Neuronale Netzwerke im Rampenlicht: Mit leuchtenden Proteinen zelluläre Aktivitätsmuster entschlüsseln

AbstractNeuronal networks in the spotlight: deciphering cellular activity patterns with fluorescent proteins.The brain’s astounding achievements regarding movement control and sensory processing are based on complex spatiotemporal activity patterns in the relevant neuronal networks. Our understanding of neuronal network activity is, however, still poor, not least because of the experimental difficulties to directly observe neural circuits at work in the living brain (in vivo). Over the last decade, new opportunities have emerged - especially utilizing 2-photon microscopy - to investigate neuronal networks in action. Central to this progress was the development of fluorescent proteins that change their emission depending on cell activity, enabling the visualization of dynamic activity patterns in local neuronal populations. Currently, genetically encoded calcium indicators, proteins which indicate neuronal activity based on action potential-evoked calcium influx, are becoming increasingly used. Long-term expression of these indicators allows repeated monitoring of the same neurons over weeks and months, such that stability and plasticity of their functional properties can be characterized. Furthermore, permanent indicator expression facilitates the correlation of cellular activity patterns and behavior in awake animals. Using examples from recent studies of information processing in mouse neocortex, we review in this article these fascinating new possibilities and discuss the great potential of fluorescent proteins to elucidate the mysteries of neural circuits.

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Neuronal networks in the spotlight

e-Neuroforum ◽

10.1007/s13295-013-0042-4 ◽

2013 ◽

Vol 19 (2) ◽

Author(s):

F. Helmchen ◽

M. Hübener

Keyword(s):

Neuronal Networks ◽

Neural Circuits ◽

Calcium Influx ◽

Fluorescent Proteins ◽

Activity Patterns ◽

Cell Activity ◽

Movement Control ◽

Dynamic Activity ◽

Two Photon Microscopy

AbstractThe brain’s astounding achievements regarding movement control and sensory processing are based on complex spatiotemporal activity patterns in the relevant neuronal networks. Our understanding of neuronal network activity is, however, still poor, not least because of the experimental difficulties in directly observing neural circuits at work in the living brain (in vivo). Over the last decade, new opportunities have emerged-especially utilizing two-photon microscopy-to investigate neuronal networks in action. Central to this progress was the development of fluorescent proteins that change their emission depending on cell activity, enabling the visualization of dynamic activity patterns in local neuronal populations. Currently, genetically encoded calcium indicators, proteins that indicate neuronal activity based on action potential-evoked calcium influx, are being increasingly used. Long-term expression of these indicators allows repeated monitoring of the same neurons over weeks and months, such that the stability and plasticity of their functional properties can be characterized. Furthermore, permanent indicator expression facilitates the correlation of cellular activity patterns and behavior in awake animals. Using examples from recent studies of information processing in the mouse neocortex, we review in this article these fascinating new possibilities and discuss the great potential of the fluorescent proteins to elucidate the mysteries of neural circuits.

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Inhibitory control in neuronal networks relies on the extracellular matrix integrity

Cellular and Molecular Life Sciences ◽

10.1007/s00018-021-03861-3 ◽

2021 ◽

Author(s):

Egor Dzyubenko ◽

Michael Fleischer ◽

Daniel Manrique-Castano ◽

Mina Borbor ◽

Christoph Kleinschnitz ◽

...

Keyword(s):

Extracellular Matrix ◽

Inhibitory Control ◽

Neuronal Networks ◽

Synaptic Strength ◽

Inhibitory Synapse ◽

Receptor Expression ◽

Network Activity ◽

Inhibitory Synapses ◽

Neuronal Network Activity ◽

Synapse Density

AbstractInhibitory control is essential for the regulation of neuronal network activity, where excitatory and inhibitory synapses can act synergistically, reciprocally, and antagonistically. Sustained excitation-inhibition (E-I) balance, therefore, relies on the orchestrated adjustment of excitatory and inhibitory synaptic strength. While growing evidence indicates that the brain’s extracellular matrix (ECM) is a crucial regulator of excitatory synapse plasticity, it remains unclear whether and how the ECM contributes to inhibitory control in neuronal networks. Here we studied the simultaneous changes in excitatory and inhibitory connectivity after ECM depletion. We demonstrate that the ECM supports the maintenance of E-I balance by retaining inhibitory connectivity. Quantification of synapses and super-resolution microscopy showed that depletion of the ECM in mature neuronal networks preferentially decreases the density of inhibitory synapses and the size of individual inhibitory postsynaptic scaffolds. The reduction of inhibitory synapse density is partially compensated by the homeostatically increasing synaptic strength via the reduction of presynaptic GABAB receptors, as indicated by patch-clamp measurements and GABAB receptor expression quantifications. However, both spiking and bursting activity in neuronal networks is increased after ECM depletion, as indicated by multi-electrode recordings. With computational modelling, we determined that ECM depletion reduces the inhibitory connectivity to an extent that the inhibitory synapse scaling does not fully compensate for the reduced inhibitory synapse density. Our results indicate that the brain’s ECM preserves the balanced state of neuronal networks by supporting inhibitory control via inhibitory synapse stabilization, which expands the current understanding of brain activity regulation. Graphic abstract

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Criticality, Connectivity, and Neural Disorder: A Multifaceted Approach to Neural Computation

Frontiers in Computational Neuroscience ◽

10.3389/fncom.2021.611183 ◽

2021 ◽

Vol 15 ◽

Author(s):

Kristine Heiney ◽

Ola Huse Ramstad ◽

Vegard Fiskum ◽

Nicholas Christiansen ◽

Axel Sandvig ◽

...

Keyword(s):

Neuronal Networks ◽

Experimental Studies ◽

Theoretical Models ◽

Network Activity ◽

Network Structures ◽

Dynamic Activity ◽

Broad Perspective ◽

Theoretical Approaches ◽

Experimental Findings ◽

Criticality Analysis

It has been hypothesized that the brain optimizes its capacity for computation by self-organizing to a critical point. The dynamical state of criticality is achieved by striking a balance such that activity can effectively spread through the network without overwhelming it and is commonly identified in neuronal networks by observing the behavior of cascades of network activity termed “neuronal avalanches.” The dynamic activity that occurs in neuronal networks is closely intertwined with how the elements of the network are connected and how they influence each other's functional activity. In this review, we highlight how studying criticality with a broad perspective that integrates concepts from physics, experimental and theoretical neuroscience, and computer science can provide a greater understanding of the mechanisms that drive networks to criticality and how their disruption may manifest in different disorders. First, integrating graph theory into experimental studies on criticality, as is becoming more common in theoretical and modeling studies, would provide insight into the kinds of network structures that support criticality in networks of biological neurons. Furthermore, plasticity mechanisms play a crucial role in shaping these neural structures, both in terms of homeostatic maintenance and learning. Both network structures and plasticity have been studied fairly extensively in theoretical models, but much work remains to bridge the gap between theoretical and experimental findings. Finally, information theoretical approaches can tie in more concrete evidence of a network's computational capabilities. Approaching neural dynamics with all these facets in mind has the potential to provide a greater understanding of what goes wrong in neural disorders. Criticality analysis therefore holds potential to identify disruptions to healthy dynamics, granted that robust methods and approaches are considered.

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Human neuronal networks on micro-electrode arrays are a highly robust tool to study disease-specific genotype-phenotype correlations in vitro

10.1101/2021.01.20.427439 ◽

2021 ◽

Author(s):

B. Mossink ◽

A.H.A. Verboven ◽

E.J.H. van Hugte ◽

T.M. Klein Gunnewiek ◽

G. Parodi ◽

...

Keyword(s):

Experimental Design ◽

Neuronal Network ◽

Neuronal Networks ◽

Network Activity ◽

Full Potential ◽

Electrode Arrays ◽

Neuronal Network Activity ◽

Micro Electrode Arrays ◽

Disease Specific

AbstractMicro-electrode arrays (MEAs) are increasingly used to characterize neuronal network activity of human induced pluripotent stem-cell (hiPSC)-derived neurons. Despite their gain in popularity, MEA recordings from hiPSC-derived neuronal networks are not always used to their full potential in respect to experimental design, execution and data analysis. Therefore, we benchmarked the robustness and sensitivity of MEA-derived neuronal activity patterns derived from ten healthy individual control lines. We provide recommendations on experimental design and analysis to achieve standardization. With such standardization, MEAs can be used as a reliable platform to distinguish (disease-specific) network phenotypes. In conclusion, we show that MEAs are a powerful and robust tool to uncover functional neuronal network phenotypes from hiPSC-derived neuronal networks, and provide an important resource to advance the hiPSC field towards the use of MEAs for disease-phenotyping and drug discovery.

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Emergence and fragmentation of the alpha-band driven by neuronal network dynamics

PLoS Computational Biology ◽

10.1371/journal.pcbi.1009639 ◽

2021 ◽

Vol 17 (12) ◽

pp. e1009639

Author(s):

Lou Zonca ◽

David Holcman

Keyword(s):

Neuronal Network ◽

Neuronal Networks ◽

Network Activity ◽

Neuronal Network Activity ◽

Up States ◽

Synaptic Noise ◽

Reciprocal Connections ◽

Neuronal Network Dynamics ◽

Thalamocortical Oscillations ◽

Synaptic Dynamics

Rhythmic neuronal network activity underlies brain oscillations. To investigate how connected neuronal networks contribute to the emergence of the α-band and to the regulation of Up and Down states, we study a model based on synaptic short-term depression-facilitation with afterhyperpolarization (AHP). We found that the α-band is generated by the network behavior near the attractor of the Up-state. Coupling inhibitory and excitatory networks by reciprocal connections leads to the emergence of a stable α-band during the Up states, as reflected in the spectrogram. To better characterize the emergence and stability of thalamocortical oscillations containing α and δ rhythms during anesthesia, we model the interaction of two excitatory networks with one inhibitory network, showing that this minimal topology underlies the generation of a persistent α-band in the neuronal voltage characterized by dominant Up over Down states. Finally, we show that the emergence of the α-band appears when external inputs are suppressed, while fragmentation occurs at small synaptic noise or with increasing inhibitory inputs. To conclude, α-oscillations could result from the synaptic dynamics of interacting excitatory neuronal networks with and without AHP, a principle that could apply to other rhythms.

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Extracellular matrix supports excitation-inhibition balance in neuronal networks by stabilizing inhibitory synapses

10.1101/2020.07.13.200113 ◽

2020 ◽

Author(s):

Egor Dzyubenko ◽

Michael Fleischer ◽

Daniel Manrique-Castano ◽

Mina Borbor ◽

Christoph Kleinschnitz ◽

...

Keyword(s):

Extracellular Matrix ◽

Neuronal Network ◽

Neuronal Plasticity ◽

Neuronal Networks ◽

Network Activity ◽

Inhibitory Synapses ◽

Neuronal Network Activity ◽

The Brain

AbstractMaintaining the balance between excitation and inhibition is essential for the appropriate control of neuronal network activity. Sustained excitation-inhibition (E-I) balance relies on the orchestrated adjustment of synaptic strength, neuronal activity and network circuitry. While growing evidence indicates that extracellular matrix (ECM) of the brain is a crucial regulator of neuronal excitability and synaptic plasticity, it remains unclear whether and how ECM contributes to neuronal circuit stability. Here we demonstrate that the integrity of ECM supports the maintenance of E-I balance by retaining inhibitory connectivity. Depletion of ECM in mature neuronal networks preferentially decreases the density of inhibitory synapses and the size of individual inhibitory postsynaptic scaffolds. After ECM depletion, inhibitory synapse strength homeostatically increases via the reduction of presynaptic GABAB receptors. However, the inhibitory connectivity reduces to an extent that inhibitory synapse scaling is no longer efficient in controlling neuronal network activity. Our results indicate that the brain ECM preserves the balanced network state by stabilizing inhibitory synapses.Significance statementThe question how the brain’s extracellular matrix (ECM) controls neuronal plasticity and network activity is key for an appropriate understanding of brain functioning. In this study, we demonstrate that ECM depletion much more strongly affects the integrity of inhibitory than excitatory synapses in vitro and in vivo. We revealed that by retaining inhibitory connectivity, ECM ensures the efficiency of inhibitory control over neuronal network activity. Our work significantly expands our current state of knowledge about the mechanisms of neuronal network activity regulation. Our findings are similarly relevant for researchers working on the physiological regulation of neuronal plasticity in vitro and in vivo and for researchers studying the remodeling of neuronal networks upon brain injury, where prominent ECM alterations occur.

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A novel approach to investigate neuronal network activity patterns affected by deep brain stimulation in rats

Journal of Psychiatric Research ◽

10.1016/j.jpsychires.2010.12.008 ◽

2011 ◽

Vol 45 (7) ◽

pp. 927-930 ◽

Cited By ~ 15

Author(s):

Julia Klein ◽

Maria L. Soto-Montenegro ◽

Javier Pascau ◽

Lydia Günther ◽

Andreas Kupsch ◽

...

Keyword(s):

Deep Brain Stimulation ◽

Neuronal Network ◽

Brain Stimulation ◽

Activity Patterns ◽

Network Activity ◽

Neuronal Network Activity ◽

Novel Approach ◽

Deep Brain

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Intracellular Ca2+ stores control in vivo neuronal hyperactivity in a mouse model of Alzheimer’s disease

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1714409115 ◽

2018 ◽

Vol 115 (6) ◽

pp. E1279-E1288 ◽

Cited By ~ 33

Author(s):

Chommanad Lerdkrai ◽

Nithi Asavapanumas ◽

Bianca Brawek ◽

Yury Kovalchuk ◽

Nima Mojtahedi ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cortical Neurons ◽

Healthy Aging ◽

Activity Patterns ◽

Network Activity ◽

Neuronal Network Activity ◽

Model Of Alzheimer’S Disease ◽

Intracellular Ca

Neuronal hyperactivity is the emerging functional hallmark of Alzheimer’s disease (AD) in both humans and different mouse models, mediating an impairment of memory and cognition. The mechanisms underlying neuronal hyperactivity remain, however, elusive. In vivo Ca2+ imaging of somatic, dendritic, and axonal activity patterns of cortical neurons revealed that both healthy aging and AD-related mutations augment neuronal hyperactivity. The AD-related enhancement occurred even without amyloid deposition and neuroinflammation, mainly due to presenilin-mediated dysfunction of intracellular Ca2+ stores in presynaptic boutons, likely causing more frequent activation of synaptic NMDA receptors. In mutant but not wild-type mice, store emptying reduced both the frequency and amplitude of presynaptic Ca2+ transients and, most importantly, normalized neuronal network activity. Postsynaptically, the store dysfunction was minor and largely restricted to hyperactive cells. These findings identify presynaptic Ca2+ stores as a key element controlling AD-related neuronal hyperactivity and as a target for disease-modifying treatments.

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meaRtools: an R Package for the Analysis of Neuronal Networks Recorded on Microelectrode Arrays

10.1101/242065 ◽

2018 ◽

Cited By ~ 1

Author(s):

Sahar Gelfman ◽

Quanli Wang ◽

Yi-Fan Lu ◽

Diana Hall ◽

Christopher D. Bostick ◽

...

Keyword(s):

Spike Train ◽

Neuronal Networks ◽

Microelectrode Arrays ◽

R Package ◽

Network Activity ◽

Neuronal Cultures ◽

Mixed Cell ◽

Spike Train Analysis ◽

Neuronal Network Activity

AbstractHere 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/.Author summaryCultured neuronal networks are widely used to study and characterize neuronal network activity. Among the many uses of neuronal cultures are the capabilities to evaluate neurotoxicity and the effects of pharmacological compounds on cellular physiology. Multi-well microelectrode arrays (MEAs) can collect high-throughput data from multiple neuronal cultures simultaneously, and thereby make possible hypotheses-driven inquiries into neurobiology and neuropharmacology. The analysis of MEA-derived information presents many computational challenges. High frequency data recorded simultaneously from hundreds of electrodes can be difficult to handle. The need to compare network activity across various drug treatments or genotypes recorded on the same plate from experiments lasting several weeks presents another challenge. These challenges inspired us to develop meaRtools; an MEA data analysis package that contains new methods to characterize network activity patterns, which are illustrated here using examples from a genetic mouse model of epilepsy. Among the highlights of meaRtools are novel algorithms designed to characterize neuronal activity dynamics and network properties such as bursting and synchronization, options to combine multiple recordings and use a robust statistical framework to draw appropriate statistical inferences, and finally data visualizations and plots. In summary, meaRtools provides a platform for the analyses of singular and longitudinal MEA experiments.

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

Toxicological Sciences ◽

10.1093/toxsci/kfaa136 ◽

2020 ◽

Vol 178 (1) ◽

pp. 71-87

Author(s):

Anke M Tukker ◽

Fiona M J Wijnolts ◽

Aart de Groot ◽

Remco H S Westerink

Keyword(s):

Microelectrode Array ◽

Activity Patterns ◽

Primary Cultures ◽

Induced Pluripotent Stem Cell ◽

Network Activity ◽

Neuronal Network Activity ◽

Cortical Cultures ◽

Life Threatening ◽

Induced Pluripotent

Abstract 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.

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