An Information-Theoretic Framework to Measure the Dynamic Interaction Between Neural Spike Trains

  title={An Information-Theoretic Framework to Measure the Dynamic Interaction Between Neural Spike Trains},
  author={Gorana Mijatovic and Yuri Antonacci and Tatjana Lon{\vc}ar-Turukalo and Ludovico Minati and Luca Faes},
  journal={IEEE Transactions on Biomedical Engineering},
<italic>Objective:</italic> While understanding the interaction patterns among simultaneous recordings of spike trains from multiple neuronal units is a key topic in neuroscience, existing methods either do not consider the inherent point-process nature of spike trains or are based on parametric assumptions. This work presents an information-theoretic framework for the model-free, continuous-time estimation of both undirected (symmetric) and directed (Granger-causal) interactions between spike… 

Figures from this paper

Early lock-in of structured and specialised information flows during neural development
This work characterises the flow of information during the crucial periods of population bursts and finds that, during these bursts, nodes tend to undertake specialised computational roles as either transmitters, mediators, or receivers of information, with these roles tending to align with their average spike ordering.
Early lock-in of structured and specialised information flows during neural development
This work represents the first study which compares information flows in the intrinsic dynamics across development time and makes use of a recently proposed continuous-time transfer entropy estimator for spike trains, which is able to capture important effects occurring on both small and large timescales simultaneously.
Multi-Tier Platform for Cognizing Massive Electroencephalogram
An end-to-end platform assembling multiple tiers offers visible and graphical inter-pretations of the temporal characteristics of EEG by identifying the critical episodes, which is de-manded in neurodynamics but hardly appears in conventional cognition scenarios.
THPs: Topological Hawkes Processes for Learning Causal Structure on Event Sequences.
A Topological Hawkes process (THP) is proposed to draw a connection between the graph convolution in the topology domain and the temporal Convolution in time domains to learn causal structure learning method on THP in a likelihood framework.
Measuring the Rate of Information Exchange in Point-Process Data With Application to Cardiovascular Variability
The implementation of MIR for point process applications in Network Physiology and cardiovascular variability is presented, showing that cMIR reflects physiological mechanisms of cardiovascular variability related to the joint neural autonomic modulation of heart rate and arterial compliance.
Measuring the Rate of Information Transfer in Point-Process Data: Application to Cardiovascular Interactions
  • G. Mijatovic, Y. Antonacci, L. Faes
  • Computer Science
    2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
  • 2021
The method allows to compute the transfer entropy rate (TER) from a source to a target point process in continuous time, thus overcoming the severe limitations associated with time discretization of event-based processes.
Adaptive Spike-Like Representation of EEG Signals for Sleep Stages Scoring
This study proposes an adaptive scheme to probabilistically encode, accumulate and accumulate the input signals and weight the resultant features by the half-Gaussian probabilities of signal intensities, feeding into a transformer model to automatically mine the relevance between features and corresponding stages.


Directed Information Measures in Neuroscience
Highlights include the theoretical quantification and practical estimation of information transfer, description of transfer locally in space and time, multivariate directed measures, information decomposition among a set of stimulus/responses variables and the relation between interventional and observational causality.
The local information dynamics of distributed computation in complex systems
A complete information-theoretic framework to quantify these operations on information, and in particular their dynamics in space and time, is applied to cellular automata, and delivers important insights into the fundamental nature of distributed computation and the dynamics of complex systems.
Journal of Intelligent Material Systems and Structures
Medical Image Analysis: Progress over Two Decades and the Challenges Ahead
A look at progress in the field over the last 20 years is looked at and some of the challenges that remain for the years to come are suggested.
Plos Computational Biology主编关于论文获得发表的10条简单法则的评析
介绍Plos Computational Biology主编Philip E.Bourne关于论文发表的10务简单法则,包括:读很多论文,客观看待自身工作,选择好的编辑,提高英语水平,忍受退稿,提高论文质量等。以期对医学生和研究人员发表文章提供有益帮助。
I and J
Entropy 19
  • 5
  • 2017
PLoS Comput Biol 8
  • e1002522
  • 2012
Journal of bioscience and bioengineering 100
  • 131
  • 2005
and G
  • Petri, Physics Reports
  • 2020