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University of Cambridge

Graphene Brain on a Chip Platform for the Study of Neurodegeneration

Abstract

dc:description.abstract

A complex network of interconnected neurons forms the brain. This network is disrupted in neurodegenerative diseases---such as Parkinson's disease (PD), and there are limited tools available to study the molecular mechanisms behind the degradation of the neuronal network. This indicates a gap in the understanding of how neurodegenerative diseases and PD initiate and propagate. Therefore, graphene microelectrode arrays (MEAs) were explored to bridge this gap. However, there are currently no protocols or methods available to fabricate reliably and apply the graphene MEAs for the study of neurodegeneration. This work demonstrates a new reproducible protocol for the fabrication of graphene MEAs, a new method for using the graphene MEAs---including analysing the simultaneous calcium imaging, electrophysiology, and super-resolution imaging data obtained, and a physiologically relevant application for the graphene MEAs in neurodegeneration research. The fabricated devices demonstrated a higher spatiotemporal resolution and lower impedance than commercially available MEAs, due to the properties of the graphene---such as the high transparency---as well as the fabrication techniques. Due to the higher spatiotemporal resolution provided by the graphene, the imaging of spontaneous neuronal activity, electrophysiology, and correlative imaging and electrophysiology recordings of neurons on a network level and a single-cell level could be obtained. In addition, the transparency allowed for the sub-cellular investigations of the degenerating neurons using super-resolution microscopy. A machine-learning model was used to classify the neuronal spikes and analyse the imaging and electrophysiology data. Using U18666A to induce Niemann-Pick disease type C, the graphene MEAs and methodology for simultaneous imaging and electrophysiology were validated. It was found that U18666A had a significant degenerative impact on the synchronicity, activity, connectivity, and morphology of the neurons---which was verified by electrophysiology, microscopy, correlative imaging and electrophysiology, and super-resolution microscopy. In addition, further investigations into PD were carried out and preliminary degenerative effects of cholesterol and alpha-synuclein combined were observed using the graphene MEAs. A reliable, reproducible, and valuable tool for the study of neurodegeneration has been developed. This protocol and methodology immediately allows researchers to investigate neurodegenerative diseases in depth, which expands and adds to the scientific knowledge pool for PD. A deeper understanding of neuronal pathology opens the doors for developing therapeutic interventions for other neurodegenerative diseases as well. Therefore, this work unleashes a new tool for the neuroscience and drug development communities.

Degree

thesis:*
Name dc:type.qualificationname
Doctor of Philosophy (PhD)
Level dc:type.qualificationlevel
Doctoral
Grantor dc:publisher.institution
University of Cambridge
Year dc:date.issued
2024

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Hui, Ernestine
Advisor dc:contributor.advisor
  • Kaminski Schierle, Gabriele

Subjects

dc:subject × 28

Rights

dc:rights
Language dc:language
eng

Identifiers

dc:identifier.*
DOI dc:identifier.doi
https://doi.org/10.17863/CAM.106823
OAI identifier oai:identifier
oai:www.repository.cam.ac.uk:1810/365583

Chain of custody

source
Harvested from
Cambridge University
Base URL
api.repository.cam.ac.uk/server/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Hui, Ernestine. Graphene Brain on a Chip Platform for the Study of Neurodegeneration. Doctoral thesis, University of Cambridge, 2024. https://doi.org/10.17863/CAM.106823