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Near-infrared spectroscopy (NIRS) is a noninvasive neuroimaging tool used to measure activation-induced changes in cortical hemoglobin concentration. Using this technique, changes in the optical absorption of light are recorded to estimate changes in oxyhemoglobin and deoxyhemoglobin concentrations resulting from local vascular and metabolic effects during brain activity. NIRS has been successfully applied for early identification of neurodevelopmental and neurodegenerative disorders. Likewise, decreases in olfactory ability indicate similar disorders. High cortical involvement in the olfactory system makes NIRS ideal for in-depth investigation of the olfactory and cognitive systems. Due to growing popularity and potential for enhancing research in both techniques, we aimed to identify activation patterns during olfaction, summarize the locations of hemodynamic change during olfactory stimulation, highlight developmental differences, and outline functional lateralization of olfactory processes in studies using NIRS. We searched Web of Science, PsychInfo, CINAHL, PubMed, and Science Direct for olfactory related studies using NIRS methodology. The literature search generated 578 records and 124 full text articles were reviewed. Thirty-two articles comprising 588 participants from Japan and Europe met eligibility. Olfactory stimulation consistently induces hemodynamic changes in the fronto‐polar (inferior frontal), orbito-frontal, and temporal regions, while trigeminal scents also activate the somatosensory cortices. Healthy individuals showed consistent hemodynamic patterns, and these patterns differed from individuals with anosmia, developmental disorders, cognitive decline, and cognitive load. Our findings suggest that NIRS can be used to investigate olfaction across the lifespan and may have potential as a diagnostic tool. However, longitudinal, well-powered studies are needed to establish disease-specific sensitivity and specificity.

An expanding body of research highlights that a cognitively engaged lifestyle may protect against neurodegeneration in late life (e.g., thereby promoting cognitive reserve). The majority of research in this area uses education as a proxy to investigate the cognitive reserve hypothesis; however, more recent findings suggest that other factors from the lifespan contribute to cognitive reserve. The current study examined whether access to cognitive resources in childhood (e.g., number of books at home) influenced healthy and impaired life expectancies using coordinated analyses of data from eight countries. Multistate survival models examined transitions between healthy, mild, and severely impaired cognitive states and death, which were used to compute life expectancies for individuals with and without impairment. Controlling for age, sex, education, SES, and country, analyses revealed a pattern consistent with the cognitive reserve hypothesis. Specifically, having access to more cognitive resources in childhood was associated with compression of morbidity—longer life expectancy free of impairment and less time spent with cognitive impairment. Cross-country differences in this effect will be discussed. Overall, these findings underscore the importance of childhood cognitive stimulation for cognitive health in later life and emphasize the need for a lifespan-focused approach to studying cognitive reserve.

We present a new verification technique for Promela which exploits state-space symmetries induced by scalarset values used in a model. The technique involves efficiently computing a marker for each state encountered during search. We propose a complete verification method which only partially exploits symmetry, and an approximate verification method which fully exploits symmetry. We describe how symmetry markers can be efficiently computed and integrated into the Spin tool, and provide an empirical evaluation of our technique using the Topspin symmetry reduction package, which shows very good performance results and a high degree of precision for the approximate method (i.e. very few non-symmetric states receive the same marker). We also identify a class of models for which the approximate technique is precise.

We report a case study in automated incremental assertion-based proof checking with PVS. Given an annotated distributed algorithm, our tool ProPar generates the proof obligations for partial correctness, plus a proof script per obligation. ProPar then lets PVS attempt to discharge all obligations by running the proof scripts. The Chang-Roberts algorithm elects a leader on a unidirectional ring with unique identities. With ProPar, we check its correctness with a very high degree of automation: over 90% of the proof obligations is discharged automatically. This case study underlines the feasibility of the approach and is, to the best of our knowledge, the first verification of the Chang-Roberts algorithm for arbitrary ring size in a proof checker.