Neurocognitive Signatures of Naturalistic Reading of Scientific Texts: A Fixation-Related fMRI Study

Hsu, Chun-Ting; Clariana, Roy B.; Schloss, Benjamin; Li, Ping

doi:10.1038/s41598-019-47176-7

Cited by 29 publications

(18 citation statements)

References 84 publications

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“…We then employed FIRE fMRI analysis to measure neural activation associated with the content at each fixated location. FIRE fMRI has been shown to reveal underlying neural activity associated with eye fixations in reading (Schuster, Hawelka, Himmelstoss, Richlan, & Hutzler, 2020;Carter, Foster, Muncy, & Luke, 2019;Hsu, Clariana, Schloss, & Li, 2019;Desai, Choi, Lai, & Henderson, 2016;Henderson, Choi, Lowder, & Ferreira, 2016;Henderson, Choi, Luke, & Desai, 2015;Schuster, Hawelka, Richlan, Ludersdorfer, & Hutzler, 2015;Richlan et al, 2014) as well as object perception (Marsman, Renken, Haak, & Cornelissen, 2013;Marsman, Renken, Velichkovsky, Hooymans, & Cornelissen, 2012). However, little work to date has extended the method to active scene perception .…”

Section: Introductionmentioning

confidence: 99%

Neural Correlates of Fixated Low- and High-level Scene Properties during Active Scene Viewing

Henderson

Goold

Choi

et al. 2020

Journal of Cognitive Neuroscience

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During real-world scene perception, viewers actively direct their attention through a scene in a controlled sequence of eye fixations. During each fixation, local scene properties are attended, analyzed, and interpreted. What is the relationship between fixated scene properties and neural activity in the visual cortex? Participants inspected photographs of real-world scenes in an MRI scanner while their eye movements were recorded. Fixation-related fMRI was used to measure activation as a function of lower- and higher-level scene properties at fixation, operationalized as edge density and meaning maps, respectively. We found that edge density at fixation was most associated with activation in early visual areas, whereas semantic content at fixation was most associated with activation along the ventral visual stream including core object and scene-selective areas (lateral occipital complex, parahippocampal place area, occipital place area, and retrosplenial cortex). The observed activation from semantic content was not accounted for by differences in edge density. The results are consistent with active vision models in which fixation gates detailed visual analysis for fixated scene regions, and this gating influences both lower and higher levels of scene analysis.

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Section: Introductionmentioning

confidence: 99%

Neural Correlates of Fixated Low- and High-level Scene Properties during Active Scene Viewing

Henderson

Goold

Choi

et al. 2020

Journal of Cognitive Neuroscience

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“…No inhibited regions were discovered. The MNI coordinates of identified regions with numbers ) 4 Recently, one can observe a re-birth of interest to the FIBER type of analysis however up to date only in reading studies and without employment of ultrafast scanning protocols [20,21].…”

Section: Discussionmentioning

confidence: 99%

Two Visual Systems and Their Eye Movements: a Fixation-Based Event-Related Experiment with Ultrafast fMRI Reconciles Competing Views

Velichkovsky¹,

Korosteleva²,

Pannasch³

et al. 2019

Sovrem Tehnol Med

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Studies of active vision in naturalistic scenes show the existence of two classes of eye movements manifested in ambient and focal visual fixations. This finding seems to corroborate with the anatomical separation of two "streams" of visual processing related to localization (dorsal system) or to identification of objects (ventral system). Direct verification of this connection proved to be difficult due to an insufficient resolution of the conventional noninvasive brain-imaging methods. Another hypothesis recently attributed the same observation to the lateralization of global and local attention modes in the right and left hemispheres, correspondingly. Thus, there are two tentative explanations for the brain mechanisms of the same eye movement patterns in free image viewing. Our study aimed at resolution of this controversy.Materials and Methods. 13 healthy subjects (age 21 to 31 years, right handed, 8 females) with normal or corrected to normal vision and without known history of neurological diseases participated in this experiment. Using a combination of ultrafast multi-band fMRI scanning with the fixation-based event-related (FIBER) paradigm of data collection, we measured the brain functional activity in its relation to tasks, a semantic category of the inspected object (houses or faces), brain regions as well as ambient and focal visual fixations during free viewing of complex images with an unprecedently high temporal and spatial resolution.Results. The results unexpectedly showed that both competing hypotheses are confirmed. In line with our early proposal, ambient fixations were accompanied by activation of structures traditionally associated with the dorsal visual pathway, while focal fixations correlated with that of the ventral pathway. At the same time, the second hypothesis also proved to be correct: the activated structures of the dorsal pathway were localized in the right hemisphere and those of the ventral brain networks mainly -albeit not exclusively -in the left hemisphere.Conclusion. The present study for the first time demonstrates pronounced lateralization of both basic brain mechanisms in charge of visual perception and eye movement control in free processing of complex images. This conclusion poses a number of further questions about a possible relation between two modes of active vision and other forms of asymmetries found at different levels of human brain organization.

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“…It may be that high schoolers are a group of users with extremely high frequency of use of mobile phones for social networking, and this has negatively impacted their ability to make use of MALL effectively for content-based language learning. Recent behavioral and brain imaging data suggest that young people's excessive use of electronic devices including mobile phones may have adverse effects on scientific knowledge integration (Hsu, Clariana, Schloss & Li, 2019) and on Chinese literacy development (Tan & Xu, 2020). Another significant limitation of mobile devices on learning is their small screens, which may increase learners' cognitive load, especially when the processing of rich and multi-page information is necessary.…”

Section: Mobile-assisted Language Learning (Mall)mentioning

confidence: 99%

Digital Language Learning (DLL): Insights from Behavior, Cognition, and the Brain

2021

Bilingualism

Self Cite

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How can we leverage digital technologies to enhance language learning and bilingual representation? In this digital era, our theories and practices for the learning and teaching of second languages (L2) have lagged behind the pace of scientific advances and technological innovations. Here we outline the approach of digital language learning (DLL) for L2 acquisition and representation, and provide a theoretical synthesis and analytical framework regarding DLL's current and future promises. Theoretically, DLL provides a forum for understanding differences between child language and adult L2 learning, and the effects of learning context and learner characteristics. Practically, findings from learner behaviors, cognitive and affective processing, and brain correlates can inform DLL-based language pedagogies. Because of its highly interdisciplinary nature, DLL can serve as an approach to integrate cognitive, social, affective, and neural dimensions of L2 learning with new and emerging technologies including VR, AI, and big data analytics.

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Neurocognitive Signatures of Naturalistic Reading of Scientific Texts: A Fixation-Related fMRI Study

Cited by 29 publications

References 84 publications

Neural Correlates of Fixated Low- and High-level Scene Properties during Active Scene Viewing

Neural Correlates of Fixated Low- and High-level Scene Properties during Active Scene Viewing

Two Visual Systems and Their Eye Movements: a Fixation-Based Event-Related Experiment with Ultrafast fMRI Reconciles Competing Views

Digital Language Learning (DLL): Insights from Behavior, Cognition, and the Brain

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