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

Neurotoxicity and the accumulation of extracellular amyloid-beta1-42 (A\u3b2) 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 A\u3b2-neurotoxicity. We also demonstrate the potential of this in vitro model to test a plausible hypothesis underlying the A\u3b2-neurotoxicity and to assay potential therapeutic approaches. Specifically, by quantifying N-methyl D-aspartate (NMDA) concentration-dependent effects in comparison with low-concentration allogenic-A\u3b2, we confirm the role of extrasynaptic-NMDA receptors activation that may contribute to A\u3b2-neurotoxicity. Finally, we assess the potential rescue of neural stem cells (NSCs) and of two pharmacotherapies, memantine and saffron, for reversing A\u3b2-neurotoxicity and rescuing network-wide firing

From dynamics to links: a sparse reconstruction of the topology of a neural network

One major challenge in neuroscience is the identification of interrelations between signals reflecting neural activity and how information processing occurs in the neural circuits. At the cellular and molecular level, mechanisms of signal transduction have been studied intensively and a better knowledge and understanding of some basic processes of information handling by neurons has been achieved. In contrast, little is known about the organization and function of complex neuronal networks. Experimental methods are now available to simultaneously monitor electrical activity of a large number of neurons in real time. Then, the qualitative and quantitative analysis of the spiking activity of individual neurons is a very valuable tool for the study of the dynamics and architecture of the neural networks. Such activity is not due to the sole intrinsic properties of the individual neural cells but it is mostly the consequence of the direct influence of other neurons. The deduction of the effective connectivity between neurons, whose experimental spike trains are observed, is of crucial importance in neuroscience: first for the correct interpretation of the electro-physiological activity of the involved neurons and neural networks, and, for correctly relating the electrophysiological activity to the functional tasks accomplished by the network. In this work, we propose a novel method for the identification of connectivity of neural networks using recorded voltages. Our approach is based on the assumption that the network has a topology with sparse connections. After a brief description of our method, we will report the performances and compare it to the cross-correlation computed on the spike trains, which represents a gold standard method in the field

Large-scale, high-resolution electrophysiological imaging of field potentials in brain slices with microelectronic multielectrode arrays

Multielectrode arrays (MEAs) are extensively used for electrophysiological studies on brain slices, but the spatial resolution and field of recording of conventional arrays are limited by the low number of electrodes available. Here, we present a large-scale array recording simultaneously from 4096 electrodes used to study propagating spontaneous and evoked network activity in acute murine cortico-hippocampal brain slices at unprecedented spatial and temporal resolution. We demonstrate that multiple chemically induced epileptiform episodes in the mouse cortex and hippocampus can be classified according to their spatio-temporal dynamics. Additionally, the large-scale and high-density features of our recording system enable the topological localization and quantification of the effects of antiepileptic drugs in local neuronal microcircuits, based on the distinct field potential propagation patterns. This novel high-resolution approach paves the way to detailed electrophysiological studies in brain circuits spanning spatial scales from single neurons up to the entire slice network

Fast wide-volume functional imaging of engineered in vitro brain tissues

The need for in vitro models that mimic the human brain to replace animal testing and allow high-throughput screening has driven scientists to develop new tools that reproduce tissue-like features on a chip. Three-dimensional (3D) in vitro cultures are emerging as an unmatched platform that preserves the complexity of cell-to-cell connections within a tissue, improves cell survival, and boosts neuronal differentiation. In this context, new and flexible imaging approaches are required to monitor the functional states of 3D networks. Herein, we propose an experimental model based on 3D neuronal networks in an alginate hydrogel, a tunable wide-volume imaging approach, and an efficient denoising algorithm to resolve, down to single cell resolution, the 3D activity of hundreds of neurons expressing the calcium sensor GCaMP6s. Furthermore, we implemented a 3D co-culture system mimicking the contiguous interfaces of distinct brain tissues such as the cortical-hippocampal interface. The analysis of the network activity of single and layered neuronal co-cultures revealed cell-type-specific activities and an organization of neuronal subpopulations that changed in the two culture configurations. Overall, our experimental platform represents a simple, powerful and cost-effective platform for developing and monitoring living 3D layered brain tissue on chip structures with high resolution and high throughput

Tonic activation of GABA-B receptors reduces release probability at inhibitory connections in the cerebellar glomerulus

Mapelli L, Rossi P, Nieus T, D'Angelo E. Tonic activation of GABA(B) receptors reduces release probability at inhibitory connections in the cerebellar glomerulus. J Neurophysiol 101: 3089-3099, 2009. First published April 1, 2009; doi:10.1152/jn.91190.2008. In the cerebellum, granule cells are inhibited by Golgi cells through GABAergic synapses generating complex responses involving both phasic neurotransmitter release and the establishment of ambient gamma-aminobutyric acid (GABA) levels. Although at this synapse the mechanisms of postsynaptic integration have been clarified to a considerable extent, the mechanisms of neurotransmitter release remained largely unknown. Here we have investigated the quantal properties of release during repetitive neurotransmission, revealing that tonic GABA(B) receptor activation by ambient GABA regulates release probability. Blocking GABA(B) receptors with CGP55845 enhanced the first inhibitory postsynaptic current (IPSC) and short-term depression in a train while reducing trial-to-trial variability and failures. The changes caused by CGP55845 were similar to those caused by increasing extracellular Ca2+ concentration, in agreement with a presynaptic GABA(B) receptor modulation of release probability. However, the slow tail following IPSC peak demonstrated a remarkable temporal summation and was not modified by CGP55845 or extracellular Ca2+ increase. This result shows that tonic activation of presynaptic GABA(B) receptors by ambient GABA selectively regulates the onset of inhibition bearing potential consequences for the dynamic regulation of signal transmission through the mossy fibergranule cell pathway of the cerebellum

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

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. Singlecell 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

Dominant β-catenin mutations cause intellectual disability with recognizable syndromic features

The recent identification of multiple dominant mutations in the gene encoding β-catenin in both humans and mice has enabled exploration of the molecular and cellular basis of β-catenin function in cognitive impairment. In humans, β-catenin mutations that cause a spectrum of neurodevelopmental disorders have been identified. We identified de novo β-catenin mutations in patients with intellectual disability, carefully characterized their phenotypes, and were able to define a recognizable intellectual disability syndrome. In parallel, characterization of a chemically mutagenized mouse line that displays features similar to those of human patients with β-catenin mutations enabled us to investigate the consequences of β-catenin dysfunction through development and into adulthood. The mouse mutant, designated batface (Bfc), carries a Thr653Lys substitution in the C-terminal armadillo repeat of β-catenin and displayed a reduced affinity for membrane-associated cadherins. In association with this decreased cadherin interaction, we found that the mutation results in decreased intrahemispheric connections, with deficits in dendritic branching, long-term potentiation, and cognitive function. Our study provides in vivo evidence that dominant mutations in β-catenin underlie losses in its adhesion-related functions, which leads to severe consequences, including intellectual disability, childhood hypotonia, progressive spasticity of lower limbs, and abnormal craniofacial features in adult

Evaluation of the Performance of Information Theory-Based Methods and Cross-Correlation to Estimate the Functional Connectivity in Cortical Networks

Functional connectivity of in vitro neuronal networks was estimated by applying different statistical algorithms on data collected by Micro-Electrode Arrays (MEAs). First we tested these “connectivity methods” on neuronal network models at an increasing level of complexity and evaluated the performance in terms of ROC (Receiver Operating Characteristic) and PPC (Positive Precision Curve), a new defined complementary method specifically developed for functional links identification. Then, the algorithms better estimated the actual connectivity of the network models, were used to extract functional connectivity from cultured cortical networks coupled to MEAs. Among the proposed approaches, Transfer Entropy and Joint-Entropy showed the best results suggesting those methods as good candidates to extract functional links in actual neuronal networks from multi-site recordings

Loss of Gnas Imprinting Differentially Affects REM/NREM Sleep and Cognition in Mice

It has been suggested that imprinted genes are important in the regulation of sleep. However, the fundamental question of whether genomic imprinting has a role in sleep has remained elusive up to now. In this work we show that REM and NREM sleep states are differentially modulated by the maternally expressed imprinted gene Gnas. In particular, in mice with loss of imprinting of Gnas, NREM and complex cognitive processes are enhanced while REM and REM–linked behaviors are inhibited. This is the first demonstration that a specific overexpression of an imprinted gene affects sleep states and related complex behavioral traits. Furthermore, in parallel to the Gnas overexpression, we have observed an overexpression of Ucp1 in interscapular brown adipose tissue (BAT) and a significant increase in thermoregulation that may account for the REM/NREM sleep phenotypes. We conclude that there must be significant evolutionary advantages in the monoallelic expression of Gnas for REM sleep and for the consolidation of REM–dependent memories. Conversely, biallelic expression of Gnas reinforces slow wave activity in NREM sleep, and this results in a reduction of uncertainty in temporal decision-making processes

Emergent Functional Properties of Neuronal Networks with Controlled Topology

The interplay between anatomical connectivity and dynamics in neural networks plays a key role in the functional properties of the brain and in the associated connectivity changes induced by neural diseases. However, a detailed experimental investigation of this interplay at both cellular and population scales in the living brain is limited by accessibility. Alternatively, to investigate the basic operational principles with morphological, electrophysiological and computational methods, the activity emerging from large in vitro networks of primary neurons organized with imposed topologies can be studied. Here, we validated the use of a new bio-printing approach, which effectively maintains the topology of hippocampal cultures in vitro and investigated, by patch-clamp and MEA electrophysiology, the emerging functional properties of these grid-confined networks. In spite of differences in the organization of physical connectivity, our bio-patterned grid networks retained the key properties of synaptic transmission, short-term plasticity and overall network activity with respect to random networks. Interestingly, the imposed grid topology resulted in a reinforcement of functional connections along orthogonal directions, shorter connectivity links and a greatly increased spiking probability in response to focal stimulation. These results clearly demonstrate that reliable functional studies can nowadays be performed on large neuronal networks in the presence of sustained changes in the physical network connectivity