Objective. Understanding how electrophysiological activity and functional connectivity emerge and can be modulated in human neuronal networks remains a central challenge in neuroscience. In this context, this PhD work aimed to investigate how these properties can be shaped in human induced pluripotent stem cell (hiPSC)-derived neuronal networks. Specifically, the study focused on identifying electrical stimulation parameters able to elicit reliable and reproducible responses, and on evaluating how functional connectivity and network organization are modulated by controlled perturbations, both electrical and pharmacological. In addition, the work aimed to determine whether increasing structural complexity through advanced in vitro models, including three-dimensional (3D) neuronal assemblies, enhances the ability of these systems to reproduce key features of brain-like activity. Approach. Human iPSC-derived neuronal cultures were generated by direct differentiation into excitatory and inhibitory neurons through the overexpression of the transcription factors Neurogenin-2 (Ngn2) and Achaete-scute homolog 1 (Ascl1), respectively. Two network configurations were established on Micro-Electrode Arrays (MEAs): a purely excitatory population and a mixed excitatory–inhibitory network. Electrical stimulation protocols were systematically applied to probe evoked responses and to identify effective stimulation parameters capable of generating stable and reproducible activity patterns. At the same time, pharmacological manipulations were used to modulate synaptic activity and to investigate changes in network connectivity. Spontaneous and evoked activity were analyzed at both the single-channel and network levels, combining spike detection with network burst analysis. Functional connectivity was reconstructed using cross-correlation analysis and characterized through graph-theoretical metrics. Finally, perturbational complexity was quantified through the Perturbational Complexity Index (PCI), derived from the spatiotemporal patterns of evoked responses, to assess the richness of activity across the network and, in particular, to evaluate the complexity of 3D neuronal cultures in comparison to 2D systems. Main results. The results demonstrate that both electrical and pharmacological perturbations significantly modulate the dynamics and organization of hiPSC-derived neuronal networks. Effective stimulation parameters were identified, enabling reliable evoked responses in human neuronal networks, providing a robust framework for investigating network activity. Electrical stimulation also induced a marked reshaping of spontaneous dynamics, with an increase in network burst frequency, a change in the shape of network activity and a significant decrease in inter-culture variability, indicating a convergence toward more homogeneous activity patterns. Functional connectivity analysis showed a reorganization toward a more distributed but weaker network architecture, with preserved local organization. Moreover, stimulation led to a reorganization of hub distribution, with a reduction in pre-existing hubs and the emergence of new hubs preferentially located near stimulation sites, suggesting a spatially localized effect on network organization. Pharmacological manipulations confirmed the key role of synaptic transmission in regulating network integration and segregation, and high lighted differences between network compositions, with mixed excitatory–inhibitory networks showing more integrated and efficient connectivity. Finally, the analysis of perturbational complexity revealed that 3D neuronal cultures exhibit higher PCI values compared to 2D networks, approaching those observed in in vivo conditions. This indicates an enhanced ability of 3D systems to sustain complex spatiotemporal dynamics and supports their relevance as advanced in vitro models of brain-like activity. Significance. Overall, this work provides a comprehensive framework to investigate neuronal dynamics and functional connectivity in human-derived systems. By integrating controlled perturbations, advanced analysis methods, and more complex three-dimensional models, the thesis contributes to the development of physiologically relevant neuroengineering platforms, offering new tools to study brain-like activity, plasticity, and network complexity in a human-specific context.
Neuromodulation of hiPSCs derived-neuronal networks
ZANINI, GIORGIA
2026-06-15
Abstract
Objective. Understanding how electrophysiological activity and functional connectivity emerge and can be modulated in human neuronal networks remains a central challenge in neuroscience. In this context, this PhD work aimed to investigate how these properties can be shaped in human induced pluripotent stem cell (hiPSC)-derived neuronal networks. Specifically, the study focused on identifying electrical stimulation parameters able to elicit reliable and reproducible responses, and on evaluating how functional connectivity and network organization are modulated by controlled perturbations, both electrical and pharmacological. In addition, the work aimed to determine whether increasing structural complexity through advanced in vitro models, including three-dimensional (3D) neuronal assemblies, enhances the ability of these systems to reproduce key features of brain-like activity. Approach. Human iPSC-derived neuronal cultures were generated by direct differentiation into excitatory and inhibitory neurons through the overexpression of the transcription factors Neurogenin-2 (Ngn2) and Achaete-scute homolog 1 (Ascl1), respectively. Two network configurations were established on Micro-Electrode Arrays (MEAs): a purely excitatory population and a mixed excitatory–inhibitory network. Electrical stimulation protocols were systematically applied to probe evoked responses and to identify effective stimulation parameters capable of generating stable and reproducible activity patterns. At the same time, pharmacological manipulations were used to modulate synaptic activity and to investigate changes in network connectivity. Spontaneous and evoked activity were analyzed at both the single-channel and network levels, combining spike detection with network burst analysis. Functional connectivity was reconstructed using cross-correlation analysis and characterized through graph-theoretical metrics. Finally, perturbational complexity was quantified through the Perturbational Complexity Index (PCI), derived from the spatiotemporal patterns of evoked responses, to assess the richness of activity across the network and, in particular, to evaluate the complexity of 3D neuronal cultures in comparison to 2D systems. Main results. The results demonstrate that both electrical and pharmacological perturbations significantly modulate the dynamics and organization of hiPSC-derived neuronal networks. Effective stimulation parameters were identified, enabling reliable evoked responses in human neuronal networks, providing a robust framework for investigating network activity. Electrical stimulation also induced a marked reshaping of spontaneous dynamics, with an increase in network burst frequency, a change in the shape of network activity and a significant decrease in inter-culture variability, indicating a convergence toward more homogeneous activity patterns. Functional connectivity analysis showed a reorganization toward a more distributed but weaker network architecture, with preserved local organization. Moreover, stimulation led to a reorganization of hub distribution, with a reduction in pre-existing hubs and the emergence of new hubs preferentially located near stimulation sites, suggesting a spatially localized effect on network organization. Pharmacological manipulations confirmed the key role of synaptic transmission in regulating network integration and segregation, and high lighted differences between network compositions, with mixed excitatory–inhibitory networks showing more integrated and efficient connectivity. Finally, the analysis of perturbational complexity revealed that 3D neuronal cultures exhibit higher PCI values compared to 2D networks, approaching those observed in in vivo conditions. This indicates an enhanced ability of 3D systems to sustain complex spatiotemporal dynamics and supports their relevance as advanced in vitro models of brain-like activity. Significance. Overall, this work provides a comprehensive framework to investigate neuronal dynamics and functional connectivity in human-derived systems. By integrating controlled perturbations, advanced analysis methods, and more complex three-dimensional models, the thesis contributes to the development of physiologically relevant neuroengineering platforms, offering new tools to study brain-like activity, plasticity, and network complexity in a human-specific context.
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