Otolith

Summary

An otolith (ὠτο-, ōto- ear + λῐ́θος, líthos, a stone), also called statoconium or otoconium or statolith, is a calcium carbonate structure in the saccule or utricle of the inner ear, specifically in the vestibular system of vertebrates. The saccule and utricle, in turn, together make the otolith organs. These organs are what allows an organism, including humans, to perceive linear acceleration, both horizontally and vertically (gravity). They have been identified in both extinct and extant vertebrates. Counting the annual growth rings on the otoliths is a common technique in estimating the age of fish. Description Endolymphatic infillings such as otoliths are structures in the saccule and utricle of the inner ear, specifically in the vestibular labyrinth of all vertebrates (fish, amphibians, reptiles, mammals and birds). In vertebrates, the saccule and utricle together make the otolith organs. Both statoconia and otoliths are used as gravity, balance, movement, and directi

Official source

https://en.wikipedia.org/wiki/Otolith

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Balancing the Self

Mariia Kaliuzhna

The vestibular system is composed of otolith organs and semi-circular canals that encode linear and angular accelerations, as well as the position of the head with respect to gravity. Thus, the detection of self-motion, the distinction between self- and object-motion, as well as gaze stabilisation and maintenance of postural stability are the core vestibular functions. Recent research shows that vestibular information interacts with higher-level cognitive processes, such as space perception, attention orienting, body schema and bodily self-consciousness. In order to contribute to these faculties, vestibular information is dynamically combined with visual, somatosensory and proprioceptive signals. In the present thesis we explore such multimodal interactions using a human centrifuge (rotating chair). In Part 1 we show that visual and vestibular cues are integrated in accordance with statistical optimality even when large directional conflicts are introduced between these modalities. Participants were significantly better in discriminating rotation magnitude when simultaneously presented with visual and vestibular cues, as compared to each modality independently, despite the fact that the axes of rotation implied by the two cues were different (Study 1). We also demonstrate that visuo-vestibular integration is present and optimal in patients with unilateral vestibular loss (Study 2). Part 2 of the present thesis examined vestibularsomatosensory interactions. We show that vestibular stimulation in the form of passive whole-body rotations increases tactile sensitivity at the fingertips, as compared to a no-rotation baseline (Study 3). We also demonstrate that the effect of vestibular stimulation on touch is not direct, but mediated by visual information about self-motion: visual and vestibular cues first combine, and only subsequently influence tactile sensitivity (Study 4). In Part 3 of this thesis, we explored how vestibular stimulation affects visual attention and awareness. We show that when acting as an exogenous cue, vestibular stimulation orients attention at short cue-to-target delays. When acting as an endogenous cue, vestibular stimulation strongly orients attention at all cue-to-target delays (Study 5). Vestibular stimulation also affects visual awareness. Using a continuous flash suppression paradigm to suppress an optic flow stimulus during passive whole-body rotations, we show that optic flow that is congruent (i.e. counterdirectional) with the direction of the vestibular rotation breaks suppression faster than incongruent optic flow (Study 6). In sum, our findings refine the existing knowledge on multisensory processing in general and vestibular interactions with other senses in particular. Our results are of relevance for the understanding of how visual, vestibular, proprioceptive and somatosensory information are combined by the brain in order to form a coherent representation of the self in space.

EPFL2015

Many ecological studies rely on count data and involve manual counting of objects of interest, which is time-consuming and especially disadvantageous when time in the field or lab is limited. However, an increasing number of works uses digital imagery, which opens opportunities to automatise counting tasks. In this study, we use machine learning to automate counting objects of interest without the need to label individual objects. By leveraging already existing image-level annotations, this approach can also give value to historical data that were collected and annotated over longer time series (typical for many ecological studies), without the aim of deep learning applications. We demonstrate deep learning regression on two fundamentally different counting tasks: (i) daily growth rings from microscopic images of fish otolith (i.e., hearing stone) and (ii) hauled out seals from highly variable aerial imagery. In the otolith images, our deep learning-based regressor yields an RMSE of 3.40 day-rings and an R2 of 0.92. Initial performance in the seal images is lower (RMSE of 23.46 seals and R2 of 0.72), which can be attributed to a lack of images with a high number of seals in the initial training set, compared to the test set. We then show how to improve performance substantially (RMSE of 19.03 seals and R2 of 0.77) by carefully selecting and relabelling just 100 additional training images based on initial model prediction discrepancy. The regression-based approach used here returns accurate counts (R2 of 0.92 and 0.77 for the rings and seals, respectively), directly usable in ecological research.

2021

Balancing the Self

Mariia Kaliuzhna

EPFL2015