Spike Sorting Platform
End User Community
We are now working to disseminate this work - seeking to partner with any labs interested in using the NGNI-v1 platform for experimental work. If you are interested, please contact: email@example.com
Spike Sorting is the process of deinterleaving a recorded neural signal in order to determine the firing patterns of individual neurons from the aggregate spike stream.
The NGNI platform is an end-to-end solution for on-node, real-time spike sorting. By using a compact, onboard (template based) spike sorting engine, together with offline training (WaveClus-based), a low power real-time solution is achievable.
- 32-channel neural recording/streaming
- On-node, realtime template-based spike sorting
- Proprietary template building engine (based on WaveClus)
- Onboard template memory, 18.4kbit (4 templates per channel)
- Low latency (0.3ms) SPI output
- Low output data-rate - suitable for wireless communication
- MicroSD logging and control module for standalone deployment (no PC or tether required).
- Signal acquisition systems for electrophysiology
- Large-scale recording applications (multi-probe, multi-channel)
- Realtime brain machine interface applications
- Closed loop low-latency biofeedback
- Williams I, Luan S, Jackson A, Constandinou TG, 2015, "A Scalable 32 Channel Neural Recording and Real-time FPGA Based Spike Sorting System", IEEE Biomedical Circuits & Systems (BioCAS) Conference, Pages: 187-191
- Jackson A, Constandinou TG, Eftekhar A, Quiroga RQ, Navajas JA, 2015, System for a Brain-Computer Interface
- Luan S, Williams Y, Maslik M, Liu Y, Carvalho F, Jackson A, Quiroga RR, Constandinou, TG, 2017, Compact Standalone Platform for Neural Recording with Real-Time Spike Sorting and Data Logging, bioRxiv:186627