Talk, Text, Connect: Naturalistic language and social meaning across brains and AI models

For decades, cognitive neuroscience relied on highly controlled, albeit artificial, experimental designs using isolated words or fragmented sentences to map the linguistic brain. However, language in the real world is rarely static; it is a dynamic, social, and continuous medium used to build connection and convey complex intent. The recent "naturalistic turn" in neuroscience—utilizing stories, movies, and spontaneous dialogue—has revealed that the brain processes language through widespread, interconnected networks that are deeply sensitive to social context. Simultaneously, the rise of Large Language Models (LLMs) has provided researchers with unprecedented computational tools to simulate and predict human-like text processing. Despite these advancements, a significant gap remains in understanding how "social meaning"—the nuanced subtext and interpersonal resonance of communication—is represented across biological and artificial systems. This Research Topic seeks to explore how the brain and AI move beyond syntax to achieve true social connectivity.The primary goal of this Research Topic is to address the "ecological validity gap" in language neuroscience by integrating naturalistic paradigms with advanced computational modeling. While AI models can mimic human-like prose, they often lack the "grounded" social understanding that characterizes human interaction. Conversely, human neuroscience needs more robust frameworks to quantify the high-dimensional social information embedded in natural talk and text.We aim to investigate how the human brain extracts social meaning from continuous linguistic input and how these processes align with—or diverge from—state-of-the-art AI architectures. By bringing together research on neural synchronization, semantic representation, and social pragmatics, we hope to establish a multidisciplinary framework for the "neuroscience of connection." We seek to answer whether AI can truly model the "social brain" and how naturalistic linguistic interaction shapes neural activity between speakers and listeners. Ultimately, this collection will advance our understanding of language not just as a cognitive faculty, but as the primary bridge for social cognition.This Research Topic welcomes original research, reviews, and methodological papers that utilize naturalistic stimuli to probe the intersection of language, social meaning, and AI. We encourage submissions that employ diverse neuroimaging techniques (fMRI, EEG, fNIRS, MEG) and computational approaches to explore how communication fosters connection.Specific themes of interest include, but are not limited to:• Neural Alignment: Studies investigating brain-to-brain synchrony (hyperscanning) during naturalistic dialogue or storytelling.• AI-Brain Mapping: Research comparing the internal representations of Large Language Models (LLMs) with human neural activity during narrative processing.• Social Pragmatics: How the brain and AI models encode intent, sarcasm, and social context in unstructured text or speech.• Social Semantics: The neural basis of social concepts and interpersonal meaning in real-world communication.• Interactive Dynamics: The impact of AI-mediated communication on human social networks and neural processing.• Methodological Innovations: New pipelines for analyzing high-dimensional naturalistic data in relation to social behavior. Topic editors: Aaron J Newman, Yan Wu Source: https://www.frontiersin.org/research-topics/79922/talk-text-connect-naturalistic-language-and-social-meaning-across-brains-and-ai-models