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## PI with circular distributions

Here is another paper in that occasional series of theoretical considerations of Path Integration, I’ll confess that I haven’t read this particular paper – but if the abstract is anything to go by, then it will be of interest to lots of you.

Abstract: “We propose a mathematical model of the Path Integration (PI) process. Its core assumption is that orientations of a path are summarized by circular probability distributions. We compare our model with classical, deterministic models of PI and find that, although they are indistinguishable in terms of information encoded, the probabilistic model is more parsimonious when considering navigation strategies. We show how sensory events can enrich the probability distributions memorized, resulting in a continuum of navigation strategies, from PI to stimulus-triggered response. We analyze the combination of circular probability distributions (e.g., multi-cue fusion), and demonstrate that, contrary to the linear case, adding orientation cues does not always increase reliability of estimates. We discuss experimental predictions entailed by our model.”

Diard, Julien and Bessière, Pierre and Berthoz, Alain (2012) Spatial memory of paths using circular probability distributions: Theoretical properties, navigation strategies and orientation cue combination. Spatial Cognition & Computation, doi: 10.1080/13875868.2012.756490

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Categories: Papers from 2012

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