Skip to content. | Skip to navigation

Sections
Personal tools
You are here: Home Publications

Publications

Since 2008 the following publications and online resources came out that are based on data sets shared on this website.

The list is mainly the result of internet searches we sometimes perform. Please let us know of items that should be added to this list via the contact form.


A.  Peer reviewed journal publications

 

34) Spike avalanches in vivo suggest a driven, slightly subcritical brain state
Priesemann Viola, Wibral Michael, Valderrama Mario, Pr∂pper Robert, Le Van Quyen Michel, Geisel Theo, Triesch Jochen, Nikolic Danko, Munk Matthias Hans Joachim
Frontiers in Systems Neuroscience, Vol. 8 (2014).
DOI=10.3389/fnsys.2014.00108
http://journal.frontiersin.org/Journal/10.3389/fnsys.2014.00108/abstract


33) Spatially distributed local fields in the hippocampus encode rat position
G. Agarwal, I. H. Stevenson, A. Berényi, K. Mizuseki, G. Buzsáki, F. T. Sommer
Science 344 (2014): 626-630.
http://www.sciencemag.org/content/344/6184/626.abstract

32) Neurosharing: large-scale data sets (spike, LFP) recorded from the hippocampal-entorhinal system in behaving rats
Kenji Mizuseki, Kamran Diba, Eva Pastalkova, Jeff Teeters, Anton Sirota, György Buzsáki
http://f1000research.com/articles/3-98/v2<

31) Multichannel Electrophysiological Spike Sorting via Joint Dictionary Learning and Mixture Modeling
Carlson, D.E.; Vogelstein, J.T.; Qisong Wu; Wenzhao Lian; Mingyuan Zhou; Stoetzner, C.R.; Kipke, D.; Weber, D.; Dunson, D.B.; Carin, L.,
Biomedical Engineering, IEEE Transactions on , vol.61, no.1, pp.41,54, Jan. 2014
doi: 10.1109/TBME.2013.2275751
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=true&arnumber=6571240

30) The Database for Reaching Experiments and Models
Walker B, Kording K (2013). PLoS ONE 8(11): e78747. doi:10.1371/journal.pone.0078747
http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0078747

29) Sorting Electrophysiological Data via Dictionary Learning & Mixture Modeling
Carin, L.; Wu, Q.; Carlson, D.; Lian, W.; Stoetzner, C.; Kipke, D.; Weber, D.; Vogelstein, J.; Dunson, D.
Biomedical Engineering, IEEE Transactions on , vol.PP, no.99, pp.1,1, 0 (Accepted for publication, 2013)
doi:10.1109/TBME.2013.2275751
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6571240&isnumber=4359967

28) Inferring nonlinear neuronal computation based on physiologically plausible inputs
McFarland JM, Cui Y, Butts DA
PLoS Computational Biology 9(7): e1003142. (2013)
http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003143

27) Region-Based Artificial Visual Attention in Space and Time
Tünnermann, J., & Mertsching, B.
Cognitive Computation, DOI 10.1007/s12559-013-9220-5  (2013).
http://link.springer.com/article/10.1007/s12559-013-9220-5

26) Detecting cell assemblies in large neuronal populations
Vítor Lopes-dos-Santos, Sidarta Ribeiro, Adriano B.L. Tort
Journal of Neuroscience Methods, ISSN 0165-0270, April 29, 2013
http://dx.doi.org/10.1016/
http://www.sciencedirect.com/science/article/pii/S0165027013001489


25) Population-wide distributions of neural activity during perceptual decision-making
Adrien Wohrer, Mark D. Humphries, Christian K. Machens
Progress in Neurobiology.  Volume 103, April 2013, Pages 156–193
http://www.sciencedirect.com/science/article/pii/S0301008212001505


24) Computational Models of Human Visual Attention and Their Implementations: A Survey
Akisato Kimura, Ryo Yonetani, Takatsugu Hirayama
IEICE Trans. Inf. & Syst., Vol.E96-D, No.3 March 2013
http://repository.kulib.kyoto-u.ac.jp/dspace/bitstream/2433/171749/1/IEICE_E96-D_3_562.pdf
http://search.ieice.org/bin/summary.php?id=e96-d_3_562&category=D&lang=E&year=2013

23) A Simple Algorithm for Averaging Spike Trains
Hannah Julienne, Conor Houghton
Journal of Mathematical Neuroscience (2013) 3:3 DOI 10.1186/2190-8567-3-3
http://www.mathematical-neuroscience.com/content/pdf/2190-8567-3-3.pdf

22) Theta-associated high-frequency oscillations (110–160 Hz) in the hippocampus and neocortex
Adriano B.L. Tort, Robson Scheffer-Teixeira, Bryan C. Souza, Andreas Draguhn, Jurij Brankack
Progress in Neurobiology 100 (2013) 1–14
http://repositorio.ufrn.br:8080/jspui/bitstream/1/6198/1/AdrianoBLT_ICE_Theta-associated2013.pdf

21) On High-Frequency Field Oscillations (>100 Hz) and the Spectral Leakage of Spiking Activity
Robson Scheffer-Teixeira, Hindiael Belchior, Richardson N. Leao, Sidarta Ribeiro, and Adriano B. L. Tort
The Journal of Neuroscience, January 23, 2013; 33(4):1535–1539
http://www.jneurosci.org/content/33/4/1535.full.pdf

20) Functional Connectivity and Tuning Curves in Populations of Simultaneously Recorded Neurons
Ian H. Stevenson, Brian M. London, Emily R. Oby, Nicholas A. Sachs, Jacob Reimer, Bernhard Englitz, Stephen V. David, Shihab A. Shamma, Timothy J. Blanche, Kenji Mizuseki, Amin Zandvakili, Nicholas G. Hatsopoulos, Lee E. Miller, Konrad P. Kording
PLoS Comput Biol 8(11): e1002775. doi:10.1371/journal.pcbi.1002775 (2012)
http://www.physiology.northwestern.edu/secondlevel/miller/publications/media/PLoSCompBiolv8e1002775.pdf

19) Action Potential Waveform Variability Limits Multi-Unit Separation in Freely Behaving Rats

Peter Stratton, Allen Cheung, Janet Wiles, Eugene Kiyatkin, Pankaj Sah, Francois Windels
Plos One 7 (6) e38482 (2012)
http://www.plosone.org/article/info:doi/10.1371/journal.pone.0038482


18) Spike sorting of heterogeneous neuron types by multimodality-weighted PCA and explicit robust variational Bayes

Takekawa Takashi, Isomura Yoshikazu, Fukai Tomoki
Frontiers in Neuroinformatics (2012) Vol 6, No. 5.; doi: 10.3389/fninf.2012.00005
http://www.frontiersin.org/Journal/Abstract.aspx?s=752&name=neuroinformatics&ART_DOI=10.3389/fninf.2012.00005

17) State-of-the-art in Visual Attention Modeling

Ali Borji and Laurent Itti
IEEE Transactions on Pattern Analysis and Machine Intelligence
http://doi.ieeecomputersociety.org/10.1109/TPAMI.2012.89

16) Spatiotemporal receptive fields of cells in V1 are optimally shaped for stimulus velocity estimation
Giacomo Cocci, Davide Barbieri, Alessandro Sarti
J. Opt. Soc. Am. A 29, 130-138 (2012)
http://www.opticsinfobase.org/josaa/abstract.cfm?URI=josaa-29-1-130

15) Measuring the Quality of Neuronal Identification in Ensemble Recordings
Samuel A. Neymotin, William W. Lytton, Andrey V. Olypher, and André A. Fenton
The Journal of Neuroscience, 9 November 2011, 31(45): 16398-16409;
doi: 10.1523/​JNEUROSCI.4053-11.2011
http://www.jneurosci.org/content/31/45/16398.short

14) A non-parametric method for automatic neural spike clustering based on the non-uniform distribution of the data

Z Tiganj and M Mboup
Journal of Neural Engineering (2011) 8:066014 (13pp), doi:10.1088/1741-2560/8/6/066014
http://stacks.iop.org/JNE/8/066014

13) Kalman filter mixture model for spike sorting of non-stationary data
A. Calabrese and L. Paninski
Journal of Neuroscience Methods (2011) 196:159-169
http://www.sciencedirect.com

12) 1/f Neural Noise Reduction and Spike Feature Extraction using a Subset of Informative Samples
Annals of Biomedical Engineering 39 (2011): 1264-1277
Z. Yang, L. Hoang, Q. Zhao, E. Keefer, W. Liu
http://www.ece.nus.edu.sg/stfpage/eleyangz/ABME_11.pdf


11) Spike-Train Communities: Finding Groups of Similar Spike Trains
Mark D. Humphries
Journal of Neuroscience 9 February 2011, 31 (6):2321-2336
DOI:10.1523/​JNEUROSCI.2853-10.201
http://www.jneurosci.org/content/31/6/2321.short

10) Eye Movements Show Optimal Average Anticipation with Natural Dynamic Scenes

Cognitive Computation, 2011
Eleonora Vig, Michael Dorr, Thomas Martinetz, Erhardt Barth
DOI: 10.1007/s12559-010-9061-4
http://www.springerlink.com/content/73l4j324g63150n1/

 

9) Gaussian process modulated renewal processes

V. Rao and Y. W. Teh
Advances In Neural Information Processing Systems, 2011
http://books.nips.cc/papers/files/nips24/NIPS2011_1333.pdf

 

8) On the analysis of multi-channel neural spike data

B. Chen, D. Carlson and L. Carin
Advances in Neural Information Processing Systems, 2011
http://books.nips.cc/papers/files/nips24/NIPS2011_0590.pdf


7) A stochastic model of human visual attention with a dynamic Bayesian network
A. Kimura, D. Pang, T. Takeuchi, K. Miyazato, K. Kashino, J. Yamato
IEEE Transactions on pattern analysis and machine intelligence, Submitted 2010.
http://arxiv.org/pdf/1004.0085 [PDF]

6) Generation of Spatiotemporally Correlated Spike Trains and Local Field Potentials Using a Multivariate Autoregressive Process
Diego A. Gutnisky and Kresimir Josic
J Neurophysiol 103: 2912-2930, 2010. doi:10.1152/jn.00518.2009
http://jn.physiology.org/cgi/content/full/103/5/2912

5) A Continuous Entropy Rate Estimator for Spike Trains Using a K-Means-Based Context Tree
Tiger W. Lin and George N. Reeke
Neural Computation
Vol. 22, No. 4, April 2010, Pages 998-1024 (doi:10.1162/neco.2009.11-08-912)
http://www.ncbi.nlm.nih.gov/pubmed/19922298

4) Accurate spike sorting for multi-unit recordings
Takashi Takekawa , Yoshikazu Isomura, Tomoki Fukai
European Journal of Neuroscience
Vol. 31, No. 2, January 2010, pages 263 - 272
http://www3.interscience.wiley.com/journal/123239648/abstract

3) Of bits and wows: A Bayesian theory of surprise with applications to attention
Pierre Baldi and Laurent Itti
Neural Networks
Volume 23, Issue 5, June 2010, Pages 649-666
http://linkinghub.elsevier.com/retrieve/pii/S0893608009003256

2) ePPR: a new strategy for the characterization of sensory cells from input/output data
Joaquin Rapela, Gidon Felsen, Jon Touryan, Jerry M. Mendel, Norberto M. Grzywacz
Network: Computation in Neural Systems.
Vol. 21, No. 1-2, Pages 35-90
http://www.ncbi.nlm.nih.gov/pubmed/20735338


1) A new spike detection algorithm for extracellular neural recordings
Shahjahan Shahid, Jacqueline Walker, Leslie S Smith
Journal of IEEE Transactions on Biomedical Engineering; June 2009
http://www.ncbi.nlm.nih.gov/pubmed/19622433

 

B.  Book chapters

 

2) Dynamic Saliency Models and Human Attention: A Comparative Study on Videos
Nicolas Riche, Matei Mancas, Dubravko Culibrk, Vladimir Crnojevic, Bernard Gosselin, Thierry Dutoit
Lecture Notes in Computer Science Volume 7726, 2013, pp 586-598
Springer Berlin Heidelberg
http://link.springer.com/chapter/10.1007/978-3-642-37431-9_45
http://dx.doi.org/10.1007/978-3-642-37431-9_45
http://tcts.fpms.ac.be/publications/papers/2012/accv2012_nrmmbgtd.pdf

1) From Saliency to Eye Gaze: Embodied Visual Selection for a Pan-Tilt-Based Robotic Head
Matei Mancas, Fiora Pirri, Matia Pizzoli
In: Advances in Visual Computing, Lecture Notes in Computer Science; Vol. 6938, pp. 135-146. 2011
Doi: 10.1007/978-3-642-24028-7_13
Springer Berlin / Heidelberg
http://dx.doi.org/10.1007/978-3-642-24028-7_13

 

C.  Conference presentations or abstracts

 

27) Comparison of visual saliency models for compressed video
Sayed Hossein Khatoonabadi, Ivan V. Bajic ́, Yufeng Shan
Accepted for presentation at IEEE ICIP 2014
http://mcl.ensc.sfu.ca/pubs/kbs_ICIP2014.pdf

26) Predicting where we look from spatiotemporal gaps
Ryo Yonetani, Hiroaki Kawashima, Takashi Matsuyama
Proceeding ICMI '13 Proceedings of the 15th ACM on International conference on multimodal interaction
http://dl.acm.org/citation.cfm?id=2522853

25) Compressive Multiplexing of Correlated Signals
A. Ahmed and J. Romberg
In Proceedings of CoRR. 2013
http://arxiv.org/abs/1308.5146

24) Overview of eye tracking datasets
Stefan Winkler and Ramanathan Subramanian
Proc. 5th International Workshop on Quality of Multimedia Experience (QoMEX), Klagenfurt, Austria, July 3-5, 2013.
http://stefan.winkler.net/Publications/qomex2013eye.pdf

23) Neural decoding of movement targets by unsorted spike trains
Zhiming Xu, Kai Keng Ang, and Cuntai Guan
38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Vancouver, Canada, May 26-31, 2013.
http://iipl.tk/paper/ICASSP2013/pdfs/0000954.pdf

22) Compressive Multiplexers for Correlated Signals
Ali Ahmed and Justin Romberg
Signals, Systems and Computers (ASILOMAR), 2012 Conference Record of the Forty Sixth Asilomar Conference on
DOI: 10.1109/ACSSC.2012.6489159 (2012), Page(s): 963-967
http://www.aliahmed.org/pdf/conf2.pdf

21) Automatic classification of audio data using nonlinear neural response models
Jörg-Hendrik Bach, Arne-Freerk Meyer, Duncan McElfresh, Jörn Anemüller
International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Kyoto, Japan, March 25 - 30, 2012.
http://www.icassp2012.org/Papers/ViewPapers.asp?PaperNum=3285
http://www.staff.uni-oldenburg.de/joerg-hendrik.bach/publications/BachEtAl_ICASSP2012.pdf

20) Adaptive Object Tracking by Learning Background Context
Ali Borji, Simone Frintrop, Dicky N. Sihite, Laurent Itti
CVPR 2012, Egocentric Vision workshop.
http://ilab.usc.edu/~borji/Publications.html

19) Compressive sampling of correlated signals
Ahmed, A. and Romberg, J.
Signals, Systems and Computers (ASILOMAR) 2011 Conference, pp.1188-1192
doi: 10.1109/ACSSC.2011.6190203
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6190203&isnumber=6189941

18) The space of neurons
James Gillespie and Conor Houghton
Mathematical Neuroscience 2011, Edinburgh, Scotland, April 11-13, 2011.
www.maths.tcd.ie/~mnl/papers/tcd-mnl-18a.pdf
http://www.maths.tcd.ie/~mnl/papers/tcd-mnl-18a.pdf

17) Gaussian process modulated renewal processes
Vinayak Rao
Advances in Neural Information Processing Systems 24 (NIPS, 2011 conference).
http://books.nips.cc/papers/files/nips24/NIPS2011_1333.pdf

16) On the Analysis of Multi-Channel Neural Spike Data
Bo Chen, David Carlson, Lawrence Carin
Advances in Neural Information Processing Systems 24 (NIPS, 2011 conference).
http://books.nips.cc/papers/files/nips24/NIPS2011_0590.pdf

15) Fast orientation tuning in mammalian V1 neurons under high-frequency natural image stimulation
Iyer, A.V. and Grzywacz, N.M.
Annual Joint Symposium On Neural Computation 2011, UC San Diego, Institute for Neural Computation
http://inc.ucsd.edu/jsnc_2011.html
www.jsnc.caltech.edu/2011/abstracts/iyer-a.pdf

14) Human-motion saliency in multi-motion scenes and in close interaction
M. Mancas, F. Pirri, M. Pizzoli
Proceeding of the 9th International Gesture Workshop on Gesture in Embodied Communication and Human-Computer Interaction, Athens, Greece, May 2011
http://tcts.fpms.ac.be/publications/regpapers/2011/mmfpmp_isvc_LNCS.pdf

13) Hardware Accelerated Visual Attention Algorithm
P. Akselrod, F. Zhao, I. Derekli, C. Farabet, B. Martini, Y. LeCun, Eugenio Culurciello
Proc. Conference on Information Sciences and Systems (CISS), IEEE, Baltimore, 2011
http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=05766191

12) Towards guiding principles in workflow design to facilitate collaborative projects involving massively parallel electrophysiological data
Michael Denker, Andrew Davison, Markus Diesmann, Sonja Grün
Twentieth Annual Computational Neuroscience Meeting: CNS*2011
BMC Neuroscience 2011, 12 (Suppl 1):P131
http://www.biomedcentral.com/1471-2202/12/S1/P131

11) Hardware Accelerated Visual Attention Algorithm
P. Akselrod, F. Zhao, I. Derekli, C. Farabet, B. Martini, Y. LeCun, E. Culurciello
Proc. Conference on Information Sciences and Systems (CISS’11), IEEE, Baltimore, 2011
http://data.clement.farabet.net/pubs/ciss11.pdf


10) Re-testing the energy model: identifying features and nonlinearities of complex cells
Tim Lochmann, Joseph N. Stember,  Tim Blanche, Daniel A. Butts
COSYNE 2010, Poster
http://www.clfs.umd.edu/biology/ntlab/NTlab/Cosyne2010_files/Cosyne2010_V1_small.pdf

9) A dataset and evaluation methodology for visual saliency in videos
J. Li, Y. Tiang, T. Huang, W. Gao
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo, IEEE Press
http://dl.acm.org/citation.cfm?id=1699033


8) Cepstrum of Bispectrum Spike Detection applied to Extracellular Signals with Concurrent Intracellular Signals
Shahjahan Shahid and Leslie S. Smith
BMC Neuroscience Vol. 10, Supplement 1, P59, DOI 10.1186/1471-2202-10-S1-P59
Eighteenth Annual Computational Neuroscience Meeting: CNS*2009
http://www.springerlink.com/content/86163265j5323p25/


7) Assessing the effectiveness of Cepstrum of Bispectrum based spike detection on simultaneously recorded intra- and extra- cellularly recorded data
Leslie S. Smith and Shahjahan Shahid
Poster presentation, SfN09.
http://www.carmen.org.uk/publications/SFN09-poster-final-ls.pdf

6) Real-time estimation of human visual attention with dynamic Bayesian network and MCMC-based particle filter
Kouji Miyazato, Akisato Kimura, Shigeru Takagi, Junji Yamato
2009 IEEE International Conference on Multimedia and Expo (ICME 2009)
http://www.brl.ntt.co.jp/people/akisato/pdf/icme2009miyazato.pdf

5) Real time estimation of human visual attention with MCMC-based particle filter
Kouji Miyazato, Akisato Kimura, Shigeru Takagi, Junji Yamato, and Kunio Kashino
MIRU2009, The 12th International Conference on Image Recognition
Meeting on Image Recognition and Understanding
www.brl.ntt.co.jp/people/akisato/pdf/miru2009Miyazato.pdf

4) Dependent Dirichlet Process Spike Sorting
Jan Gasthaus, Frank Wood, Dilan Go ru r, Yee Whye Teh
2009 Neural Information Processing Systems conference (NIPS 2009)
http://books.nips.cc/papers/files/nips21/NIPS2008_0998.pdf

3) Spike-train communities: Finding groups of similar spike trains
M.D. Humphries, Univ. Sheffield, Sheffield, United Kingdom.
Program No. 322.11. 2009 Neuroscience Meeting Planner. Chicago, IL: Society
for Neuroscience, 2009. Online

2) Accurate spike sorting of multiunit recording data based on the robust variational Bayesian clustering
Takashi Takekawa, Yoshikazu Isomura, Tomoki Fukai
SfN 2008
http://nct.brain.riken.jp/~takekawa/SfN2008.pdf

1) Introduction of an automatic spike sorter, Clust016; its features and performance evaluation.

Hidekazu Kaneko, Hiroshi Tamura
2008 abstract
http://www2.bpe.es.osaka-u.ac.jp/multineuron/multineuron2008/abstract/Kaneko.pdf


D.  Masters Thesis

Spike Sorting Using Time-Varying Dirichlet Process Mixture Models
Jan A. Gasthaus
MSc in Intelligent Systems
University College London submitted September 5th, 2008
supervised by Frank Wood and Yee Whye Teh
http://www.gatsby.ucl.ac.uk/~ucabjga/papers/Gasthaus_2008_MScThesis.pdf

E.  Lecture slides

3) The variation of spike time
Conor Houghton
Mathematical Neuroscience Laboratory; School of Mathematics, Trinity College Dublin; Galway, January 2012
http://www.maths.tcd.ie/~mnl/papers/tcd-mnl-21a.pdf

2) Spike sorting on silicon probes
John Schulman
2012
www.eecs.berkeley.edu/~joschu/docs/caton-janelia.pdf

1) Architectures for Compressive Sampling of Ensembles of Correlated Signals
Justin Romberg and Ali Ahmed
Georgia Tech, School of ECE Mathematics and Image Analysis
January 17, 2012; Paris, France
http://www.ceremade.dauphine.fr/~peyre/mspc/mspc-mia-12/program/slides/romberg.pdf

 

F. Technical reports produced by CRCNS.org personnel

2) epHDF: A proposed standard for storing neuroscience electrophysiology data in HDF5
Jeffrey L Teeters, Friedrich T. Sommer (2013)
http://crcns.org/files/papers/ephdf.pdf


1) HDFds – Conventions to facilitate data sharing using HDF5
Jeffrey L Teeters, Friedrich T. Sommer (2013)
http://crcns.org/files/papers/hdfds.pdf

G.  Online resources

http://code.google.com/p/caton/
Spike sorting software which uses data hosted at CRCNS.org to test spike sorting algorithms.

http://xcorr.wordpress.com/2009/10/22/crcns-data-set-pvc-1-by-ringach-lab-getting-something-to-work/
Description of an analysis that was developed and tested using a data set hosted at CRCNS.org.

 

H.  Courses referencing data

CS/CNS/EE 253: Advanced Topics in Machine Learning
Taught at CalTech, Spring 2010.
http://www.cs.caltech.edu/courses/cs253/projects.html

Statistical analysis of neural data
Spring 2009, Columbia University
Instructor: Liam Paninski
http://www.stat.columbia.edu/~liam/teaching/neurostat-spr09/

 

I.  Art projects using data from CRCNS.org

What it is like to be a cat?

http://www.youtube.com/watch?v=f-nay3yAF4o

Document Actions