150 research outputs found

    Insect neuroethology of reinforcement learning

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    Historically, reinforcement learning is a branch of machine learning founded on observations of how animals learn. This involved collaboration between the fields of biology and artificial intelligence that was beneficial to both fields, creating smarter artificial agents and improving the understanding of how biological systems function. The evolution of reinforcement learning during the past few years was rapid but substantially diverged from providing insights into how biological systems work, opening a gap between reinforcement learning and biology. In an attempt to close this gap, this thesis studied the insect neuroethology of reinforcement learning, that is, the neural circuits that underlie reinforcement-learning-related behaviours in insects. The goal was to extract a biologically plausible plasticity function from insect-neuronal data, use this to explain biological findings and compare it to more standard reinforcement learning models. Consequently, a novel dopaminergic plasticity rule was developed to approximate the function of dopamine as the plasticity mechanism between neurons in the insect brain. This allowed a range of observed learning phenomena to happen in parallel, like memory depression, potentiation, recovery, and saturation. In addition, by using anatomical data of connections between neurons in the mushroom body neuropils of the insect brain, the neural incentive circuit of dopaminergic and output neurons was also explored. This, together with the dopaminergic plasticity rule, allowed for dynamic collaboration amongst parallel memory functions, such as acquisition, transfer, and forgetting. When tested on olfactory conditioning paradigms, the model reproduced the observed changes in the activity of the identified neurons in fruit flies. It also replicated the observed behaviour of the animals and it allowed for flexible behavioural control. Inspired by the visual navigation system of desert ants, the model was further challenged in the visual place recognition task. Although a relatively simple encoding of the olfactory information was sufficient to explain odour learning, a more sophisticated encoding of the visual input was required to increase the separability among the visual inputs and enable visual place recognition. Signal whitening and sparse combinatorial encoding were sufficient to boost the performance of the system in this task. The incentive circuit enabled the encoding of increasing familiarity along a known route, which dropped proportionally to the distance of the animal from that route. Finally, the proposed model was challenged in delayed reinforcement tasks, suggesting that it might take the role of an adaptive critic in the context of reinforcement learning

    Exploring neural markers of language processing using fNIRS in typically developed children and children with Developmental Language Disorder

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    Background: Developmental language disorder (DLD) is a life-long condition with no clear biological causes that affects approximately 8% of the population. The diagnosis currently relies on behavioural testing that is not reliably performed on children younger than school age. Consequently, the diagnosis and treatment of DLD is often delayed until after children enter formal education. Early work in the field suggests that neural markers of language processing could be used to develop an objective diagnostic tool that will allow for accurate and early identification of DLD in preschool years and thus access to early interventions. Here we propose the use of a novel non-invasive neuroimaging technique called functional near infrared spectroscopy (fNIRS) to identify neural markers of language processing in children with DLD. Additionally, we argue that to understand atypical language processing, it is imperative to also investigate typical cortical activations in response to language processing to establish the developmental trajectories of the language network. Parallel to these studies we also investigate patterns of neural synchrony during parent-child interactions. Speech and language development in children is thought to rely on successful parent-child interactions, however, little is known regarding the underlying neural mechanisms from which they arise. Methods: Cross-Sectional fNIRS Studies: A total of 36 participants aged 6–16-year-old (1 participant with DLD) were recruited in two cross-sectional fNIRS studies. Participants underwent a 10-minute resting state imaging session and completed a series of computer-administered language and cognitive tasks while their brain activity was recorded using fNIRS from the bilateral inferior frontal gyrus (IFG) and the bilateral auditory cortices. Hyperscanning fNIRS Study: 12 children aged between 3 and 5 years old and their mothers participated in this study. Neural synchrony in mother-child dyads was measured bilaterally over frontal and temporal areas using fNIRS whilst the dyads were asked to play together (interactive condition) and separately (independent condition). Communication patterns were captured via video recordings and conversational turns were coded. Survey Study: 43 parents of children with DLD and 44 clinicians with DLD expertise completed a qualitative online survey detailing their views, concerns and recommendations regarding the use of neuroimaging-based tool for the diagnosis and monitoring of DLD. Results: Cross sectional fNIRS studies: In typically developed children and adolescents, widespread connections between the language regions and the right IFG appear to continue decreasing as age increases. In contrast connections between temporal regions are well established by late childhood. Increased activity over right auditory regions is associated with decreased language skills. Whilst data from the DLD participant is described, further analysis was not possible due to the limited sample size (n=1). Hyperscanning fNIRS study: We successfully recorded inter-brain synchrony in bilateral prefrontal and temporal cortices in mother-child dyads while they engaged in cooperative and independent play. Compared to the independent condition, mother-child dyads showed increased neural synchrony in the interactive condition across the prefrontal cortex and temporo-parietal junction. There was no significant relationship found between neural synchrony and turn-taking, but neural synchrony was negatively correlated with the child’s levels of surgency. Survey study: Clinicians and parents perceived that a potential tool that could diagnose children with DLD earlier would positively impact the children as it would allow them to access interventions earlier. This study offered a unique account of the factors to be considered in the design and implementation of clinical measures for language disorders from the viewpoints of parents and language professionals. Conclusions: Overall, this research aimed to identify neural markers of language processing in children with DLD and typically developed children to help develop an objective early diagnostic tool. Ultimately, this research might help maximize the benefits of speech and language therapies to improve the quality of life for children with DLD. This can be very impactful translational research in language development given that currently no objective neural-based tools exist for DLD

    Exploring Animal Behavior Through Sound: Volume 1

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    This open-access book empowers its readers to explore the acoustic world of animals. By listening to the sounds of nature, we can study animal behavior, distribution, and demographics; their habitat characteristics and needs; and the effects of noise. Sound recording is an efficient and affordable tool, independent of daylight and weather; and recorders may be left in place for many months at a time, continuously collecting data on animals and their environment. This book builds the skills and knowledge necessary to collect and interpret acoustic data from terrestrial and marine environments. Beginning with a history of sound recording, the chapters provide an overview of off-the-shelf recording equipment and analysis tools (including automated signal detectors and statistical methods); audiometric methods; acoustic terminology, quantities, and units; sound propagation in air and under water; soundscapes of terrestrial and marine habitats; animal acoustic and vibrational communication; echolocation; and the effects of noise. This book will be useful to students and researchers of animal ecology who wish to add acoustics to their toolbox, as well as to environmental managers in industry and government

    Ocean Noise

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    Scientific and societal concern about the effects of underwater sound on marine ecosystems is growing. While iconic megafauna was of initial concern, more and more taxa are being included. Some countries have joined in multi-national initiatives to measure, monitor and mitigate environmental impacts of ocean noise at large, trans-boundary spatial scales. Approaches to regulating ocean noise change as new scientific evidence becomes available, but may also differ by country. The OCEANOISE conference series has provided a platform for the exchange of scientific results, management approaches, research needs, stakeholder concerns, etc. Attendees have represented various sectors, including academia, offshore industry, defence, NGOs, consultants and government regulators. The published articles in the Special Issue cover a range of topics and applications central to ocean noise

    Treatise on Hearing: The Temporal Auditory Imaging Theory Inspired by Optics and Communication

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    A new theory of mammalian hearing is presented, which accounts for the auditory image in the midbrain (inferior colliculus) of objects in the acoustical environment of the listener. It is shown that the ear is a temporal imaging system that comprises three transformations of the envelope functions: cochlear group-delay dispersion, cochlear time lensing, and neural group-delay dispersion. These elements are analogous to the optical transformations in vision of diffraction between the object and the eye, spatial lensing by the lens, and second diffraction between the lens and the retina. Unlike the eye, it is established that the human auditory system is naturally defocused, so that coherent stimuli do not react to the defocus, whereas completely incoherent stimuli are impacted by it and may be blurred by design. It is argued that the auditory system can use this differential focusing to enhance or degrade the images of real-world acoustical objects that are partially coherent. The theory is founded on coherence and temporal imaging theories that were adopted from optics. In addition to the imaging transformations, the corresponding inverse-domain modulation transfer functions are derived and interpreted with consideration to the nonuniform neural sampling operation of the auditory nerve. These ideas are used to rigorously initiate the concepts of sharpness and blur in auditory imaging, auditory aberrations, and auditory depth of field. In parallel, ideas from communication theory are used to show that the organ of Corti functions as a multichannel phase-locked loop (PLL) that constitutes the point of entry for auditory phase locking and hence conserves the signal coherence. It provides an anchor for a dual coherent and noncoherent auditory detection in the auditory brain that culminates in auditory accommodation. Implications on hearing impairments are discussed as well.Comment: 603 pages, 131 figures, 13 tables, 1570 reference

    Advanced Sensing and Image Processing Techniques for Healthcare Applications

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    This Special Issue aims to attract the latest research and findings in the design, development and experimentation of healthcare-related technologies. This includes, but is not limited to, using novel sensing, imaging, data processing, machine learning, and artificially intelligent devices and algorithms to assist/monitor the elderly, patients, and the disabled population

    Computational modelling of neural mechanisms underlying natural speech perception

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    Humans are highly skilled at the analysis of complex auditory scenes. In particular, the human auditory system is characterized by incredible robustness to noise and can nearly effortlessly isolate the voice of a specific talker from even the busiest of mixtures. However, neural mechanisms underlying these remarkable properties remain poorly understood. This is mainly due to the inherent complexity of speech signals and multi-stage, intricate processing performed in the human auditory system. Understanding these neural mechanisms underlying speech perception is of interest for clinical practice, brain-computer interfacing and automatic speech processing systems. In this thesis, we developed computational models characterizing neural speech processing across different stages of the human auditory pathways. In particular, we studied the active role of slow cortical oscillations in speech-in-noise comprehension through a spiking neural network model for encoding spoken sentences. The neural dynamics of the model during noisy speech encoding reflected speech comprehension of young, normal-hearing adults. The proposed theoretical model was validated by predicting the effects of non-invasive brain stimulation on speech comprehension in an experimental study involving a cohort of volunteers. Moreover, we developed a modelling framework for detecting the early, high-frequency neural response to the uninterrupted speech in non-invasive neural recordings. We applied the method to investigate top-down modulation of this response by the listener's selective attention and linguistic properties of different words from a spoken narrative. We found that in both cases, the detected responses of predominantly subcortical origin were significantly modulated, which supports the functional role of feedback, between higher- and lower levels stages of the auditory pathways, in speech perception. The proposed computational models shed light on some of the poorly understood neural mechanisms underlying speech perception. The developed methods can be readily employed in future studies involving a range of experimental paradigms beyond these considered in this thesis.Open Acces
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