Dr. Abbas Babajani-Feremi, PhD

Abbas Babajani-Feremi

Assistant Professor
Department of Pediatrics
Department of Anatomy and Neurobiology
The University of Tennessee Health Science Center

Le Bonheur Children's Medical Center
51 N. Dunlap St., Ste P320
Outpatient Center
Memphis, TN 38105
Phone: (901) 287-4612
Email: Abbas Babajani-Feremi


  • Ph.D. Institution: University of Tehran, Biomedical Engineering
  • Postdoctoral: Henry Ford Health System, Detroit, MI; Washington University School of Medicine, St Louis, MO - Human Connectome Project (HCP)

Research Keywords

  • Signal and image processing
  • Medical imaging
  • Brain connectivity analysis
  • Functional magnetic resonance imaging (fMRI)
  • Magnetoencephalography (MEG) and electroencephalography (EEG)
  • Electrocorticography (ECoG) (or intracranial EEG (iEEG))
  • Transcranial magnetic stimulation (TMS)
  • Dynamic contrast enhancement MRI (DCE-MRI)
  • Epilepsy, Alzheimer’s disease, sleep disorder, and traumatic brain injury (TBI)

Research Interest

My research area is in the field of medical image and signal processing and analysis. In particular, I am interested in application of neuroimaging techniques, such as functional magnetic resonance imaging (fMRI), magnetoencephalography (MEG), electroencephalography (EEG), and electrocorticography (ECoG) in diagnostic and treatment of patients with epilepsy, Alzheimer’s disease, sleep disorder, and traumatic brain injury (TBI). My main research interest is the application of the brain connectivity analysis using fMRI and MEG/EEG in diagnostic and treatment of these diseases. For instance, I am utilizing the resting-state fMRI (rs-fMRI) brain connectivity analysis in Alzheimer’s disease (AD). We combine the machine learning algorithm, e.g. the support vector machine (SVM), with the graph theoretical approach to develop an accurate diagnostic tool based on the rs-fMRI for distinguishing three groups of subjects: healthy control, patients with mild cognitive impairment, and patients with AD.

         Another research area that I have been working is the functional, and in particular language, mapping using the intracranial ECoG recording, fMRI, MEG, and transcranial magnetic stimulation (TMS). Specifically, I am interested in studying enhancement of the power of ECoG recording in the high gamma (> 50 Hz) frequency range during different cognitive tasks (e.g. language and memory).

I am also interested in applications of the dynamic contrast-enhancement MRI (DCE-MRI) for characterizing tumors. I worked on determining the tumor size and expression of vascular endothelial growth factor receptors in treated and non-treated implanted glioma (U-251) by in vivo DCE-MRI and single photon emission computed tomography (SPECT). We also assessed the utility of non-model based ‘semi-quantitative’ indices derived from DCE-MRI for differentiating treatment induced necrosis from recurrent/progressive tumor patients. The proposed semi quantitative indices were robust and reproducible clinical tool that can help in quick and efficient decision-making in evaluating efficiency of new anti-angiogenic agents. 

Representative Publications

  • Mostame P, Moharramipour A, Hossein-Zadeh GA, Babajani-Feremi A. Statistical Significance Assessment of Phase Synchrony in the Presence of Background Couplings: An ECoG Study. Brain Topogr. 2019 May 25. doi: 10.1007/s10548-019-00718-8. [Epub ahead of print] PubMed PMID: 31129754.
  • Hojjati SH, Ebrahimzadeh A, Khazaee A, Babajani-Feremi A; Alzheimer's Disease Neuroimaging Initiative. Predicting conversion from MCI to AD by integrating rs-fMRI and structural MRI. Comput Biol Med. 2018 Nov 1;102:30-39. doi: 10.1016/j.compbiomed.2018.09.004. Epub 2018 Sep 15. PubMed PMID: 30245275.
  • Moharramipour A, Mostame P, Hossein-Zadeh GA, Wheless JW, Babajani-Feremi A. Comparison of statistical tests in effective connectivity analysis of ECoG data. J Neurosci Methods. 2018 Oct 1;308:317-329. doi: 10.1016/j.jneumeth.2018.08.026. Epub 2018 Sep 3. PubMed PMID: 30189285.
  • Babajani-Feremi A, Noorizadeh N, Mudigoudar B, Wheless JW. Predicting seizure outcome of vagus nerve stimulation using MEG-based network topology. Neuroimage Clin. 2018 Jun 18;19:990-999. doi: 10.1016/j.nicl.2018.06.017. eCollection 2018. PubMed PMID: 30003036; PubMed Central PMCID: PMC6039837.
  • Babajani-Feremi A, Holder CM, Narayana S, Fulton SP, Choudhri AF, Boop FA, Wheless JW. Predicting postoperative language outcome using presurgical fMRI, MEG, TMS, and high gamma ECoG. Clin Neurophysiol. 2018 Mar;129(3):560-571. doi: 10.1016/j.clinph.2017.12.031. Epub 2018 Jan 4. PubMed PMID: 29414401.
  • Narayana S, Mudigoudar B, Babajani-Feremi A, Choudhri AF, Boop FA. Successful motor mapping with transcranial magnetic stimulation in an infant: A case report. Neurology. 2017 Nov 14;89(20):2115-2117. doi: 10.1212/WNL.0000000000004650. Epub 2017 Oct 11. PubMed PMID: 29021352.

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