The child the apple eats: processing of argument structure in Mandarin verb-final sentences.

Mandarin Chinese is typologically unusual among the world's languages in having flexible word order despite a near absence of inflectional morphology. These features of Mandarin challenge conventional linguistic notions such as subject and object and the divide between syntax and semantics. In the present study, we tested monolingual processing of argument structure in Mandarin verb-final sentences, where word order alone is not a reliable cue. We collected participants' responses to a forced agent-assignment task while measuring their electroencephalography data to capture real-time processing throughout each sentence. We found that sentence interpretation was not informed by word order in the absence of other cues, and while the coverbs BA and BEI were strong signals for agent selection, comprehension was a result of multiple cues. These results challenge previous reports of a linear ranking of cue strength. Event-related potentials showed that BA and BEI impacted participants' processing even before the verb was read and that role reversal anomalies elicited an N400 effect without a subsequent semantic P600. This study demonstrates that Mandarin sentence comprehension requires online interaction among cues in a language-specific manner, consistent with models that predict crosslinguistic differences in core sentence processing mechanisms.

Chinese text classification method based on sentence information enhancement and feature fusion.

Text classification involves annotating text data with specific labels and is a crucial research task in the field of natural language processing. Chinese text classification presents significant challenges due to the complex semantics of the language, difficulties in semantic feature extraction, and the interleaving and irregularity of lexical features. Traditional methods often struggle to manage the relationships between words and sentences in Chinese, hindering the model's ability to capture deep semantic information and resulting in poor classification performance. To address these issues, a Chinese text classification method based on utterance information enhancement and feature fusion is proposed. This method first embeds the text into a unified space and obtains feature representations of word vectors and sentence vectors using the BERT (Bidirectional Encoder Representations from Transformers) pre-trained language model. Subsequently, an utterance information enhancement module is constructed to perform syntactic enhancement and feature extraction on the sentence information within the text. Additionally, a feature fusion strategy is introduced to combine the enhanced sentence-level information features with the word-level features extracted by the Bi-GRU (Bidirectional Gated Recurrent Unit network), culminating in the classification output. This approach effectively enhances the feature representation of Chinese text and significantly filters out irrelevant and noisy information. Evaluations on several Chinese datasets demonstrate that the proposed method surpasses existing mainstream classification models in terms of classification accuracy and F1 value, validating its effectiveness and feasibility.

The Impact of Collaborative Documentation on Person-Centered Care: Textual Analysis of Clinical Notes.

Background: Collaborative documentation (CD) is a behavioral health practice involving shared writing of clinic visit notes by providers and consumers. Despite widespread dissemination of CD, research on its effectiveness or impact on person-centered care (PCC) has been limited. Principles of PCC planning, a recovery-based approach to service planning that operationalizes PCC, can inform the measurement of person-centeredness within clinical documentation. Objective: This study aims to use the clinical informatics approach of natural language processing (NLP) to examine the impact of CD on person-centeredness in clinic visit notes. Using a dictionary-based approach, this study conducts a textual analysis of clinic notes from a community mental health center before and after staff were trained in CD. Methods: This study used visit notes (n=1981) from 10 providers in a community mental health center 6 months before and after training in CD. LIWC-22 was used to assess all notes using the Linguistic Inquiry and Word Count (LIWC) dictionary, which categorizes over 5000 linguistic and psychological words. Twelve LIWC categories were selected and mapped onto PCC planning principles through the consensus of 3 domain experts. The LIWC-22 contextualizer was used to extract sentence fragments from notes corresponding to LIWC categories. Then, fixed-effects modeling was used to identify differences in notes before and after CD training while accounting for nesting within the provider. Results: Sentence fragments identified by the contextualizing process illustrated how visit notes demonstrated PCC. The fixed effects analysis found a significant positive shift toward person-centeredness; this was observed in 6 of the selected LIWC categories post CD. Specifically, there was a notable increase in words associated with achievement (ß=.774, P<.001), power (ß=.831, P<.001), money (ß=.204, P<.001), physical health (ß=.427, P=.03), while leisure words decreased (ß=-.166, P=.002). Conclusions: By using a dictionary-based approach, the study identified how CD might influence the integration of PCC principles within clinical notes. Although the results were mixed, the findings highlight the potential effectiveness of CD in enhancing person-centeredness in clinic notes. By leveraging NLP techniques, this research illuminated the value of narrative clinical notes in assessing the quality of care in behavioral health contexts. These findings underscore the promise of NLP for quality assurance in health care settings and emphasize the need for refining algorithms to more accurately measure PCC.

Rate of speech affects the comprehension of pronouns in children with developmental language disorder.

This study examined whether children with Developmental Language Disorder (DLD) have knowledge of binding principles (i.e., linking pronouns to their structurally licensed antecedent) during real-time sentence processing (cross-modal priming, real-time) and overt comprehension (sentence-picture matching, interpretative) and whether rate of speech impacted access to that knowledge. Fourteen children with DLD participated in two experiments, with sentences presented auditorily at either a regular or slow speech rate. Sentences were matched except to contain a pronoun, reflexive, or noun phrase (control) in the same syntactic position. Experiment (1) used a cross-modal picture priming paradigm to test real-time pronoun-antecedent linking abilities at both rates of speech. Children were instructed to make a binary decision during the uninterrupted auditory presentation of a sentence to a visually presented image (of the antecedent) at the offset of a pronoun, a reflexive, or a control noun. Response times between conditions (e.g., pronoun vs. control noun) were compared to determine whether participants showed evidence of facilitative priming (faster response times in the pronoun than control noun condition) at either speech rate. Experiment (2) used an auditory sentence-picture-matching task to test final comprehension of similar sentences containing a pronoun or reflexive. Accuracy was compared across both speech rates. For Experiment (1), children with DLD did not show evidence of real-time pronoun-antecedent priming at the regular speech rate. However, when sentences were slowed, they showed facilitative priming for the pronoun condition. For experiment (2), children with DLD performed at-chance when interpreting sentences with pronouns regardless of speech rate. While children with DLD have been shown to have difficulty processing sentences containing anaphors (such as pronouns), results suggest that this is not due to loss of intrinsic knowledge of binding principles. By slowing the rate of speech input, we showed that children with DLD do have access to that knowledge and can make the correct link during real-time processing between a pronoun and its structurally licensed antecedent (Experiment 1) but need more time to do so. However, the effect of slowed speech input does not extend to final comprehension (Experiment 2).

Syntactic flexibility and lexical encoding in aging sentence production: an eye tracking study.

Purpose: Successful sentence production requires lexical encoding and ordering them into a correct syntactic structure. It remains unclear how different processes involved in sentence production are affected by healthy aging. We investigated (a) if and how aging affects lexical encoding and syntactic formulation during sentence production, using auditory lexical priming and eye tracking-while-speaking paradigms and (b) if and how verbal working memory contributes to age-related changes in sentence production. Methods: Twenty older and 20 younger adults described transitive and dative action pictures following auditory lexical primes, by which the relative ease of encoding the agent or theme nouns (for transitive pictures) and the theme and goal nouns (for dative pictures) was manipulated. The effects of lexical priming on off-line syntactic production and real-time eye fixations to the primed character were measured. Results: In offline production, older adults showed comparable priming effects to younger adults, using the syntactic structure that allows earlier mention of the primed lexical item in both transitive and dative sentences. However, older adults showed longer lexical priming effects on eye fixations to the primed character during the early stages of sentence planning. Preliminary analysis indicated that reduced verbal working memory may in part account for longer lexical encoding, particularly for older adults. Conclusion: These findings indicate that syntactic flexibility for formulating different grammatical structures remains largely robust with aging. However, lexical encoding processes are more susceptible to age-related changes, possibly due to changes in verbal working memory.

LITMUS Turkish sentence repetition test: The best items, effect of scoring and diagnostic accuracy.

PURPOSE: This study aimed to examine LITMUS Turkish Sentence Repetition Test's (LITMUS-TR) diagnostic accuracy, as well as the best scoring method and most distinguishing test items. We also sought to ascertain whether age has an impact on the sensitivity and specificity. METHOD: Two hundred and fifty children with typical language development (TD) between the ages of 4 and 7, as well as 44 children with developmental language disorder (DLD), took part in the study. Data was collected using TODIL, LITMUS-TR, and the pediatric family interview form. LITMUS-TR was graded using four different methods. RESULTS: The performance of children with DLD in each score type was lower and the number of errors higher than those with TD. All items have excellent or acceptable item difficulty and discrimination values for binary scoring and total number of errors. LITMUS-TR's most distinctive items were complex structures with dependencies, such as syntactic movement and embedding. LITMUS-TR had high diagnostic accuracy for the whole test (0.887) and each scoring method. A separate analysis of each age group showed sensitivity and specificity above 0.80. CONCLUSIONS: When employed as a supportive objective measure, LITMUS-TR was proven to be an effective diagnostic tool for DLD, with age influencing the diagnostic accuracy outcomes.

Text classification models for assessing the completeness of randomized controlled trial publications based on CONSORT reporting guidelines.

Complete and transparent reporting of randomized controlled trial publications (RCTs) is essential for assessing their credibility. We aimed to develop text classification models for determining whether RCT publications report CONSORT checklist items. Using a corpus annotated with 37 fine-grained CONSORT items, we trained sentence classification models (PubMedBERT fine-tuning, BioGPT fine-tuning, and in-context learning with GPT-4) and compared their performance. We assessed the impact of data augmentation methods (Easy Data Augmentation (EDA), UMLS-EDA, text generation and rephrasing with GPT-4) on model performance. We also fine-tuned section-specific PubMedBERT models (e.g., Methods) to evaluate whether they could improve performance compared to the single full model. We performed 5-fold cross-validation and report precision, recall, F1 score, and area under curve (AUC). Fine-tuned PubMedBERT model that uses the sentence along with the surrounding sentences and section headers yielded the best overall performance (sentence level: 0.71 micro-F1, 0.67 macro-F1; article-level: 0.90 micro-F1, 0.84 macro-F1). Data augmentation had limited positive effect. BioGPT fine-tuning and GPT-4 in-context learning exhibited suboptimal results. Methods-specific model improved recognition of methodology items, other section-specific models did not have significant impact. Most CONSORT checklist items can be recognized reasonably well with the fine-tuned PubMedBERT model but there is room for improvement. Improved models can underpin the journal editorial workflows and CONSORT adherence checks.

Sentence comprehension deficits in aphasia disorders: A systematic review of mapping therapy.

Patients with aphasia (PWA), particularly those with agrammatic aphasia, experience problems in sentence comprehension. Studies have found that Mapping Therapy (MT) can improve sentence processing in PWA. This paper aims to review the literature on therapeutic studies using MT for the treatment of sentence processing in PWA. All studies on the treatment of sentence comprehension using MT were found by searching Cochrane Library, ISI Web of Knowledge, Google Scholar, Pubmed, and Scopus from 1986 until December 2023, with the combination of these search keywords: 'aphasia, sentence, comprehension, mapping therapy, treatment, rehabilitation'. All studies (single-subject or group design) on the treatment of sentence comprehension using MT in PWA were reviewed. An adaptation of the Cochrane Collaboration's risk of bias (RoB) tool was used to assess the risk of bias (RoB) in the reviewed studies. A total of 14 studies on 81 participants were selected and reviewed. All studies (13 studies) had employed a single-subject design, except for one study that had used a group design. Twelve studies (86%) showed that MT is effective in the remediation of sentence comprehension in PWA. Generalization to untrained sentences similar to the trained structure was also observed in 12 studies (86%). Generalization to untrained structures (usually passive sentences) was limited. In addition, cross-modal improvement in sentence production was observed in 8 studies (57%). This review highlights the need for a more detailed investigation of the effect of MT on cross-modal generalization using elicited production of the sentence types trained during comprehension treatment.

Letters, Words, Sentences, and Reading.

In this personal, and therefore highly selective, review article I summarize work performed in collaboration with numerous colleagues on how skilled adult readers perform identification tasks and speeded binary decision tasks involving single letters and visually presented words and sentences. The overarching aim is to highlight similarities in the processing performed at three key levels involved in written language comprehension (in languages that use an alphabetic script): letters, words, and sentences. The comparisons are made using behavioral data obtained with: i) speeded (response-limited) binary decision tasks; and ii) the effects of simultaneous surrounding context on letter and word identification using both data-limited (non-speeded) and response-limited procedures. I then propose a general framework that combines the three levels of processing, and that connects core processes at each level with the processing involved in tasks designed to reflect those core processes, and I end by suggesting possible avenues for future research with an aim to extend this general framework.

Incremental Discourse-Update Constrains Number Agreement Attraction Effect.

While a large body of work in sentence comprehension has explored how different types of linguistic information are used to guide syntactic parsing, less is known about the effect of discourse structure. This study investigates this question, focusing on the main and subordinate discourse contrast manifested in the distinction between restrictive relative clauses (RRCs) and appositive relative clauses (ARCs) in American English. In three self-paced reading experiments, we examined whether both RRCs and ARCs interfere with the matrix clause content and give rise to the agreement attraction effect. While the standard attraction effect was consistently observed in the baseline RRC structures, the effect varied in the ARC structures. These results collectively suggest that discourse structure indeed constrains syntactic dependency resolution. Most importantly, we argue that what is at stake is not the static discourse structure properties at the global sentence level. Instead, attention should be given to the incremental update of the discourse structure in terms of which discourse questions are active at any given moment of a discourse. The current findings have implications for understanding the way discourse structure, specifically the active state of discourse questions, constrains memory retrieval.

Perceptual inference corrects function word errors in reading: Errors that are not noticed do not disrupt eye movements.

Both everyday experience and laboratory research demonstrate that readers often fail to notice errors such as an omitted or repeated function word. This phenomenon challenges central tenets of reading and sentence processing models, according to which each word is lexically processed and incrementally integrated into a syntactic representation. One solution would propose that apparent failure to notice such errors reflects post-perceptual inference; the reader does initially perceive the error, but then unconsciously 'corrects' the perceived string. Such a post-perceptual account predicts that when readers fail to explicitly notice an error, the error will nevertheless disrupt reading, at least fleetingly. We present a large-scale eyetracking experiment investigating whether disruption is detectable in the eye movement record when readers fail to notice an omitted or repeated two-letter function word in naturalistic sentences. Readers failed to notice both omission and repetition errors over 36% of the time. In an analysis that included all trials, both omission and repetition resulted in pronounced eye movement disruption, compared to reading of grammatical control sentences. But in an analysis including only trials on which readers failed to notice the errors, neither type of error disrupted eye movements on any measure. Indeed, there was evidence in some measures that reading was relatively fast on the trials on which errors were missed. It does not appear that when an error is not consciously noticed, it is initially perceived, and then later corrected; rather, linguistic knowledge influences what the reader perceives.

Transcranial photobiomodulation on the left inferior frontal gyrus enhances Mandarin Chinese L1 and L2 complex sentence processing performances.

This study investigated the causal enhancing effect of transcranial photobiomodulation (tPBM) over the left inferior frontal gyrus (LIFG) on syntactically complex Mandarin Chinese first language (L1) and second language (L2) sentence processing performances. Two (L1 and L2) groups of participants (thirty per group) were recruited to receive the double-blind, sham-controlled tPBM intervention via LIFG, followed by the sentence processing, the verbal working memory (WM), and the visual WM tasks. Results revealed a consistent pattern for both groups: (a) tPBM enhanced sentence processing performance but not verbal WM for linear processing of unstructured sequences and visual WM performances; (b) Participants with lower sentence processing performances under sham tPBM benefited more from active tPBM. Taken together, the current study substantiated that tPBM enhanced L1 and L2 sentence processing, and would serve as a promising and cost-effective noninvasive brain stimulation (NIBS) tool for future applications on upregulating the human language faculty.

Novel Approach to Personalized Physician Recommendations Using Semantic Features and Response Metrics: Model Evaluation Study.

BACKGROUND: The rapid growth of web-based medical services has highlighted the significance of smart triage systems in helping patients find the most appropriate physicians. However, traditional triage methods often rely on department recommendations and are insufficient to accurately match patients' textual questions with physicians' specialties. Therefore, there is an urgent need to develop algorithms for recommending physicians. OBJECTIVE: This study aims to develop and validate a patient-physician hybrid recommendation (PPHR) model with response metrics for better triage performance. METHODS: A total of 646,383 web-based medical consultation records from the Internet Hospital of the First Affiliated Hospital of Xiamen University were collected. Semantic features representing patients and physicians were developed to identify the set of most similar questions and semantically expand the pool of recommended physician candidates, respectively. The physicians' response rate feature was designed to improve candidate rankings. These 3 characteristics combine to create the PPHR model. Overall, 5 physicians participated in the evaluation of the efficiency of the PPHR model through multiple metrics and questionnaires as well as the performance of Sentence Bidirectional Encoder Representations from Transformers and Doc2Vec in text embedding. RESULTS: The PPHR model reaches the best recommendation performance when the number of recommended physicians is 14. At this point, the model has an F1-score of 76.25%, a proportion of high-quality services of 41.05%, and a rating of 3.90. After removing physicians' characteristics and response rates from the PPHR model, the F1-score decreased by 12.05%, the proportion of high-quality services fell by 10.87%, the average hit ratio dropped by 1.06%, and the rating declined by 11.43%. According to whether those 5 physicians were recommended by the PPHR model, Sentence Bidirectional Encoder Representations from Transformers achieved an average hit ratio of 88.6%, while Doc2Vec achieved an average hit ratio of 53.4%. CONCLUSIONS: The PPHR model uses semantic features and response metrics to enable patients to accurately find the physician who best suits their needs.

Dissociating Cerebellar Regions Involved in Formulating and Articulating Words and Sentences.

We investigated which parts of the cerebellum are involved in formulating and articulating sentences using (i) a sentence production task that involved describing simple events in pictures; (ii) an auditory sentence repetition task involving the same sentence articulation but not sentence formulation; and (iii) an auditory sentence-to-picture matching task that involved the same pictorial events and no overt articulation. Activation for each of these tasks was compared to the equivalent word processing tasks: noun production, verb production, auditory noun repetition, and auditory noun-to-picture matching. We associate activation in bilateral cerebellum lobule VIIb with sequencing words into sentences because it increased for sentence production compared to all other conditions and was also activated by word production compared to word matching. We associate a paravermal part of right cerebellar lobule VIIIb with overt motor execution of speech, because activation was higher during (i) production and repetition of sentences compared to the corresponding noun conditions and (ii) noun and verb production compared to all matching tasks, with no activation relative to fixation during any silent (nonspeaking) matching task. We associate activation within right cerebellar Crus II with covert articulatory activity because it activated for (i) all speech production more than matching tasks and (ii) sentences compared to nouns during silent (nonspeaking) matching as well as sentence production and sentence repetition. Our study serendipitously segregated, for the first time, three distinct functional roles for the cerebellum in generic speech production, and it demonstrated how sentence production enhanced the demands on these cerebellar regions.

Language Markers of Dementia and Their Role in Early Diagnosis of Alzheimer's Disease: Exploring Grammatical and Syntactic Competence via Sentence Repetition.

Background: Earlier research focuses primarily on the cognitive changes due to Alzheimer's disease (AD); however, little is known with regard to changes in language competence across the lifespan. Objective: The present study aims to investigate the decline of language skills at the grammatical and syntactic levels due to changes in cognitive function. Methods: We administered the Litmus Sentence Repetition Task (SRT) to 150 native speakers of Greek who fall into five groups: 1) young healthy speakers, 2) cognitively intact elder healthy speakers, 3) speakers with subjective cognitive impairment (SCI), 4) speakers with mild cognitive impairment (MCI); and 5) speakers with AD dementia at the mild/moderate stages. All participants underwent a physical and neurological examination and cognitive screening with a standardized neuropsychological battery to assess cognitive status comprehensively and evaluate aspects like working memory, executive function, attention and memory to appropriately classify them. Results: The data analysis revealed that the SRT had high discriminatory value in the development of AD; specifically, both accuracy and grammaticality indices were related to cognitive decline. Additionally, syntax significantly affected the performance of speakers with structures such as clitics being particularly challenging and in most structures the performance of speakers with MCI drops significantly compared to speakers with SCI. Conclusions: Linguistic indices revealed subtle early signs of cognitive decline that can be helpful in the early detection of AD, thus facilitating the clinical process offering support to language-based assessment tools such as sentence repetition, a non-invasive type of assessment to evaluate symptoms of AD.

Comparison of user interfaces for measuring the matrix sentence test on a smartphone.

OBJECTIVE: Smartphone-based self-testing could facilitate large-scale data collection and remote diagnostics. For this purpose, the matrix sentence test (MST) is an ideal candidate due to its repeatability and accuracy. In clinical practice, the MST requires professional audiological equipment and supervision, which is infeasible for smartphone-based self-testing. Therefore, it is crucial to investigate the feasibility of self-administering the MST on smartphones, including the development of an appropriate user interface for the small screen size. DESIGN: We compared the traditional closed matrix user interface (10 × 5 matrix) to three alternative, newly-developed interfaces (slide, type, wheel) regarding SRT consistency, user preference, and completion time. STUDY SAMPLE: We included 15 younger normal hearing and 14 older hearing-impaired participants in our study. RESULTS: The slide interface is most suitable for mobile implementation, providing consistent and fast SRTs and enabling all participants to perform the tasks effectively. While the traditional matrix interface works well for most participants, some participants experienced difficulties due to its small size on the screen. CONCLUSIONS: We propose the newly-introduced slide interface as a plausible alternative for smartphone screens. This might be more attractive for elderly patients that may exhibit more challenges with dexterity and vision than our test subjects employed here.

Guessing errors made by children with dyslexia in word and text reading.

Introduction: Children with dyslexia face persistent difficulties in reading acquisition, which results in poor reading accuracy. In addition to the commonly studied reading errors such as omissions, additions, substitutions, and letter reversals, they also make guessing errors characterized by replacing a word with an orthographic neighbor. These errors, which occur in the context of isolated words and sentence or text reading, might be linked to the inhibition issues that have already been demonstrated in connection to dyslexia. However, to the best of our knowledge, there is no experimental evidence that children with dyslexia make more guessing errors than typically developing children, as is the case for sequential errors. The current study aimed to evaluate whether children with dyslexia made more guessing errors than typically developing children and whether these errors were more frequent in an isolated word or sentence context. Methods: Twenty-eight children with dyslexia from Grade 4 were matched with typically developing children by either chronological age or reading level. Reading was assessed through word and text reading tasks. Error types were classified into seven categories and analyzed. Results and conclusion: A repeated-measure ANOVA showed that children with dyslexia made more guessing errors, particularly visual and morphemic errors, than typically developing children. Moreover, these errors were found at both the single word and sentence levels. These findings suggest that children with dyslexia tend to use a global treatment of words, relying on incomplete information to compensate for their difficulties. The findings have practical implications for pedagogical and therapeutic approaches.

Comparative Evaluation of Pre-Trained Language Models for Biomedical Information Retrieval.

Finding relevant information in the biomedical literature increasingly depends on efficient information retrieval (IR) algorithms. Cross-Encoders, SentenceBERT, and ColBERT are algorithms based on pre-trained language models that use nuanced but computable vector representations of search queries and documents for IR applications. Here we investigate how well these vectorization algorithms estimate relevance labels of biomedical documents for search queries using the OHSUMED dataset. For our evaluation, we compared computed scores to provided labels by using boxplots and Spearman's rank correlations. According to these metrics, we found that Sentence-BERT moderately outperformed the alternative vectorization algorithms and that additional fine-tuning based on a subset of OHSUMED labels yielded little additional benefit. Future research might aim to develop a larger dedicated dataset in order to optimize such methods more systematically, and to evaluate the corresponding functions in IR tools with end-users.

Processing causal structure sentences in Mandarin Chinese: an eye movements study.

It remains uncertain whether causal structure prediction can improve comprehension in Chinese sentences and whether the position of the headword mediates the prediction effect. We conducted an experiment to explore the effect of causal prediction and headword position in Chinese sentence reading. Participants were asked to read sentences containing causal connectives with their eye movements recorded. In the experiment, we manipulated the causal structure of the sentence and the position of the headword. We found a promoting effect of causal structure on first-pass reading time and a hindering impact on total reading time. However, the effect was not mediated by the headword position. The results show that causal syntactic prediction facilitated early-stage processing and increased the integration cost in the late stage of Chinese sentence processing. These findings also support the constraint-based approach, which suggests an isolation between semantic and syntactic processing.

The Neurofunctional Correlates of Morphosyntactic and Thematic Impairments in Aphasia: A Systematic Review and Meta-analysis.

Lesion-symptom studies in persons with aphasia showed that left temporoparietal damage, but surprisingly not prefrontal damage, correlates with impaired ability to process thematic roles in the comprehension of semantically reversible sentences (The child is hugged by the mother). This result has led to challenge the time-honored view that left prefrontal regions are critical for sentence comprehension. However, most studies focused on thematic role assignment and failed to consider morphosyntactic processes that are also critical for sentence processing. We reviewed and meta-analyzed lesion-symptom studies on the neurofunctional correlates of thematic role assignment and morphosyntactic processing in comprehension and production in persons with aphasia. Following the PRISMA checklist, we selected 43 papers for the review and 27 for the meta-analysis, identifying a set of potential bias risks. Both the review and the meta-analysis confirmed the correlation between thematic role processing and temporoparietal regions but also clearly showed the involvement of prefrontal regions in sentence processing. Exploratory meta-analyses suggested that both thematic role and morphosyntactic processing correlate with left prefrontal and temporoparietal regions, that morphosyntactic processing correlates with prefrontal structures more than with temporoparietal regions, and that thematic role assignment displays the opposite trend. We discuss current limitations in the literature and propose a set of recommendations for clarifying unresolved issues.