Dear Colleagues,

Large Language Models (LLMs), such as ChatGPT, are increasingly embedded in daily life and academic practice, prompting urgent questions about how these systems influence core cognitive and neural functions. This Special Issue focuses on the effects of using LLM on attention, memory, and decision-making, emphasizing both the potential benefits and the risks of outsourcing cognitive operations to AI tools. We invite multidisciplinary contributions that examine how interactions with LLMs reshape attentional engagement, alter memory encoding and retrieval processes, and influence human judgment, reasoning, and choice behavior.

Relevant approaches include cognitive neuroscience, psychology, linguistics, human–computer interaction, and computational modeling. Topics of interest span neural correlates of LLM-supported cognition (EEG, fMRI, neuroimaging), changes in attentional patterns during AI-assisted tasks, memory dependence or offloading, decision biases in human–AI collaboration, and implications for learning, expertise development, and information evaluation.

Through a multidisciplinary lens, this Special Issue aims to clarify how large language models intersect with cognitive and neural functions, while promoting evidence-based integration of AI tools into research, clinical practice, and neuroscience education.

Dr. Paschalis Theotokis
Guest Editor