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NAME: Morgan, Victoria Lee
eRA COMMONS USER NAME (credential, e.g., agency login):  matangvl
POSITION TITLE: Associate Professor of Radiology and Radiological Sciences

EDUCATION/TRAINING (Begin with baccalaureate or other initial professional education, such as nursing, include postdoctoral training and residency training if applicable. Add/delete rows as necessary.)


(if applicable)


Completion Date





Wright State University, Dayton, OH B.S. 08/1990 Biomedical Engineering
Vanderbilt University, Nashville, TN M.S. 05/1994 Biomedical Engineering
Vanderbilt University, Nashville, TN Ph.D. 12/1996 Biomedical Engineering

A. Personal Statement

In 2002, I was one of the first to apply functional MRI connectivity techniques to investigate networks in epilepsy (i). Since then, I have developed a research program focused on developing and applying methods to quantify networks in epilepsy to better understand the effects of seizures on the brain. I hypothesized that network alterations could be used to quantify seizure propagation pathways across the brain. This work was initially funded by an Epilepsy Foundation Research Grant and then by the NIH which resulted in the development of a method to detect regions of epileptic activity which are nodes in the epileptic network. I applied these methods to examine relationships between functional connectivity across the identified epileptic networks and epilepsy status, and expanded this to include other more advanced fMRI network analyses including Granger causality. My most recent study investigated the relationship between functional and structural connectivity measured with diffusion MRI and seizures and cognitive effects in order to predict treatment outcomes. That work resulted in a preliminary MRI connectivity biomarker of seizure outcome after mesial temporal lobe epilepsy surgery (ii).

(i) Morgan VL, Abou-Khalil B, Modur P, Wushensky C, Price RR. MRI Functional Connectivity to Lateralize Temporal Lobe Epilepsy. Tenth Scientific Meeting of the International Society for Magnetic Resonance in Medicine 2002:1536.

(ii) Morgan VL, Englot DJ, Rogers BP, Landman BA, Cakir A, Abou-Khalil BW, Anderson AW. Magnetic resonance imaging connectivity for the prediction of seizure outcome in temporal lobe epilepsy. Epilepsia 2017;58(7):1251-1260. PMCID:PMC5498250

B.  Positions and Honors

Positions and Employment

1990-1992         Test Engineer, Impact Test Facility, Inland Fisher Guide Div., General                               Motors Corporation, Dayton, OH
1997                  Consultant, Center for Cardiovascular Magnetic Resonance, Barnes-                              Jewish Hospital at Washington University Medical Center, St. Louis,                                 MO
1997-1999         Sr. Research Assistant, Department of Radiology and Radiological                                   Sciences, Vanderbilt University, Nashville, TN
1999-2000         Instructor, Department of Radiology and Radiological Sciences,                                        Vanderbilt University, Nashville, TN
2000-2012          Assistant Professor, Department of Radiology and Radiological                                        Sciences, Vanderbilt University, Nashville, TN
2008-2013          Assistant Professor, Department of Biomedical Engineering,                                             Vanderbilt University, Nashville, TN
2012-Present     Associate Professor, Department of Radiology and Radiological                                        Sciences, Vanderbilt University, Nashville, TN
2013-Present     Associate Professor, Department of Biomedical Engineering,                                             Vanderbilt  University, Nashville, TN

Other Experience and Professional Memberships

2000-Present   Member, International Society of Magnetic Resonance in Medicine
2008-Present    Member, American Epilepsy Society
2001                  Grant reviewer, American Heart Association
2007                  Grant reviewer, Medical Research Council (UK)
2009                  Grant reviewer, NIH Challenge grants panel #23
2010                  Grant reviewer, Italian Ministry of Health Competition for Targeted                                    Research Funding
2010                  Steering Committee on Imaging Science, National Academies Keck                                Futures Initiative
2011                  Grant reviewer, NIH MEDI Study Section
2012                  ZGM1 PPBC-Y (AN), NIH grant review panel, ad hoc reviewer
2013                  ZGM1 PPBC-Y (AN), NIH grant review panel, ad hoc reviewer
2014                  ZRG1 SBIB-Z(03) M, NIH grant review panel, ad hoc reviewer
2014                  ZMH1 ERB-C(09) R – BRAIN Initiative: Development and Validation of                            Novel Tools, NIH grant    review panel, ad hoc reviewer
2014-2015        NOIT study section, NIH grant review panel, ad hoc reviewer
2014-2015        American Epilepsy Society, Scientific Program Committee
2014-20187      International Society of Magnetic Resonance in Medicine, Brain                                       Function Study Group, Officer
2015-present    NOIT study section, NIH grant review panel member
2017-present    International League Against Epilepsy (ILAE) Imaging Task Force of                               the  Commission on Diagnostic Methods
2018                 “My Brain Map” Workshop, Epilepsy Foundation


2003                 Young Investigator’s Bursary Award, International Epilepsy                                               Congress, Lisbon, Portugal
2016-present    American Epilepsy Society Fellow
2017                 Academy for Radiological and Biomedical Imaging Research,                                           Distinguished Investigator

 C. Contributions to Science

  1. Motion in fMRI. My earliest work in neurological functional MRI (fMRI) was focused on understanding the effect of motion on fMRI measures. This is arguably the biggest challenge in fMRI in both research and clinical applications. I served as a co-investigator on these studies to develop computer-generated phantoms to accurately incorporate physiological, magnetic field and acquisition related artifacts in human-like fMRI data to provide a platform to evaluate and compare different motion correction algorithms. This work was funded by an NIH R01 that I served as co-investigator (D. Pickens –PI).

(1a) Pickens DR, Li Y, Morgan VL, Dawant BM. Development of computer-generated phantoms for FMRI software evaluation. MRI, 2005;23:653-663.

(1b) Xu N, Fitzpatrick JM, Li, Y, Dawant BM, Pickens DR, Morgan VL. Computer-generated fMRI phantoms with motion-distortion interaction. Magn Reson Imaging 2007;25(10):1376-1384. PMCID:PMC4424598

(1c) Morgan VL, Dawant BM, Li Y, Pickens DR. Comparison of fMRI statistical software packages and strategies for analysis of images containing random and stimulus-correlated motion. Computerized Medical Imaging and Graphics 2007, 31(6):436-446. PMCID:PMC2570159

(1d) Li Y, Xu N, Fitzpatrick JM, Morgan VL, Pickens DR, Dawant BM. Accounting for signal loss due to dephasing in the correction of distortions in gradient-echo EPI via nonrigid registration. IEEE Transactions in Medical Imaging 2007;26(12):1698-1707.

2. Data driven fMRI methods for focal epilepsy. As one of the first researchers to attempt to apply MRI functional connectivity mapping to the study of epileptogenic networks (abstract in 2003, award cited above), I found that the identification of the nodes of these networks would be a significant challenge. Some research institutions focused on the use of simultaneous EEG and MRI methods to localize interictal spikes presumed to be these nodes, but this technique and hardware was not widely available and remains not clinically feasible. Therefore, I developed an fMRI data driven approach to identify the timing of interictal epileptic events called two-dimensional temporal clustering analysis (2dTCA). After some pilot study (2a,2b), I have validated the method on healthy controls (2c) and epilepsy patients (2d). This work has launched a field of data driven analyses of interictal epileptic fMRI data for both clinical and research purposes. I served as the primary investigator on all of these studies listed below. This work was funded by the Epilepsy Foundation (PI-Morgan) and an NIH R01 grant (PI-Morgan).

(2a) Morgan VL, Li Y, Abou-Khalil B, Gore JC. Development of 2dTCA for detection of irregular, transient BOLD activity. Human Brain Mapping, 2008;29(1):57-69. PMCID: PMC2719759

(2b) Morgan, VL, Gore, JC. Detection of irregular, transient fMRI activity in normal controls using 2dTCA: comparison to event-related analysis using known timing. Human Brian Mapping 2009;30:3393-3405. PMCID: PMC2748174

(2c) Morgan, VL, Gore, JC, Abou-Khalil, B. Functional epileptic network in left mesial temporal lobe epilepsy detected using resting fMRI. Epilepsy Research 2010;88:168-178. PMCID: PMC2823966

(2d) Maziero D, Velasco TR, Salmon CEG, Morgan VL. Two-dimensional temporal clustering analysis for patients with epilepsy: detecting epilepsy-related information in EEG-fMRI concordant, discordant and spike-less patients. Brain Topography 2018;31(2):322-336. PMCID: PMC5884070

  1. MRI functional connectivity in epilepsy. After identifying potential nodes in temporal lobe epilepsy networks using methods including 2dTCA, my group has focused on using MRI functional connectivity mapping to determine the evolution of these seizure networks over years of seizure duration. We hypothesize that this information can ultimately be used to understand how repeated seizures are linked to cognitive and behavioral deficits (3b), and can be used to predict post-surgical outcome in these patients. Towards this goal, we have measured an increase causal effect of the contralateral hippocampus over the ipsilateral one in the later years of the disease (3a). Additionally, we have found increasing functional isolation of the ipsilateral temporal lobe structures with simultaneous increasing synchronization with extra-temporal lobe structures as duration increases (3c, 3d), a process that may facilitate the spread of seizures over time. I served as the primary investigator on all of these studies listed below. This work was funded through a NIH R01 grant (PI-Morgan).

(3a) Morgan VL, Roger BP, Sonmezturk HH, Gore JC, Abou-Khalil B. Cross hippocampal influence in mesial temporal lobe epilepsy measured with high temporal resolution functional Magnetic Resonance Imaging. Epilepsia 2011;52(9):1741-1749. PMCID:PMC4428312

(3b) Holmes MJ, Folley BS, Sonmezturk HH, Gore JC, Kang H, Abou-Khalil B, Morgan VL. Resting state functional connectivity of the hippocampus associated with neurocognitive function in left temporal lobe epilepsy. Human Brain Mapping, 2014;35(3):735-44. PMCID:PMC3915042

(3c) Morgan VL, Abou-Khalil B, Rogers BP. Evolution of functional connectivity networks and their dynamic interaction in temporal lobe epilepsy. Brain Connectivity 2015;5(1):35-44. PMCID:PMC4313394

(3d) Englot DJ, Konrad PE, Morgan VL. Regional and global connectivity disturbances in focal epilepsy, related cognitive sequelae, and potential mechanistic underpinnings. Epilepsia 2016;57(10):1546-1557. PMCID:PMC5056148

  1. White matter structural and functional connectivity. In addition to functional connectivity methods, gray matter structure and white matter structural and functional connectivity are also important in understanding the evolution of the brain in diseases such as epilepsy. For this work I have collaborated with Zhaohua Ding, Ph.D. to design and implement MRI structural methodologies in healthy controls (4a) and then in the epileptic networks studied previously (4b). In epilepsy we found that there was a linear relationship between functional connectivity and gray matter concentration in key regions of these seizure networks, which may be important in predicting the post-surgical outcome in these patients. In these two studies, I was the primary investigator. In our most recent collaboration (4c, 4d), I have supported Dr. Ding in his innovative development of spatio-temporal correlation tensors, which are a completely novel investigation of functional connectivity of white matter. My role in this work is to help determine validation procedures and to relate the findings to traditional functional connectivity methodologies.

(4a) Morgan VL, Mishra A, Newton AT, Gore JC, Ding Z. Integrating Functional and Diffusion Magnetic Resonance Imaging for Analysis of Structure-Function Relationship in the Human Language Network. PLoS ONE 2009;4(8):E6660. doi:10.1371/journal.pone.0006660 PMCID:PMC2721978

(4b) Holmes MJ, Yang X, Landman BA, Ding Z, Kang H, Abou-Khalil BA, Sonmezturk HH, Gore JC, Morgan VL. Functional networks in temporal lobe epilepsy: a voxel-wise study of resting-state functional connectivity and gray matter concentration. Brain Connectivity 2013; 3(1):22-30. PMCID:PMC3621340

(4c) Ding Z, Newton AT, Xu R, Anderson AW, Morgan VL, Gore JC. Spatio-temporal correlation tensors reveal functional structure in human brain. PLoS ONE 2013; 8(12):e82107. PMCID:PMC3855380

(4d) Ding Z, Xu R, Bailey SK, Wu TL, Morgan VL, Cutting LE, Anderson AW, Gore JC. Visualizing functional pathways in the human brain using correlation tensors and Magnetic Resonance Imaging. Magnetic Resonance Imaging 2016;34(1):8-17. PMCID PMC4714593

  1. Mild traumatic brain injury (mTBI). Recently I have worked to apply the MRI methods I developed for epilepsy to investigate mTBI. In one study I collaborated with the Vanderbilt athletic department to image varsity athletes within one week of sports concussion. That study determined an increase in cerebrovascular reactivity in these subjects over age-matched healthy controls (5a). This hyper-reactivity is similar to that detected in migraine, and may show the similarities between the two conditions. In the same study we found a linear relationship between functional connectivity and hyper-reactivity which suggests caution in interpreting functional connectivity measures in patient populations where the neurovascular coupling may be altered. In another study of adults with accidental mTBI, the normalization of thalamocortical functional connectivity was a strong indicator of improvement of pain scores and post-concussive symptoms after rehabilitation (5b).

5a. Militana AR, Donahue MJ. Sills AK, Solomon GS, Gregory AJ, Strother MK, Morgan VL. Alterations in default-mode network connectivity may be influenced by cerebrovascular changes within one week of sports related concussion in college varsity athletes: a pilot study. Brain Imaging and Behavior 2016;10(2):559-568. PMCID:PMC4644725

5b. Banks SD, Coronado RA, Clemons LR, Abraham CM, Pruthi S, Conrad BN, Morgan VL, Guillamondegui OD, Archer KR. Thalamic functional connectivity in mild traumatic brain injury: Longitudinal associations with patient-reported outcomes and neurophsysiological tests. Archives of Physical Medicine and Rehabilitation 2016; 97(8):1254-61. PMCID:PMC4990202