Pazzaglia, Dube, and Rotello (2013) have provided a lengthy critique of threshold and continuous models of recognition memory. Although the early pages of their article focus mostly on the problems they see with 3 vintage threshold models compared with models from signal detection theory (SDT), it becomes clear rather quickly that Pazzaglia et al. are concerned more generally with problems they see with multinomial processing tree (MPT) models. First, we focus on Pazzaglia et al.'s discussion of the evidence concerning receiver operating characteristics (ROCs) in simple recognition memory, then we consider problems they raise with a subclass of MPT models for more complex recognition memory paradigms, and finally we discuss the difference between scientific models and measurement models in the context of MPT and SDT models in general. We argue that Pazzaglia et al. have not adequately considered the evidence relevant to the viability of the simple threshold models and that they have not adequately represented the issues concerning validating a cognitive measurement model. We further argue that selective influence studies and model flexibility studies are as important as studies showing that a model can fit behavioral data. In particular, we note that despite over a half century of effort, no generally accepted scientific theory of recognition memory has emerged and that it is unlikely to ever emerge with studies using standard behavioral measures. Instead, we assert that useful measurement models of both the SDT and the MPT type have been and should continue to be developed.

This paper provides a critical examination of the current state and future possibility of formal cognitive theory for insight problem solving and its associated "aha!" experience. Insight problems are contrasted with move problems, which have been formally defined and studied extensively by cognitive psychologists since the pioneering work of Alan Newell and Herbert Simon. To facilitate our discussion, a number of classical brainteasers are presented along with their solutions and some conclusions derived from observing the behavior of many students trying to solve them. Some of these problems are interesting in their own right, and many of them have not been discussed before in the psychological literature. The main purpose of presenting the brainteasers is to assist in discussing the status of formal cognitive theory for insight problem solving, which is argued to be considerably weaker than that found in other areas of higher cognition such as human memory, decision-making, categorization, and perception. We discuss theoretical barriers that have plagued the development of successful formal theory for insight problem solving. A few suggestions are made that might serve to advance the field.

Molecular testing for genomic variants is recommended in advanced non-small cell lung cancer (NSCLC). Standard tissue biopsy is sometimes infeasible, procedurally risky, or insufficient in tumor tissue quantity. We present the analytical validation and concordance study of EGFR variants using a new 17-gene liquid biopsy assay (NCT02762877). Of 144 patients enrolled with newly diagnosed or progressive stage IV nonsquamous NSCLC, 140 (97%) had liquid assay results, and 117 (81%) had both EGFR blood and tissue results. Alterations were detected in 58% of liquid samples. Overall tissue-liquid concordance for EGFR alterations was 94.0% (95% CI 88.1%, 97.6%) with positive percent agreement of 76.7% (57.7%, 90.1%) and negative percent agreement of 100% (95.8%, 100%). Concordance for ALK structural variants was 95.7% (90.1%, 98.6%). This assay detected alterations in other therapeutically relevant genes at a rate similar to tissue analysis. These results demonstrate the analytical and clinical validity of this 17-gene assay.

Clinical tests used for psychodiagnostic purposes, such as the well-known Alzheimer's Disease Assessment Scale: Cognitive subscale (ADAS-Cog), include a free-recall task. The free-recall task taps into latent cognitive processes associated with learning and memory components of human cognition, any of which might be impaired with the progression of Alzheimer's disease (AD). A Hidden Markov model of free recall is developed to measure latent cognitive processes used during the free-recall task. In return, these cognitive measurements give us insight into the degree to which normal cognitive functions are differentially impaired by medical conditions, such as AD and related disorders. The model is used to analyze the free-recall data obtained from healthy elderly participants, participants diagnosed as having mild cognitive impairment, and participants diagnosed with early AD. The model is specified hierarchically to handle item differences because of the serial position curve in free recall, as well as within-group individual differences in participants' recall abilities. Bayesian hierarchical inference is used to estimate the model. The model analysis suggests that the impaired patients have the following: (1) long-term memory encoding deficits, (2) short-term memory (STM) retrieval deficits for all but very short time intervals, (3) poorer transfer into long-term memory for items successfully retrieved from STM, and (4) poorer retention of items encoded into long-term memory after longer delays. Yet, impaired patients appear to have no deficit in immediate recall of encoded words in long-term memory or for very short time intervals in STM.

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