Exploratory Search: Information Matters More than Primary Reward

In the study of animal foraging, resource exploitation (prey pursuit, handling, and consumption) has received much more attention than the search or exploratory process that leads predator to potential prey—whatever they are. Yet, in an unpredictable environment, exploration is crucial to optimize resource exploitation, or at least make this latter effective enough, and maintain organisms alive and capable of reproduction in the long term. I argue that environmental exploration requires psychological mechanisms that differ from those of resource exploitation. During exploration, organisms attempt to resolve the uncertainty about reward procurement rather than attempting to obtain reward. Behaviors that do not maximize reward procurement in some experimental designs are often described as suboptimal or even “irrational.” However, these designs might expose organisms to conditions that stimulate exploration more than exploitation. I suggest three general psychological principles assumed to govern environmental exploration, and report experimental evidence that justifies each of them. These principles may help account for behaviors difficult to explain by means of traditional theoretical frameworks

Neuronal and psychological underpinnings of pathological gambling

Like in the case of drugs, gambling hijacks reward circuits in a brain which is not prepared to receive such intense stimulation. Dopamine is normally released in response to reward and uncertainty in order to allow animals to stay alive in their environment – where rewards are relatively unpredictable. In this case, behavior is regulated by environmental feedbacks, leading animals to persevere or to give up. In contrast, drugs provide a direct, intense pharmacological stimulation of the dopamine system that operates independently of environmental feedbacks, and hence causes “motivational runaways”. With respect to gambling, the confined environment experienced by gamblers favors the emergence of excitatory conditioned cues, so that positive feedbacks take over negative feedbacks. Although drugs and gambling may act differently, their abnormal activation of reward circuitry generates an underestimation of negative consequences and promotes the development of addictive/compulsive behavior. In Parkinson’s and Huntington’s disease, dopamine-related therapies may disrupt these feedbacks on dopamine signalling, potentially leading to various addictions, including pathological gambling. The goal of this Research Topic is to further our understanding of the neurobiological mechanisms underlying the development of pathological gambling. This eBook contains a cross-disciplinary collection of research and review articles, ranging in scope from animal behavioral models to human imaging studies

An overview of commonalities in the mechanisms underlying gambling and substance use disorders

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: Recueil de fiches pédagogiques du réseau MAPS

DoctoralLe réseau thématique MAPS «Modélisation multi-Agent appliquée aux Phénomènes Spatialisés » propose depuis 2009 des évènements scientifiques ayant pour but de diffuser les pratiques de modélisations multi-agents au sein des Sciences de l’Homme et de la Société (SHS). Ce collectif pluridisciplinaire de chercheurs, d’enseignants-chercheurs et de doctorants est labellisé en tant que ≪ réseau thématique » par le Réseau National des Systèmes Complexes (GIS RNSC) et bénéficie du soutien du CNRS au titre de la Formation Permanente. Depuis 2009, plusieurs modèles ont été développés au cours d'événements MAPS. Ces modèles ont fait l'objet de fiches pédagogiques détaillées destinées aux communautés éducatives et universitaires et en particulier aux enseignants qui souhaiteraient faire découvrir la modélisation à leurs étudiants, mais aussi à ceux qui envisagent d’approfondir certains aspects avec un public plus averti. Elles sont également destinées à tous les curieux qui souhaiteraient découvrir ce que la modélisation apporte aux SHS, du point de vue heuristique et du point de vue opérationnel. Enfin, elles sont aussi des supports pour toutes les personnes qui souhaiteraient diffuser les réflexions scientifiques sur la modélisation et la simulation qui ont présidé à la rédaction de ces fiches

Does reward unpredictability reflect risk?

Most decisions made in real-life situations are risky because they are associated with possible negative consequences. Current models of decision-making postulate that the occasional, unpredictable absence of reward that may result from free choice is a negative consequence interpreted as risk by organisms in laboratory situations. I argue that such a view is difficult to justify because, in most experimental paradigms, reward omission does not represent a cost for the decision maker. Risk only exists when unpredictability may cause a potential loss of own limited resources, whether energetic, social, financial, and so on. Thus the experimental methodologies used to test humans and non-humans relative to risk-taking seem to be limited to studying the effects of reward uncertainty in the absence of true decision cost. This may have important implications for the conclusions that can be drawn with respect to the neurobehavioural determinants of risk-taking in real-life situations

Loss in risk-taking: Absence of optimal gain or reduction in one’s own resources?

Determining how living beings react to tasks that reflect realistic situations of risk has given rise to a vast literature. However, I argue that the methodologies traditionally used to test humans and nonhumans relative to risk often fail to achieve their goal. When risk is modelled in laboratory, potential decision cost (or potential loss) typically denotes an absence of optimal gain. In contrast, when risk occurs in real-life situations, potential loss denotes the reduction in an individual’s limited resources – whether energetic, social, financial, etc. This conceptual difference about the nature of risk may have important implications for the understanding of the parameters that control risk-taking behaviour

Sensitivity to tactile novelty in the terrestrial isopod, Porcellio scaber

Invertebrates have been studied at biochemical, ecological, and behavioural levels, but current knowledge about the impact that learning may have on behaviour is rather sparse. The present study aimed to examine the sensitivity of isolated rough woodlice (Porcellio scaber Latreille 1804) to the tactile novelty of their environment. A simple way to test this issue was to refer to the place preference paradigm, traditionally used in vertebrates. In Experiment 1, woodlice were placed in a compartment for 30 min in order to assess their ability to develop habituation in the absence of reward. In Experiment 2, woodlice were exposed to a compartment for 20 min (habituation phase) and were then given free choice between that compartment and a novel compartment for 2 min (preference phase). Depending on test conditions, rewards (humidity and/or shelter) were present or absent in the familiar compartment. The familiar and novel compartments differed with respect to the texture of the floor. In Experiment 3, the floor texture was the same in the two compartments in order to control for a novelty effect. The main results indicate that woodlice exhibited increased locomotion time, increased distance travelled, and increased speed in the novel compartment compared to the familiar compartment. There was no preference for either compartment when the floor textures of both were identical

The frame problem in cognitive modeling

peer reviewe

Dopamine, motivation, and the evolutionary significance of gambling-like behaviour

If given a choice between certain and uncertain rewards, animals tend to prefer the uncertain option, even when the net gain is suboptimal. Animals are also more responsive to reward-related cues in uncertain situations. This well-documented phenomenon in many animal species is in opposition to the basic principles of reinforcement as well as the optimal foraging theory, which suggest that animals will prefer the option associated with the highest reward rate. How does the brain code the attractiveness of unreliable/poor reward sources? And how can we interpret this evidence from an adaptive point of view? I argue that unpredictability and deprivation – whether physiological or psychological – enhance motivation to seek valuable stimuli for the same reason: compensating the difficulty an organism has to predict significant objects and events in the environment