Biology subjects

Sandvig, I.

Publications and source records attributed to Sandvig, I..

At least 19 recordsLinked to original sources

bioRxiv2026

Ion modulation restores local synaptic function in APOE4 neuronal networks despite persistent impairments in global network organization

The apolipoprotein E epsilon 4 (APOE4) allele is the strongest genetic risk factor for developing sporadic Alzheimer's disease (AD), which accounts for the vast majority of AD cases. Ion dysfunction has emerged as a central mechanism involved in APOE4-related pathology, reflecting the importance of ion homeostasis for cell membrane excitability, synaptic transmission, and plasticity. We have previously demonstrated that ion dysfunction contributes to early AD-related network vulnerability, and that engaging synaptic plasticity mechanisms via ion modulation can restore network balance in neurodegenerative disease. Here, we investigated whether synaptic mobilization by ion modulation could ameliorate APOE4-associated dysfunction in human neuronal networks compared with isogenic APOE3 controls. APOE4 networks exhibited progressive structural and functional deterioration, manifesting as increased neurite length, reduced neurite branching, and reduced firing rate and number of active recording electrodes. This was accompanied by compensatory hypersynchronization, rendering networks vulnerable to pathological spread, and reduced synaptic AMPAR levels compared with isogenic APOE3 control networks. Modulating ion homeostasis restored the local firing dynamics and stabilized synaptic AMPAR levels. However, the elevated synchronization and aberrant morphology of APOE4 networks were not alleviated by engaging synaptic plasticity mechanisms, demonstrating that APOE4 networks retain a capacity for adaptive plasticity enabling restoration of local neuronal function, but that this recovery does not extend to higher-order network organization.

neuroscience↗

bioRxiv2026

Structural and Synaptic Dysregulation Drives Network Vulnerability in APOE4 Human Neuronal Networks

Synaptic failure and associated neuronal network dysfunction are key pathological processes involved in the early stages of Alzheimers disease (AD). A better understanding of the specific synaptic pathways and network topologies that drive disease vulnerability is therefore essential for the development of a targeted therapeutic intervention. In the present study, we aimed to determine how defined synaptic pathways and connectivity patterns shape the emergence and progression of the structural and functional network dynamics of human neuronal networks with inherent vulnerability to AD. We performed longitudinal microelectrode array recordings, assessed excitatory and inhibitory activity, quantified neurite growth, and performed proteomic analyses of synaptosomes from human induced pluripotent stem cell-derived neuronal networks carrying homozygous apolipoprotein E epsilon 4 (APOE4), the strongest genetic risk factor for developing late-onset AD. This integrated approach enabled multiscale characterization of synaptic alterations, structural maturation, and functional network dynamics associated with AD vulnerability. Compared to isogenic homozygous APOE3 networks, we found that APOE4 drives a distinct topological regime, characterized by high assortativity combined with low transitivity, which reflects a compensatory organization with reduced redundancy and flexibility, consistent with an intrinsically fragile network structure. APOE4 networks exhibited reduced firing rates, dynamic excitatory and inhibitory imbalance, impaired synchronization, absence of network bursting, and reduced global routing efficiency. Despite retaining small-world properties indicative of baseline information processing capacity, the topological and functional profile of APOE4 networks suggests a reliance on compensatory mechanisms associated with elevated metabolic cost and increased susceptibility to pathological spread. Structurally, APOE4 networks displayed reduced dendritic length, branching, and total dendrite area, accompanied by dysregulation of synaptic organization and signaling, ion dynamics, and intracellular signaling pathways. Together, these findings establish that APOE4 drives a multiscale reorganization of neuronal networks that not only mirrors synaptic alterations identified in patients, but also contextualizes these changes within network-level dynamics, advancing a more comprehensive understanding of early AD pathology.

neuroscience↗

bioRxiv2025

Microscale dysfunction and mesoscale compensation in degenerating neuronal networks

Progressive neurodegenerative diseases involve neuronal dysfunction from cellular to circuit to whole-brain levels, but complexity and variability, both between and within diseases, pose significant research challenges. However, although they are differentiated by anatomical origins, vulnerable neuronal subtypes, and specific misfolded proteins, neurodegenerative diseases also share many important features. During presymptomatic disease phases, neural networks initiate multiple compensatory processes to maintain network function, including increased network centralisation and reliance on a rich-club of hub nodes, which have been proposed as common reconfigurations to neural network damage. Currently, while supporting evidence for such mechanisms has been found in some neurodegenerative diseases, it is limited in others, like ALS. This knowledge gap makes it challenging to ascertain if there are indeed common pre-symptomatic mechanisms within and across different neurodegenerative diseases. To address this, we investigated the structural and functional properties of ALS patient derived motor neuron networks and counterpart networks from a healthy donor using longitudinal multielectrode array recordings and graph theory-based network analysis. We demonstrate microscale-level motor neuron dysfunction, including TDP-43 proteinopathy, hyperactivity and reduced spike amplitude. Structurally, we observed neurite hypertrophy, indicating that degenerating networks attempt to establish new connections. We furthermore document mesoscale-level functional reconfigurations, including increased rich-club connectivity and network assortativity, indicating functional compensation in ALS where networks become more centralised to maintain computational capacity. We thus provide novel evidence that ALS networks become increasingly centralised, which places progressively mounting demands on a rich-club, predisposing networks to further damage, consistent with existing models of common reconfigurations in neurodegenerative disease. Significance statementThis study makes significant contributions to preclinical modelling of neurodegenerative disease, with specific relevance for ALS research. By utilising human cellular models, longitudinal extracellular electrophysiology, and advanced network analysis, we show that known features of ALS can be recapitulated in in vitro engineered neural networks, and that these networks allow for novel hypothesis testing and identification of pre-symptomatic pathological processes including increased centralisation. This has previously been observed in other neurodegenerative diseases, but evidence has been limited in ALS. Our results advance our understanding of motor neuron network dynamics in ALS and contribute to a shared understanding of how neurodegenerative diseases affect neural networks which go beyond specific disease diagnosis, elucidating fundamental processes in neural network function and disease response.

neuroscience↗

bioRxiv2025

Induced long-term potentiation improves synaptic stability and restores network function in ALS motor neurons

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease causing progressive dysfunction and degeneration of upper and lower motor neurons. An increasing body of evidence has identified synaptic alterations in patients and experimental models of ALS. Importantly, these have been associated with functional impairments in motor neuron networks, suggesting that synaptic impairments are early events in the disease cascade resulting in functional compensatory reconfigurations. The synapse may therefore represent a disease-modifying target to delay disease progression. In this study, we aimed to stabilize synapses and modify structural connectivity to restore network balance in ALS patient-derived motor neuron networks. To this end, we blocked the potassium channels using tetraethylammonium (TEA) which has been shown to induce chemical long-term potentiation (cLTP). The unperturbed ALS patient-derived motor neuron networks developed clear signs of subtle network dysfunction, including increased firing rate and bursting, and accompanying structural abnormalities. These features were partially restored by temporarily blocking the potassium channels. Specifically, the TEA-treated ALS networks were characterized by a reduction in aberrant branching and stabilization of dendritic spines, alongside a temporary reduction in firing rate and bursting. Furthermore, protein expression assays revealed restoration of dysregulated molecular pathways, including protein synthesis and metabolic pathways, and upregulation of pathways involved in synapse organization in the TEA-treated ALS networks. Collectively, these findings improve our understanding of the association between synaptic impairments and functional alterations in ALS, and demonstrate the relevance of modulating synaptic plasticity to promote network balance.

neuroscience↗

bioRxiv2025

Influence of neural network bursts on functional connectivity

Network bursts or synchronized burst events are a typical activity seen in most in vitro neural networks. Network bursts arise early in development and as networks mature, activity becomes dominated by bursts propagating across the entirety of the network. The reason for this developmental plateau in vitro is unknown, but to bypass it would confer a significant advantage in the use of in vitro networks for computation. As most neurons in a network participate in network bursts, burst onset supersedes any ongoing activity thereby placing a limit on short term computations equal to the recovery period between bursts. By assessing 521 multielectrode array recordings from day 4-39 in vitro we find that network bursts influence the connectivity, but this change is only weakly associated with the origin of the network bursts. The impacts of bursts on functional integration and segregation in neural networks are discussed along with approaches to mitigate the development and propagation of network bursts in vitro. Additionally, we hypothesize that burst initiation zones or pacemakers are viable targets for stimulation for computation in the context of control and reservoir.

neuroscience↗

bioRxiv2024

Reduced spatial spread of nodes in geometric network models improves topology associated with increased computational capabilities

Biological neural networks are characterized by short average path lengths, high clustering, and modular and hierarchical architectures. These complex network topologies strike a balance between local specialization and global synchronization via long-range connections, resulting in highly efficient communication. Efficient network organization and information processing are directly affected after network perturbation, e.g., as a result of trauma or neurodegenerative disease. Here, we used a spatial network model combining changes to spatial constraints on neuron placement with different wiring probabilities to investigate the effects of wiring cost principles on network complexity for different spatial conformations. By combining different wiring probabilities with varying levels of spatial clustering, we aimed to understand how alterations to mechanisms such as the neurons ability to group together, leading to different levels of clustering, in combination with altered axon outgrowth and branching, change network topology. Through targeted pruning of the networks we further aimed to understand how these topologies changed due to perturbations, resulting in a breakdown of function. We found that both long-range and intermediate wiring probabilities only conform to small-world architectures for neurons in dense spatial clusters due to a decrease in wiring cost within clusters. Furthermore, both small-worldness and modularity were reduced in systems with long-range connections caused by a reduction in network clustering. The presence of long-range connections were found to improve global information transmission, especially in networks with strong spatial clustering. In addition, these connections were shown to have a protective effect on the networks during targeted pruning, maintaining global connectivity even with high levels of pruning. Combining spatial clustering with wiring cost principles allows for novel insights into mechanisms underlying adaptive or maladaptive network alterations, explaining how specific interactions may lead to observed changes in networks. Our findings corroborate previous work showing that both wiring probability and spatial distributions play a key role in neural network development and response to perturbations, and increase our understanding of how maladaptive responses may lead to increased strain on local circuitry while negatively impacting global communication. Author summaryBiological neural networks organize into networks capable of performing a variety of complex tasks in a cost-efficient manner. In networks where neurons are subject to neuropathological disease or perturbations, the mechanisms leading to these networks are disrupted, resulting in changes to the computational capabilities of the networks which can be challenging to elucidate. In this study, we combine spatial network models with different wiring costs used to establish connections between nodes of the network to gain an understanding of how changes to the wiring cost and spatial distribution of nodes in a network impacts the resulting topologies. We find that irrespective of wiring cost, sufficient spatial clustering is required for the emergence of network capabilities related to onset and maintenance of activity found in biological neural networks. Furthermore, we find that a balance between local connectivity and long-range connections improve outcomes when networks are subject to targeted perturbations of these connections. To summarize, spatial models prove an efficient method for understanding how changes related to wiring cost and targeted deletion of connections may change topologies of networks, allowing us to understand how specific changes to networks may arise and manifest in in vitro and in vivo cases.

neuroscience↗

bioRxiv2024

Nanoporous Platinum Microelectrode Arrays for Neuroscience Applications

Microelectrode arrays are invaluable tools for investigating the electrophysiological behaviour of neuronal networks with high spatiotemporal precision. In recent years, it has become increasingly common to functionalize such electrodes with highly porous platinum to increase their effective surface area, and hence their signal-to-noise ratio. Although such functionalization significantly improves the electrochemical performance of the electrodes, the impact of various electrode morphologies on biocompatibility and electrophysiological performance in cell cultures remains poorly understood. In this study, we introduce reproducible protocols for depositing highly porous platinum with varying morphologies on microelectrodes designed for neural cell cultures. We also evaluate the impact of morphology and electrode size on the signal-to-noise ratio in recordings from rat cortical neurons cultured on these electrodes. Our results indicate that electrodes with a uniform layer of highly nanoporous platinum offer the best trade-off between biocompatibility, electrochemical, and electrophysiological performance. While more microporous electrodes exhibited lower impedance, nanoporous electrodes detected higher extracellular signal amplitudes from neurons, suggesting reduced distance between perisomatic neuronal areas and the electrodes. Additionally, these nanoporous electrodes showed fewer thickness variations at their edges compared to the more porous electrodes. Such edges can be mechanically broken off during cell culturing and contribute to long-term cytotoxic effects, which is highly undesirable. We hope this work will contribute to better standardization in creating and utilizing nanoporous platinum microelectrodes for neuroscience applications. Improving the accessibility and reproducibility of this technology is crucial for enhancing the quality of electrophysiological data and advancing our understanding of neuronal network function and dysfunction.

neuroscience↗

bioRxiv2024

Engineered Cortical Microcircuits for Investigations of Neuroplasticity

Recent advances in neural engineering have opened new ways to investigate the impact of topology on neural network function. Leveraging microfluidic technologies, it is possible to establish modular circuit motifs that promote both segregation and integration of information processing in the engineered neural networks, similar to those observed in vivo. However, the impact of the underlying topologies on network dynamics and response to pathological perturbation remains largely unresolved. In this work, we demonstrate the utilization of microfluidic platforms with 12 interconnected nodes to structure modular, cortical engineered neural networks. By implementing geometrical constraints inspired by a Tesla valve within the connecting microtunnels, we additionally exert control over the direction of axonal outgrowth between the nodes. Interfacing these platforms with nanoporous microelectrode arrays reveals that the resulting laminar cortical networks exhibit pronounced segregated and integrated functional dynamics across layers, mirroring key elements of the feedforward, hierarchical information processing observed in the neocortex. The multi-nodal configuration also facilitates selective perturbation of individual nodes within the networks. To illustrate this, we induced hypoxia, a key factor in the pathogenesis of various neurological disorders, in well-connected nodes within the networks. Our findings demonstrate that such perturbations induce ablation of information flow across the hypoxic node, while enabling the study of plasticity and information processing adaptations in neighboring nodes and neural communication pathways. In summary, our presented model system recapitulates fundamental attributes of the microcircuit organization of neocortical neural networks, rendering it highly pertinent for preclinical neuroscience research. This model system holds promise for yielding new insights into the development, topological organization, and neuroplasticity mechanisms of the neocortex across the micro- and mesoscale level, in both healthy and pathological conditions.

neuroscience↗

bioRxiv2024

Functional Complexity of Engineered Neural Networks Self-Organized on Novel 3D Interfaces

Engineered neural networks are indispensable tools for studying neural function and dysfunction in controlled microenvironments. In vitro, neurons self-organize into complex assemblies with structural and functional similarities to in vivo circuits. Traditionally, these models are established on planar interfaces, but studies suggest that the lack of a three-dimensional growth space affects neuronal organization and function. While methods supporting 3D growth exist, reproducible 3D neuroengineering techniques compatible with electrophysiological recording methods are still needed. In this study, we developed a novel biocompatible interface made of the polymer SU-8 to support 3D network development. Using electron microscopy and immunocytochemistry, we show that neurons utilize these 3D scaffolds to self-assemble into complex, multi-layered networks. Furthermore, interfacing the scaffolds with custom microelectrode arrays enabled characterizing of electrophysiological activity. Both planar control networks and 3D networks displayed complex interactions with integrated and segregated functional dynamics. However, control networks showed stronger functional interconnections, higher entropy, and increased firing rates. In summary, our interfaces provide a versatile approach for supporting neural networks with a 3D growth environment, compatible with assorted electrophysiology and imaging techniques. This system can offer new insights into the impact of 3D topologies on neural network organization and function.

neuroscience↗

bioRxiv2024

Dysregulation of synaptic transcripts underlies network abnormalities in ALS patient-derived motor neurons

Amyotrophic lateral sclerosis (ALS) is characterized by dysfunction and loss of upper and lower motor neurons. Several studies have identified structural and functional alterations in the motor neurons before the manifestation of symptoms, yet the underlying cause of such alterations and how they contribute to the progressive degeneration of affected motor neuron networks remain unclear. Importantly, the short and long-term spatiotemporal dynamics of neuronal network activity make it challenging to discern how ALS-related network reconfigurations emerge and evolve. To address this, we systematically monitored the structural and functional dynamics of motor neuron networks with a confirmed endogenous C9orf72 mutation. We show that ALS patient-derived motor neurons display time-dependent neural network dysfunction, specifically reduced firing rate and spike amplitude, impaired bursting, but higher overall synchrony in network activity. These changes coincided with altered neurite outgrowth and branching within the networks. Moreover, transcriptional analyses revealed dysregulation of molecular pathways involved in synaptic development and maintenance, neurite outgrowth and cell adhesion, suggesting impaired synaptic stabilization. This study identifies early synaptic dysfunction as a contributing mechanism resulting in network-wide structural and functional compensation, which may over time render the networks vulnerable to neurodegeneration.

neuroscience↗

bioRxiv2024

In vitro survival and neurogenic potential of central canal-derived neural stem cells depend on spinal cord injury type

The central canal (CC) of the spinal cord is a neurogenic niche consisting of quiescent neural stem cells (NSCs) capable of responding to traumatic damage to the spinal cord by increasing their proliferative activity and sending migrating progeny toward the site of injury, where they contribute to the formation of the glial scar. However, CC NSCs have been demonstrated to have the capability to differentiate into all neural lineage cells in vitro, but also in vivo, in response to infusion of specific growth factors that promote neuronal induction after injury, as well as when transplanted into other neurogenic niches, such as the subgranular zone of the hippocampus. This suggests that CC NSCs may represent a recruitable endogenous source of neural lineage cells that could be harnessed to replenish damaged or lost neural tissue after traumatic spinal cord injury (SCI). NSCs isolated from the CC neurogenic niche of uninjured rats and mice have been shown to display limited proliferative capacity in vitro, with significantly greater proliferative activity achieved with NSCs isolated from SCI-lesioned rats and mice indicating an injury-specific activation of the quiescent CC NSC pool. A central question that currently remains unanswered is whether, and to what extent the CC niche can spontaneously generate viable neurons, and act as a potential source of new cells to replace lost neuronal populations in situ, and whether SCI sequalae impact future NSC neurogenic potential. To address this question, we need to understand whether the nature of the injury plays a role in the CC neurogenic niche response. In this study, we compared the intrinsic proliferative response and neurogenic potential of NSCs harvested from the CC neurogenic niche in adult female Sprague Dawley rats by culturing said NSCs across three conditions; (i) control, i.e., uninjured tissue, (ii) after in vivo compression injury 3 days before harvesting, and (iii) after in vivo simulated burst fracture injury 3 days before harvesting in vitro. We found that lacerations of the dura mater surrounding the spinal cord during a compression injury resulted in drastically altered and persistent in vitro NSC behavior encompassing both proliferation and development compared to uninjured control and compression injury with the dura intact.

neuroscience↗

bioRxiv2024

Neural stem cells isolated from activated brain neurogenic niches after traumatic injury demonstrate distinct behaviors in vitro

The subventricular zone (SVZ) of the lateral ventricle and subgranular zone (SGZ) of the dentate gyrus (DG) in the hippocampus represents neurogenic niches within the brain housing distinct populations of neural stem cells (NSCs), known for their exclusive capacity to sustain neurogenesis in the adult mammalian CNS. These niches respond to traumatic brain injury (TBI) by becoming activated, leading to NSC proliferation, a small number of which subsequently migrate towards the injury site, and differentiate predominantly into astrocytes. Although the capacity of activated NSCs to differentiate into neurons appears to be limited, it is intrinsically interesting to determine whether these cells may represent a potential source of new neurons that may replenish and replace damaged and lost neuronal tissue. To address this question, it is necessary to understand the intrinsic behavior of NSCs derived from the activated SVZ and SGZ neurogenic niches after TBI, in terms of cell maturation, and differentiation capacity. In this study, we induced a focal TBI lesion specifically targeting the SVZ or SGZ neurogenic niche in adult rats, harvested NSCs three days post-lesioning, and subsequently expanded them in culture. We found that the isolated NSCs displayed distinct proliferation, differentiation, and spontaneous organization in vitro, dependent on the activated niche of origin. Furthermore, these behaviors differed from NSCs derived from the SVZ or SGZ niche of uninjured control animals.

neuroscience↗

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

Inhibition of excitatory synaptic transmission alters functional organization and efficiency in cortical neural networks

Fundamental neural mechanisms such as activity dependent Hebbian and homeostatic neuroplasticity are driven by balanced excitatory - inhibitory synaptic transmission, and work in tandem to coordinate and regulate complex neural network dynamics in both healthy and perturbed conditions. These neuroplasticity processes shape neural network activity, as well as structural and functional aspects of network organization, information transmission and processing. While crucial for all aspects of network function, understanding how the brain utilizes plasticity mechanisms to retain or regain function during and after perturbation is often challenging. This is because these processes occur at varying spatiotemporal scales simultaneously across diverse circuits and brain regions and are thus highly complicated to distinguish from other underlying mechanisms. However, neuroplasticity and self-organizing properties of the brain are largely conserved in in vitro biological neural networks, and as such, these networks enable us to investigate both structural and functional plasticity responses to perturbation networks at the micro and mesoscale level. In this study, we selectively silenced excitatory synaptic transmission in in vitro neural networks to investigate the impact of the perturbation on structural and functional network organization and resilience. Our results demonstrate that selective inhibition of excitatory transmission leads to transient de-clustering of modular structure, increased path length and degree in perturbed networks. These changes indicate a transient loss of network efficiency; with the network subsequently reorganizing to a state of increased clustering and short path lengths following recovery. These findings highlight the remarkable capacity of neural networks to reconfigure their functional organization following perturbation. The ability to detect and decode such processes as they evolve highlights the robustness of our models to investigate certain dynamic network properties that are often not accessible by in vivo methods.

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

Microdissection and culturing of adult lateral entorhinal cortex layer II neurons from APP/PS1 Alzheimer model mice

BackgroundPrimary neuronal cultures enable cell-biological studies of Alzheimers disease (AD), albeit typically non-neuron-specific. The first cortical neurons affected in AD reside in layer II of the lateralmost part of the entorhinal cortex, and they undergo early accumulation of intracellular amyloid-{beta}, form subsequent tau pathology, and start degenerating pre-symptomatically. These vulnerable entorhinal neurons uniquely express the glycoprotein reelin and provide selective inputs to the hippocampal memory system. Gaining a more direct access to study these neurons is therefore highly relevant. New methodWe demonstrate a methodological approach for microdissection and long-term culturing of adult lateral entorhinal layer II-neurons from AD-model mice. ResultsWe maintain adult microdissected lateralmost entorhinal layer II-neurons beyond two months in culture. We show that they express neuronal markers, and that they are electrophysiologically active by 15 days in vitro and continuing beyond 2 months. Comparison with existing methodsPrimary neurons are typically harvested from embryonic or early postnatal brains because such neurons are easier to culture compared to adult neurons. Methods to culture adult primary neurons have been reported, however, to our knowledge, culturing of adult entorhinal subregion-specific primary neurons from AD-model animals has not been reported. ConclusionsOur methodological approach offers a window to study initial pathological changes in the AD disease-cascade. This includes the study of proteinopathy, single-neuron changes, and network-level dysfunction. HighlightsO_LIWe microdissect and culture neurons from layer II of the lateralmost part of the entorhinal cortex from adult AD model mice and littermate controls C_LIO_LIThese entorhinal neurons self-organize into networks, express reelin, NeuN and intracellular amyloid-{beta}. C_LIO_LIThe neurons are electrophysiologically active by day 15 in culture and remain viable beyond two months. C_LI

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↗