The flash-lag effect as a motion-based predictive shift
reproduce results using the code available @ https://github.com/laurentperrinet/Khoei_2017_PLoSCB
press release (in French) http://www.cnrs.fr/insb/recherche/parutions/articles2017/l-perrinet.html
press release (in English).
- Mina A. Khoei, Guillaume S. Masson, Laurent U. Perrinet. The flash-lag effect as a motion-based predictive shift, URL URL2 . PLoS Computational Biology, 13(1):e1005068, 2017 abstractDue to its inherent neural delays,the visual system has an outdated access to sensory informationabout the current position of moving objects.In contrast, living organisms are remarkably able to track and intercept moving objectsunder a large range of challenging environmental conditions.Physiological, behavioral and psychophysical evidences strongly suggestthat position coding is extrapolated using an explicit andreliable representation of object's motionbut it is still unclear how these two representations interact.For instance, the so-called flash-lag effect supports the idea ofa differential processing of position between moving and static objects. Although elucidating such mechanisms is crucial in our understanding ofthe dynamics of visual processing,a theory is still missing to explain the different facets of this visual illusion.Here, we reconsider several of the key aspects of the flash-lag effect in orderto explore the role of motion upon neural coding of objects' position.First, we formalize the problem using a Bayesian modeling frameworkwhich includes a graded representation of the degree of belief about visual motion.We introduce a motion-based prediction modelas a candidate explanation for the perception of coherent motion.By including the knowledge of a fixed delay,we can model the dynamics of sensory information integrationby extrapolating the information acquired at previous instants in time.Next, we simulate the optimal estimation of object positionwith and without delay compensation andcompared it with human perceptionunder a broad range of different psychophysical conditions.Our computational study suggests that the explicit, probabilistic representationof velocity information is crucial in explaining position coding,and therefore the flash-lag effect.We discuss these theoretical results in light of the putative corrective mechanismsthat can be used to cancel out the detrimental effects of neural delays andilluminate the more general question of the dynamical representation of spatial information at the present time in the visual pathways..
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This work was supported by the FACETS ITN project (EU funding, grant number 237955), a 'Marie-Curie Initial Training Network'.
This work was supported by European Union project Number FP7-269921, "BrainScales".