Unravelling how neural circuits generate complex behaviours remains one of the most compelling challenges in neuroscience. This endeavor requires tools that provide both cellular precision and systems-level insight. Breakthroughs in optogenetics, viral tracing, calcium imaging, genetically encoded sensors, connectomics, single-cell and spatial transcriptomics, are rapidly expanding our ability to map and manipulate brain function with unprecedented accuracy. At the same time, advances in machine learning, computational modelling, closed-loop and AI-guided perturbation technologies are transforming how we decode and control circuit dynamics.

While these tools are typically developed in separate domains, their integration is essential to advance our understanding of individual variability relevant to personalized medicine. A major challenge is understanding the roots of social behaviors such as empathy and mentalization, which emerge from the dynamic interactions of specific brain circuits. Linking these technological innovations to the dynamics of regions such as the medial prefrontal cortex, temporoparietal junction, amygdala, and hippocampus will be essential to elucidate how neural circuits give rise to both individual variability and complex social relationships.

Animal models, including rodents, remain essential for dissecting neural circuits with causal precision, while human neuroimaging and electrophysiological studies provide critical translational insights. Bridging discoveries across species and methodologies is key to understanding the multiscale organization of brain circuits that shape both normal and pathological behavior.

By integrating traditional neuroscience with cutting-edge innovations, including brain organoids, machine learning, and scalable behavioral pipelines, this Topic highlights reproducible and translational approaches that deepen our understanding of brain function across in vivo, ex vivo, in vitro, in silico and in cognitivo systems, reflecting the growing integration of AI-guided and computationally informed neuroscience.

We invite submissions that explore experimental and analytical approaches in circuit neuroscience, including original research, methods papers, brief reports, reviews, and opinion pieces. Themes of interest include, but are not limited to:

• Circuit mapping and manipulation (optogenetics, chemogenetics, viral tools)
• Optical imaging, electrophysiology, and multimodal data integration
• AI-assisted analysis of neural and behavioral data
• Organoid and cell-based models of circuit function
• Single-cell, spatial, and connectomic approaches
• Open-source tools and pipelines for circuit neuroscience
• Closed-loop neuromodulation and translational applications

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Precision neurocircuitry: emerging tools to map, modulate, and model behavior

Topic Coordinator