scholarly journals A computational evaluation of two models of retrieval processes in sentence processing in aphasia

2020 ◽  
Author(s):  
Paula Lissón ◽  
Dorothea Pregla ◽  
Bruno Nicenboim ◽  
Dario Paape ◽  
Mick L. van het Nederend ◽  
...  

Can sentence comprehension impairments in aphasia be explained by difficulties arising from dependency completion processes in parsing? Two distinct models of dependencycompletion difficulty are investigated, the Lewis and Vasishth (2005) activation-based model, and the direct-access model (McElree, 2000). These models’ predictive performance is compared using data from individuals with aphasia (IWAs) and control participants. The data are from a self-paced listening task involving subject and object relative clauses. The relative predictive performance of the models is evaluated using k-fold cross validation. For both IWAs and controls, the activation model furnishes a somewhat better quantitativefit to the data than the direct-access model. Model comparison using Bayes factors shows that, assuming an activation-based model, intermittent deficiencies may be the best explanation for the cause of impairments in IWAs. This is the first computational evaluation of different models of dependency completion using data from impaired andunimpaired individuals. This evaluation develops a systematic approach that can be used to quantitatively compare the predictions of competing models of language processing.

2021 ◽  
Author(s):  
Paula Lissón ◽  
Dario Paape ◽  
Dorothea Pregla ◽  
Nicole Stadie ◽  
Frank Burchert ◽  
...  

Sentence comprehension requires the listener to link incoming words with short-term memory representations in order to build linguistic dependencies. The cue-based retrieval theory of sentence processing predicts that the retrieval of these memory representations is affected by similarity-based interference. We present the first large-scale computational evaluation of interference effects in two models of sentence processing – the activation-based model, and a modification of the direct-access model – in individuals with aphasia (IWA) and control participants in German. The parameters of the models are linked to prominent theories of processing deficits in aphasia, and the models are tested against two linguistic constructions in German: Pronoun resolution and relative clauses. The data come from a visual-world eye-tracking experiment combined with a sentence-picture matching task. The results show that both control participants and IWA are susceptible to retrieval interference, and that a combination of theoretical explanations (intermittent deficiencies, slow syntax, and resource reduction) can explain IWA’s deficits in sentence processing. Model comparisons reveal that both models have a similar predictive performance in pronoun resolution, but the activation-based model outperforms the direct-access model in relative clauses.


2019 ◽  
Author(s):  
Shravan Vasishth ◽  
Bruno Nicenboim ◽  
Felix Engelmann ◽  
Frank Burchert

Sentence comprehension requires that the comprehender work out who did what to whom. This process has been characterized as retrieval from memory. This review summarizes the quantitative predictions and empirical coverage of the two existing computational models of retrieval, and shows how the predictive performance of these two competing models can be tested against a benchmark data-set. We also show how computational modeling can help us better understand sources of variability in both unimpaired and impaired sentence comprehension.


2021 ◽  
Author(s):  
Paula Lissón ◽  
Dorothea Pregla ◽  
Dario Paape ◽  
Frank Burchert ◽  
Nicole Stadie ◽  
...  

Several researchers have argued that sentence comprehension is mediated via a content addressable retrieval mechanism that allows fast and direct access to memory items. Initially failed retrievals can result in backtracking, which leads to correct retrieval. We present an augmented version of the direct access model that allows backtracking to fail. Based on self-paced listening data from individuals with aphasia, we compare the augmented model to the base model without backtracking failures. The augmented model shows quantitatively similar performance to the base model, but only the augmented model can account for slow incorrect responses. We argue that the modified direct-access model is theoretically better suited to fit data from impaired populations.


2021 ◽  
Author(s):  
Paula Lissón ◽  
Dorothea Pregla ◽  
Dario Paape ◽  
Frank Burchert ◽  
Nicole Stadie ◽  
...  

2021 ◽  
Author(s):  
Shravan Vasishth ◽  
Felix Engelmann

Sentence comprehension - the way we process and understand spoken and written language - is a central and important area of research within psycholinguistics. This book explores the contribution of computational linguistics to the field, showing how computational models of sentence processing can help scientists in their investigation of human cognitive processes. It presents the leading computational model of retrieval processes in sentence processing, the Lewis and Vasishth cue-based retrieval mode, and develops a principled methodology for parameter estimation and model comparison/evaluation using benchmark data, to enable researchers to test their own models of retrieval against the present model. It also provides readers with an overview of the last 20 years of research on the topic of retrieval processes in sentence comprehension, along with source code that allows researchers to extend the model and carry out new research. Comprehensive in its scope, this book is essential reading for researchers in cognitive science.


Author(s):  
Fernanda Ferreira ◽  
James Nye

Today, the modular view of sentence processing is unpopular, but the arguments against modularity are not as strong as this apparent consensus would suggest. Almost all experimental investigations of modularity have focused on properties pertaining to information encapsulation, and most of those studies have evaluated just one specific modular architecture. A review of these studies of sentence comprehension suggests that the evidence against information encapsulation is really evidence against that one architecture only, and a whole range of other possible modular architectures remain untested. Although psycholinguistic work has largely ignored the modularity claims relating to shallow outputs, new findings from studies to test “good enough” language processing suggest that the output of the language processing module can be characterized as shallow or minimal. Perhaps, then, the modularity hypothesis was prematurely rejected. Evidence for shallow outputs provides intriguing new support for the idea that sentence processing is indeed modular.


Entropy ◽  
2020 ◽  
Vol 22 (4) ◽  
pp. 446
Author(s):  
Yair Lakretz ◽  
Stanislas Dehaene ◽  
Jean-Rémi King

Sentence comprehension requires inferring, from a sequence of words, the structure of syntactic relationships that bind these words into a semantic representation. Our limited ability to build some specific syntactic structures, such as nested center-embedded clauses (e.g., “The dog that the cat that the mouse bit chased ran away”), suggests a striking capacity limitation of sentence processing, and thus offers a window to understand how the human brain processes sentences. Here, we review the main hypotheses proposed in psycholinguistics to explain such capacity limitation. We then introduce an alternative approach, derived from our recent work on artificial neural networks optimized for language modeling, and predict that capacity limitation derives from the emergence of sparse and feature-specific syntactic units. Unlike psycholinguistic theories, our neural network-based framework provides precise capacity-limit predictions without making any a priori assumptions about the form of the grammar or parser. Finally, we discuss how our framework may clarify the mechanistic underpinning of language processing and its limitations in the human brain.


2009 ◽  
Vol 21 (12) ◽  
pp. 2434-2444 ◽  
Author(s):  
David January ◽  
John C. Trueswell ◽  
Sharon L. Thompson-Schill

For over a century, a link between left prefrontal cortex and language processing has been accepted, yet the precise characterization of this link remains elusive. Recent advances in both the study of sentence processing and the neuroscientific study of frontal lobe function suggest an intriguing possibility: The demands to resolve competition between incompatible characterizations of a linguistic stimulus may recruit top–down cognitive control processes mediated by prefrontal cortex. We use functional magnetic resonance imaging to test the hypothesis that individuals use shared prefrontal neural circuitry during two very different tasks—color identification under Stroop conflict and sentence comprehension under conditions of syntactic ambiguity—both of which putatively rely on cognitive control processes. We report the first demonstration of within-subject overlap in neural responses to syntactic and nonsyntactic conflict. These findings serve to clarify the role of Broca's area in, and the neural and psychological organization of, the language processing system.


2021 ◽  
Vol 12 ◽  
Author(s):  
Veena D. Dwivedi ◽  
Janahan Selvanayagam

We examined whether the N400 Event-Related Potential (ERP) component would be modulated by dispositional affect during sentence processing. In this study, 33 participants read sentences manipulated by direct object type (congruent vs. incongruent) and object determiner type (definite vs. demonstrative). We were particularly interested in sentences of the form: (i) The connoisseur tasted thewineon the tour vs. (ii) The connoisseur tasted the #roof… We expected that processing incongruent direct objects (#roof) vs. congruent objects (wine) would elicit N400 effects. Previous ERP language experiments have shown that participants in (induced) positive and negative moods were differentially sensitive to semantic anomaly, resulting in different N400 effects. Presently, we ask whether individual dispositional affect scores (as measured by the Positive and Negative Affect Schedule; PANAS) would modulate N400 effects as shown previously. Namely, previous results showed larger N400 effects associated with happy moods and attenuated amplitudes associated with sad moods. Results revealed significant N400 effects, driven by the #roof vs. the wine, where larger amplitude differences were found for individuals showing smaller negative affect (NA) scores, thus partially replicating previous findings. We discuss our results in terms of theories of local (lexical) inhibition, such that low NA promotes stronger lexico-semantic links in sentences. Finally, our results support accounts of language processing that include social and biological characteristics of individuals during real-time sentence comprehension.


2019 ◽  
Author(s):  
Evgeniia Diachek ◽  
Idan Blank ◽  
Matthew Siegelman ◽  
Josef Affourtit ◽  
Evelina Fedorenko

AbstractAside from the language-selective left-lateralized fronto-temporal network, language comprehension sometimes additionally recruits a domain-general bilateral fronto-parietal network implicated in executive functions: the multiple demand (MD) network. However, the nature of the MD network’s contributions to language comprehension remains debated. To illuminate the role of this network in language processing, we conducted a large-scale fMRI investigation using data from 30 diverse word and sentence comprehension experiments (481 unique participants, 678 scanning sessions). In line with prior findings, the MD network was active during many language tasks. Moreover, similar to the language-selective network, which is robustly lateralized to the left hemisphere, these responses were stronger in the left-hemisphere MD regions. However, in stark contrast with the language-selective network, the MD network responded more strongly (i) to lists of unconnected words than to sentences, and critically, (ii) in paradigms with an explicit task compared to passive comprehension paradigms. In fact, many passive comprehension tasks failed to elicit a response above the fixation baseline in the MD network, in contrast to strong responses in the language-selective network. In tandem, these results argue against a role for the MD network in core aspects of sentence comprehension like inhibiting irrelevant meanings or parses, keeping intermediate representations active in working memory, or predicting upcoming words or structures. These results align with recent evidence of relatively poor tracking of the linguistic signal by the MD regions during naturalistic comprehension, and instead suggest that the MD network’s engagement during language processing likely reflects effort associated with extraneous task demands.Significance StatementDomain-general executive processes, like working memory and cognitive control, have long been implicated in language comprehension, including in neuroimaging studies that have reported activation in domain-general multiple demand (MD) regions for linguistic manipulations. However, much prior evidence has come from paradigms where language interpretation is accompanied by extraneous tasks. Using a large fMRI dataset (30 experiments/481 participants/678 sessions), we demonstrate that MD regions are engaged during language comprehension in the presence of task demands, but not during passive reading/listening—conditions that strongly activate the fronto-temporal language network. These results present a fundamental challenge to proposals whereby linguistic computations, like inhibiting irrelevant meanings, keeping representations active in working memory, or predicting upcoming elements, draw on domain-general executive resources.


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