eating the food. In two experiments, we systematically examined the role of simulations on salivation to food cues. As stimuli, both experiments used an attractive, a neutral, and a sour food, as well as a non-food control object. In Experiment 1, participants were instructed to simulate eating every object they would be exposed to. We then exposed them to each object separately. Salivation was assessed by having participants spit their saliva into a cup after one minute of exposure. In Experiment 2, we instructed half of participants to simulate eating each object, and half to merely look at them, while measuring salivation as in Experiment 1. Afterwards, participants rated their simulations and desire to eat for each object separately. As predicted, foods increased salivation compared to the non-food control object, especially when they were attractive or sour (Exp. 1 and 2). Importantly, attractive and sour foods especially increased salivation when instructed to simulate (Exp. 2). These findings suggest that consumption simulations play an important role in inducing salivary responses to food cues. We discuss directions for future research as well as the role of simulations for other appetitive processes.
Clinical practice still relies heavily on traditional paper-and-pencil testing to assess a patient's cognitive functions. Digital technology has the potential to be an efficient and powerful alternative, but for many of the existing digital tests and test batteries the psychometric properties have not been properly established. We validated a newly developed digital test battery consisting of digitized versions of conventional neuropsychological tests. Two confirmatory factor analysis models were specified: a model based on traditional neuropsychological theory and expert consensus and one based on the Cattell-Horn-Carroll (CHC) taxonomy. For both models, the outcome measures of the digital tests loaded on the cognitive domains in the same way as established in the neuropsychological literature. Interestingly, no clear distinction could be made between the CHC model and traditional neuropsychological model in terms of model fit. Taken together, these findings provide preliminary evidence for the structural validity of the digital cognitive test battery.
Objective To validate a fully automated scoring algorithm for the Rey-Osterrieth Complex Figure Test (ROCFT) by comparing the scoring results of the algorithm to the results of human raters. Method The algorithm consisted of a cascade of deep neural networks which were trained on human rater scores to extract the 18 segments of the figure, and to quantify the patient’s performance. Algorithm results were compared to six expert raters for 303 drawings. We tested whether the average correlation between algorithm scores and scores by all human raters was equivalent to the average inter-rater correlation (with equality bound Δr < .05). The immediate and delayed recall trial were used; the copy trial showed a strong ceiling effect. Results The mean Pearson correlation between raters was .94 (SD = 0.01). The correlation between to algorithm and the raters was .88 (SD = 0.02). A two-one-sided t-tests (TOST) equivalence test showed that these correlations were not strictly equivalent, t(5) = 4.02, p = .995, 95% CI [0.35, 0.52]. Conclusions Although not strictly equivalent to human ratings, the algorithm’s performance is high, approaching a level of reliability found among human raters. We expect that improved individual segment detection will bring the algorithm scoring accuracy on par with that of human raters. Algorithmic scoring of the ROCFT will likely save valuable time and lead to higher levels of standardization in clinical practice.
Objective: To collect evidence of validity for a selection of digital tests on the Philips IntelliSpace Cognition (ISC) platform. Method: A total of 200 healthy participants (age 50-80) completed both the ISC battery and an analog version of the battery during separate visits. The battery included the following screeners and cognitive tests: Mini-Mental State Examination (2 nd edition), Clock Drawing Test, Trail-Making Test (TMT), Rey Auditory Verbal Learning Test (RAVLT), Rey-Osterrieth Complex Figure Test (ROCFT), Letter Fluency, Star Cancellation Test, and Digit Span Test. The ISC tests were administered on an iPad Pro and were automatically scored using designated algorithms. The analog tests were administered in line with existing guidelines and scored by trained neuropsychologists. Criterion validity was established through relative agreement coefficients and raw score equivalence tests. In addition,measurement invariance analysis was used to compare the factor structures of both versions. Finally, we explored effects of demographics and experience with digital devices on performance. Results: We found fair to excellent relative agreement between test versions. Absolute equivalence was found for RAVLT, Letter Fluency, Star Cancellation Test, and Digit Span Test. Importantly, we demonstrated equal loadings of the digital and analog test versions on the same set of underlying cognitive domains. Demographic effects were mostly comparable between modalities, and people's experience with digital devices was found to only influence performance on TMT B. Conclusions: This study provides several sources of evidence for the validity of the ISC test battery, offering an important step in validating ISC for clinical use.Digital cognitive testing has been gaining traction in recent years as a powerful and flexible alternative to traditional analog testing. Its potential benefits are well-documented, and include a high level of standardization, a significant increase © 2021 Koninklijke philips n.V. published by informa uK limited, trading as Taylor & Francis group CONTACT gijs van elswijk
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