Neuroimaging techniques such as fMRI, EEG, and VSDI allow visualizing brain structure and function. Computational techniques are developed to analyze the results, and in some cases to model the underlying circuitry and processes in order to explain how the results arise.
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Combining fMRI Data and Neural Networks to Quantify Contextual Effects in the Brain Nora Aguirre-Celis and Risto Miikkulainen In Shouyi Wang, Vicky Yamamoto, Jianzhong Su, Yang Yang, Eric Jones, Leon Iasemidis, Tom Mitchell, e... 2018

From Words to Sentences & Back: Characterizing Context-dependent Meaning Representations in the Brain Nora Aguirre-Celis, Manuel Valenzuela, and Risto Miikkulainen In Proceedings of the 39th Annual Meeting of the Cognitive Science Society, London, UK, July... 2017

Mean-field thalamocortical modeling of longitudinal EEG acquired during intensive meditation training Manish Saggar, Anthony P. Zanesco, Brandon G. King, David A. Bridwell, Katherine A. MacLean, Stephen... NeuroImage, 114:88-104, 2015. Elsevier. 2015

Intensive training induces longitudinal changes in meditation state-related EEG oscillatory activity Manish Saggar, Brandon G King, Anthony P Zanesco, Katherine A MacLean, Stephen R Aichele, Tonya L Ja... Amishi P Jha, editors, Frontiers in Human Neuroscience, 6(00256), Sep 2012. 2012

Computational Analysis of Meditation Manish Saggar PhD Thesis, Department of Computer Sciences, The University of Texas at Austin, Austin, TX, 2011. 2011

Behavioral, neuroimaging, and computational evidence for perceptual caching in repetition priming Manish Saggar, Risto Miikkulainen, David Schnyer Journal of Brain Research, 1315:75--91, 2010. 2010

Computational models inform clinical science and assessment: An application to category learning in striatal-damaged patients W. Todd Maddox, J. Vincent Filoteo and Dagmar Zeithamova Journal of Mathematical Psychology, 54(1):109-122, 2010. 2010

A Population Gain Control Model of Spatiotemporal Responses in the Visual Cortex Yiu Fai Sit PhD Thesis, Department of Computer Sciences, University of Texas at Austin, Austin, TX, 2009. Techni... 2009

Complex Dynamics of V1 Population Responses Explained by a Simple Gain-Control Model Yiu Fai Sit, Yuzhi Chen, Wilson S. Geisler, Risto Miikkulainen, and Eyal Seidemann Neuron, 64:943-956, 2009. 2009

Category Learning Systems Dagmar Zeithamova PhD Thesis, Institute for Neuroscience, The University of Texas at Austin, 2008. 2008

Memory Processes in Perceptual Decision Making Manish Saggar, Risto Miikkulainen, David M Schnyer In Proceedings of the 30th Annual Conference of the Cognitive Science Society, Nashville, TN,... 2008

Dissociable prototype learning systems: Evidence from brain imaging and behavior Dagmar Zeithamova, W. Todd Maddox and David M. Schnyer Journal of Neuroscience, 28(49):13194-13201, 2008. 2008

A Computational Model of the Signals in Optical Imaging with Voltage-Sensitive Dyes Yiu Fai Sit and Risto Miikkulainen Neurocomputing:1853-1857, 2007. 2007

Shlomo Bentin Former Collaborator shlomo bentin [at] huji ac il
Wilson S. Geisler Former Collaborator geisler [at] psy utexas edu
Ralph E. Hoffman Former Collaborator ralph hoffman [at] yale edu
Risto Miikkulainen Faculty risto [at] cs utexas edu
Manish Saggar Ph.D. Alumni saggar [at] stanford edu
Clifford Saron Former Collaborator cdsaron [at] ucdavis edu
Eyal Seidemann Former Collaborator eyal [at] mail cps utexas edu
Yiu Fai Sit Ph.D. Alumni yfsit [at] cs utexas edu
Dasa Zeithamova Former Collaborator zeithamova [at] mail utexas edu