Spike Train Similarity Space (SSIMS) Method Detects Effects of Obstacle Proximity and Experience on Temporal Patterning of Bat Biosonar

Frontiers in Behavioral Neuroscience
Alyssa W AccomandoJames A Simmons

Abstract

Bats emit biosonar pulses in complex temporal patterns that change to accommodate dynamic surroundings. Efforts to quantify these patterns have included analyses of inter-pulse intervals, sonar sound groups, and changes in individual signal parameters such as duration or frequency. Here, the similarity in temporal structure between trains of biosonar pulses is assessed. The spike train similarity space (SSIMS) algorithm, originally designed for neural activity pattern analysis, was applied to determine which features of the environment influence temporal patterning of pulses emitted by flying big brown bats,Eptesicus fuscus. In these laboratory experiments, bats flew down a flight corridor through an obstacle array. The corridor varied in width (100, 70, or 40 cm) and shape (straight or curved). Using a relational point-process framework, SSIMS was able to discriminate between echolocation call sequences recorded from flights in each of the corridor widths. SSIMS was also able to tell the difference between pulse trains recorded during flights where corridor shape through the obstacle array matched the previous trials (fixed, or expected) as opposed to those recorded from flights with randomized corridor shape (variable, or une...Continue Reading

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Citations

Mar 17, 2019·The Journal of Experimental Biology·James A SimmonsUday Shriram
Apr 19, 2019·Journal of Comparative Physiology. A, Neuroethology, Sensory, Neural, and Behavioral Physiology·M Jerome BeetzJulio C Hechavarría
Jan 23, 2020·Scientific Reports·James A SimmonsAndrea M Simmons

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Software Mentioned

SSIMS
MATLAB

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