The time course of visual adaptation

Maddison, Sarah (2019) The time course of visual adaptation. PhD thesis, University of Nottingham.

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Visual neurons persistently alter their operating properties in response to changes in the statistics of the visual environment – a process termed adaptation. The prevalence of adaptation has led it to be considered a universal law of visual processing.

Neural adaptation produces measurable perceptual aftereffects. One such aftereffect is the tilt aftereffect; whereby prolonged viewing of a tilted stimulus causes subsequently viewed stimuli to appear tilted away from the adapting stimulus orientation. This aftereffect is used as a proxy for adaptation throughout this thesis. Longer adapting durations result in larger perceptual aftereffects. These aftereffects show a characteristic time course of logarithmic growth and decay, however little is known about whether this time course is fixed or whether it can be altered by previous visual experience.

To measure changes in the time course of adaptation, it must be measured with high temporal resolution. Traditionally, adaptation growth is measured using multiple discrete periods of continuous adaptation, increasing in duration. This method is time consuming and has low temporal resolution. Therefore, we explored the use of a single period of adaptation that was briefly interrupted by the measurement of adaptation magnitude – we refer to this as ‘interrupted adaptation’.

Interrupted adaptation was shown to be a valid high temporal resolution measure of the time course of the tilt aftereffect. However, overall adaptation magnitude was suppressed using this measure when compared to the same duration of adaptation measured with tradition continuous adaptation. We explored the effects of passive recovery, attention, and memory on the suppression of the tilt aftereffect, but found suppression was produced by passive recovery alone. The magnitude of the suppression could not be accounted for using a simple model of adaptation with a fixed rate of growth and decay, suggesting rates of growth and decay may differ.

Once a valid high temporal resolution measure of the time course had been achieved, we explored whether the time course of visual adaptation could be altered by previous visual experience. We hypothesised that the rate of adaptation could be determined by the rate of change recently encountered in the environment. Observers were exposed to temporally high-pass and low-pass filtered videos, followed by the measurement of the time course of the tilt aftereffect. Exposure to predominantly high temporal frequencies resulted in the increased rate and magnitude of tilt aftereffect growth, consistent with the hypothesis that the rate of adaptation growth reflects the rate of recently encountered change. Exposure to predominantly low temporal frequencies had negligible effects on the time course of the tilt aftereffect, likely due to their prevalence in natural statistics.

The original finding of increased rate and magnitude of adaptation following exposure to fast temporal statistics failed to be replicated using high temporal frequency contrast-modulated artificial stimuli. This led to the hypothesis that differences in the average contrast of the filtered videos, rather than differences in temporal statistics, drove the original effect. In line with this hypothesis, increased rate and magnitude of the tilt aftereffect was observed following exposure to a temporally unfiltered video with contrast matched to the original high-pass filtered video. Further exploration revealed that exposure to videos with increased contrast relative to natural scenes leads to a suppression of the tilt aftereffect in line with a response gain control mechanism.

Throughout this thesis the mechanisms underlying the time course of adaptation were explored through modelling. Consistent with previous research, many of the empirical findings are well captured by a two-mechanism leaky integrator model. However, further work is needed to identify the precise nature and number of mechanisms driving adaptation across a wide range of timescales.

Item Type: Thesis (University of Nottingham only) (PhD)
Supervisors: Webb, Ben
Roach, Neil
Keywords: Vision, visual system, adaptation, timescales, time course, psychophysics, Neuroplasticity
Subjects: Q Science > QP Physiology > QP351 Neurophysiology and neuropsychology
Faculties/Schools: UK Campuses > Faculty of Science > School of Psychology
Item ID: 56004
Depositing User: Maddison, Sarah
Date Deposited: 17 Jul 2019 04:40
Last Modified: 17 Jul 2019 04:40

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