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https://www.readbyqxmd.com/read/28822813/reinforcement-learning-based-control-of-drug-dosing-for-cancer-chemotherapy-treatment
#1
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
#2
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
#3
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
#4
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
#5
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
#6
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
#7
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
https://www.readbyqxmd.com/read/28753016/high-throughput-metabolomics-for-discovering-potential-metabolite-biomarkers-and-metabolic-mechanism-from-the-appswe-ps1de9-transgenic-model-of-alzheimer-s-disease
#8
Jingbo Yu, Ling Kong, Aihua Zhang, Ying Han, Zhidong Liu, Hui Sun, Liang Liu, Xijun Wang
Alzheimer's disease (AD), a neurodegenerative disorder, is the major form of dementia. As AD is an irreversible disease, it is necessary to focus on earlier intervention. However, the potential biomarkers of preclinical AD are still not clear. In this study, urinary metabolomics based on ultra-high-performance liquid chromatography coupled with quadruple time-of-flight mass spectrometry was performed for delineating the metabolic changes and potential early biomarkers in APPswe/PS1dE9 (APP/PS1) transgenic mice...
August 16, 2017: Journal of Proteome Research
https://www.readbyqxmd.com/read/28746138/faculty-resident-co-learning-a-longitudinal-exploration-of-an-innovative-model-for-faculty-development-in-quality-improvement
#9
Brian M Wong, Joanne Goldman, Jeannette M Goguen, Christian Base, Leahora Rotteau, Elaine Van Melle, Ayelet Kuper, Kaveh G Shojania
PURPOSE: To examine the effectiveness of co-learning, wherein faculty and trainees learn together, as a novel approach for building quality improvement (QI) faculty capacity. METHOD: From July 2012 through September 2015, the authors conducted 30 semistructured interviews with 23 faculty participants from the Co-Learning QI Curriculum of the Department of Medicine, Faculty of Medicine, University of Toronto, and collected descriptive data on faculty participation and resident evaluations of teaching effectiveness...
August 2017: Academic Medicine: Journal of the Association of American Medical Colleges
https://www.readbyqxmd.com/read/28741627/chronic-exposure-to-methamphetamine-disrupts-reinforcement-based-decision-making-in-rats
#10
Stephanie M Groman, Katherine M Rich, Nathaniel J Smith, Daeyeol Lee, Jane R Taylor
The persistent use of psychostimulant drugs, despite the detrimental outcomes associated with continued drug use, may be due to disruptions in reinforcement-learning processes that enable behavior to remain flexible and goal-directed in dynamic environments. To identify the reinforcement-learning processes that are affected by chronic exposure to the psychostimulant methamphetamine (MA), the current study sought to use computational and biochemical analyses to characterize decision-making processes, assessed by probabilistic reversal learning, in rats before and after they were exposed to an escalating dose regimen of MA (or saline control)...
July 25, 2017: Neuropsychopharmacology: Official Publication of the American College of Neuropsychopharmacology
https://www.readbyqxmd.com/read/28740466/a-tyrosine-hydroxylase-characterization-of-dopaminergic-neurons-in-the-honey-bee-brain
#11
Stevanus R Tedjakumala, Jacques Rouquette, Marie-Laure Boizeau, Karen A Mesce, Lucie Hotier, Isabelle Massou, Martin Giurfa
Dopamine (DA) plays a fundamental role in insect behavior as it acts both as a general modulator of behavior and as a value system in associative learning where it mediates the reinforcing properties of unconditioned stimuli (US). Here we aimed at characterizing the dopaminergic neurons in the central nervous system of the honey bee, an insect that serves as an established model for the study of learning and memory. We used tyrosine hydroxylase (TH) immunoreactivity (ir) to ensure that the neurons detected synthesize DA endogenously...
2017: Frontiers in Systems Neuroscience
https://www.readbyqxmd.com/read/28732231/kernel-dynamic-policy-programming-applicable-reinforcement-learning-to-robot-systems-with-high-dimensional-states
#12
Yunduan Cui, Takamitsu Matsubara, Kenji Sugimoto
We propose a new value function approach for model-free reinforcement learning in Markov decision processes involving high dimensional states that addresses the issues of brittleness and intractable computational complexity, therefore rendering the value function approach based reinforcement learning algorithms applicable to high dimensional systems. Our new algorithm, Kernel Dynamic Policy Programming (KDPP) smoothly updates the value function in accordance to the Kullback-Leibler divergence between current and updated policies...
June 29, 2017: Neural Networks: the Official Journal of the International Neural Network Society
https://www.readbyqxmd.com/read/28731839/cost-benefit-arbitration-between-multiple-reinforcement-learning-systems
#13
Wouter Kool, Samuel J Gershman, Fiery A Cushman
Human behavior is sometimes determined by habit and other times by goal-directed planning. Modern reinforcement-learning theories formalize this distinction as a competition between a computationally cheap but inaccurate model-free system that gives rise to habits and a computationally expensive but accurate model-based system that implements planning. It is unclear, however, how people choose to allocate control between these systems. Here, we propose that arbitration occurs by comparing each system's task-specific costs and benefits...
July 1, 2017: Psychological Science
https://www.readbyqxmd.com/read/28723943/stress-enhances-model-free-reinforcement-learning-only-after-negative-outcome
#14
Heyeon Park, Daeyeol Lee, Jeanyung Chey
Previous studies found that stress shifts behavioral control by promoting habits while decreasing goal-directed behaviors during reward-based decision-making. It is, however, unclear how stress disrupts the relative contribution of the two systems controlling reward-seeking behavior, i.e. model-free (or habit) and model-based (or goal-directed). Here, we investigated whether stress biases the contribution of model-free and model-based reinforcement learning processes differently depending on the valence of outcome, and whether stress alters the learning rate, i...
2017: PloS One
https://www.readbyqxmd.com/read/28719247/telehealth-in-schools-using-a-systematic-educational-model-based-on-fiction-screenplays-interactive-documentaries-and-three-dimensional-computer-graphics
#15
Diogo Julien Miranda, Chao Lung Wen
BACKGROUND: Preliminary studies suggest the need of a global vision in academic reform, leading to education re-invention. This would include problem-based education using transversal topics, developing of thinking skills, social interaction, and information-processing skills. We aimed to develop a new educational model in health with modular components to be broadcast and applied as a tele-education course. MATERIALS AND METHODS: We developed a systematic model based on a "Skills and Goals Matrix" to adapt scientific contents on fictional screenplays, three-dimensional (3D) computer graphics of the human body, and interactive documentaries...
July 18, 2017: Telemedicine Journal and E-health: the Official Journal of the American Telemedicine Association
https://www.readbyqxmd.com/read/28706499/valence-dependent-belief-updating-computational-validation
#16
Bojana Kuzmanovic, Lionel Rigoux
People tend to update beliefs about their future outcomes in a valence-dependent way: they are likely to incorporate good news and to neglect bad news. However, belief formation is a complex process which depends not only on motivational factors such as the desire for favorable conclusions, but also on multiple cognitive variables such as prior beliefs, knowledge about personal vulnerabilities and resources, and the size of the probabilities and estimation errors. Thus, we applied computational modeling in order to test for valence-induced biases in updating while formally controlling for relevant cognitive factors...
2017: Frontiers in Psychology
https://www.readbyqxmd.com/read/28696337/memristive-device-based-learning-for-navigation-in-robots
#17
Mohammad Sarim, Manish Kumar, Rashmi Jha, Ali A Minai
Biomimetic robots have gained attention recently for various applications ranging from resource hunting to search and rescue operations during disasters. Biological species are known to intuitively learn from the environment, gather and process data, and make appropriate decisions. Such sophisticated computing capabilities in robots are difficult to achieve, especially if done in real-time with ultra- low energy consumption. Here, we present a novel memristive device based learning architecture for robots. Two terminal memristive devices with resistive switching of oxide layer are modeled in a crossbar array to develop a neuromorphic platform that can impart active real-time learning capabilities in a robot...
July 11, 2017: Bioinspiration & Biomimetics
https://www.readbyqxmd.com/read/28680395/a-biologically-plausible-architecture-of-the-striatum-to-solve-context-dependent-reinforcement-learning-tasks
#18
Sabyasachi Shivkumar, Vignesh Muralidharan, V Srinivasa Chakravarthy
Basal ganglia circuit is an important subcortical system of the brain thought to be responsible for reward-based learning. Striatum, the largest nucleus of the basal ganglia, serves as an input port that maps cortical information. Microanatomical studies show that the striatum is a mosaic of specialized input-output structures called striosomes and regions of the surrounding matrix called the matrisomes. We have developed a computational model of the striatum using layered self-organizing maps to capture the center-surround structure seen experimentally and explain its functional significance...
2017: Frontiers in Neural Circuits
https://www.readbyqxmd.com/read/28678984/association-of-neural-and-emotional-impacts-of-reward-prediction-errors-with-major-depression
#19
Robb B Rutledge, Michael Moutoussis, Peter Smittenaar, Peter Zeidman, Tanja Taylor, Louise Hrynkiewicz, Jordan Lam, Nikolina Skandali, Jenifer Z Siegel, Olga T Ousdal, Gita Prabhu, Peter Dayan, Peter Fonagy, Raymond J Dolan
Importance: Major depressive disorder (MDD) is associated with deficits in representing reward prediction errors (RPEs), which are the difference between experienced and predicted reward. Reward prediction errors underlie learning of values in reinforcement learning models, are represented by phasic dopamine release, and are known to affect momentary mood. Objective: To combine functional neuroimaging, computational modeling, and smartphone-based large-scale data collection to test, in the absence of learning-related concerns, the hypothesis that depression attenuates the impact of RPEs...
August 1, 2017: JAMA Psychiatry
https://www.readbyqxmd.com/read/28671967/implementation-of-real-time-energy-management-strategy-based-on-reinforcement-learning-for-hybrid-electric-vehicles-and-simulation-validation
#20
Zehui Kong, Yuan Zou, Teng Liu
To further improve the fuel economy of series hybrid electric tracked vehicles, a reinforcement learning (RL)-based real-time energy management strategy is developed in this paper. In order to utilize the statistical characteristics of online driving schedule effectively, a recursive algorithm for the transition probability matrix (TPM) of power-request is derived. The reinforcement learning (RL) is applied to calculate and update the control policy at regular time, adapting to the varying driving conditions...
2017: PloS One
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