Cognition axis themes

The cognition axis focuses on the study of cognitive mechanisms and substrates of cognitive functions, considering their within-individual (developmental perspective) and between-individual dynamics (including their social dimension), their flexibility and plasticity in normal or pathological situations (considering functional adaptations to perturbations and disabilities).

Five research themes will be developed in this axis:

Perception and Action

  •  Models of audio-visual integration and attention deployment in cluttered and interactive environments, with demonstrators using social robotics and cobotics platforms.
  • Novel experimental paradigms relying on process tracing methods (e.g., eye-tracking in dynamic situations where fixations are ill-defined, computer mouse-tracking for digital experiments, or full body movement in performance or education sciences). 
  • Bridging the gap between perceptual decisions (e.g., visual categorization) and action decisions (e.g., reaching behavior) which usually rely on different mechanistic and probabilistic models, combining them into a common mathematical framework of decision-making processes in sensorimotor systems able to adequately fit empirical data (decision patterns, response times distributions, neuroimaging or neurophysiological data).

Language

  • Extended task-related functional connectome of human language applying network theory as a computational tool to structure neurocognitive data. We will enrich the connectome with new data on large developing cohorts in a lifespan perspective, gender and various atypical situations. 
  • Set of linguistic descriptions of spoken and written language at all psycholinguistic levels and across a large variety of contexts for language use (crossing situations and languages/dialects); automatic speech and language processing systems based on both theoretical and technological challenges. 
  • Theoretical and computational framework for speech and language achieved by capitalizing on collected developmental data on speech and language acquisition, in both typical and atypical language development in infants and children, in speech sound disorders, and on computational models of perception and control and deep neural network simulations.
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Memory, executive functions and metacognition

  • Theoretical and computational models of short-term/working memory in a lifespan perspective. Determine factors underpinning modifications of memory, executive functions and metacognition with age and understand variability of modifications.
  • Links between episodic retrieval and spatial processes, according to which, the episodic retrieval is a reconstruction sustained by egocentric updating. Study of the role of metacognition in episodic memory, conceptualized as monitoring and control processes evoked in human learning

Cognitive systems in interaction

  • Virtual or robotic assistants for learning and cognitive remediation, at home or at institutions, using interactive personalized exercises and interfaces, with online analysis of performance.
  • Case studies and validation of education science hypotheses using context-aware-classrooms and learning platforms.
  • Design recommendations to better react to crisis situations at the collective level by selecting and circulating necessary information across computer and human information systems, depending on context.

Social cognition, emotion and motivation

  • Theoretical bases of collective memories, on how they can be constructed, shared and transmitted across individuals and generations. The objective is to understand and alleviate the consequences of traumatic events on individuals. The relationship between functional (e.g., group dynamics) and structural aspects (e.g., cultural artifacts) are simulated with various forms of multi-agent systems. 
  • Validated self-report scales for studying emotion and body regulation across individuals in various cultures (using multi-site international studies) to investigate how interindividual dynamics and norms are influenced by environmental characteristics. We aim at understanding and preventing deficiencies in social interactions, contributing to the health and well-being of individuals. 
  • Artificial intelligence systems designed to prevent the reproduction of human biases (e.g., recruitment or teaching assistants, user profiling, targeted advertising) by studying and modeling self-presentation strategies, stereotype learning, active sampling and active learning mechanisms leading to confirmation bias

Submitted on March 6, 2023

Updated on April 25, 2023