FISHEARS SIGNED

Project "FISHEARS" data sheet

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 Project objective

One of the predominant riddles of sensory biology is the diversity in fish auditory systems. It is widely accepted that fishes are well adapted to utilising underwater sounds as sensory cues in key life-history events. However, the functional significance and the driving force leading to the differences in fish inner ear sizes and structures are unknown. A complex interplay of physical, evolutionary, functional and ecological factors may shape the different elements: a multiscale environment too complicated for human conceptualisation. I propose to address this question by applying novel bioimaging and computational tools to investigate elasmobranch fish ears. Firstly, diffusible iodine-based contrast enhanced computed tomography (diceCT) will be used, co-registered with MRI data, to build 3D high resolution models of the inner ears. Secondly, a Finite Element (FE) model will be created to digitally replicate a fish ear and understand the biomechanics of its structure. Finally, a statistical framework will be developed to incorporate the factors that may shape the hearing system of elasmobranch fishes, including the collected data, together with the available physiological, ecological and biogeographical information on each species, as well as species’ acoustic environmental parameters. A Machine Learning algorithm will be applied to infer patterns and relationships between the factors, to perform both cluster and prediction analyses. Thus, a reliable model will be developed, which can predict the hearing capability of any elasmobranch species based on the ear morphology and the first evidence of the function of fish ear diversity.