Towards an Accurate Identification of Pyloric Neuron Activity with VSDi

dos Santos, Filipa; Andras, Peter; Lam, K.P.

Abstract

Voltage-sensitive dye imaging (VSDi) which enables simultaneous optical recording of many neurons in the pyloric circuit of the stomatogastric ganglion is an important technique to supplement electrophysiological recordings. However, utilising the technique to identify pyloric neurons directly is a computationally exacting task that requires the development of sophisticated signal processing procedures to analyse the tri-phasic pyloric patterns generated by these neurons. This paper presents our work towards commissioning such procedures. The results achieved to date are most encouraging.

• Presentation Conference Type: Conference Paper (Published)
• Conference Name: ICANN 2017: 26th International Conference on Artificial Neural Networks
• Start Date: Sep 11, 2017
• End Date: Sep 14, 2017
• Online Publication Date: Oct 24, 2017
• Publication Date: 2017
• Deposit Date: Nov 4, 2021
• Publisher: Springer
• Pages: 121-128
• Series Title: Lecture Notes in Computer Science
• Series Number: 10613
• Series ISSN: 1611-3349
• Book Title: Artificial Neural Networks and Machine Learning – ICANN 2017
• ISBN: 978-3-319-68599-1
• DOI: https://doi.org/10.1007/978-3-319-68600-4_15
• Keywords: Duty cycle, Tri-phasic pyloric neural network, Voltage-sensitive dye imaging, Singular Spectrum Analysis, Dynamic phase detection
• Public URL: http://researchrepository.napier.ac.uk/Output/2809234