Spike Sorting Platform
Interested in using?
If this platform could be useful to your research, please contact us. We are currently seeking labs to beta test and/or adopt the platform for experimental work.
Overview
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.
Features
- 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).
Applications
- Signal acquisition systems for electrophysiology
- Large-scale recording applications (multi-probe, multi-channel)
- Realtime brain machine interface applications
- Closed loop low-latency biofeedback
References
- Luan S, Williams I, Maslik M, Liu Y, De Carvalho F, Jackson A, Quiroga RQ, Constandinou TG, 2018, Compact standalone platform for neural recording with real-time spike sorting and data logging, J Neural Eng, Vol: 15, No: 4, 046014
- Jackson A, Constandinou TG, Eftekhar A, Quiroga RQ, Navajas JA, 2015, System for a Brain-Computer Interface, PCT/WO2015/114347 A1 (Filed January 2014)