Microsaccade-related brain potentials signal the focus of visuospatial attention

Meyberg, Susann; Werkle‐Bergner, Markus; Sommer, Werner; Dimigen, Olaf

doi:10.1016/j.neuroimage.2014.09.065

Cited by 48 publications

(49 citation statements)

References 72 publications

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“…Recent technological advances make it possible to study attention shifts using combined eye tracking and EEG (e.g., Kulke and Wattam-Bell, 2013; Dimigen, 2014; Kulke et al, 2015b; Meyberg et al, 2015), which gives us an opportunity to measure neural mechanisms of attention shifts without explicit verbal instructions. However, it is unclear how these tasks relate to previous paradigms with explicit instructions.…”

Section: Introductionmentioning

confidence: 99%

Neural Differences between Covert and Overt Attention Studied using EEG with Simultaneous Remote Eye Tracking

Kulke¹,

Atkinson

Braddick

2016

Front. Hum. Neurosci.

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Research on neural mechanisms of attention has generally instructed subjects to direct attention covertly while maintaining a fixed gaze. This study combined simultaneous eye tracking and electroencephalogram (EEG) to measure neural attention responses during exogenous cueing in overt attention shifts (with saccadic eye movements to a target) and compared these with covert attention shifts (responding manually while maintaining central fixation). EEG analysis of the period preceding the saccade latency showed similar occipital response amplitudes for overt and covert shifts, although response latencies differed. However, a frontal positivity was greater during covert attention shifts, possibly reflecting saccade inhibition to maintain fixation. The results show that combined EEG and eye tracking can be successfully used to study natural overt shifts of attention (applicable to non-verbal infants) and that requiring inhibition of saccades can lead to additional frontal responses. Such data can be used to refine current neural models of attention that have been mainly based on covert shifts.

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Section: Introductionmentioning

confidence: 99%

Neural Differences between Covert and Overt Attention Studied using EEG with Simultaneous Remote Eye Tracking

Kulke¹,

Atkinson

Braddick

2016

Front. Hum. Neurosci.

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“…Other visual and oculomotor covariates will introduce similar biases. For example, both the stimulus features in the currently foveated image region (Dimigen, Sommer, & Kliegl, 2013;Gaarder, Krauskopf, Graf, Kropfl, & Armington, 1964;Ossandon, Helo, Montefusco-Siegmund, & Maldonado, 2010;Ries et al, 2018b), the fixation location on the screen (Cornelissen et al, 2019;Dimigen et al, 2013), and the direction of the incoming saccade (Cornelissen et al, 2019;Meyberg, Werkle-Bergner, Sommer, & Dimigen, 2015; see also the results in this paper) modulate the FRP waveshape. It is therefore reasonable to conclude that most existing FRP results (including our own) are confounded to some degree, since they did not fully control for differences in overlap and low-level covariates.…”

Section: Low-level Covariates Influencing Eye Movement-related Responsesmentioning

confidence: 68%

“…Another major advantage compared to traditional averaging is that deconvolution also provides us with a clean, unbiased version of the (micro)saccade-related brain activity in the task. This is interesting, since potentials from small saccades have been shown to carry valuable information about the time course of attentional (Meyberg et al, 2015) and affective (Guérin-Dugué et al, 2018) processing in the task. With deconvolution, we can mine these "hidden" brain responses to learn more about the participant's attentional or cognitive state.…”

Section: Resultsmentioning

confidence: 99%

“…Second, the number of covariates that can be simultaneously matched under practical conditions is limited and likely smaller than the number of variables that are already known to modulate the FRP. In particular, variables shown to affect the waveform include the durations of the preceding and current fixation, the temporal overlap with the stimulus-onset ERP (Coco et al, 2020), the amplitude (e.g., Gaarder et al, 1964;Thickbroom et al, 1991) and direction (Cornelissen et al, 2019;Meyberg et al, 2015) of the incoming saccade, the fixated region of the screen (Dimigen et al, 2013), and local image properties at the foveated spot, such as the local luminance (Armington, Gaarder, & Schick, 1967;Gaarder et al, 1964;Ossandon et al, 2010) and spatial frequency spectrum (Armington & Bloom, 1974;Armington et al, 1967;Ries et al, 2018b;Yagi, Ishida, & Katayama, 1992). In our experience, in a task like sentence reading, it is rarely possible to match more than two to three covariates, at least if these covariates show sizeable condition differences in the first place.…”

Section: Fixation Matching: Limitations and Problemsmentioning

confidence: 99%

“…Previous co-registration studies have shown that despite their small size, miniature saccades can generate sizable eye muscle (Craddock et al, 2016;Yuval-Greenberg & Deouell, 2009) and brain potentials (Dimigen et al, 2009;Gaarder et al, 1964;Meyberg et al, 2015) in EEG. Furthermore, because the amplitude and rate of miniature saccades often differs systematically between experimental conditions (Rolfs, 2009), these additional signals can seriously distort stimulus-locked analyses in the time and frequency domain (Dimigen et al, 2009;Yuval-Greenberg et al, 2008).…”

Section: Experiments 1: Face Perceptionmentioning

confidence: 99%

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Analyzing combined eye-tracking/EEG experiments with (non)linear deconvolution models

Dimigen¹,

Ehinger

2019

Preprint

Self Cite

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Fixation-related potentials (FRPs), neural responses aligned to saccade offsets, are a promising tool to study the dynamics of attention and cognition under natural viewing conditions. In the past, four methodological problems have complicated the analysis of such combined eye-tracking/EEG experiments: (i) the synchronization of data streams, (ii) the removal of ocular artifacts, (iii) the condition-specific temporal overlap between the brain responses evoked by consecutive fixations, (iv) and the fact that numerous low-level stimulus and saccade properties also influence the post-saccadic neural responses. While effective solutions exist for the first two problems, the latter ones are only beginning to be addressed. In the current paper, we present and review a unified framework for FRP analysis that allows us to deconvolve overlapping potentials and control for linear and nonlinear confounds on theFRPs. An open software implementation is provided for all procedures. We then demonstrate the advantages of this approach for data from three commonly studied paradigms: face perception, scene viewing, and natural sentence reading. First, for a traditional ERP face recognition experiment, we show how deconvolution can separate stimulus-ERPs from overlapping muscle and brain potentials produced by small (micro)saccades on the face.Second, in scene viewing, we isolate multiple non-linear influences of saccade parameters on the FRP. Finally, for a natural sentence reading experiment using the boundary paradigm, we show how it is possible to study the neural correlates of parafoveal preview after removing spurious overlap effects caused by the associated difference in average fixation time. Our results suggest a principal way of measuring reliable fixation-related brain potentials during natural vision.

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Fixational Eye Movements

Huerta

Lynch

Zayit‐Soudry

et al. 2019

Studies in Neuroscience, Psychology and Behavioral Economics

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Microsaccade-related brain potentials signal the focus of visuospatial attention

Cited by 48 publications

References 72 publications

Neural Differences between Covert and Overt Attention Studied using EEG with Simultaneous Remote Eye Tracking

Neural Differences between Covert and Overt Attention Studied using EEG with Simultaneous Remote Eye Tracking

Analyzing combined eye-tracking/EEG experiments with (non)linear deconvolution models

Fixational Eye Movements

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