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Topics in Cognitive Science May 2024One important goal of cognitive science is to understand the mind in terms of its representational and computational capacities, where computational modeling plays an...
One important goal of cognitive science is to understand the mind in terms of its representational and computational capacities, where computational modeling plays an essential role in providing theoretical explanations and predictions of human behavior and mental phenomena. In my research, I have been using computational modeling, together with behavioral experiments and cognitive neuroscience methods, to investigate the information processing mechanisms underlying learning and visual cognition in terms of perceptual representation and attention strategy. In perceptual representation, I have used neural network models to understand how the split architecture in the human visual system influences visual cognition, and to examine perceptual representation development as the results of expertise. In attention strategy, I have developed the Eye Movement analysis with Hidden Markov Models method for quantifying eye movement pattern and consistency using both spatial and temporal information, which has led to novel findings across disciplines not discoverable using traditional methods. By integrating it with deep neural networks (DNN), I have developed DNN+HMM to account for eye movement strategy learning in human visual cognition. The understanding of the human mind through computational modeling also facilitates research on artificial intelligence's (AI) comparability with human cognition, which can in turn help explainable AI systems infer humans' belief on AI's operations and provide human-centered explanations to enhance human-AI interaction and mutual understanding. Together, these demonstrate the essential role of computational modeling methods in providing theoretical accounts of the human mind as well as its interaction with its environment and AI systems.
PubMed: 38781432
DOI: 10.1111/tops.12737 -
Behavior Research Methods Jan 2024Language is an advanced cognitive function of humans, and verbs play a crucial role in language. To understand how the human brain represents verbs, it is critical to...
Language is an advanced cognitive function of humans, and verbs play a crucial role in language. To understand how the human brain represents verbs, it is critical to analyze what knowledge humans have about verbs. Thus, several verb feature datasets have been developed in different languages such as English, Spanish, and German. However, there is still a lack of a dataset of Chinese verbs. In this study, we developed a semantic feature dataset of 1140 Chinese Mandarin verbs (CVFD) with 11 dimensions including verb familiarity, agentive subject, patient, action effector, perceptual modality, instrumentality, emotional valence, action imageability, action complexity, action intensity, and the usage scenario of action. We calculated the semantic features of each verb and the correlation between dimensions. We also compared the difference between action, mental, and other verbs and gave some examples about how to use CVFD to classify verbs according to different dimensions. Finally, we discussed the potential applications of CVFD in the fields of neuroscience, psycholinguistics, cultural differences, and artificial intelligence. All the data can be found at https://osf.io/pv29z/ .
Topics: Humans; Semantics; Artificial Intelligence; Language; Psycholinguistics; China
PubMed: 36622559
DOI: 10.3758/s13428-022-02047-4 -
Philosophical Transactions. Series A,... Mar 2024Sheaves are mathematical objects that describe the globally compatible data associated with open sets of a topological space. Original examples of sheaves were...
Sheaves are mathematical objects that describe the globally compatible data associated with open sets of a topological space. Original examples of sheaves were continuous functions; later they also became powerful tools in algebraic geometry, as well as logic and set theory. More recently, sheaves have been applied to the theory of contextuality in quantum mechanics. Whenever the local data are not necessarily compatible, sheaves are replaced by the simpler setting of presheaves. In previous work, we used presheaves to model lexically ambiguous phrases in natural language and identified the order of their disambiguation. In the work presented here, we model syntactic ambiguities and study a phenomenon in human parsing called garden-pathing. It has been shown that the information-theoretic quantity known as 'surprisal' correlates with human reading times in natural language but fails to do so in garden-path sentences. We compute the degree of signalling in our presheaves using probabilities from the large language model BERT and evaluate predictions on two psycholinguistic datasets. Our degree of signalling outperforms surprisal in two ways: (i) it distinguishes between hard and easy garden-path sentences (with a [Formula: see text]-value [Formula: see text]), whereas existing work could not, (ii) its garden-path effect is larger in one of the datasets (32 ms versus 8.75 ms per word), leading to better prediction accuracies. This article is part of the theme issue 'Quantum contextuality, causality and freedom of choice'.
PubMed: 38281713
DOI: 10.1098/rsta.2023.0013 -
Frontiers in Psychology 2023
PubMed: 38090184
DOI: 10.3389/fpsyg.2023.1326408 -
Journal of Psycholinguistic Research Aug 2023The purpose of the current study is to explore listeners' perception of accented speech in terms of confidence and intelligence. To this end, three groups of listeners...
The purpose of the current study is to explore listeners' perception of accented speech in terms of confidence and intelligence. To this end, three groups of listeners were asked to rate speakers of English with various accent strengths based on a 9-point scale in terms of accent magnitude, confidence and intelligence. Results show that the two Jordanian listener groups, unlike the English listeners, reacted similarly toward Jordanian-accented speakers of English. Overall, the three groups tended to link accentedness with perceptions of confidence and intelligence. The findings of this study have significant implications for advocating a tolerant attitude toward speakers of English as a foreign language in the fields of education, employment opportunities, and social justice. It is suggested that stereotyping speakers as inferior in terms of qualities such as confidence and intelligence reflects established listener's bias rather than lack of speaker's intelligibility.
Topics: Humans; Speech Perception; Speech Intelligibility; Language; Cognition; Intelligence
PubMed: 36867293
DOI: 10.1007/s10936-023-09940-9 -
Journal of Psycholinguistic Research Aug 2023In line with the concept of mobile learning in English Language Teaching (ELT), the aim of this research is to explore how Iranian ELT practitioners take advantage of...
In line with the concept of mobile learning in English Language Teaching (ELT), the aim of this research is to explore how Iranian ELT practitioners take advantage of social media to propose supportive and impactful language learning programs by adhering to persuasive linguistic devices. The research design is nonexperimental and explorative. ELT-related commercial videos and pictures were identified on social media platforms, including Instagram, Facebook, TikTok, and YouTube. We delved into the syntactic and pragmatic features of the data on ELT-related ads to identify the persuasive techniques and strategies these ads resort to for attracting language learners to online classes and services. To analyze the data, the widely-used and acknowledged Cialdini's (The psychology of persuasion, Quill William Morrow, 1984) principles of persuasion are employed. The results manifested that 'reciprocity' and 'scarcity' were the most used persuasive strategies, while 'commitment and consistency' and 'consensus' were the least favorable persuasion principles in these ads. The analysis of the Iranian ELT-related ads indicated that the language used within this context is purposeful and strategic. A contextual investigation of the ELT-related ads on social media can meaningfully contribute to social practices underlying English language pedagogy and digital literacy.
Topics: Humans; Persuasive Communication; Social Media; Advertising; Iran; Language
PubMed: 36853477
DOI: 10.1007/s10936-023-09942-7 -
Topics in Cognitive Science Mar 2024In the present paper, we describe the Enhanced Literate Mind (ELM) hypothesis. As individuals learn to read and write, they are, from then on, exposed to extensive...
In the present paper, we describe the Enhanced Literate Mind (ELM) hypothesis. As individuals learn to read and write, they are, from then on, exposed to extensive written-language input and become literate. We propose that acquisition and proficient processing of written language ("literacy") leads to, both, increased language knowledge as well as enhanced language and nonlanguage (perceptual and cognitive) skills. We also suggest that all neurotypical native language users, including illiterate, low literate, and high literate individuals, share a Basic Language Cognition (BLC) in the domain of oral informal language. Finally, we discuss the possibility that the acquisition of ELM leads to some degree of "knowledge parallelism" between BLC and ELM in literate language users, which has implications for empirical research on individual and situational differences in spoken language processing.
PubMed: 38554287
DOI: 10.1111/tops.12731 -
Quarterly Journal of Experimental... Feb 2024Pseudowords are letter strings that look like words but are not words. They are used in psycholinguistic research, particularly in tasks such as lexical decision. In...
Pseudowords are letter strings that look like words but are not words. They are used in psycholinguistic research, particularly in tasks such as lexical decision. In this context, it is essential that the pseudowords respect the orthographic statistics of the target language. Pseudowords that violate them would be too easy to reject in a lexical decision and would not enforce word recognition on real words. We propose a new pseudoword generator, UniPseudo, using an algorithm based on Markov chains of orthographic n-grams. It generates pseudowords from a customizable database, which allows one to control the characteristics of the items. It can produce pseudowords in any language, in orthographic or phonological form. It is possible to generate pseudowords with specific characteristics, such as frequency of letters, bigrams, trigrams, or quadrigrams, number of syllables, frequency of biphones, and number of morphemes. Thus, from a list of words composed of verbs, nouns, adjectives, or adverbs, UniPseudo can create pseudowords resembling verbs, nouns, adjectives, or adverbs in any language using an alphabetic or syllabic system.
Topics: Humans; Reading; Language; Psycholinguistics; Linguistics
PubMed: 36891822
DOI: 10.1177/17470218231164373 -
Brain and Language Nov 2023Events are a fundamentally important part of our understanding of the world. How lexical concepts denoting events are represented in the brain remains controversial. We...
Events are a fundamentally important part of our understanding of the world. How lexical concepts denoting events are represented in the brain remains controversial. We conducted two experiments using event and object nouns matched on a range of psycholinguistic variables, including concreteness, to examine spatial and temporal characteristics of event concepts. Both experiments used magnitude and valence tasks on event and object nouns. The fMRI experiment revealed a distributed set of regions for events, including the angular gyrus, anterior temporal lobe, and posterior cingulate across tasks. In the EEG experiment, events and objects differed in amplitude within the 300-500 ms window. Together these results shed light into the spatiotemporal characteristics of event concept representation and show that event concepts are represented in the putative hubs of the semantic system. While these hubs are typically associated with object semantics, they also represent events, and have a likely role in temporal integration.
Topics: Humans; Brain Mapping; Brain; Semantics; Language; Parietal Lobe; Magnetic Resonance Imaging
PubMed: 37847931
DOI: 10.1016/j.bandl.2023.105328 -
Genetics in Medicine : Official Journal... Nov 2023
PubMed: 37658852
DOI: 10.1016/j.gim.2023.100962