A Computational Evaluation of Two Models of Retrieval Processes in Sentence Processing in Aphasia

RPI-GGCN: Prediction of RNA-Protein Interaction Based on Interpretability Gated Graph Convolution Neural Network and Co-Regularized Variational Autoencoders

RNA-protein interactions (RPIs) play an important role in several fundamental cellular physiological processes, including cell motility, chromosome replication, transcription and translation, and signaling. Predicting RPI can guide the exploration of cellular biological functions, intervening in diseases, and designing drugs. Given this, this study proposes the RPI-gated graph convolutional network (RPI-GGCN) method for predicting RPI based on the gated graph convolutional neural network (GGCN) and co-regularized variational autoencoder (Co-VAE). First, different types of feature information were extracted from RNA and protein sequences by nine feature extraction methods. Second, Co-VAEs are used to eliminate the redundancy of fused features and generate optimal features. Finally, this study introduces gated cyclic units into graph convolutional networks (GCNs) to construct a model for RPI prediction, which efficiently extracts topological information and improves the model's interpretable feature learning and expression capabilities. In the fivefold cross-validation test, the RPI-GGCN method achieved prediction accuracies of 97.27%, 97.32%, 96.54%, 95.76%, and 94.98% on the RPI369, RPI488, RPI1446, RPI1807, and RPI2241 datasets. To test the generalization performance of the model, we used the model trained on RPI369 to predict the independent NPInter v3.0 dataset and achieved excellent performance in all six independent validation sets. By visualizing the RPI network graph based on the prediction results, we aim to provide a new perspective and reference for studying RPI mechanisms and exploring new RPIs. Extensive experimental results demonstrate that RPI-GGCN can provide an efficient, accurate, and stable RPI prediction method.

Delta-band Activity Underlies Referential Meaning Representation during Pronoun Resolution

Human language offers a variety of ways to create meaning, one of which is referring to entities, objects, or events in the world. One such meaning maker is understanding to whom or to what a pronoun in a discourse refers to. To understand a pronoun, the brain must access matching entities or concepts that have been encoded in memory from previous linguistic context. Models of language processing propose that internally stored linguistic concepts, accessed via exogenous cues such as phonological input of a word, are represented as (a)synchronous activities across a population of neurons active at specific frequency bands. Converging evidence suggests that delta band activity (1-3 Hz) is involved in temporal and representational integration during sentence processing. Moreover, recent advances in the neurobiology of memory suggest that recollection engages neural dynamics similar to those which occurred during memory encoding. Integrating from these two research lines, we here tested the hypothesis that neural dynamic patterns, especially in delta frequency range, underlying referential meaning representation, would be reinstated during pronoun resolution. By leveraging neural decoding techniques (i.e., representational similarity analysis) on a magnetoencephalogram data set acquired during a naturalistic story-listening task, we provide evidence that delta-band activity underlies referential meaning representation. Our findings suggest that, during spoken language comprehension, endogenous linguistic representations such as referential concepts may be proactively retrieved and represented via activation of their underlying dynamic neural patterns.

Delayed onset facilitates subsequent retrieval of words during language comprehension

Prior research has shown that during language comprehension, memory representations associated with premodified words (e.g., the injured and dangerous bear) are retrieved faster from memory than those associated with unmodified words (e.g., the bear). Current explanations attribute this effect to the semantic richness of modified words. However, it is not clear whether the presence of modifying words are in fact necessary for a retrieval benefit. Premodifiers necessarily delay the onset of the target word (i.e., bear), and temporal delays may heighten attention to upcoming stimuli, and/or strengthen encoding by producing free time during encoding, facilitating subsequent retrieval. We therefore examined whether a simple delay in the onset of the target can produce a retrieval benefit. Our results show that delayed onset facilitates the subsequent retrieval of target words in the absence of any modifying information. These results lend support to models of language comprehension according to which delays may enhance attention to upcoming words, and also to models of working memory based on which free time replenishes encoding resources, strengthening the memory trace of encoded information and facilitating its retrieval at a subsequent point. Our results also contribute to current memory-based theories of sentence comprehension by showing that retrieval from memory may be affected by nonlinguistic factors such as delay-induced attention enhancement, or free time during encoding.

The effect of time on lexical and syntactic processing in aphasia

Processing deficits at the lexical level, such as delayed and reduced lexical activation, have been theorized as the source of breakdowns in syntactic operations and thus contribute to sentence comprehension deficits in individuals with aphasia (IWA). In the current study, we investigate the relationship between lexical and syntactic processing in object-relative sentences using eye-tracking while listening in IWA. We explore whether manipulating the time available to process a critical lexical item (the direct-object noun) when it is initially heard in a sentence has an immediate effect on lexical access as well as a downstream effect on syntactic processing. To achieve this aim, we use novel temporal manipulations to provide additional time for lexical processing to occur. In addition to exploring these temporal effects in IWA, we also seek to understand the effect that additional time has on sentence processing in neurotypical age-matched adults (AMC). We predict that the temporal manipulations designed to provide increased processing time for critical lexical items will 1) enhance lexical processing of the target noun, 2) facilitate syntactic integration, and 3) improve sentence comprehension for both IWA and AMC. We demonstrate that strengthening lexical processing via the addition of time can affect lexical processing and facilitate syntactic retrieval of the target noun and lead to enhanced interference resolution in both unimpaired and impaired systems. In aphasia, additional time can mitigate impairments in spreading activation thereby improving lexical access and reducing interference during downstream dependency linking. However, individuals with aphasia may require longer additions of time to fully realize these benefits.

Can the resource reduction hypothesis explain sentence processing in aphasia? A visual world study in German

Resource limitation has often been invoked as a key driver of sentence comprehension difficulty, in both theories of language-unimpaired and language-impaired populations. In the field of aphasia, one such influential theory is Caplan's resource reduction hypothesis (RRH). In this large investigation of online processing in aphasia in German, we evaluated three key predictions of the RRH in 21 individuals with aphasia and 22 control pparticipants. Measures of online processing were obtained by combining a sentence-picture matching task with the visual world paradigm. Four sentence types were used to investigate the generality of the findings, and two test phases were used to investigate RRH's predictions regarding variability in aphasia. The processing patterns were consistent with two of the three predictions of the RRH. Overall, our investigation shows that the RRH can account for important aspects of sentence processing in aphasia.

Estimating the True Cost of Garden Pathing: A Computational Model of Latent Cognitive Processes

What is the processing cost of being garden-pathed by a temporary syntactic ambiguity? We argue that comparing average reading times in garden-path versus non-garden-path sentences is not enough to answer this question. Trial-level contaminants such as inattention, the fact that garden pathing may occur non-deterministically in the ambiguous condition, and "triage" (rejecting the sentence without reanalysis; Fodor & Inoue, 2000) lead to systematic underestimates of the true cost of garden pathing. Furthermore, the "pure" garden-path effect due to encountering an unexpected word needs to be separated from the additional cost of syntactic reanalysis. To get more realistic estimates for the individual processing costs of garden pathing and syntactic reanalysis, we implement a novel computational model that includes trial-level contaminants as probabilistically occurring latent cognitive processes. The model shows a good predictive fit to existing reading time and judgment data. Furthermore, the latent-process approach captures differences between noun phrase/zero complement (NP/Z) garden-path sentences and semantically biased reduced relative clause (RRC) garden-path sentences: The NP/Z garden path occurs nearly deterministically but can be mostly eliminated by adding a comma. By contrast, the RRC garden path occurs with a lower probability, but disambiguation via semantic plausibility is not always effective.

Individual Differences in Cue Weighting in Sentence Comprehension: An Evaluation Using Approximate Bayesian Computation

Cue-based retrieval theories of sentence processing assume that syntactic dependencies are resolved through a content-addressable search process. An important recent claim is that in certain dependency types, the retrieval cues are weighted such that one cue dominates. This cue-weighting proposal aims to explain the observed average behavior, but here we show that there is systematic individual-level variation in cue weighting. Using the Lewis and Vasishth cue-based retrieval model, we estimated individual-level parameters for reading speed and cue weighting using 13 published datasets; hierarchical approximate Bayesian computation (ABC) was used to estimate the parameters. The modeling reveals a nuanced picture of cue weighting: we find support for the idea that some participants weight cues differentially, but not all participants do. Only fast readers tend to have the predicted higher weighting for structural cues, suggesting that reading proficiency (approximated here by reading speed) might be associated with cue weighting. A broader achievement of the work is to demonstrate how individual differences can be investigated in computational models of sentence processing without compromising the complexity of the model.

Semantic Attraction in Sentence Comprehension

Agreement attraction is a cross-linguistic phenomenon where a verb occasionally agrees not with its subject, as required by grammar, but instead with an unrelated noun ("The key to the cabinets were…"). Despite the clear violation of grammatical rules, comprehenders often rate these sentences as acceptable. Contenders for explaining agreement attraction fall into two broad classes: Morphosyntactic accounts specifically designed to explain agreement attraction, and more general sentence processing models, such as the Lewis and Vasishth model, which explain attraction as a consequence of how linguistic structure is stored and accessed in content-addressable memory. In the present research, we disambiguate between these two classes by testing a surprising prediction made by the Lewis and Vasishth model but not by the morphosyntactic accounts, namely, that attraction should not be limited to morphosyntax, but that semantic features of unrelated nouns equally induce attraction. A recent study by Cunnings and Sturt provided initial evidence that this may be the case. Here, we report three single-trial experiments in English that compared semantic and agreement attraction and tested whether and how the two interact. All three experiments showed strong semantically induced attraction effects closely mirroring agreement attraction effects. We complement these results with computational simulations which confirmed that the Lewis and Vasishth model can faithfully reproduce the observed results. In sum, our findings suggest that attraction is a more general phenomenon than is commonly believed, and therefore favor more general sentence processing models, such as the Lewis and Vasishth model.

Variability in sentence comprehension in aphasia in German

An important aspect of aphasia is the observation of behavioral variability between and within individual participants. Our study addresses variability in sentence comprehension in German, by testing 21 individuals with aphasia and a control group and involving (a) several constructions (declarative sentences, relative clauses and control structures with an overt pronoun or PRO), (b) three response tasks (object manipulation, sentence-picture matching with/without self-paced listening), and (c) two test phases (to investigate test-retest performance). With this systematic, large-scale study we gained insights into variability in sentence comprehension. We found that the size of syntactic effects varied both in aphasia and in control participants. Whereas variability in control participants led to systematic changes, variability in individuals with aphasia was unsystematic across test phases or response tasks. The persistent occurrence of canonicity and interference effects across response tasks and test phases, however, shows that the performance is systematically influenced by syntactic complexity.