ArticleeLife2018
Real-time classification of experience-related ensemble spiking patterns for closed-loop applications.
Article in eLife, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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
16 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Systematic Review of Closed-Loop Feedback Techniques in Sleep Studies-Related Issues and Future Directions.Sensors (Basel, Switzerland) · 2020Pooled it
- Decoding Naturalistic Episodic Memory with Artificial Intelligence and Brain-Machine Interface.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Laminar organization of cellular microcircuits modulating human interictal epileptiform discharges.Nature neuroscience · 2026Article
- A State-Space Framework for Causal Detection of Hippocampal Ripple-Replay Events.IEEE transactions on bio-medical engineering · 2026Article
- Article
- How our understanding of memory replay evolves.Journal of neurophysiology · 2023Review
- Disrupting ripples: Methods, results, and caveats in closed-loop approaches in rodents.Journal of sleep research · 2022Review
- A consensus statement on detection of hippocampal sharp wave ripples and differentiation from other fast oscillations.Nature communications · 2022Review
- Uncovering spatial representations from spatiotemporal patterns of rodent hippocampal field potentials.Cell reports methods · 2021Article
- Improving scalability in systems neuroscience.Neuron · 2021Review
- Efficient Position Decoding Methods Based on Fluorescence Calcium Imaging in the Mouse Hippocampus.Neural computation · 2020Article
- Five Decades of Hippocampal Place Cells and EEG Rhythms in Behaving Rats.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2020Review
- The evolving view of replay and its functions in wake and sleep.Sleep advances : a journal of the Sleep Research Society · 2020Review
- Article
- Myopic control of neural dynamics.PLoS computational biology · 2019Article
- Real-Time Readout of Large-Scale Unsorted Neural Ensemble Place Codes.Cell reports · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Communication in neural circuits across the cortex is thought to be mediated by spontaneous temporally organized patterns of population activity lasting ~50 -200 ms. Closed-loop manipulations have the unique power to reveal direct and causal links between such patterns and their contribution to cognition. Current brain-computer interfaces, however, are not designed to interpret multi-neuronal spiking patterns at the millisecond timescale. To bridge this gap, we developed a system for classifying ensemble patterns in a closed-loop setting and demonstrated its application in the online identification of hippocampal neuronal replay sequences in the rat. Our system decodes multi-neuronal patterns at 10 ms resolution, identifies within 50 ms experience-related patterns with over 70% sensitivity and specificity, and classifies their content with 95% accuracy. This technology scales to high-count electrode arrays and will help to shed new light on the contribution of internally generated neural activity to coordinated neural assembly interactions and cognition.
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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.