Space as an invention of biological organisms

The question of the nature of space around us has occupied thinkers since the dawn of humanity, with scientists and philosophers today implicitly assuming that space is something that exists objectively. Here we show that this does not have to be the case: the notion of space could emerge when biological organisms seek an economic representation of their sensorimotor flow. The emergence of spatial notions does not necessitate the existence of real physical space, but only requires the presence of sensorimotor invariants called `compensable' sensory changes. We show mathematically and then in simulations that na\"ive agents making no assumptions about the existence of space are able to learn these invariants and to build the abstract notion that physicists call rigid displacement, which is independent of what is being displaced. Rigid displacements may underly perception of space as an unchanging medium within which objects are described by their relative positions. Our findings suggest that the question of the nature of space, currently exclusive to philosophy and physics, should also be addressed from the standpoint of neuroscience and artificial intelligence

Predictive processing, perceptual presence, and sensorimotor theory

International audienc

Eye Movement Control During Reading: A Simulation of Some Word-Targeting Strategies

McConkie, Kerr, Reddix, & Zola [(1988). Vision Research, 28, 1107–1118] demonstrated that the distributions of landing sites on a word tended to be gaussian in shape. They provided a detailed account of the behaviour of the eye once a target had been selected and a saccade initiated, but said little about the process of target selection itself. The purpose of this study was to take as a starting point the landing site distributions of McConkie et al., in particular the residuals derived from fitting the gaussians to the empirical data, and to explore by computer simulation a number of saccade targeting strategies in order to discover candidates that best accounted for the residual data. Our results indicate that the strategy that gives the best fit involves targeting the longest word in a right parafoveal window extending 20 characters to the right of the currently fixated word. The implications of this finding for models of reading are discussed