Estimation of overlapped Eye Fixation Related Potentials: The General Linear Model, a more flexible framework than the ADJAR algorithm

(Micro)saccade-related potentials during face recognition: A study combining EEG, eye-tracking, and deconvolution modeling

Under natural viewing conditions, complex stimuli such as human faces are typically looked at several times in succession, implying that their recognition may unfold across multiple eye fixations. Although electrophysiological (EEG) experiments on face recognition typically prohibit eye movements, participants still execute frequent (micro)saccades on the face, each of which generates its own visuocortical response. This finding raises the question of whether the fixation-related potentials (FRPs) evoked by these tiny gaze shifts also contain psychologically valuable information about face processing. Here, we investigated this question by corecording EEG and eye movements in an experiment with emotional faces (happy, angry, neutral). Deconvolution modeling was used to separate the stimulus ERPs to face onset from the FRPs generated by subsequent microsaccades-induced refixations on the face. As expected, stimulus ERPs exhibited typical emotion effects, with a larger early posterior negativity (EPN) for happy/angry compared with neutral faces. Eye tracking confirmed that participants made small saccades in 98% of the trials, which were often aimed at the left eye of the stimulus face. However, while each saccade produced a strong response over visual areas, this response was unaffected by the face's emotional expression, both for the first and for subsequent (micro)saccades. This finding suggests that the face's affective content is rapidly evaluated after stimulus onset, leading to only a short-lived sensory enhancement by arousing stimuli that does not repeat itself during immediate refixations. Methodologically, our work demonstrates how eye tracking and deconvolution modeling can be used to extract several brain responses from each EEG trial, providing insights into neural processing at different latencies after stimulus onset.

Refixation behavior in naturalistic viewing: Methods, mechanisms, and neural correlates

When freely viewing a scene, the eyes often return to previously visited locations. By tracking eye movements and coregistering eye movements and EEG, such refixations are shown to have multiple roles: repairing insufficient encoding from precursor fixations, supporting ongoing viewing by resampling relevant locations prioritized by precursor fixations, and aiding the construction of memory representations. All these functions of refixation behavior are understood to be underpinned by three oculomotor and cognitive systems and their associated brain structures. First, immediate saccade planning prior to refixations involves attentional selection of candidate locations to revisit. This process is likely supported by the dorsal attentional network. Second, visual working memory, involved in maintaining task-related information, is likely supported by the visual cortex. Third, higher-order relevance of scene locations, which depends on general knowledge and understanding of scene meaning, is likely supported by the hippocampal memory system. Working together, these structures bring about viewing behavior that balances exploring previously unvisited areas of a scene with exploiting visited areas through refixations.

WildLab: A naturalistic free viewing experiment reveals previously unknown electroencephalography signatures of face processing

Neural mechanisms of face perception are predominantly studied in well-controlled experimental settings that involve random stimulus sequences and fixed eye positions. Although powerful, the employed paradigms are far from what constitutes natural vision. Here, we demonstrate the feasibility of ecologically more valid experimental paradigms using natural viewing behaviour, by combining a free viewing paradigm on natural scenes, free of photographer bias, with advanced data processing techniques that correct for overlap effects and co-varying non-linear dependencies of multiple eye movement parameters. We validate this approach by replicating classic N170 effects in neural responses, triggered by fixation onsets (fixation event-related potentials [fERPs]). Importantly, besides finding a strong correlation between both experiments, our more natural stimulus paradigm yielded smaller variability between subjects than the classic setup. Moving beyond classic temporal and spatial effect locations, our experiment furthermore revealed previously unknown signatures of face processing: This includes category-specific modulation of the event-related potential (ERP)'s amplitude even before fixation onset, as well as adaptation effects across subsequent fixations depending on their history.

Towards real-world neuroscience using mobile EEG and augmented reality

Our visual environment impacts multiple aspects of cognition including perception, attention and memory, yet most studies traditionally remove or control the external environment. As a result, we have a limited understanding of neurocognitive processes beyond the controlled lab environment. Here, we aim to study neural processes in real-world environments, while also maintaining a degree of control over perception. To achieve this, we combined mobile EEG (mEEG) and augmented reality (AR), which allows us to place virtual objects into the real world. We validated this AR and mEEG approach using a well-characterised cognitive response-the face inversion effect. Participants viewed upright and inverted faces in three EEG tasks (1) a lab-based computer task, (2) walking through an indoor environment while seeing face photographs, and (3) walking through an indoor environment while seeing virtual faces. We find greater low frequency EEG activity for inverted compared to upright faces in all experimental tasks, demonstrating that cognitively relevant signals can be extracted from mEEG and AR paradigms. This was established in both an epoch-based analysis aligned to face events, and a GLM-based approach that incorporates continuous EEG signals and face perception states. Together, this research helps pave the way to exploring neurocognitive processes in real-world environments while maintaining experimental control using AR.

Synchronization of acquisition devices in neuroimaging: An application using co-registration of eye movements and electroencephalography

Interest in applications for the simultaneous acquisition of data from different devices is growing. In neuroscience for example, co-registration complements and overcomes some of the shortcomings of individual methods. However, precise synchronization of the different data streams involved is required before joint data analysis. Our article presents and evaluates a synchronization method which maximizes the alignment of information across time. Synchronization through common triggers is widely used in all existing methods, because it is very simple and effective. However, this solution has been found to fail in certain practical situations, namely for the spurious detection of triggers and/or when the timestamps of triggers sampled by each acquisition device are not jointly distributed linearly for the entire duration of an experiment. We propose two additional mechanisms, the "Longest Common Subsequence" algorithm and a piecewise linear regression, in order to overcome the limitations of the classical method of synchronizing common triggers. The proposed synchronization method was evaluated using both real and artificial data. Co-registrations of electroencephalographic signals (EEG) and eye movements were used for real data. We compared the effectiveness of our method to another open source method implemented using EYE-EEG toolbox. Overall, we show that our method, implemented in C++ as a DOS application, is very fast, robust and fully automatic.

The extrafoveal preview paradigm as a measure of predictive, active sampling in visual perception

A key feature of visual processing in humans is the use of saccadic eye movements to look around the environment. Saccades are typically used to bring relevant information, which is glimpsed with extrafoveal vision, into the high-resolution fovea for further processing. With the exception of some unusual circumstances, such as the first fixation when walking into a room, our saccades are mainly guided based on this extrafoveal preview. In contrast, the majority of experimental studies in vision science have investigated "passive" behavioral and neural responses to suddenly appearing and often temporally or spatially unpredictable stimuli. As reviewed here, a growing number of studies have investigated visual processing of objects under more natural viewing conditions in which observers move their eyes to a stationary stimulus, visible previously in extrafoveal vision, during each trial. These studies demonstrate that the extrafoveal preview has a profound influence on visual processing of objects, both for behavior and neural activity. Starting from the preview effect in reading research we follow subsequent developments in vision research more generally and finally argue that taking such evidence seriously leads to a reconceptualization of the nature of human visual perception that incorporates the strong influence of prediction and action on sensory processing. We review theoretical perspectives on visual perception under naturalistic viewing conditions, including theories of active vision, active sensing, and sampling. Although the extrafoveal preview paradigm has already provided useful information about the timing of, and potential mechanisms for, the close interaction of the oculomotor and visual systems while reading and in natural scenes, the findings thus far also raise many new questions for future research.

Regression-based analysis of combined EEG and eye-tracking data: Theory and applications

Fixation-related potentials (FRPs), neural responses aligned to the end of saccades, are a promising tool for studying 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/electroencephalogram experiments: (1) the synchronization of data streams, (2) the removal of ocular artifacts, (3) the condition-specific temporal overlap between the brain responses evoked by consecutive fixations, and (4) the fact that numerous low-level stimulus and saccade properties also influence the postsaccadic neural responses. Although effective solutions exist for the first two problems, the latter two are only beginning to be addressed. In the current paper, we present and review a unified regression-based framework for FRP analysis that allows us to deconvolve overlapping potentials while also controlling for both linear and nonlinear confounds on the FRP waveform. An open software implementation is provided for all procedures. We then demonstrate the advantages of this proposed (non)linear deconvolution modeling approach for data from three commonly studied paradigms: face perception, scene viewing, and reading. First, for a traditional event-related potential (ERP) face recognition experiment, we show how this technique can separate stimulus ERPs from overlapping muscle and brain potentials produced by small (micro)saccades on the face. Second, in natural scene viewing, we model and isolate multiple nonlinear effects 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 eye movement-related brain activity during natural vision.

Fixation-related Brain Potentials during Semantic Integration of Object–Scene Information

In vision science, a particularly controversial topic is whether and how quickly the semantic information about objects is available outside foveal vision. Here, we aimed at contributing to this debate by coregistering eye movements and EEG while participants viewed photographs of indoor scenes that contained a semantically consistent or inconsistent target object. Linear deconvolution modeling was used to analyze the ERPs evoked by scene onset as well as the fixation-related potentials (FRPs) elicited by the fixation on the target object (t) and by the preceding fixation (t − 1). Object–scene consistency did not influence the probability of immediate target fixation or the ERP evoked by scene onset, which suggests that object–scene semantics was not accessed immediately. However, during the subsequent scene exploration, inconsistent objects were prioritized over consistent objects in extrafoveal vision (i.e., looked at earlier) and were more effortful to process in foveal vision (i.e., looked at longer). In FRPs, we demonstrate a fixation-related N300/N400 effect, whereby inconsistent objects elicit a larger frontocentral negativity than consistent objects. In line with the behavioral findings, this effect was already seen in FRPs aligned to the pretarget fixation t − 1 and persisted throughout fixation t, indicating that the extraction of object semantics can already begin in extrafoveal vision. Taken together, the results emphasize the usefulness of combined EEG/eye movement recordings for understanding the mechanisms of object–scene integration during natural viewing.

Eye Movements and Fixation-Related Potentials in Reading: A Review

The present review is addressed to researchers in the field of reading and psycholinguistics who are both familiar with and new to co-registration research of eye movements (EMs) and fixation related-potentials (FRPs) in reading. At the outset, we consider a conundrum relating to timing discrepancies between EM and event related potential (ERP) effects. We then consider the extent to which the co-registration approach might allow us to overcome this and thereby discriminate between formal theoretical and computational accounts of reading. We then describe three phases of co-registration research before evaluating the existing body of such research in reading. The current, ongoing phase of co-registration research is presented in comprehensive tables which provide a detailed summary of the existing findings. The thorough appraisal of the published studies allows us to engage with issues such as the reliability of FRP components as correlates of cognitive processing in reading and the advantages of analysing both data streams (i.e., EMs and FRPs) simultaneously relative to each alone, as well as the current, and limited, understanding of the relationship between EM and FRP measures. Finally, we consider future directions and in particular the potential of analytical methods involving deconvolution and the potential of measurement of brain oscillatory activity.

Influence of reading skill and word length on fixation-related brain activity in school-aged children during natural reading

Word length is one of the main determinants of eye movements during reading and has been shown to influence slow readers more strongly than typical readers. The influence of word length on reading in individuals with different reading skill levels has been shown in separate eye-tracking and electroencephalography studies. However, the influence of reading difficulty on cortical correlates of word length effect during natural reading is unknown. To investigate how reading skill is related to brain activity during natural reading, we performed an exploratory analysis on our data set from a previous study, where slow reading (N = 27) and typically reading (N = 65) 12-to-13.5-year-old children read sentences while co-registered ET-EEG was recorded. We extracted fixation-related potentials (FRPs) from the sentences using the linear deconvolution approach. We examined standard eye-movement variables and deconvoluted FRP estimates: intercept of the response, categorical effect of first fixation versus additional fixation and continuous effect of word length. We replicated the pattern of stronger word length effect in eye movements for slow readers. We found a difference between typical readers and slow readers in the FRP intercept, which contains activity that is common to all fixations, within a fixation time-window of 50-300 ms. For both groups, the word length effect was present in brain activity during additional fixations; however, this effect was not different between groups. This suggests that stronger word length effect in the eye movements of slow readers might be mainly due re-fixations, which are more probable due to the lower efficiency of visual processing.

Optimizing the ICA-based removal of ocular EEG artifacts from free viewing experiments

Combining EEG with eye-tracking is a promising approach to study neural correlates of natural vision, but the resulting recordings are also heavily contaminated by activity of the eye balls, eye lids, and extraocular muscles. While Independent Component Analysis (ICA) is commonly used to suppress these ocular artifacts, its performance under free viewing conditions has not been systematically evaluated and many published reports contain residual artifacts. Here I evaluated and optimized ICA-based correction for two tasks with unconstrained eye movements: visual search in images and sentence reading. In a first step, four parameters of the ICA pipeline were varied orthogonally: the (1) high-pass and (2) low-pass filter applied to the training data, (3) the proportion of training data containing myogenic saccadic spike potentials (SP), and (4) the threshold for eye tracker-based component rejection. In a second step, the eye-tracker was used to objectively quantify the correction quality of each ICA solution, both in terms of undercorrection (residual artifacts) and overcorrection (removal of neurogenic activity). As a benchmark, results were compared to those obtained with an alternative spatial filter, Multiple Source Eye Correction (MSEC). With commonly used settings, Infomax ICA not only left artifacts in the data, but also distorted neurogenic activity during eye movement-free intervals. However, correction results could be strongly improved by training the ICA on optimally filtered data in which SPs were massively overweighted. With optimized procedures, ICA removed virtually all artifacts, including the SP and its associated spectral broadband artifact from both viewing paradigms, with little distortion of neural activity. It also outperformed MSEC in terms of SP correction. Matlab code is provided.

Unfold: an integrated toolbox for overlap correction, non-linear modeling, and regression-based EEG analysis

Electrophysiological research with event-related brain potentials (ERPs) is increasingly moving from simple, strictly orthogonal stimulation paradigms towards more complex, quasi-experimental designs and naturalistic situations that involve fast, multisensory stimulation and complex motor behavior. As a result, electrophysiological responses from subsequent events often overlap with each other. In addition, the recorded neural activity is typically modulated by numerous covariates, which influence the measured responses in a linear or non-linear fashion. Examples of paradigms where systematic temporal overlap variations and low-level confounds between conditions cannot be avoided include combined electroencephalogram (EEG)/eye-tracking experiments during natural vision, fast multisensory stimulation experiments, and mobile brain/body imaging studies. However, even "traditional," highly controlled ERP datasets often contain a hidden mix of overlapping activity (e.g., from stimulus onsets, involuntary microsaccades, or button presses) and it is helpful or even necessary to disentangle these components for a correct interpretation of the results. In this paper, we introduce unfold, a powerful, yet easy-to-use MATLAB toolbox for regression-based EEG analyses that combines existing concepts of massive univariate modeling ("regression-ERPs"), linear deconvolution modeling, and non-linear modeling with the generalized additive model into one coherent and flexible analysis framework. The toolbox is modular, compatible with EEGLAB and can handle even large datasets efficiently. It also includes advanced options for regularization and the use of temporal basis functions (e.g., Fourier sets). We illustrate the advantages of this approach for simulated data as well as data from a standard face recognition experiment. In addition to traditional and non-conventional EEG/ERP designs, unfold can also be applied to other overlapping physiological signals, such as pupillary or electrodermal responses. It is available as open-source software at http://www.unfoldtoolbox.org.

Presaccadic EEG activity predicts visual saliency in free-viewing contour integration

While viewing a scene, the eyes are attracted to salient stimuli. We set out to identify the brain signals controlling this process. In a contour integration task, in which participants searched for a collinear contour in a field of randomly oriented Gabor elements, a previously established model was applied to calculate a visual saliency value for each fixation location. We studied brain activity related to the modeled saliency values, using coregistered eye tracking and EEG. To disentangle EEG signals reflecting salience in free viewing from overlapping EEG responses to sequential eye movements, we adopted generalized additive mixed modeling (GAMM) to single epochs of saccade-related EEG. We found that, when saliency at the next fixation location was high, amplitude of the presaccadic EEG activity was low. Since presaccadic activity reflects covert attention to the saccade target, our results indicate that larger attentional effort is needed for selecting less salient saccade targets than more salient ones. This effect was prominent in contour-present conditions (half of the trials), but ambiguous in the contour-absent condition. Presaccadic EEG activity may thus be indicative of bottom-up factors in saccade guidance. The results underscore the utility of GAMM for EEG-eye movement coregistration research.