Projects2017

Deep brain stimulation (DBS) is an effective treatment for medically intractable motor symptoms of Parkinson’s disease (PD) such as tremor, slowness of movement, and rigidity. This therapy, analogous to a cardiac pacemaker for the brain, involves placing a stimulating lead into the deep brain structures (i.e. subthalamic nucleus, thalamus, globus pallidus) to modulate abnormal electrical circuit activity and improve motor function. Our lab focuses on elucidating the pathophysiology of Parkinson’s disease and the mechanism of action of DBS to treat the symptoms in both human and NHP studies. Further, there is growing interest and need to address sleep disorders in PD that are sometimes overlooked in patients receiving DBS due to the success of this therapy treating the motor symptoms. Almost every patient with PD has some form of burdensome sleep disorder that degrades her or his quality of life. Current standard of care includes pharmacological treatments that often are accompanied by unwanted side effects and have inconsistent efficacy from patient to patient. We are conducting a new study to investigate sleep oscillations in patients with DBS for PD to help better understand the role the therapy to treat such non-motor symptoms. The project will involve recording and analyzing brain local field potentials and patient behavior in a clinical setting.

http://udall.umn.edu

http://www.neurology.umn.edu/profile_vitek.html

We are studying the basis of high level learning, using ultra high field functional magnetic resonance imaging (fMRI) to study how shape processing areas of the cerebral cortex change when subjects develop perceptual expertise. The interested student will gain experience with the collection of high resolution fMRI data, learn to use of standard toolkits and custom MATLAB code to analyze imaging data, and have the opportunity to work with vision scientists and MRI physicists at the world renowned University of Minnesota Center for Magnetic Resonance Imaging.

http://www.ghoselab.cmrr.umn.edu

This project focuses on the development and validation of a novel algorithm to compress neural data. The student will involve in algorithm and hardware development and testing.
Wireless neural interfaces: in wireless neural interfaces, there is insufficient bandwidth and power to transmit raw data. One solution is to integrate data compression into recorders thus reducing the wireless data rate. However, conventional compression techniques are computationally demanding, requiring too much silicon area for implementation.
Compressive sensing: compressive sensing (CS) is an emerging strategy for non-adaptive, sub-Nyquist sampling of sparse signals. CS has been used to design sub-Nyquist analog front-end and digital source encoders in neural recording systems. The current CS encoders rely on random measurement matrices, which require a parallel processing architecture that is not suitable for hardware implementation.
Our work: in our recent research, we have developed a novel CS encoder by incorporating deterministic measurement matrix, namely Quasi-Cyclic Array Code (QCAC) based matrix. The QCAC-based matrix exhibits highly structured data pattern, which yields to both area- and energy- efficient CS encoder architecture.
This project: in this project, we will implement the QCAC-CS encoder in an advanced CMOS technology for neural data compression.

http://yanglabumn.com/index.html

This project will utilize a virtual reality headset and EEG recording to create an immersive virtual training environment for brain-computer interface applications. The goal of this project is to increase user’s ability to control virtual objects by presenting them with realistic visual stimuli. In this project a student will assist with data analysis, experiment design, and the development of a virtual training environment.

http://helab.umn.edu/index.html

Pluripotent stem cells can be created from tissue samples taken from a patient. These stem cells can then be converted into neural tissue through application of appropriate cellular signals. When this neural tissue is grown in a flask, it makes little chunks of neural tissue that may have similar properties as the patient's own brain tissue. In this project, you will be taking these neural organoids and trying different neural recording methods to identify if they produce activity similar to that seen in the brain. If these orgnoids do produce neural acitivity, you will then try to identify differences in the neural activity can be observed in organoids generated from control patients from patients with epilepsy.

http://neuralnetoff.umn.edu

The Pacinian corpuscle (PC) is a mechanoreceptor found within the dermis of skin that responds to high frequency (20-1000 Hz) vibrations. When the surface of skin is vibrated, this vibration is transmitted through the skin to the PC where it deforms the PC tissue and stretches the nerve fiber at the PC’s center, initiating action potentials. PCs are found within clusters in the skin, where multiple PCs branch off of a single nerve and are grouped together. These PCs may have different sizes and shapes and be oriented differently with respect to the skin surface. We have developed a finite-element model of PCs embedded with skin and are looking for a summer student to expand this model to study the PCs within a cluster can respond differently to the same vibration and how this affects the neural output from the cluster. The cluster model can be combined with our neural model of a PC to draw insight into how PC clustering can enhance sensation.

https://sites.google.com/a/umn.edu/barocas/home

The Pacinian corpuscle (PC) is a mechanoreceptor that responds to high frequency (20-1000 Hz) vibrations. In response to vibration, the tissue portion of the PC deforms, causing the nerve at its center to stretch and initiate action potentials. Though the PC is very important to the field of haptics, there are many open questions about how it discriminates different vibrotactile signals. Our lab has set up a testing apparatus for psychophysical experiments to test the discriminability of different waveforms on the surface of skin. We are looking for a summer student to conduct experiments on how subjects perceive different complex waveforms. We also have a neural model of the PC which the student can use to model the psychophysical experiments and draw insight into why waveforms may be perceived differently.
 

https://sites.google.com/a/umn.edu/barocas/home

Development of various devices for behavioral data collection for Parkinson's Disease research. The devices can be both mechanical and electrical. There are several devices that our lab needs developed.

http://neuromod.umn.edu