A Generalized Linear Model for Estimating Spectrotemporal Receptive Fields from Responses to Natural Sounds

In the auditory system, the stimulus-response properties of single neurons are often described in terms of the spectrotemporal receptive field (STRF), a linear kernel relating the spectrogram of the sound stimulus to the instantaneous firing rate of the neuron. Several algorithms have been used to estimate STRFs from responses to natural stimuli; these algorithms differ in their functional models, cost functions, and regularization methods. Here, we characterize the stimulus-response function of auditory neurons using a generalized linear model (GLM). In this model, each cell's input is described by: 1) a stimulus filter (STRF); and 2) a post-spike filter, which captures dependencies on the neuron's spiking history. The output of the model is given by a series of spike trains rather than instantaneous firing rate, allowing the prediction of spike train responses to novel stimuli. We fit the model by maximum penalized likelihood to the spiking activity of zebra finch auditory midbrain neurons in response to conspecific vocalizations (songs) and modulation limited (ml) noise. We compare this model to normalized reverse correlation (NRC), the traditional method for STRF estimation, in terms of predictive power and the basic tuning properties of the estimated STRFs. We find that a GLM with a sparse prior predicts novel responses to both stimulus classes significantly better than NRC. Importantly, we find that STRFs from the two models derived from the same responses can differ substantially and that GLM STRFs are more consistent between stimulus classes than NRC STRFs. These results suggest that a GLM with a sparse prior provides a more accurate characterization of spectrotemporal tuning than does the NRC method when responses to complex sounds are studied in these neurons

Age-related Changes in Auditory Cortex Without Detectable Peripheral Alterations: A Multi-level Study in Sprague–Dawley Rats

International audienceAging is often considered to affect both the peripheral (i.e. the cochlea) and central (brainstem and thalamus-cortex) auditory systems. We investigated the effects of aging on the cochlea, brainstem and cortex of female Sprague-Dawley rats. The auditory nerve threshold remained stable between the ages of nine and 21 months, as did distortion product otoa-coustic emissions and the number of ribbon synapses between inner hair cells and nerve fibers. The first clear signs of aging appeared in the brainstem, in which response amplitude decreased, with thresholds remaining stable until the age of 15 months, and increasing slightly thereafter. The responses of primary auditory cortex neurons revealed specific effects of aging: at 21 months, receptive fields were spectrally narrower and the temporal reliability of responses to communication sounds was lower. However, aging had a null or even positive effect on neuronal responses in the presence of background noise, responses to amplitude-modulated sounds, and responses in gap-detection protocols. Overall, inter-animal variability remained high relative to the variability across groups of different ages, for all parameters tested. Beha-vioral performance for the modulation depth of amplitude modulation noise was worse in 21-month old animals than in other animals. Age-related alterations of cortical and behavioral responses were thus observed in animals displaying no signs of aging at the peripheral level. These results suggest that intrinsic, central aging effects can affect the perception of acoustic stimuli independently of the effects of aging on peripheral receptors

Encoding of Ultrasonic Communication Signals in Rat Auditory Cortex

All social animals require a means of communication, and for many species that need is filled by the use of vocalizations. While far less intricate than human speech, many animals employ systems of vocalizations in order to attract mates, convey information about the environment, or to express an emotional state. One such animal is the rat, which communicates via a set of ultra-sonic vocalizations (USVs) in the 50kHz frequency range. These USVs have a conveniently simple structure, making them easy to synthesize and modify. The rat thus provides an excellent model system with which to probe the processing and encoding of such communication signals in the mammalian brain. In the studies contained within this work we take several novel steps in the investigation of rat vocalizations, and in the study of auditory objects in general. We develop a novel system for parameterizing, purifying, and modifying rat USVs. We model neural responses to USVs, and show that a simple model based on frequency modulation outperforms a more traditional, spectral-based model. We study how neurons in the auditory cortex react to shifts in the statistical structure of USVs, and find evidence that the primary auditory cortex is specialized for the temporal structure of natural vocalizations. We go on to examine the degree to which neural representations of USVs are invariant to small transformations of the USVs, and find evidence that this invariance is greater in the higher brain area SRAF, than in the lower brain area A1. Finally, we develop and implement an experimental system that allows us to probe a rat\u27s perception of a stimulus by examining the rat\u27s behavioral reactions

Cortical And Subcortical Mechanisms For Sound Processing

The auditory cortex is essential for encoding complex and behaviorally relevant sounds. Many questions remain concerning whether and how distinct cortical neuronal subtypes shape and encode both simple and complex sound properties. In chapter 2, we tested how neurons in the auditory cortex encode water-like sounds perceived as natural by human listeners, but that we could precisely parametrize. The stimuli exhibit scale-invariant statistics, specifically temporal modulation within spectral bands scaled with the center frequency of the band. We used chronically implanted tetrodes to record neuronal spiking in rat primary auditory cortex during exposure to our custom stimuli at different rates and cycle-decay constants. We found that, although neurons exhibited selectivity for subsets of stimuli with specific statistics, over the population responses were stable. These results contribute to our understanding of how auditory cortex processes natural sound statistics. In chapter 3, we review studies examining the role of different cortical inhibitory interneurons in shaping sound responses in auditory cortex. We identify the findings that support each other and the mechanisms that remain unexplored. In chapter 4, we tested how direct feedback from auditory cortex to the inferior colliculus modulated sound responses in the inferior colliculus. We optogenetically activated or suppressed cortico-collicular feedback while recording neuronal spiking in the mouse inferior colliculus in response to pure tones and dynamic random chords. We found that feedback modulated sound responses by reducing sound selectivity by decreasing responsiveness to preferred frequencies and increasing responsiveness to less preferred frequencies. Furthermore, we tested the effects of perturbing intra-cortical inhibitory-excitatory networks on sound responses in the inferior colliculus. We optogenetically activated or suppressed parvalbumin-positive (PV) and somatostatin-positive (SOM) interneurons while recording neuronal spiking in mouse auditory cortex and inferior colliculus. We found that modulation of neither PV- nor SOM-interneurons affected sound-evoked responses in the inferior colliculus, despite significant modulation of cortical responses. Our findings imply that cortico-collicular feedback can modulate responses to simple and complex auditory stimuli independently of cortical inhibitory interneurons. These experiments elucidate the role of descending auditory feedback in shaping sound responses. Together these results implicate the importance of the auditory cortex in sound processing

SENSORY AND PERCEPTUAL CODES IN CORTICAL AUDITORY PROCESSING

A key aspect of human auditory cognition is establishing efficient and reliable representations about the acoustic environment, especially at the level of auditory cortex. Since the inception of encoding models that relate sound to neural response, three longstanding questions remain open. First, on the apparently insurmountable problem of fundamental changes to cortical responses depending on certain categories of sound (e.g. simple tones versus environmental sound). Second, on how to integrate inner or subjective perceptual experiences into sound encoding models, given that they presuppose existing, direct physical stimulation which is sometimes missed. And third, on how does context and learning fine-tune these encoding rules, as adaptive changes to improve impoverished conditions particularly important for communication sounds. In this series, each question is addressed by analysis of mappings from sound stimuli delivered-to and/or perceived-by a listener, to large-scale cortically-sourced response time series from magnetoencephalography. It is first shown that the divergent, categorical modes of sensory coding may unify by exploring alternative acoustic representations other than the traditional spectrogram, such as temporal transient maps. Encoding models of either of artificial random tones, music, or speech stimulus classes, were substantially matched in their structure when represented from acoustic energy increases –consistent with the existence of a domain-general common baseline processing stage. Separately, the matter of the perceptual experience of sound via cortical responses is addressed via stereotyped rhythmic patterns normally entraining cortical responses with equal periodicity. Here, it is shown that under conditions of perceptual restoration, namely cases where a listener reports hearing a specific sound pattern in the midst of noise nonetheless, one may access such endogenous representations in the form of evoked cortical oscillations at the same rhythmic rate. Finally, with regards to natural speech, it is shown that extensive prior experience over repeated listening of the same sentence materials may facilitate the ability to reconstruct the original stimulus even where noise replaces it, and to also expedite normal cortical processing times in listeners. Overall, the findings demonstrate cases by which sensory and perceptual coding approaches jointly continue to expand the enquiry about listeners’ personal experience of the communication-rich soundscape

Influences of behavioral state and developmental vocal learning on neural coding in the songbird auditory system

Vocal communicators such as humans and songbirds rely on their auditory systems to learn, recognize, and encode acoustic features of communication vocalizations. Yet it remains unclear how varying behavioral, experimental, and developmental contexts impact neural coding in the songbird auditory system. In this dissertation I demonstrate that experimental and behavioral contexts relating to arousal are sufficient to alter neural excitability in a way that has implications for neural coding in the songbird auditory system. First I show that urethane, a common anesthetic used in neurophysiological studies of songbird and mammalian auditory neurons, suppresses neural excitability but does not alter spectrotemporal tuning or neural discrimination in single auditory midbrain neurons. Next, I demonstrate that neurons in the songbird primary auditory cortical region Field L are sensitive to local concentrations of norepinephrine, a neurotransmitter involved mediating changes in arousal and behavioral state. Lastly, I report the results of a developmental study that demonstrates experience-dependent changes in temporal and spectral tuning in songbird auditory cortical neurons during vocal learning. These developmental effects were found to have region and cell-type specificity, and highlight potential functional roles for dorsal and ventral auditory cortical neurons in the songbird auditory cortex. The findings reported here have important implications for future studies into the neurophysiology of vocal learning

Frequency selectivity measured both psychophysically and physiologically

The ability to resolve the individual frequency components of a complex sound is known as frequency selectivity. The auditory system seems to act as a series of overlapping band-pass filters or auditory filters (AF), the width of which describe frequency selectivity. It is a fundamental and extensively studied property of the auditory system, yet its neural basis is not fully understood. This is due, in part, to the fact that two distinct approaches are taken to explore it; psychophysics and physiology, the results of which are difficult to reconcile. AF are measured in quite different ways in the two sub-fields. Psychophysics measures the ability of the system as a whole by using masking paradigms to measure the bandwidth of AF from behavioural data. A preferred method in human psychophysics is notched noise (NN) masking using forward masking with fixed signal level, since it does not suffer from confounds like suppression and off-frequency listening. In physiology bandwidth can be measured for single cells, or a population of cells, at various levels of the auditory system, and is traditionally done by observing the number of action potentials elicited in response to pure tone stimuli. The auditory system is known to be highly non-linear and so comparing the results of such vastly different approaches is problematic. Also, psychophysics measures the detection threshold of 'signal' sounds; how this compares to mean spike rates used in physiology is not clear. Attempts have been made in the past to apply the same method in animals to measure both psychophysical and physiological bandwidths, with varying degree of success. No successful attempt has been made to use an up-to-date method used in human psychophysics. In this thesis I take a step towards comparing psychophysical and physiological results by 1) developing a novel method that allows forward masked NN bandwidths to be measured behaviourally in the ferret, and 2) applying the same psychophysical paradigm to measuring bandwidth in guinea pig inferior colliculus (IC) and primary auditory cortex (A1) neurons. In addition a signal detection theory (SDT) approach is used on the physiological data to make results more comparable to psychophysical ones. Results from the behavioural method show that it can be used to successfully measure both forward and simultaneously masked NN bandwidths in the same animal, and that these measurements are in close agreement with one another and with bandwidths measured using previous methods. Results from the guinea pig physiology study show that bandwidths measured from IC neurons using the psychophysical NN paradigm are narrower than pure tone estimates of bandwidth, in the same neurons. However, the NN estimates are in close agreement with auditory peripheral and perceptual bandwidths, a finding which differs substantially from previous studies. Unexpectedly, however, bandwidths estimated from A1 neurons using masking show much finer tuning at high frequencies than seen further down the auditory system. This tuning is not only narrower than pure tone tuning in these neurons, but also finer than psychophysically measured estimates, which represent the auditory system as a whole. However, this may be related to the greater non-linearity of cortical neurons compared with those in the midbrain and lower. This work demonstrates that it is possible to reconcile different measurements of tuning in the auditory system by using appropriate methods. It also highlights the complex nature of auditory neurons and how care must be taken when measuring frequency selectivity using different approaches. In addition it provides a method for measuring auditory bandwidths psychophysically and physiologically in the same animal, allowing a direct comparison between the two; a vital step in investigating the neural basis of perceptual frequency selectivity

Neural mechanisms of auditory scene analysis in a non-mammalian animal model

University of Minnesota Ph.D. dissertation. September 2014. Major: Neuroscience. Advisor: Mark A. Bee. 1 computer file (PDF); iv, 178 pages, appendices 1-2.Healthy auditory systems perform well in quiet places where there are no overlapping sounds, but are greatly challenged in noisy environments. In these environments, all of the sounds in the "acoustic scene" combine to create a single waveform that impinges on the receiver's ear, from which the auditory system must extract some meaningful signal. A particular example of this auditory scene analysis occurs in multi-talker environments, where the acoustic scene consists of the overlapping sounds of competing signalers. The problem of communicating in multi-talker environments has been well-studied in the human hearing literature, where it is known as the cocktail party problem, but it is not unique to humans. Many non-human animals also encounter noisy social environments and have evolved to solve cocktail-party-like problems of vocal communication. However, the mechanisms that humans and other animals use to solve the problem may differ. While human and other vertebrate auditory systems share ancestral traits from their most recent common ancestor, there is evidence for divergence of auditory systems between the separate tetrapod lineages. The independent evolution of auditory systems suggests that vertebrates may have evolved ta diversity of novel solutions to cocktail-party-like problems. Traditionally, research into similar problems in other non-human animals has been limited. The aim of my dissertation research was to investigate mechanisms that enable a non-mammalian vertebrate, specifically a frog, to navigate noisy, multi-signaler environments

Frequency selectivity measured both psychophysically and physiologically

The ability to resolve the individual frequency components of a complex sound is known as frequency selectivity. The auditory system seems to act as a series of overlapping band-pass filters or auditory filters (AF), the width of which describe frequency selectivity. It is a fundamental and extensively studied property of the auditory system, yet its neural basis is not fully understood. This is due, in part, to the fact that two distinct approaches are taken to explore it; psychophysics and physiology, the results of which are difficult to reconcile. AF are measured in quite different ways in the two sub-fields. Psychophysics measures the ability of the system as a whole by using masking paradigms to measure the bandwidth of AF from behavioural data. A preferred method in human psychophysics is notched noise (NN) masking using forward masking with fixed signal level, since it does not suffer from confounds like suppression and off-frequency listening. In physiology bandwidth can be measured for single cells, or a population of cells, at various levels of the auditory system, and is traditionally done by observing the number of action potentials elicited in response to pure tone stimuli. The auditory system is known to be highly non-linear and so comparing the results of such vastly different approaches is problematic. Also, psychophysics measures the detection threshold of 'signal' sounds; how this compares to mean spike rates used in physiology is not clear. Attempts have been made in the past to apply the same method in animals to measure both psychophysical and physiological bandwidths, with varying degree of success. No successful attempt has been made to use an up-to-date method used in human psychophysics. In this thesis I take a step towards comparing psychophysical and physiological results by 1) developing a novel method that allows forward masked NN bandwidths to be measured behaviourally in the ferret, and 2) applying the same psychophysical paradigm to measuring bandwidth in guinea pig inferior colliculus (IC) and primary auditory cortex (A1) neurons. In addition a signal detection theory (SDT) approach is used on the physiological data to make results more comparable to psychophysical ones. Results from the behavioural method show that it can be used to successfully measure both forward and simultaneously masked NN bandwidths in the same animal, and that these measurements are in close agreement with one another and with bandwidths measured using previous methods. Results from the guinea pig physiology study show that bandwidths measured from IC neurons using the psychophysical NN paradigm are narrower than pure tone estimates of bandwidth, in the same neurons. However, the NN estimates are in close agreement with auditory peripheral and perceptual bandwidths, a finding which differs substantially from previous studies. Unexpectedly, however, bandwidths estimated from A1 neurons using masking show much finer tuning at high frequencies than seen further down the auditory system. This tuning is not only narrower than pure tone tuning in these neurons, but also finer than psychophysically measured estimates, which represent the auditory system as a whole. However, this may be related to the greater non-linearity of cortical neurons compared with those in the midbrain and lower. This work demonstrates that it is possible to reconcile different measurements of tuning in the auditory system by using appropriate methods. It also highlights the complex nature of auditory neurons and how care must be taken when measuring frequency selectivity using different approaches. In addition it provides a method for measuring auditory bandwidths psychophysically and physiologically in the same animal, allowing a direct comparison between the two; a vital step in investigating the neural basis of perceptual frequency selectivity