Real-Time Calcium Imaging Based Neural Decoding with a Support Vector Machine

We present a novel real-time neural decoding system for calcium imaging data. Miniature calcium imaging is of great utility for examining neural activity in populations of animals. Our real-time neural decoding system is developed using a carefully-designed support vector machine (SVM) subsystem together with dataflow-based techniques for system design, which capture the high-level structure of the application and enable powerful system-level analysis and optimization. Through extensive experiments, we have evaluated the proposed system using calcium imaging datasets in which neural activities of D1 medium spiny neurons (MSNs) in the dorsal striatum were recorded. The results show that the performance of the proposed system is significantly better than that of previously developed neural decoding systems for calcium imaging.