The Encoding‐Error Model of Pathway Completion without Vision

TLDR

The study introduces a model explaining shortcut errors in visually deprived individuals navigating triangular pathways. The model attributes shortcut errors to encoding inaccuracies, positing that participants compress turn and distance ranges toward the mean during segment encoding, with individual differences driven by encoding‑function parameters. The model accurately predicts errors on simple triangular paths but underestimates errors on more complex routes, suggesting encoding errors alone cannot explain all navigation mistakes, though they likely contribute broadly.

Abstract

We present a model that accounts for errors in short‐cutting to complete a triangular pathway by individuals deprived of visual input. The model assumes that systematic error arises from components of navigation concerned with encoding an internal representation of the pathway, rather than the computation of a homeward trajectory or motor output per se. Subjects' tendency to compress the range of actually produced turns and distances, in comparison to the range of correct values, is attributed to regression toward the mean of encoded values during encoding of segments and turns, in the face of uncertainty about the actual values. Individual‐subject variations are attributed to differences in the encoding‐function parameters, not to variations in the processes themselves. The model provides excellent accounts of data obtained with triangular pathways but fares less well when pathway complexity increases, at which point errors do not appear to be solely attributable to encoding processes. The sources of error identified by the model are likely to play a role in navigation more generally.