Biology subjects

Chacon, D. A.

Publications and source records attributed to Chacon, D. A..

5 recordsLinked to original sources

bioRxiv2024

Quick, Don't Move!: Wh-Movement and Wh-In-Situ Structures in Rapid Parallel Reading - EEG studies in English, Urdu, and Mandarin Chinese

A fundamental question in the cognitive neuroscience of language is how grammatical representations are reflected in the organization and activity of the brain. This is challenging in part because superficial differences between languages, e.g., word order, exert different demands on the memory systems that process these structures. Here, we present an electroencephalography (EEG) study to investigate the brains responses to wh-constructions in English, Urdu, and Mandarin Chinese. In addition to the different word orders, writing systems, and morphological typologies of the 3 languages, these languages diverge with regard to how wh-constructions are formed: English requires filler-gap dependencies for wh-objects, whereas Urdu and Mandarin Chinese do not. We use a rapid parallel reading task, in which short sentences are displayed in parallel for 200ms to mitigate the different demands placed on memory systems. We show that neural responses distinguish wh-object constructions from their controls in midline anterior (Urdu, Mandarin Chinese) and right posterior sensors (English, Mandarin Chinese), from 200-400ms (English, Mandarin Chinese) and 500-800ms (English, Urdu). Although there is no detectable uniform, language-invariant response to wh-constructions across languages, there are a number of shared features in the evoked response between any pair of languages, i.e., wh-in-situ constructions generate an evoked response in midline anterior sensors. Moreover, behavioral evidence shows a robust cross-language cost of processing wh-object constructions, regardless of their surface form. This demonstrates that readers of diverse languages can process some grammatical information in a short 200ms fixation, and that the RPVP methodology may enable new ways of linking cognitive neuroscience of language to comparative syntax, i.e., the systematic description of similarities and differences between grammatical structures.

neuroscience↗

bioRxiv2024

Rapid visual form-based processing of (some) grammatical features in parallel reading: An EEG study in English

Theories of language processing - and typical experimental methodologies - emphasize the word-by-word processing of sentences. This paradigm is good for approximating speech or careful text reading, but arguably, not for the common, cursory glances used while reading short sentences (e.g., cellphone notifications, social media posts). How can we interpret a sentence in a single glance? In an electroencephalography (EEG) study, brain responses to grammatical sentences (the dogs chase a ball) presented for 200ms diverged from non-lexical consonant strings (thj rjxb zkhtb w lhct) [~]160ms post-sentence onset and from scrambled constructions (a dogs chase ball the) [~]250ms post-sentence onset, demonstrating - at different time points - rapid recognition and cursory analysis of linguistic stimuli. In the grammatical sentences, unigram probability correlated with EEG data [~]150-300ms post-sentence onset, and probability of the word given its context estimated by BERT correlated with EEG data after [~]700-800ms. EEG responses did not diverge between grammatical sentences and their counterparts with ungrammatical agreement (the dogs chases a ball), although EEG responses did diverge for plural vs. singular morphology at [~]200ms. These results suggest that at-a-glance reading is possible, based on coactivation of individual lexical items, morphological structures, and constituent structure at [~]200-300ms, but that words are not integrated into a coherent syntactic/semantic analysis, as evidenced by the substantially later responses to BERT probability and the absence of sensitivity to agreement errors.

neuroscience↗

bioRxiv2024

Same Sentences, Different Grammars, Different Brain Responses: An MEG study on Case and Agreement Encoding in Hindi and Nepali Split-Ergative Structures

At first glance, the brains language network appears to be universal, but languages clearly differ. How does the brain adapt to the specific details of individual grammatical systems? Here, we present an MEG study on case and agreement in Hindi and Nepali. Both languages use split-ergative case systems. However, these systems interact with verb agreement differently - in Hindi, case features conspire to determine which noun phrase (NP) the verb agrees with (subject, object, or neither), but in Nepali the verb always agrees with the subject NP. We found that left inferior frontal and left anterior temporal regions are sensitive to case features in both languages. Across case configurations, these same brain areas in Hindi participants show different patterns of activity for sentences that require masculine vs. feminine marking on the verb, before the comprehenders encounter it. Additionally, the left temporoparietal junction in Hindi shows different activity for subject and object agreement configurations. Both findings are not observed in Nepali participants. We suggest that this brain response demonstrates a unique-to-Hindi selection of an agreement controller and pre-encoding of the verbs morphological features. This shows that brain activity reflects psycholinguistic processes that are intimately tied to grammatical features. HighlightsO_LIThe left inferior frontal lobe and the left anterior temporal lobe distinguish accusative objects versus bare object NPs in Hindi and Nepali, and pre-emptively encode gender agreement features in Hindi. C_LIO_LIThe left inferior parietal lobe shows a differential sensitivity to object-agreement and subject-agreement constructions in Hindi that is absent in Nepali C_LIO_LIMEG can reveal differences in neural activity that reflect specific requirements of different grammatical systems C_LI

neuroscience↗

bioRxiv2023

How long is long? Word length effects in reading correspond to minimal graphemic units: An MEG study in Bangla

This paper presents a magnetoencephalography (MEG) study on reading in Bangla, an east Indo-Aryan language predominantly written in an abugida script. The study aims to uncover how visual stimuli are processed and mapped onto abstract linguistic representations in the brain. Specifically, we investigate the neural responses that correspond to word length in Bangla, a language with a unique orthography that introduces multiple ways to measure word length. Our results show that MEG signals localised in the anterior left fusiform gyrus, at around 130ms, are highly correlated with word length when measured in terms of the number of minimal graphemic units in the word rather than independent graphemic units (ak[s]ar) or phonemes. Our findings suggest that minimal graphemic units could serve as a suitable metric for measuring word length in non-alphabetic orthographies such as Bangla.

neuroscience↗

bioRxiv2021

Assembling an illustrated family-level tree of life for exploration in mobile devices

Since the concept of the tree of life was introduced by Darwin about a century and a half ago, a considerable fraction of the scientific community has focused its efforts on its reconstruction, with remarkable progress during the last two decades with the advent of DNA sequences. However, the assemblage of a comprehensive tree of life for its exploration has been a difficult task to achieve due to two main obstacles: i) information is scattered into a plethora of individual sources and ii) practical visualization tools for exceptionally large trees are lacking. To overcome both challenges, we aimed to synthetize a family-level tree of life by compiling over 1400 published phylogenetic studies, ensuring that the source trees represent the best phylogenetic hypotheses to date based on a set of objective criteria. Moreover, we dated the synthetic tree by employing over 550 secondary-calibration points, using publicly available sequences for more than 5000 taxa, and by incorporating age ranges from the fossil record for over 2800 taxa. Additionally, we developed a mobile app (Tree of Life) for smartphones in order to facilitate the visualization and interactive exploration of the resulting tree. Interactive features include an easy exploration by zooming and panning gestures of touch screens, collapsing branches, visualizing specific clades as subtrees, a search engine, a timescale to determine extinction and divergence dates, and quick links to Wikipedia. Small illustrations of organisms are displayed at the tips of the branches, to better visualize the morphological diversity of life on earth. Our assembled Tree of Life currently includes over 7000 taxonomic families (about half of the total family-level diversity) and its content will be gradually expanded through regular updates to cover all life on earth at family-level.

evolutionary biology↗