Python for large-scale electrophysiology

Frontiers in Neuroinformatics

Volumn 2, Issue JAN, 2009, Pages

  Spacek, Martin ^a   Blanche, Tim ^b   Swindale, Nicholas ^a  

^a UNIVERSITY OF BRITISH COLUMBIA   (Canada)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

In vivo; Primary visual cortex; Python; Silicon polytrodes

Indexed keywords

EID: 70350099636     PISSN: 16625196     EISSN: None     Source Type: Journal    
DOI: 10.3389/neuro.11.009.2008     Document Type: Article

References (20)

1. Blanche, T. J. (2005). Large scale neuronal recording. Ph.D. dissertation, University of British Columbia, Vancouver, BC.
2. Blanche, T. J., Spacek, M. A., Hetke, J. F., and Swindale, N. V. (2005). Polytrodes: high-density silicon electrode arrays for large-scale multiunit recording. J. Neurophysiol. 93, 2987-3000.
3. Blanche, T. J., and Swindale, N. V. (2006). Nyquist interpolation improves neuron yield in multiunit recordings. J. Neurosci. Methods 155, 81-91.
4. Dayan, P., and Abbott, L. F. (2001). Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems. Cambridge, MA, MIT Press.
5. Golomb, S. W. (1967). Shift Register Sequences. San Francisco, Holden-Day.
6. Hetland, M. L. (2005). Beginning Python: From Novice to Professional. Berkeley, CA, Apress.
7. Jones, E., Oliphant, T., Peterson, P., et al. (2001). SciPy: open source scientific tools for Python. http://scipy.org.
8. Langtangen, H. P. (2008). Python Scripting for Computational Science, 3rd Edn. Berlin, Springer-Verlag.
9. Lutz, M. (2006). Programming Python, 3rd Edn. Sebastopol, CA, O'Reilly.
10. Mainen, Z. F., and Sejnowski, T. J. (1995). Reliability of spike timing in neocortical neurons. Science 268, 1503.
11. Peters, T. (2004). The Zen of Python. http://www.python.org/dev/peps/pep-0020.
12. Rappin, N., and Dunn, R. (2006). wxPython in Action. Greenwich, CT, Manning.
13. Schneidman, E., Berry, M. J. II, Segev, R., and Bialek, W. (2006). Weak pairwise correlations imply strongly correlated network states in a neural population. Nature 440, 1007-1012.
14. Shlens, J., Field, G. D., Gauthier, J. L., Grivich, M. I., Petrusca, D., Sher, A., Litke, A. M., and Chichilnisky, E. J. (2006). The structure of multi-neuron firing patterns in primate retina. J. Neurosci. 26, 8254-8266.
15. Spacek, M. A., Blanche, T. J., Seamans, J. K., and Swindale, N. V. (2007). Accounting for network states in cortex: are (local) pairwise correlations suffi cient? Soc. Neurosci. Abstr. 33, 790.1. http://swindale.ecc.ubc.ca/Publications.
16. Straw, A. D. (2008). Vision Egg: an open-source library for realtime visual stimulus generation. Front. Neuroinform. 2, 4.
17. Teeters, J. L., Harris, K. D., Millman, K. J., Olshausen, B. A., and Sommer, F. T. (2008). Data sharing for computational neuroscience. Neuroinformatics 6, 47-55.
18. VanRullen, R., and Thorpe, S. J. (2002). Surfi ng a spike wave down the ventral stream. Vis. Res. 42, 2593-2615.
19. Williams, P. E., Mechler, F., Gordon, J., Shapley, R., and Hawken, M. J. (2004). Entrainment to video displays in primary visual cortex of macaque and humans. J. Neurosci. 24, 8278-8288.
20. Wollman, D. E., and Palmer, L. A. (1995). Phase locking of neuronal responses to the vertical refresh of computer display monitors in cat lateral geniculate nucleus and striate cortex. J. Neurosci. Methods 60, 107-113.