Biology subjects

Winter-Hjelm, N.

Publications and source records attributed to Winter-Hjelm, N..

4 recordsLinked to original sources

bioRxiv2024

ALS patient-derived motor neuron networks exhibit microscale dysfunction and mesoscale compensation rendering them highly vulnerable to perturbation

Amyotrophic lateral sclerosis affects upper and lower motor neurons, causing progressive neuropathology leading to structural and functional alterations of affected neural networks long prior to development of symptoms. Certain genetic mutations, such as expansions in C9orf72, predispose motor neuron populations to pathological dysfunction. However, it is not known how underlying pathological predisposition affects structural and functional dynamics within vulnerable networks. Here, we studied micro-and mesoscale dynamics of ALS patient derived motor neuron networks over time. We show, for the first time, that ALS patient derived motor neurons with endogenous genetic predisposition develop classical ALS cytopathology in the form of cytoplasmic TDP-43 inclusions and self-organise into computationally efficient networks, albeit with functional hallmarks of higher metabolic cost compared to healthy controls. These hallmarks included microscale impairments and mesoscale compensation including increased centralisation of function. Moreover, we show that these networks are highly susceptible to transient perturbation by exhibiting induced hyperactivity.

neuroscience↗

bioRxiv2023

Altered structural organization and functional connectivity in feedforward neural networks after induced perturbation

Reciprocal structure-function relationships underlie both healthy and pathological behaviors in complex neural networks. Thus, understanding neuropathology and network dysfunction requires a thorough investigation of the complex interactions between structural and functional network reconfigurations in response to perturbation. Such adaptations are often difficult to study in vivo. For example, subtle, evolving changes in synaptic connectivity, transmission, and the electrophysiological shift from healthy to pathological states, as for example alterations that may be associated with evolving neurodegenerative disease, such as Alzheime[r]s, are difficult to study in the brain. Engineered in vitro neural networks are powerful models that enable selective targeting, manipulation, and monitoring of dynamic neural network behavior at the micro- and mesoscale in physiological and pathological conditions. In this study, we engineered feedforward cortical neural networks using two-nodal microfluidic devices with controllable connectivity interfaced with microelectrode arrays (mMEAs). We induced P301L mutated tau protein to the presynaptic node of these networks and monitored network dynamics over three weeks. Induced perturbation resulted in altered structural organization and extensive axonal retraction starting in the perturbed node. Perturbed networks also exhibited functional changes in intranodal activity, which manifested as an overall decline in both firing rate and bursting activity, with a progressive increase in synchrony over time, and decrease in internodal signal propagation between pre- and postsynaptic nodes. These results provide insights into dynamic structural and functional reconfigurations at the micro- and mesoscale as a result of evolving pathology and illustrate the utility of engineered networks as models of network function and dysfunction.

neuroscience↗

bioRxiv2023

Reverse Engineering of Feedforward Cortical-Hippocampal Neural Networks Relevant for Preclinical Disease Modelling

Engineered biological neural networks are indispensable models for investigation of neural function and dysfunction from the subcellular to the network level. Notably, advanced neuro-engineering approaches are of significant interest for their potential to replicate the topological and functional organization of brain networks. In this study, we reverse engineered feed-forward neural networks of primary cortical and hippocampal neurons, using a custom-designed multinodal microfluidic device with Tesla valve inspired microtunnels. By interfacing this device with nanoporous microelectrodes, we show that the reverse engineered multinodal neural networks exhibit capacity for both segregated and integrated functional activity, mimicking brain network dynamics. To advocate the broader applicability of our model system, we induced localized perturbations with amyloid beta to study the impact of pathology on network functionality. Additionally, we demonstrate long-term culturing of subregion- and layer specific neurons extracted from the entorhinal cortex and hippocampus of adult Alzheimer ss-model mice and rats. Our results thus highlight the potential of our approach for reverse engineering of anatomically relevant multinodal neural networks to study dynamic structure-function relationships in both healthy and pathological conditions.

neuroscience↗

bioRxiv2022

Structure-Function Dynamics of Engineered, Modular Neuronal Networks with Controllable Afferent-Efferent Connectivity

Microfluidic devices interfaced with microelectrode arrays have in recent years emerged as powerful platforms for studying and manipulating in vitro neuronal networks at the micro- and mesoscale. By segregating neuronal populations using microchannels only permissible to axons, neuronal networks can be designed to mimic the highly organized, modular topology of neuronal assemblies in the brain. However, little is known about how the underlying topological features of such engineered neuronal networks contribute to their functional profile. To start addressing this question, a key parameter is control of afferent or efferent connectivity within the network. In this study, we show that a microfluidic device featuring axon guiding channels with geometrical constraints inspired by a Tesla valve effectively promotes unidirectional axonal outgrowth between neuronal nodes, thereby enabling us to control afferent connectivity. Our results moreover indicate that these networks exhibit a more efficient network organization with higher modularity compared to single nodal controls. We verified this by applying designer viral tools to fluorescently label the neurons to visualize the structure of the networks, combined with extracellular electrophysiological recordings using embedded nanoporous microelectrodes to study the functional dynamics of these networks during maturation. We furthermore show that electrical stimulations of the networks induce signals selectively transmitted in a feedforward fashion between the neuronal populations. A key advantage with our microdevice is the ability to longitudinally study and manipulate both the structure and function of neuronal networks with high accuracy. This model system has the potential to provide novel insights into the development, topological organization, and neuroplasticity mechanisms of neuronal assemblies at the micro- and mesoscale in healthy and perturbed conditions.

neuroscience↗