yuchen xu
Wenzhou Medical University
Wenzhou, China
892
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Manuscript Submission Deadline 5 January 2026
This Research Topic is currently accepting articles.
Connectomics is an emerging field within neuroscience that seeks to map the complex web of neural connections in the brain—known as the connectome. By leveraging advanced imaging technologies, computational modeling, and data analysis, connectomics aims to decipher how neural circuits give rise to specific behaviors, cognitive functions, and neurological conditions. Understanding these intricate networks is essential for uncovering the neural basis of perception, learning, memory, and decision-making. With the rise of high-resolution brain mapping and machine learning tools, researchers can now investigate connections at both micro- and macro-scales, linking structure to function with increasing precision. This research area holds immense potential for transforming our understanding of brain function and dysfunction, paving the way for novel therapeutic interventions. The study of how neural circuits drive behavior represents a critical step toward unraveling the brain’s fundamental mechanisms, making it a key focus in the field of computational neuroscience.
Despite advances in neuroscience, linking neural circuits to behavior remains a key challenge. Traditional methods often identify active brain regions but fall short of revealing how specific patterns of connectivity drive behavior. Connectomics seeks to bridge this gap by mapping the brain’s wiring in detail. However, integrating these structural maps with functional and behavioral data is still a major hurdle.
Recent breakthroughs in high-resolution imaging, neural reconstruction, and activity mapping tools like optogenetics have opened new avenues for exploring brain networks. The goal of this Research Topic is to highlight studies that use connectomic approaches to uncover how neural circuits generate behavior. We aim to bring together work that combines imaging, computational modeling, and functional analysis to better understand brain dynamics. Contributions exploring cross-scale integration, novel technologies, and theoretical frameworks are especially encouraged.
This Research Topic welcomes original research, reviews, and methodological papers that explore the relationship between neural connectivity and behavior through the lens of connectomics. We invite contributions that address themes such as the structural and functional mapping of neural circuits, integration of multi-scale connectomic data, and the development of computational models linking connectivity to behavior. Studies employing cutting-edge imaging techniques, neural simulations, or machine learning tools to analyze brain networks are highly encouraged. We are also interested in research that investigates how alterations in connectivity relate to neurodevelopmental, psychiatric, or neurodegenerative disorders. Manuscripts focusing on cross-species comparisons, technological innovations in neural reconstruction, or theoretical frameworks for interpreting connectomic data are welcome. The scope includes both microscopic and macroscopic levels of analysis, with an emphasis on how connectivity patterns underpin perception, learning, decision-making, and other behaviors. Interdisciplinary approaches bridging neuroscience, computer science, and engineering are particularly valued.
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Keywords: Computational Neuroscience, Neuroscience, Connectomics, Neural circuits, Computational modeling, Brain connectivity, Neural networks
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