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INVESTIGATING NEURAL ARCHITECTURE AND CONNECTIVITY IN THE LARVAL ZEBRAFISH FOREBRAIN USING AN OPEN-SOURCE WHOLE-BRAIN ELECTRON MICROSCOPY DATASET
Mina Koçand 1 co-author
Koç University
FENS Forum 2026 (2026)
Barcelona, Spain
Board PS06-09PM-397
Presentation
Date TBA
Board: PS06-09PM-397
Event Information
Poster Board
PS06-09PM-397
Poster
View posterAbstract
Zebrafish is a small, transparent, genetically tractable vertebrate with optical access to the entire brain for imaging neural activity in vivo. Recent investigations have demonstrated that the zebrafish forebrain is not merely a relay station, but a sophisticated center for cognitively demanding tasks, including spatial representations and associative learning. Our lab’s latest preprint revealed that the zebrafish forebrain is hierarchically organized, where topographically organized forebrain regions receive and process sensory information differentially to guide behavior. However, the exact synaptic architecture that supports this functional hierarchy remains to be explored.
In this study, we utilize a whole-brain serial-section electron microscopy (EM) dataset of a 7-day-old zebrafish larva, which provides a complete neural catalog at nanometer resolution. By using the Connectome Annotation Versioning Engine (CAVE) for programmatic data mining, we developed an analytical pipeline to analyze zebrafish forebrain neurons. First, we focused on the connectivity between the preglomerular nucleus and the pallium. Our preliminary analysis reveals a high degree of structural heterogeneity within these circuits, suggesting a complex organization beyond simple sensory relay. We are currently utilizing network analysis to characterize how different neural populations within the preglomerular nucleus contribute to the broader forebrain hierarchy. This project provides a transformative bridge between synaptic architecture and vertebrate brain function, offering a comprehensive view of how structural connectivity constraints and enables neural computation.
In this study, we utilize a whole-brain serial-section electron microscopy (EM) dataset of a 7-day-old zebrafish larva, which provides a complete neural catalog at nanometer resolution. By using the Connectome Annotation Versioning Engine (CAVE) for programmatic data mining, we developed an analytical pipeline to analyze zebrafish forebrain neurons. First, we focused on the connectivity between the preglomerular nucleus and the pallium. Our preliminary analysis reveals a high degree of structural heterogeneity within these circuits, suggesting a complex organization beyond simple sensory relay. We are currently utilizing network analysis to characterize how different neural populations within the preglomerular nucleus contribute to the broader forebrain hierarchy. This project provides a transformative bridge between synaptic architecture and vertebrate brain function, offering a comprehensive view of how structural connectivity constraints and enables neural computation.
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