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model-based reinforcement learning

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https://www.readbyqxmd.com/read/29016461/social-learning-pathways-in-the-relation-between-parental-chronic-pain-and-daily-pain-severity-and-functional-impairment-in-adolescents-with-functional-abdominal-pain
#1
Amanda L Stone, Stephen Bruehl, Craig A Smith, Judy Garber, Lynn S Walker
Having a parent with chronic pain (CP) may confer greater risk for persistence of CP from childhood into young adulthood. Social learning, such as parental modeling and reinforcement, represents one plausible mechanism for the transmission of risk for CP from parents to offspring. Based on a 7-day pain diary in 154 pediatric patients with functional abdominal CP, we tested a model in which parental CP predicted adolescents' daily average CP severity and functional impairment (distal outcomes) via parental modeling of pain behaviors and parental reinforcement of adolescent's pain behaviors (mediators) and adolescents' cognitive appraisals of pain threat (proximal outcome representing adolescents' encoding of parents' behaviors)...
October 6, 2017: Pain
https://www.readbyqxmd.com/read/28968827/learning-similar-actions-by-reinforcement-or-sensory-prediction-errors-rely-on-distinct-physiological-mechanisms
#2
Shintaro Uehara, Firas Mawase, Pablo Celnik
Humans can acquire knowledge of new motor behavior via different forms of learning. The two forms most commonly studied have been the development of internal models based on sensory-prediction errors (error-based learning) and success-based feedback (reinforcement learning). Human behavioral studies suggest these are distinct learning processes, though the neurophysiological mechanisms that are involved have not been characterized. Here, we evaluated physiological markers from the cerebellum and the primary motor cortex (M1) using noninvasive brain stimulations while healthy participants trained finger-reaching tasks...
September 14, 2017: Cerebral Cortex
https://www.readbyqxmd.com/read/28957319/flexibility-to-contingency-changes-distinguishes-habitual-and-goal-directed-strategies-in-humans
#3
Julie J Lee, Mehdi Keramati
Decision-making in the real world presents the challenge of requiring flexible yet prompt behavior, a balance that has been characterized in terms of a trade-off between a slower, prospective goal-directed model-based (MB) strategy and a fast, retrospective habitual model-free (MF) strategy. Theory predicts that flexibility to changes in both reward values and transition contingencies can determine the relative influence of the two systems in reinforcement learning, but few studies have manipulated the latter...
September 2017: PLoS Computational Biology
https://www.readbyqxmd.com/read/28955225/using-the-single-prolonged-stress-model-to-examine-the-pathophysiology-of-ptsd
#4
REVIEW
Rimenez R Souza, Lindsey J Noble, Christa K McIntyre
The endurance of memories of emotionally arousing events serves the adaptive role of minimizing future exposure to danger and reinforcing rewarding behaviors. However, following a traumatic event, a subset of individuals suffers from persistent pathological symptoms such as those seen in posttraumatic stress disorder (PTSD). Despite the availability of pharmacological treatments and evidence-based cognitive behavioral therapy, a considerable number of PTSD patients do not respond to the treatment, or show partial remission and relapse of the symptoms...
2017: Frontiers in Pharmacology
https://www.readbyqxmd.com/read/28945743/predictive-representations-can-link-model-based-reinforcement-learning-to-model-free-mechanisms
#5
Evan M Russek, Ida Momennejad, Matthew M Botvinick, Samuel J Gershman, Nathaniel D Daw
Humans and animals are capable of evaluating actions by considering their long-run future rewards through a process described using model-based reinforcement learning (RL) algorithms. The mechanisms by which neural circuits perform the computations prescribed by model-based RL remain largely unknown; however, multiple lines of evidence suggest that neural circuits supporting model-based behavior are structurally homologous to and overlapping with those thought to carry out model-free temporal difference (TD) learning...
September 2017: PLoS Computational Biology
https://www.readbyqxmd.com/read/28925358/preconditioned-cues-have-no-value
#6
Melissa J Sharpe, Hannah M Batchelor, Geoffrey Schoenbaum
Sensory preconditioning has been used to implicate midbrain dopamine in model-based learning, contradicting the view that dopamine transients reflect model-free value. However, it has been suggested that model-free value might accrue directly to the preconditioned cue through mediated learning. Here, building on previous work (Sadacca et al., 2016), we address this question by testing whether a preconditioned cue will support conditioned reinforcement in rats. We found that while both directly conditioned and second-order conditioned cues supported robust conditioned reinforcement, a preconditioned cue did not...
September 19, 2017: ELife
https://www.readbyqxmd.com/read/28918312/-reinforcement-learning-to-forage-optimally
#7
REVIEW
Nils Kolling, Thomas Akam
Foraging effectively is critical to the survival of all animals and this imperative is thought to have profoundly shaped brain evolution. Decisions made by foraging animals often approximate optimal strategies, but the learning and decision mechanisms generating these choices remain poorly understood. Recent work with laboratory foraging tasks in humans suggest their behaviour is poorly explained by model-free reinforcement learning, with simple heuristic strategies better describing behaviour in some tasks, and in others evidence of prospective prediction of the future state of the environment...
September 14, 2017: Current Opinion in Neurobiology
https://www.readbyqxmd.com/read/28894463/joint-extraction-of-entities-and-relations-using-reinforcement-learning-and-deep-learning
#8
Yuntian Feng, Hongjun Zhang, Wenning Hao, Gang Chen
We use both reinforcement learning and deep learning to simultaneously extract entities and relations from unstructured texts. For reinforcement learning, we model the task as a two-step decision process. Deep learning is used to automatically capture the most important information from unstructured texts, which represent the state in the decision process. By designing the reward function per step, our proposed method can pass the information of entity extraction to relation extraction and obtain feedback in order to extract entities and relations simultaneously...
2017: Computational Intelligence and Neuroscience
https://www.readbyqxmd.com/read/28890391/learned-pleasure-from-eating-an-opportunity-to-promote-healthy-eating-in-children
#9
REVIEW
Lucile Marty, Stéphanie Chambaron, Sophie Nicklaus, Sandrine Monnery-Patris
Across the lifespan, eating is a common everyday act driven by the search for pleasure and reinforced by experienced pleasure. Pleasure is an innate indicator of the satisfaction of physiological needs, in addition to other attributes. Pleasure from eating is also learned and contributes to the development of children's eating habits, which remain mostly stable until adulthood. Based on classical models of determinants of food consumption behaviour, we identified three dimensions of pleasure from eating learned during childhood: 1/the sensory dimension, i...
September 8, 2017: Appetite
https://www.readbyqxmd.com/read/28881969/chromatin-accessibility-prediction-via-convolutional-long-short-term-memory-networks-with-k-mer-embedding
#10
Xu Min, Wanwen Zeng, Ning Chen, Ting Chen, Rui Jiang
Motivation: Experimental techniques for measuring chromatin accessibility are expensive and time consuming, appealing for the development of computational approaches to predict open chromatin regions from DNA sequences. Along this direction, existing methods fall into two classes: one based on handcrafted k -mer features and the other based on convolutional neural networks. Although both categories have shown good performance in specific applications thus far, there still lacks a comprehensive framework to integrate useful k -mer co-occurrence information with recent advances in deep learning...
July 15, 2017: Bioinformatics
https://www.readbyqxmd.com/read/28876358/animal-models-in-biological-and-biomedical-research-experimental-and-ethical-concerns
#11
Monica L Andersen, Lucile M F Winter
Animal models have been used in experimental research to increase human knowledge and contribute to finding solutions to biological and biomedical questions. However, increased concern for the welfare of the animals used, and a growing awareness of the concept of animal rights, has brought a greater focus on the related ethical issues. In this review, we intend to give examples on how animals are used in the health research related to some major health problems in Brazil, as well as to stimulate discussion about the application of ethics in the use of animals in research and education, highlighting the role of National Council for the Control of Animal Experimentation (Conselho Nacional de Controle de Experimentação Animal - CONCEA) in these areas...
September 4, 2017: Anais da Academia Brasileira de Ciências
https://www.readbyqxmd.com/read/28866566/progressive-learning-of-topic-modeling-parameters-a-visual-analytics-framework
#12
Mennatallah El-Assady, Rita Sevastjanova, Fabian Sperrle, Daniel Keim, Christopher Collins
Topic modeling algorithms are widely used to analyze the thematic composition of text corpora but remain difficult to interpret and adjust. Addressing these limitations, we present a modular visual analytics framework, tackling the understandability and adaptability of topic models through a user-driven reinforcement learning process which does not require a deep understanding of the underlying topic modeling algorithms. Given a document corpus, our approach initializes two algorithm configurations based on a parameter space analysis that enhances document separability...
August 29, 2017: IEEE Transactions on Visualization and Computer Graphics
https://www.readbyqxmd.com/read/28838468/computational-dysfunctions-in-anxiety-failure%C3%A2-to%C3%A2-differentiate-signal-from-noise
#13
He Huang, Wesley Thompson, Martin P Paulus
BACKGROUND: Differentiating whether an action leads to an outcome by chance or by an underlying statistical regularity that signals environmental change profoundly affects adaptive behavior. Previous studies have shown that anxious individuals may not appropriately differentiate between these situations. This investigation aims to precisely quantify the process deficit in anxious individuals and determine the degree to which these process dysfunctions are specific to anxiety. METHODS: One hundred twenty-two subjects recruited as part of an ongoing large clinical population study completed a change point detection task...
September 15, 2017: Biological Psychiatry
https://www.readbyqxmd.com/read/28822813/reinforcement-learning-based-control-of-drug-dosing-for-cancer-chemotherapy-treatment
#14
Regina Padmanabhan, Nader Meskin, Wassim M Haddad
The increasing threat of cancer to human life and the improvement in survival rate of this disease due to effective treatment has promoted research in various related fields. This research has shaped clinical trials and emphasized the necessity to properly schedule cancer chemotherapy to ensure effective and safe treatment. Most of the control methodologies proposed for cancer chemotherapy scheduling treatment are model-based. In this paper, a reinforcement learning (RL)-based, model-free method is proposed for the closed-loop control of cancer chemotherapy drug dosing...
August 16, 2017: Mathematical Biosciences
https://www.readbyqxmd.com/read/28813815/how-do-strength-and-coordination-recovery-interact-after-stroke-a-computational-model-for-informing-robotic-training
#15
Sumner L Norman, Joan Lobo-Prat, David J Reinkensmeyer
Robotic devices can train strength, coordination, or a combination of both. If a robotic device focuses on coordination, what happens to strength recovery, and vice versa? Understanding this interaction could help optimize robotic training. We developed a computational neurorehabilitation model to gain insight into the interaction between strength and coordination recovery after stroke. In the model, the motor system recovers by optimizing the activity of residual corticospinal cells (focally connected, excitatory and inhibitory) and reticulospinal cells (diffusely connected and excitatory) to achieve a motor task...
July 2017: IEEE ... International Conference on Rehabilitation Robotics: [proceedings]
https://www.readbyqxmd.com/read/28792571/-improving-population-mental-health-by-integrating-mental-health-care-into-primary-care
#16
Matthew Menear, Michel Gilbert, Marie-Josée Fleury
Objective The objectives of this review were to identify and compare major international initiatives aiming to integrate mental health services in primary care and to summarize the lessons learned for similar integration efforts in the province of Quebec, Canada.Methods We conducted a narrative review of the literature guided by a conceptual framework drawn from the literature on integrated care. We identified relevant initiatives to support primary mental health care integration through Pubmed searches and through previous systematic reviews on this topic...
2017: Santé Mentale Au Québec
https://www.readbyqxmd.com/read/28792570/-the-global-model-of-public-mental-health-and-recovery-mentors
#17
Jean-François Pelletier, Émilie Auclair
Objectives The aim of this paper is to revisit the Global Model of Public Mental Health (GMPMH) in light of the 4th Civic Forum. Recovery mentors of the University of Recovery chaired this public event, which was held in East-end Montreal, Canada, in 2016. The University of Recovery is a concept of co-learning among its members.Methods Being able to refer to international conventions and human rights standards is a key component of a genuine global approach that is supportive of individuals and communities in their quest for recovery and full citizenship...
2017: Santé Mentale Au Québec
https://www.readbyqxmd.com/read/28790900/maladaptive-decision-making-in-adults-with-a-history-of-adolescent-alcohol-use-in-a-preclinical-model-is-attributable-to-the-compromised-assignment-of-incentive-value-during-stimulus-reward-learning
#18
Lauren C Kruse, Abigail G Schindler, Rapheal G Williams, Sophia J Weber, Jeremy J Clark
According to recent WHO reports, alcohol remains the number one substance used and abused by adolescents, despite public health efforts to curb its use. Adolescence is a critical period of biological maturation where brain development, particularly the mesocorticolimbic dopamine system, undergoes substantial remodeling. These circuits are implicated in complex decision making, incentive learning and reinforcement during substance use and abuse. An appealing theoretical approach has been to suggest that alcohol alters the normal development of these processes to promote deficits in reinforcement learning and decision making, which together make individuals vulnerable to developing substance use disorders in adulthood...
2017: Frontiers in Behavioral Neuroscience
https://www.readbyqxmd.com/read/28759606/spaced-education-in-medical-residents-an-electronic-intervention-to-improve-competency-and-retention-of-medical-knowledge
#19
Jason Matos, Camille R Petri, Kenneth J Mukamal, Anita Vanka
BACKGROUND: Spaced education is a novel method that improves medical education through online repetition of core principles often paired with multiple-choice questions. This model is a proven teaching tool for medical students, but its effect on resident learning is less established. We hypothesized that repetition of key clinical concepts in a "Clinical Pearls" format would improve knowledge retention in medical residents. METHODS: This study investigated spaced education with particular emphasis on using a novel, email-based reinforcement program, and a randomized, self-matched design, in which residents were quizzed on medical knowledge that was either reinforced or not with electronically-administered spaced education...
2017: PloS One
https://www.readbyqxmd.com/read/28755695/preimaginal-exposure-to-azadirachtin-affects-food-selection-and-digestive-enzymes-in-adults-of-drosophila-melanogaster-diptera-drosophilidae
#20
Samira Kilani-Morakchi, Radia Bezzar-Bendjazia, Maroua Ferdenache, Nadia Aribi
Among the plant derived product, azadirachtin, a neem-based insecticide, is exceptional in having a broad range of bioactivity including toxicity, growth, development and reproduction effects, repellency and antifeedancy. If considerable progress on the physiological and biological activities and agricultural application of azadirachtin has been achieved, its exact mechanism of action remains uncertain. In this study, we aimed at assessing the lethal and sublethal behavioral and physiological effects of azadirachtin on Drosophila melanogaster Meigen, 1830 (Diptera: Drosophilidae) as biological model...
August 2017: Pesticide Biochemistry and Physiology
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