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Table 1.

Design.

Example item crossing the factors expectancy (E+–) and lexical association (A+–). Literal translation given in italics.

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Table 1 Expand

Table 2.

Descriptive statistics.

Descriptive statistics of the results of the Cloze (scale 0-1) and the association (scale 1-7) norming studies.

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Table 2 Expand

Table 3.

Correlations.

Correlations between stimulus properties.

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Table 3 Expand

Fig 1.

Grand-average ERPs.

Grand-average ERPs on three midline electrodes in the four conditions crossing adverbial clause association and expectancy. Negative voltages are plotted upwards. Ribbons indicate standard error computed from the per-subject per-condition averages.

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Fig 1 Expand

Fig 2.

Scalp distributions.

Topographic distributions of the average potentials in the N400 (row 1) and P600 time windows (row 2), relative to the baseline condition (columns 1-3) or relative to the unexpected-associated condition (column 4). Topographies computed from all non-reference electrodes.

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Fig 2 Expand

Fig 3.

Residual error: Cloze.

Residual error between observed voltages and estimated voltages in Conditions A and C using raw Cloze (left) or log(Cloze) (right) as predictor. Larger deviations from zero indicate larger model error. Ribbons indicate standard error computed from the per-subject per-condition averages.

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Fig 3 Expand

Fig 4.

Residual error: Association.

Residual error between observed voltages and estimated voltages in Conditions C and D using noun-target (left) or verb-target association (right) as predictor. Larger deviations from zero indicate larger model error. Ribbons indicate standard error computed from the per-subject per-condition averages.

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Fig 4 Expand

Fig 5.

Estimated ERPs and residual error.

Estimated ERP waveforms (left) and residual error (right) computed from lmerERP models with log(Cloze) and noun-target association as predictor. Ribbons indicate standard error computed from the per-subject per-condition averages.

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Fig 5 Expand

Fig 6.

ERP coefficients and z-values.

Coefficients (left; added to their intercept), effect sizes (z-values) and corrected p-values (right) from the lmerERP model with log(Cloze) and noun-target association as predictors. Ribbons indicate the standard error on the coefficients from the statistical model.

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Fig 6 Expand

Fig 7.

Exploratory analysis.

Coefficients (left; added to their intercept) and estimated ERPs (right) for exploratory LMER models fitted only on Condition A. Error bars indicate the standard error on the coefficients from the statistical model (right) and standard error computed from the per-subject per-value averages (right).

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Fig 7 Expand

Fig 8.

Reading times.

Log Reading Times per condition on the pre-critical, critical, spillover, and post-spillover region. Error bars indicate standard error computed from the per-subject per-condition averages.

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Fig 8 Expand

Fig 9.

Estimated RTs and residual error.

Estimated log-Reading Times (left) and residual error (right) per condition on the pre-critical, critical, spillover, and post-spillover region. Error bars indicate standard errors on the condition means.

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Fig 9 Expand

Fig 10.

RT coefficients and z-values.

Coefficicents (left, added to their intercept), effect sizes (z-values) and p-values (right) for each predictor on the pre-critical, critical, spillover, and post-spillover region. Error bars indicate the standard error on the coefficients from the statistical model.

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Fig 10 Expand

Fig 11.

Exploratory RT analysis.

Coefficients (left; added to their intercept) and estimated log-RTs (right) for exploratory LMER models fitted only on Condition A. Error bars indicate the standard error on the coefficients from the statistical model (right) and standard error computed from the per-subject per-value averages.

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Fig 11 Expand