The effects of fixational tremor on the retinal image

Abstract

The study of fixational eye motion has implications for the neural and computational underpinnings of vision. One component of fixational eye motion is tremor, a high-frequency oscillatory jitter reported to be anywhere from ∼11–60 arcseconds in amplitude. In order to isolate the effects of tremor on the retinal image directly and in the absence of optical blur, high-frequency, high-resolution eye traces were collected in six subjects from videos recorded with an adaptive optics scanning laser ophthalmoscope. Videos were acquired while subjects engaged in an active fixation task where they fixated on a tumbling E stimulus and reported changes in its orientation. Spectral analysis was conducted on periods of ocular drift, with all drifts being concatenated together after removal of saccades from the trace. The resultant amplitude spectra showed a slight deviation from the traditional 1/f nature of optical drift in the frequency range of 50–100 Hz, which is indicative of tremor. However, this deviation rarely exceeded 1 arcsecond and the consequent standard deviation of retinal image motion over the tremor band (50–100 Hz) was just over 5 arcseconds. Given such a small amplitude, it is unlikely tremor will contribute in any meaningful way to the visual percept.

Characterizing gaze position signals and synthesizing noise during fixations in eye-tracking data

“…There is a long history of applying such analyses to eye-tracking data (e.g., Stark et al, 1958 , 1961 , 1962 ; Campbell et al, 1959 ; Bahill et al, 1981 , 1982 ). Fourier analyses of fixational eye movements have previously been done by studies such as Findlay ( 1971 ), Eizenman et al, ( 1985 ), Coey et al, ( 2012 ) and Bowers et al, ( 2019 ). General advice on how to perform such analyses has been provided by Pugh et al, ( 1987 ) and Eadie et al, ( 1995 ), therefore here we will focus on one specific application of Fourier analysis of eye-movement data: analyses of spectral color using periodograms.…”

Is apparent fixational drift in eye-tracking data due to filters or eyeball rotation?

“…The spectral color of a signal is a description of the power in the signal at different temporal frequencies. There is a long history of applying frequency analyses to eyetracking data in general (e.g., Stark et al, 1961;Campbell et al, 1959;Bahill et al, 1981) and for fixational eye movements in specific (e.g., Findlay, 1971;Eizenman et al, 1985;Stevenson et al, 2010;Coey et al, 2012;Sheehy et al, 2012;Ko et al, 2016;Bowers et al, 2019). Here, we will provide a brief discussion of how the spectral color of gaze position signals is interpreted; for a more detailed discussion of spectral analyses of eye-tracking data, see Niehorster et al (2020c).…”

“…Note also that it has recently been questioned whether video-based eye trackers are suitable for microsaccade research (Holmqvist & Blignaut, 2020). Other researchers interested in fixational eye movements use different measurement techniques that provide even better data quality (lower measurement noise levels), such as Dual-Purkinje eye trackers (Kuang et al, 2012;Horowitz et al, 2007), scleral search coils (McCamy et al, 2015;Ko et al, 2016) and various scanning laser opthalmoscopes (Stevenson et al, 2010;Sheehy et al, 2012;Bowers et al, 2019).…”

“…Even with these best-available video-based eye trackers, it is not straightforward to determine what the source of the fluctuations in the eye movement signal is because the eye movements of interest to fixational eye-movement researchers can have magnitudes close to, or even below, the noise floor of the eye tracker. One may therefore resort to knowledge about the dynamics of physiological movements and measurement noise to characterize the content and possible origin of a gaze position signal (e.g., Findlay 1971 ; Eizenman et al, 1985 ; Coey et al, 2012 ; Bowers et al, 2019 ). While formal analyses of the dynamics of the gaze position signal usually examine its spectral composition (ibid), we think there is value in training the scientist’s visual pattern recognizer to discriminate between the different types of signals.…”

“…For eye-tracking signals, such signal dynamics are often attributed to measurement noise. Since fixational eye movements have a bandwidth of up to about 100 Hz (e.g., Findlay, 1971 ; Ko et al, 2016 ; Bowers et al, 2019 ), it is expected that the spectrum at higher frequencies only reflects such measurement noise. Note that if the measurement noise of an eye tracker is too large, it will drown out the 1/ f component of the gaze position signal that is due to fixational eye movements, indicating that the eye tracker is not sensitive enough to measure the eye movements of interest.…”