A Multi-scale Perspective on the Neurobiology of Auditory Scene Analysis A.
Aims and Significance Despite the enormous advances in computing technology over the last decades, there are stills many tasks that are easy for a child, yet difficult for advanced computer systems. A particular challenge to most existing systems is dealing with complex acoustic environments, background noises and competing talkers: A challenge often experienced in cocktail parties (Cherry, 1953) and formally referred to as auditory scene analysis (Bregman, 1990). Progress in this field has tremendous implications and long- term benefits covering the medical, industrial, military and robotics domains;as well as improving communication aids (hearing aids, cochlear implants, speech-based human-computer interfaces) for the sensory-impaired and aging brains. Despite its importance for both engineering and perceptual sciences, the study of the neural underpinnings of auditory scene analysis remains in its infancy. This field is particularly challenged by the lack of integrative theories which incorporate our knowledge of the perceptual bases of scene analysis with the neural mechanisms along various stages of the auditory pathway. Because of the nature of the problem, the neural circuitry at play is intricate and multi-scale by design. The objective of the proposed research is to provide a systems view to modeling scene analysis which integrates mechanisms at the single neuron level, population level and across area interactions. The intellectual merit of the proposed theory is to elucidate the specific mechanisms and computational rules at play;facilitate its integration in engineering systems and enable generating novel testable predictions. The proposal investigates the key hypothesis that attention to a feature of a complex sound instantiates all elements that are coherent with this feature, thus binding them together as one perceptual "object" or stream. This "binding hypothesis" requires three scales of analyses: a micro-level mapping of complex sounds into a multidimensional cortical feature representation;a meso-level coherence analysis correlating activity in populations of cortical neurons;and macro-level feedback processes of attention and expectations that mediate auditory object formation. We shall formulate this hypothesis within a multi-scale computational framework that provides a unified theory for the neural underpinnings of auditory scene analysis. The three core research aims of this project explore all facets of this model employing computational and physiological approaches:
Aim I. A multi-scale coherence model: The main goal is to formulate the "binding hypothesis" as a unified biologically plausible theory of auditory streaming, integrating multi-scale sensory with cognitive cortical mechanisms. This computational effort will incorporate findings from experiments in Aims II and III, generate testable predictions, as well as provide effective algorithmic implementations to tackle the "cocktail party problem" in biomedical applications;
Aim II. Physiological investigations of the multi-scale coherence theory:
Our aim i s to use an animal model to record single-unit (micro-level, meso-level) and across area (macro-level) physiological activity in both primary auditory and prefrontal cortex, while presenting sufficiently complex acoustic environments so as to test and refine the computational model;
Aim III. Refinement of the coherence theory with physiological and perceptual testing in humans: The objective is to directly test predictions from the model in human subjects, using magnetoencephalography (MEG) and psychoacoustic experiments. We shall particularly focus on the role of cortical mechanisms in scene analysis in normal and aging brains. The proposed research draws upon the expertise of a cross-disciplinary team integrating neurobiology and engineering. It is unique in that it is the first effort to postulate a role for coherence in the scene analysis problem, and to investigate the "binding hypothesis" integrating cortical and attention mechanisms in auditory streaming experiments. In addition, by testing the theory directly on human subjects and comparing normal and aging brains (known to face perceptual difficulties in cocktail party settings), we hope to better understand the neural underpinnings of scene analysis under their normal and malfunctioning states, hence enhancing the translational potential of the model. The broader impact of this effort is to provide versatile and tractable models of auditory stream segregation, significantly facilitating the integration of such capabilities in engineering systems.

Public Health Relevance

Overcoming the Cocktail Party Problem: A Multi-scale Perspective on the Neurobiology of Auditory Scene Analysis Project Relevance: The question of how complex acoustic scenes are parsed by the auditory system into auditory objects and streams is one of the most fundamental questions in perceptual science. Despite its importance, the study of its underlying neural mechanisms remains in its infancy. We believe that significant progress in this area can be achieved by combining sophisticated computational modeling and psychophysical techniques with recently available methods for neural recording from awake behaving animals in interdisciplinary efforts, such as the one described in this proposal. In addition, by testing the theory directly on human subjects and comparing normal and aging brains (known to face perceptual difficulties in cocktail party settings), we hope to better understand the neural underpinnings of scene analysis under their normal and malfunctioning states, hence enhancing the translational potential of the model. The broader impact of this effort is to provide versatile and tractable models of auditory stream segregation, significantly facilitating the integration of such capabilities in engineering systems;as well as improving communication aids (hearing aids, cochlear implants, speech-based human-computer interfaces) for the sensory-impaired and aging brains.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Research Project (R01)
Project #
5R01AG036424-04
Application #
8477104
Study Section
Modeling and Analysis of Biological Systems Study Section (MABS)
Program Officer
Chen, Wen G
Project Start
2010-06-01
Project End
2015-05-31
Budget Start
2013-06-01
Budget End
2014-05-31
Support Year
4
Fiscal Year
2013
Total Cost
$398,608
Indirect Cost
$85,276
Name
Johns Hopkins University
Department
Engineering (All Types)
Type
Schools of Engineering
DUNS #
001910777
City
Baltimore
State
MD
Country
United States
Zip Code
21218