Optimizing intact skull intrinsic signal imaging for subsequent targeted electrophysiology across mouse visual cortex

• Authors: Armel Nsiangani, Georgia Institute of Technology; Jospeh Del Rosario, Georgia Institute of Technology; Alan C Yeh, Georgia Institute of Technology; Donghoon Shin, Georgia Institute of Technology; Shea Wells, Georgia Institute of Technology; Tidhar Lev-Ari, Georgia Institute of Technology; Brice Williams, Georgia Institute of Technology; Bilal Haider, Emory University
• Journal Title: SCIENTIFIC REPORTS
• Volume: Volume 12, Number 1
• Publisher: NATURE PORTFOLIO | 2022-02-08, Pages 2063-2063
• Type of Work: Article | Final Publisher PDF
• Publisher DOI: http://doi.org/10.1038/s41598-022-05932-2
• Subjects: Computer Science
• Keywords: Science & Technology; Multidisciplinary Sciences; Science & Technology - Other Topics; FUNCTIONAL SPECIALIZATION; PLASTICITY; ADULT; MICE; ISOFLURANE; RESOLUTION; V1

Abstract

Understanding brain function requires repeatable measurements of neural activity across multiple scales and multiple brain areas. In mice, large scale cortical neural activity evokes hemodynamic changes readily observable with intrinsic signal imaging (ISI). Pairing ISI with visual stimulation allows identification of primary visual cortex (V1) and higher visual areas (HVAs), typically through cranial windows that thin or remove the skull. These procedures can diminish long-term mechanical and physiological stability required for delicate electrophysiological measurements made weeks to months after imaging (e.g., in subjects undergoing behavioral training). Here, we optimized and directly validated an intact skull ISI system in mice. We first assessed how imaging quality and duration affect reliability of retinotopic maps in V1 and HVAs. We then verified ISI map retinotopy in V1 and HVAs with targeted, multi-site electrophysiology several weeks after imaging. Reliable ISI maps of V1 and multiple HVAs emerged with ~ 60 trials of imaging (65 ± 6 min), and these showed strong correlation to local field potential (LFP) retinotopy in superficial cortical layers (r2 = 0.74–0.82). This system is thus well-suited for targeted, multi-area electrophysiology weeks to months after imaging. We provide detailed instructions and code for other researchers to implement this system.