This page aims at presenting my research interests (past and future) in more details.

I have always been fascinated by time (physical and subjective) and how we can perceive and conceptualize something so elusive, and yet essential to successful interaction with the environment.

I defended my PhD in May 2022, during which my work focused on the representation of temporal order. Drawing upon theoretical frameworks such as those of neural reuse and correlational learning (Hebbian and anti-hebbian), I explored the functional role of the sensorimotor system in representing temporal order, moving beyond the idea of a purely epiphenomenon. To address this question, I developed, programmed, and conducted several innovative experimental protocols that combined behavioral measures, such as movement initiation times, with techniques like mouse tracking and eye-tracking. The lockdowns during the COVID-19 pushed me to adapt some of my protocols and conduct large-scale online studies, aggregating data from over a thousand participants. Through these experiences, I honed strong empirical, technical and statistical skills (e.g., linear mixed-effects regression models and Bayesian modeling in R). Overall, results of my PhD suggests that the sensorimotor system plays a key role for the processing of temporal order.

To complement the behavioural work I have already conducted, I am now developing further my neuroscientific skills (e.g., EEG, machine learning) as a postdoctoral researcher involved in the EXPERIENCE Project, supervised by Virginie van Wassenhove at Neurospin. In my current research, I explore how environmental size influences subjective duration, combining virtual reality and EEG to study the brain’s electrophysiological correlates. In a related project, we are working on mapping the geometry of duration representations by integrating behavioral data with EEG recordings and aligning these representations across individuals using unsupervised methods from optimal transport. We gather subjective similarity judgements and EEG data to generate representational dissimilarity matrices, which are then projected into a multi-dimensional conceptual space through multidimensional scaling. This approach produces individual embeddings that reflect both subjective and neural similarity structures for durations.

Besides my research-focused training, I am also a qualified neuropsychologist. Accordingly, in the future, I would like to investigate time cognition both in typically and atypically developing individuals (especially in Parkinson’s disease, schizophrenia, and ADHD).

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Camille Grasso

Neuropsychologist & Researcher