Rick O. Gilmore - US grants

THE DEVELOPMENT OF HEADING PERCEPTION IN INFANCY

Rick O. Gilmore
Department of Psychology
Pennsylvania State University
University Park, PA 16802

When moving around the environment, animals generate a pattern of visual
motion called optic flow. Optic flow provides information about where and
how fast the observer is moving. This information is crucial for safely
moving through the environment. Despite its importance, very little is
known about how the ability to perceive optic flow develops early in life.
This project will examine how young infants develop the ability to
determine which direction they are moving or heading through the
environment. It will examine the role that changes in visual factors, such
as acuity or sensitivity to motion, play in the ability to perceive one's
heading. The project will examine how infants' emerging abilities to crawl
and walk shape their perceptual capacities. The project also will examine
how infants develop the ability to use visual information to maintain
balance and control posture. The results will provide new information
about the development of a perceptual skill that is critical for maintaining
balance, avoiding collisions, and moving safely through the environment.
In turn, the results will lay the groundwork for future research into the
impact of postnatal brain development on other aspects of perceptual and
motor development. Finally, this CAREER project will incorporate educational
activities that will help to train a new generation of students in the
emerging field of developmental

DESCRIPTION (provided by applicant): Despite a vast literature on the habituation of visual attention in infants, there has been very little attention paid to critical questions about the nature of this basic psychological phenomenon. In particular, there has been little research and almost no formal theory concerning the time course of habituation in individual infants. The overarching goal of this research project is to develop and test a statistical model of the habituation process. In doing so, we propose to address the following questions: what is the form of the habituation function? In particular, what function, or suitable family of functions best describes the habituation process in individual infants? How can habituation be rigorously assessed? How can the issue of individual differences in habituation functions be captured within a unified habituation model framework? Do individual infants show distinct "types" of habituation patterns, as has been widely suspected, and how can these be identified rigorously? How can one use information from habituation to improve inference about subsequent performance during the test phase? Our efforts to address these questions will involve developing new techniques for measuring habituation and testing these methods in real time by collecting habituation data from infants and applying the techniques to the resulting data. The development of a model-based approach to infant visual habituation will provide improved tools for equating levels of familiarity among infants, determining when habituation has occurred, rigorously classifying patterns of response in individual infants, and for using habituation data to assess post-habituation responses.

This INSPIRE award is partially funded by the Robust Intelligence (RI) Program in the Division of Information and Intelligent Systems in the Directorate for Computer and Information Science and Engineering, and the Perception, Action and Cognition (PAC) Program in the Division of Behavioral and Cognitive Sciences in the Directorate for Social, Behavioral and Economic Sciences.

This research integrates theoretical, experimental and algorithmic thrusts to construct a novel conceptual framework for predicting and understanding the full range of regularity perception, both in humans, by measuring human brain activation and behavior, and in machines, through a computational framework for adaptive symmetry detection in computer vision. The ability to detect patterns in natural scenes serves critical biological needs while posing substantial computational difficulties for machine intelligence. Research on human and computer perception of pattern regularity has primarily focused on bilateral symmetry, despite a wide variety of regular patterns beyond reflection. A unique feature of the proposed project is to use symmetry group theory as an organizing principle for the study of both human and computer perception of patterns. Symmetry group theory, instantiated by its subgroup hierarchy, provides a formal and exhaustive categorization of all regular patterns.

The project sits at an interdisciplinary nexus between computer science, psychology, neuroscience, and mathematics. The outcomes of this research could potentially transform the theory of human pattern perception and make a quantum leap in robust automatic detection of real world regularities. Because patterns are ubiquitous, this research impacts all information processing systems challenged by large digital datasets that are hard to explore manually. Its impact is strengthened further by a systemic outreach to the respective research communities through interdisciplinary workshops, publications, data sharing, classroom lectures, postdoc and student training. Applications include anomaly detection in medicine and surveillance data; mobile robot localization in man-made environments; and generic pattern indexing and retrieval.

People move. The world we move about in is filled with objects, animals, and other people that also move. Perceiving patterns of visual motion provides humans with information about where they are heading and how fast, and about the kinds of objects, animals, and people in the environment. Scientists have relatively detailed knowledge about how adults perceive motion and how their brains respond to it. But, researchers know very little about how motion perception develops in infancy and childhood, and we know even less about the brain systems that detect and process motion. It appears that both perception and brain activity take many years to mature. So, this project will measure perception and brain activity in infants, school-age children, and adults to describe the patterns of development in detail. This project will also create computer-based models that mimic how the human brain develops. The goal is to understand how motion perception and motion-related brain activity change as humans mature.

Several feature of this project strengthen its intellectual merit: Motion processing contributes to many aspects of perception, cognition, and action; few studies focus on perceptual development from infancy through adulthood; and, the combination of behavior, brain activity and computer-based simulation, promises new insights into a fundamental perceptual system. The project will have broader impacts by leveraging expertise and resources from the existing NSF-funded Center of Excellence for Learning in Education, Science and Technology (CELEST); by focusing on scientific questions important for child safety and normal cognitive and motor development; and by engaging young adults, especially women and individuals from underrepresented groups, in scientific research.

PROJECT SUMMARY The overall goal of the PLAY (Play & Learning Across a Year) project is to catalyze discovery about behavioral development in infancy. PLAY will focus on the critical period from 12 to 24 months of age when infants show remarkable advances in language, object interaction, locomotion, and emotion regulation. PLAY will leverage the joint expertise of 63 ?launch group? researchers, and capitalize on the Databrary video-sharing library and Datavyu video-coding tool to exploit the power of video to reveal the richness and complexity of behavior. Together, PLAY researchers will collect, transcribe, code, share, and use a video corpus of infant and mother naturalistic activity in the home to test behavioral, developmental, and environmental cascades. The project will demonstrate the value and feasibility of a cross-domain synergistic approach, and advance new ways to use video as documentation to facilitate discovery and ensure transparency and reproducibility. Aim 1 is to create the first, cross-domain, large-scale, transcribed, coded, and curated video corpus of human behavior?collected with a common protocol and coded with common criteria jointly developed by the launch group. The corpus will consist of videos of 900 infant-mother dyads (300 12-, 18-, and 24-month-olds) from 30 diverse sites across the United States. Videos will be transcribed and coded for infant and mother communicative acts, gestures, object interactions, locomotion, and emotion. The corpus will be augmented with video home tours and questionnaire data on infant language, temperament, locomotion/fall injuries, gender identity and socialization; home environment and media use; and family health and demographics. Aim 2 is to leverage the potential of time-locked video codes to test critical questions about behavioral, developmental, and environmental cascades?from one domain to another, between infants and mothers, and from the macro environment (e.g., SES, geographic region, home language) and proximal home environment (e.g., objects for play, home chaos and clutter) to infant and mother behaviors. Aim 3 is to advance new ways to use video as documentation to ensure scientific transparency and reproducibility. The entire protocol and code definitions are documented in a wiki with exemplar video clips to illustrate text-based descriptions. The entire corpus and all tools will be openly shared with the developmental and behavioral science communities on Databrary and in other language and behavior repositories (CHILDES, HomeBank, WordBank, OSF). PLAY will create a cross-domain, shared video corpus of unprecedented scope and richness. It will provide launch group members and the larger research community with the data, tools, and know-how to use time-locked video codes to investigate the unfolding of natural behavior in real time. The novel, synergistic approach to crowdsourcing the research will reduce overall costs while increasing scientific payoffs. The use of shared video as both data and documentation will accelerate the pace of discovery in developmental science.

Researchers in disciplines across the behavioral, social, educational, computational, and life sciences collect data whose sharing can pose significant practical and ethical challenges due to privacy concerns, political risk, cultural sensitivities, legal or policy restrictions, and intellectual property constraints. How should researchers protect data while making access as open as possible, in alignment with the principles of open science? And how should data repositories clearly communicate who has what sort of access in ways that encourage suitable uses? This project will create generalizable models and infrastructure that strike a balance between providing open access to research data and materials while protecting research data. The results will bolster transparent, reproducible, integrative, interdisciplinary and insight-generating research across scientific fields by enhancing an existing research data infrastructure that specializes in sharing sensitive research data with restricted scientific audiences.

The proposed infrastructure builds on Databrary.org, a restricted access data library specializing in storing and sharing video data and documentation. Databrary was co-developed by the PI with support from NSF. The project has two aims: (1) Implement interface and metadata enhancements to the NSF-supported Databrary digital library to make sensitive, restricted-access data maximally discoverable to the widest range of audiences, including users of the NSF Public Access Repository (NSF-PAR), and (2) Ensure that Databrary embodies best practices and shares its innovations widely. The activities associated with these aims will expand access to Databrary?s existing holdings, improve the findability, accessibility, interoperability, and reusability of data shared there, and provide insights and knowledge that should benefit other scholarly communities facing similar challenges.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.