ArticleJournal of neuroscience methods2020
Adaptive spike-artifact removal from local field potentials uncovers prominent beta and gamma band neuronal synchronization.
Article in Journal of neuroscience methods, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 36 citations in OpenAlex.
- KIASORT: Knowledge-Integrated Automated Spike Sorting for Geometry-Free Neuron Tracking.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026Article
- Prefrontal cortex interneurons and their contributions to attention, working memory, and adaptive behavior.Progress in neurobiology · 2026Review
- High-frequency bursts facilitate fast communication for human spatial attention.Nature neuroscience · 2026Article
- Theta phase precession supports memory formation and retrieval of naturalistic experience in humans.Nature human behaviour · 2024Article
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- Subthalamic nucleus synchronization between beta band local field potential and single-unit activity in Parkinson's disease.Physiological reports · 2024Article
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- Serotonergic modulation of local network processing in V1 mirrors previously reported signatures of local network modulation by spatial attention.The European journal of neuroscience · 2023Article
- Oscillations without cortex: Working memory modulates brainwaves in the endbrain of crows.Progress in neurobiology · 2022Article
- A consensus statement on detection of hippocampal sharp wave ripples and differentiation from other fast oscillations.Nature communications · 2022Review
- ABOT: an open-source online benchmarking tool for machine learning-based artefact detection and removal methods from neuronal signals.Brain informatics · 2022Article
- Spontaneous Spiking Is Governed by Broadband Fluctuations.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2022Article
- Neurons detect cognitive boundaries to structure episodic memories in humans.Nature neuroscience · 2022Article
- SANTIA: a Matlab-based open-source toolbox for artifact detection and removal from extracellular neuronal signals.Brain informatics · 2021Article
- Article
- Measuring Synchronization between Spikes and Local Field Potential Based on the Kullback-Leibler Divergence.Computational intelligence and neuroscience · 2021Article
- Phase of firing coding of learning variables across the fronto-striatal network during feature-based learning.Nature communications · 2020Article
- Fast spiking interneuron activity in primate striatum tracks learning of attention cues.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Mechanisms of Network Interactions for Flexible Cortico-Basal Ganglia-Mediated Action Control.eNeuroArticle
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Authors and funding
3 authors at 3 institutions in 3 countries.
Funding
Abstract
backgroundMany neurons synchronize their action potentials to the phase of local field potential (LFP) fluctuations in one or more frequency bands. Analyzing this spike-to-LFP synchronization is challenging, however, when neural spikes and LFP are generated in the same local circuit, because the spike's action potential waveform leak into the LFP and distort phase synchrony estimates. Existing approaches to address this spike bleed-through artifact relied on removing the average action potential waveforms of neurons, but this leaves artifacts in the LFP and distorts synchrony estimates. NEW
methodWe describe a spike-removal method that surpasses these limitations by decomposing individual action potentials into their frequency components before their removal from the LFP. The adaptively estimated frequency components allow for variable spread, strength and temporal variation of the spike artifact.
resultsThis adaptive approach effectively removes spike bleed-through artifacts in synthetic data with known ground truth, and in single neuron and LFP recordings in nonhuman primate striatum. For a large population of neurons with both narrow and broad action potential waveforms, the use of adaptive artifact removal uncovered 20-35 Hz beta and 35-45 Hz gamma band spike-LFP synchronization that would have remained contaminated otherwise. COMPARISON WITH EXISTING
methodsWe demonstrate that adaptive spike-artifact removal cleans LFP data that remained contaminated when applying existing Bayesian and non-Bayesian methods of average spike-artifact removal.
conclusionsApplying adaptive spike-removal from field potentials allows to estimate the phase at which neurons synchronize and the consistency of their phase-locked firing for both beta and low gamma frequencies. These metrics may prove essential to understand cell-to-circuit neuronal interactions in multiple brain systems.
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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.