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Table of contents
As cognitive processes have an evident influence on eye movements [ 4 ], changes in gaze pattern due to differences in conditions reflect the mixing of brain activity from different sources in the latter parts of the averaged epoch [ 40 ]. We propose to untangle this issue by analysing the time courses of these underlying activity patterns by separating them with blind-source separation methods, such as ICA [ 36 , 41 ]. Even though identifying and removing artefactual signals with ICA from the signal of interest is the typical use in contemporary EEG analysis [ 42 ], ICA can also be applied to separate brain signals from each other.
This can be of particular interest for late latency components, which typically have multiple neural sources, or when there are multiple overlapping sensory responses. The underlying assumptions of ICA place certain restrictions on the nature of the sources detected. First, a signal arising from a spatial source is assumed to be temporally independent from other spatial sources [ 36 , 41 ]. Second, the spatial source is assumed to be in a fixed location throughout the duration of the measurement of the data of interest [ 43 ].
As independent components are defined as spatially fixed sources that change in activity through time, several interesting possibilities arise. Second, data from several experiments from the same subject can be inserted into the same decomposition to determine whether different experiments share psychological processes and underlying neural mechanisms [ 42 ]. Third, a decomposition analysis run can also include data from multiple subjects, and thus the obtained group solutions can be applied to all of the subjects [ 45 ]. Hence, the application of ICA beyond artefact cleaning is a promising approach for FRP experiments on natural reading, as the stationarity of sources provides a solution to the ever-present spatio-temporal overlap of activity from previous and consequent fixations and their potential confounds to the scalp signal.
Running ICA across a sample of participants also reduces measurement-related error variation e. In the current study, we employed a group ICA procedure to disentangle spatially overlapping processes during sentence reading and when encountering semantic anomalies in the sentences.
A total of 66 typically reading elementary school students in grade 6 from Written consent was acquired from the parents of the participants, and the children had the opportunity to discontinue the experiment at any time. The experiment was administered using Experiment Builder 1.
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Both eyes were recorded at Hz. The synchrony between the eye movements and EEG measures was established with a combination of triggering Ethernet messages and transistor to transistor logic TTL pulses, both originating from the workstation running the experiment. The stability of the synchronisation between the eye-tracker recording and EEG was checked by comparing the time differences in the trial onset and offset messages in both data streams.
The black dots also served as confirmation for the validity of the calibration. If the fixation on the dot differed from the calibration by more than 1 degree, the experiment software alerted the experimenter, and the calibration was redone. After the experimenter accepted the fixation, the fixation dot disappeared, and the sentence appeared. There was no time limit for responding, and the sentence disappeared only after the response. The experiment was divided into four blocks, between which the eye tracker was recalibrated and the quality of the EEG maintained.
The stimuli consisted of sentences with a median length of six words ranging from 5 to 9. On the screen, one letter subtended 0.
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The sentences were divided into three categories: plausible sentences, 50 sentences where the target word was severely anomalous to preceding sentence context and 50 sentences where the target word was severely anomalous to the preceding context but was an orthographic word neighbour of a plausible word. Examples of the sentences are presented in Fig 1. The frequency of the target words and the previous words was controlled for 2x3 repeated measures ANOVA: previous word vs.
The frequencies of the target and previous words Table 1 were extracted from a newspaper corpus [ 49 ]. Also the plausible ending of the sentences in the anomalous word neighbour condition was included in the norming study. These norms are presented in Table 1. The part of the sentence that deviates from the context is highlighted in red.
Frequencies mean incidence in 1 million words of target and preceding words with standard deviations. Data were preprocessed using Eeglab The saccades were detected from the gaze location data with a median velocity-based algorithm [ 50 ], using 6 standard deviations from the median velocity as a threshold for a saccade minimum duration of 4ms; if the two saccades were less than 50ms apart from each other, they were merged into a single saccade.
EEG data were off-line filtered, with a high-pass filter of 0. Electric manifestations of eye movements ocular artefacts were modelled with ICA, with a PCA principal component analysis reduction of the channels to principal components prior to the ICA training. The components were selected to correspond with the optical recording of eye movements using the temporal covariance criterion [ 37 ] of 1. After the ocular artefact pruning, the EEG epochs with the fixations of interest were selected. These included the first fixation on the target word and the previous fixation.
If the previous fixation was not on the word preceding the target word, the whole trial was discarded to make the baseline segments of the FRP similar. Epochs for averaging were ms to ms, time-locked to the fixation onset. Trials with both correct and incorrect answers were kept.
Fixations and their corresponding epochs were discarded if the EEG during the averaging epoch differed by more than 5 standard deviations from the mean on any channel or if the trial ended within the ms after first fixation on the target word to avoid confounding activity from trial offset. Segmented single trial data ms to ms were subjected to a second run of ICA to determine shared fixation-related components.
Prior to ICA, the data for each subject were standardised basic z-score conversion so that individuals with strong voltages would not drive the ICA decomposition. The data were downsampled to Hz to make computational requirements feasible, and the group matrix was whitened to 30 principal components with PCA. Extended Infomax, an ICA algorithm sensitive to sub-Gaussian distributions [ 51 ], was used because it has been shown to produce good results with non-simulated group EEG data [ 52 ].
The resulting group-level ICA weights were then applied to the Hz individual data, and the resulting IC activities were used for statistical inference. Ten of the 30 components were determined by visual inspection to be such that they could be generated by a cortical source by displaying a dipolar pattern.
Pattern was judged to be dipolar if it had either 1-pole uniform field on several adjacent channels or 2-pole field on several adjacent channels and nearby polarity reversal. Components judged to be noise were pruned out of the data if they displayed known artefact characteristics eye movements, single channel pop-out artefacts. Topographies of all components derived with the group ICA are presented in Fig 2. Components 1, 2, 3, 4, 5, 6, 7, 9, 11 and 12 were retained in the data because they were judged to have a dipolar field structure and thus were likely be generated by brain tissue.
Components 8 and 10 were pruned out of the data since they were judged to be likely to have been caused by eye movements. Components 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29 and 30 were pruned out of the data because they were judged to be random pop-out artefacts and mechanical artefacts mostly constrained to few channels. PVAF percentage of variance accounted for values for each component.
The average quantity of fixations and the corresponding epochs for averaging for each condition were as follows: plausible 83, unrelated anomalous 41 and word neighbour anomalous 41 fixations. The effects of the conditions on response accuracy were analysed using a Wilcoxon sign-rank test, from which we report Z-values, P-values and effect sizes [ 53 ].
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Based on the eye-movement variables, the previous fixation duration PFD , the first fixation duration, gaze duration and immediate re-fixations were analysed. Because trials that were ended with a participant response within ms of the first fixation onset were discarded, the re-fixation measure here is a binary measure of regression to earlier parts of the sentence vs.
The estimated random structure was simple intercept structure for trials and subjects. The mean values of the eye-movement variables are presented in Table 3 and also in Fig 3. Bar graph presentation of the behavioural measures; exact values are presented in Table 3.
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A Percentage of correct answers, B Fixation durations of the previous fixation PFD and the first fixation FFD and C Re-fixation probability RFP after the first fixation on the target word in a semantic sensibility judgement task in a sentence reading context of to The error bars denote 1 standard error. FRPs were analysed with nonparametric cluster-based pairwise permutation statistics in Besa statistics 2. Nonparametric cluster-based permutation tests have two essential steps. First, the desired test here normal t-test is run over all channels when done at the scalp level and time-points.
Here, these criteria were temporal adjacency significant samples were consecutive and an electrode distance of 3cm a significant sample in the electrode was part of a cluster if the distance from another significant sample in another electrode was less than 3cm. All t-values of the clusters each sample, each electrode are summed to form the cluster test statistic, which is used to estimate test significance. Second, the distribution to estimate this test statistic is generated by randomly re-assigning the condition labels in each average and running the test and clustering procedure again and storing the results in the permutation distribution.
When the real observed sum-t probability in contrast to permutation distribution is smaller than 0. We used 10, permutations to define the permutation distribution. With three conditions, the pairwise condition contrasts for the permutation statistics were as follows: unrelated anomalous vs. For the sake of simplicity, when we use the terms negative or positive in the results section, they describe the amplitude difference between the first response and the second response in the paired comparison.
The cluster was initially observed in the occipital fringe channels, from which it moved to central parietal locations roughly ms onwards. Coloured bars under each channel highlight time-points with significant differences that belong to a cluster in the nonparametric permutation test. The zero time-point is the onset of the first fixation on the target word. The scale depicts differences between the first element of the pair to the second element of the pair in values of the test statistic t. Rectangles signify that the sensor displays a statistically significant difference and belongs to a cluster.
The colour of the stars within the squares signifies membership in a specific cluster. The behavioural results suggest clear and strong effects of semantic anomaly, as the FFDs, GDs and RFPs on the target words all show similar results with increased reading time to anomalous target words. Response accuracy was highest for the unrelated anomalous condition than for the responses for the plausible and anomalous word neighbour conditions. It is important to note, however, that the PFDs in the pre-target word do not show any effects of the semantic manipulation. This effectively shows that the processing shares the same trajectory until the first fixation on the target word.
The topographical analysis of the FRPs time-locked to the first fixation onset show a systematic pattern of early frontal negativity at ca —ms and late parietal positivity at ca —ms for both of the anomalous target word categories. The differences between conditions that we observe are long and widespread. This may, in part, also be due to continuous reading being analogous of the RSVP with fast stimulus rates; fast presentation rates have been shown to diminish N and P amplitudes in adults [ 18 ].
The relatively late parietal positivity can fairly reliably be identified as P The P difference between anomalous word neighbour and plausible conditions was later than for the unrelated anomalous vs. This may suggest that semantic processing of the word neighbour anomalous words of plausible words is delayed in relation to the semantic processing of unrelated anomalous words.
The frontal negativity observed for both anomalous conditions begins quite early and lasts through the remainder of the FRP waveform. One possibility is that this pattern is related to the age difference of our subjects compared to most of the N literature reporting adult responses.
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- Total Number of words made out of Anomaly = 62.
However, support for the age-related shift of the N topography in the previous literature is scarce and relatively old [ 55 ]. Thus, the argument for developmental differences is suggested here and would require more systematic developmental study with a traditional RSVP experimentation style.
A reasonable line of thought could also be to relate the current results to the evidence of early contributions of the dorsolateral frontal cortex to visual processing [ 56 ].
These contributions have been assumed to be of a top-down nature [ 57 , 58 ], and thus one cannot rule out the possibility that these effects are in fact also modulating the fixation durations or saccade targeting refixation or regression either directly or indirectly. The possible contribution of saccadic control is supported by the fact that the difference topography is directly on the top of structures that include frontal eye fields FEFs [ 56 ].
However this cannot be determined by topographical analysis alone. Thus, this claim would gain more support from source analysis and the interpretation would be constrained by providing information regarding the source time behaviour and location estimates.