Rachel K. Clifton - US grants

A series of experiments will investigate adults' perception of an auditory phenomenon known as the precedence effect. The precedence effect occurs when two identical sounds are delivered from two spatial locations (e.g., two loudspeakers), with the onset of one leading the other by a few thousandths of a second. The listener localizes the sound solely at the leading location and does not hear the sound at the lagging location at all. When the time delay between onsets is increased, the echo threshold is reached and the lagging sound is heard as an echo. The precedence effect is due to the nervous system's active suppression of the echoes. These experiments will be directed toward establishing the conditions under which this suppression breaks down. Previous work has shown that a sudden switch in the location of leading and lagging sound will break down the suppression. These experiments will explore whether the presence of the echo before the switch is necessary and whether only the leading (or lagging) sound being changed in location is sufficient to break the suppression. Acoustic characteristics of the sound, such as intensity and frequency, will be varied to determine how they affect suppression. Inhibition of echoes is a critical feature of everyday listening in normal settings. Without echo suppression, it would be very difficult to detect the original source of a sound, leading to confusion of sound sources. Because the precedence effect is an inhibitory process of the central nervous system, brain damage produced by lesions or strokes could impair a person's ability to localize sound. Better understanding of the precedence effect and the stimulus conditions affecting it has relevance for theories of binaural hearing and has practical implications for patients with damage in the auditory areas of the brain.

CDA-9703217 Grupen, Roderic A. University of Massachusetts A Facility for Cross Disciplinary Research on Sensorimotor Development in Humans and Machines This award is for supporting research activities in Computer Science and Psychology at UMass in assembling an infrastructure for experimental work on the development of conceptual structure from sensorimotor activity. An interactionist theory is advanced in which the origin of knowledge is interactive behavior in an environment. By this account, the nature of the environment and the agent's native resources (sensors, effectors, and control) lead directly to appropriate conceptual structures in natural and artificial systems. The central claim of this research is that the first task facing an intelligent, embodied agent is coordinated sensory and motor interaction with its environment and that this task leads to policies and abstractions that influence the subsequent acquisition of higher cognitive abilities. An interdisciplinary team specializing in robotics, cognitive development, and motor development, learning, planning and language lead the effort. The infrastructure incorporates robot hands and arms, binocular vision, binaural audition, haptic and kinesthetic information in a common framework to provide a rich sensory and motor encoding of interaction with the world. In addition to the robotics facilities, the infrastructure includes tools for gathering precise, quantitative observations of postures and rates of movement in human subjects. These facilities are designed to support analogs of nontrivial human processes so that computational models of development may be compared to data from infant subjects.

This project is being funded through the Learning and Intelligent Systems (LIS) initiative. A key aim of this initiative is to understand how highly complex intelligent systems could arise from simple initial knowledge through interactions with the environment. The best real-world example of such a system is the human infant who progresses from relatively simple abilities at birth to quite sophisticated abilities by two-years-of-age. This research focuses on the development of reaching by infants because (a) only rudimentary reaching ability is present at birth; (b) older infants use their arms in a sophisticated way to exploit and explore the world; and (c) the problems facing the infant are similar to those an artificial system would face. The project brings together two computer scientists who are experts on learning control algorithms and neural networks, and two psychologists who are experts on the behavioral and neural aspects of infant reaching, to investigate and test various algorithms by which infants might gain control over their arms. The proposed research focuses on the control strategies that infants use in executing reaches, how infants develop appropriate and adaptive modes of reaching, the mechanisms by which infants improve their ability to reach with age, the role of sensory information in controlling the reach, and how such knowledge might be stored in psychologically appropriate and computationally powerful ways. Preliminary results suggest that computational models that are appropriate for modeling the development of human reaching are different in significant ways from traditional computational models. Understanding the mechanisms by which intelligence can develop through learning can have significant impact in many scientific and engineering domains because the ability to build such systems would be simpler and faster than engineering a system with the intelligence specified by the engineer and because systems based on interactive learning could rapidly adapt to changing environmental conditions.