Minimally invasive electrocorticography (ECoG) recording in common marmosets

皮质电图 神经科学 脑电图 心理学
作者
Silvia Spadacenta,Peter W. Dicke,Peter Thier
出处
期刊:Journal of Neuroscience Methods [Elsevier BV]
卷期号:417: 110409-110409 被引量:4
标识
DOI:10.1016/j.jneumeth.2025.110409
摘要

BACKGROUND: Electrocorticography (ECoG) provides a valuable compromise between spatial and temporal resolution for recording brain activity with excellent signal quality, crucial for presurgical epilepsy mapping and advancing neuroscience, including brain-machine interface development. ECoG is particularly effective in the common marmoset (Callithrix jacchus), whose lissencephalic (unfolded) brain surface provides broad cortical access. One of the key advantages of ECoG recordings is the ability to study interactions between distant brain regions. Traditional methods rely on large electrode arrays, necessitating extensive trepanations and a trade-off between size and electrode spacing. NEW METHOD: This study introduces a refined ECoG technique for examining interactions among multiple cortical areas in marmosets, combining circumscribed trepanations with high-density electrode arrays at specific sites of interest. COMPARISON WITH EXISTING METHODS: Standard ECoG techniques typically require large electrode arrays and extensive trepanation, which heighten surgical risks and the likelihood of infection, while potentially compromising spatial resolution. In contrast, our method facilitates detailed and stable recordings across multiple cortical areas with minimized invasiveness and reduced complication risks, all while preserving high spatial resolution. RESULTS: Two adult marmosets underwent ECoG implantation in frontal, temporal, and parietal regions. Postoperative monitoring confirmed rapid recovery, long-term health, and stable, high-quality neural recordings during various behavioral tasks. CONCLUSIONS: This refined ECoG method enhances the study of cortical interactions in marmosets while minimizing surgical invasiveness and complication risks. It offers potential for broader application in other species and opens new avenues for long-term data collection, ultimately advancing both neuroscience and brain-machine interface research.
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