Neural Models of Subcortical Auditory Processing

An important feature of the auditory system is its ability to distinguish many simultaneous sound sources. The primary goal of this work was to understand how a robust, preattentive analysis of the auditory scene is accomplished by the subcortical auditory system. Reasonably accurate modelling of the morphology and organisation of the relevant auditory nuclei, was seen as being of great importance. The formulation of plausible models and their subsequent simulation was found to be invaluable in elucidating biological processes and in highlighting areas of uncertainty. In the thesis, a review of important aspects of mammalian auditory processing is presented and used as a basis for the subsequent modelling work. For each aspect of auditory processing modelled, psychophysical results are described and existing models reviewed, before the models used here are described and simulated. Auditory processes which are modelled include the peripheral system, and the production of tonotopic maps of the spectral content of complex acoustic stimuli, and of modulation frequency or periodicity. A model of the formation of sequential associations between successive sounds is described, and the model is shown to be capable of emulating a wide range of psychophysical behaviour. The grouping of related spectral components and the development of pitch perception is also investigated. Finally a critical assessment of the work and ideas for future developments are presented. The principal contributions of this work are the further development of a model for pitch perception and the development of a novel architecture for the sequential association of those groups. In the process of developing these ideas, further insights into subcortical auditory processing were gained, and explanations for a number of puzzling psychophysical characteristics suggested.Royal Naval Engineering College, Manadon, Plymout

Neural correlates of auditory pattern learning in the auditory cortex

Learning of new auditory stimuli often requires repetitive exposure to the stimulus. Fast and implicit learning of sounds presented at random times enables efficient auditory perception. However, it is unclear how such sensory encoding is processed on a neural level. We investigated neural responses that are developed from a passive, repetitive exposure to a specific sound in the auditory cortex of anesthetized rats, using electrocorticography. We presented a series of random sequences that are generated afresh each time, except for a specific reference sequence that remains constant and re-appears at random times across trials. We compared induced activity amplitudes between reference and fresh sequences. Neural responses from both primary and non-primary auditory cortical regions showed significantly decreased induced activity amplitudes for reference sequences compared to fresh sequences, especially in the beta band. This is the first study showing that neural correlates of auditory pattern learning can be evoked even in anesthetized, passive listening animal models

Cortical Maps

In this article, we review functional organization in sensory cortical regions-how the cortex represents the world. We consider four interrelated aspects of cortical organization: (1) the set of receptive fields of individual cortical sensory neurons, (2) how lateral interaction between cortical neurons reflects the similarity of their receptive fields, (3) the spatial distribution of receptive-field properties across the horizontal extent of the cortical tissue, and (4) how the spatial distributions of different receptive-field properties interact with one another. We show how these data are generally well explained by the theory of input-driven self-organization, with a family of computational models of cortical maps offering a parsimonious account for a wide range of map-related phenomena. We then discuss important challenges to this explanation, with respect to the maps present at birth, maps present under activity blockade, the limits of adult plasticity, and the lack of some maps in rodents. Because there is not at present another credible general theory for cortical map development, we conclude by proposing key experiments to help uncover other mechanisms that might also be operating during map development

The Human Auditory System

This book presents the latest findings in clinical audiology with a strong emphasis on new emerging technologies that facilitate and optimize a better assessment of the patient. The book has been edited with a strong educational perspective (all chapters include an introduction to their corresponding topic and a glossary of terms). The book contains material suitable for graduate students in audiology, ENT, hearing science and neuroscience

Sound processing in the mouse auditory cortex: organization, modulation, and transformation

The auditory system begins with the cochlea, a frequency analyzer and signal amplifier with exquisite precision. As neural information travels towards higher brain regions, the encoding becomes less faithful to the sound waveform itself and more influenced by non-sensory factors such as top-down attentional modulation, local feedback modulation, and long-term changes caused by experience. At the level of auditory cortex (ACtx), such influences exhibit at multiple scales from single neurons to cortical columns to topographic maps, and are known to be linked with critical processes such as auditory perception, learning, and memory. How the ACtx integrates a wealth of diverse inputs while supporting adaptive and reliable sound representations is an important unsolved question in auditory neuroscience. This dissertation tackles this question using the mouse as an animal model. We begin by describing a detailed functional map of receptive fields within the mouse ACtx. Focusing on the frequency tuning properties, we demonstrated a robust tonotopic organization in the core ACtx fields (A1 and AAF) across cortical layers, neural signal types, and anesthetic states, confirming the columnar organization of basic sound processing in ACtx. We then studied the bottom-up input to ACtx columns by optogenetically activating the inferior colliculus (IC), and observed feedforward neuronal activity in the frequency-matched column, which also induced clear auditory percepts in behaving mice. Next, we used optogenetics to study layer 6 corticothalamic neurons (L6CT) that project heavily to the thalamus and upper layers of ACtx. We found that L6CT activation biases sound perception towards either enhanced detection or discrimination depending on its relative timing with respect to the sound, a process that may support dynamic filtering of auditory information. Finally, we optogenetically isolated cholinergic neurons in the basal forebrain (BF) that project to ACtx and studied their involvement in columnar ACtx plasticity during associative learning. In contrast to previous notions that BF just encodes reward and punishment, we observed clear auditory responses from the cholinergic neurons, which exhibited rapid learning-induced plasticity, suggesting that BF may provide a key instructive signal to drive adaptive plasticity in ACtx

Common principles in the lateralization of auditory cortex structure and function for vocal communication in primates and rodents

This review summarizes recent findings on the lateralization of communicative sound processing in the auditory cortex (AC) of humans, non-human primates and rodents. Functional imaging in humans has demonstrated a left hemispheric preference for some acoustic features of speech, but it is unclear to which degree this is caused by bottom-up acoustic feature selectivity or top-down modulation from language areas. Although non-human primates show a less pronounced functional lateralization in AC, the properties of AC fields and behavioural asymmetries are qualitatively similar. Rodent studies demonstrate microstructural circuits that might underlie bottom-up acoustic feature selectivity in both hemispheres. Functionally, the left AC in the mouse appears to be specifically tuned to communication calls, whereas the right AC may have a more 'generalist' role. Rodents also show anatomical AC lateralization, such as differences in size and connectivity. Several of these functional and anatomical characteristics are also lateralized in human AC. Thus, complex vocal communication processing shares common features among rodents and primates. We argue that a synthesis of results from humans, non-human primates and rodents is necessary to identify the neural circuitry of vocal communication processing. However, data from different species and methods are often difficult to compare. Recent advances may enable better integration of methods across species. Efforts to standardize data formats and analysis tools would benefit comparative research and enable synergies between psychological and biological research in the area of vocal communication processing

Cognitive Analysis of Complex Acoustic Scenes

Natural auditory scenes consist of a rich variety of temporally overlapping sounds that originate from multiple sources and locations and are characterized by distinct acoustic features. It is an important biological task to analyze such complex scenes and extract sounds of interest. The thesis addresses this question, also known as the “cocktail party problem” by developing an approach based on analysis of a novel stochastic signal contrary to deterministic narrowband signals used in previous work. This low-level signal, known as the Stochastic Figure-Ground (SFG) stimulus captures the spectrotemporal complexity of natural sound scenes and enables parametric control of stimulus features. In a series of experiments based on this stimulus, I have investigated specific behavioural and neural correlates of human auditory figure-ground segregation. This thesis is presented in seven sections. Chapter 1 reviews key aspects of auditory processing and existing models of auditory segregation. Chapter 2 presents the principles of the techniques used including psychophysics, modeling, functional Magnetic Resonance Imaging (fMRI) and Magnetoencephalography (MEG). Experimental work is presented in the following chapters and covers figure-ground segregation behaviour (Chapter 3), modeling of the SFG stimulus based on a temporal coherence model of auditory perceptual organization (Chapter 4), analysis of brain activity related to detection of salient targets in the SFG stimulus using fMRI (Chapter 5), and MEG respectively (Chapter 6). Finally, Chapter 7 concludes with a general discussion of the results and future directions for research. Overall, this body of work emphasizes the use of stochastic signals for auditory scene analysis and demonstrates an automatic, highly robust segregation mechanism in the auditory system that is sensitive to temporal correlations across frequency channels

Software tool for modelling coding and processing of information in auditory cortex of mice

Autor Markéta Popelová Název práce Software tool for modelling coding and processing of information in auditory cortex of mice Abstrakt Porozumění zpracovávání a kódování informací ve sluchové k·ře (AC) je stále ne- dostatečné. Z několika r·zných d·vod· by bylo užitečné mít výpočetní model AC, například z d·vodu vysvětlení, či ujasnění procesu kódování informací v AC. Prv- ním cílem této práce bylo vytvořit softwarový nástroj (simulátor SUSNOMAC), zaměřený na modelování AC. Druhým cílem bylo navrhnout výpočetní model AC s následujícími vlastnostmi: Izhikevich·v model neuronu, dlouhodobá plasticita ve formě Spike-timing-dependent plasticity (STDP), šestivrstvá architektura, pa- rametrizované typy neuron·, hustota neuron· a pravděpodobnost vzniku synapsí. Navržený model byl testován v desítkách experiment·, s r·znými sadami para- metr· a v r·zných velikostech (až 100 000 neuron· s takřka 21 milióny synapsí). Experimenty byly analyzovány a jejich výsledky srovnány s pozorováním skutečné AC. V práci popisujeme a analyzujeme několik zajímavých pozorování o aktivitě modelované sítě a vzniku tonotopického uspořádání AC. 1Department of Software and Computer Science EducationKatedra softwaru a výuky informatikyMatematicko-fyzikální fakultaFaculty of Mathematics and Physic