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. 2020 Nov 1;1(4):492-522.
doi: 10.1162/nol_a_00023. eCollection 2020.

Neural Mechanisms Underlying the Dynamic Updating of Native Language

Affiliations

Neural Mechanisms Underlying the Dynamic Updating of Native Language

Kelly Sharer et al. Neurobiol Lang (Camb). .

Abstract

Language users encounter different sentence structures from different people in different contexts. Although syntactic variability and adults' ability to adapt to it are both widely acknowledged, the relevant mechanisms and neural substrates are unknown. We hypothesized that syntactic updating might rely on cognitive control, which can help detect and resolve mismatch between prior linguistic expectations and new language experiences that countervail those expectations and thereby assist in accurately encoding new input. Using functional neuroimaging (fMRI), we investigated updating in garden-path sentence comprehension to test the prediction that regions within the left inferior frontal cortex might be relevant neural substrates, and additionally, explored the role of regions within the multiple demand network. Participants read ambiguous and unambiguous main-verb and relative-clause sentences. Ambiguous relative-clause sentences led to a garden-path effect in the left pars opercularis within the lateral frontal cortex and the left anterior insula/frontal operculum within the multiple demand network. This effect decreased upon repeated exposure to relative-clause sentences, consistent with updating. The two regions showed several contrastive patterns, including different activation relative to baseline, correlation with performance in a cognitive control task (the Stroop task), and verb-specificity versus generality in adaptation. Together, these results offer new insight into how the brain updates native language. They demonstrate the involvement of left frontal brain regions in helping the language system adjust to new experiences, with different areas playing distinct functional roles.

Keywords: adaptation; cognitive control; left inferior frontal gyrus (LIFG); multiple-demand (MD) network; sentence comprehension; syntax.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

<b>Figure 1.</b>
Figure 1.
Sequence of stimulus presentation in sentence (left) and baseline (right) trials.
<b>Figure 2.</b>
Figure 2.
Activation for different sentence types relative to baseline in Run1 within Sentence > Baseline regions of interest. Only the left pars opercularis showed an interaction corresponding to a conflict effect. Here and elsewhere, error bars denote Cousineau-Morey within-subject standard errors (Rmisc package; Morey, 2008). L = left, ParsOp = pars opercularis, ParsTri = pars triangularis, FrOrb = frontal orbital cortex, MTG = middle temporal gyrus, RCA = relative clause ambiguous, RCU = relative clause unambiguous, MVA = main verb ambiguous, MVA = main verb unambiguous.
<b>Figure 3.</b>
Figure 3.
Left: Activation for relative clause ambiguous (RCA) and unambiguous (RCU) structures within the left pars opercularis in Run2. There was an ambiguity effect at the first and second but not at the third and fourth occurrence of verbs. Right: Slope of change over time for each participant. Bold line indicates mean slope.
<b>Figure 4.</b>
Figure 4.
Correlation between individuals’ representational conflict processing score (Stroop) and adaptation of the relative clause ambiguity effect in the left pars opercularis in Run2. Individuals with better cognitive control demonstrated greater adaptation. The ellipse represents the bounding area for included versus excluded bivariate data points. The shaded region represents the 95% CI for the correlation.
<b>Figure 5.</b>
Figure 5.
Activation for different sentences relative to baseline in Run3 within the left pars opercularis. Exposed verbs did not show an RC ambiguity effect. Unexposed verbs showed a significant RC ambiguity effect and a difference from exposed verbs. RC = relative clause, MV = main verb, amb = ambiguous, unamb = unambiguous.
<b>Figure 6.</b>
Figure 6.
Activation for different sentence types relative to baseline in Run1 within the multiple-demand regions of interest. Only the left AI/FO showed an interaction corresponding to a conflict effect. AI/FO = anterior insula/frontal operculum, IFS = inferior frontal sulcus, ACC = anterior cingulate cortex, IPS = intraparietal sulcus, RCA = relative clause ambiguous, RCU = relative clause unambiguous, MVA = main verb ambiguous, MVA = main verb unambiguous.
<b>Figure 7.</b>
Figure 7.
Left: Activation for relative clause ambiguous (RCA) and unambiguous (RCU) structures within left AI/FO in Run2. There was no ambiguity effect at the first to third occurrences and a reverse ambiguity effect at the fourth occurrence of verbs. Right: Slope of change over time for each participant. Bold line indicates mean slope. AI/FO = anterior insula/frontal operculum.
<b>Figure 8.</b>
Figure 8.
Activation for different sentences relative to baseline in Run3 within the left anterior insula/frontal operculum. Neither exposed nor unexposed verbs showed an RC ambiguity effect. RC = relative clause, MV = main verb, amb = ambiguous, unamb = unambiguous.

References

    1. Altmann, G. T., & Kamide, Y. (1999). Incremental interpretation at verbs: Restricting the domain of subsequent reference. Cognition, 73(3), 247–264. DOI: 10.1016/S0010-0277(99)00059-1 - DOI - PubMed
    1. Bates, D., Maechler, M., Bolker, B., & Walker, S. (2015). Fitting linear mixed-effects models using lme4. Journal of Statistical Software, 67(1), 1–48. DOI: 10.18637/jss.v067.i01 - DOI
    1. Ben-Shachar, M., Hendler, T., Kahn, I., Ben-Bashat, D., & Grodzinsky, Y. (2003). The neural reality of syntactic transformations: Evidence from functional magnetic resonance imaging. Psychological Science, 14(5), 433–440. DOI: https://doi.org/10.1111/1467-9280.01459, PMID: 12930473 - DOI - PubMed
    1. Bernolet, S., & Hartsuiker, R. J. (2010). Does verb bias modulate syntactic priming? Cognition, 114(3), 455–461. DOI: https://doi.org/10.1016/j.cognition.2009.11.005, PMID: 20034624 - DOI - PubMed
    1. Bock, K., & Griffin, Z. M. (2000). The persistence of structural priming: Transient activation or implicit learning? Journal of Experimental Psychology: General, 129(2), 177. DOI: https://doi.org/10.1037/0096-3445.129.2.177, PMID: 10868333 - DOI - PubMed

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