PT - JOURNAL ARTICLE AU - Sarah E.W. Light AU - James D. Jontes TI - Multiplane calcium imaging reveals disrupted development of network topology in zebrafish <em>pcdh19</em> mutants AID - 10.1523/ENEURO.0420-18.2019 DP - 2019 May 06 TA - eneuro PG - ENEURO.0420-18.2019 4099 - http://www.eneuro.org/content/early/2019/05/03/ENEURO.0420-18.2019.short 4100 - http://www.eneuro.org/content/early/2019/05/03/ENEURO.0420-18.2019.full AB - Functional brain networks self-assemble during development, although the molecular basis of network assembly is poorly understood. Protocadherin-19 (pcdh19) is a homophilic cell adhesion molecule that is linked to neurodevelopmental disorders, and influences multiple cellular and developmental events in zebrafish. Although loss of PCDH19 in humans and model organisms leads to functional deficits, the underlying network defects remain unknown. Here, we employ multiplane, resonant-scanning in vivo two-photon calcium imaging of developing zebrafish, and use graph theory to characterize the development of resting state functional networks in both wild type and pcdh19 mutant larvae. We find that the brain networks of pcdh19 mutants display enhanced clustering and an altered developmental trajectory of network assembly. Our results show that functional imaging and network analysis in zebrafish larvae is an effective approach for characterizing the developmental impact of lesions in genes of clinical interest.Significance Statement Non-clustered protocadherins are linked to neurodevelopmental disorders that include microcephaly, intellectual disability, autism spectrum disorders and epilepsy. In humans, mutations in PCDH19 cause a female limited form of infantile epileptic encephalopathy and are associated with an increased incidence of schizophrenia and autism. In this study, we use large-scale calcium imaging to reveal that mutations in zebrafish pcdh19 alter the development of brain network topology. This work is the first to use functional imaging to explore the effects of a clinically relevant mutation on brain-wide network assembly in vivo. We show that graph analysis of spontaneous network activity is a sensitive method for revealing subtle changes to network architecture in response to genetic perturbations.