Adaptive map alignment in the superior colliculus of the barn owl: a neuromorphic implementation

Adaptation is one of the basic phenomena of biology, while adaptability is an important feature for neural network. Young barn owl can well adapt its visual and auditory integration to the environmental change, such as prism wearing. At first, a mathematical model is introduced by the related study in biological experiment. The model well explained the mechanism of the sensory map realignment through axongenesis and synaptogenesis. Simulation results of this model are consistent with the biological data. Thereafter, to test the model’s application in hardware, the model is implemented into a robot. Visual and auditory signals are acquired by the sensors of the robot and transferred back to PC through bluetooth. Results of the robot experiment are presented, which shows the SC model allowing the robot to adjust visual and auditory integration to counteract the effects of a prism. Finally, based on the model, a silicon Superior Colliculus is designed in VLSI circuit and fabricated. Performance of the fabricated chip has shown the synaptogenesis and axogenesis can be emulated in VLSI circuit. The circuit of neural model provides a new method to update signals and reconfigure the switch network (the chip has an automatic reconfigurable network which is used to correct the disparity between signals). The chip is also the first Superior Colliculus VLSI circuit to emulate the sensory map realignment

An Adaptive Neural Mechanism for Acoustic Motion Perception with Varying Sparsity

Biological motion-sensitive neural circuits are quite adept in perceiving the relative motion of a relevant stimulus. Motion perception is a fundamental ability in neural sensory processing and crucial in target tracking tasks. Tracking a stimulus entails the ability to perceive its motion, i.e., extracting information about its direction and velocity. Here we focus on auditory motion perception of sound stimuli, which is poorly understood as compared to its visual counterpart. In earlier work we have developed a bio-inspired neural learning mechanism for acoustic motion perception. The mechanism extracts directional information via a model of the peripheral auditory system of lizards. The mechanism uses only this directional information obtained via specific motor behaviour to learn the angular velocity of unoccluded sound stimuli in motion. In nature however the stimulus being tracked may be occluded by artefacts in the environment, such as an escaping prey momentarily disappearing behind a cover of trees. This article extends the earlier work by presenting a comparative investigation of auditory motion perception for unoccluded and occluded tonal sound stimuli with a frequency of 2.2 kHz in both simulation and practice. Three instances of each stimulus are employed, differing in their movement velocities–0.5°/time step, 1.0°/time step and 1.5°/time step. To validate the approach in practice, we implement the proposed neural mechanism on a wheeled mobile robot and evaluate its performance in auditory tracking

Sensorimotor maps can be dynamically calibrated using an adaptive-filter model of the cerebellum

Substantial experimental evidence suggests the cerebellum is involved in calibrating sensorimotor maps. Consistent with this involvement is the well-known, but little understood, massive cerebellar projection to maps in the superior colliculus. Map calibration would be a significant new role for the cerebellum given the ubiquity of map representations in the brain, but how it could perform such a task is unclear. Here we investigated a dynamic method for map calibration, based on electrophysiological recordings from the superior colliculus, that used a standard adaptive-filter cerebellar model. The method proved effective for complex distortions of both unimodal and bimodal maps, and also for predictive map-based tracking of moving targets. These results provide the first computational evidence for a novel role for the cerebellum in dynamic sensorimotor map calibration, of potential importance for coordinate alignment during ongoing motor control, and for map calibration in future biomimetic systems. This computational evidence also provides testable experimental predictions concerning the role of the connections between cerebellum and superior colliculus in previously observed dynamic coordinate transformations

Calibration of sound source localisation for robots using multiple adaptive filter models of the cerebellum

The aim of this research was to investigate the calibration of Sound Source Localisation (SSL) for robots using the adaptive filter model of the cerebellum and how this could be automatically adapted for multiple acoustic environments. The role of the cerebellum has mainly been identified in the context of motor control, and only in recent years has it been recognised that it has a wider role to play in the senses and cognition. The adaptive filter model of the cerebellum has been successfully applied to a number of robotics applications but so far none involving auditory sense. Multiple models frameworks such as MOdular Selection And Identification for Control (MOSAIC) have also been developed in the context of motor control, and this has been the inspiration for adaptation of audio calibration in multiple acoustic environments; again, application of this approach in the area of auditory sense is completely new. The thesis showed that it was possible to calibrate the output of an SSL algorithm using the adaptive filter model of the cerebellum, improving the performance compared to the uncalibrated SSL. Using an adaptation of the MOSAIC framework, and specifically using responsibility estimation, a system was developed that was able to select an appropriate set of cerebellar calibration models and to combine their outputs in proportion to how well each was able to calibrate, to improve the SSL estimate in multiple acoustic contexts, including novel contexts. The thesis also developed a responsibility predictor, also part of the MOSAIC framework, and this improved the robustness of the system to abrupt changes in context which could otherwise have resulted in a large performance error. Responsibility prediction also improved robustness to missing ground truth, which could occur in challenging environments where sensory feedback of ground truth may become impaired, which has not been addressed in the MOSAIC literature, adding to the novelty of the thesis. The utility of the so-called cerebellar chip has been further demonstrated through the development of a responsibility predictor that is based on the adaptive filter model of the cerebellum, rather than the more conventional function fitting neural network used in the literature. Lastly, it was demonstrated that the multiple cerebellar calibration architecture is capable of limited self-organising from a de-novo state, with a predetermined number of models. It was also demonstrated that the responsibility predictor could learn against its model after self-organisation, and to a limited extent, during self-organisation. The thesis addresses an important question of how a robot could improve its ability to listen in multiple, challenging acoustic environments, and recommends future work to develop this ability

A biologically inspired approach to the cocktail party problem

At a cocktail party, one can choose to scan the room for conversations of interest, attend to a specific conversation partner, switch between conversation partners, or not attend to anything at all. The ability of the normal-functioning auditory system to flexibly listen in complex acoustic scenes plays a central role in solving the cocktail party problem (CPP). In contrast, certain demographics (e.g., individuals with hearing impairment or older adults) are unable to solve the CPP, leading to psychological ailments and reduced quality of life. Since the normal auditory system still outperforms machines in solving the CPP, an effective solution may be found by mimicking the normal-functioning auditory system. Spatial hearing likely plays an important role in CPP-processing in the auditory system. This thesis details the development of a biologically based approach to the CPP by modeling specific neural mechanisms underlying spatial tuning in the auditory cortex. First, we modeled bottom-up, stimulus-driven mechanisms using a multi-layer network model of the auditory system. To convert spike trains from the model output into audible waveforms, we designed a novel reconstruction method based on the estimation of time-frequency masks. We showed that our reconstruction method produced sounds with significantly higher intelligibility and quality than previous reconstruction methods. We also evaluated the algorithm's performance using a psychoacoustic study, and found that it provided the same amount of benefit to normal-hearing listeners as a current state-of-the-art acoustic beamforming algorithm. Finally, we modeled top-down, attention driven mechanisms that allowed the network to flexibly operate in different regimes, e.g., monitor the acoustic scene, attend to a specific target, and switch between attended targets. The model explains previous experimental observations, and proposes candidate neural mechanisms underlying flexible listening in cocktail-party scenarios. The strategies proposed here would benefit hearing-assistive devices for CPP processing (e.g., hearing aids), where users would benefit from switching between various modes of listening in different social situations.2022-05-19T00:00:00

Engineering derivatives from biological systems for advanced aerospace applications

The present study consisted of a literature survey, a survey of researchers, and a workshop on bionics. These tasks produced an extensive annotated bibliography of bionics research (282 citations), a directory of bionics researchers, and a workshop report on specific bionics research topics applicable to space technology. These deliverables are included as Appendix A, Appendix B, and Section 5.0, respectively. To provide organization to this highly interdisciplinary field and to serve as a guide for interested researchers, we have also prepared a taxonomy or classification of the various subelements of natural engineering systems. Finally, we have synthesized the results of the various components of this study into a discussion of the most promising opportunities for accelerated research, seeking solutions which apply engineering principles from natural systems to advanced aerospace problems. A discussion of opportunities within the areas of materials, structures, sensors, information processing, robotics, autonomous systems, life support systems, and aeronautics is given. Following the conclusions are six discipline summaries that highlight the potential benefits of research in these areas for NASA's space technology programs

The robot vibrissal system: Understanding mammalian sensorimotor co-ordination through biomimetics

Chapter 10 The Robot Vibrissal System: Understanding Mammalian Sensorimotor Co-ordination Through Biomimetics Tony J. Prescott, Ben Mitchinson, Nathan F. Lepora, Stuart P. Wilson, Sean R. Anderson, John Porrill, Paul Dean, Charles ..

Mechanisms of multisensory integration and attention

Spatial attention is an essential mechanism that helps us perceive our surroundings by bringing into consciousness environmental occurrences or objects that may be of importance. Studies of spatial attention have classically recorded behavioural responses to targets presented in a region of space where attention had previously been allocated to. Such investigations show a behavioural facilitation at the same location due to cueing, but less in known about the effects of shifts of attention when the cued location is not the location of interest. This thesis presents seven experiments aimed at investigating this by implementing and revising the attentional repulsion effect (ARE). The ARE is a perceptual localisation error when attention is diverted from the region of interest and it has been extensively studied in the visual domain, however, the rising number of ARE studies has created numerous research methodologies used to evoke the effect, which may have led to isolated reports. This thesis attempts to combine past methodologies with a new approach to quantify the effect, and will address some methodological differences evident in the literature, in order to optimise the stimulus paradigms and maximise the effect. The results show that a robust ARE can be elicited in the visual modality, but the same is not observed in the auditory modality. Furthermore, when using cues that are of different modality than the targets, the ARE is only observed in the visual target modality. Using visual cues and auditory targets will produce an attraction effect, in line with the ventriloquism theory. However, the implementation of interstimuli intervals up to 1.5 seconds would be enough to disrupt the ventriloquism illusion, but it did not alter the resulted attraction. Lastly, one question regarding the role of attention in sensory adaptation was addressed. I hypothesise that sensory adaptation could be further a contributor to the ARE given that most psychophysics paradigms of the ARE repeat the same stimuli thousands of times, uninterruptedly. The results are inconclusive mainly due to experimental design. All results are discussed in relation with theories of spatial and multimodal attention