Predictive Coding Theory Research Articles

Predictive coding as a model of the V1 saliency map hypothesis

The predictive coding/biased competition (PC/BC) model is a specific implementation of the predictive coding theory that has previously been shown to provide a detailed account of the response properties of orientation tuned cells in primary visual cortex (V1). Here it is shown that the same model can successfully simulate psychophysical data relating to the saliency of unique items in search arrays, of contours embedded in random texture, and of borders between textured regions. This model thus provides a possible implementation of the hypothesis that V1 generates a bottom-up saliency map. However, PC/BC is very different from previous models of visual salience, in that it proposes that saliency results from the failure of an internal model of simple elementary image components to accurately predict the visual input. Saliency can therefore be interpreted as a mechanism by which prediction errors attract attention in an attempt to improve the accuracy of the brain's internal representation of the world.

Implicit multisensory associations influence voice recognition.

Natural objects provide partially redundant information to the brain through different sensory modalities. For example, voices and faces both give information about the speech content, age, and gender of a person. Thanks to this redundancy, multimodal recognition is fast, robust, and automatic. In unimodal perception, however, only part of the information about an object is available. Here, we addressed whether, even under conditions of unimodal sensory input, crossmodal neural circuits that have been shaped by previous associative learning become activated and underpin a performance benefit. We measured brain activity with functional magnetic resonance imaging before, while, and after participants learned to associate either sensory redundant stimuli, i.e. voices and faces, or arbitrary multimodal combinations, i.e. voices and written names, ring tones, and cell phones or brand names of these cell phones. After learning, participants were better at recognizing unimodal auditory voices that had been paired with faces than those paired with written names, and association of voices with faces resulted in an increased functional coupling between voice and face areas. No such effects were observed for ring tones that had been paired with cell phones or names. These findings demonstrate that brief exposure to ecologically valid and sensory redundant stimulus pairs, such as voices and faces, induces specific multisensory associations. Consistent with predictive coding theories, associative representations become thereafter available for unimodal perception and facilitate object recognition. These data suggest that for natural objects effective predictive signals can be generated across sensory systems and proceed by optimization of functional connectivity between specialized cortical sensory modules.