Solving the ‘Two Times Problem’ With an Information Gathering and Utilizing System (IGUS)

There is a long standing ‘two times problem’ in that a satisfactory reconciliation between the time of physics and that of psychology has not been realized. A partial solution to the past/present/future phenomenon has been successfully given by the Hartle information gathering and processing system (IGUS) view. That model IGUS robot is enhanced here for the entire ‘two times problem’ to deal with not only the temporal experiences of the flow of time but also those of manifest time. A dualistic robot is proposed which has a veridical system of temporal experiences that are compatible with various spacetime cosmologies. It also has an illusory system of corresponding temporal experiences. This dualistic IGUS robot was made possible by discovering temporal experience within the brain that correspond to those of physics. The dualistic theory suggests that the veridical system, as a result of evolution, begets the illusory system to enhance behavioral adaptation. Thus, there is just one fundamental physical time which the brain does, indeed, possess and then enhances with illusory counterparts. Therefore, there should no longer be a need to reify illusory temporal experiences as modern spacetime cosmologies tend to do. Physical time already resides within human time.

Distance Traveled in Times of Pandemic: An Endogenous Switching Regression Approach

This paper studies the change in the distance traveled by domestic tourists considering the pre- and post-pandemic outbreak summer periods of 2019 and 2020. Using representative monthly microdata involving more than 31,000 trips conducted by Spanish residents, we examine the heterogeneity in behavioral adaptation to COVID-19 based on sociodemographic and trip-related characteristics. To account for selection effects and the potential change in the population composition of travelers between the two periods, we estimate an endogenous switching regression that conducts separate regressions for the pre- and post-pandemic periods in a unified econometric framework. Our results point to heterogeneous shifts in the distance traveled by domestic travelers after COVID-19 outbreak per sociodemographic group, with notable differences by travel purpose and lower relevance of traditional determinants like income.

How Can Transactional Semantics Enhance the Commit Rate of Context-aware Service Composition in Advanced Pervasive Systems?

Context-aware composition of services exhibiting transactional properties poses several challenges. A major challenge is the transactional behavior of candidate services which is subject to perpetual change while the composition is running. Compositions of services displaying transactional properties must be dynamically adapted at run time to cope with context fluctuations. By dynamic adaptation, we refer to the ability to alter the composition behavior in response to changes affecting its execution. We focus on changes impacting the successful commit rate of transactional service composition. This has led us to explore the trail of a flexible homeomorphism between alternative behaviors. We propose a behavioral adaptation approach that adjusts the behavior of transactional compositions of services in a proactive and transparent manner. This strategy is based on the Profiled Task Class concept. A service composition generator has also been developed for the performance evaluation of components implementing the behavioral adaptation strategy in order to identify its impact on the commit rate of CATS compositions.

Nonsedated Magnetic Resonance Imaging for Visualization of the Velopharynx in the Pediatric Population

Background Non-sedated MRI is gaining traction in clinical settings for visualization of the velopharynx in children with velopharyngeal insufficiency. However, the behavioral adaptation and training aspects that are essential for successful pediatric MRI have received limited attention. Solution We outline a program of behavioral modifications combined with patient education and provider training that has led to high success rates for non-sedated velopharyngeal MRI in children.

Timing of social feedback shapes observational learning in strategic interaction

Many types of social interaction require the ability to anticipate others' behavior, which is commonly referred to as strategic sophistication. In this context, observational learning can represent a decisive tool for behavioral adaptation. However, little is known on whether and when individuals learn from observation in interactive settings. In the current study, 321 participants played one-shot interactive games and, at a given time along the experiment, they could observe the choices of an overtly efficient player. This social feedback could be provided before or after the participant’s choice in each game. Results reveal that players with a sufficient level of strategic skills increased their level of sophistication only when the social feedback was provided after their choices, whereas they relied on blind imitation when they received feedback before their decision. Conversely, less sophisticated players did not increase their level of sophistication, regardless of the type of social feedback. Our findings disclose the interplay between endogenous and exogenous factors modulating observational learning in strategic interaction.

Dynamic dichotomy of accumbal population activity underlies cocaine sensitization

Locomotor sensitization (LS) is an early behavioral adaptation to addictive drugs, driven by the increase of dopamine in the Nucleus Accumbens (NAc). However, the effect on accumbal population activity remains elusive. Here we used single cell calcium imaging in mice to record the activity of dopamine-1-receptor (D1R) and dopamine-2-receptor (D2R) expressing spiny projection neurons (SPNs) during cocaine LS. Acute exposure to cocaine elevated D1R SPN activity and reduced D2R SPN activity, albeit with high variability between neurons. During LS, the number of D1R and D2R neurons responding in opposite directions increased. Moreover, preventing LS by inhibition of the ERK signaling pathway decreased the number of cocaine responsive D1R SPNs, but had little effect on D2R SPNs. These results indicate that accumbal population dichotomy is dynamic and contains a subgroup of D1R SPNs that eventually drives LS. Insights into the drug-related activity dynamics provides a foundation for understanding the circuit-level addiction pathogenesis.

Para-Aminobenzoic Acid, Calcium, and c-di-GMP Induce Formation of Cohesive, Syp-Polysaccharide-Dependent Biofilms in Vibrio fischeri

Bacteria integrate environmental signals to regulate gene expression and protein production to adapt to their surroundings. One such behavioral adaptation is the formation of a biofilm, which can promote adherence and colonization and provide protection against antimicrobials.

Methods for Robot Behavior Adaptation for Cognitive Neurorehabilitation

An estimated 11% of adults report experiencing some form of cognitive decline, which may be associated with conditions such as stroke or dementia and can impact their memory, cognition, behavior, and physical abilities. While there are no known pharmacological treatments for many of these conditions, behavioral treatments such as cognitive training can prolong the independence of people with cognitive impairments. These treatments teach metacognitive strategies to compensate for memory difficulties in their everyday lives. Personalizing these treatments to suit the preferences and goals of an individual is critical to improving their engagement and sustainment, as well as maximizing the treatment's effectiveness. Robots have great potential to facilitate these training regimens and support people with cognitive impairments, their caregivers, and clinicians. This article examines how robots can adapt their behavior to be personalized to an individual in the context of cognitive neurorehabilitation. We provide an overview of existing robots being used to support neurorehabilitation and identify key principles for working in this space. We then examine state-of-the-art technical approaches for enabling longitudinal behavioral adaptation. To conclude, we discuss our recent work on enabling social robots to automatically adapt their behavior and explore open challenges for longitudinal behavior adaptation. This work will help guide the robotics community as it continues to provide more engaging, effective, and personalized interactions between people and robots. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 5 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Performance Errors Influence Voluntary Task Choices

Humans adjust their behavior after they committed an error, but it is unclear whether and how error commissions influence voluntary task choices. In the present article, we review different accounts on effects of errors in the previous trial (transient error effects) and overall error probabilities (sustained error effects) on behavioral adaptation. Based on this review, we derived five statistical models how errors might influence voluntary task choices. We analyzed the data of three experiments in which participants voluntarily selected one of two tasks before each trial whereby task difficulty, and concomitantly error probability, increased successively for the selected/performed tasks. Model comparison suggested that choice behavior was best explained by a combination of error probability of the performed task, error probability of the alternative task, and whether the previous response was correct or incorrect. The results revealed that participants were most likely to switch tasks in situations where the error probability of the performed task was high, the error probability of the alternative task was low, and after an error on the previous trial. We conclude that task selection processes are influenced by transient and sustained error effects.