| Abstract: | Perceptual input changes constantly in an unpredictable fashion, often changing before our somewhat sluggish perceptual systems have adequately processed this input. This can give rise to source confusion—how do we know whether a given perceptual activation is due to the current input, or a previous input that had yet to be completely processed? We propose that activity‐dependent neural accommodation naturally limits this source confusion by suppressing items once they have been identified. We review behavioral paradigms from different literatures that measure the correlates of persistence and accommodation. Of the various accommodative mechanisms, we focus on synaptic depression, deriving a rate‐coded expression that can be used to produce accommodating dynamics in any neural network with real valued activation. We implement this expression in a hierarchical model of perception termed, “a neural mechanism for responding optimally with unknown sources of evidence” (nROUSE). This model can be viewed as a more detailed version of the more abstract ROUSE model of Huber, Shiffrin, Lyle, and Ruys (2001), which produces accommodated levels of feature evidence through an optimal calculation. We apply nROUSE to three short‐term priming experiments that manipulated prime duration. |
