ArticlePloS one2014
Large-scale, high-resolution multielectrode-array recording depicts functional network differences of cortical and hippocampal cultures.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.
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Who cites it
35 citing papers in PubMed.
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- High-density multielectrode arrays bring cellular resolution to neuronal activity and network analyses of corticospinal motor neurons.Scientific reports · 2025Article
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- Astrocytes induce desynchronization and reduce predictability in neuron-astrocyte networks cultured on microelectrode arrays.Royal Society open science · 2024Article
- Investigating Communication Dynamics in Neuronal Network using 3D Gold Microelectrode Arrays.ACS nano · 2024Article
- Mind In Vitro Platforms: Versatile, Scalable, Robust, and Open Solutions to Interfacing with Living Neurons.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- The serotonergic psychedelic N,N-dipropyltryptamine alters information-processing dynamics in in vitro cortical neural circuits.Network neuroscience (Cambridge, Mass.) · 2024Article
- Decomposing past and future: Integrated information decomposition based on shared probability mass exclusions.PloS one · 2023Article
- Nanomaterial-based microelectrode arrays for in vitro bidirectional brain-computer interfaces: a review.Microsystems & nanoengineering · 2023Review
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- Inferring Excitatory and Inhibitory Connections in Neuronal Networks.Entropy (Basel, Switzerland) · 2021Article
- Partial information decomposition reveals that synergistic neural integration is greater downstream of recurrent information flow in organotypic cortical cultures.PLoS computational biology · 2021Article
- What Triggers the Interictal Epileptic Spike? A Multimodal Multiscale Analysis of the Dynamic of Synaptic and Non-synaptic Neuronal and Vascular Compartments Using Electrical and Optical Measurements.Frontiers in neurology · 2021Article
- Modeling the temporal network dynamics of neuronal cultures.PLoS computational biology · 2020Article
- Correlated activity favors synergistic processing in local cortical networks in vitro at synaptically relevant timescales.Network neuroscience (Cambridge, Mass.) · 2020Article
- Hopf Bifurcation in Mean Field Explains Critical Avalanches in Excitation-Inhibition Balanced Neuronal Networks: A Mechanism for Multiscale Variability.Frontiers in systems neuroscience · 2020Article
- Organotypic brain slice cultures to model neurodegenerative proteinopathies.Molecular neurodegeneration · 2019Review
Corrections and comments
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Authors and funding
9 authors.
Funding
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Abstract
Understanding the detailed circuitry of functioning neuronal networks is one of the major goals of neuroscience. Recent improvements in neuronal recording techniques have made it possible to record the spiking activity from hundreds of neurons simultaneously with sub-millisecond temporal resolution. Here we used a 512-channel multielectrode array system to record the activity from hundreds of neurons in organotypic cultures of cortico-hippocampal brain slices from mice. To probe the network structure, we employed a wavelet transform of the cross-correlogram to categorize the functional connectivity in different frequency ranges. With this method we directly compare, for the first time, in any preparation, the neuronal network structures of cortex and hippocampus, on the scale of hundreds of neurons, with sub-millisecond time resolution. Among the three frequency ranges that we investigated, the lower two frequency ranges (gamma (30-80 Hz) and beta (12-30 Hz) range) showed similar network structure between cortex and hippocampus, but there were many significant differences between these structures in the high frequency range (100-1000 Hz). The high frequency networks in cortex showed short tailed degree-distributions, shorter decay length of connectivity density, smaller clustering coefficients, and positive assortativity. Our results suggest that our method can characterize frequency dependent differences of network architecture from different brain regions. Crucially, because these differences between brain regions require millisecond temporal scales to be observed and characterized, these results underscore the importance of high temporal resolution recordings for the understanding of functional networks in neuronal systems.
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