scholarly journals The effect of semantic brightness on pupil size: A replication with Dutch words

2019 ◽  
Author(s):  
Sebastiaan Mathôt ◽  
Leevke Sundermann ◽  
Hedderik van Rijn
Keyword(s):  
Language Processing ◽  
Pupil Size ◽  
Word Processing ◽  
Light Response ◽  
Motor Simulation ◽  
Brain Areas ◽  
Embodied Language ◽  
Pupil Constriction ◽  
Pupil Light Response ◽  
Key Questions

AbstractTheories of embodied language hold that word processing is automatically accompanied by sensory and motor simulations. For example, when you read the word ‘sun’, a sensory simulation of brightness as well as a motor simulation of pupil constriction would be automatically triggered. Consistent with this notion, Mathôt, Grainger, and Strijkers (2017) found that the eye’s pupil was slightly smaller after reading single words that were associated with brightness (e.g. ‘sun’) as compared to darkness (e.g. ‘night’); that is, the pupil light response was modulated by the semantic brightness of words. However, (other) key findings within the field of embodied language have proven difficult to replicate, and we therefore felt that it was crucial to replicate the effect of semantic brightness on pupil size. To this end, we conducted a close-but-non-identical replication of two key experiments from Mathôt, Grainger, and Strijkers (2017): one experiment with visually presented words, and one experiment with spoken words. Both experiments were successfully replicated. We propose that cognitive modulations of the pupil light response reflect activity in visual brain areas; therefore, the effect of semantic brightness on pupil size can be used as a marker for the involvement of visual brain areas in language processing, and thus to address a wide variety of key questions within psycholinguistics.

scholarly journals The Pupillary Light Response Reflects Visual Working Memory Content

2018 ◽  
Author(s):  
Cecília Hustá ◽  
Edwin Dalmaijer ◽  
Artem Belopolsky ◽  
Sebastiaan Mathôt
Keyword(s):  
Working Memory ◽  
Visual Working Memory ◽  
Pupil Size ◽  
Light Response ◽  
Memory Representation ◽  
Brain Areas ◽  
Active Memory ◽  
Pupillary Light ◽  
Memory Content ◽  
Higher Cognitive Functions

AbstractRecent studies have shown that the pupillary light response (PLR) is modulated by higher cognitive functions, presumably through activity in visual sensory brain areas. Here we use the PLR to test the involvement of sensory areas in visual working memory (VWM). In two experiments, participants memorized either bright or dark stimuli. We found that pupils were smaller when a pre-stimulus cue indicated that a bright stimulus should be memorized; this reflects a covert shift of attention during encoding of items into VWM. Crucially, we obtained the same result with a post-stimulus cue, which shows that internal shifts of attention within VWM affect pupil size as well. Strikingly, pupil size reflected VWM content only briefly. This suggests that a shift of attention within VWM momentarily activates an “active” memory representation, but that this representation quickly transforms into a “hidden” state that does not rely on sensory areas.

The Opposition of Surprisal and Semantic Similarity in the Prediction of Language Processing: Evidence from Eye-tracking Data

2020 ◽  
Author(s):  
Kun Sun
Keyword(s):  
Eye Tracking ◽  
Semantic Similarity ◽  
Cognitive Processing ◽  
Language Processing ◽  
Language Comprehension ◽  
Word Processing ◽  
Reading Time ◽  
Computational Models ◽  
Tracking Data ◽  
Dynamic Approach

Expectations or predictions about upcoming content play an important role during language comprehension and processing. One important aspect of recent studies of language comprehension and processing concerns the estimation of the upcoming words in a sentence or discourse. Many studies have used eye-tracking data to explore computational and cognitive models for contextual word predictions and word processing. Eye-tracking data has previously been widely explored with a view to investigating the factors that influence word prediction. However, these studies are problematic on several levels, including the stimuli, corpora, statistical tools they applied. Although various computational models have been proposed for simulating contextual word predictions, past studies usually preferred to use a single computational model. The disadvantage of this is that it often cannot give an adequate account of cognitive processing in language comprehension. To avoid these problems, this study draws upon a massive natural and coherent discourse as stimuli in collecting the data on reading time. This study trains two state-of-art computational models (surprisal and semantic (dis)similarity from word vectors by linear discriminative learning (LDL)), measuring knowledge of both the syntagmatic and paradigmatic structure of language. We develop a `dynamic approach' to compute semantic (dis)similarity. It is the first time that these two computational models have been merged. Models are evaluated using advanced statistical methods. Meanwhile, in order to test the efficiency of our approach, one recently developed cosine method of computing semantic (dis)similarity based on word vectors data adopted is used to compare with our `dynamic' approach. The two computational and fixed-effect statistical models can be used to cross-verify the findings, thus ensuring that the result is reliable. All results support that surprisal and semantic similarity are opposed in the prediction of the reading time of words although both can make good predictions. Additionally, our `dynamic' approach performs better than the popular cosine method. The findings of this study are therefore of significance with regard to acquiring a better understanding how humans process words in a real-world context and how they make predictions in language cognition and processing.

scholarly journals Listener’s personality traits predict changes in pupil size during auditory language comprehension

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Isabell Hubert Lyall ◽  
Juhani Järvikivi
Keyword(s):  
Personality Traits ◽  
Language Processing ◽  
Language Comprehension ◽  
Pupil Size ◽  
Pupil Dilation ◽  
Systematic Research ◽  
Cognitive Resources ◽  
Personality Profiles ◽  
Pupillary Responses ◽  
Grammatical Errors

AbstractResearch suggests that listeners’ comprehension of spoken language is concurrently affected by linguistic and non-linguistic factors, including individual difference factors. However, there is no systematic research on whether general personality traits affect language processing. We correlated 88 native English-speaking participants’ Big-5 traits with their pupillary responses to spoken sentences that included grammatical errors, "He frequently have burgers for dinner"; semantic anomalies, "Dogs sometimes chase teas"; and statements incongruent with gender stereotyped expectations, such as "I sometimes buy my bras at Hudson's Bay", spoken by a male speaker. Generalized additive mixed models showed that the listener's Openness, Extraversion, Agreeableness, and Neuroticism traits modulated resource allocation to the three different types of unexpected stimuli. No personality trait affected changes in pupil size across the board: less open participants showed greater pupil dilation when processing sentences with grammatical errors; and more introverted listeners showed greater pupil dilation in response to both semantic anomalies and socio-cultural clashes. Our study is the first one demonstrating that personality traits systematically modulate listeners’ online language processing. Our results suggest that individuals with different personality profiles exhibit different patterns of the allocation of cognitive resources during real-time language comprehension.

scholarly journals Sentence Reading: A Functional MRI Study at 4 Tesla

1997 ◽  
Vol 9 (5) ◽  
pp. 664-686 ◽  
Author(s):  
D. Bavelier ◽  
D. Corina ◽  
P. Jezzard ◽  
S. Padmanabhan ◽  
V. P. Clark ◽  
...  
Keyword(s):  
Language Processing ◽  
Word Processing ◽  
Blood Oxygenation ◽  
Anterior Portion ◽  
Individual Subject ◽  
Sentence Reading ◽  
Wernicke’S Area ◽  
Classical Language ◽  
Mri Study ◽  
Language Areas

In this study, changes in blood oxygenation and volume were monitored while monolingual right-handed subjects read English sentences. Our results confirm the role of the left peri-sylvian cortex in language processing. Interestingly, individual subject analyses reveal a pattern of activation characterized by several small, limited patches rather than a few large, anatomically well-circumscribed centers. Between-subject analyses confirm a lateralized pattern of activation and reveal active classical language areas including Broca's area, Wernicke's area, and the angular gyms. In addition they point to areas only more recently considered as language-relevant including the anterior portion of the superior temporal sulcus. This area has not been reliably observed in imaging studies of isolated word processing. This raises the hypothesis that activation in this area is dependent on processes specific to sentence reading.

scholarly journals Deep learning-based pupil model predicts time and spectral dependent light responses

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Babak Zandi ◽  
Tran Quoc Khanh
Keyword(s):  
Deep Learning ◽  
Time Course ◽  
Light Response ◽  
Absolute Error ◽  
Light Responses ◽  
Temporal Prediction ◽  
Feed Forward Neural Networks ◽  
Self Learning ◽  
Pupil Light Response ◽  
Planckian Locus

AbstractAlthough research has made significant findings in the neurophysiological process behind the pupillary light reflex, the temporal prediction of the pupil diameter triggered by polychromatic or chromatic stimulus spectra is still not possible. State of the art pupil models rested in estimating a static diameter at the equilibrium-state for spectra along the Planckian locus. Neither the temporal receptor-weighting nor the spectral-dependent adaptation behaviour of the afferent pupil control path is mapped in such functions. Here we propose a deep learning-driven concept of a pupil model, which reconstructs the pupil’s time course either from photometric and colourimetric or receptor-based stimulus quantities. By merging feed-forward neural networks with a biomechanical differential equation, we predict the temporal pupil light response with a mean absolute error below 0.1 mm from polychromatic (2007 $$\pm$$ ± 1 K, 4983 $$\pm$$ ± 3 K, 10,138 $$\pm$$ ± 22 K) and chromatic spectra (450 nm, 530 nm, 610 nm, 660 nm) at 100.01 ± 0.25 cd/m2. This non-parametric and self-learning concept could open the door to a generalized description of the pupil behaviour.

scholarly journals A visual circuit uses complementary mechanisms to support transient and sustained pupil constriction

eLife ◽  
2016 ◽  
Vol 5 ◽  
Author(s):  
William Thomas Keenan ◽  
Alan C Rupp ◽  
Rachel A Ross ◽  
Preethi Somasundaram ◽  
Suja Hiriyanna ◽  
...  
Keyword(s):  
Neural Coding ◽  
Pupil Size ◽  
Neural Circuit ◽  
Ganglion Cells ◽  
Retinal Ganglion ◽  
Neural Basis ◽  
Behavioral Dynamics ◽  
Pupil Constriction ◽  
Sustained Responses ◽  
Stable Control

Rapid and stable control of pupil size in response to light is critical for vision, but the neural coding mechanisms remain unclear. Here, we investigated the neural basis of pupil control by monitoring pupil size across time while manipulating each photoreceptor input or neurotransmitter output of intrinsically photosensitive retinal ganglion cells (ipRGCs), a critical relay in the control of pupil size. We show that transient and sustained pupil responses are mediated by distinct photoreceptors and neurotransmitters. Transient responses utilize input from rod photoreceptors and output by the classical neurotransmitter glutamate, but adapt within minutes. In contrast, sustained responses are dominated by non-conventional signaling mechanisms: melanopsin phototransduction in ipRGCs and output by the neuropeptide PACAP, which provide stable pupil maintenance across the day. These results highlight a temporal switch in the coding mechanisms of a neural circuit to support proper behavioral dynamics.

The use of a rapid priming technique I: Adult language processing

1999 ◽  
Vol 10 (1) ◽  
pp. 85-91
Author(s):  
Chris Davis ◽  
Anne Castles
Keyword(s):  
Word Recognition ◽  
Incomplete Information ◽  
Language Processing ◽  
Word Processing ◽  
Recognition System ◽  
Masked Priming ◽  
Written Language ◽  
Psycholinguistic Research ◽  
Skilled Readers ◽  
Priming Technique

ABSTRACTThis paper discusses the background and use of the masked priming procedure in adult psycholinguistic research. Using this technique, we address the issue of how precise the letter and word processing systems of adults is for rapidly displayed stimuli. Data is reviewed that suggests that, for skilled readers, the letter and word recognition system is sensitively tuned to the discrimination demands imposed on it by the properties of the written language. That is, the recognition system is able to be discriminative where precision is required, but is also able to consider and use incomplete information when this is predictive.

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