Behavioral regulation relies on interacting forces and predictive models.

OBJECTIVE: We discuss how our recent neural network model of personality and motivation can explain many aspects of the regulation of behavior. METHOD: Contrary to approaches that focus on a goal-corrected, set-point, and discrepancy-reducing mechanism, we argue that many aspects of regulation can be understood in terms of two other mechanisms. First, many aspects of the stability and coherence of personality, as well as the dynamics of personality, can be understood in terms of the interaction of forces within organized motivational systems, and their interaction with features of the environment and interoceptive states, that identify an individual's current needs. This has been described as a settling point or equilibrium of forces model, rather than a set-point architecture. Second, regulation has been shown to depend also on the use of predictive models of the world, either learned or innate. Such models can be thought of as feedforward models, in contrast to the feedback models characteristic of set-point, goal-corrected systems. RESULTS AND CONCLUSIONS: We describe a neural network model of these processes that simulates the behavior over time and situations of an individual and shows how important regulatory processes can operate through a process of interactive forces and predictive models of the world.

Modeling incentive salience in Pavlovian learning more parsimoniously using a multiple attribute model.

We present a multi-attribute incentive salience (MAIS) model as a computational account of incentive salience in model-based Pavlovian learning. A model of incentive salience as a joint function of reward value and physiological state has been previously proposed by Zhang et al. (2009). In that model, the function takes additive or multiplicative forms depending on whether a preference shifts from positive to negative or vice versa. We demonstrate that arbitrarily varying this function is unnecessary to explain observed data. A multiplicative function is sufficient if one takes into account empirical data suggesting the incentive salience function for an incentive is comprised of multiple physiological signals. We compare our model to the previously proposed model on two datasets. We find the MAIS model predicts the outcomes equally well, fits empirical data describing multiple sensory representations of a single stimulus, better approximates the dual-structure appetitive-aversive nature of the reward system, is compatible with existing knowledge about incentive salience in Pavlovian learning, and better describes revaluation in Pavlovian learning. This model addresses a call (Dayan & Berridge, 2014) for algorithmic and computational models of model-based Pavlovian learning that consistently and fully explain empirical observations. Because a multi-attribute model is relevant even for simple Pavlovian associations, it should be useful in a wide variety of decision-making contexts, including agent modeling and addiction research.

Using Neural Networks as Models of Personality Process: A Tutorial.

This paper presents a tutorial for creating neural network models of personality processes. Such models enable researchers to create explicit models of both personality structure and personality dynamics, and to address issues of recent concern in personality, such as, "If personality is stable, then how is it possible that within subject variability in personality states can be as large as or larger than between subject variability in personality?" or "Is it possible to understand personality dynamics and personality structure within a common framework?" We discuss why one should want to use neural networks, review what a neural network model is, review a previous model we have constructed, discuss how to conceptualize issues in such a way that they can be computationally modeled, show how that conceptualization can be translated into a model, and discuss the utility of such models for understanding personality structure and personality dynamics. To build our model we use a neural network modeling package called emergent that is freely available, and a specific architecture called Leabra to build a runnable model that addresses one of the questions posed above: How can within subject variability in personality related states be as large as between subject variability in personality?

The role of the dorsal anterior insula in sexual risk: Evidence from an erotic Go/NoGo task and real-world risk-taking.

The insula plays an important role in response inhibition. Most relevant here, it has been proposed that the dorsal anterior insular cortex (dAIC) plays a central role in a salience network that is responsible for switching between the default mode network and the executive control network. However, the insula's role in sexually motivated response inhibition has not yet been studied. In this study, eighty-five 18- to 30-year-old sexually active men who have sex with men (MSM) performed an erotic Go/NoGo task while in an MRI scanner. Participants' real-world sexual risk-taking (frequency of condomless anal intercourse over the past 90 days) was then correlated with their neural activity during the task. We found greater activity in bilateral anterior insular cortex (both dorsal and ventral) on contrasts with stronger motivational information (attractive naked male pictures versus pictures of clothed, middle-aged females) and on contrasts requiring greater response inhibition (NoGo versus Go). We also found that activity in the right dAIC was negatively correlated with participants' real-world sexual risk-taking. Our results confirmed the involvement of the insular cortex in motivated response inhibition. Especially, the decreased right dAIC activity may reduce the likelihood that the executive control network will come online when individuals are faced with situations requiring inhibitory control and thus lead them to make more risky choices.

Prefrontal Cortical Activity During the Stroop Task: New Insights into the Why and the Who of Real-World Risky Sexual Behavior.

Background: Research suggests that deficits in both executive functioning and trait impulsivity may play a role in risky sexual behavior. At the neural level, differences in regulation of the prefrontal cortex have been linked to impulsivity, measured neurocognitively and through self-report. The relationship between neurocognitive measures of executive control and trait impulsivity in predicting risky sexual behavior has not been investigated. Purpose: To investigate the relationship between neural functioning during the Stroop task and risky sexual behavior, as well as the effect of individual differences in urgent (positive and negative) impulsivity on this relationship. Methods: A total of 105 sexually active men who have sex with men completed the Stroop task during functional magnetic resonance imaging scanning. They also completed impulsivity inventories and self-reported their risky sexual behavior (events of condomless anal sex in the last 90 days). Results: Risky participants had greater activation than safe participants during the color congruent condition of the Stroop task in anterior cingulate cortex/dorsomedial prefrontal cortex, dorsolateral prefrontal cortex, left frontal pole, and right insula. Across these regions, this neural activation mediated the link between (positive and/or negative) urgent impulsivity and risky sexual behavior. Conclusions: Findings suggest that the brains of men who engage in risky sexual behavior may employ a different distribution of cognitive resources during tasks of executive functioning than men who practice safe sex, and that this may relate to differences in the prefrontal cortical/fronto-insular system responsible for impulse control.

Identity Conflict and Sexual Risk for Black and Latino YMSM.

Young (aged 18-30) Black and Latino men who have sex with men are at a higher risk of contracting HIV than their White counterparts. In order to better understand the unique nature of sexual risk-taking, we examined the extent to which ethnic group, ethnic identity, and sexual pride predicted condomless anal sex with casual partners among 161 young men who have sex with men (YMSM) who identify as Black or Latino. Negative binomial regressions were conducted using a cross-sectional design. Sexual pride was a negative predictor of condomless anal sex across all participants, but this effect was moderated by ethnic exploration and ethnic group; the relationship between sexual pride and condomless anal sex was strengthened by greater ethnic exploration among Latino YMSM, and weakened by greater ethnic exploration among Black YMSM. Implications for intersectional identity, identity conflict, and HIV prevention among young gay men of color are discussed.

Modeling the dynamics of evaluation: a multilevel neural network implementation of the iterative reprocessing model.

We present a neural network implementation of central components of the iterative reprocessing (IR) model. The IR model argues that the evaluation of social stimuli (attitudes, stereotypes) is the result of the IR of stimuli in a hierarchy of neural systems: The evaluation of social stimuli develops and changes over processing. The network has a multilevel, bidirectional feedback evaluation system that integrates initial perceptual processing and later developing semantic processing. The network processes stimuli (e.g., an individual's appearance) over repeated iterations, with increasingly higher levels of semantic processing over time. As a result, the network's evaluations of stimuli evolve. We discuss the implications of the network for a number of different issues involved in attitudes and social evaluation. The success of the network supports the IR model framework and provides new insights into attitude theory.

Correlation of adrenomedullin gene expression in peripheral blood leukocytes with severity of ischemic stroke.

Human adrenomedullin (ADM), a 52-amino acid peptide, belongs to the calcitonin/calcitonin gene-related peptide (CGRP)/amylin peptide family. ADM acts as a multifunctional regulatory peptide and is upregulated in response to hypoxia. Previous microarray studies have found increased ADM gene (ADM) expression in peripheral blood cells of patients with stroke, however, it is unknown if an increased ADM level is correlated with severity of human ischemic stroke. This study investigated ADM expression in peripheral blood leukocytes (PBL) of healthy controls and subjects at day 1, week 1 and week 3 postacute ischemic stroke using rtPCR methodology. We found that ADM expression was significantly upregulated on the first day of stroke compared to the healthy subjects and the disease controls; the levels remained elevated for up to week 3. Further, ADM expression at day 1 was correlated with stroke severity measured by the National Institute of Healthy Stroke Scale (NIHSS), the modified Barthel Index (mBI) and the modified Rankin Scale (mRS). This could indicate that ADM expression level is related to the severity of tissue damage. We suggest that increased ADM expression in PBL after acute ischemic stroke is most likely to indicate that these cells have been subjected to hypoxia and that the magnitude of expression is likely to be related to the volume of hypoxic tissue. Hypoxia can affect lymphocytes function and could affect the immune response to stroke. The correlation of ADM expression level with the measures of stroke severity implicates ADM--a potential blood bio-marker in studies of ischemic stroke.

Development of a multivariate prediction model for antidepressant resistant depression using reward-related predictors.

Introduction: Individuals with depression who do not respond to two or more courses of serotonergic antidepressants tend to have greater deficits in reward processing and greater internalizing symptoms, yet there is no validated self-report method to determine the likelihood of treatment resistance based on these symptom dimensions. Methods: This online case-control study leverages machine learning techniques to identify differences in self-reported anhedonia and internalizing symptom profiles of antidepressant non-responders compared to responders and healthy controls, as an initial proof-of-concept for relating these indicators to medication responsiveness. Random forest classifiers were used to identify a subset from a set of 24 reward predictors that distinguished among serotonergic medication resistant, non-resistant, and non-depressed individuals recruited online (N = 393). Feature selection was implemented to refine model prediction and improve interpretability. Results: Accuracies for full predictor models ranged from .54 to .71, while feature selected models retained 3-5 predictors and generated accuracies of .42 to .70. Several models performed significantly above chance. Sensitivity for non-responders was greatest after feature selection when compared to only responders, reaching .82 with 3 predictors. The predictors retained from feature selection were then explored using factor analysis at the item level and cluster analysis of the full data to determine empirically driven data structures. Discussion: Non-responders displayed 3 distinct symptom profiles along internalizing dimensions of anxiety, anhedonia, motivation, and cognitive function. Results should be replicated in a prospective cohort sample for predictive validity; however, this study demonstrates validity for using a limited anhedonia and internalizing self-report instrument for distinguishing between antidepressant resistant and responsive depression profiles.

Toward a General Framework of Biased Reasoning: Coherence-Based Reasoning.

A considerable amount of experimental research has been devoted to uncovering biased forms of reasoning. Notwithstanding the richness and overall empirical soundness of the bias research, the field can be described as disjointed, incomplete, and undertheorized. In this article, we seek to address this disconnect by offering "coherence-based reasoning" as a parsimonious theoretical framework that explains a sizable number of important deviations from normative forms of reasoning. Represented in connectionist networks and processed through constraint-satisfaction processing, coherence-based reasoning serves as a ubiquitous, essential, and overwhelmingly adaptive apparatus in people's mental toolbox. This adaptive process, however, can readily be overrun by bias when the network is dominated by nodes or links that are incorrect, overweighted, or otherwise nonnormative. We apply this framework to explain a variety of well-established biased forms of reasoning, including confirmation bias, the halo effect, stereotype spillovers, hindsight bias, motivated reasoning, emotion-driven reasoning, ideological reasoning, and more.

Psychological Intimate Partner Violence, Insecure Attachment, and Parental Psychological Control from Adolescence to Emerging Adulthood.

We examine if psychological intimate partner violence (pIPV) is predicted by parental psychological control (PPC) via insecure attachment. Our results analyzing longitudinal data from the Child Development Project show that PPC perceived at age 16 predicts insecure attachment at age 18, which then predicts pIPV at age 24. Moreover, the paths with attachment anxiety are consistently significant while ones with attachment avoidance are not. Further, all the paths are significant regardless of the gender of the adolescents and parents, which indicates that PPC is detrimental regardless of the gender of the adolescents or parents. Lastly, PPC perceived at age 16 does not directly predict pIPV at age 24, which suggests that social learning theory of aggression (Bandura, 1978) may not explain the association from PPC to pIPV. Our results suggest that research and practice would benefit by considering PPC as an antecedent of pIPV via insecure attachment from adolescence to emerging adulthood.

Ischemic stroke and transient ischemic attack after head and neck radiotherapy: a review.

BACKGROUND AND PURPOSE: Cerebrovascular disease can complicate head and neck radiotherapy and result in transient ischemic attack and ischemic stroke. Although the incidence of radiation vasculopathy is predicted to rise with improvements in median cancer survival, the pathogenesis, natural history, and management of the disease are ill defined. METHODS: We examined studies on the epidemiology, imaging, pathogenesis, and management of medium- and large-artery intra- and extra-cranial disease after head and neck radiotherapy. Controlled prospective trials and larger retrospective trials from the last 30 years were prioritized. RESULTS: The relative risk of transient ischemic attack or ischemic stroke is at least doubled by head and neck radiotherapy. Chronic radiation vasculopathy affecting medium and large intra- and extra-cranial arteries is characterized by increasing rates of hemodynamically significant stenosis with time from radiotherapy. Disease expression is the likely consequence of the combined radiation insult to the intima-media (accelerating atherosclerosis) and to the adventitia (injuring the vasa vasorum). Optimal medical treatment is not established. Carotid endarterectomy is confounded by the need to operate across scarred tissue planes, whereas carotid stenting procedures have resulted in high restenosis rates. CONCLUSIONS: Head and neck radiotherapy significantly increases the risk of transient ischemic attack and ischemic stroke. Evidence-based guidelines for the management of asymptomatic and symptomatic (medium- and large-artery) radiation vasculopathy are lacking. Long-term prospective studies remain a priority, as the incidence of the problem is anticipated to rise with improvements in postradiotherapy patient survival.

User-Agent Bond in Generalizable Environments: Long-Term Risk-Reduction via Nudged Virtual Choices.

Avatars or agents are digitized self-representations of a player in mediated environments. While using agents to navigate through mediated environments, players form bonds with their self-agents or characters, a process referred to as identification. Identification can involve automatic, but temporary, self-concept "shifts in implicit self-perceptions" (Klimmt et al., 2010, p. 323) of the media user by adopting or emphasizing the action choices on behalf of the social expectation of the avatar in the mediated environment. In the current study, we test the possibility that users' identification with video game avatars-a bond built between avatars and players- would account for subsequent behavior changes. We did so by using 3-month longitudinal data involving a narratively-based serious game: Socially Optimized Learning in Virtual Environments (SOLVE), a 3D-interactive game designed to reduce risky sexual behaviors among young men who have sex with men (n = 444). Results show that video game identification predicts both the reduction of risky sexual behaviors over time, and reduction in the number of non-primary partners with whom risky sex occurs. And when players identify with the game character, they tend to make healthier choices, which significantly mediates the link between video game identification and reduction of risky behaviors.

The effect of ageing on human lymphocyte subsets: comparison of males and females.

BACKGROUND: There is reported to be a decline in immune function and an alteration in the frequency of circulating lymphocytes with advancing age. There are also differences in ageing and lifespan between males and females. We performed this study to see if there were differences between males and females in the frequency of the different lymphocyte subsets with age. RESULTS: Using flow cytometry we have examined different populations of peripheral blood leukocytes purified from healthy subjects with age ranging from the third to the tenth decade. We used linear regression analysis to determine if there is a linear relationship between age and cell frequencies. For the whole group, we find that with age there is a significant decline in the percentage of naïve T cells and CD8(+) T cells, and an increase in the percentage of effector memory cells, CD4(+)foxp3(+) T cells and NK cells. For all cells where there was an effect of ageing, the slope of the curve was greater for men than for women and this was statistically significant for CD8(+)alphabeta(+) T cells and CD3(+)CD45RA(-)CCR7(-) effector memory cells. There was also a difference for naïve cells but this was not significant. CONCLUSION: The cause of the change in percentage of lymphocyte subsets with age, and the different effects on males and females is not fully understood but warrants further study.

Fatal and non-fatal events within 14 days after early, intensive mobilization post stroke.

OBJECTIVE: This tertiary analysis from AVERT examined fatal and non-fatal Serious Adverse Events (SAEs) at 14 days. METHOD: AVERT was a prospective, parallel group, assessor blinded, randomized international clinical trial comparing mobility training commenced <24 hours post stroke, termed very early mobilization (VEM) to usual care (UC). Primary outcome was assessed at 3 months. Included: Patients with ischaemic and haemorrhagic stroke within 24 hours of onset. Treatment with thrombolytics allowed. Excluded: Patients with severe premorbid disability and/or comorbidities. Interventions continued for 14 days or hospital discharge if less. The primary early safety outcome was fatal SAEs within 14 days. Secondary outcomes were non-fatal SAEs classified as neurologic, immobility-related, and other. Mortality influences were assessed using binary logistic regression adjusted for baseline stroke severity (NIHSS) and age. RESULTS: 2,104 participants were randomized to VEM (n = 1,054) or UC (n = 1,050) with a median age of 72 years (IQR 63-80) and NIHSS 7 (IQR 4-12). By 14 days, 48 had died in VEM, 32 in UC, age and stroke severity adjusted Odds Ratio of 1.76 (95% CI 1.06-2.92, p = 0.029). Stroke progression was more common in VEM. Exploratory subgroup analyses showed higher odds of death in intracerebral haemorrhage and >80 years subgroups, but there was no significant treatment by subgroup interaction. No difference in non-fatal SAEs found. CONCLUSION: While the overall case fatality at 14 days post-stroke was only 3.8%, mortality adjusted for age and stroke severity was increased with high dose, intensive training compared to usual care. Stroke progression was more common in VEM. CLASSIFICATION OF EVIDENCE: This study provides Class I evidence that very early mobilization increases mortality at 14 days post stroke. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry, ACTRN12606000185561.

Immune activation in the peripheral blood of patients with acute ischemic stroke.

Lymphocytes, neutrophils and macrophages are found in the brain in areas of acute ischaemic stroke. There is also evidence of modulation of systemic immune function after stroke, with post-stroke immunosuppression being observed. Because lymphocytes are activated in the peripheral immune compartment, before entry to the target organ, we reasoned that activated lymphocytes would be present in the circulation, prior to entering the brain, in patients after stroke. Because immune responses are controlled by regulatory mechanisms, we also reasoned that the post-stroke immunosuppression would involve T regulatory cells. The aim of the study was to look for evidence of immune activation and alterations in regulatory T cells in the peripheral blood of patients after acute ischaemic stroke, in comparison to age-matched healthy controls and patients with other neurological diseases (OND), and to determine the phenotype of the activated cells. The percentages of total and activated T cells, B cells, monocyte/ macrophages, and NK/NK-T cells were determined by labelling peripheral blood leukocytes with specific cell surface markers and analysis with 4-colour flow cytometry. The percentages of activated T cells and regulatory T cells were significantly increased in patients with ischemic stroke compared to healthy subjects and patients with OND. There was also an increase in the percentage of CCR7+ T cells. There were no significant differences in the activation of other cell types. In conclusion, there is evidence of immune activation and Treg cells in acute ischaemic stroke.

The relationship between social norms and sexual risk-reduction intentions and behavior among men who have sex with men: Findings from an eHealth intervention.

Normative-based research has found that norms are significant predictors of safe sex behavioral intentions and behavior. Research shows that group identity moderates the relationship between norms and intentions/behavior. The present study used the theory of normative social behavior to evaluate whether identification with characters in an HIV-prevention interactive video moderated the relationship between sexual risk-taking norms and risk reduction intentions/behavior. Participants included 540 men between the ages 18 and 30 enrolled in a randomized controlled trial with a 3-month follow-up. We found support for the hypothesized interaction. At low levels of character identification, the negative relationship between sexual risk-taking norms and risk reduction intentions was strong. However, as character identification increased, the link between norms and intentions became weaker. The mean intentions score of high-risk norm participants was elevated to the level reported by low risk norm participants, demonstrating the favorable effect of character identification on narrative persuasion in entertainment-education. The utility of a social norms approach to health behavior change is discussed in the context of eHealth interventions. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Neurocognitive decision-making processes of casual methamphetamine users.

Neuroadaptations caused by chronic methamphetamine (MA) use are likely major contributors to high relapse rate following treatment. Thus, focusing intervention efforts at pre-empting addiction in vulnerable populations, thereby preventing MA-use-induced neurological changes that make recovery so challenging, may prove more effective than targeting chronic users. One approach is studying casual/recreational users, not diagnosed with substance use disorder. This group may be at high risk for addiction due to their experience with MA. On the other hand, they may be resilient against addiction since they were able to maintain casual use over the years and not become addicted. Understanding their neuro-cognitive characteristics during decision-making and risk-taking would help solve this dilemma and, may help identify intervention strategies. Unfortunately, research on neuro-cognitive characteristics of casual MA users is currently lacking. In this work we begin to address this deficit. This study was part of a larger investigation of neural correlates of risky sexual decision-making in men who have sex with men. While undergoing functional magnetic resonance imaging, 31 casual MA users and 66 non-users performed the CUPS task, in which they decided to accept or refuse a series of mixed gambles. Convergent results from whole brain, region of interest and psychophysiological interaction (PPI) analyses are presented. Whole brain analysis identified an amygdala-striatal cluster with weaker activation in casual MA users compared to non-users during decision-making. Activity in that cluster inversely correlated with decisions to gamble: lower activation corresponded to higher risk taking. Using this cluster as a seed in PPI analyses, we identified a wide range of neural network differences between casual MA users and non-users. Parametric whole brain analyses identified clusters in the ventral striatum, posterior insula and precuneus where activations modulated by risk and reward were significantly weaker in casual MA users than in non-users. The striatal cluster identified in these analyses overlapped with the amygdala-striatal cluster. This work identified neural differences in casual MA users' reward processing and outcome learning systems which may underlie their increased real-world risk-taking. It suggests that while making decisions casual MA users focus primarily on potential gain unlike non-users who also take the riskiness of the choice into consideration.

Causal Inference in Generalizable Environments: Systematic Representative Design.

Causal inference and generalizability both matter. Historically, systematic designs emphasize causal inference, while representative designs focus on generalizability. Here, we suggest a transformative synthesis - Systematic Representative Design (SRD) - concurrently enhancing both causal inference and "built-in" generalizability by leveraging today's intelligent agent, virtual environments, and other technologies. In SRD, a "default control group" (DCG) can be created in a virtual environment by representatively sampling from real-world situations. Experimental groups can be built with systematic manipulations onto the DCG base. Applying systematic design features (e.g., random assignment to DCG versus experimental groups) in SRD affords valid causal inferences. After explicating the proposed SRD synthesis, we delineate how the approach concurrently advances generalizability and robustness, cause-effect inference and precision science, a computationally-enabled cumulative psychological science supporting both "bigger theory" and concrete implementations grappling with tough questions (e.g., what is context?) and affording rapidly-scalable interventions for real-world problems.

A general connectionist model of attitude structure and change: the ACS (Attitudes as Constraint Satisfaction) model.

A localist, parallel constraint satisfaction, artificial neural network model is presented that accounts for a broad collection of attitude and attitude-change phenomena. The network represents the attitude object and cognitions and beliefs related to the attitude, as well as how to integrate a persuasive message into this network. Short-term effects are modeled by activation patterns due to parallel constraint satisfaction processes, and long-term effects are modeled by weight changes due to the settling patterns of activation. Phenomena modeled include thought-induced attitude polarization, elaboration and attitude strength, motivated reasoning and social influence, an integrated view of heuristic versus systematic persuasion, and implicit versus explicit attitude change. Results of the simulations are consistent with empirical results. The same set of simple mechanisms is used to model all the phenomena, which allows the model to offer a parsimonious theoretical account of how structure can impact attitude change. This model is compared with previous computational approaches to attitudes, and implications for attitude research are discussed.