September 2017
Volume 17, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   August 2017
Quantifying the relation between pupil size and electrophysiological engagement of visual cortex
Author Affiliations
  • Nina Thigpen
    University of Florida
  • Andreas Keil
    University of Florida
Journal of Vision August 2017, Vol.17, 126. doi:
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      Nina Thigpen, Andreas Keil; Quantifying the relation between pupil size and electrophysiological engagement of visual cortex. Journal of Vision 2017;17(10):126. doi:

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      © ARVO (1962-2015); The Authors (2016-present)

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Little is known about how physical properties of the eye influence how light information is received in early visual cortex. In humans, mass activity in the primary visual cortex can by quantified by measuring the steady-state visually evoked potential (ssVEP). Given that both the ssVEP and pupil size are often modulated by the same manipulations, such as stimulus brightness and physiological arousal, the question arises whether pupil size is directly related to the amount of primary visual cortical engagement to a given stimulus. To test this hypothesis, we systematically manipulated pupil size by manipulating the brightness of five sinusoidal gratings, shown one at a time to participants for 3 seconds, 40 times each. Each stimulus flickered at either 6, 10, or 15 Hz, to elicit ssVEPs, used as a measure of visual cortical engagement. We observed a strong negative linear relation between pupil size and ssVEP amplitude, across participants and driving frequencies. Surprisingly, we observed a quadratic relationship between pupil size and the amplitude of the second harmonic of the driving frequency. These results suggest that there is a systematic relation between pupil size and mass activity in primary visual cortex that is not explained by light energy entering the retina. The data may play an important role in the understanding of the bi-directional relationships between the autonomic nervous system and primary visual cortex.

Meeting abstract presented at VSS 2017


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