Quantifying activity in nascent neuronal networks derived from embryonic stem cells

Abstract

PhD ThesisThe relationship between spatiotemporal patterns of spontaneous activity and functional specialisation in developing neuronal networks is complex and its study is crucial to our understanding of how network communication is initiated. This project quantifies transitions between structural and functional states in embryonic stem cell cultures during differentiation. The work also focussed on the role of γ-aminobutyric acid (GABA), known to be vital for neuronal network development. The work used many techniques, including carbon nanotube (CNT) -patterned substrates to manipulate network architecture, multi-electrode arrays (MEAs) and calcium imaging to quantify function. An embryonic stem cell line (CC9) was used to generate ‘de novo’ neuronal networks and these were monitored over 13 – 22 days in vitro (DIV), while network structure forms and stabilizes. On CNT-patterned arrays, differentiating CC9s migrated and sub-clustered on CNT islands showing that network structure could be manipulated. No spontaneous electrophysiological (unit) activity was found in these cultures. However, intracellular calcium responses were readily induced and seen spontaneously at 13-20 DIV. Activity rate, kinetics and number of active cells increased between 16-18 DIV, correlating with changes in network clustering. Post 17 DIV, activity transformed from near-random to periodic and synchronous. Many events were initiated by ‘hubs’ and degrees of critical behaviour were observed, moving towards more efficient information processing states with development. Blockade of GABAA receptors lead to elevated spontaneous activity and supercritical behaviour, depending on developmental stage. Application of exogenous GABA induced large, slow calcium transients in a developmental stage-dependent manner, suggestive of a mixed excitatory/inhibitory role. These findings begin to show how activity develops as stem cells differentiate to form neuronal networks. GABA’s role in controlling patterns of activity was more complex that previously reported for neuronal networks in situ, but GABA clearly played a vital role in shaping population behaviour to optimise information processing properties in early, developing networks