Abbas Babajani-Feremi

Abbas Babajani-Feremi, Phd

Associate Professor Of Neurology And AI; Director Of Magnetoencephalography (MEG) Lab

Department: MD-NEUROLOGY-EPILEPSY
Business Phone: (352) 273-5550
Business Email: babajani.a@ufl.edu

About Abbas Babajani-Feremi

Dr. Abbas Babajani-Feremi is an Associate Professor in the Department of Neurology, Division of Epilepsy at UF and the Director of the Magnetoencephalography (MEG) Laboratory. Abbas joined as a postdoctoral fellow in the department of Neurology at the Henry Ford Hospital, Detroit, MI in 2007 after completing his Ph.D. degree in Biomedical Engineering at the University of Tehran. In 2011, he joined as a member of the MEG team in the Human Connectome Project (HCP) at the Washington University School of Medicine in St. Louis. The HCP was one of the largest funded projects by NIH in system neuroscience and aimed to map the human brain by outlining the neural pathways using cutting-edge neuroimaging data from a large number of subjects. Then Dr. Babajani-Feremi joined as an Assistant Professor in the Department of Pediatrics at the University of Tennessee, Memphis, in 2013, and was the Research Director of MEG Laboratory, Director of High-density Electroencephalography (hd-EEG) Laboratory, and Director of Intracranial EEG (iEEG) Functional Mapping Laboratory at Le Bonheur Children’s Hospital, Memphis, TN. In January 2021, Abbas joined as an Associate Professor in the Department of Neurology at University of Texas at Austin, and was the Director of MEG Lab at Dell Children’s Medical Center, Texas, Austin.

Dr. Babajani-Feremi has two main research interests: (1) applications of the brain connectomics and machine learning based on neuroimaging and electrophysiological methods (such as MEG, functional MRI [fMRI], and intracranial EEG [iEEG]) in diagnostic and treatment of patients with epilepsy, Alzheimer’s disease, and other neurological conditions; and (2) study of the brain’s functions, specifically language, using the electrophysiological and neuroimaging modalities.

Research Profile

RESEARCH INTERESTS Brain connectivity analysis using magnetoencephalography (MEG), electroencephalography (EEG), functional MRI (fMRI), and intracranial EEG (iEEG); Study of the brain’s function, e.g. language and memory, using iEEG, fMRI, and EEG/MEG; Application of brain connectivity analysis in epilepsy, Alzheimer’s disease, sleep disorder, and traumatic brain injury (TBI); Epilepsy seizure localization; Application of dynamic contrast enhancement MRI (DCE-MRI) in the diagnosis of cancer and monitoring of tumor response to treatment; Machine learning & deep learning; Signal and image processing; Medical imaging;

Publications

2022
Behavioral phenotypes of pediatric temporal lobe epilepsy.
Epilepsia. 63(5):1177-1188 [DOI] 10.1111/epi.17193. [PMID] 35174484.
2022
Reproducibility of graph measures derived from resting-state MEG functional connectivity metrics in sensor and source spaces.
Human brain mapping. 43(4):1342-1357 [DOI] 10.1002/hbm.25726. [PMID] 35019189.
2021
Characterizing resting-state networks in Parkinson’s disease: A multi-aspect functional connectivity study.
Brain and behavior. 11(5) [DOI] 10.1002/brb3.2101. [PMID] 33784022.
2021
Diffusion Tensor Imaging-Based Analysis of Baseline Neurocognitive Function and Posttreatment White Matter Changes in Pediatric Patients With Craniopharyngioma Treated With Surgery and Proton Therapy.
International journal of radiation oncology, biology, physics. 109(2):515-526 [DOI] 10.1016/j.ijrobp.2020.08.060. [PMID] 32898610.
2021
Functional Magnetic Resonance Imaging and Applications in Dermatology.
JID innovations : skin science from molecules to population health. 1(3) [DOI] 10.1016/j.xjidi.2021.100015. [PMID] 35024683.
2021
Magnetometers vs Gradiometers for Neural Speech Decoding.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference. 2021:6543-6546 [DOI] 10.1109/EMBC46164.2021.9630489. [PMID] 34892608.
2021
Prediction and Modeling of Neuropsychological Scores in Alzheimer’s Disease Using Multimodal Neuroimaging Data and Artificial Neural Networks.
Frontiers in computational neuroscience. 15 [DOI] 10.3389/fncom.2021.769982. [PMID] 35069161.
2020
Lateralization of epilepsy using intra-hemispheric brain networks based on resting-state MEG data.
Human brain mapping. 41(11):2964-2979 [DOI] 10.1002/hbm.24990. [PMID] 32400923.
2020
Somatosensory evoked fields predict response to vagus nerve stimulation.
NeuroImage. Clinical. 26 [DOI] 10.1016/j.nicl.2020.102205. [PMID] 32070812.
2019
A model for visual naming based on spatiotemporal dynamics of ECoG high-gamma modulation.
Epilepsy & behavior : E&B. 99 [DOI] 10.1016/j.yebeh.2019.106455. [PMID] 31419636.
2019
Identification of the Early Stage of Alzheimer’s Disease Using Structural MRI and Resting-State fMRI.
Frontiers in neurology. 10 [DOI] 10.3389/fneur.2019.00904. [PMID] 31543860.
2019
Localization of Expressive Language Cortex in a 2-Year-Old Child Using High-Gamma Electrocorticography.
Journal of child neurology. 34(13):837-841 [DOI] 10.1177/0883073819863999. [PMID] 31339411.
2019
Mapping critical hubs of receptive and expressive language using MEG: A comparison against fMRI.
NeuroImage. 201 [DOI] 10.1016/j.neuroimage.2019.116029. [PMID] 31325641.
2019
Statistical Significance Assessment of Phase Synchrony in the Presence of Background Couplings: An ECoG Study.
Brain topography. 32(5):882-896 [DOI] 10.1007/s10548-019-00718-8. [PMID] 31129754.
2018
Comparison of statistical tests in effective connectivity analysis of ECoG data.
Journal of neuroscience methods. 308:317-329 [DOI] 10.1016/j.jneumeth.2018.08.026. [PMID] 30189285.
2018
Predicting conversion from MCI to AD by integrating rs-fMRI and structural MRI.
Computers in biology and medicine. 102:30-39 [DOI] 10.1016/j.compbiomed.2018.09.004. [PMID] 30245275.
2018
Predicting postoperative language outcome using presurgical fMRI, MEG, TMS, and high gamma ECoG.
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology. 129(3):560-571 [DOI] 10.1016/j.clinph.2017.12.031. [PMID] 29414401.
2018
Predicting seizure outcome of vagus nerve stimulation using MEG-based network topology.
NeuroImage. Clinical. 19:990-999 [DOI] 10.1016/j.nicl.2018.06.017. [PMID] 30003036.
2017
Classification of patients with MCI and AD from healthy controls using directed graph measures of resting-state fMRI.
Behavioural brain research. 322(Pt B):339-350 [DOI] 10.1016/j.bbr.2016.06.043. [PMID] 27345822.
2017
Identifying seizure onset zone from electrocorticographic recordings: A machine learning approach based on phase locking value.
Seizure. 51:35-42 [DOI] 10.1016/j.seizure.2017.07.010. [PMID] 28772200.
2017
Letter re: Practice guideline summary: Use of fMRI in the presurgical evaluation of patients with epilepsy: Report of the Guideline Development, Dissemination, and Implementation Subcommittee of the American Academy of Neurology.
Neurology. 89(6) [DOI] 10.1212/WNL.0000000000004204. [PMID] 28784636.
2017
Neural Mechanism Underling Comprehension of Narrative Speech and Its Heritability: Study in a Large Population.
Brain topography. 30(5):592-609 [DOI] 10.1007/s10548-017-0550-6. [PMID] 28214981.
2017
Predicting conversion from MCI to AD using resting-state fMRI, graph theoretical approach and SVM.
Journal of neuroscience methods. 282:69-80 [DOI] 10.1016/j.jneumeth.2017.03.006. [PMID] 28286064.
2017
Successful motor mapping with transcranial magnetic stimulation in an infant: A case report.
Neurology. 89(20):2115-2117 [DOI] 10.1212/WNL.0000000000004650. [PMID] 29021352.
2017
The Role of the Primary Sensory Cortices in Early Language Processing.
Journal of cognitive neuroscience. 29(10):1755-1765 [DOI] 10.1162/jocn_a_01147. [PMID] 28557692.
2016
Altered cross-frequency coupling in resting-state MEG after mild traumatic brain injury.
International journal of psychophysiology : official journal of the International Organization of Psychophysiology. 102:1-11 [DOI] 10.1016/j.ijpsycho.2016.02.002. [PMID] 26910049.
2016
Application of advanced machine learning methods on resting-state fMRI network for identification of mild cognitive impairment and Alzheimer’s disease.
Brain imaging and behavior. 10(3):799-817 [DOI] 10.1007/s11682-015-9448-7. [PMID] 26363784.
2016
Brain activation profiles during kinesthetic and visual imagery: An fMRI study.
Brain research. 1646:249-261 [DOI] 10.1016/j.brainres.2016.06.009. [PMID] 27288703.
2016
Breathing as a Fundamental Rhythm of Brain Function.
Frontiers in neural circuits. 10 [DOI] 10.3389/fncir.2016.00115. [PMID] 28127277.
2016
Language mapping using high gamma electrocorticography, fMRI, and TMS versus electrocortical stimulation.
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology. 127(3):1822-36 [DOI] 10.1016/j.clinph.2015.11.017. [PMID] 26679420.
2016
Spatial-temporal functional mapping of language at the bedside with electrocorticography.
Neurology. 87(24) [PMID] 27956570.
2015
Assessing motor function in young children with transcranial magnetic stimulation.
Pediatric neurology. 52(1):94-103 [DOI] 10.1016/j.pediatrneurol.2014.08.031. [PMID] 25439485.
2015
Comparison of brain network models using cross-frequency coupling and attack strategies.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference. 2015:7426-9 [DOI] 10.1109/EMBC.2015.7320108. [PMID] 26738008.
2015
Functional connectivity changes detected with magnetoencephalography after mild traumatic brain injury.
NeuroImage. Clinical. 9:519-31 [DOI] 10.1016/j.nicl.2015.09.011. [PMID] 26640764.
2015
Identifying patients with Alzheimer’s disease using resting-state fMRI and graph theory.
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology. 126(11):2132-41 [DOI] 10.1016/j.clinph.2015.02.060. [PMID] 25907414.
2014
Variation in the topography of the speech production cortex verified by cortical stimulation and high gamma activity.
Neuroreport. 25(18):1411-7 [DOI] 10.1097/WNR.0000000000000276. [PMID] 25371284.
2013
Adding dynamics to the Human Connectome Project with MEG.
NeuroImage. 80:190-201 [DOI] 10.1016/j.neuroimage.2013.05.056. [PMID] 23702419.
2012
Characterization of scale-free properties of human electrocorticography in awake and slow wave sleep States.
Frontiers in neurology. 3 [DOI] 10.3389/fneur.2012.00076. [PMID] 22701446.
2012
Connectivity analysis of novelty process in habitual short sleepers.
NeuroImage. 63(3):1001-10 [DOI] 10.1016/j.neuroimage.2012.08.011. [PMID] 22906789.
2012
Determination of neural state classification metrics from the power spectrum of human ECoG.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference. 2012:4336-40 [DOI] 10.1109/EMBC.2012.6346926. [PMID] 23366887.
2012
MRI tracking of FePro labeled fresh and cryopreserved long term in vitro expanded human cord blood AC133+ endothelial progenitor cells in rat glioma.
PloS one. 7(5) [DOI] 10.1371/journal.pone.0037577. [PMID] 22662174.
2011
Development of a variational scheme for model inversion of multi-area model of brain. Part I: simulation evaluation.
Mathematical biosciences. 229(1):64-75 [DOI] 10.1016/j.mbs.2010.10.009. [PMID] 21070788.
2011
Development of a variational scheme for model inversion of multi-area model of brain. Part II: VBEM method.
Mathematical biosciences. 229(1):76-92 [DOI] 10.1016/j.mbs.2010.11.001. [PMID] 21087617.
2011
Differentiating treatment-induced necrosis from recurrent/progressive brain tumor using nonmodel-based semiquantitative indices derived from dynamic contrast-enhanced T1-weighted MR perfusion.
Neuro-oncology. 13(9):1037-46 [DOI] 10.1093/neuonc/nor075. [PMID] 21803763.
2010
Changes in vascular permeability and expression of different angiogenic factors following anti-angiogenic treatment in rat glioma.
PloS one. 5(1) [DOI] 10.1371/journal.pone.0008727. [PMID] 20090952.
2010
Multi-area neural mass modeling of EEG and MEG signals.
NeuroImage. 52(3):793-811 [DOI] 10.1016/j.neuroimage.2010.01.034. [PMID] 20080193.
2008
Integrated MEG/fMRI model validated using real auditory data.
Brain topography. 21(1):61-74 [DOI] 10.1007/s10548-008-0056-3. [PMID] 18478325.

Contact Details

Phones:
Business:
(352) 273-5550
Emails:
Business:
babajani.a@ufl.edu
Addresses:
Business Mailing:
PO Box 100236
GAINESVILLE FL 32610
Business Street:
1149 NEWELL DR RM L3 100
GAINESVILLE FL 32610