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Antiseizure drugs (ASDs) modulate synaptic and ion channel function to prevent abnormal hypersynchronous or excitatory activity arising in neuronal networks, but the relationship between ASDs with respect to their impact on network activity is poorly defined. In this study, we first investigated whether different ASD classes exert differential impact upon network activity, and we then sought to classify ASDs according to their impact on network activity.We used multielectrode arrays (MEAs) to record the network activity of cultured cortical neurons after applying ASDs from two classes: sodium channel blockers (SCBs) and γ-aminobutyric acid type A receptor-positive allosteric modulators (GABA PAMs). A two-dimensional representation of changes in network features was then derived, and the ability of this low-dimensional representation to classify ASDs with different molecular targets was assessed.A two-dimensional representation of network features revealed a separation between the SCB and GABA PAM drug classes, and could classify several test compounds known to act through these molecular targets. Interestingly, several ASDs with novel targets, such as cannabidiol and retigabine, had closer similarity to the SCB class with respect to their impact upon network activity.These results demonstrate that the molecular target of two common classes of ASDs is reflected through characteristic changes in network activity of cultured neurons. Furthermore, a low-dimensional representation of network features can be used to infer an ASDs molecular target. This approach may allow for drug screening to be performed based on features extracted from MEA recordings.

BACKGROUND AND PURPOSE: Hyperpolarization-activated Cyclic Nucleotide-gated (HCN) channels are encoded by four genes (HCN1-4) with distinct biophysical properties and functions within the brain. HCN4 channels activate slowly at robust hyperpolarizing potentials, making them more likely to be engaged during hyperexcitable neuronal network activity seen during seizures. HCN4 channels are also highly expressed in thalamic nuclei, a brain region implicated in seizure generalisation. Here we assessed the utility of targeting the HCN4 channel as an anti-seizure strategy using pharmacological and genetic approaches. EXPERIMENTAL APPROACH: The impact of reducing HCN4 channel function on seizure susceptibility and neuronal network excitability was studied using a HCN4 channel preferring blocker (EC18) and a conditional brain specific HCN4 knockout mouse model. KEY RESULTS: EC18 (10mg kg-1 ) and brain-specific HCN4 channel knockout reduced seizure susceptibility and proconvulsant-mediated cortical spiking recorded using electrocorticography, with minimal effects on other mouse behaviours. EC18 (10μM) decreased neuronal network bursting in mouse cortical cultures. Importantly, EC18 was not protective against proconvulsant-mediated seizures in the conditional HCN4 channel knockout mouse and did not reduce bursting behaviour in AAV-HCN4 shRNA infected mouse cortical cultures. CONCLUSIONS AND IMPLICATIONS: These data suggest the HCN4 channel as a potential pharmacologically relevant target for anti-seizure drugs that is likely to have a low side-effect liability in the central nervous system.

Objective: In Victoria, Prevention and Recovery Care Services have been established to provide a partial alternative to inpatient admissions through short-term residential mental health care in the community. This study set out to determine whether Prevention and Recovery Care Services are achieving their objectives in relation to reducing service use and costs, fostering least restrictive care and leading to positive clinical outcomes. Methods: We matched 621 consumers whose index admission in 2014 was to a Prevention and Recovery Care (‘PARCS consumers’) with 621 similar consumers whose index admission in the same year was to an acute inpatient unit and who had no Prevention and Recovery Care stays for the study period (‘inpatient-only consumers’). We used routinely collected data to compare them on a range of outcomes. Results: Prevention and Recovery Care Services consumers made less subsequent use of acute inpatient services and, on balance, incurred costs that were similar to or lower than inpatient-only consumers. They were also less likely to spend time on an involuntary treatment order following their index admission. Prevention and Recovery Care Services consumers also experienced positive clinical outcomes over the course of their index admission, but the magnitude of this improvement was not as great as for inpatient-only consumers. This type of clinical improvement is important for Prevention and Recovery Care Services, but they may place greater emphasis on personal recovery as an outcome. Conclusion: Prevention and Recovery Care Services can provide an alternative, less restrictive care option for eligible consumers who might otherwise be admitted to an acute inpatient unit and do so at no greater cost.

Background: Stem cells-derived neuronal cultures hold great promise for in vitro disease modelling and drug screening. However, currently stem cells-derived neuronal cultures do not recapitulate the functional properties of primary neurons, such as network properties. Cultured primary murine neurons develop networks which are synchronised over large fractions of the culture, whereas neurons derived from mouse embryonic stem cells (ESCs) display only partly synchronised network activity and human pluripotent stem cells-derived neurons have mostly asynchronous network properties. Therefore, strategies to improve correspondence of derived neuronal cultures with primary neurons need to be developed to validate the use of stem cell-derived neuronal cultures as in vitro models.New method: By combining serum-free derivation of ESCs from mouse blastocysts with neuronal differentiation of ESCs in morphogen-free adherent culture we generated neuronal networks with properties recapitulating those of mature primary cortical cultures.Results: After 35 days of differentiation ESC-derived neurons developed network activity very similar to that of mature primary cortical neurons. Importantly, ESC plating density was critical for network development. Comparison with existing method(s): Compared to the previously published methods this protocol generated more synchronous neuronal networks, with high similarity to the networks formed in mature primary cortical culture.Conclusion: We have demonstrated that ESC-derived neuronal networks recapitulating key properties of mature primary cortical networks can be generated by optimising both stem cell derivation and differentiation. This validates the approach of using ESC-derived neuronal cultures for disease modelling and in vitro drug screening. (C) 2017 Elsevier B.V. All rights reserved.

Determining the mechanism of action (MOA) of novel or naturally occurring compounds mostly relies on assays tailored for individual target proteins. Here we explore an alternative approach based on pattern matching response profiles obtained using cultured neuronal networks. Conolidine and cannabidiol are plant-derivatives with known antinociceptive activity but unknown MOA. Application of conolidine/cannabidiol to cultured neuronal networks altered network firing in a highly reproducible manner and created similar impact on network properties suggesting engagement with a common biological target. We used principal component analysis (PCA) and multi-dimensional scaling (MDS) to compare network activity profiles of conolidine/cannabidiol to a series of well-studied compounds with known MOA. Network activity profiles evoked by conolidine and cannabidiol closely matched that of ω-conotoxin CVIE, a potent and selective Cav2.2 calcium channel blocker with proposed antinociceptive action suggesting that they too would block this channel. To verify this, Cav2.2 channels were heterologously expressed, recorded with whole-cell patch clamp and conolidine/cannabidiol was applied. Remarkably, conolidine and cannabidiol both inhibited Cav2.2, providing a glimpse into the MOA that could underlie their antinociceptive action. These data highlight the utility of cultured neuronal network-based workflows to efficiently identify MOA of drugs in a highly scalable assay.

In vitro Multi-Electrode Arrays (MEA) are an extracellular recording technology that enables the analysis of networks of neurons in vitro. Neurons in culture exhibit a range of behavioral dynamics, which can be measured in terms of individual action potentials, network-wide synchronized firing and a host of other features that characterize network activity. MEA data analysis was historically focused on high frequency spike data forgoing the low frequency content of the signal. In this study, we use local field potentials, which are low frequency components of MEA signals, to differentiate between two types of antiepileptic drugs (p

Multielectrode arrays (MEAs) can be used to capture electrophysiological activity of neuronal cultures with high spatio-temporal resolution and have been successfully employed in detecting changes in activity in the presence of pharmacological additions. One of the key network dynamics of these cultures is spontaneous bursting that spans across the entire network and holds rich information content. In this work, we propose the use of normalized channel-wise propagation delays during such burst events for assessing the effect of pharmacological additions. Furthermore, we investigate multiple metrics based on propagation delays and show that they effectively identify changes induced by an analgesic (a substance with pain relieving properties). Our results show that the change in the proposed metrics induced by the analgesic is significantly more pronounced (p = 0.003−0.0147) than the change induced by control perturbations.

OBJECTIVE: Multielectrode arrays are an informative extracellular recording technology that enables the analysis of cultured neuronal networks and network bursts (NBs) are a dominant feature observed in these recordings. This paper focuses on the validation of NB detection methods on different network activity patterns and developing a detection method that performs robustly across a wide variety of activity patterns. APPROACH: A firing rate based approach was used to generate artificial spike timestamps where NBs were introduced as episodes where the probability of spiking increases. Variations in firing and bursting characteristics were also included. In addition, an improved methodology of detecting NBs is proposed, based on time-binned average firing rates and time overlaps of single channel bursts. The robustness of the proposed method was compared against three existing algorithms using simulated, publicly available and newly acquired data. MAIN RESULTS: A range of activity patterns were generated by changing simulation variables that correspond to NB duration (40-2200 ms), intervals (0.3-16 s), firing rates (0.1-1 spikes s(-1)), local burst percentage (0%-90%), number of channels in local bursts (20-40) as well as the number of tonic and frequently-bursting channels. By extracting simulation parameters directly from real data, we generated synthetic data that closely resemble activity of mouse and rat cortical cultures at native and chemically perturbed states. In 50 simulated data sets with randomly selected parameter values, the improved NB detection method performed better (ascertained by the f-measure) than three existing methods (p