Brain Imaging – EEG fMRI

EEG References

  1. Gupta, D., Du, X., Summerfelt, A., Hong, L. E., & Choa, F.-S. (2023). Brain connectivity signature extractions from TMS invoked EEGs. Sensors, 23, 4078. https://doi.org/10.3390/s23084078
  2. Gupta, D., Summerfelt, A., Luzhansky, J., Li, D., Hong, E., & Choa, F.-S. (2021). LEDA-Localized-EEG Dynamics Analyzer: a MATLAB-Based Innovative Toolbox for Analysis of EEG Source Dynamics. Journal of Signal Processing Systems, 93, 951–964. http://dx.doi.org/10.1007/s11265-020-01617-z
  3. Meng, Q., Gupta, D., Wudenhe, A., Du, X., Hong, L. E., & Choa, F.-S. (2017). Three-dimensional EEG signal tracking for reproducible monitoring of self-contemplating imagination. Advances in Science, Technology and Engineering Systems Journal, 2(3), 1634–1646. https://doi.org/10.25046/aj0203203
  4. Gupta, D., Du, X., Velraj, J., Varanasi, S., Hong, E., & Choa, F.-S. (2022). Three-dimension EEG-based connectivity biomarkers for neurological disorder detections. In Cullum, B. M., McLamore, E. S., & Kiehl, D. (Eds.), Smart Biomedical and Physiological Sensor Technology XIV. SPIE Proceedings Volume 12123.
  5. Chowdhury, F. N., Sood, R., Nam, H., Lobo, M. K., & Choa, F.-S. (2019). Flexible polyimide-based 34-channel electrode arrays for mouse EEG measurement. SPIE Proceedings Volume 11020, Smart Biomedical and Physiological Sensor Technology XV, 110200T. https://doi.org/10.1117/12.2518830
  6. Gupta, D., Du, X., Hong, E., & Choa, F.-S. (2019). Neural Connectivity Analysis by using 3-D TMS-EEG with Source Localization and Sliding Window Coherence Techniques. SPIE Proceedings: Signal Processing, Sensor/Information Fusion, and Target Recognition XXVIII. https://doi.org/10.1117/12.2519065
  7. Gupta, D., Du, X., Hong, L., & Choa, F.-S. (2019). TMS-EEG based Source Localized Connectivity Signature Extraction by using Unsupervised Machine Learning. 9th International IEEE/EMBS Conference on Neural Engineering (NER), San Francisco, CA. https://doi.org/10.1109/NER.2019.8716962
  8. Wudenhe, A., Meng, Q., & Choa, F.-S. (2016). Three-Dimensional EEG Signal Tracking for Reproducible Brain Activity Monitoring. IEEE Signal Processing in Medicine and Biology Symposium, Paper P01.08, Temple University, Philadelphia, PA. https://doi.org/10.1109/spmb.2016.7846869
  9. Meng, Q., Hong, E., & Choa, F.-S. (2016). Electroencephalograph (EEG) Study on Self-Contemplating Image Formation. Proc. SPIE 9863, Smart Biomedical and Physiological Sensor Technology XIII, 98630X. https://doi.org/10.1117/12.2225132
  10. Meng, Q., Hong, E., & Choa, F.-S. (2015). Electroencephalograph (EEG) study of brain bistable illusion. SPIE DSS 9487. https://doi.org/10.1117/12.2177520
  11. Meng, Q., Choa, F.-S., Hong, E., Wang, Z., & Islam, M. (2014). Control channels in the brain and their influence on brain executive functions. SPIE Defense, Security, and Sensing Conference, Paper 9107-42. https://doi.org/10.1117/12.2050147

fMRI References

  1. Allen, J. D., Varanasi, S., Han, F., Hong, L. E., & Choa, F.-S. (2024). Functional Connectivity Biomarker Extraction for Schizophrenia Based on Energy Landscape Machine Learning Techniques. Sensors, 24(23), 7742. https://doi.org/10.3390/s24237742
  2. Varanasi, S., Tuli, R., Han, F., Chen, R., & Choa, F.-S. (2023). Age Related Functional Connectivity Signature Extraction Using Energy-Based Machine Learning Techniques. Sensors, 23(3), 1603. https://doi.org/10.3390/s23031603
  3. Varanasi, S., Zhai, T., Gu, H., Yang, Y., & Choa, F.-S. (2024). Functional connectivity differences between cocaine users and healthy controls: an fMRI study. In Cullum, B. M., McLamore, E. S., & Kiehl, D. (Eds.), Smart Biomedical and Physiological Sensor Technology XXI (p. 9). SPIE. https://doi.org/10.1117/12.3013689
  4. Varanasi, S., Zhai, T., Gu, H., Yang, Y., & Choa, F.-S. (2024). Extracting functional connectivity signatures in substance use disorder using energy landscape analysis. In Cullum, B. M., McLamore, E. S., & Kiehl, D. (Eds.), Smart Biomedical and Physiological Sensor Technology XXI (p. 8). SPIE. https://doi.org/10.1117/12.3013694
  5. Allen, J. D., Xia, L., Hong, L. E., & Choa, F.-S. (2024). Exploring connections between auditory hallucinations and language model structures and functions. In Cullum, B. M., McLamore, E. S., & Kiehl, D. (Eds.), Smart Biomedical and Physiological Sensor Technology XXI (p. 10). SPIE. https://doi.org/10.1117/12.3013964
  6. Allen, J. D., Xia, L., Hong, L. E., & Choa, F.-S. (2024). Exploring connections between auditory hallucinations and language model structures and functions. Proc. SPIE 13059, Smart Biomedical and Physiological Sensor Technology XXI, 130590A. https://doi.org/10.1117/12.3013964
  7. Allen, J., Varanasi, S., Chen, R., Hong, E., & Choa, F.-S. (2023). Observing Brain Most Visited Common Band Connectivity States from fMRI Resting State Studies. IEEE 11th International IEEE/EMBS Conference on Neural Engineering (NER), 1–4. https://doi.org/10.1109/ner52421.2023.10123853
  8. Allen, J. D., Varanasi, S., Hong, E., & Choa, F.-S. (2022). Flexible energy landscape analysis of functional connectivity through region bundling. In Grewe, L. L., Blasch, E. P., & Kadar, I. (Eds.), Signal Processing, Sensor/Information Fusion, and Target Recognition XXXI. SPIE Proceedings Volume 12122. http://dx.doi.org/10.1117/12.2619126
  9. Varanasi, S., Allen, J. D., Chen, R., Sahoo, K. P., Patra, A., & Choa, F.-S. (2022). Energy landscape analysis based sliding window studies of brain dynamics in young and old subjects. In Grewe, L. L., Blasch, E. P., & Kadar, I. (Eds.), Signal Processing, Sensor/Information Fusion, and Target Recognition XXXI. Proc. SPIE 12122, 1212212. http://dx.doi.org/10.1117/12.2618951
  10. Udall, J., & Choa, F.-S. (2022). Comparing energy levels in brain regions of interest in ADHD subjects. In Cullum, B. M., McLamore, E. S., & Kiehl, D. (Eds.), Smart Biomedical and Physiological Sensor Technology XIX. SPIE Proceedings Volume 12123, 1212305. http://dx.doi.org/10.1117/12.2618207
  11. Varanasi, S., Allen, J., Chen, R., & Choa, F.-S. (2021). Sliding window study of brain connectivity dynamics based on Energy Landscape analysis. SPIE Proceedings Volume 11756, Signal Processing, Sensor/Information Fusion, and Target Recognition XXX, 117560Z. https://doi.org/10.1117/12.2588048
  12. Allen, J. D., Varanasi, S., Hong, E., & Choa, F.-S. (2021). Energy landscape analysis of fMRI data from schizophrenic and healthy subjects. SPIE Proceedings Volume 11756, Signal Processing, Sensor/Information Fusion, and Target Recognition XXX, 1175610. https://doi.org/10.1117/12.2588046