@article{chen_peng_wu_huang_kim_traylor_muller_chhatbar_nam_feng_et al._2022, title={Numerical and experimental evaluation of low-intensity transcranial focused ultrasound wave propagation using human skulls for brain neuromodulation}, volume={11}, ISSN={["2473-4209"]}, DOI={10.1002/mp.16090}, abstractNote={AbstractBackgroundLow‐intensity transcranial focused ultrasound (tFUS) has gained considerable attention as a promising noninvasive neuromodulatory technique for human brains. However, the complex morphology of the skull hinders scholars from precisely predicting the acoustic energy transmitted and the region of the brain impacted during the sonication. This is due to the fact that different ultrasound frequencies and skull morphology variations greatly affect wave propagation through the skull.PurposeAlthough the acoustic properties of human skull have been studied for tFUS applications, such as tumor ablation using a multielement phased array, there is no consensus about how to choose a single‐element focused ultrasound (FUS) transducer with a suitable frequency for neuromodulation. There are interests in exploring the magnitude and dimension of tFUS beam through human parietal bone for modulating specific brain lobes. Herein, we aim to investigate the wave propagation of tFUS on human skulls to understand and address the concerns above.MethodsBoth experimental measurements and numerical modeling were conducted to investigate the transmission efficiency and beam pattern of tFUS on five human skulls (C3 and C4 regions) using single‐element FUS transducers with six different frequencies (150–1500 kHz). The degassed skull was placed in a water tank, and a calibrated hydrophone was utilized to measure acoustic pressure past it. The cranial computed tomography scan data of each skull were obtained to derive a high‐resolution acoustic model (grid point spacing: 0.25 mm) in simulations. Meanwhile, we modified the power‐law exponent of acoustic attenuation coefficient to validate numerical modeling and enabled it to be served as a prediction tool, based on the experimental measurements.ResultsThe transmission efficiency and −6 dB beamwidth were evaluated and compared for various frequencies. An exponential decrease in transmission efficiency and a logarithmic decrease of −6 dB beamwidth with an increase in ultrasound frequency were observed. It is found that a >750 kHz ultrasound leads to a relatively lower tFUS transmission efficiency (<5%), whereas a <350 kHz ultrasound contributes to a relatively broader beamwidth (>5 mm). Based on these observations, we further analyzed the dependence of tFUS wave propagation on FUS transducer aperture size.ConclusionsWe successfully studied tFUS wave propagation through human skulls at different frequencies experimentally and numerically. The findings have important implications to predict tFUS wave propagation for ultrasound neuromodulation in clinical applications, and guide researchers to develop advanced ultrasound transducers as neural interfaces.}, journal={MEDICAL PHYSICS}, author={Chen, Mengyue and Peng, Chang and Wu, Huaiyu and Huang, Chih-Chung and Kim, Taewon and Traylor, Zachary and Muller, Marie and Chhatbar, Pratik Y. and Nam, Chang S. and Feng, Wuwei and et al.}, year={2022}, month={Nov} }
 @article{mousavian_chen_traylor_greening_2021, title={Depression detection from sMRI and rs-fMRI images using machine learning}, volume={8}, ISSN={["1573-7675"]}, url={http://dx.doi.org/10.1007/s10844-021-00653-w}, DOI={10.1007/s10844-021-00653-w}, journal={JOURNAL OF INTELLIGENT INFORMATION SYSTEMS}, publisher={Springer Science and Business Media LLC}, author={Mousavian, Marzieh and Chen, Jianhua and Traylor, Zachary and Greening, Steven}, year={2021}, month={Aug} }
 @misc{nam_traylor_chen_jiang_feng_chhatbar_2021, title={Direct Communication Between Brains: A Systematic PRISMA Review of Brain-To-Brain Interface}, volume={15}, ISSN={["1662-5218"]}, url={http://dx.doi.org/10.3389/fnbot.2021.656943}, DOI={10.3389/fnbot.2021.656943}, abstractNote={This paper aims to review the current state of brain-to-brain interface (B2BI) technology and its potential. B2BIs function via a brain-computer interface (BCI) to read a sender's brain activity and a computer-brain interface (CBI) to write a pattern to a receiving brain, transmitting information. We used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) to systematically review current literature related to B2BI, resulting in 15 relevant publications. Experimental papers primarily used transcranial magnetic stimulation (tMS) for the CBI portion of their B2BI. Most targeted the visual cortex to produce phosphenes. In terms of study design, 73.3% (11) are unidirectional and 86.7% (13) use only a 1:1 collaboration model (subject to subject). Limitations are apparent, as the CBI method varied greatly between studies indicating no agreed upon neurostimulatory method for transmitting information. Furthermore, only 12.4% (2) studies are more complicated than a 1:1 model and few researchers studied direct bidirectional B2BI. These studies show B2BI can offer advances in human communication and collaboration, but more design and experiments are needed to prove potential. B2BIs may allow rehabilitation therapists to pass information mentally, activating a patient's brain to aid in stroke recovery and adding more complex bidirectionality may allow for increased behavioral synchronization between users. The field is very young, but applications of B2BI technology to neuroergonomics and human factors engineering clearly warrant more research.}, journal={FRONTIERS IN NEUROROBOTICS}, publisher={Frontiers Media SA}, author={Nam, Chang S. and Traylor, Zachary and Chen, Mengyue and Jiang, Xiaoning and Feng, Wuwei and Chhatbar, Pratik Yashvant}, year={2021}, month={May} }
 @article{rakhmatulin_parfenov_traylor_nam_lebedev_2021, title={Low-cost brain computer interface for everyday use}, volume={9}, url={http://dx.doi.org/10.1007/s00221-021-06231-4}, DOI={10.1007/s00221-021-06231-4}, abstractNote={With the growth in electroencephalography (EEG) based applications the demand for affordable consumer solutions is increasing. Here we describe a compact, low-cost EEG device suitable for daily use. The data are transferred from the device to a personal server using the TCP-IP protocol, allowing for wireless operation and a decent range of motion for the user. The device is compact, having a circular shape with a radius of only 25 mm, which would allow for comfortable daily use during both daytime and nighttime. Our solution is also very cost effective, approximately $350 for 24 electrodes. The built-in noise suppression capability improves the accuracy of recordings with a peak input noise below 0.35 μV. Here, we provide the results of the tests for the developed device. On our GitHub page, we provide detailed specification of the steps involved in building this EEG device which should be helpful to readers designing similar devices for their needs  https://github.com/Ildaron/ironbci .}, journal={Experimental Brain Research}, publisher={Springer Science and Business Media LLC}, author={Rakhmatulin, Ildar and Parfenov, Andrey and Traylor, Zachary and Nam, Chang S. and Lebedev, Mikhail}, year={2021}, month={Sep} }