Institut Jean Nicod

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I hold a Master’s degree in philosophy (École des Hautes Études en Sciences Sociales (EHESS) and École Normale Supérieure (ENS)) as well as a Master’s degree in anthropology (EHESS). I am currently a doctoral student at Institut Jean Nicod; I am also a visiting student researcher at the Department of Anthropology of Stanford University. My doctoral supervisor is Jérôme Dokic and my work at Stanford is being supervised by Tanya Luhrmann.


Research interests.

• Cognitive science, Cultural psychology, Cognitive science of religion

• Amazonian ethnography, Cognitive anthropology, Experimental anthropology

• Philosophy of mind, Philosophy of perception, Experimental philosophy, Epistemology

• Neurophenomenology, Neuroanthropology


Fields, tools and methods.

My research work combines (1) conceptual analysis (analytic philosophy), (2) theorization based on existing empirical findings (mainly: anthropological, psychological, neuroscientific and biological findings), (3) collection of experimental/psychological data, and, (4) collection of ethnographic data.

My ethnographic fieldwork is located in Shipibo communities of the Middle Ucayali, in the Peruvian Amazon. As yet, I have conducted 4 experiments in that region (two with adults and two with children).


Research project (I): Hallucination, culture and the Bayesian brain.

My current PhD research project consists in exploring the interplay between neurobiology and culture in hallucinogenic experiences. I am especially focusing on experiences induced by serotoninergic hallucinogens, on the one hand, and by anticholinergic hallucinogens, on the other. Looking at cultural uses of these substances, I investigate how rituals and high-level cognitive processes can variably modulate low-level neuropharmacological processes. The anthropological data on which this investigation is based are from all over the world but a strong emphasis is put on Amazonian shamanism and vegetalismo.

The model I am developing is largely influenced by the Bayesian, the predictive coding and the free energy frameworks advocated by neuroscientists such as Karl Friston, Chris Frith and Philip Corlett. Part of my PhD research consists in examining the theoretical consequences of this general Bayesian model of altered consciousness, especially in the fields of philosophy of mind and philosophy of perception. I also explore the implications of this model for the cognitive science of religion and for theories of religious experience.


Research project (II): Animism, essentialism and Bayesian cognition.

In the recent years, animism has become a heated topic among anthropologists. Remarkably, most of the contemporary anthropological theories of animism share the key assumption that animism can be boiled down to some kind of hyper-mentalization (to some kind hyper- or over-attribution of mental states to entities of the world). In order to illustrate this claim, anthropologists have been mainly drawing on ethnographic data from the Amazon, the circumpolar region, Northern Siberia and Melanesia.

In my own work on animism, I am making four important claims:

(1) Influential models of animism, such as those championed by Descola and Viveiros de Castro, are based on various conceptual fallacies and they fail to be supported by ethnographic evidence.

(2) Cultures in which paradigmatic cases of animism can be encountered are not specifically characterized by hyper-mentalization. The phenomenon of hyper-mentalization goes far beyond cultures that anthropologists usually recognized as animistic.

(3) Cultures usually recognized as animistic can be specifically characterized as exhibiting some kind of weak essentialism (in Gelman’s sense of the word).

(4) This weak essentialism has remarkable consequences in the way people categorize the world and make property inductions. Indeed, in these cultures, abstract knowledge governing categorization and property induction is arguably structured in a relational and dynamical fashion rather than in a static tree-taxonomical one. Bayesian models of cognition (and notably hierarchical Bayesian models) provide the most powerful and fruitful tools to investigate these issues (Josh Tenenbaum, Tom Griffiths, Charles Kemp, etc.).