kugel: Update references

1 files changed, 51 insertions, 0 deletions

diff --git a/buch/papers/kugel/references.bib b/buch/papers/kugel/references.bib
index 7603f2f..07e4d5d 100644
--- a/buch/papers/kugel/references.bib
+++ b/buch/papers/kugel/references.bib
@@ -291,4 +291,55 @@ This photo was taken during studies that resulted in the publication: Hope, C, S
 	urldate = {2022-08-28},
 	date = {2013},
 	file = {Full Text:/Users/npross/Zotero/storage/A8XM56WK/Davari and Ahmadi - 2013 - New Implementation of Legendre Polynomials for Sol.pdf:application/pdf},
+}
+
+@article{srinivasan_estimating_1998,
+	title = {Estimating the spatial Nyquist of the human {EEG}},
+	volume = {30},
+	issn = {0743-3808, 1532-5970},
+	url = {http://link.springer.com/10.3758/BF03209412},
+	doi = {10.3758/BF03209412},
+	pages = {8--19},
+	number = {1},
+	journaltitle = {Behavior Research Methods, Instruments, \& Computers},
+	shortjournal = {Behavior Research Methods, Instruments, \& Computers},
+	author = {Srinivasan, Ramesh and Tucker, Don M. and Murias, Michael},
+	urldate = {2022-08-28},
+	date = {1998-03},
+	langid = {english},
+	file = {Full Text:/Users/npross/Zotero/storage/RCY73VUB/Srinivasan et al. - 1998 - Estimating the spatial Nyquist of the human EEG.pdf:application/pdf},
+}
+
+@misc{ruffini_spherical_2002,
+	title = {Spherical Harmonics Interpolation, Computation of Laplacians and Gauge Theory},
+	url = {http://arxiv.org/abs/physics/0206007},
+	doi = {10.48550/arXiv.physics/0206007},
+	abstract = {The aim in this note is to define an algorithm to carry out minimal curvature spherical harmonics interpolation, which is then used to calculate the Laplacian for multi-electrode {EEG} data analysis. The approach taken is to respect the data. That is, we implement a minimal curvature condition for the interpolating surface subject to the constraints determined from the multi-electrode data. We implement this approach using spherical harmonics interpolation. In this elegant example we show that minimization requirement and constraints complement each other to fix all degrees of freedom automatically, as occurs in gauge theories. That is, the constraints are respected, while only the orthogonal subspace minimization constraints are enforced. As an example, we discuss the application to interpolate control data and calculate the temporal sequence of laplacians from an {EEG} Mismatch Negativity ({MMN}) experiment (using an implementation of the algorithm in {IDL}).},
+	number = {{arXiv}:physics/0206007},
+	publisher = {{arXiv}},
+	author = {Ruffini, Giulio and Marco, Josep and Grau, Carles},
+	urldate = {2022-08-30},
+	date = {2002-06-03},
+	eprinttype = {arxiv},
+	eprint = {physics/0206007},
+	keywords = {Physics - Data Analysis, Statistics and Probability, Physics - Medical Physics, Quantitative Biology - Neurons and Cognition},
+	file = {arXiv Fulltext PDF:/Users/npross/Zotero/storage/R7Z5FP8D/Ruffini et al. - 2002 - Spherical Harmonics Interpolation, Computation of .pdf:application/pdf;arXiv.org Snapshot:/Users/npross/Zotero/storage/ESQCQXAJ/0206007.html:text/html},
+}
+
+@article{pascual-marqui_current_1988,
+	title = {Current Source Density Estimation and Interpolation Based on the Spherical Harmonic Fourier Expansion},
+	volume = {43},
+	issn = {0020-7454},
+	url = {https://doi.org/10.3109/00207458808986175},
+	doi = {10.3109/00207458808986175},
+	abstract = {A method for the spatial analysis of {EEG} and {EP} data, based on the spherical harmonic Fourier expansion ({SHE}) of scalp potential measurements, is described. This model provides efficient and accurate formulas for: (1) the computation of the surface Laplacian and (2) the interpolation of electrical potentials, current source densities, test statistics and other derived variables. Physiologically based simulation experiments show that the {SHE} method gives better estimates of the surface Laplacian than the commonly used finite difference method. Cross-validation studies for the objective comparison of different interpolation methods demonstrate the superiority of the {SHE} over the commonly used methods based on the weighted (inverse distance) average of the nearest three and four neighbor values.},
+	pages = {237--249},
+	number = {3},
+	journaltitle = {International Journal of Neuroscience},
+	author = {Pascual-marqui, Roberto D. and Gonzalez-andino, Sara L. and Valdes-sosa, Pedro A.},
+	urldate = {2022-08-30},
+	date = {1988-01-01},
+	note = {Publisher: Taylor \& Francis
+\_eprint: https://doi.org/10.3109/00207458808986175},
+	keywords = {cross-validated current source density (csd) estimation, cross-validated functional brain mapping, cross-validated laplacian estimation, {ROLANDO} {BISCAY}-{LIRIO}, source derivations, spatial analysis, spherical harmonic fourier expansion},
 }
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