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.
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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.
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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.
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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
Control of criticality and computation in spiking neuromorphic networks with plasticity
Benjamin Cramer,David Stöckel,Markus Kreft,Michael Wibral,Johannes Schemmel,K. Meier,Viola Priesemann,Viola Priesemann +7 more
TL;DR: In this article, the authors demonstrate a relation between criticality, task-performance and information theoretic fingerprint in a spiking neuromorphic network with synaptic plasticity, and provide an understanding of how the collective network state should be tuned to task requirement.
Journal ArticleDOI
Homeostatic Plasticity and External Input Shape Neural Network Dynamics
TL;DR: In this article, the authors found that differences in collective behavior between isolated neuron networks and the cortex of mammalian brains can be attributed to the strength of external inputs, which could open a path for creating more cortical-like behavior in neuronal networks cultured in a dish.
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Between Perfectly Critical and Fully Irregular: A Reverberating Model Captures and Predicts Cortical Spike Propagation.
TL;DR: This approach enables us to predict yet unknown properties from very short recordings and for every circuit individually, including responses to minimal perturbations, intrinsic network timescales, and the strength of external input compared to recurrent activation, informing about the underlying coding principles for each circuit, area, state and task.
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Distinct Structure of Cortical Population Activity on Fast and Infraslow Timescales.
TL;DR: frequency domain analyses are used to study the structure of individual neurons’ spiking activity and its coupling to local population rate and to arousal level across 0.01–100 Hz frequency range, extending the understanding of infraslow cortical activity beyond the mesoscale resolution of fMRI.
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Operating in a Reverberating Regime Enables Rapid Tuning of Network States to Task Requirements.
Jens Wilting,Jonas Dehning,Joao Pinheiro Neto,Lucas Rudelt,Michael Wibral,Johannes Zierenberg,Johannes Zierenberg,Viola Priesemann,Viola Priesemann +8 more
TL;DR: It is argued that this task-dependent tuning of the network, which is called “dynamic adaptive computation,” presents a central organization principle of cortical networks and discusses first experimental evidence.