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Volumn 181, Issue 1, 2009, Pages 119-144

Automatic spike train analysis and report generation. An implementation with R, R2HTML and STAR

Author keywords

Extracellular recordings; Nonparametric analysis; Smoothing spline; Stimulus response

Indexed keywords

ANIMAL EXPERIMENT; ARTICLE; COCKROACH; CONTROLLED STUDY; INTRACELLULAR RECORDING; MALE; MARKUP LANGUAGE; NEUROPHYSIOLOGY; NONHUMAN; NONPARAMETRIC TEST; OLFACTORY DISCRIMINATION; PRIORITY JOURNAL; SPIKE WAVE; STATISTICAL ANALYSIS; STIMULUS RESPONSE;

EID: 67349278162     PISSN: 01650270     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jneumeth.2009.01.037     Document Type: Article
Times cited : (34)

References (55)
  • 3
    • 0023686914 scopus 로고
    • Maximum likelihood analysis of spike trains of interacting nerve cells
    • Brillinger D.R. Maximum likelihood analysis of spike trains of interacting nerve cells. Biol Cybern 59 (1988) 189-200
    • (1988) Biol Cybern , vol.59 , pp. 189-200
    • Brillinger, D.R.1
  • 7
    • 0033476673 scopus 로고    scopus 로고
    • Computing with data: concepts and challenges
    • Chambers J. Computing with data: concepts and challenges. Am Stat 53 (1999) 73-84
    • (1999) Am Stat , vol.53 , pp. 73-84
    • Chambers, J.1
  • 8
    • 23044523760 scopus 로고    scopus 로고
    • Users, programmers and statistical software
    • Chambers J.M. Users, programmers and statistical software. J Comput Graph Stat 9 (2000) 404-422
    • (2000) J Comput Graph Stat , vol.9 , pp. 404-422
    • Chambers, J.M.1
  • 12
    • 34250263445 scopus 로고
    • Smoothing noisy data with spline functions. estimating the correct degree of smoothing by the method of generalized cross-validation
    • Craven P., and Wahba G. Smoothing noisy data with spline functions. estimating the correct degree of smoothing by the method of generalized cross-validation. Numer Math 31 (1979) 377-404
    • (1979) Numer Math , vol.31 , pp. 377-404
    • Craven, P.1    Wahba, G.2
  • 13
    • 1842665178 scopus 로고    scopus 로고
    • Confidence intervals for nonparametric curve estimates: toward more uniform pointwise coverage
    • Cummins D.J., Filloon T.G., and Nychka D. Confidence intervals for nonparametric curve estimates: toward more uniform pointwise coverage. J Am Stat Assoc 96 (2001) 233-246
    • (2001) J Am Stat Assoc , vol.96 , pp. 233-246
    • Cummins, D.J.1    Filloon, T.G.2    Nychka, D.3
  • 20
    • 0002318041 scopus 로고
    • An approach to the quantitative analysis of electrophysiological data from single neurons
    • Gerstein G.L., and Kiang N.Y.S. An approach to the quantitative analysis of electrophysiological data from single neurons. Biophys J 1 (1960) 15-28
    • (1960) Biophys J , vol.1 , pp. 15-28
    • Gerstein, G.L.1    Kiang, N.Y.S.2
  • 21
    • 0000457666 scopus 로고
    • Cross-validating non-gaussian data
    • Gu C. Cross-validating non-gaussian data. J Comput Graph Stat 1 (1992) 169-179
    • (1992) J Comput Graph Stat , vol.1 , pp. 169-179
    • Gu, C.1
  • 23
    • 44449167998 scopus 로고    scopus 로고
    • Smoothing noisy data via regularization: statistical perspectives
    • Gu C. Smoothing noisy data via regularization: statistical perspectives. Inverse Problems 24 (2008) 034002
    • (2008) Inverse Problems , vol.24 , pp. 034002
    • Gu, C.1
  • 24
    • 0035622815 scopus 로고    scopus 로고
    • Cross-validating non-gaussian data: generalized approximate cross-validation revisited
    • Gu C., and Xiang D. Cross-validating non-gaussian data: generalized approximate cross-validation revisited. J Comput Graph Stat 10 (2001) 581-591
    • (2001) J Comput Graph Stat , vol.10 , pp. 581-591
    • Gu, C.1    Xiang, D.2
  • 25
    • 0030305457 scopus 로고    scopus 로고
    • R: a language for data analysis and graphics
    • Ihaka R., and Gentleman R. R: a language for data analysis and graphics. J Graph Comput Stat 5 (1996) 299-314
    • (1996) J Graph Comput Stat , vol.5 , pp. 299-314
    • Ihaka, R.1    Gentleman, R.2
  • 26
    • 0030447513 scopus 로고    scopus 로고
    • Point process models of single-neuron discharges
    • Johnson D. Point process models of single-neuron discharges. J Comput Neurosci 3 (1996) 275-299
    • (1996) J Comput Neurosci , vol.3 , pp. 275-299
    • Johnson, D.1
  • 30
    • 0015000439 scopus 로고
    • Some results on tchebycheffian spline functions
    • Kimeldorf G., and Wahba G. Some results on tchebycheffian spline functions. J Math Anal Appl 33 (1971) 82-95
    • (1971) J Math Anal Appl , vol.33 , pp. 82-95
    • Kimeldorf, G.1    Wahba, G.2
  • 31
    • 59549103885 scopus 로고    scopus 로고
    • The R2HTML package
    • Lecoutre E. The R2HTML package. R News 3 (2003) 33-36
    • (2003) R News , vol.3 , pp. 33-36
    • Lecoutre, E.1
  • 32
    • 34250748463 scopus 로고    scopus 로고
    • Rstream: streams of random numbers for stochastic simulation
    • L'Ecuyer P., and Leydold J. Rstream: streams of random numbers for stochastic simulation. R News 5 (2005) 16-20
    • (2005) R News , vol.5 , pp. 16-20
    • L'Ecuyer, P.1    Leydold, J.2
  • 33
    • 0036877268 scopus 로고    scopus 로고
    • An objected-oriented random-number package with many long streams and substreams
    • L'Ecuyer P., Simard R., Chen E.J., and Kelton W.D. An objected-oriented random-number package with many long streams and substreams. Oper Res 50 (2002) 1073-1075
    • (2002) Oper Res , vol.50 , pp. 1073-1075
    • L'Ecuyer, P.1    Simard, R.2    Chen, E.J.3    Kelton, W.D.4
  • 34
    • 67349273879 scopus 로고    scopus 로고
    • Leydold J. Rstream: streams of random numbers. R package version 1.2.2; 2007
    • Leydold J. Rstream: streams of random numbers. R package version 1.2.2; 2007.
  • 39
    • 33845606053 scopus 로고
    • Bayesian confidence intervals for smoothing splines
    • Nychka D. Bayesian confidence intervals for smoothing splines. J Am Stat Assoc 83 (1988) 1134-1143
    • (1988) J Am Stat Assoc , vol.83 , pp. 1134-1143
    • Nychka, D.1
  • 40
    • 0012346731 scopus 로고
    • Statistical models for earthquake occurrences and residual analysis for point processes
    • Ogata Y. Statistical models for earthquake occurrences and residual analysis for point processes. J Am Stat Assoc 83 (1988) 9-27
    • (1988) J Am Stat Assoc , vol.83 , pp. 9-27
    • Ogata, Y.1
  • 41
    • 67349177610 scopus 로고    scopus 로고
    • Peng RD. CacheSweave: tools for caching sweave computations. R package version 0.4-3; 2007
    • Peng RD. CacheSweave: tools for caching sweave computations. R package version 0.4-3; 2007.
  • 42
    • 0014109171 scopus 로고
    • Neuronal spike trains and stochastic point processes. I the single spike train
    • Perkel D.H., Gerstein G.L., and Moore G.P. Neuronal spike trains and stochastic point processes. I the single spike train. Biophys J 7 (1967) 391-418
    • (1967) Biophys J , vol.7 , pp. 391-418
    • Perkel, D.H.1    Gerstein, G.L.2    Moore, G.P.3
  • 43
    • 0014104894 scopus 로고
    • Neuronal spike trains and stochastic point processes. II. Simultaneous spike trains
    • Perkel D.H., Gerstein G.L., and Moore G.P. Neuronal spike trains and stochastic point processes. II. Simultaneous spike trains. Biophys J 7 (1967) 419-440
    • (1967) Biophys J , vol.7 , pp. 419-440
    • Perkel, D.H.1    Gerstein, G.L.2    Moore, G.P.3
  • 46
    • 67349238053 scopus 로고    scopus 로고
    • Rossini A, Tierney L, Li N. Simple parallel statistical computing in R, UW biostatistics working paper series 193. University of Washington; 2003.
    • Rossini A, Tierney L, Li N. Simple parallel statistical computing in R, UW biostatistics working paper series 193. University of Washington; 2003.
  • 47
    • 0000589160 scopus 로고
    • Local likelihood estimation
    • Tibshirani R., and Hastie T. Local likelihood estimation. J Am Stat Assoc 82 (1987) 559-567
    • (1987) J Am Stat Assoc , vol.82 , pp. 559-567
    • Tibshirani, R.1    Hastie, T.2
  • 48
    • 67349228285 scopus 로고    scopus 로고
    • Tierney L, Rossini AJ, Li N, Sevcikova H. Snow: simple network of workstations. R package version 0.3-3; 2008
    • Tierney L, Rossini AJ, Li N, Sevcikova H. Snow: simple network of workstations. R package version 0.3-3; 2008.
  • 49
    • 19544394715 scopus 로고    scopus 로고
    • The string method of burst identification in neuronal spike trains
    • Turnbull L., Dian E., and Gross G. The string method of burst identification in neuronal spike trains. J Neurosci Methods 145 (2005) 23-35
    • (2005) J Neurosci Methods , vol.145 , pp. 23-35
    • Turnbull, L.1    Dian, E.2    Gross, G.3
  • 50
    • 0346490012 scopus 로고    scopus 로고
    • Statistical analysis of temporal evolution in single-neuron firing rates
    • Ventura V., Carta R., Kass R.E., Gettner S.N., and Olson C.R. Statistical analysis of temporal evolution in single-neuron firing rates. Biostat 3 (2002) 1-20
    • (2002) Biostat , vol.3 , pp. 1-20
    • Ventura, V.1    Carta, R.2    Kass, R.E.3    Gettner, S.N.4    Olson, C.R.5
  • 51
    • 0000939344 scopus 로고
    • Bayesian "confidence intervals" for the cross-validated smoothing spline
    • Wahba G. Bayesian "confidence intervals" for the cross-validated smoothing spline. J R Stat Soc Ser B (Methodol) 45 (1983) 133-150
    • (1983) J R Stat Soc Ser B (Methodol) , vol.45 , pp. 133-150
    • Wahba, G.1
  • 53
    • 47949099044 scopus 로고    scopus 로고
    • An implementation of Bayesian adaptive regression splines (BARS) in C with S and R wrappers
    • Wallstrom G., Liebner J., and Kass R.E. An implementation of Bayesian adaptive regression splines (BARS) in C with S and R wrappers. J Stat Softw 26 (2007) 1-21
    • (2007) J Stat Softw , vol.26 , pp. 1-21
    • Wallstrom, G.1    Liebner, J.2    Kass, R.E.3
  • 55
    • 21444449622 scopus 로고    scopus 로고
    • A generalized approximate cross validation for smoothing splines with non-gaussian data
    • Xiang D., and Wahba G. A generalized approximate cross validation for smoothing splines with non-gaussian data. Stat Sinica 6 (1996) 675-692
    • (1996) Stat Sinica , vol.6 , pp. 675-692
    • Xiang, D.1    Wahba, G.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.