Evolution of inner ear neuroanatomy of bats and implications for echolocation

Correlated evolution between body size and echolocation in bats (order Chiroptera)

BACKGROUND

Body size and echolocation call frequencies are related in bats. However, it is unclear if this allometry applies to the entire clade. Differences have been suggested between nasal and oral emitting bats, as well as between some taxonomic families. Additionally, the scaling of other echolocation parameters, such as bandwidth and call duration, needs further testing. Moreover, it would be also interesting to test whether changes in body size have been coupled with changes in these echolocation parameters throughout bat evolution. Here, we test the scaling of peak frequency, bandwidth, and call duration with body mass using phylogenetically informed analyses for 314 bat species. We specifically tested whether all these scaling patterns differ between nasal and oral emitting bats. Then, we applied recently developed Bayesian statistical techniques based on large-scale simulations to test for the existence of correlated evolution between body mass and echolocation.

RESULTS

Our results showed that echolocation peak frequencies, bandwidth, and duration follow significant allometric patterns in both nasal and oral emitting bats. Changes in these traits seem to have been coupled across the laryngeal echolocation bats diversification. Scaling and correlated evolution analyses revealed that body mass is more related to peak frequency and call duration than to bandwidth. We exposed two non-exclusive kinds of mechanisms to explain the link between size and each of the echolocation parameters.

CONCLUSIONS

The incorporation of Bayesian statistics based on large-scale simulations could be helpful for answering macroevolutionary patterns related to the coevolution of traits in bats and other taxonomic groups.

Molecular adaptations underlying high-frequency hearing in the brain of CF bats species

BACKGROUND

The majority of bat species have developed remarkable echolocation ability, especially for the laryngeally echolocating bats along with high-frequency hearing. Adaptive evolution has been widely detected for the cochleae in the laryngeally echolocating bats, however, limited understanding for the brain which is the central to echolocation signal processing in the auditory perception system, the laryngeally echolocating bats brain may also undergo adaptive changes.

RESULT

In order to uncover the molecular adaptations related with high-frequency hearing in the brain of laryngeally echolocating bats, the genes expressed in the brain of Rhinolophus ferrumequinum (CF bat) and Myotis pilosus (FM bat) were both detected and also compared. A total of 346,891 genes were detected and the signal transduction mechanisms were annotated by the most abundant genes, followed by the transcription. In hence, there were 3,088 DEGs were found between the two bat brains, with 1,426 highly expressed in the brain of R. ferrumequinum, which were significantly enriched in the neuron and neurodevelopmental processes. Moreover, we found a key candidate hearing gene, ADCY1, playing an important role in the R. ferrumequinum brain and undergoing adaptive evolution in CF bats.

CONCLUSIONS

Our study provides a new insight to the molecular bases of high-frequency hearing in two laryngeally echolocating bats brain and revealed different nervous system activities during auditory perception in the brain of CF bats.

Development of the hyolaryngeal architecture in horseshoe bats: insights into the evolution of the pulse generation for laryngeal echolocation

BACKGROUND

The hyolaryngeal apparatus generates biosonar pulses in the laryngeally echolocating bats. The cartilage and muscles comprising the hyolarynx of laryngeally echolocating bats are morphologically modified compared to those of non-bat mammals, as represented by the hypertrophied intrinsic laryngeal muscle. Despite its crucial contribution to laryngeal echolocation, how the development of the hyolarynx in bats differs from that of other mammals is poorly documented. The genus Rhinolophus is one of the most sophisticated laryngeal echolocators, with the highest pulse frequency in bats. The present study provides the first detailed description of the three-dimensional anatomy and development of the skeleton, cartilage, muscle, and innervation patterns of the hyolaryngeal apparatus in two species of rhinolophid bats using micro-computed tomography images and serial tissue sections and compares them with those of laboratory mice. Furthermore, we measured the peak frequency of the echolocation pulse in active juvenile and adult individuals to correspond to echolocation pulses with hyolaryngeal morphology at each postnatal stage.

RESULTS

We found that the sagittal crests of the cricoid cartilage separated the dorsal cricoarytenoid muscle in horseshoe bats, indicating that this unique morphology may be required to reinforce the repeated closure movement of the glottis during biosonar pulse emission. We also found that the cricothyroid muscle is ventrally hypertrophied throughout ontogeny, and that the cranial laryngeal nerve has a novel branch supplying the hypertrophied region of this muscle. Our bioacoustic analyses revealed that the peak frequency shows negative allometry against skull growth, and that the volumetric growth of all laryngeal cartilages is correlated with the pulse peak frequency.

CONCLUSIONS

The unique patterns of muscle and innervation revealed in this study appear to have been obtained concomitantly with the acquisition of tracheal chambers in rhinolophids and hipposiderids, improving sound intensity during laryngeal echolocation. In addition, significant protrusion of the sagittal crest of the cricoid cartilage and the separated dorsal cricoarytenoid muscle may contribute to the sophisticated biosonar in this laryngeally echolocating lineage. Furthermore, our bioacoustic data suggested that the mineralization of these cartilages underpins the ontogeny of echolocation pulse generation. The results of the present study provide crucial insights into how the anatomy and development of the hyolaryngeal apparatus shape the acoustic diversity in bats.

Cochlea development shapes bat sensory system evolution

Sensory organs must develop alongside the skull within which they are largely encased, and this relationship can manifest as the skull constraining the organs, organs constraining the skull, or organs constraining one another in relative size. How this interplay between sensory organs and the developing skull plays out during the evolution of sensory diversity; however, remains unknown. Here, we examine the developmental sequence of the cochlea, the organ responsible for hearing and echolocation, in species with distinct diet and echolocation types within the ecologically diverse bat super-family Noctilionoidea. We found the size and shape of the cochlea largely correlates with skull size, with exceptions of Pteronotus parnellii, whose high duty cycle echolocation (nearly constant emission of sound pulses during their echolocation process allowing for detailed information gathering, also called constant frequency echolocation) corresponds to a larger cochlear and basal turn, and Monophyllus redmani, a small-bodied nectarivorous bat, for which interactions with other sensory organs restrict cochlea size. Our findings support the existence of developmental constraints, suggesting that both developmental and anatomical factors may act synergistically during the development of sensory systems in noctilionoid bats.

A 50-million-year-old, three-dimensionally preserved bat skull supports an early origin for modern echolocation

Bats are among the most recognizable, numerous, and widespread of all mammals. But much of their fossil record is missing, and bat origins remain poorly understood, as do the relationships of early to modern bats. Here, we describe a new early Eocene bat that helps bridge the gap between archaic stem bats and the hyperdiverse modern bat radiation of more than 1,460 living species. Recovered from ∼50 million-year-old cave sediments in the Quercy Phosphorites of southwestern France, Vielasia sigei's remains include a near-complete, three-dimensionally preserved skull-the oldest uncrushed bat cranium yet found. Phylogenetic analyses of a 2,665 craniodental character matrix, with and without 36.8 kb of DNA sequence data, place Vielasia outside modern bats, with total evidence tip-dating placing it sister to the crown clade. Vielasia retains the archaic dentition and skeletal features typical of early Eocene bats, but its inner ear shows specializations found in modern echolocating bats. These features, which include a petrosal only loosely attached to the basicranium, an expanded cochlea representing ∼25% basicranial width, and a long basilar membrane, collectively suggest that the kind of laryngeal echolocation used by most modern bats predates the crown radiation. At least 23 individuals of V. sigei are preserved together in a limestone cave deposit, indicating that cave roosting behavior had evolved in bats by the end of the early Eocene; this period saw the beginning of significant global climate cooling that may have been an evolutionary driver for bats to first congregate in caves.

Perceiving like a Bat: Hierarchical 3D Geometric-Semantic Scene Understanding Inspired by a Biomimetic Mechanism

Geometric-semantic scene understanding is a spatial intelligence capability that is essential for robots to perceive and navigate the world. However, understanding a natural scene remains challenging for robots because of restricted sensors and time-varying situations. In contrast, humans and animals are able to form a complex neuromorphic concept of the scene they move in. This neuromorphic concept captures geometric and semantic aspects of the scenario and reconstructs the scene at multiple levels of abstraction. This article seeks to reduce the gap between robot and animal perception by proposing an ingenious scene-understanding approach that seamlessly captures geometric and semantic aspects in an unexplored environment. We proposed two types of biologically inspired environment perception methods, i.e., a set of elaborate biomimetic sensors and a brain-inspired parsing algorithm related to scene understanding, that enable robots to perceive their surroundings like bats. Our evaluations show that the proposed scene-understanding system achieves competitive performance in image semantic segmentation and volumetric-semantic scene reconstruction. Moreover, to verify the practicability of our proposed scene-understanding method, we also conducted real-world geometric-semantic scene reconstruction in an indoor environment with our self-developed drone.

Brain-inspired multimodal hybrid neural network for robot place recognition

Place recognition is an essential spatial intelligence capability for robots to understand and navigate the world. However, recognizing places in natural environments remains a challenging task for robots because of resource limitations and changing environments. In contrast, humans and animals can robustly and efficiently recognize hundreds of thousands of places in different conditions. Here, we report a brain-inspired general place recognition system, dubbed NeuroGPR, that enables robots to recognize places by mimicking the neural mechanism of multimodal sensing, encoding, and computing through a continuum of space and time. Our system consists of a multimodal hybrid neural network (MHNN) that encodes and integrates multimodal cues from both conventional and neuromorphic sensors. Specifically, to encode different sensory cues, we built various neural networks of spatial view cells, place cells, head direction cells, and time cells. To integrate these cues, we designed a multiscale liquid state machine that can process and fuse multimodal information effectively and asynchronously using diverse neuronal dynamics and bioinspired inhibitory circuits. We deployed the MHNN on Tianjic, a hybrid neuromorphic chip, and integrated it into a quadruped robot. Our results show that NeuroGPR achieves better performance compared with conventional and existing biologically inspired approaches, exhibiting robustness to diverse environmental uncertainty, including perceptual aliasing, motion blur, light, or weather changes. Running NeuroGPR as an overall multi-neural network workload on Tianjic showcases its advantages with 10.5 times lower latency and 43.6% lower power consumption than the commonly used mobile robot processor Jetson Xavier NX.

Evolution of Placental Hormones: Implications for Animal Models

Human placenta secretes a variety of hormones, some of them in large amounts. Their effects on maternal physiology, including the immune system, are poorly understood. Not one of the protein hormones specific to human placenta occurs outside primates. Instead, laboratory and domesticated species have their own sets of placental hormones. There are nonetheless several examples of convergent evolution. Thus, horse and human have chorionic gonadotrophins with similar functions whilst pregnancy-specific glycoproteins have evolved in primates, rodents, horses, and some bats, perhaps to support invasive placentation. Placental lactogens occur in rodents and ruminants as well as primates though evolved through duplication of different genes and with functions that only partially overlap. There are also placental hormones, such as the pregnancy-associated glycoproteins of ruminants, that have no equivalent in human gestation. This review focusses on the evolution of placental hormones involved in recognition and maintenance of pregnancy, in maternal adaptations to pregnancy and lactation, and in facilitating immune tolerance of the fetal semiallograft. The contention is that knowledge gained from laboratory and domesticated mammals can translate to a better understanding of human placental endocrinology, but only if viewed in an evolutionary context.