Manish Saggar
Ph.D. Alumni
Manish did PhD on computational analysis and modeling of EEG recordings on meditation training, with Cliff Saron of UC Davis as his co-advisor. Manish went on for a postdoc at Allan Reiss's lab at Stanford University.
Mean-field thalamocortical modeling of longitudinal EEG acquired during intensive meditation training 2015
Manish Saggar, Anthony P. Zanesco, Brandon G. King, David A. Bridwell, Katherine A. MacLean, Stephen R. Aichele, Tonya L. Jacobs, B. Alan Wallace, Clifford D. Saron, Risto Miikkulainen, NeuroImage, Vol. 114 (2015), pp. 88-104. Elsevier.
Intensive training induces longitudinal changes in meditation state-related EEG oscillatory activity 2012
Manish Saggar, Brandon G King, Anthony P Zanesco, Katherine A MacLean, Stephen R Aichele, Tonya L Jacobs, David A Bridwell, Phillip R Shaver, Erika L Rosenberg, Baljinder K Sahdra, Emilio Ferrer, Akaysha C Tang, George R Mangun, B Alan Wallace, Risto Miikkulainen, and Clifford D Saron, Frontiers in Human NeuroscienceAmishi P Jha (Eds.), Vol. 6, 00256 (2012).
Computational Analysis of Meditation 2011
Manish Saggar, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin.
Behavioral, neuroimaging, and computational evidence for perceptual caching in repetition priming 2010
Manish Saggar, Risto Miikkulainen, David Schnyer, Journal of Brain Research, Vol. 1315 (2010), pp. 75--91.
Memory Processes in Perceptual Decision Making 2008
Manish Saggar, Risto Miikkulainen, David M Schnyer, In Proceedings of the 30th Annual Conference of the Cognitive Science Society, Nashville, TN 2008.
A computational model of the motivation-learning interface 2007
Manish Saggar, Arthur B Markman, W Todd Maddox, Risto Miikkulainen, In Proceedings of the 29th Annual Conference of the Cognitive Science Society, Nashville, TN 2007.
Autonomous Learning of Stable Quadruped Locomotion 2007
Manish Saggar, Thomas D'Silva, Nate Kohl, and Peter Stone, In RoboCup-2006: Robot Soccer World Cup X, Gerhard Lakemeyer and Elizabeth Sklar and Domenico Sorenti and Tomoichi Takahashi (Eds.), Vol. 4434, pp. 98-109, Berlin 2007. Springer Verlag.
System Identification for the Hodgkin-Huxley Model using Artificial Neural Networks 2007
Manish Saggar, Tekin Mericli, Sari Andoni, Risto Miikkulainen, In Proceedings of International Joint Conference on Neural Networks, Orlando, Florida, August 2007.
Formerly affiliated with Neural Networks