Tzyy-Ping Jung - US grants
Affiliations: | SCCN | University of California, San Diego, La Jolla, CA |
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The funding information displayed below comes from the NIH Research Portfolio Online Reporting Tools and the NSF Award Database.The grant data on this page is limited to grants awarded in the United States and is thus partial. It can nonetheless be used to understand how funding patterns influence mentorship networks and vice-versa, which has deep implications on how research is done.
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High-probability grants
According to our matching algorithm, Tzyy-Ping Jung is the likely recipient of the following grants.Years | Recipients | Code | Title / Keywords | Matching score |
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2014 — 2015 | Kirsh, David (co-PI) [⬀] Jung, Tzyy-Ping Brown, Sheldon Saygin, Ayse (co-PI) [⬀] Viirre, Erik (co-PI) [⬀] |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
@ University of California-San Diego The project proposes to create a distributed, multi-user social computing environment that will develop the capabilities of human Electroencephalography (EEG) to analyze users engagement with digitally based experiences. For this project, users will wear non-invasive, EEG headsets while navigating a shared virtual world. Beginning with a handful of EEG systems, the team will scale up over the course of the project to gather signals from dozens of users, providing a basis for larger scale studies. By comparing the EEG signals with each participants activities in virtual world, and with the brain activity and the activities of other users, a model of human brain activity will be developed for different types of behavior profiles and subjective states. This will allow significant improvement for the development of neural markers of human perceptual, cognitive and affective states, the parsing of EEG signals, the applicability of EEG interfaces to new types of experiences, all of which can enhance distance learning, collaborative distributed work, improved mobile computing interfaces and health care applications. The project will advance the capabilities for determining an individuals cognitive state by the creation of new computing methods utilizing comparative EEG analysis and data analysis of event states in a digital simulation. Bringing methods of large scale data analysis to articulate patterns across many users in the situated milieu of the online virtual world will create a new method to utilize EEG analysis to infer human subjective experience. The necessity of conducting this analysis in real-time, with data gathered from distributed, wireless EEG instruments will provide the impetus for utilizing accelerated hybrid multi-core techniques to bear on this domain. |
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2015 — 2016 | Jung, Tzyy-Ping Medeiros, Felipe |
R21Activity Code Description: To encourage the development of new research activities in categorical program areas. (Support generally is restricted in level of support and in time.) |
Development of a Portable Objective Method For Assessment of Visual Field Loss @ University of California San Diego ? DESCRIPTION (provided by applicant): Glaucoma is a leading cause of irreversible blindness and disability. The disease can remain relatively asymptomatic until late stages and, therefore, early detection and monitoring of functional damage is paramount to prevent functional impairment and blindness. Detection of functional loss in the disease has traditionally been made using standard automated perimetry (SAP). However, SAP testing is limited by the complexity of the examination, subjectivity of patient responses, large variability, cost, and lack of portability. The overall goal of this proposal is to address limitations of currently available techniques by developing a portable objective method for assessment of visual field loss in glaucoma. The investigations of this proposal will address the following 3 specific aims: 1) To develop a portable, objective, multifocal steady state (mfSSVEP)-based visual field assessment platform, integrating a wearable, wireless dry EEG system and a head-mounted display; 2) To develop and validate an Electrooculogram (EOG)-guided method to assess eye- gaze during testing with the envisioned portable platform and 3) To evaluate the reproducibility of the envisioned platform and to conduct preliminary studies evaluating its ability to detect visual fiel loss in patients with glaucoma compared to healthy control subjects. In Specific Aim 1, we will develop a prototype portable device integrating a dry-electrode EEG platform to a cell phone-based head-mounted display for stimulus presentation. We have used similar technology for recent development of brain-computer interfaces, with wireless SSVEP data acquisition and processing. In our preliminary investigation, we have also shown the feasibility of using mfSSVEP for assessment of visual field loss. In the current investigation, advanced signal processing methods will be used to improve signal-to-noise ratio of mfSSVEP from high-density recording. Exploratory studies will be conducted by varying test parameters until a stable testing platform is achieved. In Specific Aim 2, we will integrate an EOG method to the portable plataform, in order to identify fixation losses and allow identification of unreliable mfSSVEP signals to be removed from further analyses. Appropriate eye fixation is essential in order to ensure matching of SSVEP signals to corresponding visual field locations. We will conduct experiments to assess whether the EOG method to filter out unreliable signals improves the accuracy of mfSSVEP to detect visual field losses. In Specific Aim 3, we will conduct validating studies evaluating the reproducibility of measurements obtained with the proposed device, as well as its accuracy for detecting visual field loss in patients with glaucoma. A validated, portable, objective method for assessment of visual field loss in glaucoma may potentially improve screening, diagnosis and detection of glaucoma progression and reduce rates of functional impairment and blindness from the disease. |
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2015 — 2018 | Jung, Tzyy-Ping Khalil, Alexander (co-PI) [⬀] Iversen, John Fitzgerald, Matthew Kalbfleisch, Layne (co-PI) [⬀] |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Sl-Cn: Group Brain Dynamics in Learning Network @ University of California-San Diego Electrophysiology has long played an important role in our understanding of brain dynamics in learning, but only at an individual level. With the advent of low-cost, easy to use electroencephalography (EEG) devices that can measure brain responses from an entire classroom at a time, it is now possible to study group brain dynamics during learning in a naturalist classroom setting. This is opportunity to gather data from thousands of students and schools will provide insights not available from earlier approaches. There is however, a critical need to rigorously define how this technology might play a role in improving learning. To address this need, the present project will form a research network of experts to develop and test new EEG methods to measure group brain dynamics. This network includes experts in child development, learning EEG technology, classroom teaching and outreach. Collaborative research will be conducted in three geographic areas reflecting diverse populations: San Diego, the San Francisco Bay Area and the Washington DC Area. The research will focus on assessing important foundational skills: using EEG to assess the quality of encoding of speech by the brain, using EEG to assess attention in real-time, and examining the role of temporal synchronization in promoting attentional behaviors. In addition to research the project features a strong commitment to building interdisciplinary connections within science, as well as vigorously engaging the study communities in the research to foster productive dialog among educators, students, and other researchers. |
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2017 — 2020 | Chi, Yu Mullen, Tim (co-PI) [⬀] Cauwenberghs, Gert [⬀] Makeig, Scott (co-PI) [⬀] Jung, Tzyy-Ping |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Pfi:Bic - Unobtrusive Neurotechnology and Immersive Human-Computer Interface For Enhanced Learning @ University of California-San Diego The increasing prevalence of learning disorders, attention deficits, and lackluster appetite for reading across all walks of life, and particularly among school-age children, poses severe problems to humanity and, in the long run, burdens social and economic development. This Partnership for Innovation Building Innovation Capacity (PFI:BIC) collaborative project tackles the impending threats to humanity of illiteracy and faltering education heads-on by creating a new smart-service human-computer interface (HCI) neurotechnology platform as a highly effective, user-friendly, and fun-to-use tool aiding learning and stimulating cognitive development at home and in the classroom. The immersive HCI neurotechnology will allow directly measuring progress at the cognitive level and providing real-time feedback to guide the user in learning to read more effectively. The project is highly Science, Technology, Engineering and Mathematics (STEM) intensive both in its activities and in the targeted benefits of the developed technology, which extends directly to learning science and mathematics by probing cognitive performance of children while they solve puzzles. The development of unobtrusive neurotechnology further addresses a critical need for practical integrated and modular brain-computer interface (BCI) solutions in HCI promoting widespread consumer and clinical use in the marketplace. The partnership provides opportunities for students to gain practical experience in innovation in the marketplace through internships with the industrial partners. |
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2017 — 2020 | Jung, Tzyy-Ping Wu, Ying Choon Brown, Sheldon |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
The Impact of Real World Stressors On Problem-Solving @ University of California-San Diego This project examines how variability in daily stress and fatigue--previously dismissed as uncontrollable 'noise' in cognitive processing--relates to variability in learning and problem-solving. This project is motivated in part by evidence that performance on tests of executive function and memory can fluctuate as a function of recently experienced, real-world, daily stressors. Because problem-solving recruits these and other cognitive abilities, it is hypothesized that day-to-day stressors can also impact our approaches to and success with complex, open-ended challenges regularly faced in educational and professional contexts. Further, on the basis of preliminary research, it is anticipated that a subset of individuals will exhibit greater resilience to stressors than others. In other words, for some, day-to-day stressors may create contexts that facilitate tackling problems to greater or lesser degrees, whereas for others, recent stressors may impact outcomes minimally. This work wields important implications for STEM education given the increasing priority placed on problem-solving skills. It will offer new foundations for modeling individual differences in resilience and vulnerability to everyday stressors during complex tasks. Moreover, understanding stressor-related intra-individual variability can lead to strategies for improving performance of high-stakes, resource demanding operations (e.g., piloting an airplane). |
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2020 | Jung, Tzyy-Ping | N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
@ University of California-San Diego UCSD and FDA will jointly develop and test a wearable and easily deployable system, based on virtual-reality goggles, to collect synchronized brain and biometric signals from mild traumatic brain injury (TBI) patients and healthy participants. They will also develop advanced computational approaches to identify abnormal biomedical signals associated with TBI. The goal of this project is to test the feasibility of using a portable, compact, and deployable system as a pre- and post-hospital diagnostic and monitoring tool of TBI. |
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