# Ricomprendo: an assessment test for fine-graded alterations of syntactic processing

Giulia Gilardone, Mauro Viganò, Chiara Longo, Edoardo Nicolò Aiello, Giulia de Luca, Beatrice Curti, Federica Giglio, Carlo Cecchetto, Costanza Papagno

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Giulia Gilardone, Mauro Viganò, Chiara Longo, Edoardo Nicolò Aiello, Giulia de Luca, et al. Ricomprendo: an assessment test for fine-graded alterations of syntactic processing. Neurological Sciences, 2025, 10.1007/s10072-025-08192-w. http://hal-05053195

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Preprint version of the paper:

Gilardone, G., Viganò, M., Longo, C., Aiello, E.N., De Luca, G., Curti, B., Giglio, F., Cecchetto, C., & Papagno, C. (2025). RiComprendo: An assessment test for fine-graded alterations of syntactic processing. *Neurological Sciences*. DOI: 10.1007/s10072-025-08192-w.

The work is subject to the laws of copyright and intellectual property.
RICOMPRENDO: AN ASSESSMENT TEST FOR FINE-GRADED ALTERATIONS OF
SYNTACTIC PROCESSING

Giulia Gilardone¹, Mauro Viganò², Chiara Longo³, Edoardo Nicolò Aiello⁴, Giulia De Luca⁴, Beatrice Curti⁴, Federica Giglio⁵, *Carlo Cecchetto²,⁵, *Costanza Papagno⁶

¹ Department of Neurorehabilitation Sciences, Casa di Cura Igea, Milan, Italy

² UMR 7023 Structures Formelles du Langage, CNRS & Université Paris 8, Paris, France

³ Department of Neurology, Santa Chiara Hospital, Azienda Provinciale per i Servizi Sanitari, Trento, Italy

⁴ Department of Neurology and Laboratory of Neuroscience, IRCCS Istituto Auxologico Italiano, Milan, Italy

⁵ Department of Psychology, University of Milano-Bicocca, Milano, Italy

⁶ CIMeC - Center for Mind/Brain Sciences, University of Trento, Trento, Italy

* These two authors equally contributed to the work

Authors' e-mail addresses and ORCIDs:

Giulia Gilardone: g.gilardone@casadicuraigea.it; 0000-0003-1482-9891; corresponding author.

Mauro Viganò: dott.mauro.vigano@gmail.com; 0000-0003-3447-4792

Chiara Longo: chiara.longo@apss.tn.it

Edoardo Nicolò Aiello: e.aiello@auxologico.it

Giulia De Luca: g.deluca@auxologico.it

Beatrice Curti: b.curti@auxologico.it

Federica Giglio: f.giglio@campus.unimib.it

Carlo Cecchetto: carlo.cecchetto@unimib.it; 0000-0001-9985-7087

Costanza Papagno: costanza.papagno@unitn.it
# RICOMPRENDO: AN ASSESSMENT TEST FOR FINE-GRADED ALTERATIONS OF SYNTACTIC PROCESSING

## Abstract

**Introduction:** RiComprendo was designed as a comprehensive tool to evaluate comprehension of various syntactic structures with a sentence-to-picture matching-task. The study sets normative data and investigates the influence of demographic characteristics and sentence types.

**Methods:** Two-hundred-ten right-handed healthy Italian native speakers were included. RiComprendo was administered via E-Prime, collecting both accuracy and response time (RTs) data. Adjusted scores for age and education and equivalent scores for each sentence type (i.e., simple active sentences, passives, peripheral and center-embedded subject and object relatives, and coordination) were computed. The effect of sentence type, age and education on accuracy and RTs was investigated through generalized linear mixed models. Item difficulty was tested with an Item Response Theory (IRT) model.

**Results:** Normative data and a spreadsheet for scores automatic computation are provided. The mixed models identified a significant impact of sentence type both on accuracy and RTs. Simple sentences presented high accuracy, while the worst performance was found with center-embedded object relatives. Higher education was significantly associated with better accuracy, while older age was associated with longer RTs and with a marginally negative effect on accuracy.

**Discussion:** Sentence comprehension is influenced by structural complexity and demographic characteristics (age and education). Providing normative data for different sentence types, RiComprendo enables the evaluation of effects of specific syntactic properties (i.e., canonicity, number of clauses, filler-gap dependencies, intervention, center-embedding).

**Conclusion:** RiComprendo could serve as a valuable tool for testing the comprehension of complex sentences in research and clinical settings, informing in-depth functional assessment and tailored intervention.

## Keywords

Sentence comprehension; assessment; syntactic complexity; acquired language disorders; normative data.
# 1. Introduction

Evaluating sentence comprehension requires a comprehensive analysis of various cognitive and linguistic abilities. This process entails distinguishing between different components of language processing, for example lexical-semantic access skills (i.e., the ability to understand single words) and syntactic proficiency (i.e., the capacity to process and interpret grammatical structures governed by syntactic rules). Once lexical comprehension has been assessed, the focus should turn to examining the individual's ability to understand sentences characterized by different degree of syntactic complexity. The evaluation of sentence comprehension should also consider the role of phonological short-term memory (pSTM) and working memory (WM), as well as attention and executive function deficits that may affect behavioral performance and compromise the reliability of psychometric test results [1-3].

A comprehensive assessment of these processes is necessary to define the characteristics and severity of a morphosyntactic disorder and to correctly interpret its functional origin. This is crucial for establishing the most appropriate rehabilitative treatment, including intervention methodology and stimulus selection. Important information about morphological abilities (i.e., concerning the presence and the appropriateness of morphemes marking person, number and gender) and syntactic abilities (i.e., concerning the internal structure of matrix and subordinate clauses) can be obtained from spontaneous communicative interactions and from tests and batteries designed for people with aphasia. In Italy, standardized language assessment batteries such as BADA [4], ENPA [5], AAT [6], and Esame del Linguaggio II [7] incorporate syntactic tasks. These comprehension abilities are evaluated through oral and written sentence comprehension tests, grammaticality judgments, and simple and complex commands. However, in these tools, a limited number of items is dedicated to syntactic comprehension evaluation, restricting the variety of syntactic structures they explore. Consequently, while these batteries are valuable for a broad evaluation of language abilities, they may not provide an exhaustive assessment of syntactic comprehension.

Before looking at available clinical tests for sentence comprehension in Italian, it is useful to present the main syntactic factors that have been identified as sources of difficulties for the clinical population in the previous literature. In the present study we considered the following syntactic factors: non-canonicity, presence of filler-gap dependency, structural intervention, and center embedding (defined hereafter).

**Non-canonicity** is the discrepancy with respect to the unmarked word order of the arguments of the verb. An example of non-canonical sentences is passives. While in active sentences (e.g., “The boy chases the dog”), the noun phrase that corresponds to the *Agent* precedes the one that corresponds to the *Patient* of the action, in passive sentences the order is non-canonical as the subject, instead of functioning as the
Agent, assumes the role of the Patient (e.g., "The dog<sub>i</sub> is chased e<sub>i</sub> by the cat"). Clinical populations characterized by a pure deficit in syntactic representation, like people with non-fluent agrammatic aphasia, present impairments even in shorter, monoclausal sentences that involve passivization [8].

In some types of clauses, like relative clauses, there is a long-distance link between the position where a noun phrase appears and the position where it is interpreted, defined as **filler-gap dependency**. For example, in the object relative "the dog<sub>i</sub> that the cat chases e<sub>i</sub>", the noun phrase "the dog" (named *filler*) is generated as the direct object of the relative clause and is moved to the position the precedes the relative pronoun "that" leaving an empty spot in its original position "e" (named *gap*). Identifying the members of filler-gap dependency is necessary for meaning extraction. For example, understanding the meaning of "the dog<sub>i</sub> that the cat chases e<sub>i</sub>" requires comprehending that it is the dog that undergoes the action of being chased, namely the dog is the Patient. Some types of filler-gap dependencies can be a source of difficulty for clinical populations, like people with aphasia [9, 10]. Notice that in passives as well there is a filler-gap dependency, as the subject corresponds to the Patient. Non-canonicity and a filler gap dependency are two different notions because there are canonical sentences with a filler gap dependency (i.e. subject relatives).

When there is a filler-gap dependency, the phenomenon of **intervention** is determined by the presence of a category similar to the filler that structurally intervenes between the filler and the gap. This happens in the object relative "the dog<sub>i</sub> that the cat chases e<sub>i</sub>", as the subject of the relative clause "the cat" is a potential candidate to fill the gap position (hence for the assignment of the role of Patient). On the contrary, in the subject relative "the dog<sub>i</sub> that e<sub>i</sub> chases the cat", no intervention arises as the filler and the gap are structurally and linearly adjacent and the dependency is immediately resolved. Intervention is known to be a factor of complexity for clinical populations, like people with nonfluent aphasia [11, 12]. Non-canonicity and intervention are two different notions because there are non-canonical sentences without an intervention configuration (i.e. passives being a likely candidate).

A relative clause can appear in different positions in the main clause. For example, in "the dog<sub>i</sub> that e<sub>i</sub> chases the cat watches the grandpa" the relative is inserted between the subject of the main clause ("the dog") and its predicate ("watches the grandpa"). This configuration, known as **center-embedding**, introduces a high load on phonological short-term memory (pSTM) because it demands significant computational resources, since the filler-gap dependency in the relative clause and the agreement dependency between the matrix subject and the matrix verb require simultaneous storage and retrieval of linguistic information in the memory buffer. However, the relative clause can appear in the final position in the sentence as in "The mum watches the dog<sub>i</sub> that the boy chases e<sub>i</sub>". The relatives in this
configuration, known as right branching or peripheral, are less complex for patients with pSTM deficits
[13].

Considering now the available tests to detect syntactic comprehension deficits, Parisi and Pizzamiglio [14] developed a specific tool for assessing comprehension abilities, which includes 80 stimuli. However, it has a limited number of items testing complex syntactic structures. Notably, the test includes only four items assessing the comprehension of relative clauses, which is insufficient for identifying deficits in these structures, despite their relevance for diagnosing syntactic disorders [9]. Another tool available for the evaluation of syntactic abilities is the Northwestern Assessment of Verbs and Sentences battery (NAVS), originally developed in English [15] and adapted for the Italian population [11, 12]. The Sentence Comprehension Test (SCT) of the NAVS controls for canonicity, filler gap dependency and intervention as it includes actives, passives, subject and object clefts and subject and object right-branching relatives. The small number of items in the SCT – only five for each sentence type – was considered sufficient to identify and characterize the performance of people with aphasia [10, 12]. However, such limited number of items could be insufficient to detect mild alteration of sentence comprehension in other clinical populations. Importantly, both Parisi and Pizzamiglio’s test [8] and NAVS [10,11] do not consider sentences with center embedding.

In this context, the battery Comprendo [18], stands out as a comprehensive instrument designed to assess comprehension across different sentence types in both clinical and non-clinical settings. Comprendo is the sole battery accessible in Italy allowing an in-depth evaluation of sentence comprehension, measuring both accuracy and response times comprehensively.

Comprendo was built to measure all the four factors of complexity considered above as it included:

- *Transitive active sentences* (e.g., “The boy chases the dog”)

- *Active dative sentences* (e.g., “The boy gives the cake to the grandma”)

- *Passives*: (e.g., “The dogᵢ is chased eᵢ by the cat”).

- *Right-branching (or peripheral) subject relatives*: (e.g., “The mom watches the girlᵢ that eᵢ pulls the dog”).

- *Right-branching (or peripheral) object relatives*: (e.g., “The mum watches the dogᵢ that the boy chases eᵢ”).

- *Center-embedded subject relatives*: (e.g., “The dogᵢ that eᵢ chases the cat watches the grandpa).

- *Center-embedded object relatives*: (e.g., “The catᵢ that the boy watches eᵢ drinks milk”).

- *Coordinated structures*: coordination of two verb phrases (e.g., “The boy eats the banana and watches the cake”), coordination of two independent clauses (e.g., “The dad touches the cat and the dog chases
the boy”) and coordination of two noun phrases in the object position (“The boy eats the banana and the cake”).

The use of Comprendo in clinical and scientific research settings revealed some limitations [8], leading to the development of a new battery called RiComprendo, described in the next section, that encompasses the innovations of Comprendo but tries to overcome its weaknesses. Specifically, in Comprendo, the transitive active and active dative sentence types are considered separately. In RiComprendo, both types are categorized as *Simple*, as clinical practice has confirmed that they are simple structures which can be easily understood by individuals with or without neurological deficits (with the exception of people with severe language impairments, who can be identified by a first-level assessment). Sentences involving the coordination of verb phrases (“The boy eats the banana and watches the cake”) and of two independent clauses (“The dad touches the cat and the dog chases the boy”), which were tested separately in Comprendo, are classified under a single category (Coord) in RiComprendo. Sentences with the coordination of noun phrases (“The boy eats the banana and the cake”), are removed in RiComprendo, because both in Comprendo and in clinical studies [8] they reported almost the same performances as the coordination of verb phrases (VPs) and they were, therefore, considered uninformative.

RiComprendo comprises a total of 140 stimuli, compared to the 100 of Comprendo. It includes 20 items for each sentence type, enhancing the statistical reliability of the test, although leading to a slight increase in administration time.

Concerning response alternatives, in RiComprendo, the foil containing unrelated characters was removed, as it was never chosen by either healthy controls or PWA. Thus, RiComprendo presents only three alternatives. These stimuli are currently arranged vertically to enable the test to be administered also to individuals with hemineglect. A preliminary test to assess the comprehension of lexical items (nouns and verbs) used within the sentences is included.

The aim of this study was to establish normative data for RiComprendo battery in a sample of the Italian population and to assess the impact of age, education, sex and sentence type on syntactic comprehension, considering both accuracy and response times. Equivalent Scores were computed to ensure comparability between subtests and other neuropsychological assessments.

# 2. Methods

## 2.1. Participants

Normative data were gathered from 210 right-handed native Italian speakers across Italy. Recruitment took place between May 2020 and May 2023. Participants did not report history of neurological or
psychiatric disorders. The sample was carefully balanced concerning sex, age, and years of formal
education. The study adhered to the principles outlined in the Declaration of Helsinki, and all participants
provided written informed consent. Ethical approval for the study was obtained from the Ethical
Committee (DATA WILL BE INSERTED AFTER BLIND REVIEW PROCESS).

**2.2. Procedures**

RiComprendo is a sentence-to-picture-matching task designed for the assessment of sentence comprehension in adults. The battery comprises 140 stimuli divided into seven sentence types each containing 20 items. The sentences primarily consist of high-frequency words to prevent errors stemming from word comprehension deficits. RiComprendo was administered using E-Prime software (version 3.0). Participants were instructed to listen to audio-recorded sentences (max duration 5000ms) and then to select the corresponding picture among three alternatives (the target picture, a picture with thematic role inversion, and another depicting the same characters in different actions). The three pictures are displayed on the computer screen 1000ms before the end of the auditory trace and remain visible until the response is given s (see **Figure 1**). Sentence presentation order is randomized, and there is no time limit for responses. The entire test takes approximately 30 minutes to complete. Upon completion, individual accuracy and reaction time (RT) for each item were retrieved for the analyses. E-Prime script for RiComprendo administration is available upon motivated request to the corresponding author.

**2.3. Stimuli**

The seven sentence types evaluated by RiComprendo are:

**Simple:** transitive active sentences ("The boy chases the dog"), and active dative sentences ("The boy gives the cake to the grandma").

**Passive:** "The dogi is chased ei by the cat".

**PerSR:** Right-branching (or peripheral) subject relatives ("The mom watches the girli that ei pulls the dog").

**PerOR:** right-branching (or peripheral) object relatives, ("The mum watches the dogi that the boy chases
ei").

**EmbSR:** center-embedded subject relatives ("The dogi that ei chases the cat watches the grandpa").

**EmbOR:** center-embedded object relatives ("The dogi that the cat chases ei watches the grandpa").

**Coord:** Sentences with a coordinated verb phrase ("The boy eats the banana and watches the cake") or with two coordinated clauses ("The dad touches the cat and the dog chases the boy").
**Table 1** summarizes how the structures included in RiComprendo are associated to the four factors introduced above that are likely to modulate their complexity. Each "+" indicates that the structure is potentially challenging with respect to the listed property. Notice that neither **Coord** nor **Simple** are associated to any of the four complexity factors. However, the inclusion of **Coord** as an independent category is motivated because it has been proposed that some coordinated structures are complex for the clinical population (cf. [19] but [13] for a critical assessment of this claim). Finally, note that the four types of relatives (PerSR, PerOR, EmbSR and EmbOR) are the only structures in the battery involving subordination.

## 2.4. Statistics

### 2.4.1. Norms

Normative data were derived according to the Equivalent Score (ES) method [20, 21]. The initial step of such approach lies in the exploration of the effects of demographic confounders on raw test measures. The effect of sex was first tested *via* independent-sample *t*-tests. Then, the effects of age and education, as well as of their quadratic, cubic, square-root, logarithmic and reciprocal transforms, were tested *via* stepwise, multiple linear regression models. All the predictors yielding significance within the abovementioned steps were then entered into an individual model, based on which equations to adjust raw scores based on relevant demographic confounders were built. Subsequently, outer and inner tolerance limits (oTL; iTL) were identified on ranked adjusted scores (ASs) in order to provide a non-parametric, interval estimate of the cut-off. ASs lower than/equal to the oTL are classified as impaired (i.e., ES=0), whilst those higher than the oTL and equal to/lower than the iTL are judged as falling under a “grey area” where no inference on their “normality” or “defectiveness” can be drawn. Finally, ASs higher than the oTL and lower than/equal to the median are further classified into the following ability levels according to a z-score-based subdivision: ES=1 → “borderline”; ES=2 → “low-end normal”; ES=3 → “normal”; ES=4 (i.e., ASs equal to/higher than the median) → “high-end normal”.

In accordance with previous normative studies [22; 23], the minimum sample size was set at *N*=146 to the aim of detecting a small-to-*medium* effect size (f² =0.1) with the significance threshold set at α=.05 and a statistical power 1-β of 90%. Such an *a priori* sample size estimation was performed *via* the R 4.3 package *pwr* (https://CRAN.R-project.org/package=pwr) within a multiple linear regression model that addressed, besides the abovementioned parameters, 3 predictors (i.e., age, education and sex; *df*<sub>numerator</sub>=3)
### 2.4.2. Sentence type effects

The effect of sentence type on both RiComprendo measures – i.e., Accuracy and RTs –, generalized linear mixed models were run by addressing *Subject* and *Item* as the clusters – with a random intercept being fitted for both – and *Sentence type* as the predictor. More specifically, a Binomial distribution was addressed when analyzing Accuracy scores – as it being a dichotomous outcome (0 = “incorrect”; 1 = “correct”) –, whilst a Gamma distribution was assumed as underlying RTs. RTs indeed proved to be featured by marked floor effects and high inter-individual variability, and the Gamma distribution models heavily right-skewed and overdispersed data [24]. Within these models, age and education were entered as covariates, and post-hoc comparisons were Bonferroni-corrected.

### 2.4.3. Item difficulty

In order to test item difficulty, a 1-parameter logistic (1-PL) Item Response Theory model was run via the R 4.3 package *ltm* (https://github.com/drizopoulos/ltm) on all RiComprendo items. Within this model, items 16, 19 and 37 were not entered as yielding no variability (i.e., the whole sample provided a correct response to these items). Based on Arifin & Yusoff's [25] recommendations, difficulty values ranging from -3 to +3 were addressed as typical (with values $\le$-3 indexing an extremely easy item and those $\ge$+3 an extremely difficult items).

Analyses were run via R 4.3 (R Core Team, 2023) and jamovi 2.3 (the jamovi project, 2022).

## 3. Results

### 3.1. Participants

The sample of 210 Italian native speakers consisted of 109 females and 101 males. Their mean age was 48.14 years (*range* = 20-80, *SD* = 17.65) whilst their average level of formal education expressed in years was 14.05 (*range* = 6-22, *SD* = 3.75). **Supplementary table 1** reports the sample stratification according to age, education and sex.

### 3.2. Norms

**Table 2** shows adjustment equations for each raw measure on RiComprendo. Overall, no sex effects were detected ($p \ge$.120) on either Accuracy or RTs. Among Accuracy measures, that relating to Simple sentences proved not to be predicted by either age ($p$=.911) or education ($p$=.115); at variance, education proved to be systematically predictive of remaining Accuracy measures ($p \le$.002), with age further predicting those related to EmbSR ($p$<.001) and EmbOR sentences ($p$=.043). As to RTs, age proved to
be a systematic predictor (*p*<.001), whilst education was predictive of all RTs (*p*≤.042) except for those related to EmbSR and Coord sentences (*p*≥.060). **Table 3** reports tolerance limits and ES thresholds for each RiComprendo measure.

**3.2.1. Sentence type effects**

Descriptive statistics for Accuracy, RTs and type of errors for each sentence type are displayed in **Table 4**. A significant main effect of *Sentence type* was detected on both Accuracy ($\chi^2(6)=226.67; p<.001$) and RTs ($\chi^2(6)=262.66; p<.001$). **Figure 2** represents the probability of a correct response separately for each sentence type: overall, all post-hoc comparisons (see **Supplementary table 2**) yielded significance except for those between Coord and both Passive and PerSR sentences (*p*=1.00), as well as of that between PerOR and EmbSR ones (*p*=1.00). **Figure 3** presents the RTs for each sentence type, while the results of post-hoc comparisons regarding RTs are displayed in **Supplementary table 3**. Overall, RTs to simple sentences proved to be lower when compared to those to other sentence types (*p*<.001) but passive ones (*p*=1.00); similarly, RTs to passive sentences were lower than those to all the other sentence types (*p*<.001). Additionally, RTs were lower in response to PerSR sentences when compared to EmbOR ones (*p*<.001), as well as for Coord sentences when compared to EmbOR ones (*p*=.008). No other significant comparisons yielded (*p*≥.383).

As to covariates, higher education was associated with a higher probability of a correct response (*b*=.12; *z*=6.96; *p*<.001) whilst only a marginally, negative effect of age on Accuracy was detected (*b*=-.01; *z*=-1.86; *p*=.064). Within the model addressing RTs, the opposite scenario occurred – with older age being strongly associated with higher RTs (*b*=.01; *z*=4.42; *p*<.001) and higher education being mildly, non-significantly associated with lower RTs (*b*=-.01; *z*=-1.67; *p*=.094).

**3.2.2. Item difficulty**

The aggregated results of the 1-PL model for the 137 items entered into it are shown in **Table 5**. Overall, PerOR and EmbOR items proved to fall under the typical range of difficulty, whilst items included within the remaining sections were found to be extremely easy on average.

**4. Discussion**

The present study provides normative data for RiComprendo obtained from a sample of 210 neurologically healthy Italian native speakers. RiComprendo battery tests sentence comprehension with a sentence-to-picture matching task, assessing seven types of sentences with different degrees of
complexity. The norms are provided for accuracy and RTs, considering the possible effect of sex, age, and education. Additional analyses investigated the effect of sentence type on the normative sample performance.

**4.1. Norms**

**Table 3** presents the tolerance limits and the Equivalent Scores (ESs) for each sentence type and for the global score. Since either age or education proved to be significant predictors of performances for all measures (except for Simple sentences accuracy), raw scores should be always corrected with the adjustment equations reported in **Table 2** for interpretation. To facilitate the implementation of this procedure in clinical and research practice, and reduce the risk of mistakes, we provided a spreadsheet (**Supplementary Material A**, https://osf.io/ze4sc/?view_only=8721399a6b6f4111b7f721e39048b12e) for computing automatically adjusted scores (ASs) and ESs. This represents an advantage in comparison with previous studies on similar assessment tools [11, 18].

Focusing on specific sentence types, the accuracy with Simple sentences was overall almost-at-ceiling with a very limited variability in the normative sample. For this reason, the only normative threshold available for this subscale is the outer tolerance limit (oTL, that correspond to an ES=0), suggestive of a pathological performance. Conversely, right-branching object relatives and especially center-embedded object relatives were on average the most difficult even for the healthy population

As mentioned above, the administration of RiComprendo to the normative sample was implemented via E-Prime software, to retrieve the information regarding the RTs. In the clinical practice, these measures could be important to detect early alterations in the syntactic processing among people with mild cognitive or linguistic decline. However, this procedure might be poorly feasible due to setting or material (e.g., software license) restrictions or due to the difficulties that certain clinical populations might have in using the computer or undertaking such a demanding task in terms of attentional resources.

A future development of the research on this tool will include cross-sectional and longitudinal studies with different neurological populations (characterized by language impairments) in order to investigate its clinimetric properties and the validation of an equivalent pencil-and-paper version of the battery.

Specifically, we intend to explore the equivalence between the computerized version detailed in this study and a paper-based version of RiComprendo, in which the examiner reads the sentences aloud and participants select the correct picture on paper. This alternative format aims to ensure accessibility and usability in in-person clinical settings, especially for individuals who may have limited experience with
computers, cognitive barriers to use digital interfaces, or motor impairments that could hinder their ability to interact with a computerized system effectively.

## 4.2. Sentence types and demographic characteristics effects

The generalized linear mixed effect models revealed a main effect of sentence type both considering accuracy and RTs performances.

Considering accuracy, the post hoc analysis showed that simple active sentences obtained the highest accuracy, followed by passives, coordination, and right-branching subject relatives, then by center-embedded subject relatives and right-branching object relatives, and finally by center-embedded object relatives with the lowest accuracy. These results suggest that the presence of a filler-gap dependency per se does not impact on sentence comprehension in the healthy population, as participants performed very well with both passives and right-branching subject relatives. The syntactic phenomena having a stronger impact on accuracy are the intervention effect and the center embedding. In particular, the combination of these two in center-embedded object relatives seems particularly challenging even for healthy speakers. Interestingly, subject relatives are associated with a high level of accuracy (with a median of 96.04 for PerSR and 92.82 for EmbSR), showing that, in this type of task, healthy speaker do not interpret these sentences as object relatives with a postverbal subject, although, generally speaking, Italian grammar allows subjects to be postverbal (e.g., "La mamma guarda la ragazza$_i$ che $e_j$ tira $e_i$ il cane$_j$", is interpreted as "The mom watches the girl that the dog pulls"). Conversely, wh-questions in Italian are known to present this ambiguity: for example, a sentence like "Chi guarda la mamma?" can either be interpreted as a subject-extracted wh-question (i.e., "Who watches the mom?") or object-extracted wh-question with a postverbal subject (i.e., interpreted as "Who does the mom watch"?), according to the context. Our findings, therefore, point out that subject relatives as built in RiComprendo are a suitable structure for testing sentence comprehension. Moreover, the analyses of the types of errors showed that participants selected more frequently the foil with the inversion of the thematic roles in the case of passives, right-branching object relatives and center-embedded subject relatives. On the contrary, the types of errors for center-embedded object relatives are more balanced between the two distractors, suggesting a more random behavior for this complex sentence type. Considering the impact of the demographic characteristics on comprehension accuracy, sex was not associated to a significant effect, while formal education displayed a significant effect in the mixed model and as a predictor in the regression models for each sentence type. Age was only marginally significant in the mixed model but was a significant predictor in the regression models for both subject and object center embedded relatives.
This might suggest that processing center embedding is more demanding in terms of cognitive resources, leading to a degradation of accuracy in elderly people that can present a physiological reduction of pSTM [26].

We found a significant effect of sentence type also in the generalized linear mixed model for RTs. Post hoc analyses revealed that simple active and passive sentences presented significantly lower RTs in comparison with all the other types, while center-embedded object relatives required on average longer RTs in comparison with right-branching subject relatives and sentences with coordination. Sentence types associated with lower accuracy presented also longer RTs. This finding rules out the possibility to explain the poor accuracy for these sentences because of rushed and impulsive responses. In particular, the performance with center-embedded object relatives in terms of accuracy and RTs suggests that processing these syntactic structures is particularly challenging and demanding for cognitive resources. Considering the demographic characteristics, sex had no significant effect on RTs, while age displayed a significant effect in the mixed model *and* was a predictor in the regression models for all sentence types. This is in line with the scientific literature reporting an overall age-related increase in processing and response times [27].

**5. Conclusion**

Encompassing difficult structures, RiComprendo is not intended as a first-line assessment tool for people with severe linguistic deficits, but it was designed to detect specific alterations of syntactic processing. Covering a wide range of linguistic properties like canonicity, syntactic dependencies, intervention and center-embedding, it allows an in-depth characterization of the receptive syntactic abilities for planning a tailored intervention.

For a single sentence type, the one that combines all these dimensions of complexity (i.e., center-embedded object relatives), the clinical use of this subscale might be underinformative due to a widespread distribution of the accuracy scores. However, altogether RiComprendo could be a useful research tool to differentiate among individuals with language disorders by comparing their distributions of adjusted scores (ASs) in each subscale. In conclusion, RiComprendo battery is a useful tool for assessing the comprehension of complex sentences both in the clinical and research field.

**Data availability statement**
## References

[1] Papagno, C., & Cecchetto, C. (2019). Is STM involved in sentence comprehension?. *Cortex*, 112, 80-90.

[2] Varkanitsa, M., & Caplan, D. (2018). On the association between memory capacity and sentence comprehension: Insights from a systematic review and meta-analysis of the aphasia literature. *Journal of Neurolinguistics*, 48, 4-25.

[3] Gilardone, M., & Monti, A. (Eds.). (2019). *Afasiologia: Clinica, valutazione, trattamento*. FrancoAngeli.

[4] Miceli, G., Laudanna, A., Burani, C., & Capasso, R. (1994). BADA. Batteria per l'Analisi dei Deficit Afasici. *Roma: CEPSAG, Universita Cattolica del Sacro Cuore*.

[5] Capasso, R., & Miceli, G. (2001). *Esame Neuropsicologico per l'Afasia: ENPA* (Vol. 4). Springer Science & Business Media.

[6] Luzzatti, C., Poeck, K., Weniger, D., Willmes, K., De Bleser, R., & Huber, W. (1996). *AAT: Aachener aphasie test: manuale e dati normativi*. Organizzazioni speciali.

[7] Ciurli, P., Marangolo, P., & Basso, A. (1996). *Esame del Linguaggio* (II versione).

[8] Gilardone, G., Viganò, M., Costantini, G., Monti, A., Corbo, M., Cecchetto, C., & Papagno, C. (2023). The role of verbal short-term memory in complex sentence comprehension: An observational study on aphasia. *International Journal of Language & Communication Disorders*.

[9] Friedmann, N. A., & Grodzinsky, Y. (1997). Tense and agreement in agrammatic production: Pruning the syntactic tree. *Brain and language*, 56(3), 397-425.

[10] Friedmann, N. A. (2001). Agrammatism and the psychological reality of the syntactic tree. *Journal of Psycholinguistic Research*, 30, 71-90.

[11] Rizzi, L. (1990). Relativized minimality. The MIT Press.

[12] Grillo, N. (2008). Generalized minimality. *Utrecht Institute of Linguistics, OTS*.

[13] Papagno, C., Cecchetto, C., Reati, F., & Bello, L. (2007). Processing of syntactically complex
sentences relies on verbal short-term memory: Evidence from a short-term memory patient. *Cognitive Neuropsychology, 24*(3), 292-311.

[14] Parisi, D., & Pizzamiglio, L. (1970). Syntactic comprehension in aphasia. *Cortex, 6*(2), 204-215.

[15] Cho-Reyes, S., & Thompson, C. K. (2012). Verb and sentence production and comprehension in aphasia: Northwestern Assessment of Verbs and Sentences (NAVS). *Aphasiology, 26*(10), 1250-1277.

[16] Barbieri, E., Brambilla, I., Thompson, C. K., & Luzzatti, C. (2019). Verb and sentence processing patterns in healthy Italian participants: Insight from the Northwestern Assessment of Verbs and Sentences (NAVS). *Journal of communication disorders, 79*, 58-75.

[17] Barbieri, E., Alessio, V., Zanobio, E., Scola, I., Luzzatti, C., & Thompson, C. K. (2024). Assessment of verb and sentence processing deficits in stroke-induced aphasia: the Italian version of the Northwestern Assessment of Verbs and Sentences (NAVS-I). *Aphasiology, 38*(3), 510-543.

[18] Cecchetto C., Di Domenico, A., Garraffa M., & Papagno C. (2012). COMPRENDO. Batteria per la comprensione di frasi negli adulti, Milano: Raffaele Cortina.

[19] Rochon, E., Waters, G., & Caplan, D. (2000). The relationship between measures of working memory and sentence comprehension in patients with Alzheimer's disease. *Journal of Speech, Language and Hearing Research, 43*, 395-413.

[20] Capitani, E., & Laiacona, M. (2017). Outer and inner tolerance limits: their usefulness for the construction of norms and the standardization of neuropsychological tests. *The Clinical Neuropsychologist, 31*(6-7), 1219-1230.

[21] Aiello, E. N., & Depaoli, E. G. (2022). Norms and standardizations in neuropsychology via equivalent scores: software solutions and practical guides. *Neurological Sciences, 43*(2), 961-966.

[22] Pasotti, F., De Luca, G., Aiello, E. N., Gramegna, C., Di Gangi, M., Foderaro, G., ... & Bottini, G. (2022). A multi-component, adaptive Working Memory Assessment battery (WoMAB): validation and norms in an Italian population sample. *Neurological Sciences, 43*(2), 985-992.

[23] Pasotti, F., Aiello, E. N., Bollani, A., Querzola, M., Cozzi, S., Manfrin, F., ... & Bottini, G. (2024). The Single-Matrix Digit Cancellation Test, a Screener for Selective Attention Deficits: Standardization in an Italian Population Sample and Clinical Usability in Acute Stroke Patients. *Cerebrovascular Diseases, 1-7*.
[24] Diana, L., Pilastro, P., N. Aiello, E., K. Eberhard-Moscicka, A., M. Müri, R., & Bolognini, N. (2021). Saccades, attentional orienting and disengagement: the effects of anodal tDCS over right posterior parietal cortex (PPC) and frontal eye field (FEF). In *ACM Symposium on Eye Tracking Research and Applications* (pp. 1-7).

[25] Arifin, W. N., & Yusoff, M. S. B. (2017). Item Response Theory for Medical Educationists. *Education in Medicine Journal*, 9, 69-81.

[26] Bopp, K. L., & Verhaeghen, P. (2005). Aging and verbal memory span: A meta-analysis. *The Journals of Gerontology Series B: Psychological Sciences and Social Sciences*, 60(5), P223-P233.

[27] Verhaeghen, P. (2016). Age-related slowing in response times, causes and consequences. *Aging*, 29(2), 329-341.
<table><caption>**Table 1.** Factors of syntactic complexity associated with each structure included in RiComprendo.</caption><thead><tr><th></th><th>Filler gap dependency</th><th>Intervention</th><th>Center embedding</th><th>Non-canonical order</th></tr></thead><tbody><tr><td>Simple</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>Passive</td><td>+</td><td>-</td><td>-</td><td>+</td></tr><tr><td>PerSR</td><td>+</td><td>-</td><td>-</td><td>-</td></tr><tr><td>PerOR</td><td>+</td><td>+</td><td>-</td><td>+</td></tr><tr><td>EmbSR</td><td>+</td><td>-</td><td>+</td><td>-</td></tr><tr><td>EmbOR</td><td>+</td><td>+</td><td>+</td><td>+</td></tr><tr><td>Coord</td><td>-</td><td>-</td><td>-</td><td>-</td></tr></tbody></table>
<table><caption>**Table 2.** Adjustment equations for raw RiComprendo measures.</caption><thead><tr><th colspan="2">Adjustment Equations</th></tr></thead><tbody><tr><th colspan="2">Accuracy</th></tr><tr><td>Total Accuracy</td><td>AS=RS+115.7753*[(1/education)-0.077682]</td></tr><tr><td>Simple - Accuracy</td><td>n.a.</td></tr><tr><td>Passive - Accuracy</td><td>AS=RS-0.334231*(education-14.06667)</td></tr><tr><td>PerSR - Accuracy</td><td>AS=RS-8.131651*[ln(education)-2.602759]</td></tr><tr><td>PerOR - Accuracy</td><td>AS=RS-7.550638*[sqrt(education)-3.713877]</td></tr><tr><td>EmbSR - Accuracy</td><td>AS=RS-144.4237*[(1/age)-0.02454]-14.60581*[log<sub>10</sub>(education)-1.130364]</td></tr><tr><td>EmbOR - Accuracy</td><td>AS=RS+0.138334*(age-48.02857)+303.5774*[(1/education)-0.077682]</td></tr><tr><td>Coord - Accuracy</td><td>AS=RS+92.34107*[(1/education)-0.077682]</td></tr><tr><th colspan="2">Reaction Times</th></tr><tr><td>Total RT</td><td>AS=RS-0.004875*[(age)<sup>3</sup>-155690.685714]+69.16938*(education-14.066667)</td></tr><tr><td>Simple - RT</td><td>AS=RS-0.003291*[(age)<sup>3</sup>-155690.685714]+0.069761*[(education)<sup>3</sup>-3356.809524]</td></tr><tr><td>Passive - RT</td><td>AS=RS-0.003603*[(age)<sup>3</sup>-155690.685714]+1.977753*[(education)<sup>2</sup>-211.895238]</td></tr><tr><td>PerSR - RT</td><td>AS=RS-0.004673*[(age)<sup>3</sup>-155690.685714]+2.962859*[(education)<sup>2</sup>-211.895238]</td></tr><tr><td>PerOR - RT</td><td>AS=RS-0.005264*[(age)<sup>3</sup>-155690.685714]+1362.655*[ln(education)-2.602759]</td></tr><tr><td>EmbSR - RT</td><td>AS=RS-0.006226*[(age)<sup>3</sup>-155690.685714]</td></tr><tr><td>EmbOR - RT</td><td>AS=RS-0.005538*[(age)<sup>3</sup>-155690.685714]+4.465497*[(education)<sup>2</sup>-211.895238]</td></tr><tr><td>Coord - RT</td><td>AS=RS-0.006183*[(age)<sup>3</sup>-155690.685714]</td></tr></tbody></table>

**Notes.** AS=adjusted score; RS=raw score; n.a. =adjustment equation not applicable (no significant demographic predictors for this measures); RT=Reaction Time; PerSR=Peripheral Subject Relatives; PerOR=Peripheral Object Relatives; EmbSR=Embedded Subject Relatives; EmbOR=Embedded Object Relatives; Coord=Coordinated.
<table><caption>**Table 3.** Tolerance limits and Equivalent Score thresholds for adjusted RiComprendo measures.</caption><thead><tr><th rowspan="2"></th><th rowspan="2">oTL</th><th rowspan="2">iTTL</th><th colspan="4">Equivalent Scores</th></tr><tr><th>0</th><th>1</th><th>2</th><th>3</th><th>4</th></tr></thead><tbody><tr><th colspan="8">Accuracy</th></tr><tr><td>Total Accuracy</td><td>74.91</td><td>83.48</td><td>≤74.91</td><td>74.92-84.20</td><td>84.21-90.30</td><td>90.31-93.48</td><td>≥93.49</td></tr><tr><td>Simple - Accuracy</td><td>85</td><td>100</td><td>≤85</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>Passive - Accuracy</td><td>77.03</td><td>89.35</td><td>≤77.03</td><td>77.04-91.02</td><td>91.03-97.03</td><td>97.04-99.02</td><td>≥99.03</td></tr><tr><td>PerSR - Accuracy</td><td>74.26</td><td>83.13</td><td>≤74.26</td><td>74.27-85.31</td><td>85.32-91.67</td><td>91.68-96.03</td><td>≥96.04</td></tr><tr><td>PerOR - Accuracy</td><td>55.82</td><td>73.80</td><td>≤55.82</td><td>55.83-76.01</td><td>76.02-86.01</td><td>86.02-91.89</td><td>≥91.90</td></tr><tr><td>EmbSR - Accuracy</td><td>74.61</td><td>79.50</td><td>≤74.61</td><td>74.62-79.86</td><td>79.87-86.60</td><td>86.61-92.81</td><td>≥92.82</td></tr><tr><td>EmbOR - Accuracy</td><td>37.03</td><td>52.40</td><td>≤37.03</td><td>37.04-53.69</td><td>53.70-68.50</td><td>68.51-81.31</td><td>≥81.32</td></tr><tr><td>Coord - Accuracy</td><td>74.93</td><td>88.60</td><td>≤74.93</td><td>74.94-88.60</td><td>88.61-93.09</td><td>93.10-98.26</td><td>≥98.27</td></tr><tr><th colspan="8">Reaction Times</th></tr><tr><td>Total RT</td><td>9719.36</td><td>7873.23</td><td>≥9719.36</td><td>9719.35-7647.53</td><td>7647.52-6360.08</td><td>6360.07-5294.17</td><td>≤5294.16</td></tr><tr><td>Simple - RT</td><td>6279.24</td><td>5047.21</td><td>≥6279.24</td><td>6279.23-4944.12</td><td>4944.11-4008.38</td><td>4008.37-3397.32</td><td>≤3397.31</td></tr><tr><td>Passive - RT</td><td>7221.13</td><td>5703.66</td><td>≥7221.13</td><td>7221.12-5391.23</td><td>5391.22-4456.27</td><td>4456.26-3727.26</td><td>≤3727.25</td></tr><tr><td>PerSR - RT</td><td>9467.09</td><td>8110.29</td><td>≥9467.09</td><td>9467.08-7688.31</td><td>7688.30-6440.46</td><td>6440.45-5305.78</td><td>≤5305.77</td></tr><tr><td>PerOR - RT</td><td>10966.64</td><td>8896.37</td><td>≥10966.64</td><td>10966.63-8794.26</td><td>8794.25-7110.29</td><td>7110.28-5898.97</td><td>≤5898.96</td></tr><tr><td>EmbSR - RT</td><td>9935.09</td><td>8762.84</td><td>≥9935.09</td><td>9935.08-8429.84</td><td>8429.83-7263.46</td><td>7263.45-5983.26</td><td>≤5983.25</td></tr><tr><td>EmbOR - RT</td><td>14286.98</td><td>11656.53</td><td>≥14286.98</td><td>14286.97-10735.04</td><td>10735.03-8298.03</td><td>8298.02-6612.25</td><td>≤6612.24</td></tr><tr><td>Coord - RT</td><td>10657.93</td><td>7993.59</td><td>≥10657.93</td><td>10657.92-7934.57</td><td>7934.56-6733.99</td><td>6733.98-5524.59</td><td>≤5524.58</td></tr></tbody></table>

**Notes.** oTL=outer tolerance limit; iTL=inner tolerance limit; RT=Reaction Time; PerSR=Peripheral Subject Relatives; PerOR=Peripheral Object Relatives; EmbSR=Embedded Subject Relatives; EmbOR=Embedded Object Relatives; Coord=Coordinated.
<table><caption>**Table 4.** Descriptive statistics of the type of mistake within the incorrect responses for each sentence type. The percentages are computed considering the overall dataset and indicate the ratio between the selection of the distractor with the inversion of the thematic roles and the number of incorrect responses.</caption><thead><tr><th>Sentence type</th><th>Mean</th><th>SD</th><th>Range</th><th>% reversible foil*</th></tr></thead><tbody><tr><td><strong>Accuracy</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>Total</td><td>91.905</td><td>6.298</td><td>65.714-100</td><td>72.15%</td></tr><tr><td>Simple</td><td>98.286</td><td>3.305</td><td>80-100</td><td>51.39%</td></tr><tr><td>Passive</td><td>96.833</td><td>5.958</td><td>65-100</td><td>88.28%</td></tr><tr><td>PerSR</td><td>93.929</td><td>7.927</td><td>60-100</td><td>66.67%</td></tr><tr><td>PerOR</td><td>89.405</td><td>11.850</td><td>45-100</td><td>93.72%</td></tr><tr><td>EmbSR</td><td>91.333</td><td>7.788</td><td>70-100</td><td>86.54%</td></tr><tr><td>EmbOR</td><td>78.024</td><td>18.773</td><td>30-100</td><td>61.65%</td></tr><tr><td>Coord</td><td>95.524</td><td>6.504</td><td>65-100</td><td>49.21%</td></tr><tr><td><strong>Reaction Times</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>Total</td><td>5463.396</td><td>1852.823</td><td>2240.910-13377.926</td><td></td></tr><tr><td>Simple</td><td>3568.129</td><td>1183.108</td><td>1570.053-8476.333</td><td></td></tr><tr><td>Passive</td><td>3914.456</td><td>1391.872</td><td>1736.300-9914.800</td><td></td></tr><tr><td>PerSR</td><td>5546.690</td><td>1959.465</td><td>2224.250-14070.375</td><td></td></tr><tr><td>PerOR</td><td>6238.503</td><td>2437.995</td><td>2428.000-20470.583</td><td></td></tr><tr><td>EmbSR</td><td>6088.299</td><td>2047.947</td><td>1940.950-13944.700</td><td></td></tr><tr><td>EmbOR</td><td>7067.239</td><td>3026.252</td><td>2380.143-22489.600</td><td></td></tr><tr><td>Coord</td><td>5820.456</td><td>2109.922</td><td>2323.053-16427.214</td><td></td></tr></tbody></table>

**Notes.** PerSR=Peripheral Subject Relatives; PerOR=Peripheral Object Relatives; EmbSR=Embedded Subject Relatives; EmbOR=Embedded Object Relatives; Coord=Coordinated. SD=standard deviation; Range=minimum-maximum measure. *The percentages are computed considering the overall dataset and indicate the ratio between the selection of the distractor with the inversion of the thematic roles and the number of incorrect responses.
<table><caption>**Table 5.** Aggregate descriptive statistics of difficulty values based on sentence type as yielded by the 1-PL model.</caption><thead><tr><td>Sentence Type</td><td><em>M</em></td><td><em>SD</em></td><td><em>Min</em></td><td><em>Max</em></td></tr></thead><tbody><tr><td>Simple</td><td>-5.21</td><td>1.12</td><td>-6.41</td><td>-2.39</td></tr><tr><td>Passive</td><td>-4.49</td><td>0.82</td><td>-5.64</td><td>-3.19</td></tr><tr><td>PerSR</td><td>-3.62</td><td>0.85</td><td>-5.63</td><td>-2.54</td></tr><tr><td>PerOR</td><td>-2.83</td><td>0.51</td><td>-3.55</td><td>-1.92</td></tr><tr><td>EmbSR</td><td>-3.24</td><td>0.83</td><td>-4.59</td><td>-1.19</td></tr><tr><td>EmbOR</td><td>-1.77</td><td>0.64</td><td>-2.97</td><td>-0.71</td></tr><tr><td>Coord</td><td>-4.08</td><td>0.81</td><td>-5.18</td><td>-2.83</td></tr></tbody></table>

Notes. 1-PL=one-parameter logistic; PerSR=Peripheral Subject Relatives; PerOR=Peripheral Object Relatives; EmbSR=Embedded Subject Relatives; EmbOR=Embedded Object Relatives; Coord=Coordinated.
<table><caption>**Supplementary table 1.** Demographic characteristics of the sample.</caption><thead><tr><th rowspan="2">N° of participants</th><th rowspan="2"></th><th colspan="6">Age (years)</th><th rowspan="2">Total</th></tr><tr><th>18-29</th><th>30-39</th><th>40-49</th><th>50-59</th><th>60-69</th><th>70-80</th></tr></thead><tbody><tr><th rowspan="2">Education (years)</th><th>Gender</th><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><th>&lt; 9</th><td>M</td><td>n.a.</td><td>2</td><td>3</td><td>3</td><td>5</td><td>5</td><td>18</td></tr><tr><th>&lt; 9</th><td>F</td><td>n.a.</td><td>2</td><td>2</td><td>5</td><td>5</td><td>5</td><td>19</td></tr><tr><th rowspan="2">9-13</th><td>M</td><td>10</td><td>7</td><td>6</td><td>6</td><td>5</td><td>5</td><td>39</td></tr><tr><td>F</td><td>10</td><td>7</td><td>5</td><td>7</td><td>5</td><td>6</td><td>40</td></tr><tr><th rowspan="2">&gt; 13</th><td>M</td><td>10</td><td>9</td><td>5</td><td>6</td><td>8</td><td>6</td><td>44</td></tr><tr><td>F</td><td>10</td><td>9</td><td>9</td><td>10</td><td>7</td><td>5</td><td>50</td></tr><tr><th>Total</th><td></td><td>40</td><td>36</td><td>30</td><td>37</td><td>35</td><td>32</td><td>210</td></tr></tbody></table>

Notes. M=male; F=female; n.a.=no participant included.
<table><caption>**Supplementary table 2.** Bonferroni-corrected post-hoc comparisons for Accuracy measures for each sentence type.</caption><thead><tr><th>Sentence type</th><th>exp(b)</th><th>SE</th><th>z</th><th>p<sub>Bonferroni</sub></th></tr></thead><tbody><tr><td>Simple - Passive</td><td>2.291</td><td>0.618</td><td>3.074</td><td>.044</td></tr><tr><td>Simple - PerSR</td><td>4.932</td><td>1.292</td><td>6.092</td><td>&lt;.001</td></tr><tr><td>Simple - PerOR</td><td>10.429</td><td>2.695</td><td>9.072</td><td>&lt;.001</td></tr><tr><td>Simple - EmbSR</td><td>7.385</td><td>1.919</td><td>7.696</td><td>&lt;.001</td></tr><tr><td>Simple - EmbOR</td><td>27.231</td><td>6.983</td><td>12.886</td><td>&lt;.001</td></tr><tr><td>Simple - Coord</td><td>3.543</td><td>0.938</td><td>4.778</td><td>&lt;.001</td></tr><tr><td>Passive - PerSR</td><td>2.152</td><td>0.518</td><td>3.184</td><td>.031</td></tr><tr><td>Passive - PerOR</td><td>4.552</td><td>1.075</td><td>6.418</td><td>&lt;.001</td></tr><tr><td>Passive - EmbSR</td><td>3.223</td><td>0.767</td><td>4.918</td><td>&lt;.001</td></tr><tr><td>Passive - EmbOR</td><td>11.885</td><td>2.779</td><td>10.586</td><td>&lt;.001</td></tr><tr><td>Passive - Coord</td><td>1.546</td><td>0.377</td><td>1.788</td><td>1.000</td></tr><tr><td>PerSR - PerOR</td><td>2.115</td><td>0.479</td><td>3.305</td><td>.020</td></tr><tr><td>PerSR - EmbSR</td><td>1.498</td><td>0.342</td><td>1.766</td><td>1.000</td></tr><tr><td>PerSR - EmbOR</td><td>5.522</td><td>1.238</td><td>7.622</td><td>&lt;.001</td></tr><tr><td>PerSR - Coord</td><td>0.718</td><td>0.169</td><td>-1.409</td><td>1.000</td></tr><tr><td>PerOR - EmbSR</td><td>0.708</td><td>0.158</td><td>-1.545</td><td>1.000</td></tr><tr><td>PerOR - EmbOR</td><td>2.611</td><td>0.570</td><td>4.393</td><td>&lt;.001</td></tr><tr><td>PerOR - Coord</td><td>0.340</td><td>0.078</td><td>-4.700</td><td>&lt;.001</td></tr><tr><td>EmbSR - EmbOR</td><td>3.687</td><td>0.814</td><td>5.909</td><td>&lt;.001</td></tr><tr><td>EmbSR - Coord</td><td>0.480</td><td>0.111</td><td>-3.170</td><td>.032</td></tr><tr><td>EmbOR - Coord</td><td>0.130</td><td>0.030</td><td>-8.971</td><td>&lt;.001</td></tr></tbody></table>

**Notes.** PerSR=Peripheral Subject Relatives; PerOR=Peripheral Object Relatives; EmbSR=Embedded Subject Relatives; EmbOR= Embedded Object Relatives; Coord=Coordinated.
<table><caption>**Supplementary table 3.** Bonferroni-corrected post-hoc comparisons for RTs measures for each sentence type.</caption><thead><tr><th>Sentence type</th><th>exp(b)</th><th>SE</th><th>z</th><th>p<sub>Bonferroni</sub></th></tr></thead><tbody><tr><td>Simple - Passive</td><td>0.916</td><td>0.050</td><td>-1.623</td><td>1.000</td></tr><tr><td>Simple - PerSR</td><td>0.648</td><td>0.035</td><td>-8.002</td><td>&lt;.001</td></tr><tr><td>Simple - PerOR</td><td>0.575</td><td>0.031</td><td>-10.199</td><td>&lt;.001</td></tr><tr><td>Simple - EmbSR</td><td>0.579</td><td>0.031</td><td>-10.094</td><td>&lt;.001</td></tr><tr><td>Simple - EmbOR</td><td>0.509</td><td>0.028</td><td>-12.451</td><td>&lt;.001</td></tr><tr><td>Simple - Coord</td><td>0.617</td><td>0.033</td><td>-8.915</td><td>&lt;.001</td></tr><tr><td>Passive - PerSR</td><td>0.708</td><td>0.038</td><td>-6.376</td><td>&lt;.001</td></tr><tr><td>Passive - PerOR</td><td>0.628</td><td>0.034</td><td>-8.572</td><td>&lt;.001</td></tr><tr><td>Passive - EmbSR</td><td>0.632</td><td>0.034</td><td>-8.465</td><td>&lt;.001</td></tr><tr><td>Passive - EmbOR</td><td>0.556</td><td>0.030</td><td>-10.824</td><td>&lt;.001</td></tr><tr><td>Passive - Coord</td><td>0.674</td><td>0.037</td><td>-7.286</td><td>&lt;.001</td></tr><tr><td>PerSR - PerOR</td><td>0.888</td><td>0.048</td><td>-2.199</td><td>.585</td></tr><tr><td>PerSR - EmbSR</td><td>0.893</td><td>0.048</td><td>-2.090</td><td>.770</td></tr><tr><td>PerSR - EmbOR</td><td>0.786</td><td>0.043</td><td>-4.450</td><td>&lt;.001</td></tr><tr><td>PerSR - Coord</td><td>0.952</td><td>0.052</td><td>-0.910</td><td>1.000</td></tr><tr><td>PerOR - EmbSR</td><td>1.006</td><td>0.055</td><td>0.110</td><td>1.000</td></tr><tr><td>PerOR - EmbOR</td><td>0.885</td><td>0.048</td><td>-2.251</td><td>.512</td></tr><tr><td>PerOR - Coord</td><td>1.072</td><td>0.058</td><td>1.290</td><td>1.000</td></tr><tr><td>EmbSR - EmbOR</td><td>0.880</td><td>0.048</td><td>-2.361</td><td>.383</td></tr><tr><td>EmbSR - Coord</td><td>1.066</td><td>0.058</td><td>1.180</td><td>1.000</td></tr><tr><td>EmbOR - Coord</td><td>1.212</td><td>0.066</td><td>3.541</td><td>.008</td></tr></tbody></table>

**Notes.** RTs(response times; PerSR=Peripheral Subject Relatives; PerOR=Peripheral Object Relatives; EmbSR=Embedded Subject Relatives; EmbOR=Embedded Object Relatives; Coord=Coordinated.
**Figure 1.** Experimental procedure of RiComprendo. In this example participants hear the sentence "Il gatto è inseguito dal cane" (The dog is chased by the cat) and the matching picture is displayed as the first one at the top of the screen.

<figure><img src="image_2.png" /></figure>
<figure><img src="image_3.png" /><figcaption>**Figure 2.** Probability of a correct response on RiComprendo item as a function of sentence type.</figcaption></figure>

**Notes.** P.=probability; PerSR=Peripheral Subject Relatives; PerOR=Peripheral Object Relatives; EmbSR=Embedded Subject Relatives; EmbOR=Embedded Object Relatives; Coord=Coordinated. Reported values are plotted as estimated marginal means with *SE* bars.
<figure><img src="image_4.png" /><figcaption>**Figure 3.** RTs on RiComprendo item as a function of sentence type.</figcaption></figure>

**Notes.** PerSR=Peripheral Subject Relatives; PerOR=Peripheral Object Relatives; EmbSR=Embedded Subject Relatives; EmbOR=Embedded Object Relatives; Coord=Coordinated. Reported values are plotted as estimated marginal means with *SE* bars.