1. Introduction 2. Reward-Guided Decision Making 3. Content in the Model 4. How to Deflate a Metarepresentational Reading Proust and Carruthers on metacognitive feelings 5. A Deflationary Treatment of RPEs? 5.1 Dispensing with prediction errors 5.2 What is use of the RPE focused on? 5.3 Alternative explanations—worldly correlates 5.4 Contrast cases 6. Conclusion Appendix: Temporal Difference Learning Algorithms.
According to the reward-prediction error hypothesis of dopamine, the phasic activity of dopaminergic neurons in the midbrain signals a discrepancy between the predicted and currently experienced reward of a particular event. It can be claimed that this hypothesis is deep, elegant and beautiful, representing one of the largest successes of computational neuroscience. This paper examines this claim, making two contributions to existing literature. First, it draws a comprehensive historical account of the main steps that led to the formulation (...) and subsequent success of the RPEH. Second, in light of this historical account, it explains in which sense the RPEH is explanatory and under which conditions it can be justifiably deemed deeper than the incentive salience hypothesis of dopamine, which is arguably the most prominent contemporary alternative to the RPEH. (shrink)
This study investigates the ability of individuals with psychopathy to perform passive avoidance learning and whether this ability is modulated by level of reinforcement/punishment. Nineteen psychopathic and 21 comparison individuals, as defined by the Hare Psychopathy Checklist Revised (Hare, 1991), were given a passive avoidance task with a graded reinforcement schedule. Response to each rewarding number gained a point reward specific to that number (i.e., 1, 700, 1400 or 2000 points). Response to each punishing number lost a point punishment (...) specific to that number (i.e., the loss of 1, 700, 1400 or 2000 points). In line with predictions, individuals with psychopathy made more passive avoidance errors than the comparison individuals. In addition, while the performance of both groups was modulated by level of reward, only the performance of the comparison population was modulated by level of punishment. The results are interpreted with reference to a computational account of the emotional learning impairment in individuals with psychopathy. (shrink)
Bioinformatics – the so-called shotgun marriage between biology and computer science – is an interdiscipline. Despite interdisciplinarity being seen as a virtue, for having the capacity to solve complex problems and foster innovation, it has the potential to place projects and people in anomalous categories. For example, valorised ‘outputs’ in academia are often defined and rewarded by discipline. Bioinformatics, as an interdisciplinary bricolage, incorporates experts from various disciplinary cultures with their own distinct ways of working. Perceived problems of interdisciplinarity include (...) difficulties of making explicit knowledge that is practical, theoretical, or cognitive. But successful interdisciplinary research also depends on an understanding of disciplinary cultures and value systems, often only tacitly understood by members of the communities in question. In bioinformatics, the ‘parent’ disciplines have different value systems; for example, what is considered worthwhile research by computer scientists can be thought of as trivial by biologists, and vice versa. This paper concentrates on the problems of reward and recognition described by scientists working in academic bioinformatics in the United Kingdom. We highlight problems that are a consequence of its cross-cultural make-up, recognising that the mismatches in knowledge in this borderland take place not just at the level of the practical, theoretical, or epistemological, but also at the cultural level too. The trend in big, interdisciplinary science is towards multiple authors on a single paper; in bioinformatics this has created hybrid or fractional scientists who find they are being positioned not just in-between established disciplines but also in-between as middle authors or, worse still, left off papers altogether. (shrink)
Acts of helping others are often based on mixed motivations. Based on this claim, it has been argued that the use of a financial reward to incentivize organ donation is compatible with promoting altruism in organ donation. In its report Human Bodies: Donation for Medicine and Research, the Nuffield Council on Bioethics uses this argument to justify its suggestion to pilot a funeral payment scheme to incentivize people to register for deceased organ donation in the UK. In this article, (...) I cast a sceptical eye on the above Nuffield report's argument that its proposed funeral payment scheme would prompt deceased organ donations that remain altruistic . Specifically, I illustrate how this scheme may prompt various forms of mixed motivations which would not satisfy the report's definition of altruism. Insofar as the scheme produces an expectation of the reward, it stands diametrical to promoting an ‘altruistic perspective’. My minimal goal in this article is to argue that altruism is not motivationally compatible with reward as an incentive for donation. My broader goal is to argue that if a financial reward is used to incentivize organ donation, then we should recognize that the donation system is no longer aiming to promote altruism. Rewarded donation would not be altruistic but it may be ethical given a persistent organ shortage situation. (shrink)
This paper employs a case study from the history of neuroscience—brain reward function—to scrutinize the inductive argument for the so-called 'Heuristic Identity Theory' (HIT). The case fails to support HIT, illustrating why other case studies previously thought to provide empirical support for HIT also fold under scrutiny. After distinguishing two different ways of understanding the types of identity claims presupposed by HIT and considering other conceptual problems, we conclude that HIT is not an alternative to the traditional identity theory (...) so much as a relabeling of previously discussed strategies for mechanistic discovery. (shrink)