Papers

This material is based upon work supported by the National Science Foundation under Grant Numbers 1065513, 0542947, 0328269, 0208958, 9202100. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

Here are links to additional publications in the form of posters, talks and popular press.

2019

• Advancing the Rehabilitative and Therapeutic Potential of BCI and Noninvasive Sensing Systems.
  Scott, S.M., Raftery, C., and Anderson, C. (2019) In Brain Art Brain-Computer Interfaces for Artistic Expression, ed. by Anton Nijholt, Chapter 12, pp. 327–354, Springer, 2019.
• Convolutional neural networks for EEG signal classification in asynchronous brain-computer interfaces.
  Elliott M. Forney. (2019) Ph.D.Dissertation, Department of Computer Science, Colorado State University, 2019.
• A Comparison of Tri-Polar Concentric Ring Electrodes to Disc Electrodes for Decoding Real and Imaginary Finger Movements.
  Saleh Ibrahim Alzahrani. (2019) Ph.D. Dissertation, School of Biomedical Engineering, Colorado State University, 2019.

2018

• Auditory priming improves neural synchronization in auditory-motor entrainment.
  Crasta, J.E., Thaut, M.H., Anderson, C.W., Davies, P.L., and Gavin, W.J. (2018) Neuropsychologia, vol. 117, pp. 102–112.
• Comparison of Conventional and Tripolar EEG Electrodes in BCI Paradigms.
  Anderson, C., Besio, W. and Alzahrani, S. (2018) In Proceedings of the Seventh International Brain-Computer Interface Meeting: BCIs, Not Getting Lost in Translation, May, 2018, Asilomar Conference Center, Pacific Grove, California, USA.
• Mental-Task BCIs Using Convolutional Networks with Label Aggregation and Transfer Learning.
  Forney, E., Anderson, C., Gavin, W. and Davies, P. (2018) In Proceedings of the Seventh International Brain-Computer Interface Meeting: BCIs, Not Getting Lost in Translation, May, 2018, Asilomar Conference Center, Pacific Grove, California, USA.

2016

• CEBL3: A New Software Platform for EEG Analysis and Rapid Prototyping of BCI Technologies.
  Forney, E., Anderson, C., Gavin, W., Davies, P., Roll, M., Ryzhkov, I., and Vafaei, F. (2016) In Proceedings of the Sixth International Brain-Computer Interface Meeting: BCI Past, Present, and Future, May 30 – June 3 2016, Asilomar Conference Center, Pacific Grove, California, USA, page 145, DOI:10.3217/978-3-85125-467-9-145
• Detecting P300 ERPs with Convolutional Networks.
  Forney, E., Anderson, C., Davies, P., Gavin, W., Roll, M. (2016) In Proceedings of the Sixth International Brain-Computer Interface Meeting: BCI Past, Present, and Future, May 30 – June 3 2016, Asilomar Conference Center, Pacific Grove, California, USA, page 206, DOI:10.3217/978-3-85125-467-9-206

2015

• Echo State Networks for Modeling and Classification of EEG Signals in Mental-Task Brain Computer Interfaces
  Forney, EM., Anderson, CW., Gavin, WJ., Davies, PL., Roll, MC., Taylor, BK., (2015) Technical Report, Department of Computer Science, Colorado State University, Fort Collins, CO.
• EEG Subspace Analysis and Classification Using Principal Angles for Brain-Computer Interfaces
  Ashari, R., (2014) Ph.D. Dissertation, Department of Computer Science, Colorado State University, Fort Collins, CO.

2014

• EEG Subspace Analysis and Classification Using Principal Angles for Brain-Computer Interfaces
  Ashari, R. and Anderson, C., In Proceedings of the 2014 IEEE Symposium on Computational Intelligence in Brain-Computer Interfaces (CIBCI), DOI: 10.1109/CIBCI.2014.7007793, pp. 57–63, 2014.
• Brain Computer Interface Classifier Parameters Are Influenced by Practice: Results from a P300 Speller
  The, K., Taylor, B., Crasta, J., Lin, M-H, Forney, E., Anderson, C., Davies, P., and Gavin, W. In Proceedings of the Society of Psychophisological Research (SPR) 2014 Meeting
• Generative Topographic Mapping of Electroencephalography (EEG) Data
  Dantanarayana, Navini, (2014) Masters Thesis, Department of Computer Science, Colorado State University, Fort Collins, CO.
• Detecting Error-Related Negativity Using EEG Potentials Generated During Simulated Brain Computer Interaction
  Verlekar, P., (2014) Masters Thesis, Department of Computer Science, Colorado State University, Fort Collins, CO.
• P300 Classification Using Deep Belief Networks
  Sobhani, A., (2014) Masters Thesis, Department of Computer Science, Colorado State University, Fort Collins, CO.
• Localized anomaly detection via hierarchical integrated activity discovery
  Thiyagarajan, C., (2014) Masters Thesis, Department of Computer Science, Colorado State University, Fort Collins, CO.
• Workshops of the Fifth International Brain-Computer Interface Meeting: Defining the Future.
  Huggins, J., Guger, C., Allison, B., Anderson, C., Batista, A., Brouwer, A., Brunner, C., Chavarriaga, R., Fried-Oken, M., Gunduz, A., Gupta, D., Kübler, A., Leeb, R., Lotte, R., Miller, L., Müller-Putz, R., Rutkowski, T, Tangermann, M., Thompson, D. Brain-Computer Interfaces, vol. 1, no. 1, pg. 27-4. Taylor & Francis, 2014.

2013

• A Stimulus-Free Brain-Computer Interface Using Mental Tasks and Echo State Networks
  Forney, E., Anderson, C., Gavin, W., and Davies, P. In Proceedings of the Fifth International Brain-Computer Interface Meeting: Defining the Future, June 3 - 7, 2013. Graz University of Technology Publishing House. DOI:10.3217/978-3-85125-260-6-148. (Best Overall Poster Award)
• The N100 of Averaged ERPs Predicts LDA Classifier Success on an Individual Basis
  Taylor, B., Forney, E., Gavin, W., Anderson, C., and Davies, P. In Proceedings of the Fifth International Brain-Computer Interface Meeting: Defining the Future, June 3 - 7, 2013. Graz University of Technology Publishing House. DOI:10.3217/978-3-85125-260-6-28
• A Comparison of EEG Systems for Use in P300 Spellers by Users With Motor Impairments in Real-World Environments
  Forney, E., Anderson, C., Davies, P., Gavin, W., Taylor, B., and Roll M. In Proceedings of the Fifth International Brain-Computer Interface Meeting: Defining the Future, June 3 - 7, 2013. Graz University of Technology Publishing House. DOI:10.3217/978-3-85125-260-6-14
• Cloud-Based Analysis of EEG Signals for BCI Applications
  Ericson, K., Pallickara, S., and Anderson, C.W. In Proceedings of the Fifth International Brain-Computer Interface Meeting: Defining the Future, June 3 - 7, 2013. Graz University of Technology Publishing House. DOI:10.3217/978-3-85125-260-6-178
• Single-Trial P300 Classification using PCA with LDA and Neural Networks
  Nand Sharma (2013) Masters Thesis, Department of Computer Science, Colorado State University, Fort Collins, CO.

2012

• EEG character identification using stimulus sequences designed to maximize mimimal hamming distance
  Tadanori Fukami, Takamasa Shimada, Elliott Forney, Charles W Anderson, Annual International Conference of the IEEE Engineering in Medicine and Biology Society, August 28 - September 1, 2012. pp. 1782 - 1785. 2012.

2011

• Electroencephalogram Classification by Forecasting with Recurrent Neural Networks
  Elliott Forney (2011) Masters Thesis, Department of Computer Science, Colorado State University, Fort Collins, CO.
• Classification of EEG During Imagined Mental Tasks by Forecasting with Elman Recurrent Neural Networks
  Forney, E. and Anderson, C. In Proceedings of the International Joint Conference on Neural Networks, July 31 - August 5, 2011. pp. 2749 - 2755, 2011, DOI: 10.1109/IJCNN.2011.6033579.
• Comparison of EEG Preprocessing Methods to Improve the Classification of P300 Trials
  Zachary Cashero (2011) Masters Thesis, Department of Computer Science, Colorado State University, Fort Collins, CO.
• Comparison of EEG Blind Source Separation Techniques to Improve the Classification of P300 Trials
  Cashero, Z. and Anderson, C. To be presented at the International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC '11), August 30th - Sept 3rd, 2011, Boston, MA.
• Reliable identification of mental tasks using time-embedded EEG and sequential evidence accumulation
  Anderson, C., Forney, E., Hains, D., Natarajan, A. Journal of Neural Engineering, vol. 8, no. 2, 025023.
• Critical issues in state-of-the-art brain-computer interface signal processing
  Krusienski, Dl, Grosse-Wentrup, M., Galan, F., Coyle, D., Miller, K., Forney, E., Anderson, C. Journal of Neural Engineering, vol. 8, no. 2, 025002.
• Brain Computer Interfaces Benefit from Cloud Advancements
  Kate Ericson, HPC in the Cloud, March 23, 2011.

2010

• Analyzing Electroencephalograms Using Cloud Computing Technologies
  Kate Ericson, Shrideep Pallickara, and Chuck Anderson, IEEE Conference on Cloud Computing Technology and Science, 2010. (Best Student Paper Award)

2009

• Estimating Sparse Inverse Covariance Matrix for Brain Computer Interface Applications
  Natarajan, A. (2009) Masters Thesis, Department of Computer Science, Colorado State University, Fort Collins, CO.
• Nonlinear Dimensionality Reduction of Electroencephalogram (EEG) for Brain Computer Interfaces
  Teli, M.N. and Anderson, C.W. (2009) In Proceedings of the International Conference of the IEEE Engineering in Medicine and Biology Society, Minneapolis, MN, Sept. 2-6, 2009.

2008

• Translating Thoughts Into Actions by Finding Patterns in Brainwaves
  Anderson, C. W. and Bratman, J.A. (2008) , In Proceedings of the Fourteenth Yale Workshop on Adaptive and Learning Systems, Yale University, New Haven, CT, June 2008, pp. 1-6.

2007

• Analysis of Temporal Structure and Normality in EEG Data
  Sokolov, Artem (2007) Masters Thesis, Department of Computer Science, Colorado State University, Fort Collins, CO.
• Classification of Time-Embedded EEG Using Short-Time Principal Component Analysis
  Anderson, C.W., Kirby, M.J., Hundley, D., and Knight, J.N. (2007) In Towards Brain-Computer Interfacing , edited by G. Dornhege, J. del R. Millan, T. Hinterberger, D.J. McFarland, and K.-R. Muller, The MIT Press, pp. 261-278.
• Dimensionality Reduction and Classification of Time Embedded EEG Signals
  Teli, Mohammad Nayeem (2007) Masters Thesis, Department of Computer Science, Colorado State University, Fort Collins, CO.
• Dimensionality Reduction using Neural Networks
  Teli, Mohammad Nayeem, ANNIE 2007
• Plasticity in EEG Oscillations Associated with Auditory Verbal Learning
  Peterson, D. (2007) , Ph.D. Dissertation, Department of Computer Science, Colorado State University.

2006

• BCI Meeting 2005---Workshop on BCI Signal Processing: Feature Extraction and Translation
  McFarland, D.J., Anderson, C.W., Muller, K.-R., Schlogl, A., and Krusienski, D.J. (2006) IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 14, no. 2, pp. 135--138, June.
• Geometric Subspace Methods and Time-Delay Embedding for EEG Artifact Removal and Classification
  Anderson, C.W., Knight, J.N., O'Connor, T., Kirby, M.J., and Sokolov, A. (2006) IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 14, no. 2, pp. 142--146.
• Numerical techniques for a Brain to Computer Interface Project
  Hundley, D., (2006) Pacific Northwest Mathematical Association of America (PNW MAA), Ashland Oregon, June 21-24.

2005

• Taxonomy of Feature Extraction and Translation Methods for BCI
  unpublished summary for the Third International Meeting on Brain-Computer Interface Technology, June 14-19, 2005.
• Feature Selection and Blind Source Separation in an EEG-Based Brain-Computer Interface
  Peterson, D., Knight, J., Kirby, M., Anderson, C., and Thaut, M. (2005) EURASIP Journal on Applied Signal Processing, vol. 19, pp. 3128--3140.
• An Inexpensive Brain-Computer Interface Based on Spatial and Temporal Analysis of EEG
  Anderson, C.W., Knight, J.N., Kirby, M.J. (2005) Proceedings of HCI International, (HCI-I) 2005, Las Vegas, NV, (CD-ROM).

2003

• Signal Fraction Analysis and Artifact Removal in EEG
  James N. Knight (2003) Masters Thesis, Department of Computer Science, Colorado State University, Fort Collins, CO.
• Geometric Analysis for the Characterization of Nonstationary Time-Series
  Kirby, M. and Anderson, C.W. (2003) In Springer Applied Mathematical Sciences Series Celebratory Volume for the Occasion of the 70th Birthday of Larry Sirovich, ed. by Kaplan, E., Marsden, J., and Sreenivasan, K.R., Springer-Verlag, Chapter 8, pp. 263--292.
• EEG Subspace Representations and Feature Selection for Brain-Computer Interfaces
  Anderson, C.W., and Kirby, M. (2003) In Proceedings of the 1st IEEE Workshop on Computer Vision and Pattern Recognition for Human Computer Interaction (CVPRHCI), June 17, 2003, Madison, Wisconsin.
• Comparison of Linear and Nonlinear Methods for EEG Signal Classification
  Garrett, D., Peterson, D.A., Anderson, C.W., Thaut, M.H. (2003) IEEE Transactions on Neural Systems and Rehabilitative Engineering, vol. 11, no. 2, pp. 141--144. Presented at the second, NIH-sponsored international brain-computer interface workshop titled Brain-Computer Interface Technology: Moving Beyond Demonstrations at the Rensselaerville Institue, New York. (Also see this NIH site.)
• Linear and Non-linear Methods in Brain-Computer Interfaces
  Muller, K.-R., Anderson, C., and Birch, G. (2003) IEEE Transactions on Neural Systems and Rehabilitative Engineering, vol. 11, no. 2, pp. 162--165, from the panel debating Linear versus Non-linear Methods in BCI Research at the second brain-computer interface workshop titled Brain-Computer Interface Technology: Moving Beyond Demonstrations at the Rensselaerville Institue, New York. (Winner of "The Best TNSRE Paper Award", awarded in 2009 by the editors of the IEEE TNSRE.)

2002

• In 2002, Sarah Matthews, a junior at Poudre High School in Fort Collins, was curious about what differences we might see in EEG when subjects hear tone pairs with varying amounts of dissonance. She designed the experiments, recorded the tones, provided the subjects, and helped record 10-channel EEG signals. Her final report is available here as sarah.doc.

2001

• Recent Advances in EEG Signal Analysis and Classification
  C. Anderson and D. Peterson (2001) In Clinical Applications of Artificial Neural Networks, ed. by R. Dybowski and V. Gant, Cambridge University Press, UK, chapter 8, pp. 175--191.

1998

• Spatial Analysis of Spontaneous EEG During Cognitive Tasks
  38th meeting of the Society for Psychophysiological Research , Denver, Colorado, September 23-27, 1998.
• Multivariate Autoregressive Models for Classification of Spontaneous Electroencephalogram During Mental Tasks
  C. Anderson, E. Stolz, and S. Shamsunder (1998) IEEE Transactions on Biomedical Engineering, vol. 45, no. 3, pp. 277-286.

1997

• Effects of Variations in Neural Network Topology and Output Averaging on the Discrimination of Mental Tasks from Spontaneous Electroencephalogram
  C. Anderson (1997) Journal of Intelligent Systems, vol. 11, no. 4, pp. 423-431.

1996

• Classification of EEG Signals from Four Subjects During Five Mental Tasks
  C. Anderson and Z. Sijercic (1996) In Solving Engineering Problems with Neural Networks: Proceedings of the Conference on Engineering Applications in Neural Networks (EANN'96), ed. by Bulsari, A.B., Kallio, S., and Tsaptsinos, D., Systems Engineering Association, PL 34, FIN-20111 Turku 11, Finland, pp. 407--414.
• Analysis of LVQ in the Context of Spontaneous EEG Signal Classification
  D. Ford (1996) Masters Dissertation, Department of Computer Science, Colorado State University, Fort Collins, CO 80523.
• Non-Linear Principal Component Analysis and Classification EEG During Mental Tasks
  S. Devulapalla (1996) Masters Dissertation, Department of Computer Science, Colorado State University, Fort Collins, CO 80523.
• EEG Signal Compression With ADPCM Subband Coding
  Z. Sijercic, G.C. Agarwal, and C. Anderson (1996) In Proceedings of the 39th Midwest Symposium on Circuits and Systems, August, 1996.

1995

• Discriminating Mental Tasks Using EEG Represented by AR Models
  C. Anderson, E. Stolz, and S. Shamsunder (1995) Proceedings of the 1995 IEEE Engineering in Medicine and Biology Annual Conference, Sept 20--23, 1995, Montreal, Canada.
• EEG Signal Classification with Different Signal Representations
  C. Anderson, S. Devulapalli, and E. Stolz (1995) In Neural Networks for Signal Processing V, ed. by F. Girosi, J. Makhoul, E. Manolakos, E. Wilson, IEEE Service Center, Piscataway, NJ, pp. 475--483.
• Determining Mental State from EEG Signals Using Neural Networks
  C. Anderson, S. Devulapalli, and E. Stolz (1995) Scientific Programming, Special Issue on Applications Analysis, 4, 3, 171--183.

1994

• Classification of EEG Signals Using a Sparse Polynomial Builder
  Ed Orosz (1994) , Technical Report 94-111, Computer Science, Colorado State University.