Axe 1 / Axis 1

Axis 1: Memory and Learning

Within this axis, we will develop a series of research investigations to experimentally study (e.g., via the transposition of laboratory paradigms in virtual environments, and the creation of new VR paradigms), the mechanisms behind explicit and implicit learning, spontaneous episodic memory and memory distortions (Schacter, 2012). In the real-world environment, memory inherently depends on emotion, attention, perception, action and self-relevance at encoding and social context (Hommel, 2004). The view of embodied cognition states that body and mind are two interconnected constructs, which cannot be considered separately because they are deeply influenced by each other (Wilson, 2002; Barsalou, 1999). Without adopting all the radical theoretical assumptions of embodied cognition (Versace et al., 2014), and using multimodal measures, the project will try to understand how and under what conditions these factors are involved in the construction and in the storage and retrieval of true and false memories and memories of different nature. We will use machine learning approach with multilevel measures to predict memory performances.When possible, the experiments will be conducted in school-aged children, adolescents and young and old adults. Thus, we will work on characterizing the developmental (PIs: N. Angeard, I. Jambaqué, S. Pacton) and aging (PIs: A. Baudouin, V. La Corte, P. Narme) mechanisms of memory and on the isolation of factors favoring memorization (e.g., attention, M Sperduti, S Blanchet).

 More precisely, we plan to explore implicit and explicit memory processes (from encoding to long-term recall via explicit and implicit measures collected from classic lab experiments and virtual environments. S. Pacton works to better understand how children learn the spelling of new words (e.g., LABEX EFL, Pacton et al., 2013; 2014), and for instance he will adapt implicit learning study paradigms, such as serial reaction time (SRT), to virtual reality situations, which has never been done to our knowledge.

S. Blanchet & M. Sperduti plan to better understand the links between attention and memory (e.g., dual task paradigm, Posner’s attentional network test, online measures of mindwandering) depending on the types of situations experienced in VR (PhD A Armougum in the context of decision making in the virtual Saint Michel Station, coll. SNCF; PhD P Blondé in the context of episodic encoding). In addition, these aspects will be studied in temporal memory and time-based memory processes (A. Baudouin), in false memory and prospective memory (V. La Corte & P Piolino) and in emotional and social memory (P. Narme & N Angeard).

 We will study the effects of explicit vs implicit embodiment on spatial memory (S Nicolas collaboration with IFSTTAR, PhD S. Lhuillier; PostDoc A Afonso, ANR RASPUTIN) and P. Piolino in long-term episodic memory (PhD P. Blondé, coll. M Sperduti) and on sense of presence and different level of consciousness and emotional states (ANR SUBLIMAE, coll M Sperduti).

 Another innovative research program, will continue to investigate the predictors of creation of episodic autobiographical memory using immersion in virtual reality (IUF Piolino). We will examine the behavioral and neurocognitive signature of the formation and consolidation of incidental memories and predictive models via machine learning approach (PhD K Abichou, coll F Vialatte). We plan to manipulate diverse factors that can modulate personal experiences and context at encoding during immersion in virtual everyday life-like situations and use different retention delay at recall (from 1 day to 6 months). 

 

                       Effects of explicit vs implicit embodiment on memory

 

                                                                                                                                                                         

embodiement
 

        Predictors of the creation and consolidation of episodic autobiographical memory                                                                       
prediction2