Open Access. Powered by Scholars. Published by Universities.®
Neuroscience and Neurobiology Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Institution
- Keyword
-
- Adaptation (1)
- Applied sciences (1)
- Biofouling (1)
- Biological sciences (1)
- Brain Computer Interfaces (1)
-
- Co-adaptive (1)
- Criticality (1)
- ECoG (1)
- Fatigue (1)
- Feature Selection (1)
- Frequency (1)
- HFO (1)
- High (1)
- Hydrocephalus (1)
- MEMS (1)
- Magnetic microactuators (1)
- Neural Engineering (1)
- Oscillation (1)
- Polyimide (1)
- Prediction (1)
- Pure sciences (1)
- Seizure (1)
- Signal processing (1)
- Sparse Algorithms (1)
- Turtle (1)
- Visual cortex (1)
- Publication
- Publication Type
Articles 1 - 6 of 6
Full-Text Articles in Neuroscience and Neurobiology
Synchronization Of Coupled Neurons Via Robust Feedback, Hector Puebla, Ricardo Aguilar-Lopez, Priti Kumar Roy
Synchronization Of Coupled Neurons Via Robust Feedback, Hector Puebla, Ricardo Aguilar-Lopez, Priti Kumar Roy
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Mechanical Reliability Of Implantable Polyimide-Based Magnetic Microactuators For Biofouling Removal, Christian G. Figueroa-Espada, Qi Yang, Hyowon Lee
Mechanical Reliability Of Implantable Polyimide-Based Magnetic Microactuators For Biofouling Removal, Christian G. Figueroa-Espada, Qi Yang, Hyowon Lee
The Summer Undergraduate Research Fellowship (SURF) Symposium
Hydrocephalus is a neurological disorder that typically requires a long-term implantation of a shunt system to manage its symptoms. These shunt systems are notorious for their extremely high failure rate. More than 40% of all implanted shunt systems fail within the first year of implantation. On average, 85% of all hydrocephalus patients with shunt systems undergo at least two shunt-revision surgeries within 10 years of implantation. A large portion of this high failure rate can be attributed to biofouling-related obstructions and infections. Previously, we developed flexible polyimide-based magnetic microactuators to remove obstructions formed on hydrocephalus shunts. To test the long-term …
Development And Investigation Of Sparse Co-Adaptive Algorithms In Ecog Based Closed-Loop Brain Computer Interface, Piyush Karande
Development And Investigation Of Sparse Co-Adaptive Algorithms In Ecog Based Closed-Loop Brain Computer Interface, Piyush Karande
McKelvey School of Engineering Theses & Dissertations
Electrocorticography (ECoG) has gained a lot of momentum and has become a serious contender as a recording modality for the implementation of Brain-Computer Interface (BCI) systems in the last few years. ECoG signals provide the right balance between minimal invasiveness and robust spectral information to accomplish a BCI task. However, all the BCI studies until now have used signals recorded from a large number of implanted electrodes and a larger number of spectral features. The recording and processing of these signals uses a lot of electrical power and thus hinders its use outside the research setting. To translate this research …
Experimental And Computational Studies Of Cortical Neural Network Properties Through Signal Processing, Wesley Patrick Clawson
Experimental And Computational Studies Of Cortical Neural Network Properties Through Signal Processing, Wesley Patrick Clawson
Graduate Theses and Dissertations
Previous studies, both theoretical and experimental, of network level dynamics in the cerebral cortex show evidence for a statistical phenomenon called criticality; a phenomenon originally studied in the context of phase transitions in physical systems and that is associated with favorable information processing in the context of the brain. The focus of this thesis is to expand upon past results with new experimentation and modeling to show a relationship between criticality and the ability to detect and discriminate sensory input. A line of theoretical work predicts maximal sensory discrimination as a functional benefit of criticality, which can then be characterized …
The Connectivity Domain: Analyzing Resting State Fmri Data Using Feature-Based Data-Driven And Model-Based Methods, Armin Iraji, Vince D. Calhoun, Natalie M. Wiseman, Esmaeil Davoodi-Bojd, Mohammad R. N. Avanaki, Zhifeng Kou
The Connectivity Domain: Analyzing Resting State Fmri Data Using Feature-Based Data-Driven And Model-Based Methods, Armin Iraji, Vince D. Calhoun, Natalie M. Wiseman, Esmaeil Davoodi-Bojd, Mohammad R. N. Avanaki, Zhifeng Kou
Biomedical Engineering Faculty Research Publications
Spontaneous fluctuations of resting state functional MRI (rsfMRI) have been widely used to understand the macro-connectome of the human brain. However, these fluctuations are not synchronized among subjects, which leads to limitations and makes utilization of first-level model-based methods challenging. Considering this limitation of rsfMRI data in the time domain, we propose to transfer the spatiotemporal information of the rsfMRI data to another domain, the connectivity domain, in which each value represents the same effect across subjects. Using a set of seed networks and a connectivity index to calculate the functional connectivity for each seed network, we transform data into …
The Viability Of High-Frequency Oscillation Analysis In Eeg Signals For Seizure Prediction, Bryan David Kern
The Viability Of High-Frequency Oscillation Analysis In Eeg Signals For Seizure Prediction, Bryan David Kern
Open Access Theses & Dissertations
Seizure prediction is a decades-old research problem that has yet to reach any satisfying conclusions. Many studies have tackled the problem with varying results, but there has yet to be any major breakthroughs that define the direction of all future research. However, a promising, new predictor may have presented itself in recent years in the form of high frequency oscillations (HFOs). With the discovery of HFOs (80 - 800 Hz) as a biomarker for epilepsy, new interest has been placed in studying the high frequency content of EEGs to find a possible link between epilepsy and HFOs. In this paper, …