Angel Vladimirov Peterchev

Angel Vladimirov Peterchev

Associate Professor in Psychiatry and Behavioral Sciences

External Address: 
Dept. Psychiatry & Behavioral, Box 3620 DUMC, Durham, NC 27710
Phone: 
919.684.0383

Overview

I direct the Brain Stimulation Engineering Lab (BSEL) which focuses on the development and modeling of devices and application paradigms for transcranial brain stimulation. Transcranial brain stimulation involves non-invasive delivery of fields (e.g., electric and magnetic) to the brain that modulate neural activity. Transcranial brain stimulation is increasingly used as a tool for brain research and a therapeutic intervention in neurology and psychiatry. My lab works closely with neuroscientists and clinicians to translate novel brain stimulation technology and optimize existing techniques. For example, we have developed a device for transcranial magnetic stimulation (TMS) that allows extensive control over the magnetic pulse parameters. We are currently deploying this device to optimize the magnetic stimulus in neuromodulatory TMS paradigms. We are also developing efficient algorithms for response estimation and individualization of brain stimulation. Another line of work is finite element computational modeling of the fields induced in the brain by electric and magnetic stimulation. My lab is involved in the integration of transcranial brain stimulation with imaging modalities such as functional magnetic resonance imaging (fMRI) and electroencephalography (EEG), as well as the evaluation of the safety of device–device interactions, for example between transcranial stimulators and implants like deep-brain stimulation (DBS) systems.

In parallel, I pursue projects related to power electronics, with applications in electrical energy conversion and storage. Recent projects include modular multilevel converters for solar energy conversion and storage, grid storage applications, as well as electric vehicles.

Education & Training

  • Ph.D., University of California - Berkeley 2005

Selected Grants

Medical Scientist Training Program awarded by National Institutes of Health (Mentor). 1997 to 2022

Realistic Measurements of tDCS-Modulated Activity and Electric Fields in the Human Brain In Vivo awarded by National Institutes of Health (Collaborator). 2019 to 2021

Impact of Timing, Targeting, and Brain State on rTMS of Human and Non-Human Primates awarded by National Institutes of Health (Co Investigator). 2017 to 2021

Transcranial magnetic stimulation with enhanced focality and depth (fdTMS) awarded by National Institutes of Health (Principal Investigator). 2017 to 2021

Quiet TMS: A Low-Acoustic-Noise Transcranial Magnetic Stimulation System awarded by National Institutes of Health (Principal Investigator). 2016 to 2021

Rational Design of TMS for Neuromodulation awarded by National Institutes of Health (Co-Principal Investigator). 2014 to 2021

Using fMRI-guided TMS to increase central executive function in older adults awarded by National Institutes of Health (Investigator). 2015 to 2021

Innovating the Transcranial Magnetic Stimulation Market: Modular Pulse Synthesizer for Flexible Stimulus Delivery awarded by North Carolina Biotechnology Center (Principal Investigator). 2016 to 2021

Pages

Peterchev, A. V., et al. “Advances in Transcranial Magnetic Stimulation Technology.” Brain Stimulation: Methodologies and Interventions, 2015, pp. 165–89. Scopus, doi:10.1002/9781118568323.ch10. Full Text

Luber, Bruce, et al. “Application of Transcranial Magnetic Stimulation (TMS) in Psychophysiology.” Handbook of Psychophysiology, Cambridge University Press, pp. 120–38. Crossref, doi:10.1017/cbo9780511546396.005. Full Text

Beynel, Lysianne, et al. “Structural controllability predicts functional patterns and brain stimulation benefits associated with working memory.J Neurosci, July 2020. Pubmed, doi:10.1523/JNEUROSCI.0531-20.2020. Full Text

Gamboa, Olga Lucia, et al. “Application of long-interval paired-pulse transcranial magnetic stimulation to motion-sensitive visual cortex does not lead to changes in motion discrimination.Neurosci Lett, vol. 730, June 2020, p. 135022. Pubmed, doi:10.1016/j.neulet.2020.135022. Full Text Open Access Copy

Gamboa Arana, Olga Lucia, et al. Dose-dependent enhancement of motion direction discrimination with transcranial magnetic stimulation of visual cortex. June 2020. Epmc, doi:10.1101/2020.06.14.151118. Full Text

Crowell, C. A., et al. “Older adults benefit from more widespread brain network integration during working memory.Neuroimage, vol. 218, May 2020, p. 116959. Pubmed, doi:10.1016/j.neuroimage.2020.116959. Full Text Open Access Copy

Koponen, Lari M., et al. “Sound comparison of seven TMS coils at matched stimulation strength.Brain Stimul, vol. 13, no. 3, May 2020, pp. 873–80. Pubmed, doi:10.1016/j.brs.2020.03.004. Full Text

Beynel, Lysianne, et al. “Site-Specific Effects of Online rTMS during a Working Memory Task in Healthy Older Adults.Brain Sci, vol. 10, no. 5, Apr. 2020. Pubmed, doi:10.3390/brainsci10050255. Full Text Open Access Copy

Aberra, Aman S., et al. “Simulation of transcranial magnetic stimulation in head model with morphologically-realistic cortical neurons.Brain Stimul, vol. 13, no. 1, Jan. 2020, pp. 175–89. Pubmed, doi:10.1016/j.brs.2019.10.002. Full Text

Gomez, Luis J., et al. “Conditions for numerically accurate TMS electric field simulation.Brain Stimul, vol. 13, no. 1, Jan. 2020, pp. 157–66. Pubmed, doi:10.1016/j.brs.2019.09.015. Full Text

Bikson, Marom, et al. “Transcranial electrical stimulation nomenclature.Brain Stimul, vol. 12, no. 6, Nov. 2019, pp. 1349–66. Pubmed, doi:10.1016/j.brs.2019.07.010. Full Text

Pages

Hans Bahamonde, I., et al. “Different parallel connections generated by the Modular Multilevel Series/Parallel Converter: An overview.” Iecon Proceedings (Industrial Electronics Conference), vol. 2019-October, 2019, pp. 6114–19. Scopus, doi:10.1109/IECON.2019.8927286. Full Text

Wang, C., et al. “Online switch open-circuit fault diagnosis using reconfigurable scheduler for modular multilevel converter with parallel connectivity.” 2019 21st European Conference on Power Electronics and Applications, Epe 2019 Ecce Europe, 2019. Scopus, doi:10.23919/EPE.2019.8915402. Full Text

Wang, C., et al. “Closed-loop predictively optimizing control for modular multilevel converter with parallel connectivity.” 2019 21st European Conference on Power Electronics and Applications, Epe 2019 Ecce Europe, 2019. Scopus, doi:10.23919/EPE.2019.8915103. Full Text

Wang, C., et al. “Submodule short-circuit fault diagnosis based on wavelet transform and support vector machines for modular multilevel converter with series and parallel connectivity.” Proceedings Iecon 2017  43rd Annual Conference of the Ieee Industrial Electronics Society, vol. 2017-January, 2017, pp. 3239–44. Scopus, doi:10.1109/IECON.2017.8216547. Full Text

Li, Z., et al. “Ripple current suppression methods for star-configured modular multilevel converters.” Proceedings Iecon 2017  43rd Annual Conference of the Ieee Industrial Electronics Society, vol. 2017-January, 2017, pp. 1505–10. Scopus, doi:10.1109/IECON.2017.8216256. Full Text

Li, Z., et al. “Predictive control of modular multilevel series/parallel converter for battery systems.” 2017 Ieee Energy Conversion Congress and Exposition, Ecce 2017, vol. 2017-January, 2017, pp. 5685–91. Scopus, doi:10.1109/ECCE.2017.8096945. Full Text

Li, Z., et al. “Distributed balancing control for modular multilevel series/parallel converter with capability of sensorless operation.” 2017 Ieee Energy Conversion Congress and Exposition, Ecce 2017, vol. 2017-January, 2017, pp. 1787–93. Scopus, doi:10.1109/ECCE.2017.8096011. Full Text

Beynel, Lysianne, et al. “fMRI- and Computationally-Guided rTMS Enhances Performance in Working Memory Manipulation.” Neuropsychopharmacology, vol. 42, NATURE PUBLISHING GROUP, 2017, pp. S114–15.

Wang, C., et al. “Photovoltaic multilevel inverter with distributed maximum power point tracking and dynamic circuit reconfiguration.” 2017 Ieee 3rd International Future Energy Electronics Conference and Ecce Asia, Ifeec  Ecce Asia 2017, 2017, pp. 1520–25. Scopus, doi:10.1109/IFEEC.2017.7992271. Full Text

Luber, Bruce, et al. “Using Diffusion Tensor Imaging to Effectively Target TMS to Deep Brain Structures.” Neuropsychopharmacology, vol. 41, 2016, pp. S524–25.

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