International Conference on Neural Information Processing

Neural Information Processing pp 324-331 | Cite as

Multivariate Autoregressive-based Neuronal Network Flow Analysis for In-vitro Recorded Bursts

  • Imali T. Hettiarachchi
  • Asim Bhatti
  • Paul A. Adlard
  • Saeid Nahavandi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9492)

Abstract

Neuroscientific studies of in vitro neuron cell cultures has attracted paramount attention to investigate the behaviour of neuronal networks in response to different environmental conditions and external stimuli such as drugs, optical and electrical stimulations. Microelectrode array (MEA) technology has been widely adopted as a tool for this investigation. In this work, we present a new approach to estimate interconnectivity of neural spikes using multivariate autoregressive (MVAR) analysis and Partial Directed Coherence (PDC). The proposed approach has the potential to discover hidden intra-burst causal connectivity patterns and to help understand the spatiotemporal communication patterns within bursts, pre and post stimulations.

Keywords

Multi electrode array Bursts Partial directed coherence Multivariate autoregressive modelling 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Imali T. Hettiarachchi
    • 1
  • Asim Bhatti
    • 1
  • Paul A. Adlard
    • 2
  • Saeid Nahavandi
    • 1
  1. 1.Centre for Intelligent Systems ResearchDeakin UniversityGeelongAustralia
  2. 2.Synaptic Neurobiology LaboratoryThe Florey Institute of Neuroscience and Mental HealthMelbourneAustralia

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