Biology subjects

Mahowald, K.

Publications and source records attributed to Mahowald, K..

4 recordsLinked to original sources

bioRxiv2023

Functional characterization of the language network of polyglots and hyperpolyglots with precision fMRI

How do polyglots--individuals who speak five or more languages--process their languages, and what can this population tell us about the language system? Using fMRI, we identified the language network in each of 34 polyglots (including 16 hyperpolyglots with knowledge of 10+ languages) and examined its response to the native language, non-native languages of varying proficiency, and unfamiliar languages. All language conditions engaged all areas of the language network relative to a control condition. Languages that participants rated as higher-proficiency elicited stronger responses, except for the native language, which elicited a similar or lower response than a non-native language of similar proficiency. Furthermore, unfamiliar languages that were typologically related to the participants high-to-moderate-proficiency languages elicited a stronger response than unfamiliar unrelated languages. The results suggest that the language networks response magnitude scales with the degree of engagement of linguistic computations (e.g., related to lexical access and syntactic-structure building). We also replicated a prior finding of weaker responses to native language in polyglots than non-polyglot bilinguals. These results contribute to our understanding of how multiple languages co-exist within a single brain and provide new evidence that the language network responds more strongly to stimuli that more fully engage linguistic computations.

neuroscience↗

bioRxiv2023

How random is the review outcome? A systematic study of the impact of external factors on eLife peer review

The advance of science rests on a robust peer review process. However whether or not a paper is accepted can depend on random external factors--e.g. the timing of the submission, the matching of editors and reviewers--that are beyond the quality of the work. This article systematically investigates the impact of these random factors independent of the papers quality on peer review outcomes in a major biomedical journal, eLife. We analyzed all of the submissions to eLife between 2016 to 2018, with 23,190 total submissions. We examined the effects of random factors at each decision point in the review process, from the gatekeeping senior editors who may desk-reject papers to review editors and reviewers who recommend the final outcome. Our results suggest that the peer-review process in eLife is robust overall and that random external factors have relatively little quantifiable bias.

bioinformatics↗

bioRxiv2021

High-level language brain regions are sensitive to sub-lexical regularities

A network of left frontal and temporal brain regions supports high-level language processing-- including the processing of word meanings, as well as word-combinatorial processing--across presentation modalities. This core language network has been argued to store our knowledge of words and constructions as well as constraints on how those combine to form sentences. However, our linguistic knowledge additionally includes information about sounds (phonemes) and how they combine to form clusters, syllables, and words. Is this knowledge of phoneme combinatorics also represented in these language regions? Across five fMRI experiments, we investigated the sensitivity of high-level language processing brain regions to sub-lexical linguistic sound patterns by examining responses to diverse nonwords--sequences of sounds/letters that do not constitute real words (e.g., punes, silory, flope). We establish robust responses in the language network to visually (Experiment 1a, n=605) and auditorily (Experiments 1b, n=12, and 1c, n=13) presented nonwords relative to baseline. In Experiment 2 (n=16), we find stronger responses to nonwords that obey the phoneme-combinatorial constraints of English. Finally, in Experiment 3 (n=14) and a post-hoc analysis of Experiment 2, we provide suggestive evidence that the responses in Experiments 1 and 2 are not due to the activation of real words that share some phonology with the nonwords. The results suggest that knowledge of phoneme combinatorics and representations of sub-lexical linguistic sound patterns are stored within the same fronto-temporal network that stores higher-level linguistic knowledge and supports word and sentence comprehension.

neuroscience↗

bioRxiv2017

A robust dissociation among the language, multiple demand, and default mode networks: evidence from inter-region correlations in effect size

Complex cognitive processes, including language, rely on multiple mental operations that are carried out by several large-scale functional networks in the frontal, temporal, and parietal association cortices of the human brain. The central division of cognitive labor is between two fronto-parietal bilateral networks: (a) the multiple demand (MD) network, which supports executive processes, such as working memory and cognitive control, and is engaged by diverse task domains, including language, especially when comprehension gets difficult; and (b) the default mode network (DMN), which supports introspective processes, such as mind wandering, and is active when we are not engaged in processing external stimuli. These two networks are strongly dissociated in both their functional profiles and their patterns of activity fluctuations during naturalistic cognition. Here, we focus on the functional relationship between these two networks and a third network: (c) the fronto-temporal left-lateralized \"core\" language network, which is selectively recruited by linguistic processing. Is the language network distinct and dissociated from both the MD network and the DMN, or is it synchronized and integrated with one or both of them? Recent work has provided evidence for a dissociation between the language network and the MD network. However, the relationship between the language network and the DMN is less clear, with some evidence for coordinated activity patterns and similar response profiles, perhaps due to the role of both in semantic processing. Here we use a novel fMRI approach to examine the relationship among the three networks: we measure the strength of activations in different language, MD, and DMN regions to functional contrasts typically used to identify each network, and then test which regions co-vary in their contrast effect sizes across 60 individuals. We find that effect sizes correlate strongly within each network (e.g., one language region and another language region, or one DMN region and another DMN region), but show little or no correlation for region pairs across networks (e.g., a language region and a DMN region). Thus, we replicate the language/MD network dissociation discovered previously with other methods, and also show that the language network is robustly dissociated from the DMN, overall suggesting that these three networks support distinct computations and contribute to high-level cognition in different ways. Inter-individual differences in effect sizes therefore do not simply reflect general differences in vascularization or attention, but exhibit sensitivity to the functional architecture of the brain. The strength of activation in each network can thus be probed separately in studies that attempt to link neural variability to behavioral or genetic variability.

neuroscience↗