The HRL organises a series of monthly seminaries. The series is labeled "nEuro-economics seminar series" because we invite Europe-based early career research to speak about their research in the cross road between neuroscience, psychology and economics. 

COMING SOON

May 20, 2022 at 2:30pm, room Ferdinand BERTHIER (U207)

Veronika Zilker (Max Planck Institute): "Nonlinear Probability Weighting Can Reflect Attentional Biases in Sequential Sampling"

AfficheNonlinear probability weighting allows cumulative prospect theory (CPT) to account for key violations of utility maximization in decision making under risk (e.g., certainty effect, fourfold pattern of risk attitudes). It describes the impact of risky outcomes on preferences in terms of a rank-dependent nonlinear transformation of their objective probabilities. However, it is unclear how specific shapes of the probability weighting function come about on the level of cognitive processing. The attentional Drift Diffusion Model (aDDM) formalizes the finding that attentional biases toward an option can shape preferences within a sequential sampling process. Here I link these two influential frameworks. The aDDM is used to simulate choices between two options while systematically varying the strength of attentional biases to either option. The resulting choices were modeled with CPT. Changes in preference due to attentional biases in the aDDM were reflected in highly systematic signatures in the parameters of CPT’s weighting function (curvature, elevation). These results advance the integration of two prominent computational frameworks for decision making. Moreover, I demonstrate that attentional biases are also empirically linked to patterns in probability weighting as suggested by the simulations, and test whether these effects of attention allocation on probability weighting are causal. Overall, the findings highlight that distortions in probability weighting can arise from simple option-specific attentional biases in information search, and suggest an alternative to common interpretations of weighting-function parameters in terms of probability sensitivity and optimism. They also point to novel, attention-based explanations for empirical phenomena associated with characteristic shapes of CPT’s probability-weighting function (e.g., certainty effect, description–experience gap), and to possible interventions to alleviate common biases in decision making under risk.
 

 

PAST EVENTS

April 21, 2022 at 4:30pm, room Camille Marbo

Christopher Summerfield (University of Oxford): "Learning and generalisation of task knowledge in humans and neural networks"

affiche

There has been a renaissance of interest in connectionist networks as models of biological computation. During sensory perception, deep neural networks learn representations that resemble those in primate neocortex. However, neural networks learn to perform and generalise cognitive tasks in very different ways to people. In my talk, I will explore these differences, and suggest computational adaptations that allow neural networks to learn multiple tasks in series, reconfigure task knowledge from limited data, and generalise knowledge between tasks.

 

 

 

 

 

March 29, 2022 at 11am, ENS, amphitheater Jaurès
Claire Gillan (Trinity College Dublin): "Getting personal with network theory of mental health and illness"

PosterNetwork theory of psychopathology posits that mental health disorders like depression might be better understood as complex systems defined by interacting elements, or ‘symptoms’, like low mood, excessive guilt and insomnia. This challenges the traditional view in psychiatry that disorders themselves are the latent cause of symptoms and offers an explanation as to why psychiatry has failed to find clear neurobiological, genetic, or environmental causes of specific DSM disorders. Though there is much excitement about the potential for network approaches to explain individual differences in clinical presentation, help us understand vulnerability, and potentially tailor treatments, there is snag; almost all of the empirical research supporting network theory rests on between-subject analyses in cross-sectional data. In this talk, I will stress the need for constructing and interrogating personalised within-subject networks to move this field forward. This allows us to ask not whether things like insomnia and guilt correlate across individuals, but how reliably guilt precedes insomnia within a person. Focusing on a core prediction of network theory, that more tightly connected networks of symptoms are associated with vulnerability, severity, and persistence of illness, I will describe some recent efforts in this area using a variety of data sources. These include clinical panel data from >65,000 patients followed through cognitive behavioural therapy, personalised networks constructed from depression-related language in Tweets (N=946), and twice-daily self-reported affect from an experience sampling study (N=208) via the neureka app (www.neureka.ie).

 

February 28, 2020, 2:30pm, ENS, Jaurès building, Langevin room, 24 rue Lhomond, 75005 Paris
Dirk Wulff (CDS, University of Basel, Switzerland): "Strategic exploration and memory representations in decisions from experience"


Computational accounts of decisions from experience often treat the information contained in new experiences as a disposable product. They are used once to update running evaluations of the available options, but once they have served their purpose they are simply discarded. When taken literal, these accounts imply that people should possess no declarative memory of the experiences that they have made. In this talk, I present evidence from a reanalysis of the 1.2 million sampling decisions in our meta-analysis (Wulff et al., 2018) and new experimental data that demonstrates that people indeed possess robust memories of experienced outcomes, as well as their relative frequencies, and that these representations guide strategic exploration.  These findings are difficult to reconcile with popular accounts of decisions from experiences, in particular those building on reinforcement learning models, and highlight the need for incorporating an episodic- or instance-based memory system in accounts of decisions from experience. 

January 31st, 2020, 2:30pm, ENS, Jaurès building, Ribot room, 24 rue Lhomond, 75005 Paris
Valérie Dufour (IPHC, Strasbourg): "Decision making under risk and ambiguity in human and non-human primates"

Decision making under risk is fundamental in humans and other animals. Biologists generally aim at highlighting particular attitudes towards risk (i.e. risk proneness or risk aversion for example) that would reflect naturally selected adaptations to past environmental conditions for a given species. By contrasts with human studies of choice, those studies often fail to consider the interplay between the mechanisms involved in the decision such as the respective role of loss aversion, risk attitudes and probability distortion. In a first part of this talk, I will present data of four ape and two monkey species tested in a food gambling game to uncover the determinants of their gambling decisions. Data were first analysed using CPT and EUT models in an attempt to quantify parameters known to influence decision making in humans. In parallel, we investigated whether some individuals used decisional heuristics to reduce the cost of evaluating odds at each new trial. Data show that several subjects used the Maximax heuristic, focussing on potential gains, while ignoring potential losses. In a second part of this talk, we investigated the response of these species under ambiguous conditions. Subjects were tested in a test very similar to the gambling game but with some information missing. They had no exact knowledge of the odds associated to the outcome of their gambling. Dealing with unpredictability may be more challenging and require more cognitive flexibility. We expected some species to reject ambiguity and/or use even simpler decision rules than under risk. However, under this ambiguous context, individuals gambled as if they had built expectations about the missing information and more so in orangutans, gorillas and chimpanzees. Using decision trees, we could identify each step of the decisional process. Results show that non-human primates can combine several decision rules to make their decision in an unpredictable environment. 


PAST EVENTS

October 15, 2019, 11am, ENS
Yael Niv (Princeton University): "The interaction between mood and reward"


Yael NivA good mood can be a blessing, but persistent bad moods or mood swings are so detrimental to our well-being that they are at the root of many psychiatric disorders. In this talk, I will present a computational model of mood and valuation that suggests that mood and unexpected outcomes (rewards or punishments) influence each other bi-directionally. After showing empirical evidence for both sides of the interaction, I will discuss the theoretical implications of such a positive feedback loop, especially for pathologies of mood instability. Finally, I will suggest that mood is not simply epiphenomonological, but might play a role in tracking global changes in the environment. This is especially useful in environments with dependencies between different states, and across time (momentum). Properly calibrated, mood may therefore allow rapid adaptation to some kinds of change and generalization of learning from one situation to another.

 

 



September 20, 2019, 2:30pm, ENS
Brian Hill (HEC): "Updating Confidence in Beliefs"

BrianHillThis paper develops a belief update rule under ambiguity, motivated by the maxim: in the face of new information, retain those conditional beliefs in which you are more confident, and relinquish only those in which you have less confidence. We provide a preference-based axiomatisation, drawing on the account of confidence in beliefs developed in Hill (2013). The proposed rule constitutes a general framework of which several existing rules for multiple priors (Full Bayesian, Maximum Likelihood) are special cases, but avoids the problems that these rules have with updating on complete ignorance. Moreover, it can handle surprising and null events, such as crises or reasoning in games, recovering traditional approaches, such as conditional probability systems, as special cases.

 

 





May 17, 2019, 2pm, ENS, room Langevin
Aurélien Baillon
(Erasmus School of Economics): "Signal perception and belief updating"

BaillonThis paper introduces a theory of signal perception to study how people update their beliefs. By allowing perceived signals to deviate from actual signals, we identify the probability that people miss or misread signals, giving indexes of conservatism and confirmatory bias. In an experiment, we elicited perceived signals from choices and obtained a structural estimation of the indexes. The subjects were conservative and acted as if they missed 43% of the signals they received. Also they exhibited confirmatory bias by misreading 19% of the signals contradicting their prior beliefs.

 

 

 

 

 



April 19, 2019, 3pm, ENS, room Langevin
Shauna Parkes (Institut de Neurosciences Cognitives et Intégratives d'Aquitaine):
"Neural and psychological bases of goal-directed behaviour in the rat"

Parks

Appropriate decision making is critical for adapting to a changing environment. Every day we must make decisions based on internal goals and the expectation that a given action will lead to goal achievement. Such decisions are experimentally defined as “goal-directed.” Over the years, we have been particularly interested in the neural circuits of incentive learning and memory; that is, the brain regions and circuits that encode and retrieve goal values to guide adaptive choice. Current evidence indicates that interactions between the insular cortex, the striatum and the amygdala are crucial for such incentive learning. Here, I will review evidence from free operant tasks employing causal interventions in rats to outline the distinct involvement of each of these regions, and the neural pathways between these regions, in the mental representation of goal values. I will also share some purely behavioural data examining how context may influence the goal representation as well as the effect of environmental factors such as diet on the balance between actions and habits.



September 12, 2018, 11am, room Langevin
Elliot Ludwig (Warvic Business School - The University of Warwick): "Memory biases in risky decisions from experience"

Elliot Ludvig

May 2d, 2018, 2pm, room Langevin
Eric Schultz (Computational Cognitive Neuroscience Lab & the Data Science Initiative Harvard University): "Exploration and generalization in structured bandits"

Eric Schultz

February 3d, 2017, 11:30am-12:30, room Assia Djebar
Uri Hertz (Univ. College London): "How to influence others and get approval from your granny: The neural computations underlying strategic management of social influence"

Uri Hertz