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Title: Hierarchical Neural Processing in γ Oscillations for Syntactic and Semantic Operations Accounts for First and Second Language Epistemology Open Access Deposited

http://creativecommons.org/licenses/by-nc/4.0/
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Abstract
  • We discuss event-related power differences (ERPDs) in low- and broadband-γ oscillations as the embedded-clause edge is processed in wh-dependencies such as Which decision regarding/about him/her did Paul say that Lydie rejected without hesitation? in first (L1) and second language (L2) French speakers. The experimental conditions manipulated whether pronouns appeared in modifiers (Mods; regarding him/her) or in noun complements (Comps; about him/her) and whether they matched or mismatched a matrix-clause subject in gender. Across L1 and L2 speakers, we found that anaphora-linked ERPDs for Mods vs. Comps in evoked power first arose in low γ and then in broadband γ. Referential elements first seem to be retrieved from working memory by narrowband processes in low-γ and then referential identification seems to be computed in broadband-γ output. Interactions between discourse- and syntax-based referential processes for the Mods vs. Comps in these ERPDs furthermore suggest that multidomain γ-range processing enables a range of elementary operations for discourse and semantic interpretation. We argue that a multidomain mechanism enabling operations conditioned by the syntactic and semantic nature of the elements processed interacts with local brain microcircuits representing features and feature sets that have been established in L1 or L2 acquisition, accounting for a single language epistemology across learning contexts.
Methodology
  • Materials and methods This research was approved by the Indiana University Institutional Review Board. At the start of the experimental session, participants read the study’s Statement of Informed Consent. They were asked whether they had any questions and whether they consented to participate in the study. They provided verbal consent to the researcher, in line with the approved IRB Protocol, and were reminded that they could withdraw at any point. The stimuli consisted of 200 trials. The 25 experimental quadruples representing 100 trials are exemplified in (1a-d). (1a, c) involve Mod structures. (1b, d) involve Comp structures. (1a, b) involve a matrix subject that matches the gender of the pronoun inside the wh-filler and (1c, d) involve a matrix subject that does not. 50% of trials involved masculine referents/pronouns and 50% of trials involved feminine referents/pronouns. 100 distractor items involved complex interrogative structures and permutations like the target items, counterbalanced so that no grouping stood out. The stimuli appeared in four blocks presented in random order and with randomization within each block, and crucially, no two items from a set ever appeared in the same block. The greater variability inherent among L2 speakers, e.g., in vocabulary size and experience with the language, needs to be mitigated in L2 research. Hence, presenting all items in a set like (1a-d) to participants enables a representative understanding of L2 grammatical processing ability, which might otherwise be diluted by differences in lexical access difficulty across conditions. E-prime (version 2016) delivered the stimuli. Each sentence appeared word by word at the center of the screen in 36-point Consolas font, using normal orthographic conventions. Participants sat in a chair facing a computer monitor about four feet away. A fixation cross at the center of the screen preceded each item, lasting 700ms. During the stimulus presentation, each word appeared for 300ms and was followed by a 250ms blank screen. Due to the time required for E-prime to load each word and for the monitor’s refresh rate, the total presentation time was 566ms (300ms word presentation, 250ms interstimulus interval, and a 16ms refresh rate between words). It accommodated L2 speakers without being unnaturally slow for L1 speakers. Indeed, the task was found to be strenuous but manageable to advanced L2 speakers in stimuli preparation. Respondents were trained to read questions like the stimuli and then complete true-false comprehension checks, which were presented in their entirety for a maximum of 3500ms. These comprehension checks were of several types: Some examined a pronoun’s anaphoric interpretation, while others queried other aspects of the sentences. Participants were asked to quickly respond to the statements by pressing the left arrow key for ‘True’ and the right arrow key for ‘False.’ There was a training session of six items, which could be repeated before moving on to the experiment. In the training, all items were followed by a comprehension check; in the task, only two thirds were. This rate maintained participant attention without being overly taxing. Naturally, a set of questions like our stimuli seems plausible in only a limited set of situations. Thus, respondents were introduced to a context involving two friends who were devoted followers of a television series. One of the friends, however, had missed some episodes and asked the other some questions to catch up. Participants and testing procedures Following Lewis, Lemhöfer, et al.’s (2016) examination of oscillations in 20 L1 speakers and 20 L2 speakers, we selected a sample size of 48 participants, with two groups of 24. We report results from 24 L1 speakers of French (20 right-handed; 4 left-handed) and 24 L2 speakers of French (23 right-handed; 1 left-handed). Grey et al. (2017) argued that neurocognitive models of language “largely formulated around data from only right-handers” (p. 27) problematically ignore variability in neurologically healthy populations. A cortical hierarchical γ operational workspace for language should hold across neuroanatomical diversity associated with handedness. Lateralization does not fully mirror the direction of handedness, as the majority of left-handers are left-lateralized for language; but the proportion of people with bilateral or right lateralization is higher in left-handers than right-handers (e.g., Woodhead et al., 2021). Furthermore, recent neurological models have argued for bilateralization in the lexical interface and combinatorial syntax-semantics mappings in speech processing (e.g., Hickok & Poeppel, 2007). However, given the long-standing practice of excluding left-handers from processing studies, the possible influence of handedness was addressed by comparing effects for the general population with effects for right-handers only. After providing biographical information, participants completed a C-test to gauge their overall proficiency in French. A C-test involves paragraph-length texts in which the second half of every other word is removed. The C-test (Renaud, 2010) consisted of two unrelated texts with 50 partially missing words (25 content words and 25 function words) across the two paragraphs. Respondents were given 5 minutes per paragraph to fill in the missing parts of the words. C-tests were scored for accuracy out of 50 points. Finally, participants completed the EEG task, with each of the four blocks lasting 13 minutes; including breaks, the total task time was around 1 hour. These procedures ensured that the subjects would not be fatigued and could be expected to stay engaged. The 24 L1 speakers of French (average age = 26.6, SD = 4.32) were tested in the US. They had, on average, lived abroad for 2.4 years (SD = 2.61) at the time of testing. The average C-test score was 48.7/50, with a range from 45-50. The 24 L2 speakers of French (average age = 28.8, SD = 6.37) began acquiring French during secondary schooling or later. These participants were graduate students and advanced undergraduate students in the US at the time of testing. They had an average total length of stay of 1.2 years (SD = 0.69) in a Francophone country. C-test scores (average 45.5/50; range 33-50) clearly indicated that they were well above intermediate-level proficiency (typical score range 25-30). All participants were college-educated individuals with no history of dyslexia. Accuracy rates on factual comprehension checks show the task to be challenging: 61% for L1 speakers and 63% for L2 speakers. On comprehension checks related to anaphoric interpretation, L1 and L2 speakers alike interpreted the pronoun as referring to the gender-matched noun phrase 70% of the time. However, comprehension check accuracy of participants was not used as a filter for analysis: γ oscillations in basic referential chain formation constitute essential processes in unconscious implicit ongoing processing of the input. Such procedural knowledge is quite distinct from conscious judgements made by speakers regarding intended meanings or linked to longer-term memory for the entire sentence. In terms of reference queries, anaphoric interpretations, although preferred, are not solely required. Even when an anaphoric dependency is preferred, deixis is never excluded. Generally, real-time basic brain processing as participants compute a bi-clausal filler-gap dependency is expected to be independent of their behavior on comprehension checks following individual sentences. EEG procedures EEG was recorded at a 1000Hz sampling rate via a 64-electrode EGI system (Electrical Geodesics Inc., Eugene, OR; as displayed in Figure 3) referenced to Cz (vertex) online. The signal was collected using a Net Amps 300 amplifier with a gain of 5000 and acquisition software Netstation (version 4.5.4). Impedances were verified to be below 50 kΩ before each of the 4 blocks in the task. All preprocessing and data cleaning procedures were performed using the EEGLAB toolbox based on MATLAB (version 9.5) (Delorme & Makeig, 2004). An 8ms latency shift due to the amplifier was corrected before preprocessing. Line noise was removed using the CleanLine plugin for EEGLAB (Mullen, 2012). The continuous data were then divided into 5.2-second epochs starting with est-ce que (the question marker) and running to the end of the sentence. Following segmentation, we visually inspected each epoch for bad channels and, if a channel was bad in more than 10% of epochs, we removed the whole channel. It has been demonstrated that muscle activity can create noise in high-frequency EEG measures, and γ-band results should thus be reported and interpreted with caution (e.g., Yuval-Greenberg et al., 2008). Hipp and Siegel (2013) showed that removing such artifacts from the EEG recording through rejecting data sections affected by artifactual signals or Independent Component Analysis (ICA) can allow for more confident analysis of high-frequency EEG. Therefore, we visually inspected each epoch and systematically removed any epoch including unexpected EMG activity (i.e., furrowing of the brow, face and neck movements, but not blinks). We used the binica algorithm for ICA to extract and then manually check the 32 most impactful components generated by principal component analysis (PCA) so that we could effectively remove the remaining ocular and cardiac activity, among any remaining artifacts. Twelve additional participants with greater than 10% bad channels or greater than 30% bad epochs were excluded from analysis, leaving the 24 L1 and 24 L2 speakers described above. An average of 85% of trials was retained across subjects (SD = 2.20). The average number of trials retained was similar across conditions, (1a), M = 21.31, SD = 2.23; (1b), M = 21.06, SD = 2.02; (1c), M = 21.17, SD = 2.42; (1d), M = 21.27, SD = 2.12; p = .91, with no differences across groups (NS: M = 21.21, SD = 2.13; L2 speakers: M = 21.20, SD = 2.28, p = .93). For L1 speakers, 290 components were rejected, for an average of 12 per subject; for L2 speakers, 345 components were rejected, for an average of 14 per subject; and for the whole population, 635 components were rejected, for an average of 13 per subject. These may seem at first like high numbers of components to remove. However, our 5.2-second epochs are much longer than in most research, and longer epochs are likely to contain more noise than shorter ones. Because component removal for artifacts may risk removing some brain activity, the procedure is conservative in terms of finding effects. No significant difference arose between groups in the number of components removed (p = .35). The data were average referenced and missing channels were interpolated for the time-frequency analysis. Time-frequency analysis The preprocessed EEG data were loaded into the FieldTrip toolbox (Oostenveld et al., 2011) as eight datasets for the structural conditions (1a - 1d) and two groups (L1 vs. L2 ). The time window of theoretical interest is constituted by the two critical bridge words dit que ‘said that,’ lasting 1132ms, 566ms for each word. The 750ms prior to the onset of the target word dit ‘said’ was included as a baseline period, for a total selected time window of 1882ms. Building on Dekydtspotter et al. (2023), which reported ERPDs in induced power in the β band, we examined γ-band activity in evoked power that reflects both time-locked and phase-locked oscillatory responses. We first calculated the ERPs of each condition for each subject. . Next, we convolved a family of Morlet wavelets of 7 cycles in .5Hz steps with the selected time window of each EEG trial, which yielded the time-frequency information of the neural activity. The length of the wavelets was set as 3 standard deviations of the Gaussian kernel. At 60Hz, the wavelet duration was 0.037 seconds. The spectral bandwidth was 17.143Hz. We log-transformed (10*log10) the derived power in Fieldtrip to standardize the unit as decibels at each of the frequencies between 30 and 120Hz for each condition of each subject in each group. The transformed power data for L1 speakers and L2 speakers was used as the basis of the following statistical analysis. Data analysis Our experiment followed a mixed between-within-subjects 2×2 factorial design for two groups. The first factor was structural conditions (Mod-Comp power differences in matrix-clause antecedent match vs. mismatch) and the second factor was group (L1 vs. L2), with the between-subject factor being the L1 vs. L2 status. We, therefore, used a 2×2 factorial model simultaneously accounting for between-subject variance and within-subject variance for the two units of observation in the data, which allows for the detection of patterns across L1 and L2 status as well as differences between groups. Procedures for a 2×2 factorial model avoid making non-statistically supported claims for superficial L1 vs. L2 differences by taking both within- and between-subject variances into consideration simultaneously. Indeed, as Cheng et al. (2021) argued, “researchers’ constructed categories...ignore the ways in which these artificially “different” groups could be similar in their perception and production of language” (p. 8). Data were analyzed with cluster-based nonparametric permutation tests to avoid the multiple comparison problem for our medium-density electrodes, on the assumption that the spatially adjacent channels exhibit similar spectral-temporal features (Groppe et al., 2011; Larson-Hall, 2016; Maris et al., 2007). We conducted two types of nonparametric statistical tests (paired-sample and independent-sample t-tests) using Monte Carlo simulations with 1000 random samplings for each channel-frequency-time triplet. As we are interested in the broadband hierarchical processing across the γ band and the narrowband processes of retrieval in low γ frequencies, we used two bins: first, 30-120Hz, to identify hierarchical processing in broadband γ, and then 30-50Hz (low γ), given the specific role of narrowband activity in cortical-subcortical transfer. We calculated Mod-Comp power differences between the antecedent match [(1a) - (1b)] and antecedent mismatch [(1c) - (1d)] conditions to address whether distinct allocations of resources to Comps vs. Mods can be found across L1 and L2 status. Power differences were analyzed with paired-sample t-tests using the maximum of the cluster t-test statistics with 1000 permutations. Bonferroni correction was performed to correct the multiple comparison problem due to the two frequency bins, so the corrected alpha level is α = .050/2 = .025. We first examined γ oscillations in L1 and L2 speakers, including both left- and right-handed respondents (Grey et al., 2017). To guard against a possible effect of different lateralization patterns in the entire population, we conducted post-hoc analyses of the exact patterns of frequency and electrode distribution on just the right-handed respondents. This ensured that the exact patterns detected for the entire population also arose in subjects with the same handedness. Because an effect of handedness effect might still be possible, we then re-ran the original analysis described above on just the right-handed respondents to compare with the original results. At each step, we adopted a Bonferroni protection for multiple comparisons.    To address possible L1-L2 differences, we compared Mod-Comp power differences [(1a+c) - (1b+d)] between L1 and L2 speakers using independent-sample t-tests using the maximum of the cluster t-test statistics with 1000 permutations. We again adopted a Bonferroni correction of α = .025 for two bins. We also examined Conditions*Group interactions between L1 vs. L2 speaker status and Mod vs. Comp structure in match vs. mismatch. FieldTrip does not provide automated interaction estimation. Therefore, following recommended procedures ( https://www.fieldtriptoolbox.org/faq/how_can_i_test_an_interaction_effect_using_cluster-based_permutation_tests/), we calculated Mod-Comp power differences between the antecedent match [(1a) - (1b)] and antecedent mismatch [(1c) - (1d)] conditions for each group. The dependent variable is therefore the difference between these power differences ([(1a) - (1b)] - [(1c) - (1d)]) for each group during the processing of dit que ‘said that’. Independent-sample t-tests based on permutations were performed on this difference of differences with a Bonferroni correction of α = .025 for two bins. Across our analysis, permutation tests provide the time window and electrodes in which a significant effect arises. They, however, lack precision as to the exact timing and location of effects (Sassenhagen & Draschkow, 2019). Our discussion of the timing of ERPD effects is therefore limited to the window in which the effects are found. (1a) Quelle décision le concernant est-ce que Paul a dit que Lydie avait rejetée which decision him regarding is-it that Paul has said that Lydie had rejected sans hésitation ? without hesitation ‘Which decision regarding him did Paul say that Lydie had rejected without hesitation?’ (1b) Quelle décision à propos de lui est-ce que Paul a dit que Lydie avait rejetée which decision at words of him is-it that Paul has said that Lydie had rejected sans hésitation ? without hesitation ‘Which decision about him did Paul say that Lydie had rejected without hesitation?’ (1c) Quelle décision le concernant est-ce que Lydie a dit que Paul avait rejetée which decision him regarding is-it that Lydie has said that Paul had rejected sans hésitation ? without hesitation ‘Which decision regarding him did Lydie say that Paul had rejected without hesitation? (1d) Quelle décision à propos de lui est-ce que Lydie a dit que Paul avait rejetée which decision at words of him is-it that Lydie has said that Paul had rejected sans hésitation ? without hesitation ‘Which decision about him did Lydie say that Paul had rejected without hesitation?’
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  • We discuss event-related power differences (ERPDs) in low- and broadband-γ oscillations as the edge of embedded clauses is processed in wh-dependencies such as Which decision regarding/about him/her did Paul say that Lydie rejected without hesitation? in native and nonnative French speakers. The experimental conditions manipulated whether pronouns appeared in modifiers (Mods) or in noun complements (Comps) and whether they matched or mismatched a matrix-clause subject in gender. Across native and nonnative speakers, we found that anaphora-linked ERPDs for Mods vs. Comps in evoked power first arose in low γ and then in broadband γ. Therefore, referential elements first seem to be retrieved from working memory by narrowband processes in low-γ and then referential identification seems to be computed in broadband-γ output. Interactions between discourse- and syntax-based referential processes for the Mods vs. Comps in these ERPDs furthermore suggest that multidomain γ-range processing enables a range of elementary operations for discourse and semantic interpretation. We argue that a multidomain mechanism enabling operations conditioned by the syntactic and semantic nature of the elements processed interacts with local brain microcircuits representing features and feature sets that have been established in first- or second-language acquisition, accounting for a single language epistemology for native and nonnative language.
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  • 07/12/2024
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To Cite this Work:
Dekydtspotter, L. Hierarchical Neural Processing in γ Oscillations for Syntactic and Semantic Operations Accounts for First and Second Language Epistemology [Data set]. Indiana University - DataCORE.

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