Neural Decoding on Imbalanced Calcium Imaging Data with a Network of Support Vector Machines.

We present a novel neural decoding system for calcium imaging data. Miniature calcium imaging is of great utility for examining population neural activity of animals. Our neural decoding system is developed using a carefully-designed support vector machine 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. Also, we introduce a framework for handling imbalanced data. This addresses a problem of imbalanced datasets, which arises commonly in neural decoding applications, as well as in a wide variety of other applications in biomedical engineering and advanced robotics. We developed an ensemble learning based method to tackle this problem. The proposed framework systemically incorporates two heterogeneous model characteristics into a combined model. Through extensive experiments, we evaluate the proposed system using calcium imaging datasets in which neural activities of D1 medium spiny neurons in the dorsal striatum were recorded. The results show that the F 1 score of the proposed system is significantly better than those of previously developed neural decoding systems for calcium imaging.

Real-Time Neuron Detection and Neural Signal Extraction Platform for Miniature Calcium Imaging.

Real-time neuron detection and neural activity extraction are critical components of real-time neural decoding. In this paper, we propose a novel real-time neuron detection and activity extraction system using a dataflow framework to provide real-time performance and adaptability to new algorithms and hardware platforms. The proposed system was evaluated on simulated calcium imaging data, calcium imaging data with manual annotation, and calcium imaging data of the anterior lateral motor cortex. We found that the proposed system accurately detected neurons and extracted neural activities in real time without any requirement for expensive, cumbersome, or special-purpose computing hardware. We expect that the system will enable cost-effective, real-time calcium imaging-based neural decoding, leading to precise neuromodulation.