research

Conscious experiences are rich. Yet they exclude a lot too. Lots of information that's processed unconsciously never makes it into experience. What information gets in for each kind of experience (visual, auditory, emotional, etc.)? Why does that information get in, while much is left out? And what can answers to these questions tell us about the nature and roles of experiences? My research aims to shed light on these questions.

Unconscious processing shapes experience in many ways. Here are two ways that especially interest me:

Cognitive and emotional influences on perception. Information processed unconsciously in perception is influenced by information processed in other systems such as emotion and cognition. Much of my work addresses the ways in which cognition does and does not influence perception, and what these issues mean for the purposes and natures of perception, emotion, and cognition.
Probabilistic processing and perceptual uncertainty. For many features represented in experience, there's evidence that the brain unconsciously maintains and updates a range of best guesses, weighted according to their probability. Rather than include all these competing guesses and probabilities for each feature, it usually seems that experiences include much less information. For example, your visual system represents the size of a nearby object. It unconsciously maintains a distribution over a range of sizes. But visual experiences would seem to represent the object as having some size or other--at least when you're attending the object in the center of your visual field. Still, there are ways in which your experiences can seem less precise. For example, experience of objects in the periphery is less precise than experience of objects centrally. Experience of objects in a fog is less precise than experience of objects in clear conditions.

In a series of papers related to cognitive and emotional influences on perception, I have addressed the possibility of top-down effects on perceptual processing and experience. One can model potential top-down effects using hierarchical probabilistic frameworks in which local top-down and bottom-up messages are pervasive in perceptual processing. I’ve argued that top-down processing in perceptual pathways is importantly different from top-down processing in motor pathways (Vance 2017). I’ve argued that cognitive influence on perceptual processing can be bad (here and Vance 2014) and sometimes good (Vance 2015b). I’ve argued that some hierarchical probabilistic accounts of cognitive influence on perception fail to explain central putative cases of such influence (Vance & Stokes 2017) and also fail to account for some forms of resistance to cognitive influence such as persistent illusions (Vance 2015a). I've also argued with Preston Werner that attention plays important roles in moral perception, some of which cognitively influenced (Vance & Werner forthcoming). These arguments help shed light on how perceptual experiences are formed as the result of complex processing, some of which is top-down. And they shed light on the role of experiences in our mental lives, including as rational grounds for belief and as guides for action.

In another project related to probabilistic processing and perceptual uncertainty, I investigate how and why experiences can seem more or less clear, precise, or certain. There’s evidence that perceptual systems unconsciously encode probabilistic information and that much of the information does not feature explicitly in experience. I've argued that the statistical property of precision in sensory signals helps explain the varying levels of clarity and uncertainty in experiences (Vance 2021, forthcoming). Precision can be modeled in terms of the variance of unconscious distributions in perceptual processing (variance is the reciprocal of statistical precision). The view that sensory precision shapes experiences such as blurry vision is supported by successful models in perception science. Precision in a related (but distinct) sense is the opposite of vagueness. I also argue that there is a kind of vagueness inherent in perceptual experiences (Vance forthcoming). Thinking about the vagueness in perceptual experience encourages us to rethink the nature and role of experiences in several ways. Most modeling in vision science assumes that the upshots of perceptual processing are determinate, distal, feature representations. Vague perception suggests that there may be more to perceptual experience than determinate, distal, feature representation: experiences may also reflect underlying uncertainty in perceptual processing. In addition, reflection on vague perception raises new questions for theories of the representational contents of experience and for accounts of vagueness in general.

Much of my work has been on visual processing and visual experiences. But I also work on processing and experiences in other sensory modalities, in emotion, and elsewhere. I'm interested in accounting for processing and experiences of all kinds. On this score, I have written about top-down effects in emotion (Vance 2014) and proprioception (Vance 2017). I’ve also written about whether emotional experiences are partly constituted by their subject's rationally evaluable commitments and what light that question might shed on the rational evaluation of perceptual experience (Vance 2018a).

Finally, I have an emerging interest in the psychology, neuroscience, and philosophy of self-representation. I've published one short paper in this area so far (Vance 2018b), and plan to publish more on the self in the coming years.

For links to the papers referenced above, check out my Papers page.

research

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