Classification of action potentials in multi-unit intrafascicular recordings using neural network pattern-recognition techniques
- 1 January 1994
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Biomedical Engineering
- Vol. 41 (1) , 89-91
- https://doi.org/10.1109/10.277276
Abstract
Neural network pattern-recognition techniques were applied to the problem of identifying the sources of action potentials in multi-unit neural recordings made from intrafascicular electrodes implanted in cats. The network was a three-layer connectionist machine that used digitized action potentials as input. On average, the network was able to reliably separate 6 or 7 units per recording. As the number of units present in the recording increased beyond this limit, the number separable by the network remained roughly constant. The results demonstrate the utility of neural networks for classifying neural activity in multi-unit recordings.Keywords
This publication has 9 references indexed in Scilit:
- Optimal Recognition Of Neural WaveformsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- Analysis of single-unit firing patterns in multi-unit intrafascicular recordingsMedical & Biological Engineering & Computing, 1993
- Separation of action potentials in multiunit intrafascicular recordingsIEEE Transactions on Biomedical Engineering, 1992
- Chronically implanted intrafascicular recording electrodesAnnals of Biomedical Engineering, 1991
- Information contained in sensory nerve recordings made with intrafascicular electrodesIEEE Transactions on Biomedical Engineering, 1991
- Pattern classification using neural networksIEEE Communications Magazine, 1989
- An intrafascicular electrode for recording of action potentials in peripheral nervesAnnals of Biomedical Engineering, 1989
- Neural network models for pattern recognition and associative memoryNeural Networks, 1989
- An introduction to computing with neural netsIEEE ASSP Magazine, 1987