Multivariate autoregressive-based neuronal network flow analysis for in-vitro recorded bursts
Hettiarachchi, Imali T., Bhatti, Asim, Adlard, Paul A. and Nahavandi, Saeid 2015, Multivariate autoregressive-based neuronal network flow analysis for in-vitro recorded bursts, in ICONIP 2015 : Neural information processing : 22nd International Conference, ICONIP 2015, Istanbul, Turkey, November 9-12, 2015 : proceedings, Springer, Berlin, Germany, pp. 324-331, doi: 10.1007/978-3-319-26561-2_39.
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Multivariate autoregressive-based neuronal network flow analysis for in-vitro recorded bursts
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. Microelec trodearray (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.
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