In the following, we compare the predictions of the extended ACT-R model with the literature on reflexives. Prominence predicts that interference in antecedent-match conditions is generally low compared to antecedent-mismatch conditions but increases as a function of distractor activation. If we assume that distractor position (grammatical role and discourse topicality) affects its base-level activation in memory, the literature summary in **Table 1** seems to conform with these predictions: Among the studies which tested both antecedentmatch and antecedent-mismatch conditions, about 75% report an interference effect (including marginal effects) in antecedentmismatch conditions while only 50% of the studies found an effect in antecedent-match conditions. All studies that did report an effect in antecedent-match conditions had the distractor either in subject position (Badecker and Straub, 2002; Chen et al., 2012; Patil, Vasishth, and Lewis, "Retrieval interference in syntactic processing: The case of reflexive binding in English," unpublished manuscript), in topicalized subject position15 (Felser et al., 2009; Cunnings and Felser, 2013; Clackson and Heyer, 2014), or had multiple distractors (Experiment 2 reported here). On the other hand, only half of the studies reporting no interference effect in antecedent-match conditions had the distractor in subject position. Obviously, not all studies that have the distractor in subject position report an effect, but the literature review suggests that subject position increases the probability of finding one. For the absence of an antecedent-match interference effect in our Experiment 1, there might be a specific reason: Dillon et al. (2015) have shown that items within restrictive relative clauses

13This is assuming that the pre-critical effects in Experiments 1 and 2 are due to difficulty with an inanimate subject, as discussed above, rather than reflecting an early application of binding during the parafoveal preview of the reflexive.

14It should be noted that the (marginal) facilitatory interference in antecedentmatch conditions reported by three studies presented in **Table 1** (Sturt, 2003; Cunnings and Felser, 2013) is compatible with the ACT-R model although this may not be intuitively obvious. An exceptionally highly activated distractor (in all three of these experiments, the distractor is a discourse prominent subject) can lead to facilitatory interference (see Engelmann et al., 2015, and our forthcoming publication Engelmann, Jäger, and Vasishth, "Confusability of retrieval cues in dependency resolution: A computational model," manuscript in preparation).

15With distractors in "topicalized subject position" we here refer to distractor nouns in subject positions which appear as the current discourse topic in the test sentence because they were introduced in a preceding context sentence.

cause more interference as compared to items in appositive relative clauses. They attribute this difference to the idea that, in contrast to restrictive relative clauses, appositive relative clauses constitute a speech act separate from the one of the main utterance (Potts, 2005; Arnold, 2007). More generally, their results suggest that the embedding environment containing a distractor influences the strength of interference caused by this distractor. In terms of ACT-R, one might think of this as different base-level activations as a function of the type of embedding environment. It might be possible that the interposed adverbial structures which contain the distractor in our materials belong to those embedding environments which cause a relatively low degree of interference. This seems a plausible assumption since in our materials, the adverbial clause can simply be ignored by the parser without affecting the grammaticality or plausibility of the whole sentence.

For antecedent-mismatch conditions, cue confusion predicts stronger inhibition the higher the crossed association between cues and features is assumed to be, that is, in contexts with frequently co-occurring cue combinations. However, note that cue confusion is compatible with both facilitatory and inhibitory effects, and even with the absence of an effect, as all this is part of the effect continuum that is illustrated in **Figure 2**. This raises the concern of how to determine a sensible confusion level in each case, since a model allowing arbitrary predictions is not useful. Currently, the model prediction can only be treated as a predicted difference between two conditions in one or the other direction along the effect continuum. In other words, a prediction should be stated in terms of whether the antecedentmismatch interference effect of one dependency tends more toward inhibition or toward facilitation in comparison to another dependency like, e.g., English reflexives. In the reasoning we apply here, we refer to English reflexives as a baseline with zero cue confusion and spot special cases where a different feature-co-occurrence rate can be assumed that would motivate a higher confusion level. We have argued that inhibitory interference was observed in antecedent-mismatch conditions in our Experiment 1 because *ziji* is a special case in the sense that the feature combination {+ *c*-*com*, +*animate*} is constant compared to the variable combinations in the different forms of English reflexives. The same logic with respect to {+ *c*-*com*, +*plural*} would apply to reciprocals. In the literature there is one study by Kush and Phillips (2014) that tested the Hindi equivalent of the reciprocal *each other* and indeed found the predicted inhibitory interference in antecedent-mismatch conditions.

Although the *post-hoc* nature of our proposals here is an important limitation that needs to be addressed with new empirical tests, theory development necessarily is data-driven, and the existing data suggest that our proposal constitutes one possible explanation. Indeed, currently it is the only computational account of the patterns of findings discussed here. In order to empirically test the predictions of cue confusion, it is necessary to experimentally manipulate feature-co-occurrence within a minimal pair. A potential experiment could use stimuli like in Example (4) to compare the interference effect in antecedent-mismatch conditions for *themselves* and *each* *other*. Cue confusion predicts a smaller facilitation or even an inhibition for *each other*. Furthermore, it should be possible to derive a numerical metric of cue confusion for a range of dependencies by computing co-occurrence frequencies in a treebank that contains dependency information as well as information about retrieval relevant features such as gender, number, and animacy.

#### (4) a. **Reflexive; distractor-match**

The *nurse* who cared for the *children* had pricked *themselves* ...

#### b. **Reflexive; distractor-mismatch**

The *nurse* who cared for the *child* had pricked *themselves* ... c. **Reciprocal; distractor-match**

The *nurse* who cared for the *children* had pricked *each other* ...

#### d. **Reciprocal; distractor-mismatch**

The *nurse* who cared for the *child* had pricked *each other* ...

A more thorough test of the extended model's predictions will be presented in a forthcoming publication (Engelmann et al., "Confusability of retrieval cues in dependency resolution: A computational model," manuscript in preparation) that includes quantitative simulations of a range of previous studies on reflexive processing and subject-verb dependencies.

As a rather speculative point we want to add that the cue confusion level of a certain dependency might not only be influenced by feature-co-occurrence but also by task demands and individual differences. If cue-feature associations are subject to an adaptive learning process, they might also be affected by resource-preserving strategies. An example where strategic adaptation of comprehension processes has been found are relative clause attachment ambiguities. Swets et al. (2008) and Logacev and Vasishth (2015) ˇ have found that processing effort in ambiguity resolution was adapted to the type of comprehension questions. Also, effects of individual differences in working memory span have been found by Traxler (2007) and von der Malsburg and Vasishth (2012) for the processing of attachment ambiguities. If analogously to task- and resource-related underspecification in attachment ambiguities, cue-feature associations are affected by resourcepreserving strategies in the sense of *good-enough processing* (Ferreira et al., 2002), we would expect that low-span readers tend to have greater cue confusion and, thus, exhibit interference effects further toward inhibition in the continuum than highspan readers. The marginal inhibitory effect for low-span readers in antecedent-mismatch conditions of Experiment 2 by Cunnings and Felser (2013) would fit with this expectation. However, more experimental data is needed in order to evaluate effects of individual differences and task-demands on cue-feature associations.

### **6. Conclusion**

We have presented experimental evidence that is incompatible with structure-based accounts of reflexive processing and also inconsistent with the original cue-based ACT-R model of sentence processing. In order to account for the observed pattern, we have proposed to add two new principles, prominence and cue confusion, to the ACT-R model. This extension to the ACT-R model is not only able to explain the pattern observed in the data presented in this article, but can also account for a range of previously unexplained patterns reported in the literature on reflexive processing. Naturally, this proposal needs to be evaluated with novel experimental data.

### **Acknowledgments**

We thank Prof. Hua Shu and the State Key Laboratory of Cognitive Neuroscience and Learning at Beijing Normal

### **References**

University, China, for allowing us to conduct our experiments in their eye-tracking lab. We are grateful to Dr. Ming Yan, Dr. Jing'er Pan and Wei Zhou for their kind assistance and their very helpful comments on the experimental materials. We thank Prof. Reinhold Kliegl for his valuable advice on the statistical analyses and Dr. Zhong Chen and Maja Stegenwallner-Schütz for constructive discussions. We thank the audience at AMLaP 2012 and 2014 for comments. This work was partly funded by the Studienstiftung des deutschen Volkes and the Potsdam Graduate School by awarding a scholarship to the first and the second author, respectively. Publication of this article was funded by the Deutsche Forschungsgemeinschaft and the Open Access Publishing Fund of the University of Potsdam.

eds R. P. Van Gompel, M. H. Fischer, W. S. Murray, and R. L. Hill (Oxford: Elsevier), 341–372.

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Copyright © 2015 Jäger, Engelmann and Vasishth. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

## **Appendix**

#### **TABLE A1 | Pretest of Experiment 2: Classification of the participants' answers in the "incorrect" trials by experimental condition.**

Percentages refer to the total number of trials including the correct trials.

# Local anaphor licensing in an SOV language: implications for retrieval strategies

#### *Dave Kush1 \* and Colin Phillips 2,3*

*1 Haskins Laboratories, New Haven, CT, USA*

*2 Linguistics, University of Maryland, College Park, MD, USA*

*3 Maryland Language Science Center, University of Maryland, College Park, MD, USA*

#### *Edited by:*

*Claudia Felser, University of Potsdam, Germany*

#### *Reviewed by:*

*Shravan Vasishth, University of Potsdam, Germany Patrick Sturt, University of Edinburgh, UK*

#### *\*Correspondence:*

*Dave Kush, Haskins Laboratories, 300 George St., Suite 900, New Haven, CT 06511, USA e-mail<EMAIL_ADDRESS>
Because morphological and syntactic constraints govern the distribution of potential antecedents for local anaphors, local antecedent retrieval might be expected to make equal use of both syntactic and morphological cues. However, previous research (e.g., Dillon et al., 2013) has shown that local antecedent retrieval is not susceptible to the same morphological interference effects observed during the resolution of morphologically-driven grammatical dependencies, such as subject-verb agreement checking (e.g., Pearlmutter et al., 1999). Although this lack of interference has been taken as evidence that syntactic cues are given priority over morphological cues in local antecedent retrieval, the absence of interference could also be the result of a confound in the materials used: the post-verbal position of local anaphors in prior studies may obscure morphological interference that would otherwise be visible if the critical anaphor were in a different position. We investigated the licensing of local anaphors (reciprocals) in Hindi, an SOV language, in order to determine whether pre-verbal anaphors are subject to morphological interference from feature-matching distractors in a way that post-verbal anaphors are not. Computational simulations using a version of the ACT-R parser (Lewis and Vasishth, 2005) predicted that a feature-matching distractor should facilitate the processing of an unlicensed reciprocal if morphological cues are used in antecedent retrieval. In a self-paced reading study we found no evidence that distractors eased processing of an unlicensed reciprocal. However, the presence of a distractor increased difficulty of processing following the reciprocal. We discuss the significance of these results for theories of cue selection in retrieval.

**Keywords: memory retrieval, anaphor resolution, Hindi, self-paced reading, computational modeling**

### **INTRODUCTION**

In order to establish grammatical dependencies between words across a distance during routine sentence processing comprehenders rely heavily on their ability to encode and retrieve items from memory. For example, processing of a local anaphor such as the reflexive *themselves* or the reciprocal *each other* in (1) requires recalling the previously seen noun phrase (NP) *the people* from memory so that it may be interpreted as the antecedent.

(1) The people talked to *themselves/each other*.

The mechanism by which previously encountered items are retrieved for subsequent processing has been the subject of recent research. A number of recent studies have motivated a processing model that exploits a cue-based access mechanism to retrieve items from content-addressable memory (e.g., McElree, 2000; McElree et al., 2003; Lewis et al., 2006; Van Dyke, 2007; Martin and McElree, 2008, 2009; Van Dyke and McElree, 2011).

A hallmark property of cue-based retrieval is that it is susceptible to interference (Nairne, 1990). Task-irrelevant items in memory whose features overlap with a probe's retrieval cues (distractors) can exert influence on the retrieval of a target item. In the context of sentence processing retrieval interference is said to occur when grammatically inappropriate distractors influence the processing of a phrase that must enter into a dependency with a previously encountered head. The influence of distractors can be *inhibitory*: a distractor may increase the difficulty of retrieving an appropriate item. Van Dyke (2007) found that distractor NPs increased the difficulty of retrieving a grammatically appropriate subject for the purposes of thematic integration with a verb (see also Van Dyke and McElree, 2006, 2011). A distractor's influence may also be *facilitatory* if its presence decreases the difficulty of processing an otherwise ungrammatical or unlicensed element. Comprehenders have repeatedly showed signs of facilitatory interference during the processing of subject-verb agreement (e.g., Pearlmutter et al., 1999; Wagers et al., 2009). Wagers and colleagues found that reading times immediately following the plural verb *were*, which mismatched the features of the singular subject *key*, were decreased when an intervening distractor [*cabinet(s)*] was plural, compared to when the distractor was singular.

(2) The key to the **cabinet(s)** unsurprisingly *were* rusty from years of disuse.

The authors argued that facilitation arose because comprehenders erroneously retrieved the plural distractor on some portion of trials when attempting to find a licensor for the plural marking on the verb. These kinds of facilitatory interference effects have also been observed in the processing of other grammatical dependencies such as negative polarity item (NPI) licensing (e.g., Drenhaus et al., 2005; Vasishth et al., 2008; Xiang et al., 2009; Parker and Phillips, submitted), and the retrieval of antecedents for null pronominal subjects (PRO) in adjunct clauses (Parker et al., 2012) and many authors have attributed these effects to misretrieval of a distractor under (partial) match with a set of retrieval cues.

Although facilitatory interference has been repeatedly observed in the processing of some dependencies, other dependencies that recruit retrieval have displayed virtual immunity to facilitation from distractors. Recent work has found that the processing of a local anaphor that lacks a grammatical antecedent is unaffected by the morphological feature-content of intervening distractors (e.g., Sturt, 2003; Dillon et al., 2013). For instance, Dillon et al. (2013) demonstrated that the processing of the unlicensed plural reflexive *themselves* in (3) is not influenced by plural-marking on the distractor *manager(s)*.

(3) The new executive who oversaw the manager(s) apparently doubted *themselves*...

The lack of facilitatory interference effects is unexpected on the assumption that the same cues as those used to find licensors for agreement dependencies (e.g., morphological features such as number) are used to identify potential antecedents of reflexives. As with agreement, reflexives must match their licensors in number and gender, so the use of morphological features as cue for retrieval of appropriate antecedents would appear to be motivated. On analogy to agreement licensing, the use of these morphological cues should in turn render antecedent retrieval subject to interference.

The results suggest that morphological features may play a different role in antecedent retrieval for local anaphors than they do in agreement licensing. One option, advocated by Dillon et al. (2013), is that antecedent retrieval forgoes the use of interferenceprone morphological features, opting instead to exclusively use *positional* syntactic features to access the local subject. Another option is that antecedent retrieval preferentially weights syntactic cues over morphological cues instead of avoiding them altogether. This second account predicts a small but non-negligible interference effect that the first does not, but previous experiments may not have had sufficient power to find this effect, so they cannot distinguish between the two competing explanations.

Although the two accounts differ, they both assign priority to positional cues. This goes against the general assumption that retrieval identifies targets through the use of a maximal cue set that uniformly weights lexical, morphological, syntactic, and semantic features (see Van Dyke and McElree, 2011 for discussion).

As it stands the previous studies may not be sufficient to establish a preference for positional features. It is possible that the absence of facilitatory interference could be attributed to a confound that masks the contribution of morphological features that are weighted equally to syntactic cues. In almost all previous studies the critical anaphor immediately followed its verb, which could potentially play a role in reducing the incidence of facilitatory interference (see King et al., 2012 for a similar suggestion).

As Dillon et al. (2013) note, the post-verbal position can provide an anaphor with privileged access to the local subject by means of recent activation alone. If subjects are retrieved by their verbs for thematic integration, the local subject *the executive* in (3) should be recalled by the verb *doubted*. Retrieval of the local subject entails that it should have the highest baseline activation out of all other items in memory immediately following the verb. At the time that a verb-adjacent reflexive is encountered, this high degree of activation may be strong enough to guarantee retrieval of the local subject instead of the feature-matching distractor even if morphological cues were used.

Alternatively, it may be that previous studies on reflexives do not provide a measure of susceptibility to facilitatory interference because establishing a dependency between the local subject and a post-verbal anaphor might not require retrieval at all. Some theories assume that the most recently retrieved item is maintained in a state that the parser can access without retrieval. In some theories this state is referred to as the *focus of attention* (e.g., McElree, 2000), in others such as Lewis and Vasishth's (2005) parsing model it is the *problem buffer*. When an anaphor is encountered immediately following the verb, it is possible that it consults the contents of this buffer to find its antecedent rather than initiating a retrieval from memory.

In this study we address the extent to which the lack of facilitatory interference in anaphoric licensing depends on an anaphor's post-verbal position. If the absence of interference is a consequence of the target anaphor occupying an immediately post-verbal position, then in languages where anaphors uniformly precede their verbs, local anaphor licensing should display facilitatory effects that have not been seen in English. We tested this prediction by investigating the processing of Hindi reciprocals. Hindi is a language in which all arguments and adjuncts precede the verb in unmarked word order. In (4), for example, the subject *LaRkoN* ("boys"), the reciprocal object *ek-dusre* ("each other"), and the adjunct *kal* ("tomorrow") precede the verb *dekhaa* ("saw").

(4) LaRkoN-ne ek-dusre-ko kal dekhaa. Boys-Erg each.other-Acc yesterday saw. '(The) boys saw each other yesterday.'

Hindi reciprocals provide a minimal contrast to English reflexives because they are subject to nearly identical licensing conditions as English local anaphors. Their antecedent must have matching morphological features: in order to license the reciprocal in (5), the local subject must bear plural features. The reciprocal's antecedent must be contained in the same local clause as the reciprocal: the main clause subject in (6) cannot antecede the reciprocal in the embedded clause, despite bearing correct number marking, because it is not local to the reciprocal. Finally, the reciprocal's antecedent must also c-command the reciprocal (cf. Dayal, 1994). In (7), the plural NP *boys* does not c-command the reciprocal because it is embedded inside the adjunct phrase *at the boys' party*. It is therefore ineligible to license the anaphor.

We test whether morphological number features engender facilitatory interference effects during the processing of Hindi reciprocals.

### **SIMULATIONS**

We ran a series of computational simulations that modeled local anaphor resolution in Hindi using equally-weighted morphological and positional features as cues for retrieval. Modeling was carried out to obtain qualitative predictions about the character and direction of interference from the distractor's morphological features that could then be compared with empirical reading times in the self-paced reading experiment.

#### **PROCEDURE**

We implemented a modified version of Lewis and Vasishth's (2005) ACT-R model of sentence processing [using code originally developed by Badecker and Lewis (2007)]. ACT-R is a general cognitive architecture that has been used to model a wide range of phenomena in cognitive psychology (Anderson, 1990). In the model, items are stored as "chunks" in a contentaddressable memory and are retrieved with a success proportional to their overall activation at the time of retrieval, which is in turn determined by the overlap of their features with those of a retrieval probe. Memory access is modeled as a rational procedure that employs a general retrieval mechanism that minimizes retrieval error in the limit (Anderson, 1989; Anderson and Milson, 1989; Anderson and Schooler, 1991). Although fully implemented ACT-R parsing models exist (e.g., Lewis and Vasishth's, 2005 ACT-R parser), the simulations here focus solely on modeling retrieval latencies, abstracting away from the contributions of other modules. Retrieval latencies do not exhaust the processes that must be carried out in order to advance to the next word in a parsing task (other operations include structural attachment and integration), but for current purposes we adopt the standard assumption that longer retrieval latencies entail longer RTs (Anderson and Milson, 1989).

In the model the probability of retrieving an item i is governed by its activation Ai, computed as in (8). Bi is chunk i's baseline activation. The weight assigned to the individual cue j is represented wj. For the purposes of our simulations cues were assigned uniform weights, so this term can be effectively dropped. Sji is the strength of association between cue j and chunk i. PM in the equation below is a term that penalizes partial matches. The term ε introduces stochastic noise.

$$\text{(8)}\ \text{A}\_{\text{i}} = \text{B}\_{\text{i}}\ \Sigma\text{w}\_{\text{j}}\text{S}\_{\text{j}\text{i}} + \text{PM} + \text{e}\_{\text{i}}$$

Sji is calculated according to the Equation in (9), where S is a parameter that specifies the maximum strength of association allowed. The fanj term reflects the number of items that bear cue j. The term provides a way of quantifying the distinctiveness of a particular cue. The fan serves to decrease the associative strength between item i and cue j as a function of the number of total cues in memory that bear j.

$$\text{(9) }\text{ S}\_{\text{ji}} = \text{S} - \ln(\text{fan}\_{\text{j}})$$

Baseline activation is calculated according to (10), where d is the decay rate of a chunk's activation in memory at a given point since retrieval time tm.

$$(10)\ \text{B}\_{\text{i}} = \ln[\Sigma\_{\text{m}} \text{ t}\_{\text{m}}^{-\text{d}}],$$

The chunk with the highest activation has the shortest retrieval latency (Ti) as calculated according to the equation below, where *F* is a scaling parameter. The chunk with the shortest retrieval latency is the chunk that is retrieved in simulations.

$$(11) \ T\_{\mathrm{i}} = F \mathrm{e}^{-A\_{\mathrm{i}}}$$

The model equations above contain a number of free parameters whose settings could impact the results of the simulation. We ran a series of simulations that systematically combined parameter values from across the range of those reported in previous work. Values of the *total source activation*, *activation noise*, *fan*, *decay rate*, and *match-penalty* parameters were manipulated1 . The scaling factor (F) was held constant at 0.75 across all simulations. This resulted in the construction of 324 different models with unique parameter value combinations. As noted by Dillon et al. (2013), conducting such a sweep through the space of possible parameter values and combinations enables the identification of model predictions that are independent of idiosyncratic parameter combinations. 10,000 Monte Carlo simulations were run for each model, providing for each simulation a prediction of the most probable retrieval target and its retrieval latency.

#### **MATERIALS**

We simulated antecedent retrieval time-locked to a position corresponding to the critical reciprocal in a sentence that contained

1Total source activation took one of three values across our simulations: 1.0, 1.25, 1.5. Four values were possible for the activation noise parameter: 0.3, 0.4, 0.5, 0.6. Three values were used for the fan parameter: 1.0, 1.5, 2.0, centered at the default value of 1.5 (Lewis and Vasishth, 2005). Three decay rates were used: 0.5 (the default rate of decay; Lewis and Vasishth, 2005), 0.25, and.001. Finally, we used three values for the match-penalty parameter: −0.2, −0.4, and −0.6.

three preceding NPs. The first NP, the *subject*, corresponded to a structurally appropriate antecedent for the reciprocal. The second NP, introduced at a lag after the subject NP, corresponded to a structurally inappropriate distractor. A third NP (NP3) was also introduced to more directly model the materials in our selfpaced reading (SPR) experiment, the design of which is discussed below. The three NPs were introduced at 300 ms, 900 ms, and 1500 ms after simulation onset. Retrieval of the critical reciprocal was scheduled at 2400 ms after simulation onset.

Each NP in the simulation was marked with three features relevant for retrieval: its *category*, *number*, and *clause index*. All NPs bore the NP category feature. Number features could be either *singular* or *plural*. The *clause index* feature was used as a proxy feature for encoding an NP's structural appropriateness for the purposes of binding the reciprocal: the local licensing requirement is assumed to be satisfied if the antecedent bears the same clause index as the reciprocal. This indexing scheme can be viewed as a feature-based implementation of the clausemate constraint on local anaphor licensing (see Lasnik, 2002 for a review of such constraints, which can differ in formulation from the c-command constraints of Chomsky, 1981; Reinhart, 1983).

Models were run to simulate four distinct conditions, corresponding to different feature combinations on the subject and distractor. The number features on the subject and the distractor were manipulated, resulting in the 2 × 2 factorial design schematized in (12). In grammatical conditions the subject was pluralmarked, in ungrammatical conditions the subject was singular. In *NoInterference* conditions the distractor was singular, while in *Interference* conditions it was plural-marked. The structurally appropriate subject NP was marked with the *main clause* feature, while both the distractor and NP3 were marked as *embedded* and were therefore ineligible to antecede the reciprocal.

	- b. *Grammatical-Interference* [Subject]+PL. . . [Distractor]+PL. . . [NP3]+SG. . . [RECIPROCAL]+PL
	- c. *Ungrammatical-NoInterference* [Subject]+SG. . . [Distractor]+SG. . . [NP3]+SG. . . [RECIPROCAL]+PL
	- b. *Ungrammatical-Interference* [Subject]+SG. . . [Distractor]+PL. . . [NP3]+SG. . . [RECIPROCAL]+PL

Antecedent retrieval at the reciprocal was modeled as specifying *NP* as a category cue and *main clause* as the clause cue. The number feature *plural* was also used in the retrieval cue set, to measure the interference effect associated with morphological features.

#### **RESULTS**

We report three measures of interest from the simulations run for each condition: (i) predicted error rate, (ii) average predicted latency by condition, and (iii) predicted interference effect.

Predicted error rate corresponds to the percentage of the runs when the distractor, rather than the appropriate subject, was retrieved as an antecedent for the reciprocal. This measure is a relevant index of facilitatory interference in the ungrammatical conditions if facilitation stems from erroneous retrieval of the distractor instead of an appropriate target NP.

Predicted latency provides a measure of how long on average the winning retrieval should take in each condition. In simulations, the chunk with the shortest retrieval latency is the chunk that is retrieved from memory. According to the fully implemented ACT-R model, reading times on a particular word or phrase are the sum of the latency of retrieval triggered at that phrase and the amount of time associated with subsequent processing required by that word or phrase. Retrieval latencies should therefore map monotonically to reading times, with longer retrieval latencies corresponding to longer overall reading times, although the mental processes that intervene between retrieval and button-press may interact or contribute additional difficulty in such a way as to distort the underlying pattern of retrieval. Despite the possibility of later processing concealing underlying retrieval patterns, previous work has found a degree of relative transparency between the qualitative pattern of retrieval latencies furnished by the model and observed effects of facilitatory interference in self-paced reading or eye-tracking measures (see e.g., Wagers et al., 2009; Dillon et al., 2013).

The interference effect is a difference measure that compares average retrieval latencies between two conditions that differ on a single feature, as a way of estimating the magnitude and direction of interference contributed by the retrieval probe matching that one feature. We report two interference effects: the difference between the two grammatical conditions, as well as the difference between the two ungrammatical conditions. These comparisons provide a quantitative prediction of the effect of distractor plural marking when the features of the appropriate subject are held constant.

#### **PREDICTED ERROR RATES**

Error rates are reported in **Table 1**. The error rates are consistent with a profile of facilitatory interference. Between the *Ungrammatical* conditions, plural marking on the distractor is predicted to increase rates of erroneous retrieval compared to when there is no NP in the sentence that matches the reciprocal in features (26.1 vs. 6.5%). On some proportion of trials, the recency of the distractor is predicted to increase the NP's baseline level of activation enough to result in it being the most highly-activated NP at retrieval. In the *Ungrammatical-NoInterference* condition, the distractor does not share any features with the reciprocal's cue set, so the main subject is still more likely to be retrieved, as it matches the retrieval probe's clause index cue. Error rate is

**Table 1 | Retrieval error rates by condition for retrieval using morphological and syntactic cues calculated as the percentage of trials on which the distractor was retrieved across 10,000 runs each of 324 different models with unique parameter combinations.**

expected to differ slightly between the two grammatical conditions: misretrieval of the distractor is 5.4% more common when it bears plural marking and the main subject matches the retrieval cues completely.

#### **AVERAGE PREDICTED RETRIEVAL LATENCIES**

In the simulations the presence of a feature-matching subject has a facilitative effect on retrieval latencies (see **Figure 1**). Overall, retrieval times should be faster in the grammatical conditions because the grammatical subject, which matches the reciprocal's morphological and syntactic retrieval cues completely, is highly activated. Increased activation due to greater feature-match with the probe results in faster retrieval latencies in accordance with Equation (11). In the *Ungrammatical* conditions, where the main subject matches only on syntactic cues, retrieval latencies should be longer because the retrieved chunk should never match the probe completely. The appropriate subject only matches the probe's category and positional cues. The distractor matches the category cue and, in the *Ungrammatical-Interference* condition, the reciprocal's number feature. A pairwise difference is also predicted between the average retrieval latencies in the *Ungrammatical-NoInterference* and *Ungrammatical-Interference* conditions, which can be linked to the presence of morphological plural marking on the distractor. On the proportion of trials where the distractor is retrieved in the *Ungrammatical-Interference* condition, latencies are reduced relative to when the

main clause subject is retrieved. This results in a reduction of average latency across retrievals.

#### **INTERFERENCE EFFECTS**

Predicted interference effects are shown in **Table 2**. The grammatical interference effect was calculated by subtracting the average predicted latency in the *Grammatical-Interference* condition from the predicted latency in the *Grammatical-NoInterference* condition. The same difference was calculated for the two ungrammatical conditions. 95% confidence intervals represent the range of predicted interference effects across simulations.

The simulation results predict that a plural-marked distractor should cause facilitatory interference in the ungrammatical conditions. The *Ungrammatical-Interference* condition exhibits faster average retrieval latencies than the *Ungrammatical-NoInterference* condition. Though the size of the effect varies, a facilitatory effect was consistently observed across all parameter combinations.

A small effect of inhibitory interference is also predicted in the grammatical conditions. This inhibition can be attributed to the fan effect (see Equation 8). In the *Grammatical-Interference* condition, the strength of association between the appropriate subject and the plural retrieval cue is decreased relative to the *Grammatical-NoInterference* condition, due to the presence of another plural-marked NP (the distractor).

#### **DISCUSSION**

The goal of the simulations was to obtain predictions about the effect that a feature-matching but syntactically inappropriate distractor would have on the retrieval of an antecedent for a local reflexive if that retrieval used morphological features as cues that were weighted equally to syntactic cues.

The simulations show that when morphological cues are assigned the same weight as syntactic cues, the presence of a feature-matching distractor should decrease the parser's ability to retrieve a syntactically appropriate but feature-mismatching subject as an antecedent for a local anaphor. Some proportion of the time, the distractor is expected to be erroneously retrieved as a result of partial overlap with the retrieval cues. This misretrieval is predicted to have a facilitating effect on reading times in comparison to a case of retrieval when neither the distractor nor the local subject match the reflexive.

### **SELF-PACED READING EXPERIMENT**

The modeling results predict that retrieval of a pre-verbal reciprocal's antecedent should display facilitatory interference effects from structurally inappropriate distractors, if morphological cues

**Table 2 | Average interference effects across 10,000 runs each of 324 different models.**

such as number are assigned the same weight as syntactic cues in retrieval. The experiment below used the self-paced reading method to investigate whether evidence of the predicted facilitatory interference would be found.

#### **MATERIALS**

The experiment had a 2 × 2 factorial design that matched the simulated conditions. The design manipulated the factors GRAMMATICALITY and INTERFERENCE. The structure of the test items is schematized in (13) and an example item is given in (14). All conditions contained a critical reciprocal (*ek-dusre*) that required a plural-marked antecedent in the main clause. The reciprocal was contained in a postpositional phrase that preceded a manner adverbial (*gupt-rupse,* "*secretly"*) and the main clause verb (*baat kii,* "*chatted" lit.* "*chat did"*).

GRAMMATICALITY was manipulated by changing whether the main clause subject was plural-marked [*Doctor(-oN),* "*doctor(s)"*]. Plural marking was unambiguously marked by the inflectional suffix *–oN*. In the grammatical conditions, the main clause subject was plural and could therefore act as a grammatical antecedent for the reciprocal. In the ungrammatical conditions, the local subject was singular and the reciprocal therefore lacked a clause-mate antecedent. The factor INTERFERENCE manipulated whether the distractor [*mariiz-(oN),* "*patient(s)"*] was plural-marked.

In previous studies on local anaphor licensing (e.g., Sturt, 2003; Dillon et al., 2013) distractors have been positioned within relative clauses (RCs) attached to the main clause subject. RCmodification of subjects is a marked construction in Hindi, so the present study embedded the distractor inside a locative phrase that preceded the critical reciprocal.

The locative phrase contained an NP denoting a location modified by an animate possessor (*nurse-ke steSan,* "the nurse's station"). The distractor was embedded as the object of a verb within a prenominal RC that was attached to this possessor. In this position the distractor was not a clause-mate of the reciprocal and was therefore ineligible to act as a potential antecedent.

Critical reciprocals were always followed by a case marking post-position, either the genitive *ke*, the objective *ko*, or the dative *se*. When followed by the genitive, reciprocals were embedded in a complex post-position that was an argument to the main verb (e.g., *ke bare-me* "about" in 14). In sentences with *ko* or *se*, adverbial material was introduced after the post-position to maintain consistent length across sentences.

(13) Subject-{sg/pl} [PP[RC Distractor-{sg/pl} V] NP's Location] Reciprocal P Adv V

(14) a. *Grammatical-NoInterference* DoctoroN-ne mariiz-ki dekhbaal karne-wali nars-ke sTeSan-me ek-dusre ke-bare-me gupt-rup-se baat kii. Doctors-Erg patient-Gen care doing-RP nurse's station-in each-other aboutsecretly chat did.

'The doctors secretly spoke about each other in the station of the nurse taking care of (a/the) patient.'

b. *Grammatical-Interference*

DoctoroN-ne mariizoN-ki dekhbaal karne-wali nars-ke sTeSan-me ek-dusre ke-bare-me gupt-rup-se baat kii. Doctors-Erg patients-Gen care doing-RP nurse's stationin each-other about secretly chat did.

'The doctors secretly spoke about each other in the station of the nurse taking care of (the) patients.'

c. *Ungrammatical-NoInterference*

Doctor-ne mariiz-Gen dekhbaal karne-wali nars-ke sTeSan-me ek-dusre ke-bare-me gupt-rup-se baat kii. Doctor-Erg patient-ki care doing-RP nurse's station-in each-other about secretly chat did.

'The doctor secretly spoke about each other in the station of the nurse taking care of (a/the) patient.'

d. *Ungrammatical-Interference*

Doctor-ne mariizoN-ki dekhbaal karne-wali nars-ke sTeSan-me ek-dusre ke-bare-me gupt-rup-se baat kii. Doctor-Erg patients-Gen care doing-RP nurse's station-in each-other about secretly chat did.

'The doctor secretly spoke about each other in the station of the nurse taking care of (the) patients.'

Inside the pre-nominal RC the distractor bore either accusative or genitive case (according to the verb's requirements). Although this increased the contrast between the nominative grammatical subject and the distractor, it is unlikely that the case difference would play a role in distinguishing appropriate from inappropriate NPs, as accusative and genitive-marked NPs can serve as antecedents for local anaphors under the right structural conditions (see, e.g., Dayal, 1994; Mohanan, 1994; Bhatt and Dayal, 2007).

A second concern with the experimental materials is that there exists the potential for temporary misanalysis of the structural position of the distractor during incremental parsing. When it initially encounters the distractor, the parser has not yet encountered any information that indicates that the distractor is contained within an embedded clause. In the absence of this information, an incremental parser is likely to analyze the distractor as a constituent of the main clause. This type of temporary misparse is common in head-final languages where embedded arguments can be encountered prior to the verb that licenses them (Inoue, 1991; Mazuka and Itoh, 1995; Miyamoto, 2003). The misanalysis would be disconfirmed at the relative pronoun *wali*, at which point the object would be correctly reanalyzed as a constituent of the relative clause. This misparse should occur across all conditions, but it may have a greater impact on processing in the *Ungrammatical-Interference* condition. Under this misanalysis the RC-internal object would initially be analyzed as a suitable antecedent for an upcoming reciprocal. We return to the ability of such a misparse to affect later parsing decisions in the *Ungrammatical-Interference* condition in the discussion.

#### **PARTICIPANTS**

32 self-reported native speakers of Hindi were recruited from the student bodies of IIT, Delhi and Jawaharlal Nehru University in New Delhi (18 male, mean age = 20.1). Participants were compensated Rs. 300 for their participation, which lasted around 35 min.

#### **PROCEDURE**

Participants were run on one of two laptop PCs using the Linger software package (Doug Rohde, MIT) in a self-paced word-by-word moving window paradigm (Just et al., 1982). Each trial began with a sentence masked by dashes appearing on the screen. Letters and punctuation marks were masked, but spaces were left unmasked so that word-boundaries were visible. As the participant pressed the spacebar, a new word appeared and the previous word was re-masked. All text appeared in Devanagari font.

A yes/no comprehension question that probed its interpretation followed each sentence (experimental materials can be found at the first author's website). Participants were instructed to read sentences at a natural pace and to respond to the comprehension questions as accurately as possible. Participants responded to questions using the f-key for "yes" and the j-key for "no." If the question was answered incorrectly the word *galat* ("incorrect/wrong") appeared briefly in the center of the screen. Each participant was randomly assigned to one of the lists and the order of the stimuli within the presentation list was randomized for each participant.

### **ANALYSIS**

Data from one participant were excluded due to failure to comply with experimental guidelines. Data from another participant were excluded because the participant's mean accuracy on comprehension questions was close to chance. This resulted in the data of 30 subjects being used for later analysis. Two items were excluded from analysis due to errors.

Statistical analyses were carried out on log-transformed reading times using linear mixed effects regression (Baayen et al., 2008). Reading times from both correct and incorrect trials were included in the analysis. Experimental fixed effects were the simple difference sum-coded factors GRAMMATICALITY and INTERFERENCE and their interaction. All models included random intercepts for both subjects and items. Models with a maximal random effects structure were fit whenever possible (Barr et al., 2013). If a maximal model failed to converge, a model was used that contained only by-subject random slopes for both fixed effects and their interaction.

#### **RESULTS**

#### *Comprehension Question Accuracy*

Comprehension question accuracy averaged 69.2%. No significant differences were found in average accuracy across conditions (logistic mixed effects model, all *z*s < 1).

#### *Reading Time Results*

Reading times from the post-reciprocal region are given in **Figure 2**.

*Pre-reciprocal region.* No significant effects were found in the pre-reciprocal region.

*Reciprocal region.* No significant effects were found in the reciprocal region.

*Post-position region.* Average reading times were reliably faster in the grammatical conditions than in the ungrammatical conditions (main effect of GRAMMATICALITY: βˆ = −0.088, s.e. = 0.034, *t* = −2.92); see **Figure 3**. Although reading times in the *Ungrammatical-Interference* condition were numerically longer than those in the *Ungrammatical-NoInterference* condition, the GRAMMATICALITY × INTERFERENCE interaction was not significant (*t* = 1.41). No reliable pairwise differences were observed between ungrammatical conditions (*t* < 1).

*Reciprocal***+***2 region.* There were no significant main effects two regions after the critical reciprocal, but the model revealed a marginally significant GRAMMATICALITY × INTERFERENCE interaction (βˆ = 0.105, s.e. = 0.054, *t* = 1.96) two regions after the reciprocal. This interaction reflected the fact that the *Ungrammatical-Interference* condition was read more slowly than any other condition, including the *Ungrammatical-NoInterference* condition. The pairwise comparison between the two ungrammatical conditions revealed the numerical difference between the

two conditions not to be significant (*t* = 1.3). However, given the relatively low power of the current study, it is possible that this interaction would achieve significance with higher power. We return to this interaction effect in the discussion.

*Reciprocal***+***3 till Final region.* No significant effects were observed in any subsequent region.

#### **DISCUSSION**

The SPR experiment sought to determine whether the processing of a pre-verbal reciprocal in Hindi was subject to facilitatory interference. The study manipulated the number features on a structurally appropriate antecedent for the reciprocal, as well as the features of the structurally inappropriate distractor, as a means of testing whether (equally weighted) morphological cues are used to access a local anaphor's antecedent.

When a structurally appropriate feature-matching antecedent was present to license the pre-verbal reciprocal the regions following the critical reciprocal were read more rapidly than when there was no feature-matching and structurally appropriate antecedent. In contrast to the prediction of the model simulations, we failed to find any evidence of facilitatory interference (see **Figure 4**). In fact, the empirical results trend in the opposite direction; there were clear inhibitory effects. The post-reciprocal region in the *Ungrammatical-Interference* condition was read at a comparable or slightly slower rate than the processing of the reciprocal

in the *Ungrammatical-NoInterference* condition. Despite the fact that our study potentially lacks the power to observe an interference effect, we are more secure in our conclusion that there is a lack of facilitatory interference in light of the direction of the numerical trend toward an interaction in the post-reciprocal region.

Two words downstream from the reciprocal, reading times were longest when the local subject did not match the features of the reciprocal but the features of the distractor did match the reciprocal's number features.2 We discuss this effect below because although it is inconsistent with the predictions of our simulations, it does potentially indicate that the distractor's morphological features may affect overall processing of the reciprocal.

The mechanism by which the distractor exerts inhibitory influence on reciprocal licensing is unclear. It is commonly assumed that inhibitory interference should occur when multiple items in memory match a retrieval cue (e.g., Badecker and Straub, 2002; Lewis and Vasishth, 2005; Van Dyke and McElree, 2011). Yet, we observed inhibition in the absence of a multiple-match configuration: the main subject matched the positional cue and the distractor matched the number cue. This suggests that the mechanism used to explain inhibition in multiple-match cases (e.g., the fan effect in Lewis and Vasishth's, 2005 model), is not the appropriate explanation for our finding. We consider three possible explanations of this inhibitory effect and the role

2We expect that this effect would be stronger with a larger sample.

that number features play in guiding initial retrieval under each scenario.

The first possible interpretation of the inhibitory effect links the slightly delayed slowdown to erroneous retrieval of the distractor during initial memory access. The increased reading times in our SPR experiment might reflect initial misretrieval of the distractor based on its morphological overlap with the probe, followed by the increased processing cost of inhibiting that distractor. This line of reasoning has been pursued by Patil et al. (2012) and Chen et al. (2012) to explain inhibitory effects in reflexive licensing. We consider this interpretation unlikely for the present data because we see no evidence of the erroneous retrieval on which the explanation is predicated. In light of subject-verb agreement and NPI licensing effects, we would expect initial misretrieval to result in some degree of facilitation, however fleeting, that would be observable in the self-paced reading times. These facilitatory interference effects consistently yield large effects on reading times in studies of other linguistic dependencies. No such facilitation was observed prior to the point of inhibitory interference in the current study.

The inhibitory effect might also be explained in terms of *cueconfusability*, as defined by Jäger et al. (2014). The proposal rests on the speculation that cues that reliably co-occur in specific retrieval contexts can be confused (less effectively deployed). In reciprocal licensing the clause and plural cues are reliably associated because both cues should be selected whenever a reciprocal is encountered. This contrasts with cue association in reflexive licensing where specific gender cues (e.g., masculine and feminine) and the clause-mate cue co-occur less reliably, e.g., it is not the case that reflexive licensing uniformly uses masculine gender. According to the proposal, confusion is more likely to occur in reciprocal licensing than in reflexive licensing. Although we note that this is a possibility in principle, we believe that the notion of cue-confusability or the mechanism by which confusion creates retrieval interference has not been sufficiently articulated to be thoroughly evaluated.

The third alternative interpretation of the effect connects the slowdown to the influence of an abandoned early garden-path parse that analyzed the distractor as a constituent of the main clause. The previous partial parse could provide an appropriately marked antecedent for the reciprocal, but would fail to provide a coherent global parse. There are no grammatical re-parses of the sentence that would allow the distractor to be reanalyzed as an appropriate antecedent for the reciprocal. We hypothesize that resolving the tension between attempting to license the reciprocal and building a globally grammatical parse of the sentence is the source of the observed interaction. The misparse is expected to intrude on the processing of the reciprocal in the *Ungrammatical-Interference* condition, where consideration of the reparse would result in a structurally appropriate, feature-matching antecedent for the reciprocal.

We favor the interpretation that this inhibitory effect reflects the influence of the mis-parse on repair strategies that are triggered by failure of initial antecedent retrieval (as proposed for similar effects by, Sturt, 2003; Chow et al., 2014). On this interpretation the failure to retrieve an appropriate antecedent for the reciprocal would initiate a more liberal search for a feature-matching phrase, or would attempt to find an alternative parse for the sentence under which the reciprocal could be grammatically bound. These repair procedures are argued to be less constrained by the structure of the previous parse (and therefore structural constraints), perhaps reflecting uncertainty in the structural analysis in light of the error signal. This scenario attributes the increase in reading times to interference, but not interference that occurs during antecedent retrieval. Rather, the locus of interference lies in retrievals associated with syntactic revision and reanalysis. It is also possible that the distractor in the mis-parsed sentence could contribute interference at retrieval time, a possibility that would be consistent with the numerical trend toward an interaction in the post-reciprocal region. We acknowledge that the present study cannot distinguish between these two options.

In sum, our SPR experiment failed to find the characteristic profile of facilitatory interference that has been found in other studies on the construction of subject-verb agreement, NPIlicensing, and control dependencies and is predicted under a cue-based retrieval model that uses morphological cues to access potential antecedents for a local anaphor. Instead, a featurematching distractor triggered a delayed inhibitory effect when the local subject could not antecede the reciprocal in Hindi. We argued that this process was not an indication of interference during antecedent retrieval, but rather interference during a repair process subsequent to antecedent retrieval.

#### **GENERAL DISCUSSION**

The purpose of the present study was to assess whether syntactic cues are given priority over morphological cues in the retrieval of antecedents of pre-verbal reciprocals in Hindi. Investigating the processing of Hindi reciprocals helps to establish whether the absence of facilitatory interference effects from morphologicallymatched distractors in previous experiments was due to a confound of anaphor position. We hypothesized that if the absence of interference were solely due to the post-verbal position of the anaphor, and not prioritization of syntactic cues, interference would be observable in the retrieval of an antecedent for a pre-verbal anaphor in Hindi.

In our self-paced reading study native Hindi speaking participants resolved a local reciprocal dependency more quickly when the main clause subject was plural than when no grammatical antecedent was present. The presence of a feature-matching distractor did not induce reliable effects of facilitatory interference when the local subject did not match the reciprocal in features. These findings are consistent with a general lack of facilitation in the licensing of local anaphors found in previous work (e.g., Sturt, 2003; Xiang et al., 2009; Dillon et al., 2013), and with lack of interference during local anaphor licensing more generally (e.g., Nicol and Swinney, 1989; Clackson, 2011). The presence of a feature-matching distractor produced a delayed inhibitory effect when an appropriate antecedent for the reciprocal could not be found. We reasoned that the inhibitory effect in our experiment might have arisen as a result of error-driven repair strategies, and not from participants accessing the distractor during initial antecedent retrieval.

The empirical results of our SPR experiment were compared against the results of a series of simulations that modeled latencies and error rates of a cue-based retrieval process that used equally-weighted morphological and positional cues to retrieve antecedents of a local anaphor. The empirical results did not align with the simulations' prediction that there should be facilitatory interference between ungrammatical conditions.

Overall, the results lend support to the hypothesis that the lack of facilitatory interference in local anaphor antecedent retrieval is not primarily determined by an anaphor's post-verbal position. In particular, the Hindi results appear to be incompatible with a number of the possible ways in which verbal adjacency could influence retrieval of antecedents for local anaphors discussed. The results cast doubt on explanations that rely on recent reactivation of the grammatical antecedent immediately before the reciprocal. In the Hindi materials there is no point at which retrieval of the subject is required between the distractor and when the reciprocal is encountered.

The results are consistent with models of cue-based antecedent retrieval that prioritize syntactic information in one manner or another. As noted in the introduction, a parser could be said to prioritize syntactic cues by assigning them greater weight than morphological cues, or by using syntactic cues exclusively.

Because some dependencies display facilitatory interference effects while others do not, it would appear that retrieval does not consistently prioritize positional cues. One question that arises is how the parser determines when it should prioritize syntactic cues. Rational models often assume that retrieval uses a set of cues and weights that maximizes the probability of retrieving the target, while minimizing the chances of interference. It is important to note that the optimal cue set for meeting both of these goals may change as a function of (i) the dependency being computed and (ii) the local syntactic context. Therefore, strategic considerations that take the local context into account may comprise an important part of the cue selection procedure. We term different solutions that the parser could adopt *retrieval strategies*.

The parser could adopt one of two strategies that make different use of morphological cues during local antecedent retrieval. First, the parser could uniformly prioritize syntactic cues for all instances of local antecedent retrieval regardless of syntactic context. Dillon et al. (2013) proposed that the parser implements such a retrieval strategy. According to these authors, local antecedent retrieval only uses structural cues.

An alternative to this proposal is that the parser could condition the use of morphological cues on the local syntactic context of the anaphor that triggers retrieval, as proposed by Kush (2013). The intuition behind this proposal stems from the observation that in certain environments structural cues alone may not suffice to identify a unique antecedent for a local anaphor. If the subject of the local clause is the anaphor's only co-argument, as it is in (15), then syntactic cues are sufficient to guarantee its retrieval. However, if there exists an additional co-argument that precedes the anaphor as in (16), a syntactic cue like the clause feature would not be able to distinguish the appropriate antecedent (*the boys*) from the structurally appropriate, but feature-mismatching NP *Mary*.

Kush (2013) proposed that a parser that could determine the number of clause-mates that preceded a local anaphor might use morphological cues to help guarantee retrieval of an appropriate antecedent. Determining whether the local subject is the anaphor's only clause-mate should be possible by consulting the local syntactic context. When processing English reflexives in direct object position, the anaphor's adjacency to the verb would be sufficient. In Hindi, verbal adjacency cannot be exploited to make such a determination. Kush (2013) proposed that the decision could be made if cue selection had access to the phrase structure rule being used to incrementally parse the input sentence. In cases where the anaphor is the first NP encountered during the incremental parse of the VP, the phrase structure predicted for the VP should not contain co-argument NPs. On the other hand, if the parser encounters a non-subject co-argument that precedes the reciprocal, the PS rule for the VP would reflect its presence and cue selection could determine that the clause index cue would no longer provide diagnostic access to the local subject.

If the parser adopts this retrieval strategy interference effects are predicted to emerge when there are non-subject clause-mates that precede a local anaphor. This proposal is consistent with recent findings from Wagers and colleagues, which suggest that that resistance to interference is, in fact, selectively conditioned on whether the anaphor is encountered after another co-argument (King et al., 2012). Under this interpretation, interference should emerge if a co-argument preceded the reciprocal in Hindi, as in (17). We leave testing this prediction to future work.

(17) ∗Larke-ne Mary-ko baccoN-ki party me ek-dusre ke-bareme bataayaa. Boy-Erg Mary-Acc kids' party in one-another about told. ∗The boy told Mary during the kids' party about *each other*.

### **CONCLUSION**

In this paper we asked whether the absence of intrusive licensing during local anaphor antecedent retrieval is restricted to postverbal anaphors, or whether the lack of interference indicates a more general cross-linguistic state of affairs. We investigated the effect of a feature-matching distractor on the processing of unlicensed pre-verbal reciprocals in Hindi and found no indication of facilitatory interference. The results suggest that antecedent retrieval's ability to accesses the syntactically appropriate subject when licensing a local anaphor does not depend on direct verbal adjacency between the anaphor and its verb. The results appear to be better explained by a cue-based retrieval process that prioritizes, or exclusively uses, structural cues over morphological features. Finally, although we did not find evidence that a feature-matching distractor facilitates the processing of an unlicensed reciprocal, it did appear that a distractor might exert an inhibitory influence on some stage of reciprocal resolution. Future work should test whether this inhibition is a general effect, or whether its appearance is related to properties of the materials used here.

### **ACKNOWLEDGMENTS**

The results from our SPR experiment were previously presented at the CUNY Sentence Processing and GLOW Conferences in 2012. We thank Usha Udaar, Karthik, Pritha Chandra and Ayesha Kidwai for their assistance in recruiting participants and providing space to run Experiment 1. We thank Ashok, Ambrish, and Manu Kush for helping to construct the materials for the SPR experiment. The code used for the simulations was generously provided by Rick Lewis. We thank Brian Dillon, Pedro Alcocer, and Dan Parker for their subsequent revisions and additions to this code. Shravan Vasishth and Umesh Patil also provided useful discussion. This work was supported by NSF IGERT DGE-0801465 to University of Maryland.

### **REFERENCES**

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Received: 22 April 2014; accepted: 15 October 2014; published online: 05 November 2014.*

*Citation: Kush D and Phillips C (2014) Local anaphor licensing in an SOV language: implications for retrieval strategies. Front. Psychol. 5:1252. doi: 10.3389/fpsyg. 2014.01252*

*This article was submitted to Language Sciences, a section of the journal Frontiers in Psychology.*

*Copyright © 2014 Kush and Phillips. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

# **Teasing apart retrieval and encoding interference in the processing of anaphors**

*Lena A. Jäger 1 \*, Lena Benz 1, Jens Roeser 2, Brian W. Dillon3 and Shravan Vasishth1*

*1 Department of Linguistics, University of Potsdam, Potsdam, Germany, 2 Department of Psychology, Nottingham Trent University, Nottingham, UK, 3 Department of Linguistics, University of Massachusetts, Amherst, MA, USA*

Two classes of account have been proposed to explain the memory processes subserving the processing of reflexive-antecedent dependencies. Structure-based accounts assume that the retrieval of the antecedent is guided by syntactic tree-configurational information without considering other kinds of information such as gender marking in the case of English reflexives. By contrast, unconstrained cue-based retrieval assumes that all available information is used for retrieving the antecedent. Similarity-based interference effects from structurally illicit distractors which match a non-structural retrieval cue have been interpreted as evidence favoring the unconstrained cue-based retrieval account since cue-based retrieval interference from structurally illicit distractors is incompatible with the structure-based account. However, it has been argued that the observed effects do not necessarily reflect interference occurring at the moment of retrieval but might equally well be accounted for by interference occurring already at the stage of encoding or maintaining the antecedent in memory, in which case they cannot be taken as evidence against the structure-based account. We present three experiments (self-paced reading and eye-tracking) on German reflexives and Swedish reflexive and pronominal possessives in which we pit the predictions of encoding interference and cue-based retrieval interference against each other. We could not find any indication that encoding interference affects the processing ease of the reflexive-antecedent dependency formation. Thus, there is no evidence that encoding interference might be the explanation for the interference effects observed in previous work. We therefore conclude that invoking encoding interference may not be a plausible way to reconcile interference effects with a structure-based account of reflexive processing.

**Keywords: anaphors, reflexives, possessives, eye-tracking, German, Swedish, working-memory, interference**

### **1. Introduction**

A central task the human sentence processing mechanism has to accomplish is to link two parts of a syntactic dependency, irrespective of how much linguistic material separates the two dependents. Many theories of sentence processing therefore assume that upon encountering the second dependent, the parser triggers a memory retrieval to access the first dependent in order to integrate it with the current node (Gibson, 2000; Lewis and Vasishth, 2005). Interference effects have recently come into focus in sentence processing research because they are taken to be

#### *Edited by:*

*Colin Phillips, University of Maryland, USA*

#### *Reviewed by:*

*Cristiano Chesi, Istituto Universitario di Studi Superiori di Pavia, Italy John E. Drury, Stony Brook University, USA*

#### *\*Correspondence:*

*Lena A. Jäger, Department of Linguistics, University of Potsdam, Karl-Liebknecht-Str. 24-25, Potsdam 14476, Germany<EMAIL_ADDRESS>
#### *Specialty section:*

*This article was submitted to Language Sciences, a section of the journal Frontiers in Psychology*

*Received: 12 January 2015 Paper pending published: 13 March 2015 Accepted: 09 April 2015 Published: 09 June 2015*

#### *Citation:*

*Jäger LA, Benz L, Roeser J, Dillon BW and Vasishth S (2015) Teasing apart retrieval and encoding interference in the processing of anaphors. Front. Psychol. 6:506. doi: 10.3389/fpsyg.2015.00506* informative about the more precise nature of the retrieval mechanisms that subserve sentence processing. However, the relationship between empirically observed similarity-based interference effects and theories of retrieval is somewhat indirect, because there are multiple distinct mechanisms that could give rise to similarity-based interference effects in online processing. Indeed, whether or not the observation of interference effects can be interpreted as evidence favoring one or another account of sentence processing depends on the exact mechanisms causing the interference effects. In this article, we will present different mechanisms that have been proposed to account for interference effects in sentence comprehension and present three experiments with different methodologies and languages to tease them apart. We will first give an overview of two kinds of mechanisms, *cuebased retrieval interference* and *encoding interference*, which in the working memory literature have been proposed to underly similarity-based interference. Subsequently, we will turn to the implications for sentence processing and antecedent-retrieval in the processing of reflexives in particular.

Similarity-based interference has long been known to be a major cause of forgetting (Anderson and Neely, 1996). In memory models which represent items as bundles or vectors of features, similarity-based interference is assumed to arise as a function of the degree of overlap between an item's features with the features of other items in memory (Nairne, 1988, 1990; Anderson and Neely, 1996; Anderson and Lebiere, 1998; Anderson et al., 2004; Oberauer and Kliegl, 2006; Lewandowsky et al., 2008). However, the various memory models differ with respect to the mechanisms which they assume to underlie similarity-based interference. Generally speaking, one can distinguish between two kinds of similarity-based interference. On the one hand, similarity-based interference is assumed to affect the encoding or maintenance of an item (Nairne, 1988, 1990; Oberauer and Kliegl, 2006; Lewandowsky et al., 2008). We will refer to this proposal as *encoding interference*. On the other hand, similarity-based interference is assumed to arise during the retrieval of an item (Anderson and Neely, 1996; Anderson and Lebiere, 1998; Anderson et al., 1998, 2004; McElree, 2006; Oberauer and Kliegl, 2006). We will refer to this second proposal as *cue-based retrieval interference*.

Encoding interference is assumed to arise from the competition between the features of similar items that occurs at the moment of encoding or maintaining items in memory. Nairne (1990), for instance, proposed that whenever two items share a feature, they compete for this feature. In a certain proportion of cases, the memory representation of one of these items therefore loses this feature.1 Hence, this item's memory representation becomes less distinct from other items and, as a result, retrieval probability decreases. An important, but subtle, point here is that even though encoding interference arises at the stage of encoding or maintaining an item in memory, it has an impact on the ease of this item's later *retrieval*. Oberauer and Kliegl (2006), who adopted Nairne (1990)'s concept of feature-overwriting, implemented the idea of an item's memory representation being degraded by decreasing this item's activation level. At the moment of later retrieval, this lower activation level leads to lower retrieval probability and a slow-down in processing times. In their model, the retrieval of an item from working memory is implemented as its gradual activation into the focus layer of the memory system. The processing speed of this gradual activation is defined as a function of this item's activation level prior to retrieval. Thus, if an item's activation level is decreased due to encoding interference from competitor items, a slow-down in the retrieval process is predicted. Note that Oberauer and Kliegl (2006) do not make any predictions about retrieval latencies. Their model is designed to explain data collected in speed-accuracy tradeoff experiments, where they experimentally controlled the time point when retrieval was supposed to happen. In their model, the slow-down in the retrieval process therefore is reflected in a higher proportion of retrieval failures rather than in increased retrieval latencies because participants are forced to interrupt the retrieval process after an experimentally defined time lag. Translating the Oberauer and Kliegl (2006) model to sentence processing, where the participant has more time to carry out retrieval, leads us to the assumption that the slow-down in the retrieval process is reflected in longer retrieval latencies. For the predictions of the experiments reported in this article, we will refer to encoding interference as implemented in the Oberauer and Kliegl (2006) model, with the additional assumption that a slow-down in the retrieval process leads to increased retrieval latencies. In sum, although encoding interference acts at the moment of encoding and maintenance rather than at retrieval, it indirectly affects the success and the speed of the retrieval process because it results in a representation that is more difficult to access.

Cue-based retrieval interference, in contrast, is assumed to arise due to cue-overload at the moment of retrieval. In a content-addressable memory architecture, cue-overload refers to a scenario when the cues used for retrieval do not point to a unique target, but rather match multiple items (Watkins and Watkins, 1975). This is assumed to lead to misretrievals of partially matching distractor items (Anderson and Lebiere, 1998; Anderson et al., 2004; McElree, 2006) and mutual inhibition between the distractors and the target resulting in a higher retrieval latency in case the target and the distractor have one or more retrieval relevant features in common (Anderson and Lebiere, 1998; Anderson et al., 2004).2 To summarize, encoding interference is predicted to occur whenever items share features, no matter whether these features are used for retrieval or not. Cue-based retrieval interference, in contrast, is predicted to occur when more than one item matches the retrieval features. Inhibition between these items occurs only when they match the same retrieval features, otherwise cue-based retrieval interference

1Nairne (1990) did not use the term *encoding interference* but rather *featureoverwriting* to refer to his conception of interference.

2Note that the model proposed by McElree (2006) predicts that cue-based retrieval interference is reflected only in retrieval probability, not in retrieval latency. In contrast, the ACT-R architecture developed by Anderson and Lebiere (1998) and Anderson et al. (2004), on which the Lewis and Vasishth (2005) model of sentence processing is based, predicts retrieval interference to be reflected in both, retrieval probability and retrieval latency.

is reflected only in misretrievals (Anderson et al., 2004). Note that encoding interference and cue-based retrieval interference are not mutually exclusive concepts. Indeed, in Oberauer and Kliegl (2006)'s working memory model, both retrieval and encoding interference are assumed and the authors show that their interference model is indeed able to account for a large range of data.

In sentence processing research, early studies investigating interference effects point rather toward encoding than cue-based retrieval interference, but they were not designed to disentangle the two. For example, Gordon et al. (2002) conducted a self-paced reading experiment where participants held a set of nouns in memory while reading the target sentence. The authors report a slow-down in reading times when the noun type (common noun vs. proper name) of the memory load words matched the nouns in the sentence compared to when the memory load nouns and the nouns in the sentence were of different types. These results are further supported by Fedorenko et al. (2006), who also observed similarity-based interference in a memoryload paradigm. Gordon and colleagues report similar results for studies that manipulated similarity between sentence internal nouns rather than memory load (Gordon et al., 2001, 2004, 2006). An example item taken from Gordon et al. (2006) is shown in (1).

### (1) **Interference/No interference** *The banker that the barber/Sophie praised climbed the mountain . . .*

Since in all of these studies, similarity of the nouns was manipulated while the efficiency of the retrieval cues (i.e., the degree to which the retrieval cues uniquely identify the target) remained constant across experimental conditions, the data reported by Gordon and colleagues favor rather encoding than cue-based retrieval interference as an explanation. However, as Van Dyke and McElree (2006) noted, the above cited studies found interference effects only in the region where the critical noun phrase was retrieved (i.e., at the region containing the verb). This might indicate that the observed effect should rather be attributed to cue-based retrieval interference since encoding interference should also affect processing ease at the moment of encoding, i.e., at the moment when the second of the similar nouns is first being encountered. Van Dyke and McElree (2006) conducted a memory load experiment where, in contrast to the memory load experiments reported by Gordon et al. (2002) and Fedorenko et al. (2006), the memory load words were held constant across experimental conditions, but the retrieval cues at the verb were manipulated. The experimental items consisted of object-cleft sentences in which the main clause object preceded the main clause verb (the critical region where retrieval was triggered); for an example taken from Van Dyke and McElree (2006) see (2).

### (2) **Interference/No interference**

*It was the boat that the guy who lived by the sea sailed/ fixed in two sunny days.*

Memory load: *table*, *sink*, *truck*

When the memory load words fit the semantic constraints of the verb, a slow-down in self-paced reading times was observed. These results cannot be attributed to encoding interference since the degree of similarity between the memory load words and the verb's object NP is constant across conditions. Van Dyke and McElree (2006)'s data are thus clear evidence for cuebased retrieval interference playing a role in sentence processing. However, note that the possibility that both retrieval and encoding interference affect sentence processing ease cannot be excluded by Van Dyke and McElree (2006)'s study since their data is clear evidence for cue-based retrieval interference but no evidence *against* encoding interference affecting sentence processing in general.

In recent years, interference effects in the processing of reflexive-antecedent dependencies have drawn considerable attention. The underlying research question was whether unconstrained cue-based retrieval, as proposed by Badecker and Straub (2002) and Patil, Vasishth, and Lewis (unpublished manuscript), or a structure-based access mechanism, as proposed by Nicol and Swinney (1989) and Sturt (2003), subserves the processing of reflexive-antecedent dependencies. Unconstrained cue-based retrieval assumes that all available cues are used to retrieve a reflexive's antecedent. Structure-based accounts, in contrast, assume that structural, i.e., syntactic tree-configurational, information guides the retrieval process. Interference effects in reflexive processing have been generally interpreted in terms of cue-based retrieval interference and taken as evidence for a cue-based retrieval mechanism since *retrieval* interference from syntactically inaccessible constituents is incompatible with the structure-based account. However, as pointed out by Dillon (2011) and Dillon et al. (2013), many of the observed effects—which we will describe more in detail below—can equally well be accounted for by *encoding* interference and hence are not necessarily incompatible with the structure-based account. Indeed, for the kind of materials commonly used to investigate the processing of reflexives (see 3; example taken from Sturt, 2003), encoding interference makes the same predictions for all experimental conditions as the unconstrained cue-based retrieval account implemented in the Lewis and Vasishth (2005) sentence processing model, which is based on the general cue-based architecture Adaptive Control of Thought-Rational (ACT-R) (Anderson and Lebiere, 1998; Anderson et al., 2004) and has been widely used for modeling the processing of reflexives (Dillon, 2011; Dillon et al., 2013; Parker and Phillips, 2014; Kush and Phillips, 2014; Jäger et al., 2015; Patil et al., unpublished manuscript).3 Thus, for the question of structure-based vs. unconstrained cue-based retrieval in reflexives, it is crucial to disentangle encoding from cue-based retrieval interference. If evidence can be found showing that encoding interference plays a role in the type of materials generally used to investigate the processing of reflexives, this implies that the interference effects that have

3The Lewis and Vasishth (2005) model *per se* does not make any commitments with respect to the question which features are used as retrieval cues. Hence it is also possible to implement the structure-based account in this framework by restricting the set of retrieval cues to structural features.

been interpreted as evidence favoring unconstrained cue-based retrieval are equally well compatible with a structure-based account.

(3)

a. **Antecedent-match; distractor-match**

*The surgeoni who treated Jonathanj had pricked* **himself***i*/∗*j* ...

#### b. **Antecedent-match; distractor-mismatch**

*The surgeoni who treated Jenniferj had pricked himselfi*/∗*j ...*

c. **Antecedent-mismatch; distractor-match** *The surgeoni who treated Jenniferj had pricked herselfi*/∗*j ...*

### d. **Antecedent-mismatch; distractor-mismatch** *The surgeoni who treated Jonathanj had pricked herselfi*/∗*j ...*

Studies investigating interference effects in the processing of reflexives mostly tested sentences in which the reflexive was bound by the local subject which c-commanded the reflexive (*surgeon* in Example 3; henceforth referred to as *antecedent*). We will express the antecedent's conformance to the structural requirements for binding the reflexive by attributing the feature {c-com:+} to it.4 The interference manipulation was achieved by inserting another noun phrase in a structurally inaccessible position, i.e., not c-commanding the reflexive ({ccom:-}) and hence not qualifying as a binder for the reflexive (*Jonathan/Jennifer* in Example 3; henceforth referred to as *distractor*). A non-structural feature (e.g., gender or number in English reflexives) of this distractor was manipulated. Crucially, the feature which was manipulated might theoretically be used as a retrieval cue. For example, in the processing of English reflexives, the gender feature {gender:masc/fem} marked at the reflexive *himself* or *herself* might be used as a cue to retrieve the antecedent. Thus, if gender is used as a retrieval cue, a gender-matching distractor is predicted to cause cue-based retrieval interference as compared to a distractor which does not match the gender of the reflexive. Therefore, interference effects caused by a feature-matching distractor can be interpreted as evidence favoring an unconstrained cue-based retrieval account. If, in contrast, no effect of a feature-matching distractor is observed, this can be taken as evidence for a structure-based account. This experimental design (or a variation thereof) was used by a large number of studies which aimed to decide whether an unconstrained cue-based retrieval or a structure-based access underlies the processing of reflexive antecedent-dependencies (Nicol and Swinney, 1989; Badecker and Straub, 2002; Sturt, 2003; Xiang et al., 2009; Chen et al., 2012; King et al., 2012; Cunnings and Felser, 2013; Dillon et al., 2013; Clackson and Heyer, 2014; Kush and Phillips, 2014; Parker and Phillips, 2014; Jäger et al., 2015; Patil et al., unpublished manuscript). Some of the cited studies also manipulated feature-match of the structurally accessible antecedent (*surgeon* in Example 3).5 An effect of antecedent match/mismatch can be accounted for by both unconstrained cue-based retrieval and structure-based accounts.

The results of the above cited studies are mixed. In antecedentmatch conditions, increased processing difficulty due to the presence of a cue-matching distractor has been reported by Badecker and Straub (2002), Experiments 3, 4, Chen et al. (2012), Clackson and Heyer (2014), Jäger et al. (2015), Experiment 2, and Patil et al. (unpublished manuscript). By contrast, Sturt (2003), Experiment 1, and Cunnings and Felser (2013), Experiment 2 found a facilitation due to a cue-matching distractor. It should be noted that in Sturt (2003)'s experiment, the effect appeared only delayed and in Cunnings and Felser (2013)'s study, the interference effect was only observed in participants with low working-memory span. Importantly, in a large number of studies, no interference effect in antecedent-match conditions was observed (Nicol and Swinney, 1989; Badecker and Straub, 2002, Experiments 5, 6; Sturt, 2003, Experiment 2; King et al., 2012; Dillon et al., 2013; Kush and Phillips, 2014; Parker and Phillips, 2014; Jäger et al., 2015, Experiment 1). In antecedentmismatch conditions, a significant processing speed-up due to a cue-matching distractor is reported by King et al. (2012) and Parker and Phillips (2014). The opposite direction of the effect was only observed in Jäger et al. (2015), Experiment 1. The absence of an effect in antecedent-mismatch conditions is reported by Sturt (2003), Xiang et al. (2009) and Dillon et al. (2013). For a literature review of interference effects in reflexives, see Jäger et al. (2015).

As mentioned above, unconstrained cue-based retrieval as implemented in the Lewis and Vasishth (2005) ACT-R model of sentence processing makes precisely the same predictions as encoding interference for sentences like the ones shown in (3). For conditions with a cue-matching antecedent (see 3a,b), the Lewis and Vasishth (2005) model predicts cue-based retrieval interference when the distractor matches the gender of the reflexive (3a). This retrieval interference is predicted to be reflected in inhibition between the antecedent and the distractor because in (3a), but not in (3b), the antecedent (*surgeon*) and the distractor (*Jonathan*) share the gender cue {gender:masc}. Thus, longer retrieval latencies (and hence longer reading times at the reflexive) are predicted in (3a) compared to (3b). Moreover, misretrievals of the partially cue-matching distractor (*Jonathan* in 3a) are predicted. These misretrievals are predicted to be reflected in response-accuracies if the comprehension questions target the reflexive-antecedent dependency. For conditions with a mismatching antecedent (see 3c, d), the unconstrained cue-based retrieval model (Lewis and Vasishth, 2005) also predicts cuebased retrieval interference due to a cue-matching distractor (3c). As in antecedent-match conditions, this retrieval interference is

4It should be noted that using {c-com:+} as a feature is a simplification since a tree-configurational relation is not as straightforward to code as a feature of an item as, e.g., gender or number. For a discussion of how tree-configurational information such as c-command could be encoded as an item's feature see Alcocer and Phillips (unpublished manuscript). On a theoretical basis, Kush (2013) argues against the representation of c-command as a feature and discusses how, in online sentence processing, the human parser might distinguish between c-commanding and non-c-commanding antecedents.

5In some experiments, only the stereotypical gender of the accessible antecedent was violated (as in 3c,d), whereas in other studies, real feature violations were used resulting in ungrammatical sentences in the antecedent-mismatch conditions.

predicted to be reflected in a higher proportion of misretrievals of the matching distractor. But, in contrast to antecedent-match conditions, no inhibition between the antecedent and the distractor is predicted because they do not share any of the experimentally manipulated retrieval relevant features (in 3c and d, the antecedent and the distractor neither share the gender cue {gender:fem} nor the structural cue {c-com:+}). Since ACT-R predicts faster retrieval latencies in the case of misretrievals as a result of a race-like configuration, the trials with misretrievals are predicted to lead to a decreased mean retrieval latency. Therefore, in the absence of inhibition between the distractor and the antecedent in antecedent-mismatch conditions, faster processing times are predicted when a feature-matching distractor is present.

Encoding interference predicts increased retrieval latencies and a higher proportion of misretrievals as a function of the number of features the target (here the antecedent) shares with other items in memory (Oberauer and Kliegl, 2006).6 Thus, in conditions with a matching antecedent (see 3a,b), a slowdown and a higher proportion of misretrievals due to a featurematching distractor (3a) is expected. By contrast, in conditions with a mismatching antecedent (see 3c,d), a slow-down and a higher proportion of misretrievals due to a *feature-mismatching* distractor (3d) is predicted since the mismatching antecedent and the mismatching distractor have the same gender feature {gender:masc}.7

To summarize, for materials as the ones presented in (3), both encoding interference and cue-based retrieval interference predict that a matching distractor leads to a processing slow-down in antecedent-match conditions and to a speedup in antecedent-mismatch conditions. For online reading time measures, both accounts thus make precisely the same predictions and can account for the inhibitory effects in antecedent-match conditions reported by Badecker and Straub (2002), Chen et al. (2012), Clackson and Heyer (2014), Jäger et al. (2015) and Patil et al. (unpublished manuscript) as well as for the facilitatory effects in antecedent-mismatch conditions reported by King et al. (2012) and Parker and Phillips (2014). For retrieval probabilities (to be reflected in response accuracies of adequate comprehension questions), both accounts also make the same predictions for antecedentmatch conditions but differ in their predictions for antecedentmismatch conditions. Hence, if online evidence for encoding interference in reflexives can be found, we need to reconsider the theoretical implications of interference effects in reflexives with respect to the debate about structurally-guided vs. unconstrained cue-based retrieval. In the following, we present two experiments on German and one experiment on Swedish designed to disentangle encoding from cue-based retrieval interference.

### **2. Experiment 1: German Reflexives (Self-Paced Reading)**

The German reflexive *sich* "himself "/"herself " is an interesting test case for teasing apart encoding from cue-based retrieval interference. The third-person singular reflexive *sich* is gender neutral and, roughly speaking, requires its antecedent to be a c-commanding noun phrase contained in the reflexive's local clause. For more details about the syntactic properties of German reflexives see Everaert (1986), Reinhart and Reuland (1993), Reuland and Reinhart (1995), Reuland (2001), Gast and Haas (2008) and Reuland (2011). Since *sich* is gender neutral and thus gender can be assumed to not be used as a retrieval cue, we do not expect any cue-based retrieval interference from a structurally inaccessible distractor that shares its gender with the antecedent. Encoding interference, in contrast, predicts that a distractor of the same gender as the antecedent leads to a degradation of the antecedent's memory representation resulting in longer processing times when retrieving the antecedent upon encountering the reflexive. Moreover, encoding interference predicts a lower retrieval probability of the antecedent when a gender-sharing distractor is present. We will use the term *genderoverlap* to refer to the situation where the antecedent and the distractor share their gender in order to reserve the term *gendermatch* for the match of an item's feature with a retrieval cue as in Example (3) discussed above.

### **2.1. Materials and Method**

### **2.1.1. Materials**

The experimental items consist of a matrix clause whose subject is the antecedent of the third person singular reflexive *sich* (see 4 for an example). The reflexive is the first constituent of a conjoint determiner phrase (*sich und die Kollegen* in 4) which as a whole is the direct object of the matrix verb. The antecedent (*der Dieb/die Diebin* in 4) is modified by an object-extracted relative clause that intervenes between the antecedent and the reflexive. The subject of this relative clause (*der Hehler/die Hehlerin* in 4) does not c-command the reflexive and hence syntactically disqualifies as antecedent. We will refer to this noun phrase as *distractor*. Both the antecedent and the distractor were always animate common nouns with a definite article. King et al. (2012) have shown that interference effects in reflexives are more likely to be detected when the verb, which triggers the retrieval of its subject—which, in turn, is also the reflexive's antecedent does not directly precede the reflexive. In order to increase the chances of detecting an effect, we chose perfective tense for our materials, because, as opposed to present tense or simple past,

6To be precise, the number of distractors sharing a certain feature with the target also affects retrieval latencies and retrieval probability because the more distractors share this feature with the target, the higher the probability that one of these distractors "robs" this feature from the memory representation of the target.

7Because we set out to determine whether invoking encoding interference is a way to reconcile interference effects with structure-based retrieval, for the predictions of encoding interference we are assuming that only structural retrieval cues are used. If, by contrast, one assumes that gender is used as a retrieval cue, the feature matching distractor (3c) is predicted to be misretrieved more often than the feature mismatching distractor (3d). This prediction is orthogonal to the question of encoding interference, but follows from the basic assumption that an item's retrieval probability depends on its features' match with the retrieval cues. This basic assumption is shared by models of encoding interference (Nairne, 1990; Oberauer and Kliegl, 2006). (Note that this point is unrelated to the cuebased retrieval interference component in the Oberauer and Kliegl, 2006 model which is assumed to cause inhibition between items sharing the same retrieval cues.)

the reflexive precedes the main verb in perfective sentences (for another study on interference effects using pre-verbal reflexives see Kush and Phillips, 2014). Moreover, we inserted a relatively long adverb between the perfective auxiliary *hat* and the reflexive. As in the classical gender-match/mismatch design, we manipulated the antecedent's and the distractor's gender. This resulted in a fully crossed 2 × 2 design with gender of the antecedent (masculine vs. feminine) and interference (gender-overlap vs. no gender-overlap between the distractor and the antecedent) as factors. For our research question, the

### **2.2. Results**

Statistical analyses were carried out in GNU-R (R Development Core Team, 2011) using linear mixed effects models provided by the lme4 package version 1.0-6 (Bates et al., 2014). Binary dependent variables were modeled using generalized linear mixed models with a logistic link function. For the analyses of comprehension questions and reading times, we fit models testing for a main effect of gender of the antecedent, a main effect of interference (i.e., effect of whether or not the distractor overlapped in gender with the antecedent) and an

'The thief whom the dealer obliged to steal surprisingly denounced himself/herself and the colleagues, reported the magazine.'

gender manipulation of the antecedent was not of interest *per se*. It was included in order to experimentally control for lexical properties such as word length or frequency which, due to the nature of the German language, are inseparable from the gender manipulation. We will discuss this issue more in detail in the Results section.

Each sentence was followed by a *yes/no* comprehension question targeting the reflexive-antecedent dependency. One half of the comprehension questions tested whether the antecedent was retrieved successfully (to be answered with *yes*) and the other half tested whether the distractor was misretrieved instead (to be answered with *no*). Question types were balanced across items and held constant within the four conditions of each item.

### **2.1.2. Participants and Procedure**

144 undergraduate students from the University of Potsdam who were all native speakers of German participated in the study for credit or payment of 5 EUR. We chose a relatively large sample size in order to increase statistical power, i.e., reduce Type II error probability. For our research question, high statistical power is particularly important since if encoding interference in the processing of reflexives is absent, a null result is predicted. The number of participants was determined based on a statistical power test assuming an effect of 20 ms and a standard deviation of 75 ms. In order to achieve power of 90%, 149 participants would be needed. Due to the restricted nature of our participant pool, the actual sample size was slightly smaller, which yielded a statistical power of 0.89%. 16 test items and 32 filler sentences were presented in a moving-window self-paced reading paradigm (Just et al., 1982). Items were arranged according to a Latin Square with a different randomization for each participant. Each trial was followed by a *yes/no* comprehension question.

interaction between the two. All models were fit with random intercepts and slopes for participants and items (Baayen et al., 2008). No correlations between random effects were estimated since in many of the models the correlation matrix of random effects was degenerate.

In German, the feminine form of a noun is usually generated by adding the suffix -*in* and in many nouns, the masculine form is more frequent than the feminine one. Therefore, a correlation between gender and word length and word frequency could not be avoided in the stimuli. More precisely, correlations between the main effect of gender and frequency/length of the antecedent as well as correlations between the interaction antecedent gender × interference and frequency/length of the distractor are expected. Crucially, including the gender manipulation of the antecedent as a fully crossed withinitems factor in our design ensured a zero correlation between frequency/length of the antecedent or the distractor with the critical main effect of interference. Along the same lines, correlations between frequency/length of the antecedent and the interaction antecedent gender × interference as well as correlations between frequency/length of the distractor and the main effect of gender of the antecedent cancel out due to the fully-crossed factorial design. To test these assumptions and to obtain estimates for the expected correlations, we computed Pearson-correlations of each of the contrasts to be tested in the linear-mixed model with centered word lengths measured in number of characters and centered log-transformed lemma frequencies taken from dlexDB8 (Heister et al., 2011) of the antecedent and the distractor (see **Table 1**). As expected, there was a positive correlation (*r* = 0.63) between the main effect of gender of the antecedent and frequency of the antecedent and a negative correlation (*r* = −0.44) between the main effect of gender of the antecedent and word length of the antecedent.

8www.dlexdb.de

#### **TABLE 1 | Experiments 1 and 2.**

*Correlations (Pearson correlation coefficient) of word length and log lemma frequency of the antecedent and the distractor with the experimental manipulations (main effect of interference, main effect of gender of the antecedent and their interaction). Word length and log lemma frequencies were centered (z-scores).*

#### **TABLE 2 | Experiment 1.**

*Mean accuracy scores of question responses in percentage by experimental condition.*

Similarly, there was a positive correlation (*r* = 0.39) between the frequency of the distractor and the interaction antecedent gender × interference and a small negative correlation between word length of the distractor and the interaction antecedent gender × interference. Thus, a main effect of gender of the antecedent and the interaction between the two main effects should not be interpreted since they might be confounded with the effects of antecedent/distractor length and frequency.

#### **2.2.1. Comprehension Questions**

Comprehension question response accuracies were analyzed using a linear mixed model with a logistic link function. Mean accuracy scores of question responses are provided in **Table 2**. Statistical analyses revealed a main effect of interference: accuracy was lower in conditions with a gender-sharing distractor (estimate = −0.25, *SE* = 0.12, *z* = −2.02, *p* < 0.05). Neither the main effect of gender nor the interaction were significant.

#### **2.2.2. Reading Times**

An overview of raw reading times for each region of the sentence is provided in **Table A1** in the Appendix. Reading times were analyzed at the reflexive, the following NP together with the preceding conjunction *und* "and" (n+1), the main clause verb (n+2) as well as at the two words preceding the reflexive as a sanity test of the baseline reading times. In order to achieve a close to normal distribution of the model residuals, we analyzed negative reciprocal reading times (Box and Cox, 1964). None of the comparisons reached significance at any region. Modeling log-transformed RTs instead of reciprocal RTs yielded similar results. The output of the linear-mixed models is provided in **Table 3**.

#### **2.3. Discussion**

In reading times, we did not find any effect of genderoverlap between the antecedent and the distractor. However, in comprehension questions, we observed lower response accuracies when the distractor overlapped in gender with the antecedent. This effect might be explained by misretrievals due to encoding interference during online processing which, critically, did not affect processing times. Alternatively, the lower response accuracies in the gender-overlap conditions might reflect an offline effect that arises at the moment of answering the comprehension question. Crucially for our research question, we could not find any evidence supporting the idea that encoding interference affects online processing times at the reflexive. With respect to previous studies on reflexives, we can therefore conclude that there is no indication that the interference effects observed in previous studies reflect encoding rather than cuebased retrieval interference.

### **3. Experiment 2: German Reflexives (Eye-Tracking)**

Experiment 2 is a cross-methodological replication of Experiment 1. Already Ronald Fisher, the father of frequentist statistics, emphasized the importance of replication (Fisher, 1937, page 16). Indeed, non-replicable findings are a major problem in experimental psychology and psycholinguistics (Simmons et al., 2011; Asendorpf et al., 2013). Moreover, a potential concern about Experiment 1 is that our conclusions are based on a null result. Although we have addressed this issue by testing a large sample and thus gaining high statistical power, one could still argue that the self-paced reading method is not sensitive enough to detect a potential effect. We therefore tested the same materials as in Experiment 1 in an eye-tracking while reading paradigm, which presumably is a more sensitive method compared to self-paced reading (Staub and Rayner, 2007).

### **3.1. Materials and Method**

### **3.1.1. Materials**

The same stimuli (including fillers) were used as in Experiment 1.

#### **3.1.2. Participants and Procedure**

151 undergraduate students from the University of Potsdam with normal or corrected-to-normal vision who were all native speakers of German participated in the experiment against credit or payment of 7 EUR. None of the participants had participated in Experiment 1.

Participants' eye movements (right eye monocular tracking) were recorded with an SR Research Eyelink 1000 eyetracker at a sampling rate of 1000 Hz using a desktop mount camera system with a 35 mm lens. The participant was seated at a height-adjustable table with his/her head stabilized using a forehead/chin-rest. Stimuli were presented on a 22 inch monitor (resolution of 1680 × 1050 pixels) with an eye-to-screen distance of 62 cm and an eye-to-camera distance of 60 cm. As a response pad, a Microsoft Button Box was used. Stimuli were presented using Experiment Builder software provided by SR Research. The experimental items were presented on a light gray background

#### **TABLE 3 | Experiment 1.**

*Main effects of interference and gender of the antecedent and their interaction on negative reciprocal RTs as dependent variable measured at the adverb preceding the reflexive (n*−*1), the reflexive (REFL), the coordinate NP following the reflexive (n*+*1) and the main clause verb (n*+*2).*

### **TABLE 4 | Experiment 2.**

*Mean accuracy scores of question responses in percentage by experimental condition.*

in black font, font type Times New Roman, font size 14. They were arranged according to a Latin Square and were pseudorandomized for each participant separately such that every experimental trial was preceded by at least one filler sentence. A nine-point calibration was carried out at the beginning of the experiment and repeated during the experiment, if needed. Each experimental session started with 6 practice trials. At the beginning of each trial, participants had to fixate a drift correction point at the left center of the screen where the first word of the sentence was to appear.

#### **3.2. Results**

Linear mixed-effects models were fit with the same predictors as for Experiment 1. As in the analysis of Experiment 1, all models were fit with varying intercepts and slopes for participants and items. No correlations between random effects were estimated since, as in the data of Experiment 1, the correlation matrix of random effects was degenerate in many of the models.

#### **3.2.1. Comprehension Questions**

Mean accuracy scores by experimental condition are provided in **Table 4**. We observed a marginal main effect of interference with lower accuracies in conditions where antecedent and distractor had the same gender (estimate = −0.20, *SE* = 0.10, *z* = −1.95, *p* = 0.05). This replicates the pattern found in Experiment 1. None of the other effects was significant.

#### **3.2.2. Eye Movements**

An overview of raw reading times at each word of the sentence is provided in **Table A2** in the Appendix. The same regions were analyzed as in Experiment 1. Raw fixation durations shorter than 20 ms or longer than 1000 ms (0.25% of the data) were excluded from all analyses. In eye-tracking data, the dependent measures can be partitioned into first-pass, regression-related (proportions of regressions and duration of regressive events) and later-pass measures. Since the exact mapping between syntactic effects and eye-tracking measures is still unclear (Clifton et al., 2007), we analyzed one representative measure from each group. As a first-pass measure, we analyzed first-pass reading time (FPRT, also referred to as gaze duration), which is defined as the sum of all first-pass fixations on a region. As regression related measures, we analyzed first-pass regression-probability (FPRP), i.e., a binary variable coded as 1 if a first-pass regression was initiated from a region, and regression-path duration (RPD), i.e., the sum of all fixation durations starting from the first fixation on a region until leaving this region to the right including all regressive fixations that fall into this time window. As a laterpass measure, we analyzed total-fixation time (TFT), i.e., the sum of all fixations on a region. Strictly speaking, TFT is not a pure late measure but rather the sum of FPRT and re-reading time. However, we chose to report TFT as a representative late measure since TFT is one of the most commonly reported measures in psycholinguistics; we do not analyze re-reading time because the critical region was re-read in only about 20% of the trials leading to very low statistical power. In order to achieve approximately normally distributed residuals, the continuous dependent variables were log-transformed (Box and Cox, 1964).

An overview of the output of the linear mixed-effects models is provided in **Table 5**. At the reflexive (n), the word preceding the reflexive and the region following the reflexive, none of the comparisons reached significance in any of the dependent variables. At region n+2 (i.e., the main clause verb), a significant effect of gender of the antecedent was observed in TFT (longer fixation times in conditions with a feminine antecedent). However, as we have argued in the Results section of Experiment 1, this effect should not be interpreted since it correlates with frequency and length of the antecedent. For our research question, only the main effect of interference is relevant.

Moreover, a *post-hoc* analysis of the region containing the relative clause verb (*zu stehlen* in Example 4) revealed a significant main effect of interference in TFT with longer fixation durations when the antecedent and the distractor overlapped in gender (estimate = 0.05, *SE* = 0.02, *t* = 2.28).

#### **3.3. Discussion**

Experiment 2 replicated the findings of Experiment 1. As in Experiment 1, no evidence for encoding interference due to gender-overlap between the reflexive's antecedent and a

#### **TABLE 5 | Experiment 2.**

*Main effects of interference and gender of the antecedent and their interaction on the dependent variables log-first-pass reading time, log-regression-path duration, first-pass regression probability and log-total fixation time measured at the adverb preceding the reflexive (n*−*1), the reflexive (REFL), the coordinate NP following the reflexive (n*+*1) and the main clause verb (n*+*2). Statistically significant (*α = *0.05) effects are marked with an asterisk.*

structurally inaccessible distractor was observed neither at the reflexive, nor at the pre- or post-critical regions.

At the relative clause verb, however, gender-overlap between the main clause subject, i.e., the antecedent, and the relative clause subject, i.e., the distractor, led to significantly longer totalfixation times. At this region, the relative clause subject needs to be retrieved. Hence, the observed effect, which appears in a similar region as the effects reported by Gordon et al. (2001), might reflect encoding interference. However, it is disconcerting that this effect was observed only in total-fixation time and was not present in Experiment 1, as a *post-hoc* analysis of the self-paced reading data showed. Thus, one might discount this effect as a possible Type I error. If one does not discount the effect, it raises the question why encoding interference affects argument-head dependency completion, but not reflexiveantecedent dependency formation. A possible explanation might be that the encoding interference effect (to the extent that it is not a Type I error) dies out by the time the reflexive is processed.9 In any case, further replication attempts of this configuration are needed. In sum, it is possible that we are seeing encoding interference at the distractor, but, which is crucial for our research question, this encoding interference does not seem to have any effect at the reflexive.

Taken together, the results of Experiments 1 and 2 are a strong indication that in reflexive-antecedent dependency formation, the sharing of a non-structural feature such as gender does not lead to encoding interference reflected in a processing slow-down. More precisely, it indicates that in materials of the type used in this experiment, encoding interference does not affect retrieval latencies of the antecedent when processing the reflexive. However, the marginal interference effect in offline comprehension accuracies, which had been significant in Experiment 1, indicates that the antecedent was retrieved less often correctly when it shared its gender with the distractor. This can be interpreted as evidence for encoding interference affecting retrieval probability of the antecedent. In sum, neither experiment provides any evidence for the claim that encoding interference affects reading time at the reflexive. However, our offline results suggest that encoding interference might affect retrieval probability of the antecedent. Crucially, even if encoding interference affected retrieval probability of the antecedent or the offline interpretation of the sentence, there is no evidence that it affects the participants' online behavior at the reflexive measured in self-paced reading times or eye-movements. Hence, encoding interference is not a plausible explanation for the *online* effects previous studies have observed in eye-tracking or self-paced reading measures.

### **4. Experiment 3: Swedish Possessives (Eye-Tracking)**

Experiments 1 and 2 yielded converging results: we found no evidence for encoding interference affecting the online processing speed of German reflexives. However, there are still two potential concerns with these results: (i) Our conclusion is based on two null-results, and (ii) we need to cross-linguistically validate our conclusion. In Experiment 3, we addressed these issues by examining the processing of Swedish possessives in an eye-tracking experiment. In

9A reviewer noticed that the effect at the relative clause verb occurs in totalfixation time, a measure which can reflect processing difficulty encountered further downstream in the sentence, and therefore might actually reflect processing difficulties at the reflexive which triggers re-readings of the previous materials. However, if this were the case, one would expect an increase in the proportion of regressions or increased regression-path durations at the reflexive. As this is not the case, it is difficult to conclude that the effect observed at the verb reflects processing difficulty associated with the reflexive.

Swedish, there are two kinds of possessives: reflexive possessives that are not gender-marked and pronominal possessives that need to agree in gender with their antecedent. The reflexive possessive *sin* "his"/"her" can only be bound by a c-commanding antecedent inside its local clause. In contrast, the pronominal possessive *hans* "his" must not be bound within gender-unmarked reflexive possessive (*sina* "his"/"her" in 5b). The distractor (*Alf* or *Ann* in 5b) is the subject of an appositive relative clause intervening between the antecedent and the reflexive possessive. As Swedish does not code masculine and feminine as grammatical gender, and the number of nouns with inherent gender such as *boy* or *girl* is very limited, both

(5) a. **Pronominal possessives; gender-overlap/no gender-overlap**

'Åke, whom Alf/Ann thanked, calls his cousins in the evening.'

its local clause, but requires an antecedent outside its clause domain (see Holmes and Hinchliffe, 1994 and Kaiser, 2003, p. 209). In a 2 × 2 factorial design, we manipulated anaphor type (pronominal possessive vs. reflexive possessive) and interference, i.e., whether or not a structurally inaccessible distractor shared the gender of the antecedent. For this design, encoding interference predicts increased processing difficulty in the gender-overlap conditions compared to the no-gender-overlap conditions, regardless of anaphor type. Cuebased retrieval interference, in contrast, predicts an interaction between anaphor type and interference: increased processing difficulty due to a gender-sharing distractor is predicted for the gender-marked pronominal possessives but not for the gender-unmarked reflexive possessives. This is because only in pronominal possessives, the gender-marked anaphor can trigger a retrieval process where gender is used as a retrieval cue. When both the antecedent and the distractor match the gender cue, cue-based retrieval interference predicts inhibition between the antecedent and distractor and a higher proportion of misretrievals of the distractor (Lewis and Vasishth, 2005). Thus, the present experiment allows us to directly pit encoding and cue-based retrieval interference against each other. In contrast to Experiments 1 and 2, cue-based retrieval interference predicts an interaction rather than a null-result.

### **4.1. Materials and Method 4.1.1. Materials**

The conditions with pronominal possessives (see 5a for an example item) consist of a superordinate clause whose subject is the antecedent (*Åke* in 5a) and a subordinate clause containing the distractor (*Alf* or *Ann* in 5a) which either matches or mismatches the gender of the antecedent and the gender-marked pronominal possessive (*hans* "his" in 5a). The conditions with reflexive possessives (see 5b for an example item) consist of a main clause containing the antecedent (*Åke* in 5b) and the the antecedent and the distractor were proper names in all experimental sentences. Indeed, it is crucial for our research question to extend the findings of Experiments 1 and 2 to proper names, which differ from common nouns with respect to their referential properties (Longobardi, 1994; Elbourne, 2005), since several of the studies reporting interference effects in reflexives actually employed proper names (e.g., Badecker and Straub, 2002).

The nouns used as antecedents and distractors are all highly frequent, gender unambiguous Swedish first names taken from Statistics Sweden, a database which contains the 100 most frequently given and used male and female first names in Sweden.10 Antecedents and distractors are all matched for word length (numbers of characters) within each item. Half of the items have a feminine antecedent and the other half a masculine antecedent. The possessed noun phrase (*sysslingar* in 5) is always a plural noun.

Two types of comprehension questions were designed. The first type probed for the correct interpretation of the anaphor-antecedent dependency. 50% of these questions were to be answered with *yes*. The second question type targeted various parts of the sentence, but not the interpretation of the anaphor. Again, 50% of these questions were to be answered with *yes*.

### **4.1.2. Participants and Procedure**

35 native speakers of Swedish currently living in Berlin or Potsdam with normal or corrected-to-normal vision participated in the experiment against payment of 5 EUR (plus 6.20 EUR to cover travel expenses). The sample size was smaller compared to Experiments 1 and 2 due to logistic limitations, but we tested a larger number of experimental items compared to Experiments 1 and 2. Participants' eye movements (right eye monocular tracking) were recorded while reading 48 experimental sentences

10http://www.scb.se/BE0001-EN; we used the data of 2012.

and 70 filler sentences. The general technical set-up was the same as in Experiment 2. Stimuli were arranged in a Latin Square and pseudo-randomized such that each experimental trial was preceded by at least one filler sentence. Each trial was followed by a comprehension question. Two thirds of the comprehension questions targeted the correct interpretation of the anaphor and one third targeted other parts of the sentence. The experiment started with 5 practice trials to familiarize participants with the procedure.

#### **4.2. Results**

On all dependent variables, we fit linear mixed-effects models with main effects of anaphor type (pronominal vs. reflexive possessive), interference (whether or not the distractor had the same gender as the antecedent) and their interaction as predictors. When the interaction reached significance, nested contrasts testing for an interference effect within each anaphor type were fit. All models were fit with varying intercepts for participants and items. No varying slopes were fit because the generalized likelihood-ratio test showed that they did not improve the model fit. The pattern of results was not affected by whether or not varying slopes were fit. For the interpretation of results, it should be kept in mind that the effect of anaphor type is not of theoretical relevance to our research question. As the two levels of anaphor type differ lexically at the pre-critical and the critical region, a main effect of anaphor type does not have any useful interpretation.

#### **4.2.1. Comprehension Questions**

Mean accuracy scores by experimental condition and question type (i.e., whether or not the comprehension question targeted the anaphor) are provided in **Table 6**. We ran a linearmixed effects model with a logistic link function with main effects of anaphor type, interference and question type and their interactions including the three-way interaction between all main effects as predictors. The model output is summarized in **Table 7**. The main effect of interference and the interaction between interference and question type reached significance. Moreover, a marginal three-way interaction between interference, anaphor type and question type was observed. A second model in which we applied nested contrasts testing for an interference effect within each level of anaphor type and question

#### **TABLE 6 | Experiment 3.**

*Mean accuracy scores of comprehension questions in percentage by experimental condition and question type, i.e., whether the question targeted the anaphor-antecedent dependency or another element of the sentence.*

type11 showed that the interactions were caused by a highly significant interference effect that was present only in questions targeting the anaphor in pronominal possessives (estimate = −1.16, *SE* = 0.25, *z* = −4.62, *p* < 0.0001). In sum, in questions targeting the anaphor-antecedent dependency, the presence of a gender matching distractor led to lower response accuracies in sentences with pronominal possessives but not in sentences with reflexive possessives. In questions not targeting the anaphorantecedent dependency, no effects were observed.

#### **4.2.2. Eye Movements**

An overview of raw reading times at each region of the sentence is provided in **Table A3** in the Appendix. We analyzed the pre-critical region containing the verb (plus postposition), the critical region containing the pronominal or reflexive possessive and the post-critical region containing the possessed noun. The same dependent variables were analyzed as in Experiment 2. Continuous dependent variables were log-transformed in order to achieve approximately normally distributed residuals.