State-dependent Representation of Sound by Neural Population Activity in Auditory Cortex PDF Download

Author: Charles R. Heller
Publisher:
ISBN:
Category : Arousal (Physiology)
Languages : en
Pages : 220

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Author: Stephan Marguet
Publisher:
ISBN:
Category : Auditory evoked response
Languages : en
Pages : 133

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Cortical information processing depends critically on an animal's brain state. Previous research has revealed there is a great deal of variability in cortical responses to repeated stimuli. This thesis addresses the question of whether activity and response variability in rat auditory cortex depends on brain state. Specifically, we hypothesized that both spontaneous and evoked activity differ between states; furthermore that cortical responses in higher-frequency "desynchronized" EEG states would be less variable and follow sensory input up to higher temporal modulation frequencies. We first assessed the spontaneous activity of auditory cortex during silence. During synchronized "slow wave" EEG states the spike counts of individual neurons in sequential time bins were irregular, but this irregular firing was coordinated across the neural population. Spike counts were more regular following a tail pinch-induced shift to higher-frequency EEG, and the population-wide coordination disappeared. We also uncovered a set of high-firing neurons with independent, rhythmic activity during desynchronized states, peaking between 8 to 18 Hz. Next we characterized responses to loud single-click stimuli. Many neurons discharged short-latency spikes with similar latency across states. These preserved spike latencies manifested as brief, sub-50ms population sequences of activity with similar profiles in different brain states. In some experiments we observed late, long-lasting effect of clicks on firing rates in synchronized states. In our last study, we show that evoked local field potentials (LFPs) can follow high-frequency amplitude modulations of broadband noise during desynchronized regimes. Spikes also track input more reliably and can be better predicted from stimuli in desynchronized states than in slow-wave states. Finally, we address whether LFPs reliably predict neural activity, and show that in most cases LFPs explain more spiking variability than our amplitude-modulated white noise stimuli. Thus much 'noise' in neural responses is not cell-specific, but reflects a source shared across many cells; such variability is state-dependent, and can be accounted for by LFP dynamics. Our first studies demonstrate that despite clear changes in spontaneous activity, strong onset responses to discrete broadband stimuli are often preserved across states. The final study suggests the desynchronized state supports improved representation of temporally modulated stimuli in auditory cortex.

Author: Jan Schnupp
Publisher: MIT Press
ISBN: 0262518023
Category : Medical
Languages : en
Pages : 367

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Book Description
An integrated overview of hearing and the interplay of physical, biological, and psychological processes underlying it. Every time we listen—to speech, to music, to footsteps approaching or retreating—our auditory perception is the result of a long chain of diverse and intricate processes that unfold within the source of the sound itself, in the air, in our ears, and, most of all, in our brains. Hearing is an "everyday miracle" that, despite its staggering complexity, seems effortless. This book offers an integrated account of hearing in terms of the neural processes that take place in different parts of the auditory system. Because hearing results from the interplay of so many physical, biological, and psychological processes, the book pulls together the different aspects of hearing—including acoustics, the mathematics of signal processing, the physiology of the ear and central auditory pathways, psychoacoustics, speech, and music—into a coherent whole.

Author: Jeffery A. Winer
Publisher: Springer Science & Business Media
ISBN: 1441900748
Category : Science
Languages : en
Pages : 711

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Book Description
There has been substantial progress in understanding the contributions of the auditory forebrain to hearing, sound localization, communication, emotive behavior, and cognition. The Auditory Cortex covers the latest knowledge about the auditory forebrain, including the auditory cortex as well as the medial geniculate body in the thalamus. This book will cover all important aspects of the auditory forebrain organization and function, integrating the auditory thalamus and cortex into a smooth, coherent whole. Volume One covers basic auditory neuroscience. It complements The Auditory Cortex, Volume 2: Integrative Neuroscience, which takes a more applied/clinical perspective.

Author: Jeffery A. Winer
Publisher: Springer Science & Business Media
ISBN: 0387270833
Category : Science
Languages : en
Pages : 720

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Book Description
Connecting the auditory brain stem to sensory, motor, and limbic systems, the inferior colliculus is a critical midbrain station for auditory processing. Winer and Schreiner's The Inferior Colliculus, a critical, comprehensive reference, presents the current knowledge of the inferior colliculus from a variety of perspectives, including anatomical, physiological, developmental, neurochemical, biophysical, neuroethological and clinical vantage points. Written by leading researchers in the field, the book is an ideal introduction to the inferior colliculus and central auditory processing for clinicians, otolaryngologists, graduate and postgraduate research workers in the auditory and other sensory-motor systems.

Author: James McClure Jeanne
Publisher:
ISBN: 9781267169013
Category :
Languages : en
Pages : 108

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The ability to learn to recognize new sensory signals such as voices or faces is an important cognitive function in many species. This ability is thought to involve the plasticity of neural representations in high-level sensory cortical areas, but this plasticity is poorly understood. Using European starlings (a species of songbird) trained to recognize natural conspecific song segments, I investigated the emergence of neural representations for learned signals across two auditory forebrain regions : the caudolateral mesopallium (CLM) and the caudomedial mesopallium (CMM). In both CLM and CMM, neurons encoded more information about the motifs (short, stereotyped segments of song) that make up songs paired with reward during training than the motifs that make up novel songs. This shows that behavioral experience is an important modulator of neural encoding in the songbird auditory forebrain. In the natural world, individuals learn which signals convey relevant information for particular behaviors. However, it is unknown how this behavioral information influences neural encoding in the brain. I explored this by training starlings on a paired-motif recognition task where one motif was informative about the behavior required to obtain reward and the other motif was not informative. Following training, single neurons in CLM responded more strongly to informative motifs than to uninformative or novel motifs, whereas single neurons in CMM responded strongly to both informative and uninformative motifs. This suggests that encoding in CLM may serve to emphasize those signals that are particularly behaviorally relevant. Sensory encoding in cortical areas is distributed across many neurons. But how learning alters these neural population representations remains unexplored. To explore this question, I analyzed the correlated activity of simultaneously recorded neurons within CLM. When processing informative motifs, the correlations led to enhanced population discriminability, relative to the correlations when processing uninformative or novel motifs. Thus, the information that a sensory signal conveys about behavior modulates neural encoding in both single neurons and in neural populations. Collectively, these studies demonstrate that behavioral relevance substantially influences neural processing by both single neurons and larger populations in cortical brain regions.

Author: David R. Moore
Publisher: Oxford University Press, USA
ISBN: 0199233284
Category : Medical
Languages : en
Pages : 592

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Book Description
Volume 1: The Ear (edited by Paul Fuchs) Volume 2: The Auditory Brain (edited by Alan Palmer and Adrian Rees) Volume 3: Hearing (edited by Chris Plack) Auditory science is one of the fastest growing areas of biomedical research. There are now around 10,000 researchers in auditory science, and ten times that number working in allied professions. This growth is attributable to several major developments: Research on the inner ear has shown that elaborate systems of mechanical, transduction and neural processes serve to improve sensitivity, sharpen frequency tuning, and modulate response of the ear to sound. Most recently, the molecular machinery underlying these phenomena has been explored and described in detail. The development, maintenance, and repair of the ear are also subjects of contemporary interest at the molecular level, as is the genetics of hearing disorders due to cochlear malfunctions.

Author: Jessica Liberty Sackville Hamilton
Publisher:
ISBN:
Category :
Languages : en
Pages : 104

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Book Description
The brain contains neurons of many different types interacting in complex functional circuits. To process sensory information these cells work in concert to form representations of the external world. In the auditory cortex, this involves integrating information from different cell types across an orderly anatomical structure of layers and columns. Representations can be observed at the level of single cells, cortical microcircuits, and large-scale sensory maps. The relationship between single cell properties and circuits within the auditory cortex, however, is still poorly understood. Furthermore, the structure-function relationships uncovered by neuroscientific study may crucially depend on the stimuli used to probe the system. This thesis brings together work from each of these different levels to describe how sounds are represented in the cortex, how this representation changes with experience, and how different cells contribute to cortical representation. First, I describe how the statistics of sound stimuli influence response properties in the mouse primary auditory cortex by comparing responses to pure tones and natural sounds (ultrasonic vocalizations). I also compare these responses to a temporally reversed vocalization to determine whether a sound with similar spectrotemporal content but no ethological relevance is represented similarly. When comparing pure tones and vocalizations, I find that the temporal response properties are similar, but that spectral response properties (e.g. frequency selectivity) often differ substantially. In particular, there are multiple sites that responded to vocalizations with frequency content outside their classical tone-derived receptive field, suggesting some specificity for behaviorally relevant sounds. When comparing forward and backward vocalizations, temporal responses are similar, but frequency bandwidth and characteristic frequency differs significantly across the population. Thus, the behaviorally relevant sound appears to be represented differently from non-behaviorally relevant synthetic and naturalistic sounds. The response properties of auditory neurons are not fixed, but rather depend on experience. In the next study, I examine how exposure to pulsed noise during different sensitive windows of the auditory critical period affects single site properties as well as circuit-level dynamics. On the single site level, I find that early exposure to pulsed noise increases receptive field thresholds and decreases frequency selectivity, while late noise exposure increases frequency bandwidths as well as spontaneous and evoked firing rates. To describe changes in functional microcircuits, I use the Ising model, which describes pairwise interactions between simultaneously recorded sites in the auditory cortex as well as interactions between sites and the stimuli that modulate them. I find that early noise exposure decreases stimulus drive, whereas late noise exposure does not change the strength of sound inputs but rather decreases the spread of functional connections from the deep to the superficial layers across sites with different frequency selectivity. Finally, I use a combination of optogenetic tools and computational methods to describe how the activity of a specific class of inhibitory neurons affects network connectivity in the auditory cortex. I examine the contribution of parvalbumin-positive (PV+) inhibitory interneurons, which make up around half of the inhibitory neurons in the cortex. These neurons are known to be involved in the generation of gamma oscillations, and their maturation corresponds with the end of the auditory critical period for plasticity. Using Ising models in tandem with linear-nonlinear vector autoregressive models, I show that stimulating PV+ neurons increases feedforward information flow through cortical circuits without changing lateral interactions within the same layers.

Author: Joshua David Downer
Publisher:
ISBN: 9781369310726
Category :
Languages : en
Pages :

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The neural codes that support sensation and perception have been a subject of inquiry in neuroscience for over a century. Up until recently, studies have focused on very simple sensory systems to understand how the nervous system translates incoming sensory information into a neural code. Moreover, these foundational studies tended to ignore the effect of animals’ behavior on such codes. In the last several decades, researchers have made huge strides in understanding not only different manifestations of the neural code, but how these codes can change to suit the ongoing needs to animals. The present work represents new advances in this frontier. We record from groups of single neurons in auditory cortex while animals perform auditory detection tasks, as well as while they sit passively awake. We provide evidence that the adaptive processing of sounds involves not only the changing activity of single neurons, but also the interactions between them. These findings help advance our understanding not only of sound processing, but also of fundamental behaviors, such as carrying on a conversation in a busy restaurant, finding a friend in a crowded airport or tasting and describing the distinct features in a glass of wine. Moreover, we present a framework that can explain not only adaptive sensory processing, but which may also inform novel models of natural computation outside of the brain.

Author: Alexandre Kempf
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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Perceptual objects are the elementary units used by the brain to construct an inner world representation of the environment from multiple physical sources, like light or sound waves. While the physical signals are first encoded by receptors in peripheral organs into neuroelectric signals, the emergence of perceptual object require extensive processing in the central nervous system which is not yet fully characterized. Interestingly, recent advances in deep learning shows that implementing series of nonlinear and linear operations is a very efficient way to create models that categorize visual and auditory perceptual objects similarly to humans. In contrast, most of the current knowledge about the auditory system concentrates on linear transformations. In order to establish a clear example of the contribution of auditory system nonlinearities to perception, we studied the encoding of sounds with an increasing intensity (up ramps) and a decreasing intensity (down ramps) in the mouse auditory cortex. Two behavioral tasks showed evidence that these two sounds are perceived with unequal salience despite carrying the same physical energy and spectral content, a phenomenon incompatible with linear processing. Recording the activity of large cortical populations for up- and down-ramping sounds, we found that cortex encodes them into distinct sets of non-linear features, and that asymmetric feature selection explained the perceptual asymmetry. To complement these results, we also showed that, in reinforcement learning models, the amount of neural activity triggered by a stimulus (e.g. a sound) impacts learning speed and strategy. Interestingly very similar effects were observed in sound discrimination behavior and could be explain by the amount of cortical activity triggered by the discriminated sounds. This altogether establishes that auditory system nonlinearities have an impact on perception and behavior. To more extensively identify the nonlinearities that influence sounds encoding, we then recorded the activity of around 60,000 neurons sampling the entire horizontal extent of auditory cortex. Beyond the fine scale tonotopic organization uncovered with this dataset, we identified and quantified 7 nonlinearities. We found interestingly that different nonlinearities can interact with each other in a non-trivial manner. The knowledge of these interactions carry good promises to refine auditory processing model. Finally, we wondered if the nonlinear processes are also important for multisensory integration. We measured how visual inputs and sounds combine in the visual and auditory cortex using calcium imaging in mice. We found no modulation of supragranular auditory cortex in response to visual stimuli, as observed in previous others studies. We observed that auditory cortex inputs to visual cortex affect visual responses concomitant to a sound. Interestingly, we found that auditory cortex projections to visual cortex preferentially channel activity from neurons encoding a particular non-linear feature: the loud onset of sudden sounds. As a result, visual cortex activity for an image combined with a loud sound is higher than for the image alone or combine with a quiet sound. Moreover, this boosting effect is highly nonlinear. This result suggests that loud sound onsets are behaviorally relevant in the visual system, possibly to indicate the presence of a new perceptual objects in the visual field, which could represent potential threats. As a conclusion, our results show that nonlinearities are ubiquitous in sound processing by the brain and also play a role in the integration of auditory information with visual information. In addition, it is not only crucial to account for these nonlinearities to understand how perceptual representations are formed but also to predict how these representations impact behavior.