Cognitive Processes in Human–AI Interaction: Neural and Behavioral Insights

A special issue of Brain Sciences (ISSN 2076-3425). This special issue belongs to the section "Behavioral Neuroscience".

Deadline for manuscript submissions: 10 July 2026 | Viewed by 867

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Department of Neuroscience, Psychology, Drug Research and Child Health (NEU-ROFARBA), University of Florence, 50100 Florence, Italy
Interests: cognitive control; human–artificial intelligence interaction
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Special Issue Information

Dear Colleagues,

With the fast diffusion of Artificial Intelligence, the use of AI-driven technologies has become increasingly embedded in everyday life. For instance, it has become increasingly common for people to use these technologies to navigate the Internet, study, find inspiration, and interact with chatbots. Our social world is evolving toward a complex fusion of real-life and virtual interactions, with the boundary between the two gradually fading, especially for individuals in developmental stages or those with psychopathological vulnerabilities. The social implications of the rise in human–AI interactions, and even relationships, are of great public interest, yet remain insufficiently understood by the scientific community.

This Special Issue aims to investigate the role of cognitive processes in human–AI interaction by investigating behavior and the underlying neural circuitry. We welcome theoretical and empirical contributions that enrich our understanding of cognitive control in human–AI interactions, with particular attention to its neural basis, societal implications, and impact on individuals in developmental stages as well as those with psychiatric or psychopathological conditions.

Dr. Gioele Gavazzi
Guest Editor

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Keywords

  • cognitive control
  • human–artificial intelligence interaction
  • inhibition & AI

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Published Papers (1 paper)

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22 pages, 1492 KB  
Systematic Review
Neural Correlates of Inhibitory Control in Impulsivity Traits in Non-Ecological Human–Computer Tasks: An ALE Meta-Analysis
by Chiara Noferini, Gioele Gavazzi, Fabio Giovannelli, Chiara Puddu, Mario Mascalchi, Massimo Cincotta, Liberatore Tramontano, Carlo Cavaliere and Maria Pia Viggiano
Brain Sci. 2026, 16(6), 609; https://doi.org/10.3390/brainsci16060609 - 3 Jun 2026
Viewed by 480
Abstract
Background/Objectives: Response inhibition is the capacity to restrain impulsive actions, representing a pivotal facet of cognitive control. Although several studies report a dynamic relationship between impulsivity and inhibitory control, the neural mechanisms remain unclear. The aim of the present study is to [...] Read more.
Background/Objectives: Response inhibition is the capacity to restrain impulsive actions, representing a pivotal facet of cognitive control. Although several studies report a dynamic relationship between impulsivity and inhibitory control, the neural mechanisms remain unclear. The aim of the present study is to explore neural correlates of response inhibition as a function of impulsive personality traits. Methods: For this purpose, two groups of fMRI studies conducted on subjects with and without impulsive traits were compared. The selected studies were included based on both the impulsivity levels and the performance of the subjects in inhibitory human–computer tasks (e.g., Go/No-go, Stop-signal). This was done to minimize potential differences due to samples’ performances. Neuroimaging data were analyzed with an Activation Likelihood Estimation (ALE) meta-analysis approach. Results: Results reveal highly congruent clusters encompassing subcortical and prefrontal brain regions in both impulsive and non-impulsive subjects, albeit with subtle distinctions. Specifically, a direct contrast highlighted different activity in the right Middle and Superior Frontal Gyrus during inhibition tasks in the impulsive group. Conclusions: These findings deepen our comprehension of the neural mechanisms governing inhibitory control in human impulsivity. Understanding such mechanisms is increasingly relevant in today’s world, where frequent interactions with artificial systems may challenge or modulate inhibitory control, with potential implications for everyday behavior. Full article
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