Validation of adaptive threshold spike detector for neural recording

Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

Volumn 26 VI, Issue , 2004, Pages 4079-4082

  Watkins, Paul T ^a   Santhanam, Gopal ^b   Shenoy, Krishna V ^b,c   Harrison, Reid R ^a  

^a University of Utah   (United States)

^b Stanford University   (United States)

^c STANFORD UNIVERSITY   (United States)

Author keywords

Action potential; Integrated circuit; Neural recording; Spike detection

Indexed keywords

ALGORITHMS; COMPUTER SIMULATION; MATHEMATICAL MODELS; MICROPROCESSOR CHIPS; PARAMETER ESTIMATION; SPURIOUS SIGNAL NOISE;

ACTION POTENTIAL; NEURAL RECORDING; SPIKE DETECTION;

NEURAL NETWORKS;

EID: 11144314777     PISSN: 05891019     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (5)

1. K. S. Guillory, R. A. Normann, "A 100-channel system for real time detection and storage of extracellular spike waveforms," J. Neuroscience Methods, vol. 91, pp. 21-29, 1999.
2. M. S. Fee, P. P. Mitra, D. Kleinfeld, "Variability of Extracellular Spike Waveforms of Cortical Neurons," J. Neurophysiology, vol. 76(6), pp. 3823-3833, 1996.
3. R. R. Harrison, "A Low-Power Integrated Circuit for Adaptive Detection of Action Potentials in Noisy Signals," in Proc. 2003 Intl. Conference of the IEEE Engineering in Medicine and Biology Society, Cancun, Mexico, Sept. 2003.
4. S. Shoham, M. R. Fellows, R. A. Normann, "Robust, automatic spike sorting using mixtures of multivariate t-distributions," J. Neuroscience Methods, vol. 127, pp. 111-122, 2003.
5. M. Sahani, "Latent Variable Models for Neural Data Analysis." Ph.D. Dissertation, Computation and Neural Systems. California Institute of Technology, 1999.