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

Alpha-synuclein-induced nigrostriatal degeneration and pramipexole treatment disrupt frontostriatal plasticity

Parkinson's disease is characterized by the degeneration of substantia nigra pars compacta (SNc) dopaminergic neurons, leading to motor and cognitive symptoms. Numerous cellular and molecular adaptations following neurodegeneration or dopamine replacement therapy (DRT) have been described in motor networks but little is known regarding associative basal ganglia loops. This study investigated the contributions of nigrostriatal degeneration and pramipexole (PPX) on neuronal activity in the orbitofrontal cortex (OFC), frontostriatal plasticity, and markers of synaptic plasticity. Bilateral nigrostriatal degeneration was induced by viral-mediated expression of human mutated alpha-synuclein in the SNc. Juxtacellular recordings were performed in anesthetized rats to evaluate neuronal activity in the OFC. Recordings in the dorsomedial striatum (DMS) were performed, and spike probability in response to OFC stimulation was measured before and after high-frequency stimulation (HFS). Post-mortem analysis included stereological assessment of nigral neurodegeneration, BDNF and TrkB protein levels. Nigrostriatal neurodegeneration led to altered firing patterns of OFC neurons that were restored by PPX. HFS of the OFC led to an increased spike probability in the DMS, while dopaminergic loss had the opposite effect. PPX led to a decreased spike probability following HFS in control rats and failed to counteract the effect of dopaminergic neurodegeneration. These alterations were associated with decreased levels of BDNF and TrkB in the DMS. This study demonstrates that nigral dopaminergic loss and PPX both contribute to alter frontostriatal transmission, precluding adequate information processing in associative basal ganglia loops as a gateway for the development of non-motor symptoms or non-motor side effects of DRT.

Detecting rhythmic spiking through the power spectra of point process model residuals

Objective. Oscillations figure prominently as neurological disease hallmarks and neuromodulation targets. To detect oscillations in a neuron's spiking, one might attempt to seek peaks in the spike train's power spectral density (PSD) which exceed a flat baseline. Yet for a non-oscillating neuron, the PSD is not flat: The recovery period ('RP', the post-spike drop in spike probability, starting with the refractory period) introduces global spectral distortion. An established 'shuffling' procedure corrects for RP distortion by removing the spectral component explained by the inter-spike interval (ISI) distribution. However, this procedure sacrifices oscillation-related information present in the ISIs, and therefore in the PSD. We asked whether point process models (PPMs) might achieve more selective RP distortion removal, thereby enabling improved oscillation detection.Approach. In a novel 'residuals' method, we first estimate the RP duration (nr) from the ISI distribution. We then fit the spike train with a PPM that predicts spike likelihood based on the time elapsed since the most recent of any spikes falling within the precedingnrmilliseconds. Finally, we compute the PSD of the model's residuals.Main results. We compared the residuals and shuffling methods' ability to enable accurate oscillation detection with flat baseline-assuming tests. Over synthetic data, the residuals method generally outperformed the shuffling method in classification of true- versus false-positive oscillatory power, principally due to enhanced sensitivity in sparse spike trains. In single-unit data from the internal globus pallidus (GPi) and ventrolateral anterior thalamus (VLa) of a parkinsonian monkey-in which alpha-beta oscillations (8-30 Hz) were anticipated-the residuals method reported the greatest incidence of significant alpha-beta power, with low firing rates predicting residuals-selective oscillation detection.Significance. These results encourage continued development of the residuals approach, to support more accurate oscillation detection. Improved identification of oscillations could promote improved disease models and therapeutic technologies.

BDNF and TRiC-inspired reagent rescue cortical synaptic deficits in a mouse model of Huntington's disease

Synaptic changes are early manifestations of neuronal dysfunction in Huntington's disease (HD). However, the mechanisms by which mutant HTT protein impacts synaptogenesis and function are not well understood. Herein we explored HD pathogenesis in the BACHD mouse model by examining synaptogenesis and function in long term primary cortical cultures. At DIV14 (days in vitro), BACHD cortical neurons showed no difference from WT neurons in synaptogenesis as revealed by colocalization of a pre-synaptic (Synapsin I) and a post-synaptic (PSD95) marker. From DIV21 to DIV35, BACHD neurons showed progressively reduced colocalization of Synapsin I and PSD95 relative to WT neurons. The deficits were effectively rescued by treatment of BACHD neurons with BDNF. The recombinant apical domain of CCT1 (ApiCCT1) yielded a partial rescuing effect. BACHD neurons also showed culture age-related significant functional deficits as revealed by multielectrode arrays (MEAs). These deficits were prevented by BDNF, whereas ApiCCT1 showed a less potent effect. These findings are evidence that deficits in BACHD synapse and function can be replicated in vitro and that BDNF or a TRiC-inspired reagent can potentially be protective against these changes in BACHD neurons. Our findings support the use of cellular models to further explicate HD pathogenesis and potential treatments.

Detecting rhythmic spiking through the power spectra of point process model residuals

Objective

Oscillations figure prominently as neurological disease hallmarks and neuromodulation targets. To detect oscillations in a neuron's spiking, one might attempt to seek peaks in the spike train's power spectral density (PSD) which exceed a flat baseline. Yet for a non-oscillating neuron, the PSD is not flat: The recovery period ("RP", the post-spike drop in spike probability, starting with the refractory period) introduces global spectral distortion. An established "shuffling" procedure corrects for RP distortion by removing the spectral component explained by the inter-spike interval (ISI) distribution. However, this procedure sacrifices oscillation-related information present in the ISIs, and therefore in the PSD. We asked whether point process models (PPMs) might achieve more selective RP distortion removal, thereby enabling improved oscillation detection.

Approach

In a novel "residuals" method, we first estimate the RP duration (nr) from the ISI distribution. We then fit the spike train with a PPM that predicts spike likelihood based on the time elapsed since the most recent of any spikes falling within the preceding nr milliseconds. Finally, we compute the PSD of the model's residuals.

Main results

We compared the residuals and shuffling methods' ability to enable accurate oscillation detection with flat baseline-assuming tests. Over synthetic data, the residuals method generally outperformed the shuffling method in classification of true- versus false-positive oscillatory power, principally due to enhanced sensitivity in sparse spike trains. In single-unit data from the internal globus pallidus (GPi) and ventrolateral anterior thalamus (VLa) of a parkinsonian monkey -- in which alpha-beta oscillations (8-30 Hz) were anticipated -- the residuals method reported the greatest incidence of significant alpha-beta power, with low firing rates predicting residuals-selective oscillation detection.

Significance

These results encourage continued development of the residuals approach, to support more accurate oscillation detection. Improved identification of oscillations could promote improved disease models and therapeutic technologies.

Calcium-Dependent Hyperexcitability in Human Stem Cell-Derived Rett Syndrome Neuronal Networks

Background

Mutations in MECP2 predominantly cause Rett syndrome and can be modeled in vitro using human stem cell-derived neurons. Patients with Rett syndrome have signs of cortical hyperexcitability, such as seizures. Human stem cell-derived MECP2 null excitatory neurons have smaller soma size and reduced synaptic connectivity but are also hyperexcitable due to higher input resistance. Paradoxically, networks of MECP2 null neurons show a decrease in the frequency of network bursts consistent with a hypoconnectivity phenotype. Here, we examine this issue.

Methods

We reanalyzed multielectrode array data from 3 isogenic MECP2 cell line pairs recorded over 6 weeks (n = 144). We used a custom burst detection algorithm to analyze network events and isolated a phenomenon that we termed reverberating super bursts (RSBs). To probe potential mechanisms of RSBs, we conducted pharmacological manipulations using bicuculline, EGTA-AM, and DMSO on 1 cell line (n = 34).

Results

RSBs, often misidentified as single long-duration bursts, consisted of a large-amplitude initial burst followed by several high-frequency, low-amplitude minibursts. Our analysis revealed that MECP2 null networks exhibited increased frequency of RSBs, which produced increased bursts compared with isogenic controls. Bicuculline or DMSO treatment did not affect RSBs. EGTA-AM selectively eliminated RSBs and rescued network burst dynamics.

Conclusions

During early development, MECP2 null neurons are hyperexcitable and produce hyperexcitable networks. This may predispose them to the emergence of hypersynchronic states that potentially translate into seizures. Network hyperexcitability depends on asynchronous neurotransmitter release that is likely driven by presynaptic Ca2+ and can be rescued by EGTA-AM to restore typical network dynamics.

Improved Cryopreservation of Human Induced Pluripotent Stem Cell (iPSC) and iPSC-derived Neurons Using Ice-Recrystallization Inhibitors

Human induced pluripotent stem cells (iPSCs) and iPSC-derived neurons (iPSC-Ns) represent a differentiated modality toward developing novel cell-based therapies for regenerative medicine. However, the successful application of iPSC-Ns in cell-replacement therapies relies on effective cryopreservation. In this study, we investigated the role of ice recrystallization inhibitors (IRIs) as novel cryoprotectants for iPSCs and terminally differentiated iPSC-Ns. We found that one class of IRIs, N-aryl-D-aldonamides (specifically 2FA), increased iPSC post-thaw viability and recovery with no adverse effect on iPSC pluripotency. While 2FA supplementation did not significantly improve iPSC-N cell post-thaw viability, we observed that 2FA cryopreserved iPSC-Ns re-established robust neuronal network activity and synaptic function much earlier compared to CS10 cryopreserved controls. The 2FA cryopreserved iPSC-Ns retained expression of key neuronal specific and terminally differentiated markers and displayed functional electrophysiological and neuropharmacological responses following treatment with neuroactive agonists and antagonists. We demonstrate how optimizing cryopreservation media formulations with IRIs represents a promising strategy to improve functional cryopreservation of iPSCs and post-mitotic iPSC-Ns, the latter of which have been challenging to achieve. Developing IRI enabling technologies to support an effective cryopreservation and an efficiently managed cryo-chain is fundamental to support the delivery of successful iPSC-derived therapies to the clinic.

Proprioceptive Modulation of Pallidal Physiology in Cervical Dystonia

BACKGROUND

There is a growing body of evidence suggesting that botulinum toxin can alter proprioceptive feedback and modulate the muscle-spindle output for the treatment of dystonia. However, the mechanism for this modulation remains unclear.

METHODS

We conducted a study involving 17 patients with cervical dystonia (CD), seven of whom had prominent CD and 10 with generalized dystonia (GD) along with CD. We investigated the effects of neck vibration, a form of proprioceptive modulation, on spontaneous single-neuron responses and local field potentials (LFPs) recorded from the globus pallidum externus (GPe) and internus (GPi).

RESULTS

Our findings demonstrated that neck vibration notably increased the regularity of neck-sensitive GPi neurons in focal CD patients. Additionally, in patients with GD and CD, the vibration enhanced the firing regularity of non-neck-sensitive neurons. These effects on single-unit activity were also mirrored in ensemble responses measured through LFPs. Notably, the LFP modulation was particularly pronounced in areas populated with burst neurons compared to pause or tonic cells.

CONCLUSION

The results from our study emphasize the significance of burst neurons in the pathogenesis of dystonia and in the efficacy of proprioceptive modulation for its treatment. Moreover, we observed that the effects of vibration on focal CD were prominent in the α band LFP, indicating modulation of pallido-cerebellar connectivity. Moreover, the pallidal effects of vibration in GD with CD involved modulation of cerebro-pallidal θ band connectivity. Our analysis provides insight into how vibration-induced changes in pallidal activity are integrated into the downstream motor circuit. © 2023 International Parkinson and Movement Disorder Society.

Deepening the role of excitation/inhibition balance in human iPSCs-derived neuronal networks coupled to MEAs during long-term development

Objective.The purpose of this study is to investigate whether and how the balance between excitation and inhibition ('E/I balance') influences the spontaneous development of human-derived neuronal networksin vitro. To achieve that goal, we performed a long-term (98 d) characterization of both homogeneous (only excitatory or inhibitory neurons) and heterogeneous (mixed neuronal types) cultures with controlled E/I ratios (i.e. E:I 0:100, 25:75, 50:50, 75:25, 100:0) by recording their electrophysiological activity using micro-electrode arrays.Approach.Excitatory and inhibitory neurons were derived from human induced pluripotent stem cells (hiPSCs). We realized five different configurations by systematically varying the glutamatergic and GABAergic percentages.Main results.We successfully built both homogeneous and heterogeneous neuronal cultures from hiPSCs finely controlling the E/I ratios; we were able to maintain them for up to 3 months. Homogeneity differentially impacted purely inhibitory (no bursts) and purely excitatory (few bursts) networks, deviating from the typical traits of heterogeneous cultures (burst dominated). Increased inhibition in heterogeneous cultures strongly affected the duration and organization of bursting and network bursting activity. Spike-based functional connectivity and image-based deep learning analysis further confirmed all the above.Significance.Healthy neuronal activity is controlled by a well-defined E/I balance whose alteration could lead to the onset of neurodevelopmental disorders like schizophrenia or epilepsy. Most of the commonly usedin vitromodels are animal-derived or too simplified and thus far from thein vivohuman condition. In this work, by performing a long-term study of hiPSCs-derived neuronal networks obtained from healthy human subjects, we demonstrated the feasibility of a robustin vitromodel which can be further exploited for investigating pathological conditions where the E/I balance is impaired.

Mixture effects of tetrodotoxin (TTX) and drugs targeting voltage-gated sodium channels on spontaneous neuronal activity in vitro

Tetrodotoxin (TTX) potently inhibits TTX-sensitive voltage-gated sodium (Na_V) channels in nerve and muscle cells, potentially resulting in depressed neurotransmission, paralysis and death from respiratory failure. Since a wide range of pharmaceutical drugs is known to also act on Na_V channels, the use of medicines could predispose individuals to a higher susceptibility towards TTX toxicity. We therefore first assessed the inhibitory effect of selected medicines that act on TTX-sensitive (Riluzole, Chloroquine, Fluoxetine, Valproic acid, Lamotrigine, Lidocaine) and TTX-resistant (Carbamazepine, Mexiletine, Flecainide) Na_V channels on spontaneous neuronal activity of rat primary cortical cultures grown on microelectrode arrays (MEA). After establishing concentration-effect curves, binary mixtures of the medicines with TTX at calculated NOEC, IC₂₀ and IC₅₀ values were used to determine if pharmacodynamic interactions occur between TTX and these drugs on spontaneous neuronal activity. At IC₂₀ and IC₅₀ values, all medicines significantly increased the inhibitory effect of TTX on spontaneous neuronal activity of rat cortical cells in vitro. Subsequent experiments using human iPSC-derived neuronal co-cultures grown on MEAs confirmed the ability of selected medicines (Carbamazepine, Flecainide, Riluzole, Lidocaine) to inhibit spontaneous neuronal activity. Despite the need for additional experiments using human iPSC-derived neuronal co-cultures, our combined data already highlight the importance of identifying and including vulnerable risk groups in the risk assessment of TTX.

Does Pallidal Physiology Determine the Success of Unilateral Deep Brain Stimulation in Cervical Dystonia?

Pallidal deep brain stimulation is a well-known surgical treatment for cervical dystonia. The resolution of dystonia typically requires bilateral pallidal stimulation, but in some instances, unilateral stimulation has been successful. In such instances, generally, the stimulated hemisphere was contralateral to the dystonic sternocleidomastoid, but rarely it was ipsilateral. We sought for the physiological features that determine the basis for success and laterality of deep brain stimulation for cervical dystonia with prominent torticollis. We found that pallidal physiology such as high burst to tonic ratio and significant interhemispheric differences in the neuronal firing rate and regularity are critical determinants of successful treatment with unilateral deep brain stimulation. We also found that higher lateralized differences in pallidal physiological parameters predict more robust improvement. In three out of four patients, the stimulation of the hemisphere ipsilateral to the dystonic sternocleidomastoid muscle was effective. These patients did not have any structural brain abnormalities on clinically available imaging studies. One patient responded to the unilateral deep brain stimulation in the hemisphere contralateral to the dystonic sternocleidomastoid. This patient had a structural putamen lesion on brain MRI. These results provide objective parameters determining the success of pallidal deep brain stimulation for treatment of cervical dystonia. The results also depict differences in the pallidal physiology in patients where ipsilateral versus contralateral deep brain stimulation was effective.

Selective inhibition of excitatory synaptic transmission alters the emergent bursting dynamics of in vitro neural networks

Neurons in vitro connect to each other and form neural networks that display emergent electrophysiological activity. This activity begins as spontaneous uncorrelated firing in the early phase of development, and as functional excitatory and inhibitory synapses mature, the activity typically emerges as spontaneous network bursts. Network bursts are events of coordinated global activation among many neurons interspersed with periods of silencing and are important for synaptic plasticity, neural information processing, and network computation. While bursting is the consequence of balanced excitatory-inhibitory (E/I) interactions, the functional mechanisms underlying their evolution from physiological to potentially pathophysiological states, such as decreasing or increasing in synchrony, are still poorly understood. Synaptic activity, especially that related to maturity of E/I synaptic transmission, is known to strongly influence these processes. In this study, we used selective chemogenetic inhibition to target and disrupt excitatory synaptic transmission in in vitro neural networks to study functional response and recovery of spontaneous network bursts over time. We found that over time, inhibition resulted in increases in both network burstiness and synchrony. Our results indicate that the disruption in excitatory synaptic transmission during early network development likely affected inhibitory synaptic maturity which resulted in an overall decrease in network inhibition at later stages. These findings lend support to the importance of E/I balance in maintaining physiological bursting dynamics and, conceivably, information processing capacity in neural networks.

Spontaneous Activity Predicts Survival of Developing Cortical Neurons

Spontaneous activity plays a crucial role in brain development by coordinating the integration of immature neurons into emerging cortical networks. High levels and complex patterns of spontaneous activity are generally associated with low rates of apoptosis in the cortex. However, whether spontaneous activity patterns directly encode for survival of individual cortical neurons during development remains an open question. Here, we longitudinally investigated spontaneous activity and apoptosis in developing cortical cultures, combining extracellular electrophysiology with calcium imaging. These experiments demonstrated that the early occurrence of calcium transients was strongly linked to neuronal survival. Silent neurons exhibited a higher probability of cell death, whereas high frequency spiking and burst behavior were almost exclusively detected in surviving neurons. In local neuronal clusters, activity of neighboring neurons exerted a pro-survival effect, whereas on the functional level, networks with a high modular topology were associated with lower cell death rates. Using machine learning algorithms, cell fate of individual neurons was predictable through the integration of spontaneous activity features. Our results indicate that high frequency spiking activity constrains apoptosis in single neurons through sustained calcium rises and thereby consolidates networks in which a high modular topology is reached during early development.

MEA-ToolBox: an Open Source Toolbox for Standardized Analysis of Multi-Electrode Array Data

Functional assessment of in vitro neuronal networks-of relevance for disease modelling and drug testing-can be performed using multi-electrode array (MEA) technology. However, the handling and processing of the large amount of data typically generated in MEA experiments remains a huge hurdle for researchers. Various software packages have been developed to tackle this issue, but to date, most are either not accessible through the links provided by the authors or only tackle parts of the analysis. Here, we present ''MEA-ToolBox'', a free open-source general MEA analytical toolbox that uses a variety of literature-based algorithms to process the data, detect spikes from raw recordings, and extract information at both the single-channel and array-wide network level. MEA-ToolBox extracts information about spike trains, burst-related analysis and connectivity metrics without the need of manual intervention. MEA-ToolBox is tailored for comparing different sets of measurements and will analyze data from multiple recorded files placed in the same folder sequentially, thus considerably streamlining the analysis pipeline. MEA-ToolBox is available with a graphic user interface (GUI) thus eliminating the need for any coding expertise while offering functionality to inspect, explore and post-process the data. As proof-of-concept, MEA-ToolBox was tested on earlier-published MEA recordings from neuronal networks derived from human induced pluripotent stem cells (hiPSCs) obtained from healthy subjects and patients with neurodevelopmental disorders. Neuronal networks derived from patient's hiPSCs showed a clear phenotype compared to those from healthy subjects, demonstrating that the toolbox could extract useful parameters and assess differences between normal and diseased profiles.

Theta oscillations in rat infralimbic cortex are associated with the inhibition of cocaine seeking during extinction

Infralimbic cortical (IL) manipulations indicate that this region mediates extinction learning and suppresses cocaine seeking following cocaine self‐administration. However, little work has recorded IL activity during the inhibition of cocaine seeking due to the difficulty of determining precisely when cocaine‐seeking behaviour is inhibited within a cocaine‐seeking session. The present study used in vivo electrophysiology to examine IL activity across extinction as well as during cocaine self‐administration and reinstatement. Sprague–Dawley rats underwent 6‐h access cocaine self‐administration in which the response lever was available during discrete signalled trials, a procedure which allowed for the comparison between epochs of cocaine seeking versus the inhibition thereof. Subsequently, rats underwent extinction and cocaine‐primed reinstatement using the same procedure. Results indicate that theta rhythms (4–10 Hz) dominated IL local‐field potential (LFP) activity during all experimental stages. During extinction, theta power fluctuated significantly surrounding the lever press and was lower when rats engaged in cocaine seeking versus when they withheld from doing so. These patterns of oscillatory activity differed from self‐administration and reinstatement stages. Single‐unit analyses indicate heterogeneity of IL unit responses, supporting the idea that multiple neuronal subpopulations exist within the IL and promote the expression of different and even opposing cocaine‐seeking behaviours. Together, these results are consistent with the idea that aggregate synaptic and single‐unit activity in the IL represent the engagement of the IL in action monitoring to promote adaptive behaviour in accordance with task contingencies and reveal critical insights into the relationship between IL activity and the inhibition of cocaine seeking.

Functional Characterization of Human Pluripotent Stem Cell-Derived Models of the Brain with Microelectrode Arrays

Human pluripotent stem cell (hPSC)-derived neuron cultures have emerged as models of electrical activity in the human brain. Microelectrode arrays (MEAs) measure changes in the extracellular electric potential of cell cultures or tissues and enable the recording of neuronal network activity. MEAs have been applied to both human subjects and hPSC-derived brain models. Here, we review the literature on the functional characterization of hPSC-derived two- and three-dimensional brain models with MEAs and examine their network function in physiological and pathological contexts. We also summarize MEA results from the human brain and compare them to the literature on MEA recordings of hPSC-derived brain models. MEA recordings have shown network activity in two-dimensional hPSC-derived brain models that is comparable to the human brain and revealed pathology-associated changes in disease models. Three-dimensional hPSC-derived models such as brain organoids possess a more relevant microenvironment, tissue architecture and potential for modeling the network activity with more complexity than two-dimensional models. hPSC-derived brain models recapitulate many aspects of network function in the human brain and provide valid disease models, but certain advancements in differentiation methods, bioengineering and available MEA technology are needed for these approaches to reach their full potential.

A multimodal 3D neuro-microphysiological system with neurite-trapping microelectrodes

Three-dimensional cell technologies as pre-clinical models are emerging tools for mimicking the structural and functional complexity of the nervous system. The accurate exploration of phenotypes in engineered 3D neuronal cultures, however, demands morphological, molecular and especially functional measurements. Particularly crucial is measurement of electrical activity of individual neurons with millisecond resolution. Current techniques rely on customized electrophysiological recording set-ups, characterized by limited throughput and poor integration with other readout modalities. Here we describe a novel approach, using multiwell glass microfluidic microelectrode arrays, allowing non-invasive electrical recording from engineered 3D neural tissues. We demonstrate parallelized studies with reference compounds, calcium imaging and optogenetic stimulation. Additionally, we show how microplate compatibility allows automated handling and high-content analysis of human induced pluripotent stem cell-derived neurons. This microphysiological platform opens up new avenues for high-throughput studies on the functional, morphological and molecular details of neurological diseases and their potential treatment by therapeutic compounds.

Increased burst coding in deep layers of the ventral anterior cingulate cortex during neuropathic pain

Neuropathic pain induces changes in neuronal excitability and synaptic connectivity in deep layers of the anterior cingulate cortex (ACC) that play a central role in the sensory, emotional and affective consequences of the disease. However, how this impacts ACC in vivo activity is not completely understood. Using a mouse model, we found that neuropathic pain caused an increase in ACC in vivo activity, as measured by the indirect activity marker c-Fos and juxtacellular electrophysiological recordings. The enhanced firing rate of ACC neurons in lesioned animals was based on a change in the firing pattern towards bursting activity. Despite the proportion of ACC neurons recruited by noxious stimuli was unchanged during neuropathic pain, responses to noxious stimuli were characterized by increased bursting. Thus, this change in coding pattern may have important implications for the processing of nociceptive information in the ACC and could be of great interest to guide the search for new treatment strategies for chronic pain.

Electrophysiological- and Neuropharmacological-Based Benchmarking of Human Induced Pluripotent Stem Cell-Derived and Primary Rodent Neurons

Human induced pluripotent stem cell (iPSC)-derived neurons are of interest for studying neurological disease mechanisms, developing potential therapies and deepening our understanding of the human nervous system. However, compared to an extensive history of practice with primary rodent neuron cultures, human iPSC-neurons still require more robust characterization of expression of neuronal receptors and ion channels and functional and predictive pharmacological responses. In this study, we differentiated human amniotic fluid-derived iPSCs into a mixed population of neurons (AF-iNs). Functional assessments were performed by evaluating electrophysiological (patch-clamp) properties and the effect of a panel of neuropharmacological agents on spontaneous activity (multi-electrode arrays; MEAs). These electrophysiological data were benchmarked relative to commercially sourced human iPSC-derived neurons (CNS.4U from Ncardia), primary human neurons (ScienCell™) and primary rodent cortical/hippocampal neurons. Patch-clamp whole-cell recordings showed that mature AF-iNs generated repetitive firing of action potentials in response to depolarizations, similar to that of primary rodent cortical/hippocampal neurons, with nearly half of the neurons displaying spontaneous post-synaptic currents. Immunochemical and MEA-based analyses indicated that AF-iNs were composed of functional glutamatergic excitatory and inhibitory GABAergic neurons. Principal component analysis of MEA data indicated that human AF-iN and rat neurons exhibited distinct pharmacological and electrophysiological properties. Collectively, this study establishes a necessary prerequisite for AF-iNs as a human neuron culture model suitable for pharmacological studies.

Early prediction of developing spontaneous activity in cultured neuronal networks

Synchronization and bursting activity are intrinsic electrophysiological properties of in vivo and in vitro neural networks. During early development, cortical cultures exhibit a wide repertoire of synchronous bursting dynamics whose characterization may help to understand the parameters governing the transition from immature to mature networks. Here we used machine learning techniques to characterize and predict the developing spontaneous activity in mouse cortical neurons on microelectrode arrays (MEAs) during the first three weeks in vitro. Network activity at three stages of early development was defined by 18 electrophysiological features of spikes, bursts, synchrony, and connectivity. The variability of neuronal network activity during early development was investigated by applying k-means and self-organizing map (SOM) clustering analysis to features of bursts and synchrony. These electrophysiological features were predicted at the third week in vitro with high accuracy from those at earlier times using three machine learning models: Multivariate Adaptive Regression Splines, Support Vector Machines, and Random Forest. Our results indicate that initial patterns of electrical activity during the first week in vitro may already predetermine the final development of the neuronal network activity. The methodological approach used here may be applied to explore the biological mechanisms underlying the complex dynamics of spontaneous activity in developing neuronal cultures.

Postsynaptic structure formation of human iPS cell-derived neurons takes longer than presynaptic formation during neural differentiation in vitro

The generation of mature synaptic structures using neurons differentiated from human-induced pluripotent stem cells (hiPSC-neurons) is expected to be applied to physiological studies of synapses in human cells and to pathological studies of diseases that cause abnormal synaptic function. Although it has been reported that synapses themselves change from an immature to a mature state as neurons mature, there are few reports that clearly show when and how human stem cell-derived neurons change to mature synaptic structures. This study was designed to elucidate the synapse formation process of hiPSC-neurons. We propagated hiPSC-derived neural progenitor cells (hiPSC-NPCs) that expressed localized markers of the ventral hindbrain as neurospheres by dual SMAD inhibition and then differentiated them into hiPSC-neurons in vitro. After 49 days of in vitro differentiation, hiPSC-neurons significantly expressed pre- and postsynaptic markers at both the transcript and protein levels. However, the expression of postsynaptic markers was lower than in normal human or normal rat brain tissues, and immunostaining analysis showed that it was relatively modest and was lower than that of presynaptic markers and that its localization in synaptic structures was insufficient. Neurophysiological analysis using a microelectrode array also revealed that no synaptic activity was generated on hiPSC-neurons at 49 days of differentiation. Analysis of subtype markers by immunostaining revealed that most hiPSC-neurons expressed vesicular glutamate transporter 2 (VGLUT2). The presence or absence of NGF, which is required for the survival of cholinergic neurons, had no effect on their cell fractionation. These results suggest that during the synaptogenesis of hiPSC-neurons, the formation of presynaptic structures is not the only requirement for the formation of postsynaptic structures and that the mRNA expression of postsynaptic markers does not correlate with the formation of their mature structures. Technically, we also confirmed a certain level of robustness and reproducibility of our neuronal differentiation method in a multicenter setting, which will be helpful for future research. Synapse formation with mature postsynaptic structures will remain an interesting issue for stem cell-derived neurons, and the present method can be used to obtain early and stable quality neuronal cultures from hiPSC-NPCs.

Pallidal neuron activity determines responsiveness to deep brain stimulation in cervical dystonia

OBJECTIVE

In patients with cervical dystonia we sought for the differences in neuronal behavior of pallidal regions where deep brain stimulation resulted in favorable therapeutic response compared to those where the response was absent.

METHODS

We compared single-unit activity of 564 neurons recorded from deep brain stimulation sensitive and non-sensitive regions in 17 cervical dystonia patients.

RESULTS

Globus pallidus internus regions responsive to the deep brain stimulation had lower firing rates and bursting compared to non-responsive areas. The differences were robust in locations where neuronal responses correlated with neck movements. Per the effects of deep brain stimulation, the pallidal regions were classified in weak, intermediate, and excellent responsive. Pallidal regions with weak response to deep brain stimulation had fewer burst neurons and higher firing rate compared to neurons in areas with excellent response. The burst index was significantly decreased in excellent response regions. There was a significant decrease in the alpha band oscillation score but a substantial increase in the gamma band in excellent response neurons.

CONCLUSION

The pallidal region that would be responsive to deep brain stimulation has distinct physiology compared to the non-responsive region.

SIGNIFICANCE

These results provide novel insights into globus pallidus interna neurons' physiology in cervical dystonia.

Neural burst codes disguised as rate codes

The burst coding hypothesis posits that the occurrence of sudden high-frequency patterns of action potentials constitutes a salient syllable of the neural code. Many neurons, however, do not produce clearly demarcated bursts, an observation invoked to rule out the pervasiveness of this coding scheme across brain areas and cell types. Here we ask how detrimental ambiguous spike patterns, those that are neither clearly bursts nor isolated spikes, are for neuronal information transfer. We addressed this question using information theory and computational simulations. By quantifying how information transmission depends on firing statistics, we found that the information transmitted is not strongly influenced by the presence of clearly demarcated modes in the interspike interval distribution, a feature often used to identify the presence of burst coding. Instead, we found that neurons having unimodal interval distributions were still able to ascribe different meanings to bursts and isolated spikes. In this regime, information transmission depends on dynamical properties of the synapses as well as the length and relative frequency of bursts. Furthermore, we found that common metrics used to quantify burstiness were unable to predict the degree with which bursts could be used to carry information. Our results provide guiding principles for the implementation of coding strategies based on spike-timing patterns, and show that even unimodal firing statistics can be consistent with a bivariate neural code.

Reconciling functional differences in populations of neurons recorded with two-photon imaging and electrophysiology

Extracellular electrophysiology and two-photon calcium imaging are widely used methods for measuring physiological activity with single-cell resolution across large populations of cortical neurons. While each of these two modalities has distinct advantages and disadvantages, neither provides complete, unbiased information about the underlying neural population. Here, we compare evoked responses in visual cortex recorded in awake mice under highly standardized conditions using either imaging of genetically expressed GCaMP6f or electrophysiology with silicon probes. Across all stimulus conditions tested, we observe a larger fraction of responsive neurons in electrophysiology and higher stimulus selectivity in calcium imaging, which was partially reconciled by applying a spikes-to-calcium forward model to the electrophysiology data. However, the forward model could only reconcile differences in responsiveness when restricted to neurons with low contamination and an event rate above a minimum threshold. This work established how the biases of these two modalities impact functional metrics that are fundamental for characterizing sensory-evoked responses.

Early functional changes associated with alpha-synuclein proteinopathy in engineered human neural networks

A patterned spread of proteinopathy represents a common characteristic of many neurodegenerative diseases. In Parkinson's disease (PD), misfolded forms of α-synuclein proteins accumulate in hallmark pathological inclusions termed Lewy bodies and Lewy neurites. Such protein aggregates seem to affect selectively vulnerable neuronal populations in the substantia nigra and to propagate within interconnected neuronal networks. Research findings suggest that these proteinopathic inclusions are present at very early time points in disease development, even before clear behavioral symptoms of dysfunction arise. In this study, we investigate the early pathophysiology developing after induced formation of such PD-related α-synuclein inclusions in a physiologically relevant in vitro setup using engineered human neural networks. We monitor the neural network activity using multielectrode arrays (MEAs) for a period of 3 wk following proteinopathy induction to identify associated changes in network function, with a special emphasis on the measure of network criticality. Self-organized criticality represents the critical point between resilience against perturbation and adaptational flexibility, which appears to be a functional trait in self-organizing neural networks, both in vitro and in vivo. We show that although developing pathology at early onset is not clearly manifest in standard measurements of network function, it may be discerned by investigating differences in network criticality states.

A novel methodology to describe neuronal networks activity reveals spatiotemporal recruitment dynamics of synchronous bursting states

We propose a novel phase based analysis with the purpose of quantifying the periodic bursts of activity observed in various neuronal systems. The way bursts are intiated and propagate in a spatial network is still insufficiently characterized. In particular, we investigate here how these spatiotemporal dynamics depend on the mean connection length. We use a simplified description of a neuron's state as a time varying phase between firings. This leads to a definition of network bursts, that does not depend on the practitioner's individual judgment as the usage of subjective thresholds and time scales. This allows both an easy and objective characterization of the bursting dynamics, only depending on system's proper scales. Our approach thus ensures more reliable and reproducible measurements. We here use it to describe the spatiotemporal processes in networks of intrinsically oscillating neurons. The analysis rigorously reveals the role of the mean connectivity length in spatially embedded networks in determining the existence of "leader" neurons during burst initiation, a feature incompletely understood observed in several neuronal cultures experiments. The precise definition of a burst with our method allowed us to rigorously characterize the initiation dynamics of bursts and show how it depends on the mean connectivity length. Although presented with simulations, the methodology can be applied to other forms of neuronal spatiotemporal data. As shown in a preliminary study with MEA recordings, it is not limited to in silico modeling.

Pallidal Activity in Cervical Dystonia with and Without Head Tremor

The relationship between two common movement disorders, dystonia and tremor, is controversial. Both deficits have correlates in the network that includes connections between the cerebellum and the basal ganglia. In order to assess the physiological relationship between tremor and dystonia, we measured the activity of 727 pallidal single-neurons during deep brain stimulation surgery in patients with cervical dystonia without head oscillations, cervical dystonia plus jerky oscillations, and cervical dystonia with sinusoidal oscillations. Cluster analyses of spike-train recordings allowed classification of the pallidal activity into burst, pause, and tonic. Burst neurons were more common, and number of spikes within spike and inter-burst intervals was shorter in pure dystonia and jerky oscillation groups compared to the sinusoidal oscillation group. Pause neurons were more common and irregular in pure tremor group compared to pure dystonia and jerky oscillation groups. There was bihemispheric asymmetry in spontaneous firing discharge in pure dystonia and jerky oscillation groups, but not in sinusoidal oscillation group. These results demonstrate that the physiology of pallidal neurons in patients with pure cervical dystonia is similar to those who have cervical dystonia combined with jerky oscillations, but different from those who have cervical dystonia combined with sinusoidal oscillations. These results imply distinct mechanistic underpinnings for different types of head oscillations in cervical dystonia.

Functional Abnormalities of Cerebellum and Motor Cortex in Spinal Muscular Atrophy Mice

Spinal muscular atrophy (SMA) is a devastating genetic neuromuscular disease. Diffuse neuropathology has been reported in SMA patients and mouse models, however, functional changes in brain regions have not been studied. In the SMNΔ7 mouse model, we identified three types of differences in neuronal function in the cerebellum and motor cortex from two age groups: P7-9 (P7) and P11-14 (P11). Microelectrode array studies revealed significantly lower spontaneous firing and network activity in the cerebellum of SMA mice in both age groups, but it was more profound in the P11 group. In the motor cortex, however, neural activity was not different in either age group. Whole-cell patch-clamp was used to study the function of output neurons in both brain regions. In cerebellar Purkinje cells (PCs) of SMA mice, the input resistance was larger at P7, while capacitance was smaller at P11. In the motor cortex, no difference was observed in the passive membrane properties of layer V pyramidal neurons (PN5s). The action potential threshold of both types of output neurons was depolarized in the P11 group. We also observed lower spontaneous excitatory and inhibitory synaptic activity in PN5s and PCs respectively from P11 SMA mice. Overall, these differences suggest functional alterations in the neural network in these motor regions that change during development. Our results also suggest that neuronal dysfunction in these brain regions may contribute to the pathology of SMA. Comprehensive treatment strategies may consider motor regions outside of the spinal cord for better outcomes.

Applicability of hiPSC-Derived Neuronal Cocultures and Rodent Primary Cortical Cultures for In Vitro Seizure Liability Assessment

Seizures are life-threatening adverse drug reactions which are investigated late in drug development using rodent models. Consequently, if seizures are detected, a lot of time, money and animals have been used. Thus, there is a need for in vitro screening models using human cells to circumvent interspecies translation. We assessed the suitability of cocultures of human-induced pluripotent stem cell (hiPSC)-derived neurons and astrocytes compared with rodent primary cortical cultures for in vitro seizure liability assessment using microelectrode arrays. hiPSC-derived and rodent primary cortical neuronal cocultures were exposed to 9 known (non)seizurogenic compounds (pentylenetetrazole, amoxapine, enoxacin, amoxicillin, linopirdine, pilocarpine, chlorpromazine, phenytoin, and acetaminophen) to assess effects on neuronal network activity using microelectrode array recordings. All compounds affect activity in hiPSC-derived cocultures. In rodent primary cultures all compounds, except amoxicillin changed activity. Changes in activity patterns for both cell models differ for different classes of compounds. Both models had a comparable sensitivity for exposure to amoxapine (lowest observed effect concentration [LOEC] 0.03 µM), linopirdine (LOEC 1 µM), and pilocarpine (LOEC 0.3 µM). However, hiPSC-derived cultures were about 3 times more sensitive for exposure to pentylenetetrazole (LOEC 30 µM) than rodent primary cortical cultures (LOEC 100 µM). Sensitivity of hiPSC-derived cultures for chlorpromazine, phenytoin, and enoxacin was 10-30 times higher (LOECs 0.1, 0.3, and 0.1 µM, respectively) than in rodent cultures (LOECs 10, 3, and 3 µM, respectively). Our data indicate that hiPSC-derived neuronal cocultures may outperform rodent primary cortical cultures with respect to detecting seizures, thereby paving the way towards animal-free seizure assessment.

Neuronal Activity of Pallidal Versus Cerebellar Receiving Thalamus in Patients with Cervical Dystonia

Cervical dystonia (CD) is a movement disorder characterized by a stereotyped pattern of involuntary turning or tilting of the head, often combined with jerky or tremulous movements. Hypotheses for the origin of CD have traditionally focused on the basal ganglia, but the contemporary discussion has considered the potential role of altered cerebellar function. As basal ganglia and the cerebellum largely project to the different thalamic nuclei, alterations in pallidal versus cerebellar output could be reflected in the activity of these thalamic regions. In this study, we analyzed a unique historic database where the single-unit activity of pallidal and cerebellar receiving thalamic nuclei was measured en route to the mesencephalon. We compared the single-unit activity of pallidal and cerebellar receiving thalamic neurons in three groups of CD patients manifesting as pure dystonia, pure jerky head oscillations, and dystonia plus jerky head oscillations. We found that among different CD manifestations, the characteristics of neuronal firing, such as burst versus a single-spike pattern, vary in cerebellar thalamic receiving nuclei. The cerebellar receiving region in patients with jerky oscillations had single-spikes neurons primarily. Wherein the manifestation of CD did not influence pattern distribution in the pallidal receiving thalamic area. We also found increased neuronal firing rate correlated with strength of theta-band neuronal oscillations during muscle contractions associated with dystonia. These results demonstrate that the manifestations of CD, such as pure dystonia, pure jerky head oscillations, or dystonia and jerky head oscillations, determine the thalamic neuronal properties.

Feedback-dependent neuronal properties make focal dystonias so focal

Focal dystonia, by definition, affects a specific body part; however, it may have a widespread neural substrate. We tested this hypothesis by examining the intrinsic behaviour and the neuronal properties that are modulated by changes in the physiological behaviour of their connections, that is feedback dependence, of the isolated pallidal neurons. During deep brain stimulation surgery in 12 patients with isolated cervical dystonia (without hand involvement), we measured spontaneous as well as evoked single-unit properties in response to fist making (hand movement) or shoulder shrug (neck movements). We measured the activity of isolated neurons that were only sensitive to the neck movements, hand movement, or not responsive to hand or neck movements. The spontaneous firing behaviour, such as the instantaneous firing rate and its regularity, was comparable in all three types of neurons. The neck movement-sensitive neurons had prominent bursting behaviour in comparison with the hand neurons. The feedback dependence of the neck movement-sensitive neurons was also significantly impaired when compared to hand movement-sensitive neurons. Motor-evoked change in firing rate of neck movement-sensitive neurons rapidly declined; the decay time constant was much shorter compared to hand movement-sensitive neurons. These results suggest that in isolated cervical dystonia, at the resolution of single neurons, the deficits are much widespread, affecting the neurons that drive the neck movement as well as the hand movements. We speculate that clinically discernable dystonia occurs when additional abnormality is added to baseline dysfunctional network, and one source of such abnormality may involve feedback.

Dextran-coated iron oxide nanoparticle-induced nanotoxicity in neuron cultures

Recent technological advances have introduced diverse engineered nanoparticles (ENPs) into our air, water, medicine, cosmetics, clothing, and food. However, the health and environmental effects of these increasingly common ENPs are still not well understood. In particular, potential neurological effects are one of the most poorly understood areas of nanoparticle toxicology (nanotoxicology), in that low-to-moderate neurotoxicity can be subtle and difficult to measure. Culturing primary neuron explants on planar microelectrode arrays (MEAs) has emerged as one of the most promising in vitro techniques with which to study neuro-nanotoxicology, as MEAs enable the fluorescent tracking of nanoparticles together with neuronal electrical activity recording at the submillisecond time scale, enabling the resolution of individual action potentials. Here we examine the dose-dependent neurotoxicity of dextran-coated iron oxide nanoparticles (dIONPs), a common type of functionalized ENP used in biomedical applications, on cultured primary neurons harvested from postnatal day 0-1 mouse brains. A range of dIONP concentrations (5-40 µg/ml) were added to neuron cultures, and cells were plated either onto well plates for live cell, fluorescent reactive oxidative species (ROS) and viability observations, or onto planar microelectrode arrays (MEAs) for electrophysiological measurements. Below 10 µg/ml, there were no dose-dependent cellular ROS increases or effects in MEA bursting behavior at sub-lethal dosages. However, above 20 µg/ml, cell death was obvious and widespread. Our findings demonstrate a significant dIONP toxicity in cultured neurons at concentrations previously reported to be safe for stem cells and other non-neuronal cell types.

Modelling and treating GRIN2A developmental and epileptic encephalopathy in mice

NMDA receptors play crucial roles in excitatory synaptic transmission. Rare variants in GRIN2A encoding the GluN2A subunit are associated with a spectrum of disorders, ranging from mild speech and language delay to intractable neurodevelopmental disorders, including but not limited to developmental and epileptic encephalopathy. A de novo missense variant, p.Ser644Gly, was identified in a child with this disorder, and Grin2a knock-in mice were generated to model and extend understanding of this intractable childhood disease. Homozygous and heterozygous mutant mice exhibited altered hippocampal morphology at 2 weeks of age, and all homozygotes exhibited lethal tonic-clonic seizures by mid-third week. Heterozygous adults displayed susceptibility to induced generalized seizures, hyperactivity, repetitive and reduced anxiety behaviours, plus several unexpected features, including significant resistance to electrically-induced limbic seizures and to pentylenetetrazole induced tonic-clonic seizures. Multielectrode recordings of neuronal networks revealed hyperexcitability and altered bursting and synchronicity. In heterologous cells, mutant receptors had enhanced NMDA receptor agonist potency and slow deactivation following rapid removal of glutamate, as occurs at synapses. NMDA receptor-mediated synaptic currents in heterozygous hippocampal slices also showed a prolonged deactivation time course. Standard anti-epileptic drug monotherapy was ineffective in the patient. Introduction of NMDA receptor antagonists was correlated with a decrease in seizure burden. Chronic treatment of homozygous mouse pups with NMDA receptor antagonists significantly delayed the onset of lethal seizures but did not prevent them. These studies illustrate the power of using multiple experimental modalities to model and test therapies for severe neurodevelopmental disorders, while revealing significant biological complexities associated with GRIN2A developmental and epileptic encephalopathy.

COUP-TFI/Nr2f1 Orchestrates Intrinsic Neuronal Activity during Development of the Somatosensory Cortex

The formation of functional cortical maps in the cerebral cortex results from a timely regulated interaction between intrinsic genetic mechanisms and electrical activity. To understand how transcriptional regulation influences network activity and neuronal excitability within the neocortex, we used mice deficient for Nr2f1 (also known as COUP-TFI), a key determinant of primary somatosensory (S1) area specification during development. We found that the cortical loss of Nr2f1 impacts on spontaneous network activity and synchronization of S1 cortex at perinatal stages. In addition, we observed alterations in the intrinsic excitability and morphological features of layer V pyramidal neurons. Accordingly, we identified distinct voltage-gated ion channels regulated by Nr2f1 that might directly influence intrinsic bioelectrical properties during critical time windows of S1 cortex specification. Altogether, our data suggest a tight link between Nr2f1 and neuronal excitability in the developmental sequence that ultimately sculpts the emergence of cortical network activity within the immature neocortex.

Subthalamic Single Cell and Oscillatory Neural Dynamics of a Dyskinetic Medicated Patient With Parkinson's Disease

Single cell neuronal activity (SUA) and local field potentials (LFP) in the subthalamic nucleus (STN) of unmedicated Parkinson's disease (PD) patients undergoing deep brain stimulation (DBS) surgery have been well-characterized during microelectrode recordings (MER). However, there is limited knowledge about the changes in the firing patterns and oscillations above and within the territories of STN after the intake of dopaminergic medication. Here, for the first time, we report the STN single cell and oscillatory neural dynamics in a medicated patient with idiopathic PD using intraoperative MER. We recorded LFP and SUA with microelectrodes at various depths during bilateral STN-DBS electrode implantation. We isolated 26 neurons in total and observed that tonic and irregular firing patterns of individual neurons predominated throughout the territories of STN. While burst-type firings have been well-characterized in the dorsal territories of STN in unmedicated patients, interestingly, this activity was not observed in our medicated subject. LFP recordings lacked the excessive beta (8-30 Hz) activity, characteristic of the unmedicated state and signal energy was mainly dominated by slow oscillations below 8 Hz. We observed sharp gamma oscillations between 70 and 90 Hz within and above the STN. Despite the presence of a broadband high frequency activity in 200-400 Hz range, no cross-frequency interaction in the form of phase-amplitude coupling was noted between low and high frequency oscillations of LFPs. While our results are in agreement with the previously reported LFP recordings from the DBS lead in medicated PD patients, the sharp gamma peak present throughout the depth recordings and the lack of bursting firings after levodopa intake have not been reported before. The lack of bursting in SUA, the lack of excessive beta activity and cross frequency coupling between HFOs and lower rhythms further validate the link between bursting firing regime of neurons and pathological oscillatory neural activity in PD-STN. Overall, these observations not only validate the existing literature on the PD electrophysiology in healthy/medicated animal models but also provide insights regarding the underlying electro-pathophysiology of levodopa-induced dyskinesias in PD patients through demonstration of multiscale relationships between single cell firings and field potentials.

Characterization and application of electrically active neuronal networks established from human induced pluripotent stem cell-derived neural progenitor cells for neurotoxicity evaluation

Neurotoxicity is mediated by a variety of modes-of-actions leading to disturbance of neuronal function. In order to screen larger numbers of compounds for their neurotoxic potential, in vitro functional neuronal networks (NN) might be helpful tools. We established and characterized human NN (hNN) from hiPSC-derived neural progenitor cells by comparing hNN formation with two different differentiation media: in presence (CINDA) and absence (neural differentiation medium (NDM)) of maturation-supporting factors. As a NN control we included differentiating rat NN (rNN) in the study. Gene/protein expression and electrical activity from in vitro developing NN were assessed at multiple time points. Transcriptomes of 5, 14 and 28 days in vitro CINDA-grown hNN were compared to gene expression profiles of in vivo human developing brains. Molecular expression analyses as well as measures of electrical activity indicate that NN mature into neurons of different subtypes and astrocytes over time. In contrast to rNN, hNN are less electrically active within the same period of differentiation time, yet hNN grown in CINDA medium develop higher firing rates than hNN without supplements. Challenge of NN with neuronal receptor stimulators and inhibitors demonstrate presence of inhibitory, GABAergic neurons, whereas glutamatergic responses are limited. hiPSC-derived GABAergic hNN grown in CINDA medium might be a useful tool as part of an in vitro battery for assessing neurotoxicity.

Enzymatically crosslinked gelatin-laminin hydrogels for applications in neuromuscular tissue engineering

We report a water-soluble and non-toxic method to incorporate additional extracellular matrix proteins into gelatin hydrogels, while obviating the use of chemical crosslinkers such as glutaraldehyde. Gelatin hydrogels were fabricated using a range of gelatin concentrations (4%-10%) that corresponded to elastic moduli of approximately 1 kPa-25 kPa, respectively, a substrate stiffness relevant for multiple cell types. Microbial transglutaminase was then used to enzymatically crosslink a layer of laminin on top of gelatin hydrogels, resulting in 2-component gelatin-laminin hydrogels. Human induced pluripotent stem cell derived spinal spheroids readily adhered and rapidly extended axons on GEL-LN hydrogels. Axons displayed a more mature morphology and superior electrophysiological properties on GEL-LN hydrogels compared to the controls. Schwann cells on GEL-LN hydrogels adhered and proliferated normally, displayed a healthy morphology, and maintained the expression of Schwann cell specific markers. Lastly, skeletal muscle cells on GEL-LN hydrogels achieved long-term culture for up to 28 days without delamination, while expressing higher levels of terminal genes including myosin heavy chain, MyoD, MuSK, and M-cadherin suggesting enhanced maturation potential and myotube formation compared to the controls. Future studies will employ the superior culture outcomes of this hybrid substrate for engineering functional neuromuscular junctions and related organ on a chip applications.

Grouping Neuronal Spiking Patterns in the Subthalamic Nucleus of Parkinsonian Patients

The subthalamic nucleus (STN) is a commonly used target in deep brain stimulation (DBS) to control the motor symptoms of Parkinson's Disease (PD). Identification of the spiking patterns in the STN is important in order to understand the neuropathophysiology of PD and can also assist in electrophysiological mapping of the structure. This study aims to provide a tool for grouping these firing patterns based on several extracted features from the spiking data. Single neuronal activity from the STN of PD subjects was detected and sorted to compute the binary spike trains. Several features including loca variation, bursting index and the prominence of the peak frequency of the power spectrum were extracted. Clustering of spike train segments was performed based on combination of features in 3D space to scrutinize how well they describe different firing regimes. The results show that this approach could be used to automate the grouping of stereotypic firing patterns in STN.

Unsupervised clustering reveals spatially varying single neuronal firing patterns in the subthalamic nucleus of patients with Parkinson's disease

Introduction

Subthalamic nucleus (STN) is an effective target for deep brain stimulation (DBS) to reduce the motor symptoms of Parkinson's disease (PD). It is important to identify firing patterns within the structure for a better understanding of the electro-pathophysiology of the disease. Using recently established metrics, our study aims to autonomously identify the discharge patterns of individual cells and examine their spatial distribution within the STN.

Methods

We recorded single unit activity (SUA) from 12 awake PD patients undergoing a standard clinical DBS surgery. Three extracted features from raw SUA (local variation, bursting index and prominence of peak) were used with k-means clustering to achieve the aforementioned unsupervised grouping of firing patterns.

Results

279 neurons were isolated and four distinct firing patterns were identified across patients: tonic (11%), irregular (55%), periodic (9%) and non-periodic bursts (25%). The mean firing rates for irregular discharges were significantly lower (p < 0.05) than the rest. Tonic firings were significantly ventral (p < 0.05) while periodic (p < 0.05) and non-periodic (p < 0.01) bursts were dorsal. The percentage of periodically bursting neurons in dorsal region and entire STN were significantly correlated with off state UPDRS tremor scores (r = 0.51, p = 0.04) and improvement in bradykinesia and rigidity (r = 0.57, p = 0.02) respectively.

Conclusion

Strengthening the application of unsupervised clustering for firing patterns of individual cells, this study shows a unique spatial affinity of tonic activity towards the ventral and bursting activity towards the dorsal region of STN in PD patients. This spatial preference, together with the correlation of clinical scores, can provide a clue towards understanding Parkinsonian symptom generation.

Functional characterization of human pluripotent stem cell-derived cortical networks differentiated on laminin-521 substrate: comparison to rat cortical cultures

Human pluripotent stem cell (hPSC)-derived neurons provide exciting opportunities for in vitro modeling of neurological diseases and for advancing drug development and neurotoxicological studies. However, generating electrophysiologically mature neuronal networks from hPSCs has been challenging. Here, we report the differentiation of functionally active hPSC-derived cortical networks on defined laminin-521 substrate. We apply microelectrode array (MEA) measurements to assess network events and compare the activity development of hPSC-derived networks to that of widely used rat embryonic cortical cultures. In both of these networks, activity developed through a similar sequence of stages and time frames; however, the hPSC-derived networks showed unique patterns of bursting activity. The hPSC-derived networks developed synchronous activity, which involved glutamatergic and GABAergic inputs, recapitulating the classical cortical activity also observed in rodent counterparts. Principal component analysis (PCA) based on spike rates, network synchronization and burst features revealed the segregation of hPSC-derived and rat network recordings into different clusters, reflecting the species-specific and maturation state differences between the two networks. Overall, hPSC-derived neural cultures produced with a defined protocol generate cortical type network activity, which validates their applicability as a human-specific model for pharmacological studies and modeling network dysfunctions.

Discrimination of bursts and tonic activity in multifunctional sensorimotor neural network using the extended hill-valley method

Individual neurons can exhibit a wide range of activity, including spontaneous spiking, tonic spiking, bursting, or spike-frequency adaptation, and can also transition between these activity types. Manual identification of these activity patterns can be subjective and inconsistent. The extended hill-valley (EHV) analysis discriminates tonic spiking and bursts in a spike train by detecting fluctuations in a local, history-dependent analysis signal derived from the spike train. Consequently, the EHV method is not susceptible to changes in baseline firing rate and can identify different types of activity patterns. In addition, output from the EHV method can be used to identify more complex activity patterns such as phasotonic bursting, in which a burst is immediately followed by a period of tonic spiking.NEW & NOTEWORTHY Neurons exhibit diverse spiking patterns, but automated activity classification has focused mainly on detecting bursts. The novel extended hill-valley algorithm uses a smoothed, history-dependent signal to discriminate different types of activity, such as bursts and tonic spiking.

MEAnalyzer - a Spike Train Analysis Tool for Multi Electrode Arrays

Despite a multitude of commercially available multi-electrode array (MEA) systems that are each capable of rapid data acquisition from cultured neurons or slice cultures, there is a general lack of available analysis tools. These analysis gaps restrict the efficient extraction of meaningful physiological features from data sets, and limit interpretation of how experimental manipulations modify neural network activity. Here, we present the development of a user-friendly, publicly-available software called MEAnalyzer. This software contains several spike train analysis methods including relevant statistical calculations, periodicity analysis, functional connectivity analysis, and advanced data visualizations in a user-friendly graphical user interface that requires no coding from the user. Widespread availability of this user friendly and mathematically advanced program will stimulate and enhance the use of MEA technologies.

Temporal pattern separation in hippocampal neurons through multiplexed neural codes

Pattern separation is a central concept in current theories of episodic memory: this computation is thought to support our ability to avoid confusion between similar memories by transforming similar cortical input patterns of neural activity into dissimilar output patterns before their long-term storage in the hippocampus. Because there are many ways one can define patterns of neuronal activity and the similarity between them, pattern separation could in theory be achieved through multiple coding strategies. Using our recently developed assay that evaluates pattern separation in isolated tissue by controlling and recording the input and output spike trains of single hippocampal neurons, we explored neural codes through which pattern separation is performed by systematic testing of different similarity metrics and various time resolutions. We discovered that granule cells, the projection neurons of the dentate gyrus, can exhibit both pattern separation and its opposite computation, pattern convergence, depending on the neural code considered and the statistical structure of the input patterns. Pattern separation is favored when inputs are highly similar, and is achieved through spike time reorganization at short time scales (< 100 ms) as well as through variations in firing rate and burstiness at longer time scales. These multiplexed forms of pattern separation are network phenomena, notably controlled by GABAergic inhibition, that involve many celltypes with input-output transformations that participate in pattern separation to different extents and with complementary neural codes: a rate code for dentate fast-spiking interneurons, a burstiness code for hilar mossy cells and a synchrony code at long time scales for CA3 pyramidal cells. Therefore, the isolated hippocampal circuit itself is capable of performing temporal pattern separation using multiplexed coding strategies that might be essential to optimally disambiguate multimodal mnemonic representations.

Cerebral organoids at the air-liquid interface generate diverse nerve tracts with functional output

Neural organoids have the potential to improve our understanding of human brain development and neurological disorders. However, it remains to be seen whether these tissues can model circuit formation with functional neuronal output. Here we have adapted air-liquid interface culture to cerebral organoids, leading to improved neuronal survival and axon outgrowth. The resulting thick axon tracts display various morphologies, including long-range projection within and away from the organoid, growth-cone turning, and decussation. Single-cell RNA sequencing reveals various cortical neuronal identities, and retrograde tracing demonstrates tract morphologies that match proper molecular identities. These cultures exhibit active neuronal networks, and subcortical projecting tracts can innervate mouse spinal cord explants and evoke contractions of adjacent muscle in a manner dependent on intact organoid-derived innervating tracts. Overall, these results reveal a remarkable self-organization of corticofugal and callosal tracts with a functional output, providing new opportunities to examine relevant aspects of human CNS development and disease.

The role of pallidum in the neural integrator model of cervical dystonia

Dystonia is the third most common movement disorder affecting three million people worldwide. Cervical dystonia is the most common form of dystonia. Despite common prevalence the pathophysiology of cervical dystonia is unclear. Traditional view is that basal ganglia is involved in pathophysiology of cervical dystonia, while contemporary theories suggested the role of cerebellum and proprioception in the pathophysiology of cervical dystonia. It was recently proposed that the cervical dystonia is due to malfunctioning of the head neural integrator - the neuron network that normally converts head velocity to position. Most importantly the neural integrator model was inclusive of traditional proposal emphasizing the role of basal ganglia while also accommodating the contemporary view suggesting the involvement of cerebellum and proprioception. It was hypothesized that the head neural integrator malfunction is the result of impairment in cerebellar, basal ganglia, or proprioceptive feedback that converge onto the integrator. The concept of converging input from the basal ganglia, cerebellum, and proprioception to the network participating in head neural integrator explains that abnormality originating anywhere in the network can lead to the identical motor deficits - drifts followed by rapid corrective movements - a signature of neural integrator dysfunction. We tested this hypothesis in an experiment examining simultaneously recorded globus pallidal single-unit activity, synchronized neural activity (local field potential), and electromyography (EMG) measured from the neck muscles during the standard-of-care deep brain stimulation surgery in 12 cervical dystonia patients (24 hemispheres). Physiological data were collected spontaneously or during voluntary shoulder shrug activating the contralateral trapezius muscle. The activity of pallidal neurons during shoulder shrug exponentially decayed with time constants that were comparable to one measured from the pretectal neural integrator and the trapezius electromyography. These results show that evidence of abnormal neural integration is also seen in globus pallidum, and that latter is connected with the neural integrator. Pretectal single neuron responses consistently preceded the muscle activity; while the globus pallidum internus response always lagged behind the muscle activity. Globus pallidum externa had equal proportion of lag and lead neurons. These results suggest globus pallidum receive feedback from the muscles or the efference copy from the integrator or the other source of the feedback. There was bi-hemispheric asymmetry in the pallidal single-unit activity and local field potentials. The asymmetry correlated with degree of lateral head turning in cervical dystonia patients. These results suggest that bihemispheric asymmetry in the feedback leads to asymmetric dysfunction in the neural integrator causing head turning.

Burst Detection Methods

'Bursting', defined as periods of high-frequency firing of a neuron separated by periods of quiescence, has been observed in various neuronal systems, both in vitro and in vivo. It has been associated with a range of neuronal processes, including efficient information transfer and the formation of functional networks during development, and has been shown to be sensitive to genetic and pharmacological manipulations. Accurate detection of periods of bursting activity is thus an important aspect of characterising both spontaneous and evoked neuronal network activity. A wide variety of computational methods have been developed to detect periods of bursting in spike trains recorded from neuronal networks. In this chapter, we review several of the most popular and successful of these methods.

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/.

Single unit activity of subthalamic nucleus of patients with Parkinson's disease under local and generalized anaesthesia: Multifactor analysis

The analysis of neuronal activity in human brain is a complicated task as it meets several limitations, including small sample sizes, dependent variables in the dataset and the short duration of recordings that entangles the analysis procedure. Here, we present the comparative research of neuronal activity in subthalamic nucleus (STN) of 8 Parkinsonian patients undergoing DBS surgery in awake state and under propofol anaesthesia using different statistical approaches. We studied 25 parameters of single unit activity and performed a direct comparison of the parameters between the groups to characterise the changes in STN activity under anaesthesia. We found a significant decrease in firing rate and a prominent increase in bursting of neurons in the anaesthetised state. Also, these data were used to determine the most important parameters for classification. We revealed the differences between parametric and nonparametric approaches regarding the identification of the most important spike train features. The random forest trees algorithm showed a greater accuracy of classification (91.7 ± 1.8%) compared to generalised linear models (82.4 ± 3.8%). The lists of the features important for classification according to F-scores and random forest trees also differed markedly. Our results indicate that feature interactions play a key role in neuronal activity analysis and must be taken into account.

Challenges in Reproducibility, Replicability, and Comparability of Computational Models and Tools for Neuronal and Glial Networks, Cells, and Subcellular Structures

The possibility to replicate and reproduce published research results is one of the biggest challenges in all areas of science. In computational neuroscience, there are thousands of models available. However, it is rarely possible to reimplement the models based on the information in the original publication, let alone rerun the models just because the model implementations have not been made publicly available. We evaluate and discuss the comparability of a versatile choice of simulation tools: tools for biochemical reactions and spiking neuronal networks, and relatively new tools for growth in cell cultures. The replicability and reproducibility issues are considered for computational models that are equally diverse, including the models for intracellular signal transduction of neurons and glial cells, in addition to single glial cells, neuron-glia interactions, and selected examples of spiking neuronal networks. We also address the comparability of the simulation results with one another to comprehend if the studied models can be used to answer similar research questions. In addition to presenting the challenges in reproducibility and replicability of published results in computational neuroscience, we highlight the need for developing recommendations and good practices for publishing simulation tools and computational models. Model validation and flexible model description must be an integral part of the tool used to simulate and develop computational models. Constant improvement on experimental techniques and recording protocols leads to increasing knowledge about the biophysical mechanisms in neural systems. This poses new challenges for computational neuroscience: extended or completely new computational methods and models may be required. Careful evaluation and categorization of the existing models and tools provide a foundation for these future needs, for constructing multiscale models or extending the models to incorporate additional or more detailed biophysical mechanisms. Improving the quality of publications in computational neuroscience, enabling progressive building of advanced computational models and tools, can be achieved only through adopting publishing standards which underline replicability and reproducibility of research results.