ArticleNeural computation2018
Methods for Assessment of Memory Reactivation.
Article in Neural computation, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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
7 citing papers in PubMed, 13 citations in OpenAlex.
- Hippocampal memory reactivation during sleep is correlated with specific cortical states of the retrosplenial and prefrontal cortices.Learning & memory (Cold Spring Harbor, N.Y.) · 2023Article
- How our understanding of memory replay evolves.Journal of neurophysiology · 2023Review
- Uncovering spatial representations from spatiotemporal patterns of rodent hippocampal field potentials.Cell reports methods · 2021Article
- Article
- Efficient Position Decoding Methods Based on Fluorescence Calcium Imaging in the Mouse Hippocampus.Neural computation · 2020Article
- On the methods for reactivation and replay analysis.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2020Review
- 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 at 1 institution in 2 countries.
Funding
Abstract
It has been suggested that reactivation of previously acquired experiences or stored information in declarative memories in the hippocampus and neocortex contributes to memory consolidation and learning. Understanding memory consolidation depends crucially on the development of robust statistical methods for assessing memory reactivation. To date, several statistical methods have seen established for assessing memory reactivation based on bursts of ensemble neural spike activity during offline states. Using population-decoding methods, we propose a new statistical metric, the weighted distance correlation, to assess hippocampal memory reactivation (i.e., spatial memory replay) during quiet wakefulness and slow-wave sleep. The new metric can be combined with an unsupervised population decoding analysis, which is invariant to latent state labeling and allows us to detect statistical dependency beyond linearity in memory traces. We validate the new metric using two rat hippocampal recordings in spatial navigation tasks. Our proposed analysis framework may have a broader impact on assessing memory reactivations in other brain regions under different behavioral tasks.
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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.