ArticlePloS one2021
MR. Estimator, a toolbox to determine intrinsic timescales from subsampled spiking activity.
Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Recovery from disorders of consciousness: Lesions and GABAergic modulation in a biologically inspired spiking neural network.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Neural timescales from a computational perspective.Nature neuroscience · 2026Review
- Hippocampal criticality tracks cognitive demand and shifts with memory impairment.Communications biology · 2026Article
- Detecting existence of a hidden mediator between a pair of individual time series.Scientific reports · 2025Article
- Sleep restores an optimal computational regime in cortical networks.Nature neuroscience · 2024Article
- Microscale Neuronal Activity Collectively Drives Chaotic and Inflexible Dynamics at the Macroscale in Seizures.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023Article
- Toward a Unified Analysis of the Brain Criticality Hypothesis: Reviewing Several Available Tools.Frontiers in neural circuits · 2022Review
- Addressing skepticism of the critical brain hypothesis.Frontiers in computational neuroscience · 2022Review
- Quasicriticality explains variability of human neural dynamics across life span.Frontiers in computational neuroscience · 2022Article
- Embedding optimization reveals long-lasting history dependence in neural spiking activity.PLoS computational biology · 2021Article
- Assessing criticality in pre-seizure single-neuron activity of human epileptic cortex.PLoS computational biology · 2021Article
Corrections and comments
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Authors and funding
7 authors.
Funding
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Abstract
Here we present our Python toolbox "MR. Estimator" to reliably estimate the intrinsic timescale from electrophysiologal recordings of heavily subsampled systems. Originally intended for the analysis of time series from neuronal spiking activity, our toolbox is applicable to a wide range of systems where subsampling-the difficulty to observe the whole system in full detail-limits our capability to record. Applications range from epidemic spreading to any system that can be represented by an autoregressive process. In the context of neuroscience, the intrinsic timescale can be thought of as the duration over which any perturbation reverberates within the network; it has been used as a key observable to investigate a functional hierarchy across the primate cortex and serves as a measure of working memory. It is also a proxy for the distance to criticality and quantifies a system's dynamic working point.
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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.