MR. Estimator, a toolbox to determine intrinsic timescales from subsampled spiking activity.
Franz Paul Spitzner,Jonas Dehning,Jens Wilting,Annika Hagemann,Joao Pinheiro Neto,Johannes Zierenberg,Viola Priesemann +6 more
TLDR
The Python toolbox “MR. Estimator” is presented to reliably estimate the intrinsic timescale from electrophysiologal recordings of heavily subsampled systems to investigate a functional hierarchy across the primate cortex and quantifies a system’s dynamic working point.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.read more
Citations
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Self-organization toward criticality by synaptic plasticity
TL;DR: It is proposed that rules that are capable of bringing the network to criticality can be classified by how long the near-critical dynamics persists after their disabling, and the role of self-organization and criticality in computation is discussed.
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How critical is brain criticality?
Jordan O’Byrne,Karim Jerbi +1 more
TL;DR: Criticality is defined as the singular state of complex systems poised at the brink of a phase transition between order and randomness as discussed by the authors , i.e. the property of a process whose trajectory in phase space is sensitive to small differences in initial conditions.
Journal ArticleDOI
Assessing criticality in pre-seizure single-neuron activity of human epileptic cortex
Annika Hagemann,Jens Wilting,Bita Samimizad,Florian Mormann,Viola Priesemann,Viola Priesemann +5 more
TL;DR: In this article, the authors analyzed single-unit spike recordings from both the epileptogenic (focal) and the non-focal cortical hemispheres of 20 epilepsy patients and quantified the distance to instability in the framework of criticality.
Journal ArticleDOI
Embedding optimization reveals long-lasting history dependence in neural spiking activity.
TL;DR: A novel approach to quantify history dependence within the spiking of a single neuron, using the mutual information between the entire past and current spiking, which captures a footprint of information processing that is beyond time-lagged measures of temporal dependence.
Journal ArticleDOI
Tackling the subsampling problem to infer collective properties from limited data
TL;DR: In this paper , the authors give an overview of some issues arising from spatial subsampling and review approaches developed in recent years to tackle the subsamspling problem, and also outline what they believe are the main open challenges.
References
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Journal ArticleDOI
Characterizing spreading dynamics of subsampled systems with nonstationary external input.
Jorge de Heuvel,Jens Wilting,Moritz F. P. Becker,Moritz F. P. Becker,Viola Priesemann,Johannes Zierenberg +5 more
TL;DR: Analytically how to overcome the subsampling bias when estimating the propagation rate for systems with certain nonstationary external input is shown.
Posted Content
Everything you wish to know about correlations but are afraid to ask
TL;DR: The various definitions of time correlation functions are discussed, both in real and in Fourier space, and how to extract from them a characteristic time scale is explained.
Posted ContentDOI
Homeostatic plasticity and external input shape neural network dynamics
TL;DR: This work analyzes a model of spiking neurons in which the input strength, mediated by spike rate homeostasis, determines the characteristics of the dynamical state, and shows consistently that under increasing input, homeostatic plasticity generates distinct dynamic states, from bursting, to close-to-critical, reverberating and irregular states.
Posted Content
No evidence that epilepsy impacts criticality in pre-seizure single-neuron activity of human cortex
TL;DR: The results from both pre-seizure and seizure-free intervals suggest that despite epilepsy, human cortex operates in the stable, slightly subcritical regime, just like cortex of other healthy mammalians.