THE QUARTERLY JOURNAL OF EXPERIMENTAL PSYCHOLOGY, 2015 Vol. 68, No. 3, 487–498, http://dx.doi.org/10.1080/17470218.2014.956766

Effects of animacy on processing relative clauses in older and younger adults Gayle DeDe Department of Speech, Language, and Hearing Sciences, University of Arizona, Tucson, AZ, USA

Sentences with object relative clauses are more difficult to process than sentences with subject relative clauses, but the processing penalty associated with object relatives is greater when the sentential subject is an animate than when it is an inanimate noun. The present study tested the hypothesis that older adults are more sensitive to this type of semantic constraint than younger adults. Older and younger adults (n = 28 per group) participated in a self-paced listening study. The critical sentences contained subject and object relative clauses and had animate or inanimate subjects. Both older and younger adults had longer listening times for critical segments in object than in subject relative clause in both animacy conditions. Critically, the animacy manipulation disrupted older adults more than younger adults. These results are consistent with the claim that older adults rely on experience-based expectations to a greater extent than younger adults. Keywords: Risky strategy hypothesis; Sentence comprehension; Ageing; Constraint satisfaction; Animacy.

There is a lot of evidence that sentence comprehension becomes slower and less accurate in normally ageing adults (e.g., Caplan, DeDe, Waters, Michaud, & Tripodis, 2011; Kemtes & Kemper, 1997; Stine-Morrow, Noh, & Shake, 2010; Stine-Morrow, Ryan & Leonard, 2000; Waters & Caplan, 2005). However, recent evidence suggests that older adults sometimes compensate for these age-related declines in language comprehension ability by using “risky” processing strategies1 (DeDe, 2014; Rayner, Reichle, Stroud, Williams, & Pollatsek, 2006; also cf. Christianson et al., 2006). On this account, older adults rely on their preexisting linguistic knowledge to make predictions about upcoming words in a sentence.

Correct predictions facilitate sentence comprehension, but incorrect predictions slow the mental operations involved in recognizing words and constructing a mental representation of the sentence (i.e., determining who did what to whom). The risky strategy hypothesis was first described in the context of recognizing words in the context of written sentences (Rayner et al., 2006), but risky strategies also influence how older adults build a mental representation of who did what to whom in a sentence (DeDe, 2014). DeDe (2014) suggested that older adults use probabilistic cues to compensate for age-related changes in sentence comprehension. Probabilistic cues are statistical likelihoods about the most

Correspondence should be addressed to Gayle DeDe, Department of Speech, Language, and Hearing Sciences, University of Arizona, Tucson, AZ 85721, USA. E-mail: [email protected] The author would like to thank Edwin Maas for comments on a previous version of this manuscript. Parts of this research were presented at the City University of New York (CUNY) Sentence Processing Conference, Columbia, South Carolina, March 2013. 1 Note that here, and throughout the paper, the term strategy is meant to indicate that the reader is unconsciously implementing a set of processes in order to build a mental representation of the sentence. © 2014 The Experimental Psychology Society

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likely semantic and syntactic contexts in which particular words will occur (cf. MacDonald, Pearlmutter, & Seidenberg, 1994; Traxler, Morris, & Seely, 2002; Trueswell & Tanenhaus, 1994). For example, some verbs typically occur in transitive constructions (e.g., The man watched the movie) whereas other verbs typically occur in intransitive constructions (e.g., The parents danced in the kitchen). Previous studies have shown that college-age adults use these types of cues to generate predictions about sentences they read and that their expectations influence the moment-tomoment processes involved in real-time sentence comprehension (cf. MacDonald et al., 1994). In a self-paced reading study, DeDe (2014) reported that older adults showed fewer processing disruptions than younger adults when probabilistic cues were consistent with the correct interpretation of the sentence. In self-paced reading, sentences are presented in short segments, and participants press a button to indicate when they have finished reading each segment. The reading time for each segment is interpreted as an index of processing demand at that point in the sentence. Reading times are typically longer for more demanding parts of the sentence. In DeDe’s study, older and younger adults read late closure sentences that contained either ditransitive or transitive subordinate verbs (e.g., When the waiter served/kissed the woman the food was still too hot). In sentences with optionally ditransitive verbs such as served, the food is temporarily ambiguous because it could be part of the subordinate clause (When the waiter served the woman the food at her table, she . . . ) or main clause (When the waiter served the woman, the food . . . ). Although the sentences are structurally identical in the kissed and served conditions, the food cannot be part of the subordinate clause in sentences with verbs such as kissed, which do not occur in ditransitive constructions. Importantly, the manipulated probabilistic cues were consistent with the correct interpretation of the sentence in the kissed condition but not in the served condition. DeDe’s (2014) self-paced reading data suggested that the younger adults tried to incorporate the food into the subordinate clause regardless of whether the verb could occur in ditransitive

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constructions (i.e., in both the kissed and served conditions). In contrast, the older adults appeared to recognize that the food must be the beginning of a new clause when the subordinate verbs were transitive (e.g., kissed). However, the older adults experienced significantly greater processing disruptions than younger adults when the probabilistic cues associated with the subordinate verb were inconsistent with the correct interpretation of the sentence (i.e., in the served condition). These results suggest that older adults used their preexisting knowledge of the verb to avoid processing disruptions in sentences with temporarily ambiguous late closure sentences. Further, younger adults did not take advantage of their knowledge about verbs in the same way. DeDe (2014) examined how older adults process temporarily ambiguous sentences, in which probabilistic cues may help comprehenders decide how to interpret a particular noun phrase (e.g., the food). It is unclear whether older adults use risky strategies when processing unambiguous sentences. In fact, there is reason to believe that older adults use probabilistic cues less effectively than younger adults in some situations (e.g., Federmeier & Kutas, 2005; also cf. Dagerman, MacDonald, & Ham, 2006). For example, Federmeier and Kutas (2005) used event-related potentials to examine older and younger adults’ brain responses to written sentences with strongly and weakly constraining contexts (e.g., No one at the reunion recognized Dan because he had grown a beard vs. At the children’s park next to the beach she saw a man with a beard). The question was whether the two age groups would use the contextual information to predict the last word in the sentence (e.g., beard ). Both age groups showed similar brain responses (i.e., N400s) in the weakly constraining conditions, but older adults appeared to use the strongly constraining contexts less effectively than the younger adults. These results suggest that older adults use probabilistic cues less effectively than younger adults, particularly when the cues rely on the online integration of the meaning of the words in the sentence. Although their results differ, both DeDe’s (2014) and Federmeier and Kutas’s (2005) results

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suggest that older and younger adults process sentences differently when probabilistic cues are manipulated. In contrast, several studies have reported that older and younger adults show similar patterns of processing for unambiguous sentences with object and subject relative clauses, in the sense that both older and younger adults show evidence of processing disruptions at similar regions in the sentences (e.g., Caplan et al., 2011; DeDe, 2013; Kemper & Liu, 2007; Waters & Caplan 2005 but cf. Stine-Morrow, Ryan, et al., 2000). However, the previous studies did not manipulate the availability of helpful probabilistic cues in sentences with object and subject relative clauses. The present study focused on how older and younger adults process sentences with object and subject relative clauses when probabilistic cues are manipulated. In general, sentences with subject relative clauses (Example 1) are easier to process than sentences with object relative clauses (Example 2; e.g., Caplan et al., 2011; Traxler et al., 2002). The difference between these sentence types can be described in several ways. For example, the distance between the object of the relative clause verb (e.g., the child in Example 2) and the verb itself (terrified in Example 2) is greater in sentences with object relative clauses than in those with subject relative clauses (Gibson, 1998). In addition, sentences with subject relative clauses are more frequent than sentences with object relative clauses in English (Roland, Dick, & Elman, 2007). 1. Subject relative: It was the movie that terrified the child because it showed a monster. 2. Object relative: It was the child that the movie terrified because it showed a monster. Studies of college-age adults typically report longer processing times for object relatives than for subject relatives, particularly at the embedded verb (and sometimes at the main verb; e.g., Gordon, Hendrick, & Johnson, 2001; Gordon, Hendrick, & Levine, 2002; Traxler et al., 2002; Traxler, Williams, Blozis, & Morris, 2005). In a self-paced reading study, Caplan et al. (2011) found that both older and younger adults spent more time reading the embedded verb (terrified) in the object

relatives than in the subject relatives in sentences such as (1) and (2). This effect of syntactic complexity was greater in older than in younger adults. Waters and Caplan (2005) reported slightly different results in a study using the auditory version of self-paced reading: self-paced listening. They found that older adults were slower and less accurate than younger adults, but that older adults did not show greater effects of syntactic complexity at critical segments in the sentence. Importantly, both studies found a similar pattern of reading and listening times for younger and older adults (also cf. DeDe, 2013). These types of data have been interpreted as evidence that older adults allocate their processing resources somewhat differently than younger adults, slowing down in order to improve their comprehension (cf. Caplan et al., 2011). However, none of the probabilistic cues in the studies about sentences with object and subject relative clauses were biased toward the object relative structure. Thus, the older adults’ difficulty in processing object relatives might reflect a greater reliance on their expectation for the more common structure. This raises the question of what would happen if the sentences contained cues that led the reader or listener to expect an object relative clause. There is evidence that the animacy of the sentential subject influences how college-age adults read sentences with object and subject relative clauses (Traxler et al., 2002, 2005; also cf. Fedorenko & Gibson, 2007). Consider Sentences 3–6, which vary with respect to both syntactic structure and the animacy of critical nouns. Sentences 3 and 5 contain subject relative (SR) clauses, whereas Sentences 4 and 6 contain object relative (OR) clauses. In Sentences 3 and 4, the sentential subject is an animate noun (i.e., a living entity: musician). In Sentences 5 and 6, the sentential subject is inanimate (i.e., a nonliving entity: accident). This is important because, at least in English, comprehenders prefer that the entity performing an action (i. e., the agent of the verb) be animate rather than inanimate (cf. Traxler et al., 2002). 3.

The musician that witnessed the accident angered the policeman a lot. (SR-animate)

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4. 5. 6.

The musician that the accident terrified angered the policeman a lot. (OR-animate) The accident that terrified the musician angered the policeman a lot. (SR-inanimate) The accident that the musician witnessed angered the policeman a lot. (OR-inanimate).

Traxler et al. (2002) demonstrated that the processing disruption associated with object relative clauses was greatly reduced when the sentential subject was an inanimate noun (Example 6). They suggested that readers initially interpreted the sentential subject as the agent of the relative clause verb in all conditions. In the subject relative conditions, this turns out to be the correct interpretation of the sentence, so no further processing is required. In the object relative conditions, readers must abandon the subject analysis and reinterpret the sentential subject as the object of the relative clause verb. The researchers argued that readers have more difficulty abandoning the initial parse when animacy cues support the misanalysis. In general, these results show that probabilistic cues related to the likely role of animate and inanimate nouns in sentences influence how difficult it is to parse sentences with object relative clauses.

THE PRESENT STUDY The present study investigated whether older adults are sensitive to the animacy constraints described by Traxler et al. (2002). To do so, Traxler et al.’s (2002) study was extended to a different population (older adults) and to a different modality and task (self-paced listening). The predictions were based on the results of Traxler et al. (2002), who focused their analyses on two regions, the relative clause and the main verb. At both of these segments, reading times were longer for object relative sentences with animate subjects than for any of the other conditions (i.e., object relatives with inanimate subjects and subject relatives with animate or inanimate subjects). In the present study, the same basic pattern was expected in both younger and older adults.

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The critical predictions relate to the effects of ageing on listening times. Previous studies generate two competing predictions about how older adults would use probabilistic cues during sentence comprehension. One prediction is that older adults are more sensitive to probabilistic cues because they have more experience and therefore rely on such cues to a greater extent than younger adults (i.e., the “risky” strategy). On this account, older adults should show reduced processing disruptions when the probabilistic cues are consistent with the interpretation of the sentence. Thus, effects of ageing on listening times for the verbs should be smaller in sentences with inanimate than in sentences with animate subjects. The alternative prediction is that older adults are less sensitive to probabilistic cues (cf. Federmeier & Kutas, 2005). On this account, older adults would not be expected to show effects of animacy on listening times for either segment.

Method Participants Older and younger adults (n = 28 per group) participated in the experiment. Older adults were 60 to 85 years of age, and younger adults were 18 to 23 years of age. All older adults earned at least 25 of 30 points on the Mini-Mental State Exam (Folstein, Folstein, & McHugh, 1975). The older adults also passed a hearing screen (at least 35 dB in the better ear). The older adults had more years of education than the younger adults and performed better on the Vocabulary subtest of the Wechsler Adult Intelligence Scale (see Table 1). Table 1. Background information about younger and older adults

Group Older Younger

Age (years)

Education (years)

WAIS Vocab (max = 70)

71.2 (7.0) 19.5 (1.4)

16.2 (2.7) 13.3 (1.1)

58.3 (9.9) 53.9 (6.7)

Note: WAIS Vocab = Wechsler Adult Intelligence Scale, Vocabulary subtest. Mean values are given, with standard deviations in parentheses.

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Materials The experimental materials comprised 23 sentence quadruplets such as those in 3–6, which are repeated as 7–12. The materials were a subset of those developed by Traxler et al. (2002).2 The relative clause verbs differed in the quadruplets, as shown in Examples 7–10. Analyses of variance (ANOVAs) with sentence type and animacy as the independent variables were used to examine whether the relative clause verbs differed as a function of length or frequency. The verbs were well matched for length (F , 0.1), but the verbs in the SR-animate and OR-inanimate conditions were numerically higher in frequency than the relative clause verbs in the SR-inanimate and ORanimate conditions, F(1, 48) = 3.3, p = .08. 7.

The musician that/ witnessed/ the accident/ angered/ the policeman/ a lot. (SR-animate) 8. The musician that/ the accident/ terrified/ angered/ the policeman/ a lot. (OR- animate) 9. The accident that/ terrified/ the musician/ angered/ the policeman/ a lot. (SR-inanimate) 10. The accident that/ the musician/ witnessed/ angered/ the policeman/ a lot. (OR-inanimate) 11. True/false question: The musician angered the policeman. Development of self-paced listening task. Sentences were presented in segments (see 7–10) in a selfpaced listening experiment, which is the auditory analogue of self-paced reading. The experiment was controlled using Psyscope Experimental Software. A female speaker of American English recorded the sentences in a sound-attenuated booth. Sentences were recorded as 16-bit sound files sampled at 44.1 kHz. Sentences were broken into segments (see Examples 7–10) using Praat (Boersma & Weenink, 2007). Segmentation was based on low signal amplitude at the end of words, as identified through visual and auditory inspection, and the breaking point that maximized the intelligibility of each segment. The waveforms were

converted into SoundEdit files (Dunn, 1994) and entered into PsyScope experimental software (Cohen, MacWhinney, Flatt, & Provost, 1993). Procedure The items were separated into four lists such that each member of the quadruplet appeared in a different list. Because there were 23 quadruplets, it was not possible to perfectly balance the items within each list. However, all participants completed all lists in four separate testing sessions, which were separated by at least one week. Thus, the materials were balanced across the experiment, and all participants saw all of the items. Order of list presentation was counterbalanced across participants. The 23 experimental items in each list were combined with 55 fillers, which were taken from other experiments and had various syntactic structures (including syntactically ambiguous sentences and simple active transitive and intransitive sentences). Items were presented in pseudorandom order, with the constraint that no more than two sentences of the same type could occur in succession. All lists were preceded by 10 practice sentences. Participants listened to auditory stimuli at comfortable listening levels played over high-quality earphones via a Macintosh iBook laptop computer. Participants paced through each segment by pressing a button on a button box interfaced with the computer. A tone marked the end of the sentence, after which a true/false comprehension question was presented (see Example 11). The button box collected response accuracy and reaction times for each button press with millisecond resolution, providing a measure of the response time for each segment.

Results Accuracy Proportion correct on the comprehension questions was analysed using mixed 2 (sentence type: SR vs. OR) by 2 (animacy: animate vs. inanimate) by 2

2 Traxler et al. (2002) contained 28 quadruplets. Three sets were excluded because they contained vocabulary that overlapped with other experimental materials that were run concurrently with this experiment. In addition, two of the quadruplets developed by Traxler et al. (2002) were included in the study but were then omitted from data analysis due to a coding error in the experimental software. The frequency and length analyses are based on the 23 sets included in the final results.

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(group: older vs. younger) ANOVA by participants (F1) and items (F2). Group was the betweenparticipants factor. Group means are presented in Figure 1. In the interests of brevity, only effects that were significant in either the analyses by participants or the analyses by items are reported here. Older adults made more comprehension errors than younger adults, F1(1, 54) = 10.1, MSE = .04, F2(1, 22) = 85.6, p = .003, h2p = .16, MSE = .004, p , .0001, h2p = .80. Both older and younger adults made more errors about sentences with animate than inanimate sentential subjects, F1(1, 54) = 169.9, MSE = .01, p , .0001, h2p = .76, F2(1, 22) = 37.8, MSE = .05, p , .0001, h2p = .63. The participants also made more errors about sentences with object than subject relatives, F1(1, 54) = 106.0, MSE = .01, p , .0001, h2p = .66, F2(1, 22) = 5.2, MSE = .12, p = .03, h2p = .19. The effect of sentence type was numerically larger in sentences with animate compared to inanimate sentential subjects, but the interaction between animacy and sentence type was only significant by participants, F1(1, 54) = 41.7, MSE = .01, p , .0001, h2p = .44, F2(1, 22) = 2.8, MSE = .08, p = .11, h2p = .11. There were no other significant effects (all Fs ≤ 3.4, all ps ≥ .08). Listening times Overview of listening time analyses. The dependent measure for the analyses of online sentence

Figure 1. Proportion correct by condition and group. Error bars show the standard error of the mean. Rel = relative.

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processing was the listening time for each critical segment. Sentences that were not correctly understood (based on performance on comprehension questions) were excluded from the analyses. Following Traxler et al. (2002), the critical segments were the relative clause verb and the main verb. Listening times for the first segment (“The musician/accident that”) were analysed to determine whether the animacy manipulation had an immediate effect on listening times. Response time for each button press was measured from the onset of the segment. The duration of the spoken segment was then subtracted from the response time to calculate the listening time (i.e., the amount of time spent listening to the segment beyond its spoken length). Because there was some hint that frequency differed across the relative clause verbs, effects of frequency were controlled using a regression approach (Ferreira & Clifton, 1986). Listening times were regressed against word frequency, separately for each participant. The resulting residuals were used in the analyses. This procedure can result in negative listening times when the observed data are faster than would be predicted based on frequency. This procedure also has the effect of minimizing main effects of age group because each participant’s mean listening time is zero (prior to removal of outliers). Listening times greater than 2.5 s were deleted, because they were not considered to reflect normal sentence processing. In addition, listening times greater or less than three standard deviations from the mean for each participant in each condition were treated as outliers and replaced with the value of the upper or lower limits. Together, these procedures accounted for 3.5% of the older adults’ data and 3.6% of the younger adults’ data. The data were first analysed to determine whether older and younger adults’ performance changed across the four sessions. To do so, the data were analysed in 4 (session: 1–4) by 2 (group: older vs. younger) × 2 (sentence type: object vs. subject relative clause) × 2 (animacy: animate vs. inanimate sentential subject) ANOVAs. There was a significant interaction between session and group: Both older and younger adults sped up

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across the four sessions, but younger adults sped up to a greater extent. The effect of session did not interact with any other variable (all Fs , 1.9, all ps . .13). For all further analyses, the data were collapsed across session. Next, the data were analysed in 2 (sentence type) by 3 (segment: first segment, relative clause verb, main verb) by 2 (animacy) by 2 (group) mixed ANOVAs by participants and items. In the interests of brevity, only highest order interactions are reported. All of the three-way interactions were significant [Animacy × Sentence Type × Segment: F1(2, 108) = 8.02, p , .0001, F2(2, 44) = 3.88, p = .03; Animacy × Sentence Type × Group: F1(1, 54) = 5.61, p = .02, F2(1, 22) = 10.64, p = .003; Sentence Type × Segment × Group: F1(2, 108) = 3.83, p = .02, F2(2, 44) = 7.95, p = .001]. The four-way interaction was marginally significant by items only, F1(2, 108) = 0.91, p = .41; F2(2, 44) = 3.29, p = .05. To facilitate the interpretation of these results, the data for each segment were analysed in separate 2 (sentence type) × 2 (animacy) × 2 (group) mixed ANOVAs by participants and items. Significant interactions were explored using Tukey post hoc tests with a criterion of p , .05. Listening times for older and younger adults are presented in Figure 2. Listening times for Segment 1 (The musician/accident that). There was a main effect of animacy, due to longer listening times for inanimate (e.g., accident) than for animate (e.g., musician) subjects, F1(1, 54) = 31.7, MSE = 3484, p , .0001, h2p = .37, 22) = 4.7, MSE = 22,665, p = .04, F2(1, h2p = .18. The interaction between animacy and group approached significance in the analysis by participants only, F1(1, 54) = 3.57, MSE = 3484, p = .06, h2p = .06, F2(1, 22) = 1.2, MSE = 3680, p = .29, h2p = .05. Similarly, the interaction

between animacy and sentence type was significant in the analysis by participants only, F1(1, 54) = 6.24, MSE = 2599, p = .02, h2p = .10, F2 , 1. The effect of animacy appeared to be greater in older than in younger adults, and the effect of animacy was numerically greater in subject relatives than in object relatives. These effects should be interpreted very cautiously because they were not reliable. Listening times for the relative clause verb. The three-way interaction between sentence type, animacy, and group was significant, F1(1, 54) = 6.4, MSE = 9267.6, p = .01, h2p = .11, F2(1, 22) = 11.4, MSE = 7025.9, p = .003, h2p = .34. Tukey post hoc tests were inspected to investigate effects of syntactic complexity (OR vs. SR), animacy (animate, AI, vs. inanimate, IA), and age group (older vs. younger). Both older and younger adults showed significant effects of syntactic complexity: Listening times were longer for object than for subject relatives, in both animacy conditions. With respect to animacy, the older adults had significantly longer listening times for object relatives with animate than with inanimate subjects. The older adults did not show effects of animacy in subject relative sentences. The younger adults did not show animacy effects for either subject or object relatives; that is, listening times did not differ for sentences with animate and inanimate subjects.3 Regarding effects of age, older adults had significantly longer listening times than the younger adults for object relatives in the animate condition, but not in any of the other conditions. Listening times for the main verb. The three-way interaction of sentence type, animacy, and group was significant, F1(1, 54) = 5.4, MSE = 7232.8, p = .02, h2p = .09, F2(1, 22) = 4.9, MSE =

3 When the groups were analysed separately, younger adults showed effects of syntactic complexity and animacy at both the relative clause and main verbs. At the relative clause verb, the interaction between animacy and sentence type was significant in the younger adults, F(1, 27) = 10.30, p = .003. Tukey tests revealed effects of syntactic complexity in both animacy conditions. The effect of animacy was significant in object relatives but not in subject relatives. At the main verb, younger adults showed effects of syntactic complexity, F(1, 27) = 6.5, p = .02, and animacy, F(1, 27) = 5.6, p = .03, but the interaction did not reach significance, F(1, 27) = 3.3, p = .08. The difference between the analyses with and without group in the model probably reflects the additional variance introduced by including younger and older adults in one model and the fact that the effects were larger in the older than in the younger adults.

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with animate subjects. Older adults did not show significant effects of syntactic complexity in sentences with inanimate subjects. Younger adults did not show effects of syntactic complexity at the main verb, in either animacy condition. The effect of animacy was only significant for older adults in sentences with object relative clauses (i.e., OR-animate vs. OR-inanimate). The younger adults did not show significant effects of animacy. None of the pairwise comparisons for age group were significant.

Figure 2. Residual listening times for older and younger adults. Error bars show standard errors. Rel = relative.

6686.5, p = .04, h2p = .18. With respect to syntactic complexity, Tukey post hoc tests showed that older adults’ listening times were longer for object relatives than for subject relatives in sentences

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Correlations One question is whether additional time spent processing object relative sentences with animate subjects was associated with better comprehension accuracy. Difference scores were calculated to estimate the magnitude of the animacy effect (i.e., ORanimate minus OR-inanimate) and syntactic complexity effect (i.e., OR-animate minus SR-animate) in sentences with object relative clauses. Difference scores were computed for the relative clause verb and the main verb. These difference scores were correlated with accuracy on the object relative sentences with animate subjects. The goal was to determine whether additional time spent processing the verb in the more complex sentences was associated with greater accuracy on comprehension questions. According to Caplan et al. (2011), a significant positive correlation would indicate that longer processing times reflect additional processing, resulting in more accurate comprehension. In contrast, negative or null correlations would suggest that longer processing times reflect compensatory processes. In the present study, only the correlation between accuracy on OR-animate sentences and the animacy effect at the relative clause verb (i.e., OR-animate minus SR-animate) approached significance (r = −.27, p = .07). No other correlations approached significance (rs ranged from .06 to .18, ps ≥ .21).

Discussion This study investigated whether there are agerelated changes in how people use semantic constraints during auditory sentence comprehension.

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The results were consistent with the “risky” strategy hypothesis: The processing disruption associated with object relatives was larger for older adults when the sentential subject was animate than when it was inanimate. The implication is that older adults experience greater processing disruptions when linguistic input differs from their knowledge-based expectations of language. The results of this study show that risky processing strategies do not only apply to temporarily ambiguous sentences. In DeDe (2014), probabilistic cues affected how older adults interpreted temporarily ambiguous sentences. The present study shows that probabilistic cues also affect the magnitude of ageing effects in unambiguous sentences with object relative clauses. The older adults experienced greater processing disruptions than younger adults when the probabilistic cues were biased away from the actual structure of the sentence (i. e., in the object relative–animate condition). The risky strategy may be viewed as smart because older adults’ knowledge-based expectations about linguistic input are likely to be correct in the real world. Indeed, studies that do not account for older adults’ ability to use probabilistic cues during sentence comprehension may overestimate the difficulty that older adults experience outside of experimental settings. For example, in Caplan et al.’s (2011) study, the subject relative sentence (It was the movie that terrified the child . . .) contained an inanimate sentential subject (the movie), whereas the object relative sentence (It was the child that the movie terrified . . .) contained an animate sentential subject (the child). This animacy pattern may have exacerbated the comparative difficulty of sentences with object and subject relative clauses. These results are inconsistent with the hypothesis that older adults are less sensitive to animacy constraints than younger adults (cf. Federmeier & Kutas, 2005; Traxler et al., 2005). This apparent inconsistency may be attributable to task differences. Federmeier and colleagues (2005) used event related potentials (ERPs) rather than selfpaced listening. Self-paced listening may detect effects of predictability that ERPs do not, possibly due to differences in the time course of how each

task measures online processing. For example, older adults may be sensitive to context effects in a later time window than that measured in the ERP studies. Another possibility is that the difference between the present study and Federmeier and Kutas’s (2005) work reflects the extent to which cues are based on preexisting knowledge. Federmeier and colleagues reported that older adults predicted words in strongly biasing contexts less effectively than younger adults. Predicting the last word in a sentence probably requires that the comprehender has accessed and integrated basic semantic information about the previous words in the sentence. In contrast, the use of animacy constraints relies on preexisting knowledge about the distribution of animate and inanimate nouns in sentences. The present results suggest that older adults use probabilistic cues based on preexisting linguistic knowledge (e.g., verb argument structure, animacy) to a greater extent than cues based on the combinatorial properties of a novel word string. Thus, the differences between the present study and Federmeier and Kutas (2005) might reflect the task or the materials. Regardless, the difference probably emerges because slowed processing makes it more difficult for older adults to rapidly integrate discourse context during online sentence comprehension (cf. Salthouse, 1996). This study did not directly address the cognitive mechanisms underlying risky processing strategies. Given that probabilistic cues are based on language experience, how they are used may change across the lifespan. That is, older and younger adults’ knowledge-based expectations may differ in some way because older adults have many more years of experience processing their language than younger adults. More years of experience could translate into more stable or less noisy expectations about linguistic input, resulting in increased processing disruptions when linguistic input deviates from their expectations. There is some support for the idea that language experience affects how older adults process sentences (Payne et al., 2014). Payne et al. (2014) recently reported that older adults with more reading experience show greater sensitivity to English attachment biases when reading sentences with relative clauses. The

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implication is that, for older adults, having more opportunities to develop language-specific expectations is associated with increased processing disruptions when those expectations are violated. Further research is needed to clearly describe the mechanism underlying the risky strategy hypothesis. Risky processing strategies are not the only possible account of why older adults show a greater influence of animacy violations than younger adults. For example, a number of authors have proposed that there are separate semantic and syntactic routes to sentence processing (e.g., BornkesselSchlesewsky & Schlesewsky, 2013; Friederici, 2009; Kuperberg, 2007; also cf. Christianson et al., 2006). Within a semantic processing stream, features like the animacy of the sentential subject might influence thematic role assignment. In contrast, the syntactic stream might compute an interpretation based on morphosyntactic rules, with no influence of animacy (e.g., Kuperberg, 2007). Older adults might rely on the semantic processing stream to a greater extent than younger adults, particularly if it is less computationally demanding to construct semantic than syntactic representations. On this view, greater effects of animacy in older than in younger adults might emerge because the older adults weigh the semantic stream, which uses animacy information, more heavily. Like the risky strategy hypothesis, this explanation requires that older adults rely on preexisting semantic knowledge to a greater extent than younger adults. The primary difference is that this alternative account does not explicitly require that older adults rely on knowledge-based experience to a greater extent than younger adults. These two accounts are not necessarily mutually exclusive. It is possible that the semantic processing stream is less computationally demanding for older adults in part because of their accumulated linguistic knowledge. One question is how effects of animacy and sentence type, as measured by longer listening times, relate to sentence comprehension, as measured by accuracy. The correlations between listening times for the critical segments and accuracy on the comprehension questions revealed a nonsignificant, negative

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relationship between listening time and accuracy (cf. Caplan et al., 2011). This result suggests that older adults take longer to recover from the mismatch between the expected structure and the actual structure, but the longer listening times do not necessarily result in better comprehension. According to Caplan et al. (2011), this pattern is indicative of imperfect compensatory processing because allotting more processing time does not result in better comprehension accuracy. The negative correlation contrasts with the positive correlations reported by Caplan et al. (2011). The difference between the two studies might reflect the type of effect (animacy vs. syntactic complexity). In the present study, the negative correlation is associated with effects of animacy, whereas the positive correlations reported by Caplan et al. were associated with effects of syntactic complexity. Regardless, all of these effects should be interpreted cautiously because they were not statistically significant (in both the present study and Caplan et al., 2011). The younger adults’ results differ somewhat from those reported by Traxler et al. (2002). However, the difference was minimal when the groups were analysed separately (see Footnote 3). In Traxler et al., total reading times for the relative clause (which may be most analogous to self-paced listening times) were longer for object relative sentences with animate subjects than for the other three conditions, which did not differ from one another. In the present study, listening times were longer for the relative clause verb in the object relative–animate condition than in any other condition. In contrast to Traxler et al. (2002), the effect of syntactic complexity was also significant in sentences with inanimate subjects (i.e., the OR-inanimate vs. SR-inanimate condition). At the main verb, Traxler et al. (2002) reported significant main effects of animacy and sentence type, but no interaction. However, the interaction between animacy and sentence type did emerge in some other measures of eye tracking (e.g., regression path durations) and in total reading times in subsequent experiments (Traxler et al., 2005). In the present study, there were main effects of animacy and sentence type at the main verb, but no interaction.

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There are several candidate explanations for the differences between Traxler and colleagues’ work and the present study. For example, there were minor differences in how segments were defined. Traxler et al. (2002, 2005) analysed the entire relative clause region rather than focusing on the verb. In addition, differences in the task and modality might contribute to the differences. DeDe (2013) reported that effects of syntactic complexity in object and subject cleft sentences were generally similar, but exaggerated in self-paced reading compared to self-paced listening. The effects of animacy may also be stronger in reading than in listening, resulting in a greater reduction of syntactic complexity effects in sentences with inanimate subjects. In contrast, the animacy constraints may reduce but not eliminate the effects of syntactic complexity in auditory comprehension. Another possibility is that self-paced listening tasks are less sensitive to the effects of animacy than other methods (cf. Kemper & Liu, 2007). Regardless, the critical observation is similar in both studies: The younger adults showed greater effects of syntactic complexity in sentences with animate than in sentences with inanimate subjects. In conclusion, there is considerable evidence that sentence comprehension ability declines in normally ageing adults. The present study suggests that older adults may compensate for these agerelated changes by relying on knowledge-based expectations of their language. This compensatory mechanism may minimize the actual impact of age-related declines in sentence comprehension ability in the older adult’s everyday life. Original manuscript received 12 July 2013 Accepted revision received 12 June 2014 First published online 30 October 2014

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Effects of animacy on processing relative clauses in older and younger adults.

Sentences with object relative clauses are more difficult to process than sentences with subject relative clauses, but the processing penalty associat...
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