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Stephen M. LaConte, Ph.D.

Stephen M. LaConte, Ph.D.

Professor

Stephen M. LaConte, Ph.D. headshot

“It’s a pretty cool question. Can we take a snapshot of the brain and see what emotion the person is interpreting?”

Capturing images of the brain as it works

Can seeing the brain in action lead to rehabilitation and therapies? 

Stephen LaConte’s lab is devoted to advanced neuroimaging acquisition and data analysis approaches, aimed at improving basic understanding of normal brain function and exploring the potential for rehabilitation and therapy for neurological and psychiatric conditions. LaConte has applied his methods to fields ranging from alcohol abuse to traumatic brain injury.

A major focus of the lab is an innovation in functional magnetic resonance imaging (fMRI) that we developed and call “temporally adaptive brain state,” or TABS fMRI.

The inception of TABS arose from two major recent advances in neuroimaging. The first is recognition that multi-voxel patterns of fMRI data can be used to decode brain states – to determine what the volunteer was “doing,” such as receiving sensory input, affecting motor output, or otherwise internally focusing on a prescribed task or thought. The second is continued advances in magnetic resonance imaging systems and experimental sophistication with fMRI that have led to the emergence of real-time fMRI as a viable tool for biofeedback.

  • Associate Professor, Fralin Biomedical Research Institute at VTC
  • Associate Professor, Department of Biomedical Engineering and Mechanics, College of Engineering
  • Associate Professor, Departments of Emergency Medicine and Radiology, School of Medicine

Li T, Murphy S, Kiselev B, Bakshi KS, Zhang J, Eltahir A, Zhang Y, Chen Y, Zhu J, Davis RM, Madsen LA, Morris JR, Karolyi DR, LaConte SM, Sheng Z, Dorn HC. (2015). A New Interleukin-13 Amino-Coated Gadolinium Metallofullerene Nanoparticle for Targeted MRI Detection of Glioblastoma Tumor Cells. Journal of the American Chemical Society 137(24): 7881-8.

Eklund A, Dufort P, Forsberg D, LaConte SM. (2013). Medical image processing on the GPU – Past, present and future. Medical Image Analysis 17(8): 1073-94.

Craddock RC, Milham MP, LaConte SM. (2013). Predicting intrinsic brain activity. Neuroimage 82: 127-36.



Baylor College of Medicine
Assistant Professor, Neuroscience 

  • University of Denver: B.S, Biomedical Science and Electrical Engineering
  • University of Minnesota: Ph.D., Biomedical Engineering
  • Dean’s Award for Outstanding New Assistant Professor, Virginia Tech College of Engineering, 2014



 

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