Object knowledge representation in the human visual cortex requires a connection with the language system DOI Creative Commons
Bo Liu, Xiaosha Wang, Xiaoying Wang

et al.

PLoS Biology, Journal Year: 2025, Volume and Issue: 23(5), P. e3003161 - e3003161

Published: May 20, 2025

How world knowledge is stored in the human brain a central question cognitive neuroscience. Object effects have been commonly observed higher-order sensory association cortices, with role of language being highly debated. Using object color as test case, we investigated whether communication system plays necessary neural representation visual cortex and corresponding behaviors, combining diffusion imaging (measuring white-matter structural integrity), functional MRI (fMRI; measuring knowledge), neuropsychological assessments behavioral integrity) group patients who suffered from stroke ( N = 33; 18 left-hemisphere lesions, 11 right-hemisphere 4 bilateral lesions). The integrity loss connection between anterior temporal region ventral had significant effect on strength behavior across modalities. These contributions could not be explained by potential early perception pathway or confounding variables. Our experiments reveal contribution vision-language occipitotemporal (VOTC) highlighting significance language-sensory interface.

Language: Английский

Can artificial intelligence be the future solution to the enormous challenges and suffering caused by Schizophrenia? DOI Creative Commons
Shijie Jiang, Qiyu Jia, Zhenlei Peng

et al.

Schizophrenia, Journal Year: 2025, Volume and Issue: 11(1)

Published: Feb. 28, 2025

This study evaluated the potential of artificial intelligence (AI) in diagnosis, treatment, and prognostic assessment schizophrenia (SZ) explored collaborative directions for AI applications future medical innovations. SZ is a severe mental disorder that causes significant suffering imposes challenges on patients. With rapid advancement machine learning deep technologies, has demonstrated notable advantages early diagnosis high-risk populations. By integrating multidimensional biomarkers linguistic behavior data patients, can provide further objective precise diagnostic criteria. Moreover, it aids formulating personalized treatment plans, enhancing therapeutic outcomes, offering new strategies patients with treatment-resistant SZ. Furthermore, excels developing individualized which enables identification disease progression, accurate prediction trajectory, timely adjustment strategies, thereby improving prognosis facilitating recovery. Despite immense management, its role as an auxiliary tool must be emphasized, clinical judgment compassionate care from healthcare professionals remaining crucial. Future research should focus optimizing human–machine interactions to achieve efficient application management. The in-depth integration technology into practice will advance field SZ, ultimately quality life outcomes

Language: Английский

Citations

3
Abstractness impacts conversational dynamics DOI Creative Commons
Claudia Mazzuca, Caterina Villani,

Tommaso Lamarra

et al.

Cognition, Journal Year: 2025, Volume and Issue: 258, P. 106084 - 106084

Published: Feb. 14, 2025

Conversation topics may vary in abstractness. This might impact the effort required by speakers to reach a common ground and, ultimately, an interactive alignment. In fact, people typically feel less confident with abstract concepts and single-words rating studies suggest are more associated social interactions than concrete concepts-hence suggesting increasing levels of abstractness enhance inner mutual monitoring processes. However, experimental addressing conversational dynamics afforded still sparse. three preregistered experiments we ask whether sentences specific constructs dialogue, i.e., higher uncertainty, curiosity willingness continue conversation, questions related causal agency aspects. We do so asking participants evaluate plausibility linguistic exchanges referring concepts. Results support theories proposing that involve compared reaching alignment dialogue is effortful

Language: Английский

Citations

2
The Double-Edged Sword of Anthropomorphism in LLMs DOI Creative Commons
Madeline G. Reinecke, Fransisca Ting, Julian Savulescu

et al.

Published: Feb. 26, 2025

Humans may have evolved to be "hyperactive agency detectors". Upon hearing a rustle in pile of leaves, it would safer assume that an agent, like lion, hides beneath (even if there ultimately nothing there). Can this evolutionary cognitive mechanism—and related mechanisms anthropomorphism—explain some people's contemporary experience with using chatbots (e.g., ChatGPT, Gemini)? In paper, we sketch how such engender the seemingly irresistible anthropomorphism large language-based chatbots. We then explore implications within educational context. Specifically, argue tendency perceive "mind machine" is double-edged sword for progress: Though can facilitate motivation and learning, also lead students trust—and potentially over-trust—content generated by To sure, do seem recognize LLM-generated content may, at times, inaccurate. argue, however, rise towards will only serve further camouflage these inaccuracies. close considering research turn aiding becoming digitally literate—avoiding pitfalls caused perceiving humanlike mental states

Language: Английский

Citations

2
Asymmetric sampling in time: evidence and perspectives DOI Creative Commons
Chantal Oderbolz, David Poeppel, Martin Meyer

et al.

Neuroscience & Biobehavioral Reviews, Journal Year: 2025, Volume and Issue: 171, P. 106082 - 106082

Published: Feb. 24, 2025

Language: Английский

Citations

1
Speaking of yourself: A meta-analysis of 80 years of research on pronoun use in schizophrenia DOI Creative Commons
Dalia Elleuch, Yinhan Chen, Qiang Luo

et al.

Schizophrenia Research, Journal Year: 2025, Volume and Issue: 279, P. 22 - 30

Published: March 30, 2025

People with schizophrenia experience significant language disturbances that profoundly affect their everyday social interactions. Given its relevance to the referential function of language, aberrations in pronoun use are particular interest study schizophrenia. This systematic review and meta-analysis, adhering PRISMA guidelines, examines frequency PubMed, PsycINFO, Scopus, Google Scholar, Web Science were searched up May 1, 2024. All studies analyzing various spoken contexts included. Bias was assessed using a modified Newcastle-Ottawa Scale. A Bayesian meta-analysis model averaging estimated effect sizes moderating factors. 13 n = 917 unique participants case-control contrasts 37.9 % patient samples women, weighted mean (SD) age 34.45 (9.72) years. 53.85 languages other than English. We report medium-sized for first-person impairment (model-averaged d 0.89, 95 CrI (0.44, 1.33)). There heterogeneity moderated by age. Evidence publication bias weak, strong support after accounting heterogeneity. small reduction inter-individual variability patients compared healthy controls (lnCVR -0.12, [-0.35, -0.13]). While all also high patients, this not robust due bias. Individuals excessively pronouns. may be marker disturbed sense self illness.

Language: Английский

Citations

1
Headmen, shamans, and mothers: Natural and sexual selection for computational services DOI
Edward H. Hagen, Zachary H. Garfield, Aaron D. Lightner

et al.

Evolution and Human Behavior, Journal Year: 2025, Volume and Issue: 46(1), P. 106651 - 106651

Published: Jan. 1, 2025

Language: Английский

Citations

1
Generative AI for Self-Adaptive Systems: State of the Art and Research Roadmap DOI Open Access
Jialong Li, Mingyue Zhang, Nianyu Li

et al.

ACM Transactions on Autonomous and Adaptive Systems, Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 20, 2024

Self-adaptive systems (SASs) are designed to handle changes and uncertainties through a feedback loop with four core functionalities: monitoring, analyzing, planning, execution. Recently, generative artificial intelligence (GenAI), especially the area of large language models, has shown impressive performance in data comprehension logical reasoning. These capabilities highly aligned functionalities required SASs, suggesting strong potential employ GenAI enhance SASs. However, specific benefits challenges employing SASs remain unclear. Yet, providing comprehensive understanding these is complex due several reasons: limited publications SAS field, technological application diversity within rapid evolution technologies. To that end, this paper aims provide researchers practitioners snapshot outlines GenAI’s SAS. Specifically, we gather, filter, analyze literature from distinct research fields organize them into two main categories benefits: (i) enhancements autonomy centered around functions MAPE-K loop, (ii) improvements interaction between humans human-on-the-loop settings. From our study, outline roadmap highlights integrating The starts outlining key need be tackled exploit for applying field concludes practical reflection, elaborating on current shortcomings proposing possible mitigation strategies. 1

Language: Английский

Citations

6
Building machines that learn and think with people DOI
Katherine M. Collins, Ilia Sucholutsky, Umang Bhatt

et al.

Nature Human Behaviour, Journal Year: 2024, Volume and Issue: 8(10), P. 1851 - 1863

Published: Oct. 22, 2024

Language: Английский

Citations

5
Psychomatics—A Multidisciplinary Framework for Understanding Artificial Minds DOI
Giuseppe Riva, Fabrizia Mantovani, Brenda K. Wiederhold

et al.

Cyberpsychology Behavior and Social Networking, Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 29, 2024

Although large language models (LLMs) and other artificial intelligence systems demonstrate cognitive skills similar to humans, such as concept learning acquisition, the way they process information fundamentally differs from biological cognition. To better understand these differences, this article introduces Psychomatics, a multidisciplinary framework bridging science, linguistics, computer science. It aims delve deeper into high-level functioning of LLMs, focusing specifically on how LLMs acquire, learn, remember, use produce their outputs. achieve goal, Psychomatics will rely comparative methodology, starting theory-driven research question-is development different in humans LLMs?-drawing parallels between systems. Our analysis shows can map manipulate complex linguistic patterns training data. Moreover, follow Grice's Cooperative principle provide relevant informative responses. However, human cognition draws multiple sources meaning, including experiential, emotional, imaginative facets, which transcend mere processing are rooted our social developmental trajectories. current lack physical embodiment, reducing ability make sense intricate interplay perception, action, that shapes understanding expression. Ultimately, holds potential yield transformative insights nature language, cognition, intelligence, both biological. by drawing processes, inform more robust human-like

Language: Английский

Citations

4
Multilingual Computational Models Reveal Shared Brain Responses to 21 Languages DOI Creative Commons
Andrea Gregor de Varda, Saima Malik-Moraleda, Greta Tuckute

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 2, 2025

Abstract At the heart of language neuroscience lies a fundamental question: How does human brain process rich variety languages? Recent developments in Natural Language Processing, particularly multilingual neural network models, offer promising avenue to answer this question by providing theory-agnostic way representing linguistic content across languages. Our study leverages these advances ask how brains native speakers 21 languages respond stimuli, and what extent representations are similar We combined existing (12 4 families; n=24 participants) newly collected fMRI data (9 n=27 evaluate series encoding models predicting activity based on from diverse (20 8 model classes). found evidence cross-lingual robustness alignment between artificial biological networks. Critically, we showed that can be transferred zero-shot languages, so trained predict set account for responses held-out language, even families. These results imply shared component processing different plausibly related meaning space.

Language: Английский

Citations

0