ArticlePLoS computational biology2017
Electrical stimulus artifact cancellation and neural spike detection on large multi-electrode arrays.
Article in PLoS computational biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
23 citing papers in PubMed.
- logLIRA: a method for reliable suppression of electrical stimulation artifacts enabling short-latency neural response recovery.Journal of neural engineering · 2026Article
- Advances in large-scale electrophysiology with high-density microelectrode arrays.Lab on a chip · 2025Review
- Article
- Removing direct photocurrent artifacts in optogenetic connectivity mapping data via constrained matrix factorization.PLoS computational biology · 2024Article
- Spike sorting in the presence of stimulation artifacts: a dynamical control systems approach.Journal of neural engineering · 2024Article
- Single-pulse electrical stimulation artifact removal using the novel matching pursuit-based artifact reconstruction and removal method (MPARRM).Journal of neural engineering · 2023Article
- Inference of Electrical Stimulation Sensitivity from Recorded Activity of Primate Retinal Ganglion Cells.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023Article
- Focal electrical stimulation of human retinal ganglion cells for vision restoration.Journal of neural engineering · 2022Article
- An improved platform for cultured neuronal network electrophysiology: multichannel optogenetics integrated with MEAs.European biophysics journal : EBJ · 2022Article
- Tracking connectivity maps in human stem cell-derived neuronal networks by holographic optogenetics.Life science alliance · 2022Article
- From End to End: Gaining, Sorting, and Employing High-Density Neural Single Unit Recordings.Frontiers in neuroinformatics · 2022Review
- Spatially patterned bi-electrode epiretinal stimulation for axon avoidance at cellular resolution.Journal of neural engineering · 2021Article
- Uncovering biomarkers during therapeutic neuromodulation with PARRM: Period-based Artifact Reconstruction and Removal Method.Cell reports methods · 2021Article
- Automatic Identification of Axon Bundle Activation for Epiretinal Prosthesis.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2021Article
- Computational challenges and opportunities for a bi-directional artificial retina.Journal of neural engineering · 2020Article
- Signal recovery from stimulation artifacts in intracranial recordings with dictionary learning.Journal of neural engineering · 2020Article
- Optimal Multichannel Artifact Prediction and Removal for Neural Stimulation and Brain Machine Interfaces.Frontiers in neuroscience · 2020Article
- Stimulation and Artifact-Suppression Techniques for In Vitro High-Density Microelectrode Array Systems.IEEE transactions on bio-medical engineering · 2019Article
- Epiretinal stimulation with local returns enhances selectivity at cellular resolution.Journal of neural engineering · 2019Article
- Towards neural co-processors for the brain: combining decoding and encoding in brain-computer interfaces.Current opinion in neurobiology · 2019Review
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Simultaneous electrical stimulation and recording using multi-electrode arrays can provide a valuable technique for studying circuit connectivity and engineering neural interfaces. However, interpreting these measurements is challenging because the spike sorting process (identifying and segregating action potentials arising from different neurons) is greatly complicated by electrical stimulation artifacts across the array, which can exhibit complex and nonlinear waveforms, and overlap temporarily with evoked spikes. Here we develop a scalable algorithm based on a structured Gaussian Process model to estimate the artifact and identify evoked spikes. The effectiveness of our methods is demonstrated in both real and simulated 512-electrode recordings in the peripheral primate retina with single-electrode and several types of multi-electrode stimulation. We establish small error rates in the identification of evoked spikes, with a computational complexity that is compatible with real-time data analysis. This technology may be helpful in the design of future high-resolution sensory prostheses based on tailored stimulation (e.g., retinal prostheses), and for closed-loop neural stimulation at a much larger scale than currently possible.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.