scholarly journals Energetic substrate availability regulates synchronous activity in an excitatory neural network

2018 ◽  
Author(s):  
David S. Tourigny ◽  
Muhammad Kaiser Abdul Karim ◽  
Rodrigo Echeveste ◽  
Mark R. N. Kotter ◽  
John S. O’Neill
Keyword(s):  
Neural Network ◽  
Primary Energy ◽  
Synaptic Function ◽  
Network Activity ◽  
Substrate Availability ◽  
Vesicle Cycling ◽  
Extracellular Glucose ◽  
Presynaptic Vesicle ◽  
Excitatory Neurotransmission ◽  
Lactate And Pyruvate

AbstractNeural networks are required to meet significant metabolic demands associated with performing sophisticated computational tasks in the brain. The necessity for efficient transmission of information imposes stringent constraints on the metabolic pathways that can be used for energy generation at the synapse, and thus low availability of energetic substrates can reduce the efficacy of synaptic function. Here we study the effects of energetic substrate availability on global neural network behavior and find that glucose alone can sustain excitatory neurotransmission required to generate high-frequency synchronous bursting that emerges in culture. In contrast, obligatory oxidative energetic substrates such as lactate and pyruvate are unable to substitute for glucose, indicating that processes involving glucose metabolism form the primary energy-generating pathways supporting coordinated network activity. Our experimental results are discussed in the context of the role that metabolism plays in supporting the performance of individual synapses, including the relative contributions from postsynaptic responses, astrocytes, and presynaptic vesicle cycling. We propose a simple computational model for our excitatory cultures that accurately captures the inability of metabolically compromised synapses to sustain synchronous bursting when extracellular glucose is depleted.

scholarly journals Altered network properties in C9ORF72 repeat expansion cortical neurons are due to synaptic dysfunction

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Emma M. Perkins ◽  
Karen Burr ◽  
Poulomi Banerjee ◽  
Arpan R. Mehta ◽  
Owen Dando ◽  
...  
Keyword(s):  
Synaptic Plasticity ◽  
Synaptic Vesicle ◽  
Cortical Neurons ◽  
Electrode Array ◽  
Repeat Expansion ◽  
Cortical Network ◽  
Synaptic Function ◽  
Network Activity ◽  
Cortical Function ◽  
Network Function

Abstract Background Physiological disturbances in cortical network excitability and plasticity are established and widespread in amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) patients, including those harbouring the C9ORF72 repeat expansion (C9ORF72RE) mutation – the most common genetic impairment causal to ALS and FTD. Noting that perturbations in cortical function are evidenced pre-symptomatically, and that the cortex is associated with widespread pathology, cortical dysfunction is thought to be an early driver of neurodegenerative disease progression. However, our understanding of how altered network function manifests at the cellular and molecular level is not clear. Methods To address this we have generated cortical neurons from patient-derived iPSCs harbouring C9ORF72RE mutations, as well as from their isogenic expansion-corrected controls. We have established a model of network activity in these neurons using multi-electrode array electrophysiology. We have then mechanistically examined the physiological processes underpinning network dysfunction using a combination of patch-clamp electrophysiology, immunocytochemistry, pharmacology and transcriptomic profiling. Results We find that C9ORF72RE causes elevated network burst activity, associated with enhanced synaptic input, yet lower burst duration, attributable to impaired pre-synaptic vesicle dynamics. We also show that the C9ORF72RE is associated with impaired synaptic plasticity. Moreover, RNA-seq analysis revealed dysregulated molecular pathways impacting on synaptic function. All molecular, cellular and network deficits are rescued by CRISPR/Cas9 correction of C9ORF72RE. Our study provides a mechanistic view of the early dysregulated processes that underpin cortical network dysfunction in ALS-FTD. Conclusion These findings suggest synaptic pathophysiology is widespread in ALS-FTD and has an early and fundamental role in driving altered network function that is thought to contribute to neurodegenerative processes in these patients. The overall importance is the identification of previously unidentified defects in pre and postsynaptic compartments affecting synaptic plasticity, synaptic vesicle stores, and network propagation, which directly impact upon cortical function.

Neural network activity and neurological soft signs in healthy adults

2015 ◽  
Vol 278 ◽  
pp. 514-519 ◽  
Author(s):  
Philipp A. Thomann ◽  
Dusan Hirjak ◽  
Katharina M. Kubera ◽  
Bram Stieltjes ◽  
Robert C. Wolf
Keyword(s):  
Neural Network ◽  
Healthy Adults ◽  
Network Activity ◽  
Neurological Soft Signs

scholarly journals Forecasting Primary Energy Requirements of Territories by Autoregressive Integrated Moving Average and Backpropagation Neural Network Models

2019 ◽  
Vol 2019 ◽  
pp. 1-14
Author(s):  
Ning-Kang Pan ◽  
Chunwan Lv
Keyword(s):  
Neural Network ◽  
Policy Making ◽  
Energy Requirement ◽  
Moving Average ◽  
Network Models ◽  
Primary Energy ◽  
Backpropagation Neural Network ◽  
Neural Network Models ◽  
Autoregressive Integrated Moving Average ◽  
Primary Energy Requirement

Forecasting energy data, especially the primary energy requirement, is the key part of policy-making. For those territories of different developing types, seeking a knowledge-based and dependable forecasting model is an essential prerequisite for the prosperous development of policy-making. In this paper, both autoregressive integrated moving average and backpropagation neural network models which have been proved to be very efficient in forecasting are applied to the forecasts of the primary energy consumption of three different developing types of territories. It is shown that the average relative errors between the actual data and simulated value are from 4.5% to 5.9% by the autoregressive integrated moving average and from 0.04% to 0.47% by the backpropagation neural network. Specially, this research shows that the backpropagation neural network model presents a better prediction of primary energy requirement when considering gross domestic product, population, and the particular values as predictors. Furthermore, we indicate that the single-input backpropagation neural network model can still work when the particular values have contributed most to the energy consumption.

Beta and gamma synchronous oscillations in neural network activity in mice-induced by food deprivation

2019 ◽  
Vol 709 ◽  
pp. 134398
Author(s):  
Nifareeda Samerphob ◽  
Acharaporn Issuriya ◽  
Dania Cheaha ◽  
Surapong Chatpun ◽  
Ole Jensen ◽  
...  
Keyword(s):  
Neural Network ◽  
Food Deprivation ◽  
Network Activity ◽  
Synchronous Oscillations

Distribution of VTA Glutamate and Dopamine Terminals, and their Significance in CA1 Neural Network Activity

Neuroscience ◽  
2020 ◽  
Vol 446 ◽  
pp. 171-198 ◽  
Author(s):  
Philip A. Adeniyi ◽  
Amita Shrestha ◽  
Olalekan M. Ogundele
Keyword(s):  
Neural Network ◽  
Network Activity

scholarly journals L-type voltage-gated calcium channel regulation of in vitro human cortical neuronal networks

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
William Plumbly ◽  
Nick Brandon ◽  
Tarek Z. Deeb ◽  
Jeremy Hall ◽  
Adrian J. Harwood
Keyword(s):  
Calcium Channel ◽  
Neuronal Networks ◽  
Gene Mutations ◽  
Synaptic Function ◽  
Neuronal Firing ◽  
Network Activity ◽  
Electrode Arrays ◽  
Voltage Gated ◽  
Voltage Gated Calcium Channel

Abstract The combination of in vitro multi-electrode arrays (MEAs) and the neuronal differentiation of stem cells offers the capability to study human neuronal networks from patient or engineered human cell lines. Here, we use MEA-based assays to probe synaptic function and network interactions of hiPSC-derived neurons. Neuronal network behaviour first emerges at approximately 30 days of culture and is driven by glutamate neurotransmission. Over a further 30 days, inhibitory GABAergic signalling shapes network behaviour into a synchronous regular pattern of burst firing activity and low activity periods. Gene mutations in L-type voltage gated calcium channel subunit genes are strongly implicated as genetic risk factors for the development of schizophrenia and bipolar disorder. We find that, although basal neuronal firing rate is unaffected, there is a dose-dependent effect of L-type voltage gated calcium channel inhibitors on synchronous firing patterns of our hiPSC-derived neural networks. This demonstrates that MEA assays have sufficient sensitivity to detect changes in patterns of neuronal interaction that may arise from hypo-function of psychiatric risk genes. Our study highlights the utility of in vitro MEA based platforms for the study of hiPSC neural network activity and their potential use in novel compound screening.

Bursting as a source for predictability in biological neural network activity

1997 ◽  
Vol 110 (3-4) ◽  
pp. 323-331 ◽  
Author(s):  
L. Menendez de la Prida ◽  
N. Stollenwerk ◽  
J.V. Sanchez-Andres
Keyword(s):  
Neural Network ◽  
Network Activity ◽  
Biological Neural Network

Respiratory Neural Network: Activity and Connectivity

2017 ◽  
pp. 227-242
Author(s):  
Laurence Mangin ◽  
Maurice Courbage
Keyword(s):  
Neural Network ◽  
Network Activity

scholarly journals A Metabolic Mechanism for Anaesthetic Suppression of Cortical Synaptic Function in Mouse Brain Slices—A Pilot Investigation

2020 ◽  
Vol 21 (13) ◽  
pp. 4703
Author(s):  
Logan J. Voss ◽  
Jamie W. Sleigh
Keyword(s):  
Brain Slices ◽  
Inhibitory Effect ◽  
Temporal Sequence ◽  
Synaptic Function ◽  
Network Activity ◽  
Tissue Oxygen ◽  
Pilot Investigation ◽  
Metabolic Mechanism ◽  
Mitochondrial Complex I Inhibitor ◽  
Measurable Change

Regulation of synaptically located ionotropic receptors is thought to be the main mechanism by which anaesthetics cause unconsciousness. An alternative explanation, which has received much less attention, is that of primary anaesthetic disruption of brain metabolism via suppression of mitochondrial proteins. In this pilot study in mouse cortical slices, we investigated the effect of disrupting cellular metabolism on tissue oxygen handling and cortical population seizure-like event (SLE) activity, using the mitochondrial complex I inhibitor rotenone, and compared this to the effects of the general anaesthetics sevoflurane, propofol and ketamine. Rotenone caused an increase in tissue oxygen (98 mmHg to 157 mmHg (p < 0.01)) before any measurable change in SLE activity. Thereafter, tissue oxygen continued to increase and was accompanied by a significant and prolonged reduction in SLE root mean square (RMS) activity (baseline RMS of 1.7 to 0.7 µV, p < 0.001) and SLE frequency (baseline 4.2 to 0.4 events/min, p = 0.001). This temporal sequence of effects was replicated by all three anaesthetic drugs. In conclusion, anaesthetics with differing synaptic receptor mechanisms all effect changes in tissue oxygen handling and cortical network activity, consistent with a common inhibitory effect on mitochondrial function. The temporal sequence suggests that the observed synaptic depression—as seen in anaesthesia—may be secondary to a reduction in cellular metabolic capacity.

A multi-laboratory evaluation of microelectrode array-based measurements of neural network activity for acute neurotoxicity testing

2017 ◽  
Vol 60 ◽  
pp. 280-292 ◽  
Author(s):  
Andrea Vassallo ◽  
Michela Chiappalone ◽  
Ricardo De Camargos Lopes ◽  
Bibiana Scelfo ◽  
Antonio Novellino ◽  
...  
Keyword(s):  
Neural Network ◽  
Microelectrode Array ◽  
Network Activity ◽  
Laboratory Evaluation ◽  
Acute Neurotoxicity
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