Noninvasive fMRI investigation of interaural level difference processing the rat auditory subcortex

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Sequence learning modulates neural responses and oscillatory coupling in human and monkey auditory cortex

Learning complex ordering relationships between sensory events in a sequence is fundamental for animal perception and human communication. While it is known that rhythmic sensory events can entrain brain oscillations at different frequencies, how learning and prior experience with sequencing relationships affect neocortical oscillations and neuronal responses is poorly understood. We used an implicit sequence learning paradigm (an “artificial grammar”) in which humans and monkeys were exposed to sequences of nonsense words with regularities in the ordering relationships between the words. We then recorded neural responses directly from the auditory cortex in both species in response to novel legal sequences or ones violating specific ordering relationships. Neural oscillations in both monkeys and humans in response to the nonsense word sequences show strikingly similar hierarchically nested low-frequency phase and high-gamma amplitude coupling, establishing this form of oscillatory coupling—previously associated with speech processing in the human auditory cortex—as an evolutionarily conserved biological process. Moreover, learned ordering relationships modulate the observed form of neural oscillatory coupling in both species, with temporally distinct neural oscillatory effects that appear to coordinate neuronal responses in the monkeys. This study identifies the conserved auditory cortical neural signatures involved in monitoring learned sequencing operations, evident as modulations of transient coupling and neuronal responses to temporally structured sensory input

Hierarchical Organization in Auditory Cortex of the Cat Using High-Field Functional Magnetic Resonance Imaging

Sensory localization within cortex is a widely accepted and documented principle. Within cortices dedicated to specific sensory information there is further organization. For example, in visual cortices a more detailed functional division and hierarchical organization has been recorded in detail. This organization starts with areas dedicated to analysis of simple visual stimuli. Areas higher in the organization are specialized for processing of progressively more complex stimuli. A similar hierarchical organization has been proposed within auditory cortex and a wealth of evidence supports this hypothesis. In the cat, the initial processing of simple auditory stimuli, such as pure tones, has been well documented in primary auditory cortex (A1) which is also the recipient of the largest projection from the thalamus. This indicates that at least the initial stages of a hierarchy exist within auditory cortex. Until now it has been difficult to investigate the remaining hierarchy in its entirety because of methodological limitations. In the present set of investigations the use of functional magnetic resonance imaging (fMRI) facilitated the investigation of auditory cortex of the cat in its entirety. Results from these investigations support the proposed hierarchy in auditory cortex in the cat with lower cortical areas selectively responding to more simple stimuli while higher areas are progressively more responsive to complex stimuli

MEG, PSYCHOPHYSICAL AND COMPUTATIONAL STUDIES OF LOUDNESS, TIMBRE, AND AUDIOVISUAL INTEGRATION

Natural scenes and ecological signals are inherently complex and understanding of their perception and processing is incomplete. For example, a speech signal contains not only information at various frequencies, but is also not static; the signal is concurrently modulated temporally. In addition, an auditory signal may be paired with additional sensory information, as in the case of audiovisual speech. In order to make sense of the signal, a human observer must process the information provided by low-level sensory systems and integrate it across sensory modalities and with cognitive information (e.g., object identification information, phonetic information). The observer must then create functional relationships between the signals encountered to form a coherent percept. The neuronal and cognitive mechanisms underlying this integration can be quantified in several ways: by taking physiological measurements, assessing behavioral output for a given task and modeling signal relationships. While ecological tokens are complex in a way that exceeds our current understanding, progress can be made by utilizing synthetic signals that encompass specific essential features of ecological signals. The experiments presented here cover five aspects of complex signal processing using approximations of ecological signals : (i) auditory integration of complex tones comprised of different frequencies and component power levels; (ii) audiovisual integration approximating that of human speech; (iii) behavioral measurement of signal discrimination; (iv) signal classification via simple computational analyses and (v) neuronal processing of synthesized auditory signals approximating speech tokens. To investigate neuronal processing, magnetoencephalography (MEG) is employed to assess cortical processing non-invasively. Behavioral measures are employed to evaluate observer acuity in signal discrimination and to test the limits of perceptual resolution. Computational methods are used to examine the relationships in perceptual space and physiological processing between synthetic auditory signals, using features of the signals themselves as well as biologically-motivated models of auditory representation. Together, the various methodologies and experimental paradigms advance the understanding of ecological signal analytics concerning the complex interactions in ecological signal structure

On the role of neuronal oscillations in auditory cortical processing

Although it has been over 100 years since William James stated that everyone knows what attention is , its underlying neural mechanisms are still being debated today. The goal of this research was to describe the physiological mechanisms of auditory attention using direct electrophysiological recordings in macaque primary auditory cortex (A1). A major focus of my research was on the role ongoing neuronal oscillations play in attentional modulation of auditory responses in A1. For all studies, laminar profiles of synaptic activity, (indexed by current source density analysis) and concomitant firing patterns in local neurons (multiunit activity) were acquired simultaneously via linear array multielectrodes positioned in A1. The initial study of this dissertation examined the contribution of ongoing oscillatory activity to excitatory and inhibitory responses in A1 in passive (no task) conditions. Next, the function of ongoing oscillations in modulating the frequency tuning of A1 during an intermodal selective attention oddball task was investigated. The last study was aimed at establishing whether there is a hemispheric asymmetry in the way neuronal oscillations are utilized by attention, corresponding to that noted in humans. The results of the first study indicate that in passive conditions, ongoing oscillations reset by stimulus related inputs modulate both excitatory and inhibitory components of local neuronal ensemble responses in A1. The second set of experiments demonstrates that this mechanism is utilized by attention to modulate and sharpen frequency tuning. Finally, we show that as in humans, there appears to be a specialization of left A1 for temporal processing, as signified by greater temporal precision of neuronal oscillatory alignment. Taken together these results underline the importance of neuronal oscillations in perceptual processes, and the validity of the macaque monkey as a model of human auditory processing

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

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