Use Of Past Experiences Research Articles

Aberrant Neural Response to Social Exclusion Without Significantly Greater Distress in Youth With Bipolar Disorder: Preliminary Findings.

BackgroundLittle is known about the effects of social exclusion on youth with bipolar disorder (BD). Understanding these effects and the functional neural correlates of social exclusion in youth with BD may establish differences from healthy youth and help identify areas of intervention.MethodsWe investigated brain function in 19 youth with BD and 14 age and gender matched healthy control (HC) participants while performing Cyberball, an fMRI social exclusion task. Whole brain activation, region-of-interest, and functional connectivity were compared between groups and examined with behavioral measures.ResultsCompared with the HC group, youth with BD exhibited greater activation in the left fusiform gyrus (FFG) during social exclusion. Functional connectivity between the left FFG and the posterior cingulate/precuneus was significantly greater in the HC compared with the BD group. For the HC group only, age and subjective distress during Cyberball significantly predicted mean FFG activation. No significant differences in distress during social exclusion were found between groups.ConclusionAlthough preliminary due to small sample size, these data suggest that youth with BD process social exclusion in a manner that focuses on basic visual information while healthy youth make use of past experiences to interpret current social encounters. This difference may account for the social cognitive issues experienced by youth with BD, which can lead to more severe anxiety and mood symptoms.

Coping and adaptation to dementia family caregiving: A pilot study

Family caregivers of Black older adults with dementia are at risk for cognitive decline and premature death. Reducing this risk and filling the void of culturally responsive interventions for caregivers requires the development of participant informed models of care that promote group strengths such as effective coping. In this pilot study, Black family caregivers (n=30) completed a survey comprised of a demographic questionnaire, various measures of function, self-efficacy, social support, and coping. Study findings point to a well-educated population with underlying health concerns such as obesity, hypertension, and diabetes that may be complicated by caregiving stress. Common coping strategies used by participants included spiritual coping (80%), use of past experiences (80%), and information gathering (75%). Clinicians can support dementia family caregivers by promoting spiritual coping and self-care, as well as providing reference resources about respite and managing challenging behaviors. Power analysis suggests a future sample size of 385.

Excitation and inhibition in anterior cingulate predict use of past experiences.

Dorsal anterior cingulate cortex (dACC) mediates updating and maintenance of cognitive models of the world used to drive adaptive reward-guided behavior. We investigated the neurochemical underpinnings of this process. We used magnetic resonance spectroscopy in humans, to measure levels of glutamate and GABA in dACC. We examined their relationship to neural signals in dACC, measured with fMRI, and cognitive task performance. Both inhibitory and excitatory neurotransmitters in dACC were predictive of the strength of neural signals in dACC and behavioral adaptation. Glutamate levels were correlated, first, with stronger neural activity representing information to be learnt about the tasks' costs and benefits and, second, greater use of this information in the guidance of behavior. GABA levels were negatively correlated with the same neural signals and the same indices of behavioral influence. Our results suggest that glutamate and GABA in dACC affect the encoding and use of past experiences to guide behavior.

A priori-knowledge/actor-critic reinforcement learning architecture for computing the mean–variance customer portfolio: The case of bank marketing campaigns

In this paper we propose a novel recurrent reinforcement learning approach for controllable Markov chains that adjusts its policies according to a preprocessing and an actor-critic architecture. The preprocessing is proposed when learning a new task is needed from reinforcement based on a priori knowledge, in order to decrease computation time and not explore and not learn everything from scratch. The actor-critic architecture is based on an iterated quadratic/Lagrange programming maximization algorithm for computing the optimal strategies of the mean–variance customer portfolio. This process can be viewed as a specific form of asynchronous value iteration with optimized computational properties. The use of only the value-maximizing action at each state is unlikely in practice. Then, a specific selection of policies is used to ensure convergence. The reinforcement model proposed predicts a learning process that takes the risk of the customer portfolio into account. The resulting policies dynamically optimize the customer portfolio. We propose to apply three different learning rules, based on the transition matrices, the utilities and the costs, to estimate the objective function for the current policies. In particular, the learning rule related to estimate the real costs imposes restrictions over the formulation of the portfolio: costs cannot be underestimated or overestimated. The learning rules allow the process to make use of past experiences and decide on future actions to take in or around a given state of the Markov chain. We provide implementation details of the learning process and the complete algorithm. In addition, we illustrate our approach with a bank marketing application example for showing the viability of the model for solving realistic problems.

Remembering the Past to Imagine the Future: A Cognitive Neuroscience Perspective

A function of memory that has been overlooked until recently concerns its role in allowing individuals to imagine or simulate possible future events. However, a growing number of recent studies show that imagining possible future events depends on much of the same cognitive and neural machinery as does remembering past events. This linkage has potentially important implications for understanding decision-making and performance under stress, which may impair the ability to make use of past experiences to simulate or predict upcoming events. This article considers recent neuroimaging, neuropsychological, and cognitive studies that reveal shared processes underlying remembering the past and imagining the future.

Construction of Health Indices Using Paired Comparisons

The paper discusses, by making use of past experiences in the area, the main issues and the methodology of developing a health status instrument for a developing country from a well-established instrument. The use of Thurstone's model of paired comparisons in evaluating the relative importance of health symptoms has been reviewed and some alternative models, i.e., Linear, Exponential, and Information, are proposed. By applying the models to the health data of Chinese elderly persons, the three models have been demonstrated to be able to produce some valid and responsive health scores.

A study of the use of past experiences in clinical decision making in emergency situations

Making decisions to call emergency assistance to patients is an important dimension of nursing practice. Most usually these decision making situations are uncertain and it is expected nurses rely on past clinical experiences. This study, approved by the ethics committees of both a university and an area health service, aimed to describe nurses’ reliance on past experiences and identify associated judgement strategies (heuristics). Thirty-two registered nurses with five or more years experience were interviewed. Main findings were: nurses did use their past experiences and these experiences were used in the form of the three ‘classic’ heuristics, representativeness, availability and anchoring and adjustment. It can be concluded past experiences are intrinsic to decision making and this has implications for both the clinical components of nursing educational programs and staffing allocations made by administrators. Some nurses, however, did not include referral to past experiences in their decision-making accounts which may be a limitation of the study design.

Development of a Case-Based System for the Supervision of an Activated Sludge Process

The development of a case-based reasoning system for the supervision of an activated sludge process is presented here. The methodology proposed permits the use of past experiences to solve new problems that arise in the process. These experiences are classified as cases or situations. The adaptation of cases and the generation of new cases are used to tune the response of the system and to learn from the new information generated by the process. The case and the case library definition, the initial seed, the search and retrieval process, the adaptation, the action, the evaluation and the learning steps are presented and outlined. The process studied is the wastewater treatment plant of Girona, Spain. Two examples of the response of the system to two different operational situations are presented. The paper also outlines the integration of different fields in a multidisciplinary approach as the most optimal solution to ensure the successful control and supervision of complex processes like the activated sludge process. With this aim the integration of an array of specific supervisory intelligent systems (for the logical analysis and reasoning) and numerical computations for detailed engineering is suggested.