Contact

  • Academic
    naryeong@stanford.edu
    University - Student Department: Bioengineering Position: Undergraduate
    University - Student Department: Political Science Position: Undergraduate
    University - Student Department: Biology Position: Graduate

Additional Info

  • Mail Code: 5020

All Publications

  • Printing anthropomorphic multi-energy CT phantoms for spectral imaging with office laser printers SPIE Medical Imaging Yang, Y., Kim, N., Bennett, R., Wang, A. S. 2024

    View details for DOI 10.1117/12.3006581

  • Direct cortical stimulation induces short-term plasticity of neural oscillations in humans. bioRxiv : the preprint server for biology Munot, S., Kim, N., Huang, Y., Keller, C. J. 2023

    Abstract

    Patterned brain stimulation is commonly employed as a tool for eliciting plasticity in brain circuits and treating neuropsychiatric disorders. Although widely used in clinical settings, there remains a limited understanding of how stimulation-induced plasticity influences neural oscillations and their interplay with the underlying baseline functional architecture. To address this question, we applied 15 minutes of 10Hz focal electrical simulation, a pattern identical to 'excitatory' repetitive transcranial magnetic stimulation (rTMS), to 14 medically-intractable epilepsy patients undergoing intracranial electroencephalographic (iEEG). We quantified the spectral features of the cortico-cortical evoked potential (CCEPs) in these patients before and after stimulation. We hypothesized that for a given region the temporal and spectral components of the CCEP predicted the location and degree of stimulation-induced plasticity. Across patients, low frequency power (alpha and beta) showed the broadest change, while the magnitude of change was stronger in high frequencies (beta and gamma). Next we demonstrated that regions with stronger baseline evoked spectral responses were more likely to undergo plasticity after stimulation. These findings were specific to a given frequency in a specific temporal window. Post-stimulation power changes were driven by the interaction between direction of change in baseline power and temporal window of change. Finally, regions exhibiting early increases and late decreases in evoked baseline power exhibited power changes after stimulation and were independent of stimulation location. Together, these findings that time-frequency baseline features predict post-stimulation plasticity effects demonstrate properties akin to Hebbian learning in humans and extend this theory to the temporal and spectral window of interest. These findings can help improve our understanding of human brain plasticity and lead to more effective brain stimulation techniques.

    View details for DOI 10.1101/2023.11.15.567302

    View details for PubMedID 38014071

    View details for PubMedCentralID PMC10680685

  • An On-Site Machine Learning Assessment Tool Using Heart Rate Variability (HRV) As a Novel Biomarker for Concussion Diagnosis Kim, N., Samavedi, S., Zimmerman, C., Fisher, M., DiSario, J. 2023
  • Personalized Repetitive Transcranial Magnetic Stimulation for Depression. Biological psychiatry. Cognitive neuroscience and neuroimaging Gogulski, J., Ross, J. M., Talbot, A., Cline, C. C., Donati, F. L., Munot, S., Kim, N., Gibbs, C., Bastin, N., Yang, J., Minasi, C., Sarkar, M., Truong, J., Keller, C. J. 2022

    Abstract

    Personalized treatments are gaining momentum across all fields of medicine. Precision medicine can be applied to neuromodulatory techniques, in which focused brain stimulation treatments such as repetitive transcranial magnetic stimulation (rTMS) modulate brain circuits and alleviate clinical symptoms. rTMS is well tolerated and clinically effective for treatment-resistant depression and other neuropsychiatric disorders. Despite its wide stimulation parameter space (location, angle, pattern, frequency, and intensity can be adjusted), rTMS is currently applied in a one-size-fits-all manner, potentially contributing to its suboptimal clinical response (∼50%). In this review, we examine components of rTMS that can be optimized to account for interindividual variability in neural function and anatomy. We discuss current treatment options for treatment-resistant depression, the neural mechanisms thought to underlie treatment, targeting strategies, stimulation parameter selection, and adaptive closed-loop treatment. We conclude that a better understanding of the wide and modifiable parameter space of rTMS will greatly improve the clinical outcome.

    View details for DOI 10.1016/j.bpsc.2022.10.006

    View details for PubMedID 36792455

  • Spectral-Temporal Electrophysiological Features Predict Short-Term Plasticity in Humans Following Repetitive Stimulation Munot, S., Kim, N., Ganesan, G., Talbot, A., Keller, C. ELSEVIER SCIENCE INC. 2022: S202

    View details for Web of Science ID 000789022200494

  • Drive-through Medicine for COVID-19 and Future Pandemics WESTERN JOURNAL OF EMERGENCY MEDICINE Ngo, J., Ravi, S., Kim, N., Boukhman, M. 2021; 22 (2): 252–56

    View details for DOI 10.5811/westjem.2020.9.48799

    View details for Web of Science ID 000628776700016

  • Spectral-temporal electrophysiological features predict short-term plasticity in humans 4th International Brain Stimulation Conference Kim, N., Munot, S., Ganesan, G., Keller, C. 2021: 3.108
  • Drive-through Medicine for COVID-19 and Future Pandemics. The western journal of emergency medicine Ngo, J., Ravi, S., Kim, N., Boukhman, M. 2020; 22 (2): 252-256

    View details for DOI 10.5811/westjem.2020.9.48799

    View details for PubMedID 33856308

    View details for PubMedCentralID PMC7972391