Spontaneous Microsaccades Reflect Shifts in Covert Attention

Yuval-Greenberg, Shlomit; Merriam, Elisha P.; Heeger, David J.

doi:10.1523/jneurosci.0582-14.2014

Cited by 124 publications

(131 citation statements)

References 62 publications

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“…However, the refractory period for a saccade involves a shift in attention prior to initiation (Kowler et al, 1995). Microsaccades, like larger saccades, also involve attentional shifts before initiation (Chen, Ignashchenkova, Their, & Hafred, 2015; Yuval-Greenberg, Merriam, & Heeger, 2014). Divided attention increases reaction time (Ninio & Kahneman, 1974), so perhaps when microsaccades are made immediately before the target appears, visual attention is divided between the attentional shifts accompanying the microsaccades and the attention directed to monitoring target onset, resulting in longer manual reaction times.…”

Section: Discussionmentioning

confidence: 99%

Saccadic latency in amblyopia

et al. 2016

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We measured saccadic latencies in a large sample (total n = 459) of individuals with amblyopia or risk factors for amblyopia, e.g., strabismus or anisometropia, and normal control subjects. We presented an easily visible target randomly to the left or right, 3.5° from fixation. The interocular difference in saccadic latency is highly correlated with the interocular difference in LogMAR (Snellen) acuity—as the acuity difference increases, so does the latency difference. Strabismic and strabismic-anisometropic amblyopes have, on average, a larger difference between their eyes in LogMAR acuity than anisometropic amblyopes and thus their interocular latency difference is, on average, significantly larger than anisometropic amblyopes. Despite its relation to LogMAR acuity, the longer latency in strabismic amblyopes cannot be attributed either to poor resolution or to reduced contrast sensitivity, because their interocular differences in grating acuity and in contrast sensitivity are roughly the same as for anisometropic amblyopes. The correlation between LogMAR acuity and saccadic latency arises because of the confluence of two separable effects in the strabismic amblyopic eye—poor letter recognition impairs LogMAR acuity while an intrinsic sluggishness delays reaction time. We speculate that the frequent microsaccades and the accompanying attentional shifts, made while strabismic amblyopes struggle to maintain fixation with their amblyopic eyes, result in all types of reactions being irreducibly delayed.

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Section: Discussionmentioning

confidence: 99%

Saccadic latency in amblyopia

et al. 2016

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“…For example, when using a threshold factor of λ=5, it makes sense to have at least three samples above threshold to detect a saccade. Indeed, if the algorithm were used to detect microsaccades during an experiment, low thresholds should be used as eye velocities during microsaccades are not as high as during saccades, while three or more samples should be evaluated (for a successful application with a different implementation, see Yuval-Greenberg, Merriam, & Heeger, 2014). If however a threshold factor of λ=20 is used, one sample above threshold may often be enough to reliably detect a saccade without adding significant additional delay.…”

Section: Discussionmentioning

confidence: 99%

An adaptive algorithm for fast and reliable online saccade detection

Schweitzer

Rolfs

2019

Preprint

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To investigate visual perception around the time of eye movements, vision scientists manipulate stimuli contingent upon the onset of a saccade. For these experimental paradigms, timing is especially crucial, as saccade offset imposes a deadline on the display change. Although efficient online saccade detection can greatly improve timing, most algorithms rely on spatialboundary techniques or absolute-velocity thresholds, which both suffer from their respective weaknesses: late detections and false alarms. We propose an adaptive, velocity-based algorithm for online saccade detection that surpasses both standard techniques in speed and accuracy and allows the user to freely define detection criteria. Inspired by the Engbert-Kliegl-algorithm for microsaccade detection, our algorithm computes two-dimensional velocity thresholds from variance in preceding fixation samples, while compensating for noisy or missing data samples. An optional direction criterion limits detection to the instructed saccade direction, further increasing robustness.We validated the algorithm by simulating its performance on a large saccade dataset and found that high detection accuracy (false-alarm rates of <1%) could be achieved with detection latencies of only 3 milliseconds. High accuracy was maintained even under simulated high-noise conditions. To demonstrate that purely intra-saccadic presentations are technically feasible, we devised an experimental test, in which a Gabor patch drifted at saccadic peak velocities. While this stimulus was invisible when presented during fixation, observers reliably detected it during saccades.Photodiode measurements verified that -including all system delays -stimuli were physically displayed on average 20 ms after saccade onset. Thus, the proposed algorithm provides valuable tool for gaze-contingent paradigms.

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“…An online detection method—for example for closed-loop experiments that require real-time detection of microsaccades, such as in Chen and Hafed (2013) and Yuval-Greenberg et al (2014)—would require a modified inference algorithm. If it is crucial to detect microsaccades online, we recommend using BMD reduced + threshold, with a Kalman filter (only the forward filter) instead of the Kalman smoother.…”

Section: Discussionmentioning

confidence: 99%

“…Microsaccades have been implicated in several perceptual and cognitive functions, including aiding performance in high-acuity visual tasks (Ko, Poletti, & Rucci, 2010; Poletti, Listorti, & Rucci, 2013; Rucci, Iovin, Poletti, & Santini, 2007) and shifts of covert spatial attention in both humans and monkeys (Engbert & Kliegl, 2003; Hafed & Clark, 2002; Hafed, Lovejoy, & Krauzlis, 2011; Lara & Wallis, 2012; Laubrock, Engbert, & Kliegl, 2005; Laubrock, Engbert, Rolfs, & Kliegl, 2007; Rolfs, 2009; Rolfs, Engbert, & Kliegl, 2004; Yuval-Greenberg, Merriam, & Heeger, 2014), though there has been some disagreement regarding this last role (Collewijn & Kowler, 2008; Horowitz, Fine, Fencsik, Yurgenson, & Wolfe, 2007). Arguments about the functional roles of microsaccades rely on accurate definition and detection of microsaccades (Poletti & Rucci, 2016).…”

Section: Introductionmentioning

confidence: 99%

Bayesian microsaccade detection

2017

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Microsaccades are high-velocity fixational eye movements, with special roles in perception and cognition. The default microsaccade detection method is to determine when the smoothed eye velocity exceeds a threshold. We have developed a new method, Bayesian microsaccade detection (BMD), which performs inference based on a simple statistical model of eye positions. In this model, a hidden state variable changes between drift and microsaccade states at random times. The eye position is a biased random walk with different velocity distributions for each state. BMD generates samples from the posterior probability distribution over the eye state time series given the eye position time series. Applied to simulated data, BMD recovers the “true” microsaccades with fewer errors than alternative algorithms, especially at high noise. Applied to EyeLink eye tracker data, BMD detects almost all the microsaccades detected by the default method, but also apparent microsaccades embedded in high noise—although these can also be interpreted as false positives. Next we apply the algorithms to data collected with a Dual Purkinje Image eye tracker, whose higher precision justifies defining the inferred microsaccades as ground truth. When we add artificial measurement noise, the inferences of all algorithms degrade; however, at noise levels comparable to EyeLink data, BMD recovers the “true” microsaccades with 54% fewer errors than the default algorithm. Though unsuitable for online detection, BMD has other advantages: It returns probabilities rather than binary judgments, and it can be straightforwardly adapted as the generative model is refined. We make our algorithm available as a software package.

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Spontaneous Microsaccades Reflect Shifts in Covert Attention

Cited by 124 publications

References 62 publications

Saccadic latency in amblyopia

Saccadic latency in amblyopia

An adaptive algorithm for fast and reliable online saccade detection

Bayesian microsaccade detection

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