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Craig S. Henriquez, James L. and Elizabeth M. Vincent Professor of Biomedical Engineering and Professor of Mechanical Engineering and Materials Science and Faculty Network Member of Duke Institute for Brain Sciences and Bass Fellow of Biomedical Engineering

 

Craig S. Henriquez

Dr. Henriquez is also a Professor of Computer Science and Co-Director of the Center for Neuroengineering. Henriquez's research interests include large scale computing, heart modeling, and brain modeling.

A breakdown of the normal electrical activation sequence of the heart can sometimes lead to a state of ventricular fibrillation in which the heart ceases to function as an effective pump. Abnormal rhythms or arrhythmias often result after an episode of ischemia (a localized reduction of blood flow to the heart itself) which affects both the ionic processes necessary to elicit an impulse and the passive electrical properties of the tissue. Identifying the complex mechanisms of arrhythmogenesis will require experimentation as well as mathematical and computer models.

Current projects include the application of the bidomain model to diseased tissue to investigate how changes in tissue structure (both natural and diseased induced) and changes in ionic current flow influences the nature of conduction and the onset of arrhythmia.

Dr. Henriquez's group is also interested in developing realistic models that will enable investigators to better interpret electrophysiological measurements made in the clinic. For example, activation maps at the surface of the heart are typically constructed based on the detection of specific features of the surface extracellular recordings. However, for complex activation, such as might arise during an arrhythmia, the features are difficult to distinguish.

The use of models that simulate both activation and the resulting extracellular potential and the application of signal processing techniques can lead to a tool for constructing more meaningful maps from experimental recordings during abnormal conduction. This works involves direct interaction with experimental research performed in the Experimental Electrophysiology Laboratory under the direction of Dr. Patrick Wolf and the Cardiac Electrophysiology & Tissue Engineering lab under the direction of Dr. Nenad Bursac.

Contact Info:
Office Location:  274 Hudson Hall Annex, Durham, NC 27708
Office Phone:  (919) 660-5168
Email Address: send me a message

Teaching (Fall 2017):

  • BME 503.01, COMPUTATIONAL NEUROENGINEERING Synopsis
    Hudson 212, WF 11:45 AM-01:00 PM
Teaching (Spring 2018):
  • BME 244L.001, QUANT PHYSIOLOGY BIOSTAT APPL Synopsis
    Hudson 125, TuTh 08:30 AM-09:45 AM
  • BME 244L9.02, QUANT PHYSIOLOGY BIOSTAT APPL Synopsis
    FITZPATRK 1392, W 04:40 PM-07:40 PM

Education:

Ph.D.Duke University1988
B.S.Duke University1981

Specialties:

Heart, Electrophysiology
Computational Biology
Neuroengineering
Neural Prosthesis

Research Interests:

Henriquez's research interests include large scale computing, heart modeling, and brain modeling.

Keywords:

Action Potentials • Adaptation, Physiological • Algorithms • Analysis of Variance • Animals • Anisotropy • Arm • Arrhythmias, Cardiac • Artificial Intelligence • Artificial Limbs • Axons • Biophysical Phenomena • Biophysics • Body Surface Potential Mapping • Brain • Brain Mapping • Cardiac Pacing, Artificial • Cardiac Volume • Cell Communication • Cell Membrane • Cell Physiological Phenomena • Cell Shape • Computer Simulation • Diagnosis, Computer-Assisted • Differential Threshold • Dogs • Electric Conductivity • Electric Countershock • Electric Stimulation • Electrocardiography • Electrodes • Electrolytes • Electromagnetic Fields • Electromyography • Electrophysiology • Endocardium • Endomyocardial Fibrosis • Equipment Design • Extracellular Space • Female • Fibroblasts • Finite Element Analysis • Gap Junctions • Guinea Pigs • Hand • Hand Strength • Heart • Heart Atria • Heart Conduction System • Heart Ventricles • Humans • Image Enhancement • Infant, Newborn • Intracellular Space • Ion Channel Gating • Ions • Kinetics • Learning • Linear Models • Macaca • Macaca mulatta • Magnetic Resonance Imaging • Membrane Potentials • Mice • Models, Anatomic • Models, Biological • Models, Cardiovascular • Models, Neurological • Models, Statistical • Models, Theoretical • Motor Activity • Motor Cortex • Muscle Cells • Muscle Fibers, Skeletal • Muscles • Myocardium • Myocytes, Cardiac • Nerve Fibers • Neural Conduction • Neurons • Pericardium • Phantoms, Imaging • Predictive Value of Tests • Pressure • Primates • Rabbits • Radiation Dosage • Reproducibility of Results • Robotics • Signal Transduction • Somatosensory Cortex • Space Perception • Surface Properties • Swine • Time Perception • User-Computer Interface • Ventricular Function

Recent Publications   (More Publications)

  1. Li, G; Henriquez, CS; Fröhlich, F, Unified thalamic model generates multiple distinct oscillations with state-dependent entrainment by stimulation., PLoS computational biology, vol. 13 no. 10 (October, 2017), pp. e1005797 [doi]  [abs]
  2. Gokhale, TA; Medvescek, E; Henriquez, CS, Modeling dynamics in diseased cardiac tissue: Impact of model choice., Chaos, vol. 27 no. 9 (September, 2017), pp. 093909 [doi]  [abs]
  3. Gokhale, TA; Kim, JM; Kirkton, RD; Bursac, N; Henriquez, CS, Modeling an Excitable Biosynthetic Tissue with Inherent Variability for Paired Computational-Experimental Studies., PLoS computational biology, vol. 13 no. 1 (January, 2017), pp. e1005342 [doi]  [abs]
  4. Zhang, X; Foderaro, G; Henriquez, C; Ferrari, S, A Scalable Weight-Free Learning Algorithm for Regulatory Control of Cell Activity in Spiking Neuronal Networks., International Journal of Neural Systems (December, 2016), pp. 1750015 [doi]  [abs]
  5. Gokhale, TA; Medvescek, E; Henriquez, CS, Continuous models fail to capture details of reentry in fibrotic myocardium, Computing in cardiology, vol. 43 (March, 2016), pp. 1-4, ISBN 9781509008964  [abs]