The present project stems from two fundamental observations concerning economic decision-making: 1) the subjective value of an option is deeply affected by the other options presented simultaneously or in the recent past (context-dependence). 2) the subjective value of an option is different if the relevant information is explicitly communicated or implicitly inferred by trial-and-error (experience/description gap). The goal of the present project is to describe the behavioral and computational mechanisms underlying context-dependent decision-making using a combination of behavioral economics and computational cognitive science. Our hypotheses are that: 1) context-dependence in economic decision-making can be formalized as a range-adaptation process where the subjective value of an outcome is normalized as a function of the minimum and maximum outcomes encountered in a given situation 2) this process is stable across explicit information- and implicit information-based decision.

Accumulating evidence suggests that naturalistic behaviours are driven by interactions between brain regions traditionally studied in isolation. For example, recent work has shown that the cerebellum and the motor cortex, two highly interconnected regions that are each crucial for motor behaviour, coordinate during motor learning and execution. However, progress towards understanding cerebello-cortical interaction has been hindered by the drastically different circuitries of these regions, coupled with the inaccessibility of the deep subcortical pathways connecting them. As a result, it remains unclear how to integrate leading theories of cerebellar and cortical function in motor control. Recent theoretical and experimental evidence has argued that the motor cortex flexibly generates the spatiotemporal patterns necessary for complex movements by exploiting its rich dynamics. This concept is strongly influenced by the emergence of recurrent neural networks (RNNs), a class of AI-inspired models that can be taught to solve a wide range of motor and cognitive tasks via changes in recurrent connectivity. In contrast, the feedforward, evolutionarily-conserved circuitry of the cerebellum is thought to be optimized for learning sensorimotor relationships and error-based adaptation of movements. Yet this classic view of cerebellar motor control is not able to explain recent evidence of reward information in cerebellar Purkinje cells, nor its mysterious role in cognition. I propose to use RNNs to probe how these two distinct neural circuits work together during motor learning. I will extend the traditional neocortical-like RNN architecture to incorporate a cerebellar-like module capturing its divergent-convergent structure and the sparser interregional pathways. I will train this cerebello-cortical RNN (CC-RNN) to perform motor and cognitive tasks using machine learning methods, and will use systems neuroscience and statistical learning tools to analyze the resulting learned structural and functional properties. With this approach, I will address four questions that have been challenging to answer with experiments or traditional circuit modeling: 1) how cerebellar and motor cortical representations co-emerge during learning, 2) how cerebellar adaptation reshapes motor representations in the neocortex, 3) the impact of cerebello-cortical scaling on complex behaviours, and 4) the role of cerebellar adaptation in cognition. More broadly, this project will lead to a fuller understanding of how cortical and subcortical regions interact to produce complex behaviours.

The goal of this proposal is not to find a vaccine, it isn’t to find a treatment either. The goal of this proposal is to learn how to deal with an epidemic in the absence of vaccines and treatment. In such circumstances, the only lever that is left for policy makers is to act on citizens’ behavior. Here, we focus on one particularly crucial behavior: handwashing. Handwashing is a universally acknowledged way of slowing the spread of pathogens, including Covid-19, but injunctions to wash hands are often met with a shrug. The goal of this proposal is to identify behavioral and cognitive obstacles hindering the adoption of healthy handwashing habits. Based on these insights, we will design messages tapping the most promising psychological levers. We will then launch online testing experiments to test the efficacy of various messages on self-reported handwashing intentions and other outcomes of interest. This will put us in a position to launch a large-scale field experiment in 300 schools in the Académie de Versailles, who has agreed to partner with us on this project. Amplifying the national conversation about handwashing is especially timely in the current context, as research has shown that timing sanitary interventions when health issues are salient increases the probability of behavioral shifts. Beyond the present crisis, improving handwashing practices is an important challenge for educators and healthcare professionals. Therefore, the lessons drawn from the current project will be widely applicable both in response to the current crisis and for the future.

The last 10 years have uncovered a treasure-trove of experimental evidence that cardiac signals influence exteroceptive (somatosensory, visual) sensory processing, through both cardiac cycle effects (CCEs) and heartbeat evoked responses (HERs). The interplay between exteroception and interoception is sometimes competitive (i.e., attending the interoceptive or the exteroceptive stream), sometimes integrative (i.e., integration of interoception and exteroception contributes to conscious experience by relating external stimulus to the neural representation of the living organism). The rules governing integration vs. competition are not known. Besides, evidence has remained mostly correlational and the nature of the mechanisms involved is largely unknown. Here, we explore the mechanisms of influence of cardiac inputs on exteroceptive signals, in an integrated approach with an interplay of biologically plausible computational modelling and experiments in humans. In WP1, we will construct a biophysically-based cardio-cortical model, where a cortical mini-column, with ongoing and sensory-evoked activity, is modulated by a dynamic cardiac oscillator (which produces synthetic realistic electrocardiograms). Using this model, we explicitly delineate the mechanisms of this ascending influence. We will validate the model by optimizing the parameters of coupling and the dynamics of the cortical and cardiac modules to fit existing electrocardiogram and intracranial data. In parallel (WP2), we will obtain further EEG data in female and male participants probing the interaction between cardiac and tactile processing with a critical manipulation of self-relevance, a factor that might govern the balance between cardio-tactile competition vs. cardio-tactile integration (WP2). We posit that self-relevance is a combination of exteroceptive stimulus properties and internal state. Stimulus-induced self-relevance is operationalized here as a tactile stimulus delivered with a near sound (more self-relevant), or with a far sound (less self-relevant), and fluctuations in self-related internal state are indexed by source-localized HERs. We hypothesize that HERs in somatosensory cortex compete with the tactile input and slow down tactile reaction times, while HERs in the self-related default mode network combine with the tactile input according to self-relevance as determined by the near or far sound. WP2 will also shed light on the existence or absence of functional links between CCEs and HERs. In WP3, we will expand the model developed in WP1 to confront the data from WP2 to test several mechanistic hypotheses on the interactions between intero- and exetero-ceptive stimuli. The aims are i) to determine the conditions under which interactions between exteroceptive inputs and cardiac cycle and/or HERs occur either in a concerted or independent manner in the primary somatosensory cortex, ii) determine whether and how self-relevance can modulate the balance between integration and competition – does self-relevance exert its influence through neuromodulatory mechanisms directly on the somatosensory cortex or is it routed through a complementary default-mode-network module? and iii) use the model to determine the conditions under which the HERs and CCEs either compete or integrate with the sensory information, with different hypotheses on the implementation of self-relevance. In summary, the project will elaborate neural mechanisms for interoceptive modulation of sensory perception mediated by cardio-cortical coupling. Altogether, this project represents an important step to move the field forward, beyond the accumulation of correlative evidence. It also offers a first step toward a mechanistic understanding of the widely employed but under-specified notion of self-relevance, with potential long-term applications in psychiatry as well as in artificial intelligence and robotics.

Poverty is associated with a wide range of detrimental outcomes ranging from increased rates of teenage pregnancies to diminished investment in health and education. There are of course many causes behind these behaviours but recent work highlights the potential role of psychological changes that arise in response to environmental scarcity. Specifically, harsh environments are known to trigger psychological changes that lead individuals to invest in short-term rather than long-term goals. This shift has important down-the-road consequences on many life decisions, including health, education or even interpersonal trust. However, the exact nature of the cognitive mechanisms that are at play in this association needs to be elucidated. Recent theoretical and empirical work suggest that poverty may compound the over-evaluation of risks. Compared to people living in favourable environments, people living in adversity might indeed suffer a double hit: their life circumstances are objectively unfavourable and they appear to perceive their surroundings as even more negative than they actually are. The goal of this proposal is to systematically assess whether poverty is indeed associated with an increased negativity bias, to pinpoint the cognitive mechanism by which this occurs and to test the extent to which the negativity bias affects inter-temporal preferences for abstract as well as real-life choices linked to health and education. The proposed project is organized in three interrelated axes that will allow us to systematically assess whether and why poverty is associated with cognitive biases that lead individuals to overestimate the existence of threats (Axis 1), whether such misperceptions shift behaviours in predictable ways (Axis 2), and whether experimental manipulations provide evidence of a causal relationship between environmental adversity and these downstream psychological outcomes (Axis 3). By acting as a conduit bringing together cognitive science and economics, this proposal has the potential to make important contributions. Indeed, despite recent interest in the psychology of poverty, a proper identification of the cognitive mechanisms that trigger the behaviours associated with deprivation has lagged behind. This is in part due to the fact that traditional methods in experimental psychology often do not allow researchers to access large and diverse participant pools. Thanks to the complementarity of the team involved in this project, we will be able to apply large-scale testing to maximize variability and to statistically model patterns of variations on multiple cognitive and behavioural traits. Another significant barrier is that projects investigating the psychology of poverty often fall short of providing properly causal explanations. Indeed, unlike many fields in cognitive psychology where participants can be randomized to various experimental conditions in order to test the causal impact of a given factor, individuals can obviously not be randomized to living in favourable or adverse environments. This specific barrier will be lifted by implementing experimental and quasi-experimental manipulations of environmental adversity. Given the domains in which a gradient of economic deprivation has been observed, the potential societal implications are important and should not be based purely on correlatory evidence. Our proposal aims to achieve precisely that goal, by going all the way from a fundamental research question in cognitive psychology to producing causal data that can inform evidence-based policy recommendations.