The New Jersey Institute of Technology's
Electronic Theses & Dissertations Project

Title:	The effects of design parameters on the neural recordings with micro-ECoG arrays
Author:	Sethia, Manan Amish
View Online:	njit-etd2021-027 (xiii, 33 pages ~ 1.5 MB pdf)
Department:	Department of Biomedical Engineering
Degree:	Master of Science
Program:	Biomedical Engineering
Document Type:	Thesis
Advisory Committee:	Sahin, Mesut (Committee chair) Zhou, Xianlian Alex (Committee member) Ihlefeld, Antje (Committee member)
Date:	2021-05
Keywords:	Micro-ECoG Rat brain model Finite element analysis Neural recording Array electrodes Neural simulation
Availability:	Unrestricted
Abstract:	In the field of neural prosthetics, electro-cortico-graph (ECoG) arrays are commonly used to record neural activity of the brain cortex both in animal and human subjects. A finite element model (FEM) was developed to simulate the electric field generated by a single neuron in the rat brain cortex and a micro ECoG array (µECoG) placed on the pia surface for recording the neural signal. The neuron was simulated as a dipole current source with a magnitude of 1µA and placed at three different depths in the motor cortex corresponding to different layers under the µECoG array. The array design was a grid of 8x8 circular contacts with a contact pitch of 500 µm and via holes between the recording contacts. The main hypothesis was that the presence of these holes should have significant impact on the amplitude and selectivity of the neural signals depending on the depth of the source in the cortex. The sizes of via holes were set to 20, 50, and 200 µm to study their effect on the recorded potentials. These results show that the recorded signal amplitudes drop at the location of the via holes and the overall amplitudes also decreases at the contact sites as compared to the design without the holes. The larger the hole size, the larger the effect on the signal amplitude. Furthermore, the simulation results supported the hypothesis that greater potential differences were created due to the presence of holes in µECoG arrays and improved the selectivity of neural recordings.