Spontaneous and Perturbational Complexity in Cortical Cultures.

Dissociated cortical neurons in vitro display spontaneously synchronized, low-frequency firing patterns, which can resemble the slow wave oscillations characterizing sleep in vivo. Experiments in humans, rodents, and cortical slices have shown that awakening or the administration of activating neuromodulators decrease slow waves, while increasing the spatio-temporal complexity of responses to perturbations. In this study, we attempted to replicate those findings using in vitro cortical cultures coupled with micro-electrode arrays and chemically treated with carbachol (CCh), to modulate sleep-like activity and suppress slow oscillations. We adapted metrics such as neural complexity (NC) and the perturbational complexity index (PCI), typically employed in animal and human brain studies, to quantify complexity in simplified, unstructured networks, both during resting state and in response to electrical stimulation. After CCh administration, we found a decrease in the amplitude of the initial response and a marked enhancement of the complexity during spontaneous activity. Crucially, unlike in cortical slices and intact brains, PCI in cortical cultures displayed only a moderate increase. This dissociation suggests that PCI, a measure of the complexity of causal interactions, requires more than activating neuromodulation and that additional factors, such as an appropriate circuit architecture, may be necessary. Exploring more structured in vitro networks, characterized by the presence of strong lateral connections, recurrent excitation, and feedback loops, may thus help to identify the features that are more relevant to support causal complexity.

Kainate Receptor Activation Shapes Short-Term Synaptic Plasticity by Controlling Receptor Lateral Mobility at Glutamatergic Synapses.

Kainate receptors (KARs) mediate postsynaptic currents with a key impact on neuronal excitability. However, the molecular determinants controlling KAR postsynaptic localization and stabilization are poorly understood. Here, we exploit optogenetic and single-particle tracking approaches to study the role of KAR conformational states induced by glutamate binding on KAR lateral mobility at synapses. We report that following glutamate binding, KARs are readily and reversibly trapped at glutamatergic synapses through increased interaction with the ß-catenin/N-cadherin complex. We demonstrate that such activation-dependent synaptic immobilization of KARs is crucial for the modulation of short-term plasticity of glutamatergic synapses. Thus, the present study unveils the crosstalk between conformational states and lateral mobility of KARs, a mechanism regulating glutamatergic signaling, particularly in conditions of sustained synaptic activity.

Constitutive Inactivation of the PRRT2 Gene Alters Short-Term Synaptic Plasticity and Promotes Network Hyperexcitability in Hippocampal Neurons.

Mutations in PRoline-Rich Transmembrane protein 2 (PRRT2) underlie a group of paroxysmal disorders including epilepsy, kinesigenic dyskinesia and migraine. Most of the mutations lead to impaired PRRT2 expression and/or function, emphasizing the pathogenic role of the PRRT2 deficiency. In this work, we investigated the phenotype of primary hippocampal neurons obtained from mouse embryos in which the PRRT2 gene was constitutively inactivated. Although PRRT2 is expressed by both excitatory and inhibitory neurons, its deletion decreases the number of excitatory synapses without significantly affecting the number of inhibitory synapses or the nerve terminal ultrastructure. Analysis of synaptic function in primary PRRT2 knockout excitatory neurons by live imaging and electrophysiology showed slowdown of the kinetics of exocytosis, weakened spontaneous and evoked synaptic transmission and markedly increased facilitation. Inhibitory neurons showed strengthening of basal synaptic transmission, accompanied by faster depression. At the network level these complex synaptic effects resulted in a state of heightened spontaneous and evoked activity that was associated with increased excitability of excitatory neurons in both PRRT2 knockout primary cultures and acute hippocampal slices. The data indicate the existence of network instability/hyperexcitability as the possible basis of the paroxysmal phenotypes associated with PRRT2 mutations.

State-dependent representation of stimulus-evoked activity in high-density recordings of neural cultures.

Neuronal responses to external stimuli vary from trial to trial partly because they depend on continuous spontaneous variations of the state of neural circuits, reflected in variations of ongoing activity prior to stimulus presentation. Understanding how post-stimulus responses relate to the pre-stimulus spontaneous activity is thus important to understand how state dependence affects information processing and neural coding, and how state variations can be discounted to better decode single-trial neural responses. Here we exploited high-resolution CMOS electrode arrays to record simultaneously from thousands of electrodes in in-vitro cultures stimulated at specific sites. We used information-theoretic analyses to study how ongoing activity affects the information that neuronal responses carry about the location of the stimuli. We found that responses exhibited state dependence on the time between the last spontaneous burst and the stimulus presentation and that the dependence could be described with a linear model. Importantly, we found that a small number of selected neurons carry most of the stimulus information and contribute to the state-dependent information gain. This suggests that a major value of large-scale recording is that it individuates the small subset of neurons that carry most information and that benefit the most from knowledge of its state dependence.

PRRT2 controls neuronal excitability by negatively modulating Na+ channel 1.2/1.6 activity.

See Lerche (doi:10.1093/brain/awy073) for a scientific commentary on this article.Proline-rich transmembrane protein 2 (PRRT2) is the causative gene for a heterogeneous group of familial paroxysmal neurological disorders that include seizures with onset in the first year of life (benign familial infantile seizures), paroxysmal kinesigenic dyskinesia or a combination of both. Most of the PRRT2 mutations are loss-of-function leading to haploinsufficiency and 80% of the patients carry the same frameshift mutation (c.649dupC; p.Arg217Profs*8), which leads to a premature stop codon. To model the disease and dissect the physiological role of PRRT2, we studied the phenotype of neurons differentiated from induced pluripotent stem cells from previously described heterozygous and homozygous siblings carrying the c.649dupC mutation. Single-cell patch-clamp experiments on induced pluripotent stem cell-derived neurons from homozygous patients showed increased Na+ currents that were fully rescued by expression of wild-type PRRT2. Closely similar electrophysiological features were observed in primary neurons obtained from the recently characterized PRRT2 knockout mouse. This phenotype was associated with an increased length of the axon initial segment and with markedly augmented spontaneous and evoked firing and bursting activities evaluated, at the network level, by multi-electrode array electrophysiology. Using HEK-293 cells stably expressing Nav channel subtypes, we demonstrated that the expression of PRRT2 decreases the membrane exposure and Na+ current of Nav1.2/Nav1.6, but not Nav1.1, channels. Moreover, PRRT2 directly interacted with Nav1.2/Nav1.6 channels and induced a negative shift in the voltage-dependence of inactivation and a slow-down in the recovery from inactivation. In addition, by co-immunoprecipitation assays, we showed that the PRRT2-Nav interaction also occurs in brain tissue. The study demonstrates that the lack of PRRT2 leads to a hyperactivity of voltage-dependent Na+ channels in homozygous PRRT2 knockout human and mouse neurons and that, in addition to the reported synaptic functions, PRRT2 is an important negative modulator of Nav1.2 and Nav1.6 channels. Given the predominant paroxysmal character of PRRT2-linked diseases, the disturbance in cellular excitability by lack of negative modulation of Na+ channels appears as the key pathogenetic mechanism.

The after-hours circadian mutant has reduced phenotypic plasticity in behaviors at multiple timescales and in sleep homeostasis.

Circadian clock is known to adapt to environmental changes and can significantly influence cognitive and physiological functions. In this work, we report specific behavioral, cognitive, and sleep homeostatic defects in the after hours (Afh) circadian mouse mutant, which is characterized by lengthened circadian period. We found that the circadian timing irregularities in Afh mice resulted in higher interval timing uncertainty and suboptimal decisions due to incapability of processing probabilities. Our phenotypic observations further suggested that Afh mutants failed to exhibit the necessary phenotypic plasticity for adapting to temporal changes at multiple time scales (seconds-to-minutes to circadian). These behavioral effects of Afh mutation were complemented by the specific disruption of the Per/Cry circadian regulatory complex in brain regions that govern food anticipatory behaviors, sleep, and timing. We derive statistical predictions, which indicate that circadian clock and sleep are complementary processes in controlling behavioral/cognitive performance during 24 hrs. The results of this study have pivotal implications for understanding how the circadian clock modulates sleep and behavior.

Recurrently connected and localized neuronal communities initiate coordinated spontaneous activity in neuronal networks.

Developing neuronal systems intrinsically generate coordinated spontaneous activity that propagates by involving a large number of synchronously firing neurons. In vivo, waves of spikes transiently characterize the activity of developing brain circuits and are fundamental for activity-dependent circuit formation. In vitro, coordinated spontaneous spiking activity, or network bursts (NBs), interleaved within periods of asynchronous spikes emerge during the development of 2D and 3D neuronal cultures. Several studies have investigated this type of activity and its dynamics, but how a neuronal system generates these coordinated events remains unclear. Here, we investigate at a cellular level the generation of network bursts in spontaneously active neuronal cultures by exploiting high-resolution multielectrode array recordings and computational network modelling. Our analysis reveals that NBs are generated in specialized regions of the network (functional neuronal communities) that feature neuronal links with high cross-correlation peak values, sub-millisecond lags and that share very similar structural connectivity motifs providing recurrent interactions. We show that the particular properties of these local structures enable locally amplifying spontaneous asynchronous spikes and that this mechanism can lead to the initiation of NBs. Through the analysis of simulated and experimental data, we also show that AMPA currents drive the coordinated activity, while NMDA and GABA currents are only involved in shaping the dynamics of NBs. Overall, our results suggest that the presence of functional neuronal communities with recurrent local connections allows a neuronal system to generate spontaneous coordinated spiking activity events. As suggested by the rules used for implementing our computational model, such functional communities might naturally emerge during network development by following simple constraints on distance-based connectivity.

Inter-Synaptic Lateral Diffusion of GABAA Receptors Shapes Inhibitory Synaptic Currents.

The lateral mobility of neurotransmitter receptors has been shown to tune synaptic signals. Here we report that GABAA receptors (GABAARs) can diffuse between adjacent dendritic GABAergic synapses in long-living desensitized states, thus laterally spreading "activation memories" between inhibitory synapses. Glutamatergic activity limits this inter-synaptic diffusion by trapping GABAARs at excitatory synapses. This novel form of activity-dependent hetero-synaptic interplay is likely to modulate dendritic synaptic signaling.

High-resolution bioelectrical imaging of Aß-induced network dysfunction on CMOS-MEAs for neurotoxicity and rescue studies.

Neurotoxicity and the accumulation of extracellular amyloid-beta1-42 (Aß) peptides are associated with the development of Alzheimer's disease (AD) and correlate with neuronal activity and network dysfunctions, ultimately leading to cellular death. However, research on neurodegenerative diseases is hampered by the paucity of reliable readouts and experimental models to study such functional decline from an early onset and to test rescue strategies within networks at cellular resolution. To overcome this important obstacle, we demonstrate a simple yet powerful in vitro AD model based on a rat hippocampal cell culture system that exploits large-scale neuronal recordings from 4096-electrodes on CMOS-chips for electrophysiological quantifications. This model allows us to monitor network activity changes at the cellular level and to uniquely uncover the early activity-dependent deterioration induced by Aß-neurotoxicity. We also demonstrate the potential of this in vitro model to test a plausible hypothesis underlying the Aß-neurotoxicity and to assay potential therapeutic approaches. Specifically, by quantifying N-methyl D-aspartate (NMDA) concentration-dependent effects in comparison with low-concentration allogenic-Aß, we confirm the role of extrasynaptic-NMDA receptors activation that may contribute to Aß-neurotoxicity. Finally, we assess the potential rescue of neural stem cells (NSCs) and of two pharmacotherapies, memantine and saffron, for reversing Aß-neurotoxicity and rescuing network-wide firing.

Nanoscale Molecular Reorganization of the Inhibitory Postsynaptic Density Is a Determinant of GABAergic Synaptic Potentiation.

Gephyrin is a key scaffold protein mediating the anchoring of GABAA receptors at inhibitory synapses. Here, we exploited superresolution techniques combined with proximity-based clustering analysis and model simulations to investigate the single-molecule gephyrin reorganization during plasticity of inhibitory synapses in mouse hippocampal cultured neurons. This approach revealed that, during the expression of inhibitory LTP, the increase of gephyrin density at postsynaptic sites is associated with the promoted formation of gephyrin nanodomains. We demonstrate that the gephyrin rearrangement in nanodomains stabilizes the amplitude of postsynaptic currents, indicating that, in addition to the number of synaptic GABAA receptors, the nanoscale distribution of GABAA receptors in the postsynaptic area is a crucial determinant for the expression of inhibitory synaptic plasticity. In addition, the methodology implemented here clears the way to the application of the graph-based theory to single-molecule data for the description and quantification of the spatial organization of the synapse at the single-molecule level.SIGNIFICANCE STATEMENT The mechanisms of inhibitory synaptic plasticity are poorly understood, mainly because the size of the synapse is below the diffraction limit, thus reducing the effectiveness of conventional optical and imaging techniques. Here, we exploited superresolution approaches combined with clustering analysis to study at unprecedented resolution the distribution of the inhibitory scaffold protein gephyrin in response to protocols inducing LTP of inhibitory synaptic responses (iLTP). We found that, during the expression of iLTP, the increase of synaptic gephyrin is associated with the fragmentation of gephyrin in subsynaptic nanodomains. We demonstrate that such synaptic gephyrin nanodomains stabilize the amplitude of inhibitory postsynaptic responses, thus identifying the nanoscale gephyrin rearrangement as a key determinant for inhibitory synaptic plasticity.

Electrical Responses and Spontaneous Activity of Human iPS-Derived Neuronal Networks Characterized for 3-month Culture with 4096-Electrode Arrays.

The recent availability of human induced pluripotent stem cells (hiPSCs) holds great promise as a novel source of human-derived neurons for cell and tissue therapies as well as for in vitro drug screenings that might replace the use of animal models. However, there is still a considerable lack of knowledge on the functional properties of hiPSC-derived neuronal networks, thus limiting their application. Here, upon optimization of cell culture protocols, we demonstrate that both spontaneous and evoked electrical spiking activities of these networks can be characterized on-chip by taking advantage of the resolution provided by CMOS multielectrode arrays (CMOS-MEAs). These devices feature a large and closely-spaced array of 4096 simultaneously recording electrodes and multi-site on-chip electrical stimulation. Our results show that networks of human-derived neurons can respond to electrical stimulation with a physiological repertoire of spike waveforms after 3 months of cell culture, a period of time during which the network undergoes the expression of developing patterns of spontaneous spiking activity. To achieve this, we have investigated the impact on the network formation and on the emerging network-wide functional properties induced by different biochemical substrates, i.e., poly-dl-ornithine (PDLO), poly-l-ornithine (PLO), and polyethylenimine (PEI), that were used as adhesion promoters for the cell culture. Interestingly, we found that neuronal networks grown on PDLO coated substrates show significantly higher spontaneous firing activity, reliable responses to low-frequency electrical stimuli, and an appropriate level of PSD-95 that may denote a physiological neuronal maturation profile and synapse stabilization. However, our results also suggest that even 3-month culture might not be sufficient for human-derived neuronal network maturation. Taken together, our results highlight the tight relationship existing between substrate coatings and emerging network properties, i.e., spontaneous activity, responsiveness, synapse formation and maturation. Additionally, our results provide a baseline on the functional properties expressed over 3 months of network development for a commercially available line of hiPSC-derived neurons. This is a first step toward the development of functional pre-clinical assays to test pharmaceutical compounds on human-derived neuronal networks with CMOS-MEAs.

Corrigendum: Regulation of output spike patterns by phasic inhibition in cerebellar granule cells.

[This corrects the article on p. 246 in vol. 8, PMID: 25202237.].

Characterizing the Input-Output Function of the Olfactory-Limbic Pathway in the Guinea Pig.

Nowadays the neuroscientific community is taking more and more advantage of the continuous interaction between engineers and computational neuroscientists in order to develop neuroprostheses aimed at replacing damaged brain areas with artificial devices. To this end, a technological effort is required to develop neural network models which can be fed with the recorded electrophysiological patterns to yield the correct brain stimulation to recover the desired functions. In this paper we present a machine learning approach to derive the input-output function of the olfactory-limbic pathway in the in vitro whole brain of guinea pig, less complex and more controllable than an in vivo system. We first experimentally characterized the neuronal pathway by delivering different sets of electrical stimuli from the lateral olfactory tract (LOT) and by recording the corresponding responses in the lateral entorhinal cortex (l-ERC). As a second step, we used information theory to evaluate how much information output features carry about the input. Finally we used the acquired data to learn the LOT-l-ERC "I/O function," by means of the kernel regularized least squares method, able to predict l-ERC responses on the basis of LOT stimulation features. Our modeling approach can be further exploited for brain prostheses applications.

Microelectronics, bioinformatics and neurocomputation for massive neuronal recordings in brain circuits with large scale multielectrode array probes.

Deciphering neural network function in health and disease requires recording from many active neurons simultaneously. Developing approaches to increase their numbers is a major neurotechnological challenge. Parallel to recent advances in optical Ca(2+) imaging, an emerging approach consists in adopting complementary-metal-oxide-semiconductor (CMOS) technology to realize MultiElectrode Array (MEA) devices. By implementing signal conditioning and multiplexing circuits, these devices allow nowadays to record from several thousands of single neurons at sub-millisecond temporal resolution. At the same time, these recordings generate very large data streams which become challenging to analyze. Here, at first we shortly review the major approaches developed for data management and analysis for conventional, low-resolution MEAs. We highlight how conventional computational tools cannot be easily up-scaled to very large electrode array recordings, and custom bioinformatics tools are an emerging need in this field. We then introduce a novel approach adapted for the acquisition, compression and analysis of extracellular signals acquired simultaneously from 4096 electrodes with CMOS MEAs. Finally, as a case study, we describe how this novel large scale recording platform was used to record and analyze extracellular spikes from the ganglion cell layer in the wholemount retina at pan-retinal scale following patterned light stimulation.

Functional Interaction between the Scaffold Protein Kidins220/ARMS and Neuronal Voltage-Gated Na+ Channels.

Kidins220 (kinase D-interacting substrate of 220 kDa)/ankyrin repeat-rich membrane spanning (ARMS) acts as a signaling platform at the plasma membrane and is implicated in a multitude of neuronal functions, including the control of neuronal activity. Here, we used the Kidins220(-/-) mouse model to study the effects of Kidins220 ablation on neuronal excitability. Multielectrode array recordings showed reduced evoked spiking activity in Kidins220(-/-) hippocampal networks, which was compatible with the increased excitability of GABAergic neurons determined by current-clamp recordings. Spike waveform analysis further indicated an increased sodium conductance in this neuronal subpopulation. Kidins220 association with brain voltage-gated sodium channels was shown by co-immunoprecipitation experiments and Na(+) current recordings in transfected HEK293 cells, which revealed dramatic alterations of kinetics and voltage dependence. Finally, an in silico interneuronal model incorporating the Kidins220-induced Na(+) current alterations reproduced the firing phenotype observed in Kidins220(-/-) neurons. These results identify Kidins220 as a novel modulator of Nav channel activity, broadening our understanding of the molecular mechanisms regulating network excitability.

From 2D to 3D: novel nanostructured scaffolds to investigate signalling in reconstructed neuronal networks.

To recreate in vitro 3D neuronal circuits will ultimately increase the relevance of results from cultured to whole-brain networks and will promote enabling technologies for neuro-engineering applications. Here we fabricate novel elastomeric scaffolds able to instruct 3D growth of living primary neurons. Such systems allow investigating the emerging activity, in terms of calcium signals, of small clusters of neurons as a function of the interplay between the 2D or 3D architectures and network dynamics. We report the ability of 3D geometry to improve functional organization and synchronization in small neuronal assemblies. We propose a mathematical modelling of network dynamics that supports such a result. Entrapping carbon nanotubes in the scaffolds remarkably boosted synaptic activity, thus allowing for the first time to exploit nanomaterial/cell interfacing in 3D growth support. Our 3D system represents a simple and reliable construct, able to improve the complexity of current tissue culture models.

Investigating cell culture dynamics combining high density recordings with dimensional reduction techniques.

High density multielectrode array recordings with CMOS-MEAs allow to monitor cell culture activity with unprecedent details respect to previous recording techniques. This is clarifying how network activity develops and is motivating the development of novel data analysis tools. Here, in order to advance in the exploitation of the richness of these large-scale array recordings, we introduce a principal component analysis approach that aims at improving on existing methodologies to describe neural activity events within large networks.

High-density MEA recordings unveil the dynamics of bursting events in Cell Cultures.

High density multielectrode arrays (MEAs) based on CMOS technology (CMOS-MEAs) can simultaneously record extracellular spiking activity in neuronal cultures from 4096 closely spaced microelectrodes. This allows for a finer investigation of neuronal network activity compared to conventional MEAs with a few tens of electrodes. However, the sensing properties of these devices differ. To highlight this aspect, here we investigate and discuss the differences observed when quantifying spontaneous synchronized bursting events (SBEs) in datasets acquired with conventional MEAs and high-density MEAs from comparable hippocampal cultures. We found that datasets acquired with high-density MEAs exhibit collective dynamics similar to conventional arrays, but are characterized by a higher percentage of random spikes, i.e. spikes that are not part of a burst, most probably resulting from the larger recording capability. Additionally, the percentage of electrodes that record a burst is remarkably small on high-density MEAs compared to what can be observed on conventional MEAs and SBEs appear to be propagating in time across the electrode array, by involving shorter sequences of spikes per electrode. Overall, these results highlight a lower level of network synchronization involved in SBEs compared to what has been debated for several decades based on conventional MEA recordings from cell cultures.

Functional connectivity estimation over large networks at cellular resolution based on electrophysiological recordings and structural prior.

Despite many structural and functional aspects of the brain organization have been extensively studied in neuroscience, we are still far from a clear understanding of the intricate structure-function interactions occurring in the multi-layered brain architecture, where billions of different neurons are involved. Although structure and function can individually convey a large amount of information, only a combined study of these two aspects can probably shade light on how brain circuits develop and operate at the cellular scale. Here, we propose a novel approach for refining functional connectivity estimates within neuronal networks using the structural connectivity as prior. This is done at the mesoscale, dealing with thousands of neurons while reaching, at the microscale, an unprecedented cellular resolution. The High-Density Micro Electrode Array (HD-MEA) technology, combined with fluorescence microscopy, offers the unique opportunity to acquire structural and functional data from large neuronal cultures approaching the granularity of the single cell. In this work, an advanced method based on probabilistic directional features and heat propagation is introduced to estimate the structural connectivity from the fluorescence image while functional connectivity graphs are obtained from the cross-correlation analysis of the spiking activity. Structural and functional information are then integrated by reweighting the functional connectivity graph based on the structural prior. Results show that the resulting functional connectivity estimates are more coherent with the network topology, as compared to standard measures purely based on cross-correlations and spatio-temporal filters. We finally use the obtained results to gain some insights on which features of the functional activity are more relevant to characterize actual neuronal interactions.

Integration of microstructured scaffolds, neurons, and multielectrode arrays.

Recent progresses in neuroelectronics and lab-on-a-chip technologies are providing novel opportunities for neuroscience research and applications. However, the experimental performances of these novel devices are not only the result of the artificially implemented features, such as those resulting from advanced electrode materials, from electrode morphologies, or from the low noise levels of the front-end electronic circuits. Rather, these performances also strictly relay on the bioartificial interface established by neurons on these devices. Here, we focus on cell culture systems adapted to neuroelectronic devices that were developed for organizing and growing neural networks in two or three dimensions. These developments span the fields of biosensors, engineering, neuroscience, and novel nanostructures and materials. Additionally, they are at the origin of novel neuroartificial hybrid technologies that can be applied for the study of neuronal networks at unprecedented scales and for applications in neuroscience that use scaffolding micro-/nanostructures, neurons, and biomolecules for advanced neuroelectronic interfaces and novel cell culture systems.