meaRtools: An R package for the analysis of neuronal networks recorded on microelectrode arrays

Here we present an open-source R package 'meaRtools' that provides a platform for analyzing neuronal networks recorded on Microelectrode Arrays (MEAs). Cultured neuronal networks monitored with MEAs are now being widely used to characterize in vitro models of neurological disorders and to evaluate pharmaceutical compounds. meaRtools provides core algorithms for MEA spike train analysis, feature extraction, statistical analysis and plotting of multiple MEA recordings with multiple genotypes and treatments. meaRtools functionality covers novel solutions for spike train analysis, including algorithms to assess electrode cross-correlation using the spike train tiling coefficient (STTC), mutual information, synchronized bursts and entropy within cultured wells. Also integrated is a solution to account for bursts variability originating from mixed-cell neuronal cultures. The package provides a statistical platform built specifically for MEA data that can combine multiple MEA recordings and compare extracted features between different genetic models or treatments. We demonstrate the utilization of meaRtools to successfully identify epilepsy-like phenotypes in neuronal networks from Celf4 knockout mice. The package is freely available under the GPL license (GPL> = 3) and is updated frequently on the CRAN web-server repository. The package, along with full documentation can be downloaded from: https://cran.r-project.org/web/packages/meaRtools/.

Characterization of Early Cortical Neural Network Development in Multiwell Microelectrode Array Plates

We examined neural network ontogeny using microelectrode array (MEA) recordings made in multiwell MEA (mwMEA) plates over the first 12 days in vitro (DIV). In primary cortical cultures, action potential spiking activity developed rapidly between DIV 5 and 12. Spiking was sporadic and unorganized at early DIV, and became progressively more organized with time, with bursting parameters, synchrony, and network bursting increasing between DIV 5 and 12. We selected 12 features to describe network activity; principal components analysis using these features demonstrated segregation of data by age at both the well and plate levels. Using random forest classifiers and support vector machines, we demonstrated that four features (coefficient of variation [CV] of within-burst interspike interval, CV of interburst interval, network spike rate, and burst rate) could predict the age of each well recording with >65% accuracy. When restricting the classification to a binary decision, accuracy improved to as high as 95%. Further, we present a novel resampling approach to determine the number of wells needed for comparing different treatments. Overall, these results demonstrate that network development on mwMEA plates is similar to development in single-well MEAs. The increased throughput of mwMEAs will facilitate screening drugs, chemicals, or disease states for effects on neurodevelopment.

A comparison of computational methods for detecting bursts in neuronal spike trains and their application to human stem cell-derived neuronal networks

We provide an unbiased quantitative assessment of eight existing methods for identifying bursts in neuronal spike trains. We reveal limitations in a number of commonly used burst detection techniques and provide recommendations for the best practice for accurate identification of bursts using existing techniques. An analysis of the ontogeny of bursting activity in a novel data set of recordings from human induced pluripotent stem cell-derived neuronal networks, using the highest-performing burst detectors from our study, is also presented.

Accurate identification of bursting activity is an essential element in the characterization of neuronal network activity. Despite this, no one technique for identifying bursts in spike trains has been widely adopted. Instead, many methods have been developed for the analysis of bursting activity, often on an ad hoc basis. Here we provide an unbiased assessment of the effectiveness of eight of these methods at detecting bursts in a range of spike trains. We suggest a list of features that an ideal burst detection technique should possess and use synthetic data to assess each method in regard to these properties. We further employ each of the methods to reanalyze microelectrode array (MEA) recordings from mouse retinal ganglion cells and examine their coherence with bursts detected by a human observer. We show that several common burst detection techniques perform poorly at analyzing spike trains with a variety of properties. We identify four promising burst detection techniques, which are then applied to MEA recordings of networks of human induced pluripotent stem cell-derived neurons and used to describe the ontogeny of bursting activity in these networks over several months of development. We conclude that no current method can provide “perfect” burst detection results across a range of spike trains; however, two burst detection techniques, the MaxInterval and logISI methods, outperform compared with others. We provide recommendations for the robust analysis of bursting activity in experimental recordings using current techniques.

Quantitative differences in developmental profiles of spontaneous activity in cortical and hippocampal cultures

BACKGROUND

Neural circuits can spontaneously generate complex spatiotemporal firing patterns during development. This spontaneous activity is thought to help guide development of the nervous system. In this study, we had two aims. First, to characterise the changes in spontaneous activity in cultures of developing networks of either hippocampal or cortical neurons dissociated from mouse. Second, to assess whether there are any functional differences in the patterns of activity in hippocampal and cortical networks.

RESULTS

We used multielectrode arrays to record the development of spontaneous activity in cultured networks of either hippocampal or cortical neurons every 2 or 3 days for the first month after plating. Within a few days of culturing, networks exhibited spontaneous activity. This activity strengthened and then stabilised typically around 21 days in vitro. We quantified the activity patterns in hippocampal and cortical networks using 11 features. Three out of 11 features showed striking differences in activity between hippocampal and cortical networks: (1) interburst intervals are less variable in spike trains from hippocampal cultures; (2) hippocampal networks have higher correlations and (3) hippocampal networks generate more robust theta-bursting patterns. Machine-learning techniques confirmed that these differences in patterning are sufficient to classify recordings reliably at any given age as either hippocampal or cortical networks.

CONCLUSIONS

Although cultured networks of hippocampal and cortical networks both generate spontaneous activity that changes over time, at any given time we can reliably detect differences in the activity patterns. We anticipate that this quantitative framework could have applications in many areas, including neurotoxicity testing and for characterising the phenotype of different mutant mice. All code and data relating to this report are freely available for others to use.

ET-receptor subtypes: roles in regional renal vascular actions of exogenous and endogenous endothelins in anesthetized rabbits

The roles of endothelin (ET)-receptor subtypes, in the regional renal vascular effects of exogenous and endogenous ETs, were examined in pentobarbitone-anesthetized rabbits. The effects of renal arterial infusion of ET-1 (0.05-12.8 ng/kg/min) and the ET(B)-agonist [Ala1,3,11,15]-ET-1 (12.5-800 ng/kg/min) were compared. We then tested the effects of the ET(A)-antagonist BQ610 and the ET(B)-antagonist BQ788 (both 200 microg/kg plus 100 microg/kg/h, i.v.) on basal hemodynamics and on responses to renal arterial ET-1. Both ET-1 and [Ala1,3,11,15]-ET-1 dose-dependently reduced total renal blood flow (RBF) and cortical blood flow (CBF), but not medullary blood flow (MBF). ET-1 was 34-fold more potent than [Ala1,3,11,15-ET-1. BQ610 reduced mean arterial pressure (MAP; 14%), and increased RBF (21%) and CBF (12%), but not MBF. BQ788 increased MAP (13%), and reduced RBF (29%) and CBF (15%) but not MBF. Coadministration of both agents increased RBF (18%) and CBF (9%), without significantly affecting MAP. Neither antagonist (alone or combined) significantly affected responses to renal arterial ET-1. We conclude that the predominant renal vascular effects of exogenous and endogenous ETs are cortical vasoconstriction, but not at vascular sites controlling MBF. ET(A)-receptors contribute to the renal vasoconstrictor effects of endogenous ETs. ET(B2)-like receptors appear to contribute to the vasoconstrictor effects of [Ala1,3,11,15]-ET-1.

Renal haemodynamic effects of endothelin-1 and the ETA/ETB antagonist TAK-044 in anaesthetized rabbits

OBJECTIVE

The aim of this study was to test the effects of exogenous endothelin-1 (ET-1) on regional kidney blood flow and renal function, and the renal haemodynamic effects of endogenous ET, in anaesthetized rabbits.

METHODS

ET-1 was infused into the left renal artery at 2 ng/kg/min for 30 min, then at 1 ng/kg/min. Cumulative doses of TAK-044 (0.1-3 mg/kg, i.v.) or its vehicle were given at 30-min intervals. In other rabbits, an extracorporeal circuit was established to adjust renal arterial pressure (RAP) independently of systemic arterial pressure (MAP). RAP was set at 65 mmHg, and either TAK-044 (3 mg/kg, i.v.) or its vehicle was administered.

RESULTS

In the infused kidney ET-1 (2 ng/kg/min) reduced renal blood flow (RBFprobe; 52+/-8%), cortical perfusion (37+/-7%), glomerular filtration rate (GFR; 49+/-8%), urine flow (47+/-14%) and sodium excretion (49+/-13%), but not medullary perfusion (5+/-6%). No effects of ET-1 on MAP or on the contralateral kidney were observed. TAK-044 dose-dependently reversed the effects of ET-1 on RBFprobe and cortical perfusion. TAK-044 also reduced MAP (by up to 11+/-3%) and increased effective renal blood flow in the contralateral kidney (by up to 46+/-27%). In the extracorporeal circuit model, TAK-044 decreased MAP by 12+/-2% and RAP by 10+/-3%, and increased RBF by 9+/-3%.

CONCLUSION

Exogenous ET-1 reduces cortical more than medullary perfusion, and reduces GFR without affecting net tubular sodium and fluid reabsorption. TAK-044 antagonizes local renal vascular responses to ET-1. Endogenous ETs appear to contribute markedly to resting renal vasomotor tone and MAP.