The Neural Time Course of Semantic Ambiguity Resolution in Speech Comprehension

How do surrogates make treatment decisions for patients with dementia: An experimental survey study

Despite the growing need for surrogate decision-making for older adults, little is known about how surrogates make decisions and whether advance directives would change decision-making. We conducted a nationally representative experimental survey that cross-randomized cognitive impairment, gender, and characteristics of advance care planning among hospitalized older adults through a series of vignettes. Our study yielded three main findings: first, respondents were much less likely to recommend life-sustaining treatments for patients with dementia, especially after personal exposure. Second, respondents were more likely to ignore patient preferences for life-extending treatment when the patient had dementia, and choose unwanted life-extending treatments for patients without dementia. Third, in scenarios where the patient's wishes were unclear, respondents were more likely to choose treatments that matched their own preferences. These findings underscore the need for improved communication and decision-making processes for patients with cognitive impairment and highlight the importance of choosing a surrogate decision-maker with similar treatment preferences.

Brain representations of lexical ambiguity: Disentangling homonymy, polysemy, and their meanings

In human languages, it is a common phenomenon for a single word to have multiple meanings. This study used fMRI to investigate how the brain processed different types of lexical ambiguity, and how it differentiated the meanings of ambiguous words. We focused on homonyms and polysemy that differed in the relatedness among multiple meanings. Participants (N = 35) performed a prime-target semantic relatedness task, where a specific meaning of an ambiguous word was primed. Results showed that homonyms elicited greater activation in bilateral dorsal prefrontal and posterior parietal cortices than polysemous words, suggesting that these regions may be more engaged in cognitive control when the meanings of ambiguous words are unrelated. Multivariate pattern analysis further revealed that meanings of homonyms with different syntactic categories were represented differently in the frontal and temporal cortices. The findings highlighted the importance of semantic relations and grammatical factors in the brain's representation of lexical ambiguities.

Inter- and intra- hemispheric interactions in reading ambiguous words

The present study investigated how the brain processes words with multiple meanings. Specifically, we examined the inter- and intra-hemispheric connectivity of unambiguous words compared to two types of ambiguous words: homophonic homographs, which have multiple meanings mapped to a single phonological representation and orthography, and heterophonic homographs, which have multiple meanings mapped to different phonological representations but the same orthography. Using a semantic relatedness judgment task and effective connectivity analysis via Dynamic Causal Modeling (DCM) on previously published fMRI data (Bitan et al., 2017), we found that the two hemispheres compete in orthographic processing during the reading of unambiguous words. For heterophonic homographs, we observed increased connectivity within the left hemisphere, highlighting the importance of top-down re-activation of orthographic representations by phonological ones for considering alternative meanings. For homophonic homographs, we found a flow of information from the left to the right hemisphere and from the right to the left, indicating that the brain retrieves different meanings using different pathways. These findings provide novel insights into the complex mechanisms involved in language processing and shed light on the different communication patterns within and between hemispheres during the processing of ambiguous and unambiguous words.

Measuring semantic memory using associative and dissociative retrieval tasks

Recent theoretical advances highlighted the need for novel means of assessing semantic cognition. Here, we introduce the associative-dissociative retrieval task (ADT), positing a novel way to test inhibitory control over semantic memory retrieval by contrasting the efficacy of associative (automatic) and dissociative (controlled) retrieval on a standard set of verbal stimuli. All ADT measures achieved excellent reliability, homogeneity, and short-term temporal stability. Moreover, in-depth stimulus level analyses showed that the associative retrieval is easier for words evoking few but strong associates, yet such propensity hampers the inhibition. Finally, we provided critical support for the construct validity of the ADT measures, demonstrating reliable correlations with domain-specific measures of semantic memory functioning (semantic fluency and associative combination) but negligible correlations with domain-general capacities (processing speed and working memory). Together, we show that ADT provides simple yet potent and psychometrically sound measures of semantic memory retrieval and offers noteworthy advantages over the currently available assessment methods.

Studying Individual Differences in Language Comprehension: The Challenges of Item-Level Variability and Well-Matched Control Conditions

Translating experimental tasks that were designed to investigate differences between conditions at the group-level into valid and reliable instruments to measure individual differences in cognitive skills is challenging (Hedge et al., 2018; Rouder et al., 2019; Rouder & Haaf, 2019). For psycholinguists, the additional complexities associated with selecting or constructing language stimuli, and the need for appropriate well-matched baseline conditions make this endeavour particularly complex. In a typical experiment, a process-of-interest (e.g. ambiguity resolution) is targeted by contrasting performance in an experimental condition with performance in a well-matched control condition. In many cases, careful between-condition matching precludes the same participant from encountering all stimulus items. Unfortunately, solutions that work for group-level research (e.g. constructing counterbalanced experiment versions) are inappropriate for individual-differences designs. As a case study, we report an ambiguity resolution experiment that illustrates the steps that researchers can take to address this issue and assess whether their measurement instrument is both valid and reliable. On the basis of our findings, we caution against the widespread approach of using datasets from group-level studies to also answer important questions about individual differences.

The words that little by little revealed everything: Neural response to lexical-semantic content during narrative comprehension

The ease with which narratives are understood belies the complexity of the information being conveyed and the cognitive processes that support comprehension. The meanings of the words must be rapidly accessed and integrated with the reader's mental representation of the overarching, unfolding scenario. A broad, bilateral brain network is engaged by this process, but it is not clear how words that vary on specific semantic dimensions, such as ambiguity, emotion, or socialness, engage the semantic, semantic control, or social cognition systems. In the present study, data from 48 participants who listened to The Little Prince audiobook during MRI scanning were selected from the Le Petit Prince dataset. The lexical and semantic content within the narrative was quantified from the transcript words with factor scores capturing Word Length, Semantic Flexibility, Emotional Strength, and Social Impact. These scores, along with word quantity variables, were used to investigate where these predictors co-vary with activation across the brain. In contrast to studies of isolated word processing, large networks were found to co-vary with the lexical and semantic content within the narrative. An increase in semantic content engaged the ventral portion of ventrolateral ATL, consistent with its role as a semantic hub. Decreased semantic content engaged temporal pole and inferior parietal lobule, which may reflect semantic integration. The semantic control network was engaged by words with low Semantic Flexibility, perhaps due to the demand required to process infrequent, less semantically diverse language. Activation in ATL co-varied with an increase in Social Impact, which is consistent with the claim that social knowledge is housed within the neural architecture of the semantic system. These results suggest that current models of language processing may present an impoverished estimate of the neural systems that coordinate to support narrative comprehension, and, by extension, real-world language processing.

A deep hierarchy of predictions enables online meaning extraction in a computational model of human speech comprehension

Understanding speech requires mapping fleeting and often ambiguous soundwaves to meaning. While humans are known to exploit their capacity to contextualize to facilitate this process, how internal knowledge is deployed online remains an open question. Here, we present a model that extracts multiple levels of information from continuous speech online. The model applies linguistic and nonlinguistic knowledge to speech processing, by periodically generating top-down predictions and incorporating bottom-up incoming evidence in a nested temporal hierarchy. We show that a nonlinguistic context level provides semantic predictions informed by sensory inputs, which are crucial for disambiguating among multiple meanings of the same word. The explicit knowledge hierarchy of the model enables a more holistic account of the neurophysiological responses to speech compared to using lexical predictions generated by a neural network language model (GPT-2). We also show that hierarchical predictions reduce peripheral processing via minimizing uncertainty and prediction error. With this proof-of-concept model, we demonstrate that the deployment of hierarchical predictions is a possible strategy for the brain to dynamically utilize structured knowledge and make sense of the speech input.

Listening Effort Is Not the Same as Speech Intelligibility Score

Listening effort is a valuable and important notion to measure because it is among the primary complaints of people with hearing loss. It is tempting and intuitive to accept speech intelligibility scores as a proxy for listening effort, but this link is likely oversimplified and lacks actionable explanatory power. This study was conducted to explain the mechanisms of listening effort that are not captured by intelligibility scores, using sentence-repetition tasks where specific kinds of mistakes were prospectively planned or analyzed retrospectively. Effort measured as changes in pupil size among 20 listeners with normal hearing and 19 listeners with cochlear implants. Experiment 1 demonstrates that mental correction of misperceived words increases effort even when responses are correct. Experiment 2 shows that for incorrect responses, listening effort is not a function of the proportion of words correct but is rather driven by the types of errors, position of errors within a sentence, and the need to resolve ambiguity, reflecting how easily the listener can make sense of a perception. A simple taxonomy of error types is provided that is both intuitive and consistent with data from these two experiments. The diversity of errors in these experiments implies that speech perception tasks can be designed prospectively to elicit the mistakes that are more closely linked with effort. Although mental corrective action and number of mistakes can scale together in many experiments, it is possible to dissociate them to advance toward a more explanatory (rather than correlational) account of listening effort.

What has social neuroscience learned from hyperscanning studies of spoken communication? A systematic review

A growing body of literature examining the neurocognitive processes of interpersonal linguistic interaction indicates the emergence of neural alignment as participants engage in oral communication. However, questions have arisen whether the study results can be interpreted beyond observations of cortical functionality and extended to the mutual understanding between communicators. This review presents evidence from electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) hyperscanning studies of interbrain synchrony (IBS) in which participants communicated via spoken language. The studies are classified into: knowledge sharing; turn-taking speech co-ordination; cooperation, problem-solving and creativity; and naturalistic discussion paradigms according to the type of interaction specified in each study. Alignment predominantly occurred in the frontal and temporo-parietal areas, which may reflect activation of the mirror and mentalizing systems. We argue that the literature presents a significant contribution to advancing our understanding of IBS and mutual understanding between communicators. We end with suggestions for future research, including analytical approaches and experimental conditions and hypothesize that brain-inspired neural networks are promising techniques for better understanding of IBS through hyperscanning.