Abbas Babajani-Feremi

Abbas Babajani-Feremi, Phd

Associate Professor Of Neurology & Artificial Intelligence (AI) Director, Magnetoencephalography (MEG) Lab

Business Phone: (352) 294-5144
Business Email:

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;

Open Researcher and Contributor ID (ORCID)



MEG language mapping using a novel automatic ECD algorithm in comparison with MNE, dSPM, and DICS beamformer.
Frontiers in neuroscience. 17 [DOI] 10.3389/fnins.2023.1151885. [PMID] 37332870.
Subject Generalization in Classifying Imagined and Spoken Speech with MEG
2023 11th International IEEE/EMBS Conference on Neural Engineering (NER). [DOI] 10.1109/ner52421.2023.10123722.
Behavioral phenotypes of pediatric temporal lobe epilepsy
Epilepsia. 63(5):1177-1188 [DOI] 10.1111/epi.17193.
Global network alterations of the cognitive phenotypes in pediatric temporal lobe epilepsy.
Epilepsy & behavior : E&B. 135 [DOI] 10.1016/j.yebeh.2022.108891. [PMID] 36049247.
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.
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.
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.
Functional Magnetic Resonance Imaging and Applications in Dermatology
JID Innovations. 1(3) [DOI] 10.1016/j.xjidi.2021.100015. [PMID] 35024683.
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.
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.
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.
Somatosensory evoked fields predict response to vagus nerve stimulation
NeuroImage: Clinical. 26 [DOI] 10.1016/j.nicl.2020.102205. [PMID] 32070812.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Breathing as a Fundamental Rhythm of Brain Function.
Frontiers in neural circuits. 10 [DOI] 10.3389/fncir.2016.00115. [PMID] 28127277.
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.
Spatial-temporal functional mapping of language at the bedside with electrocorticography.
Neurology. 87(24) [PMID] 27956570.
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.
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.
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.
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.
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.
Adding dynamics to the Human Connectome Project with MEG.
NeuroImage. 80:190-201 [DOI] 10.1016/j.neuroimage.2013.05.056. [PMID] 23702419.
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.
Connectivity analysis of novelty process in habitual short sleepers.
NeuroImage. 63(3):1001-10 [DOI] 10.1016/j.neuroimage.2012.08.011. [PMID] 22906789.
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.
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.
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.
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.
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.
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.
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.
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

(352) 294-5144
Business Mailing:
PO Box 100236
Business Street:
1149 NEWELL DR RM L3 100