ArticleFrontiers in neural circuits2012
High-density microelectrode array recordings and real-time spike sorting for closed-loop experiments: an emerging technology to study neural plasticity.
Article in Frontiers in neural circuits, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.
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Who cites it
41 citing papers in PubMed.
- Advances in large-scale electrophysiology with high-density microelectrode arrays.Lab on a chip · 2025Review
- Spontaneous Dynamics Predict the Effects of Targeted Intervention in Hippocampal Neuronal Cultures.bioRxiv : the preprint server for biology · 2025Article
- PseudoSorter: A self-supervised spike sorting approach applied to reveal Tau-induced reductions in neuronal activity.Science advances · 2025Article
- RT-Sort: An action potential propagation-based algorithm for real time spike detection and sorting with millisecond latencies.PloS one · 2024Article
- Identifying properties of pattern completion neurons in a computational model of the visual cortex.PLoS computational biology · 2023Article
- Linking cortex and contraction-Integrating models along the corticomuscular pathway.Frontiers in physiology · 2023Article
- Neural probe system for behavioral neuropharmacology by bi-directional wireless drug delivery and electrophysiology in socially interacting mice.Nature communications · 2022Article
- Fascicle localisation within peripheral nerves through evoked activity recordings: A comparison between electrical impedance tomography and multi-electrode arrays.Journal of neuroscience methods · 2021Article
- Toward Closed-Loop Electrical Stimulation of Neuronal Systems: A Review.Bioelectricity · 2020Review
- An Accurate and Robust Method for Spike Sorting Based on Convolutional Neural Networks.Brain sciences · 2020Article
- Computing on actin bundles network.Scientific reports · 2019Article
- Brain Organoids-A Bottom-Up Approach for Studying Human Neurodevelopment.Bioengineering (Basel, Switzerland) · 2019Review
- High-Density Electrical Recording and Impedance Imaging With a Multi-Modal CMOS Multi-Electrode Array Chip.Frontiers in neuroscience · 2019Article
- Optimal Electrode Size for Multi-Scale Extracellular-Potential Recording From Neuronal Assemblies.Frontiers in neuroscience · 2019Article
- RTHybrid: A Standardized and Open-Source Real-Time Software Model Library for Experimental Neuroscience.Frontiers in neuroinformatics · 2019Article
- Automatic spike sorting for high-density microelectrode arrays.Journal of neurophysiology · 2018Article
- Understanding Cerebellum Granular Layer Network Computations through Mathematical Reconstructions of Evoked Local Field Potentials.Annals of neurosciences · 2018Article
- Article
- Electrical stimulus artifact cancellation and neural spike detection on large multi-electrode arrays.PLoS computational biology · 2017Article
- Gap junctional signaling in pattern regulation: Physiological network connectivity instructs growth and form.Developmental neurobiology · 2017Review
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7 authors.
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Abstract
Understanding plasticity of neural networks is a key to comprehending their development and function. A powerful technique to study neural plasticity includes recording and control of pre- and post-synaptic neural activity, e.g., by using simultaneous intracellular recording and stimulation of several neurons. Intracellular recording is, however, a demanding technique and has its limitations in that only a small number of neurons can be stimulated and recorded from at the same time. Extracellular techniques offer the possibility to simultaneously record from larger numbers of neurons with relative ease, at the expenses of increased efforts to sort out single neuronal activities from the recorded mixture, which is a time consuming and error prone step, referred to as spike sorting. In this mini-review, we describe recent technological developments in two separate fields, namely CMOS-based high-density microelectrode arrays, which also allow for extracellular stimulation of neurons, and real-time spike sorting. We argue that these techniques, when combined, will provide a powerful tool to study plasticity in neural networks consisting of several thousand neurons in vitro.
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