The human brain selectively processes the visual information that enters the eyes, prioritizing some parts of the available information over others. This is called visual attention, and it plays a central role in determining what we see and how well we see it. Visual attention is allocated flexibly across space and dynamically across time, but most studies of visual attention have focused on its spatial aspects. Here, I propose to study temporal attention: the dynamic fluctuations of visual attention over time. I propose to develop and then empirically test a computational model of temporal attention that specifies how different types of temporal attention dynamically interact to affect visual responses. This work will unify different sources of temporal attention, previously investigated separately, into a singe theoretical framework, accounting for a range of previous findings. My proposed experiments to distinguish between alternative candidate models will identify neural processes that underlie the fluctuations and limitations of visual attention over time.
In Aim 1, I will develop a model that integrates two types of temporal attention: involuntary temporal attention, which is automatically evoked by the presentation of a behaviorally relevant stimulus, and voluntary temporal attention, which is the deliberate control of attentional allocation over time. These processes work together to prioritize processing and enhance perception of a visual stimulus at a time when it is likely to be most useful for behavior. My empirical studies (Aims 2 and 3) will systematically investigate how they are integrated and provide precise measures of their individual and joint time courses in humans. The studies will also clarify the sources of temporal attentional limitations in visual processing. Informed by model predictions, I will test hypotheses about how involuntary and voluntary temporal attention jointly influence the gain of visual responses dynamically over time, using both behavioral measures of visual sensitivity (Aim 2) and MEG measures of the sensitivity of cortical neuronal responses to visual stimuli (Aim 3). During this fellowship, I will receive training in behavioral, computational, and cognitive neuroscience methods through interactions with my research mentors, the broader NYU neuroscience community, and formal coursework. The proposed research is fully in line with the NEI mission. It investigates visual attention, an important mechanism of visual function (NEI Mission Statement). Further, as the dynamic allocation of attention is a central function of the visual system, the proposed research in healthy observers is readily applicable to translational research in special populations, and may clarify previously observed temporal attentional differences in individuals with visual neglect and ADHD.
The dynamic fluctuations of visual attention are an important determinant of sensory perception. This proposal will investigate the processes that contribute to changes in visual attention over timescales relevant for ongoing natural vision. The mechanisms explored by the proposed research are widely applicable and may clarify previously observed perceptual differences associated with personality traits like impulsivity, prevalent disorders such as ADHD, and visual impairment due to stroke or other brain injury, as in visual neglect.
| Denison, Rachel N; Adler, William T; Carrasco, Marisa et al. (2018) Humans incorporate attention-dependent uncertainty into perceptual decisions and confidence. Proc Natl Acad Sci U S A 115:11090-11095 |
| Piazza, Elise A; Denison, Rachel N; Silver, Michael A (2018) Recent cross-modal statistical learning influences visual perceptual selection. J Vis 18:1 |
| Rahnev, Dobromir; Denison, Rachel N (2018) Suboptimality in Perceptual Decision Making. Behav Brain Sci :1-107 |
| Denison, Rachel N; Heeger, David J; Carrasco, Marisa (2017) Attention flexibly trades off across points in time. Psychon Bull Rev 24:1142-1151 |
| Yashar, Amit; Denison, Rachel N (2017) Feature reliability determines specificity and transfer of perceptual learning in orientation search. PLoS Comput Biol 13:e1005882 |
