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Meta-analytic evidence indicates that the quality of the attachment relationship that infants establish with their primary caregiver has enduring significance for socioemotional and cognitive outcomes. However, the mechanisms by which early attachment experiences contribute to subsequent development remain underspecified. According to attachment theory, early attachment experiences become embodied in the form of cognitive-affective representations, referred to as internal working models (IWMs), that guide future behavior. Little is known, however, about the cognitive architecture of IWMs in infancy. In this article, we discuss significant advances made in the field of infant cognitive development and propose that leveraging insights from this research has the potential to fundamentally shape our understanding of the cognitive architecture of attachment representations in infancy. We also propose that the integration of attachment research into cognitive research can shed light on the role of early experiences, individual differences, and stability and change in infant cognition, as well as open new routes of investigation in cognitive studies, which will further our understanding of human knowledge. We provide recommendations for future research throughout the article and conclude by using our collaborative research as an example.
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http://dx.doi.org/10.1177/17456916241262693 | DOI Listing |
Psychol Rev
September 2025
Neural Computation Group, Max-Planck Institute for Human Cognitive and Brain Sciences.
It has been suggested that episodic memory relies on the well-studied machinery of spatial memory. This influential notion faces hurdles that become evident with dynamically changing spatial scenes and an immobile agent. Here I propose a model of episodic memory that can accommodate such episodes via temporal indexing.
View Article and Find Full Text PDFHum Brain Mapp
September 2025
Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Dresden, Germany.
Acting intentionally is a major aspect of human cognitive development and depends on the ability to link actions with their consequences. Action-effect binding (AEB) is a fundamental mechanism enabling this. While AEB has been well-characterized in adults, its neurophysiological underpinnings during adolescence remain unclear.
View Article and Find Full Text PDFActa Psychol (Amst)
September 2025
Shanghai Jiao Tong University, China. Electronic address:
This study investigates fundamental differences in the acquisition of morphological patterns by humans and large language models (LLMs) within an artificial language learning paradigm. Specifically, it compares how each system responds to variations in input structure-blocked versus interleaved sequences and juxtaposed versus spaced presentation-across verb classification and inflection tasks. While LLMs (GPT4mini, DeepSeek_V3, Llama3.
View Article and Find Full Text PDFAgeing Res Rev
September 2025
Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Rome, Italy; Department of Medicine and Surgery, LUM University, Casamassima, Italy. Electronic address:
Nuclear insertions of mitochondrial DNA (mtDNA) segments (NUMTs) represent an evolutionarily conserved phenomenon originating from the ancient endosymbiotic relationship between mitochondria and host cells. These insertions predominantly localize near intergenic or regulatory regions and are often enriched in tissues with high metabolic activity. Once regarded as inert pseudogenes or genomic artifacts, NUMTs are now recognized as dynamic elements capable of modulating nuclear architecture and cellular function.
View Article and Find Full Text PDFNeuroscience
September 2025
School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, Zhejiang 310018, China; Key Laboratory of Intelligent Image Analysis for Sensory and Cognitive Health, Ministry of Industry and Information Technology of China, Hangzhou, Zhejiang 310018, China.
Achieving a deep understanding of brain mechanisms requires multi-scale perspectives to capture the architecture of complex networks. In this study, we focused on patients with cognitive impairment and constructed individual brain networks from neuroimaging data. We introduced a Significant Edges Selection (SES) method, which effectively extracts the most informative connections while suppressing noise.
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