Encode a Letter and Get Its Location for Free? Assessing Incidental Binding of Verbal and Spatial Features

Abstract

Previous studies have demonstrated that when presented with a display of spatially arranged letters, participants seem to remember the letters’ locations when letters are the focus of a recognition test, but do not remember letters’ identity when locations are tested. This strong binding asymmetry suggests that encoding location may be obligatory when remembering letters, which requires explanation within theories of working memory. We report two studies in which participants focused either on remembering letters or locations for a short interval. At test, positive probes were either intact letter–location combinations or recombinations of an observed letter and another previously occupied location. Incidental binding is observed when intact probes are recognized more accurately or faster than recombined probes. Here, however, we observed no evidence of incidental binding of location to letter in either experiment, neither under conditions where participants focused on one feature exclusively for a block, nor where the to-be-remembered feature was revealed prior to encoding with a changing pre-cue, nor where the to-be-remembered feature was retro-cued and therefore unknown during encoding. Our results call into question the robustness of a strong, consistent binding asymmetry. They suggest that while incidental location-to-letter binding may sometimes occur, it is not obligatory.

PONG: A computational model of visual word recognition through bihemispheric activation.

“…Under the strongest assumption of flexibility, the tails of the positional distribution would approach an asymptote greater than zero, so that to some degree (determined by the asymptote), letters activate words irrespective of position. As it turns out, this has indeed been suggested by several studies (e.g., Delooze et al, 2022;Grainger et al, 2014;Snell et al, 2018a). But, critically, such degrees of flexibility also pose problems to the noisy slot-based approach.…”