Enigmatic fish ears: solving a sensory biology riddle with bioengineering and Artificial Intelligence

One of the predominant riddles of sensory biology is the diversity in fish auditory systems.

It is widelyaccepted that fishes are well adapted to utilising underwater sounds as sensory cues in key life-historyevents.

However, the functional significance and the driving force leading to the differences in fishinner ear sizes and structures are unknown.

A complex interplay of physical, evolutionary, functionaland ecological factors may shape the different elements: a multiscale environment too complicatedfor human conceptualisation.

I propose to address this question by applying novel bioimaging andcomputational tools to investigate elasmobranch fish ears.

Firstly, diffusible iodine-based contrast enhancedcomputed tomography (diceCT) will be used, co-registered with MRI data, to build 3D highresolution models of the inner ears.

Secondly, a Finite Element (FE) model will be created to digitallyreplicate a fish ear and understand the biomechanics of its structure.

Finally, a statistical frameworkwill be developed to incorporate the factors that may shape the hearing system of elasmobranchfishes, including the collected data, together with the available physiological, ecological andbiogeographical information on each species, as well as species’ acoustic environmental parameters.

AMachine Learning algorithm will be applied to infer patterns and relationships between the factors, toperform both cluster and prediction analyses.

Thus, a reliable model will be developed, which canpredict the hearing capability of any elasmobranch species based on the ear morphology and the firstevidence of the function of fish ear diversity.