The complexity and scale of inter-neuron communication in the human brain presents an immense obstacle to understanding the mechanisms of information processing and how changes to neuronal connectivity are associated with pathological states. Neuron interactions underlie functional roles of local brain networks, for instance memory and cognitive abilities, which are often detrimentally impacted in cognitive states. Therefore, elucidating connectivity in the brain, between numerous subtypes of cell and in different functional regions, can provide a physiological model of appropriate neuronal behaviour. This could potentially be used to identify neuronal behaviours indicative of pathological states such as Alzheimerâs disease.Advancements in imaging technologies, such as calcium imaging and fMRI, have greatly enhanced studies of neuronal networks. However, the temporal and spatial resolution of these methods are limited in precisely determining activity observed across hundreds of neurons simultaneously. Similarly, patch clamping techniques have provided a wealth of knowledge in terms of ion channels and single-cell responses, yet are not currently operable across hundreds of neurons simultaneously.Presented here is a novel microelectrode array (MEA) with high spatial resolution (60 Î¼m electrode pitch) combined with a data acquisition setup capable of sampling electrical signals at a frequency of 20 kHz, enabling precise recording of neuronal activity in acute rat brain slices. Electrode tips were exposed at the tips of silicon needles designed to bypass cellular damage resulting from tissue preparation to record from viable neurons. The device demonstrated a signal-to-noise ratio of 10:1 in the presence of tissue and platinised electrode impedances of 200 kÎ©, which are appropriate electrical characteristics with which to perform extracellular electrophysiological recordings.The device was integrated into a custom data acquisition system and, through a robust spike sorting process, successfully identified individual neurons. Neuronal signals were then assessed for temporal and amplitude features to discriminate subtypes of neurons to indicate functional roles within the network. This data was then used to develop several approaches to connectivity analysis afforded by the resolution of the device. Finally, the effectiveness of the needles in bypassing damaged tissue was evaluated histologically. These findings suggested that the preparation used here resulted in extensive cellular damage at the section surface. However, these results indicate potential for this approach to study of neuronal connectivity across hundreds of viable neurons.
|Date of Award||20 May 2020|
- University Of Strathclyde
|Sponsors||EPSRC (Engineering and Physical Sciences Research Council)|
|Supervisor||Keith Mathieson (Supervisor) & Michael Strain (Supervisor)|