98%
921
2 minutes
20
Objective: In this article, we reexamine the hypothesis of language retrogenesis, that is, the assumption that language change over healthy ageing mirrors, albeit inversely, language acquisition by the child. We additionally question whether this inverse pattern can as well be observed at the cognitive and neurobiological levels, and whether it can be informative (and a consequence, in fact) of how language evolved in humans.
Method: We compare the language strengths and weaknesses signifying language acquisition and its eventual decay in healthy ageing. We further compare age-related cognitive and neurobiological readjustments during each of these two developmental stages, with a focus on brain areas involved in language processing. Finally, we delve into the evolutionary changes experienced by these areas.
Results: We present evidence supporting the hypothesis of retrogenesis in two domains of language: the lexicon (lexical access, understanding of nonliteral meanings, and resolution of lexical competition) and syntax (understanding and production of complex sentences). Additionally, we show evidence that the brain areas supporting these complex tasks are late-myelinated in childhood and early-demyelinated during ageing. Finally, we show that some of these areas (such as the inferior frontal gyrus) are phylogenetically newer.
Conclusions: Language acquisition in children and language degradation/loss in healthy ageing follow the principle of retrogenesis, but mostly in domains that are cognitively demanding and that depend on recently evolved brain devices. Putting this differently, the components of language that emerged more recently appear to be more, and earlier, affected during ageing, as well as developed later over childhood. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1037/neu0000886 | DOI Listing |
Neural Netw
September 2025
Shanghai Maritime University, Shanghai, 201306, China. Electronic address:
Cross-modal hashing aims to leverage hashing functions to map multimodal data into a unified low-dimensional space, realizing efficient cross-modal retrieval. In particular, unsupervised cross-modal hashing methods attract significant attention for not needing external label information. However, in the field of unsupervised cross-modal hashing, there are several pressing issues to address: (1) how to facilitate semantic alignment between modalities, and (2) how to effectively capture the intrinsic relationships between data, thereby constructing a more reliable affinity matrix to assist in the learning of hash codes.
View Article and Find Full Text PDFJ Med Internet Res
September 2025
Department of Information Systems and Cybersecurity, The University of Texas at San Antonio, 1 UTSA Circle, San Antonio, TX, 78249, United States, 1 (210) 458-6300.
Background: Adverse drug reactions (ADR) present significant challenges in health care, where early prevention is vital for effective treatment and patient safety. Traditional supervised learning methods struggle to address heterogeneous health care data due to their unstructured nature, regulatory constraints, and restricted access to sensitive personal identifiable information.
Objective: This review aims to explore the potential of federated learning (FL) combined with natural language processing and large language models (LLMs) to enhance ADR prediction.
J Med Internet Res
September 2025
Department of Psychological and Brain Sciences, Boston University, Boston, United States.
Background: Lesbian, gay, bisexual, transgender, queer/questioning, intersex, asexual (LGBTQIA+) researchers and participants frequently encounter hostility in virtual environments, particularly on social media platforms where public commentary on research advertisements can foster stigmatization. Despite a growing body of work on researcher virtual hostility, little empirical research has examined the actual content and emotional tone of public responses to LGBTQIA+-focused research recruitment.
Objective: This study aimed to analyze the thematic patterns and sentiment of social media comments directed at LGBTQIA+ research recruitment advertisements, in order to better understand how virtual stigma is communicated and how it may impact both researchers and potential participants.
JMIR Med Inform
September 2025
Department of Hepatobiliary and Vascular Surgery, First Affiliated Hospital of Chengdu Medical College, Chengdu, China.
Background: Primary liver cancer, particularly hepatocellular carcinoma (HCC), poses significant clinical challenges due to late-stage diagnosis, tumor heterogeneity, and rapidly evolving therapeutic strategies. While systematic reviews and meta-analyses are essential for updating clinical guidelines, their labor-intensive nature limits timely evidence synthesis.
Objective: This study proposes an automated literature screening workflow powered by large language models (LLMs) to accelerate evidence synthesis for HCC treatment guidelines.
Acad Med
September 2025
Medical student, Indiana University School of Medicine, Indianapolis, Indiana; email: