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Peter Tse, Peter Kohler, Eric Reavis, LiWei Sun, Kevin Hartstein, Gideon Caplovitz; How Top-down Attention Alters Bottom-up preconscious operations. Journal of Vision 2018;18(10):984. doi: https://doi.org/10.1167/18.10.984.
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© ARVO (1962-2015); The Authors (2016-present)
While the selective and facilitatory roles of attention have been extensively characterized, there is an ongoing debate about whether attention can alter subjective visual experiences. Here we demonstrate that attention can strongly modulate subjective visual experiences in areas as diverse as perceived color, brightness, size, shape, and direction of motion, as well perceived sound, in certain case where the stimulus is multiply interpretable. We hypothesize that attention can specify a domain or framework, such as a boundary or layer, within which constancy and other constructive processes subsequently operate. The outputs of these preconscious processes within the attended domain are then experienced consciously. Here we demonstrate that human observers can deploy attention to selectively demarcate specific surface, layer and figural boundaries and thereby affect which constructive processes will operate and how they will operate. Top-down volitional operations can therefore constrain what the outputs of bottom-up operations will be. In order for this to be possible, attention must be able to reach down into the preconscious buffer in order to define a domain. Our data (Sun et al., 2017) suggest that this buffer spans ~300ms of processing, and that top-down volition can reach down into this buffer and alter its perceptual outputs. How such top-down 'reaching down' might operate at a neural circuit level will be considered. In particular, the 'binding-by-bursting' theory of Tse (2013) in which attention sets up a 'bucket brigade' of information processing from the LGN to V1 down the ventral stream to the hippocampus for identification will be modified to take into account the idea of domains of preconscious operator operations.
Meeting abstract presented at VSS 2018
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