Etienne B. Roesch is a Lecturer in Cognitive Science at the University of Reading, UK. His research interests include general brain functioning, emotion, perception, attention, consciousness, and cognitive science methods, i.e., theoretical, (biologically plausible) computational, and experimental work (ERG, coupled EEG-fMRI, and psychophysics). His current efforts involve the development of a novel framework for investigating the role of interaction with the environment in giving rise to our experience of the world.
Roesch E. B. (2016) In Search of a New Looking Glass: Cognitive Science Is Not Dead, It Is Just Asleep. Constructivist Foundations 11(2): 419–420. https://cepa.info/2601
Open peer commentary on the article “Exploring the Depth of Dream Experience: The Enactive Framework and Methods for Neurophenomenological Research” by Elizaveta Solomonova & Xin Wei Sha. Upshot: Solomonova and Sha draw inspiration from the work programme that sparked the enactive extension to cognitive science, and propose a framework for dream scientists. This case study for a renewed cognitive science highlights key points that are worth developing, in light of current practices in neuroscience.
Roesch E. B., Nasuto S. & Bishop J. M. (2013) Foundations of enactive cognitive science. Adaptive Behavior 21(3): 139–141. https://cepa.info/6360
Excerpt: This special issue contains a selection of the papers presented at the international symposium entitled ‘Foundations of Enactive Cognitive Science’, which was held in Windsor, UK, in February 2012. In organizing this symposium, our explicit goal was to create the space for researchers attracted to the concept of enaction to discuss the research agenda(s) for what could be described as an alternative or an extension to the orthodox paradigm(s) in cognitive science. About 70 researchers represented the five continents, and a dozen of academic disciplines. More extensive proceedings of the event can be found at
Roesch E. B., Spencer M., Nasuto S. J., Tanay T. & Bishop J. M. (2013) Authors’ Response: Learning, Anticipation and the Brain. Constructivist Foundations 9(1): 42–45. https://constructivist.info/9/1/042
Upshot: Albeit mostly supportive of our work, the commentaries we received highlighted a few points that deserve additional explanation, with regard to the notion of learning in our model, the relationship between our model and the brain, as well as the notion of anticipation. This open discussion emphasizes the need for toy computer models, to fuel theoretical discussion and prevent business-as-usual from getting in the way of new ideas.
Roesch E. B., Spencer M., Nasuto S. J., Tanay T. & Bishop J. M. (2013) Exploration of the Functional Properties of Interaction: Computer Models and Pointers for Theory. Constructivist Foundations 9(1): 26–33. https://constructivist.info/9/1/026
Context: Constructivist approaches to cognition have mostly been descriptive, and now face the challenge of specifying the mechanisms that may support the acquisition of knowledge. Departing from cognitivism, however, requires the development of a new functional framework that will support causal, powerful and goal-directed behavior in the context of the interaction between the organism and the environment. Problem: The properties affecting the computational power of this interaction are, however, unclear, and may include partial information from the environment, exploration, distributed processing and aggregation of information, emergence of knowledge and directedness towards relevant information. Method: We posit that one path towards such a framework may be grounded in these properties, supported by dynamical systems. To assess this hypothesis, we describe computational models inspired from swarm intelligence, which we use as a metaphor to explore the practical implications of the properties highlighted. Results: Our results demonstrate that these properties may serve as the basis for complex operations, yielding the elaboration of knowledge and goal-directed behavior. Implications: This work highlights aspects of interaction that we believe ought to be taken into account when characterizing the possible mechanisms underlying cognition. The scope of the models we describe cannot go beyond that of a metaphor, however, and future work, theoretical and experimental, is required for further insight into the functional role of interaction with the environment for the elaboration of complex behavior. Constructivist content: Inspiration for this work stems from the constructivist impetus to account for knowledge acquisition based on interaction.