Time-evolving psychological processes over repeated decisions.

Many psychological experiments have subjects repeat a task to gain the statistical precision required to test quantitative theories of psychological performance. In such experiments, time-on-task can have sizable effects on performance, changing the psychological processes under investigation. Most research has either ignored these changes, treating the underlying process as static, or sacrificed some psychological content of the models for statistical simplicity. We use particle Markov chain Monte-Carlo methods to study psychologically plausible time-varying changes in model parameters. Using data from three highly cited experiments, we find strong evidence in favor of a hidden Markov switching process as an explanation of time-varying effects. This embodies the psychological assumption of "regime switching," with subjects alternating between different cognitive states representing different modes of decision-making. The switching model explains key long- and short-term dynamic effects in the data. The central idea of our approach can be applied quite generally to quantitative psychological theories, beyond the models and datasets that we investigate. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Efficient selection between hierarchical cognitive models: Cross-validation with variational Bayes.

Model comparison is the cornerstone of theoretical progress in psychological research. Common practice overwhelmingly relies on tools that evaluate competing models by balancing in-sample descriptive adequacy against model flexibility, with modern approaches advocating the use of marginal likelihood for hierarchical cognitive models. Cross-validation is another popular approach but its implementation remains out of reach for cognitive models evaluated in a Bayesian hierarchical framework, with the major hurdle being its prohibitive computational cost. To address this issue, we develop novel algorithms that make variational Bayes (VB) inference for hierarchical models feasible and computationally efficient for complex cognitive models of substantive theoretical interest. It is well known that VB produces good estimates of the first moments of the parameters, which gives good predictive densities estimates. We thus develop a novel VB algorithm with Bayesian prediction as a tool to perform model comparison by cross-validation, which we refer to as CVVB. In particular, CVVB can be used as a model screening device that quickly identifies bad models. We demonstrate the utility of CVVB by revisiting a classic question in decision making research: what latent components of processing drive the ubiquitous speed-accuracy tradeoff? We demonstrate that CVVB strongly agrees with model comparison via marginal likelihood, yet achieves the outcome in much less time. Our approach brings cross-validation within reach of theoretically important psychological models, making it feasible to compare much larger families of hierarchically specified cognitive models than has previously been possible. To enhance the applicability of the algorithm, we provide Matlab code together with a user manual so users can easily implement VB and/or CVVB for the models considered in this article and their variants. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Identifying relationships between cognitive processes across tasks, contexts, and time.

It is commonly assumed that a specific testing occasion (task, design, procedure, etc.) provides insights that generalize beyond that occasion. This assumption is infrequently carefully tested in data. We develop a statistically principled method to directly estimate the correlation between latent components of cognitive processing across tasks, contexts, and time. This method simultaneously estimates individual-participant parameters of a cognitive model at each testing occasion, group-level parameters representing across-participant parameter averages and variances, and across-task correlations. The approach provides a natural way to "borrow" strength across testing occasions, which can increase the precision of parameter estimates across all testing occasions. Two example applications demonstrate that the method is practical in standard designs. The examples, and a simulation study, also provide evidence about the reliability and validity of parameter estimates from the linear ballistic accumulator model. We conclude by highlighting the potential of the parameter-correlation method to provide an "assumption-light" tool for estimating the relatedness of cognitive processes across tasks, contexts, and time.

Health care costs of incidental durotomies and postoperative cerebrospinal fluid leaks after elective spinal surgery.

PURPOSE: To explore the additional health care costs of incidental durotomies and cerebrospinal fluid (CSF) leaks after elective surgery for degenerative spinal disorders. METHODS: Prospective, observational single-center study including all patients operated for a degenerative condition of the spine over a 13-month period. Incidental durotomies and cerebrospinal fluid leaks were registered prospectively and a detailed analysis of health care costs of each case was performed. RESULTS: In total 239 patients were included; an incidental durotomy occured in ten patients and a postoperative cerebrospinal fluid leak occured in one patient causing significantly higher hospital costs, as well as significantly longer hospital stay and operation time. While the hospital costs increased by nearly 50% the hospitals reimbursement increased only by 21% and this resulted in an average financial loss of 730 per case. CONCLUSION: Incidental durotomy or postoperative cerebrospinal fluid leak after elective surgery for degenerative spinal disorders causes significantly higher health care costs.

Spectral envelope sensitivity of musical instrument sounds.

It is well known that the spectral envelope is a perceptually salient attribute in musical instrument timbre perception. While a number of studies have explored discrimination thresholds for changes to the spectral envelope, the question of how sensitivity varies as a function of center frequency and bandwidth for musical instruments has yet to be addressed. In this paper a two-alternative forced-choice experiment was conducted to observe perceptual sensitivity to modifications made on trumpet, clarinet and viola sounds. The experiment involved attenuating 14 frequency bands for each instrument in order to determine discrimination thresholds as a function of center frequency and bandwidth. The results indicate that perceptual sensitivity is governed by the first few harmonics and sensitivity does not improve when extending the bandwidth any higher. However, sensitivity was found to decrease if changes were made only to the higher frequencies and continued to decrease as the distorted bandwidth was widened. The results are analyzed and discussed with respect to two other spectral envelope discrimination studies in the literature as well as what is predicted from a psychoacoustic model.