Sixth Symposium on Biology of Decision - Making May 25 - 27 , 2016 , ICM - ENS , Paris , France

Neural firing rates in the macaque lateral intraparietal (LIP) cortex exhibit gradual "ramping" that is commonly believed to reflect the accumulation of sensory evidence during decision-making. However, ramping that appears in trial-averaged responses does not necessarily indicate that the spike rate ramps on single trials; a ramping average rate could also arise from instantaneous steps that occur at different times on each trial. In this talk, I will describe an approach to this problem based on explicit statistical latent-dynamical models of spike trains. We analyzed LIP spike responses using spike train models with: (1) ramping "accumulation-to-bound" dynamics; and (2) discrete "stepping" or "switching" dynamics. Surprisingly, we found that three quarters of choice-selective neurons in LIP are better explained by a model with stepping dynamics. We show that the stepping model provides an accurate description of LIP spike trains, allows for accurate decoding of decisions, and reveals latent structure that is hidden by conventional stimulus-aligned analyses. Finally, I will discuss more recent insights into the coding of decisions using simultaneous multi-neuron recording in areas MT and LIP during decision formation. Mapping the dynamic properties of confidence Timothy J. Pleskac, Shuli Yu, and Peter D. Kvam Max Planck Institute for Human Development & Michigan State University How confident are you in your choice? Such a simple question for people to answer. Yet, modeling how people answer that question has proven challenging. Part of the challenge has been that it has been unclear what information is used to make a choice and what information is used to make a confidence judgment. Another part of the reason is that confidence is conceptualized as a static variable that does not change over time. In this talk, I will review recent empirical work from my group addressing both of these challenges. In the first part of the talk, I will show that choice and confidence are based on the same evidence, but in contrast to recent neuro-computational models of confidence this evidence does not conform to what would be expected if the evidence reflected the likelihood of the data for the given hypotheses (i.e., the evidence accumulation process does not conform to a Bayesian optimal process). Instead for both choices and confidence people over-emphasize the strength of the information relative to the weight. Importantly though the confidence people express in their choice is not a simple snapshot of the accumulated evidence at the time of a choice. Instead, in the second part of my talk, I will map the dynamics of confidence as it changes over even very brief periods of time. I will show that part of its dynamic nature is due to the contribution of post decisional processing of evidence. But, that is not the entire explanation. Its dynamics are also due to its reflection of other aspects including the feedback people are given as well as new incoming information. Together these results support an overall hypothesis that choice and confidence are the product of the same evidence accumulation process. Understanding this interrelationship can help us not only understand the cognitive and neural processes of evidence accumulation, but also understand how and why and when people are accurate and inaccurate in their choices and judgment they make in the world. Evolutionary economics: Decision-making under uncertainty in chimpanzees, bonobos, and humans Alexandra G. Rosati Department of Human Evolutionary Biology Harvard University Human decision-making is marked by systematic biases, but the origin of these biases is unclear. They may stem from our species’ unique cultural experiences with money, markets, and exchange—or they maybe be shaped by biological dispositions that are shared with other species. Comparative studies of decision-making in our closest living relatives—chimpanzees (Pan troglodytes) and bonobos (Pan paniscus)—are critical to disentangle the roots of human economic behavior. I will present evidence that nonhuman apes exhibit many human-like biases when faced with foraging decisions, including their responses to risk (variability in payoffs), ambiguity (lack of knowledge about payoff probabilities), and framing (identical outcomes presented as a loss versus a gain). However, human decision-making is also modulated by reward currency: people respond differently to choices about evolutionarily-novel rewards such as money, compared to choices about biologically-central rewards such as food. Together, this indicates that human economic behavior has evolutionary roots as far back as the last common ancestor with nonhuman apes, but humans may also have specialized psychological skills for thinking about novel abstract rewards. A computational and neural model of momentary subjective well-being Robb B Rutledge, Archy O de Berker, Svenja Espenhahn, Nikolina Skandali, Peter Dayan, Raymond J Dolan University College London The subjective well-being or happiness of individuals is an important metric for societies, but we know little about how the cumulative influence of daily life events are aggregated into subjective feelings. Using computational modeling, I show that momentary happiness in a decision-making task is explained not by task earnings, but by the combined influence of past rewards and expectations. The robustness of this account was evident in a large-scale smartphone-based replication. I use a combination of neuroimaging and pharmacology to investigate the neural basis of mood dynamics, finding that it relates to neural responses in the striatum and to dopamine. I then show that this computational approach can be used to investigate the link between mood and behavior. Neural circuits associated with behavioral flexibility in humans and macaques Jérôme Sallet University of Oxford The human prefrontal cortex has been associated with the most sophisticated aspects of cognition, including those that are thought to be especially refined in humans. First of all I will first present data obtained using diffusion-weighted magnetic resonance imaging (DWMRI) and functional MRI (fMRI) in humans and macaques to infer and compare the organization of prefrontal cortex in the two species. Secondly I will focus on structural and functional changes associated with learning rules in macaques. In discrimination reversal (DisRev) learning tasks animals learn that one choice leads to reward while another does not. Animals also learn that when the reward assignments are switched, the previously unrewarded choice has become the one followed by reward. Behavioural flexibility in DisRev has often been thought to rely on a brain circuit centered on the orbitofrontal cortex (OFC). This view has been challenged because fiber-sparing lesions do not impair discrimination reversal learning in macaques. On the basis of longitudinal changes in grey matter and activity coupling during DisRev training, we identified a neural network associated with behavioral flexibility The role of brain bioenergetics on the effects of stress and anxiety in coping behaviors Carmen Sandi. Brain Mind Institute, Ecole Polytechnique Federale de Lausanne (EPFL), Switzerland. Stress and anxiety are strong modulators of behavior and decision-making. Importantly, individual differences in stress effects are largely related to the personality trait anxiety. I will present our recent work implicating mitochondrial function in the nucleus accumbens in coping behaviors, including the establishment of social hierarchy, and its critical involvement in the low social competitiveness associated with high trait anxiety. I will also discuss recent evidence implicating the accumbal dopaminergic system in the modulation of social competitiveness and accumbal bioenergetics by acute stress or benzodiazepine treatment. Dynamic tracking of social relationships in the human brain