LaPsyDÉ

It takes two to tango: a synergistic approach to human-machine decision making

Artificial Intelligence (AI) holds enormous potential for enhancing human decisions, improving cognitive overload and lowering bias
in high-stakes scenarios. Adoption of AI-based support systems in such applications is however minimal, chiefly due to the difficulty
of assessing their assumptions, limitations and intentions. In order to realise the promise of AI for individuals, society and economy,
people should feel they can trust AIs in terms of reliability, capacity to understand the human’s needs, and guarantees that they are
genuinely aiming at helping them. TANGO will develop the theoretical basis and computational framework for hybrid decision
support systems (HDSS) in which humans and machines are aligned in terms of values and goals, know their respective strengths, and
work together to reach an optimal decision. To this end, TANGO will develop: 1) A cognitive theory of mutual understanding and
hybrid decision making, of intuitive vs deliberative approaches to decision making and of how they affect our trust in human and AI
teammates. 2) Cognition-aware explainable AIs implementing synergistic human-machine interaction, enabling machines to
determine what information a specific decision maker (e.g., layperson vs expert) needs, or does not need, to reach an informed
decision. 3) A “Human-in-the-loop” co-evolution of human decision making and machine learning models building on bi-directional,
explanation-augmented interlocution. The TANGO framework will be evaluated on four high impact use cases, namely supporting: i)
women during pregnancy and postpartum, ii) surgical teams in intraoperative decision making, iii) loan officers and applicants in
credit lending decision processes, and iv) public policy makers in designing incentives and allocating funds. Success in these case
studies will establish TANGO as the framework of reference for developing a new generation of synergistic AI systems, and will
strengthen the leadership of Europe in human-centric AI.

Individual neurophysiological SENSoRY profiles in AUtism

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social communication, restrictive and repetitive behaviors, as well as atypical sensory responses. Notably, aberrancies in sensory processing-circuits during early development could be the stepping-stone to a cascade of cognitive and social deficits, and thus contribute to the (vast) heterogeneity of the ASD condition. The aim of SensAUry is to comprehensively assess and characterize sensory weaknesses (or strengths) in ASD by developing: (i) novel neurophysiological protocols that combine measures at the level of the central as well as the peripheral nervous system across several sensory modalities (i.e., auditory and visual), and across stimuli of various complexity (i.e., social and non-social). These biological markers will be tested in relation to (ii) neuropsychological assessments’ scores, and in the context of (iii) perceptual learning paradigms, to define sub-categories of ASD from a multidimensional perspective. The results of SensAUry will contribute to the evaluation of the functional bioclinical profile of individuals with ASD, increasing our understanding of heterogeneity in autism, and ultimately helping to target care and individualize support for those affected by the disorder.

Myelin implications in executive control in adolescence and adulthood.

During brain development, the myelination process by oligodendrocytes is critical to shape action potential fidelity and neuronal network synchronization. Although myelin is critical for the proper function of neuronal circuits and behaviour, little is known on how myelination shapes complex cognitive processes during development. We hypothesize that myelination is a crucial developmental component for the construction of neuronal network activities leading to complex cognitive processes such as executive control. Specifically, we will perform a cross-species and multi-level analysis to assess the role of myelination on cognitive control in adolescence and adulthood. First, by combining behaviour and in vivo electrophysiology with behaviour in two mouse models displaying global or specific myelin defects, we will study the impact of myelin impairments on cortical oscillations and cognitive control using an intra-/extradimensional (ID/ED) task. Then, we will examine human cognitive control using a comparable ID/ED task analysed with behaviour, in vivo brain imaging and electrophysiology (anatomo-functional connectivity from EEG, diffusion and functional MRI) in adolescent and adult subjects. This will allow us to determine whether increasing myelination from adolescence to adulthood leads to an increased anatomical connectivity, and hence to an increased functional connectivity/integration that in turn enhances cognitive control at a behavioral level. Finally, we will integrate our data in a computational model of learning and cognitive control in both humans and rodents to assess specific and subtle common behaviors that may be influenced by myelination. In summary, we will use a multi-level approach to assess the impact of myelination from the cellular to the behavioural level on executive control.

In France, women represent less than 30% of the population studying or working in physics. This pattern of under-representation can be observed in many similar disciplines (i.e., especially in "STEM" fields: Science, Technology, Engineering and Mathematics) and plays a major role in maintaining wage inequalities between men and women. Part of the reason why women are less inclined to engage in such careers seems to lie in the stereotypical beliefs and representations held about these disciplines. Numerous studies have shown that science-related gender stereotypes affect the expression of performance, the sense of personal efficacy, as well as the propensity to identify with these fields. The PHYSIS project, jointly held by the Paris Center for Cosmological Physics (PCCP) and the LaPsyDÉ, consists in developing an intervention program in high schools to remove the likely psychological barriers to girls’ involvement in science. The team is also interested in how these gender differences are expressed as a function of the students' socio-economic environment.