Link to the University of Pittsburgh Homepage
Link to the University Library System Homepage Link to the Contact Us Form

Modulation of in Vivo Neural Network Activity with Electrochemically Controlled Delivery of Neuroactive Molecules

Du, Zhanhong (2016) Modulation of in Vivo Neural Network Activity with Electrochemically Controlled Delivery of Neuroactive Molecules. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

[img]
Preview
PDF
Primary Text

Download (9MB)

Abstract

Neural interface technologies with implantable microelectrode arrays hold great promise for treating neural injuries or disorders. On neural electrode surfaces, conducting polymers can be electropolymerization with negatively charged molecules incorporated. When the polymer is reduced with negative current, dopant molecules are released from the polymer. This feature can be utilized to deliver neural transmitters and modulators from the electrodes to alter neural network activity. Previously, release of CNQX (6-cyano-7-nitroquinoxaline-2,3-dione), an AMPA (2-amino-3-(5-methyl-3-oxo-1,2- oxazol-4-yl)propanoic acid) receptor antagonist in hippocampal neuron culture effectively suppressed local neural activity in a transient manner. In this study, we further advance this technology by characterizing the drug loading and release capacity from microelectrodes, expanding the range of candidate dopants, and demonstrating in vivo effectiveness in rat somatosensory (S1) barrel cortex.
Firstly, to quantify the concentration of released drug, fluorescent model molecule was used and quantitatively assessed in a real time imaging system. Stimulation amplitude was varied to determine the amount of released drug from microelectrodes. Secondly, only negatively charged drugs have been effectively released in the past. In this study, zwitterionic transmitter γ-Aminobutyric acid (GABA) was successfully delivered with the technique, greatly expanding the applicable range for the technique. Finally, we used evoked response from barrel cortex to evaluate the release of DNQX (6,7-dinitroquinoxaline-2,3-dione), an analog of CNQX. The neural activity of barrel cortex reliably represents sensory stimuli from whiskers, hence provides an excellent in vivo network model for evaluating our neurochemical release system. Neural activity from multi-whisker stimulation was immediately and locally suppressed by released DNQX for one to six seconds, demonstrating the high spatial-temporal resolution of the technique. Furthermore, weaker activities were nearly abolished by released DNQX whilst stronger activities were less influenced, because the strong over-saturated neural input can only be partially antagonized. The system demonstrates successful modulation of neural network activity in a highly controllable manner. With the ease of being incorporated in existing neural implants without increasing the volume or complexity, this technology may find use in a wide range of neuroscience studies and potentially therapeutic devices.


Share

Citation/Export:
Social Networking:
Share |

Details

Item Type: University of Pittsburgh ETD
Status: Unpublished
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Du, Zhanhongzjeffd@gmail.com0000-0001-6535-1424
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairCui, Xinyan Tracyxic11@pitt.eduXIC11
Committee MemberSimons, Daniel Jcortex@pitt.eduCORTEX
Committee MemberBatista, Aaron Papb10@pitt.eduAPB10
Committee MemberBi, Guo-Qianggqbiustc@gmail.com
Committee MemberWeber, Douglas Jdjw50@pitt.eduDJW50
Date: 25 January 2016
Date Type: Publication
Defense Date: 22 October 2015
Approval Date: 25 January 2016
Submission Date: 2 December 2015
Access Restriction: 1 year -- Restrict access to University of Pittsburgh for a period of 1 year.
Number of Pages: 165
Institution: University of Pittsburgh
Schools and Programs: Swanson School of Engineering > Bioengineering
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: Electrochemistry, Neural modulation, Controlled Drug Release, Conducting Polymer, Carbon Nanomaterials, Neural Network.
Date Deposited: 25 Jan 2016 17:46
Last Modified: 25 Jan 2017 06:15
URI: http://d-scholarship.pitt.edu/id/eprint/26373

Metrics

Monthly Views for the past 3 years

Plum Analytics


Actions (login required)

View Item View Item