Leanne Chukoskie, Ph.D. - US grants

DESCRIPTION (Adapted from applicant's abstract): Movements of the eyes shift the retinal image by an amount equal to and opposite from that of the eye movement. The visual system must separate real world motion from retinal image shifts caused by eye movements so that motion of objects in the real world can be analyzed. The question is how and how well the neurons in the visual motion pathway can represent real world motion during movements of the eyes. Neurons in extrastriate area MT and the medial superior temporal area (MST) are selective for image direction and speed. In addition, some cells in area MST carry signals related to movements of the eyes. The experiments have two main goals: 1) to assess basic visual and smooth pursuit eye movement-related properties of MT and MST cells in awake, behaving monkeys; 2) to assess the degree to which visual and oculomotor signals interact in these same neurons. We will investigate these putative interactions by comparing responses to particular patterns of retina motion as monkeys both fixate and make smooth pursuit eye movements. Comparing speed and direction tuning under these viewing conditions will reveal the degree to which the responses of MT and MST cells compensate for movements of the eyes and represent motion of objects in the world.

This Science of Learning Collaborative Network brings together an interdisciplinary team of researchers from University of California-San Diego and Indiana University, to study how children's movements impact their learning and how learning impacts movement skill. Identifying individuals with learning difficulties and matching these individuals with appropriate opportunities for improvement is one of the greatest challenges faced in education today. Novel measurement tools and analyses from the study of movement can be productively brought to bear on these problems to realize the potential of personalized education. To achieve this goal, the Learning through Movement Network (LMN) of investigators will bring together expertise from neuroscience, engineering, computation and physics, to study movement signatures in children who experience learning difficulties in school. New tools for the study of movement outside of the lab, and that can be readily deployed in educational settings, will also be created and tested. It is expected that the new knowledge created from this research will be useful in classifying children's movement signatures as those signatures map onto each child's own educational and cognitive profile.

Movement offers an important window into brain function as a remarkable amount of the brain is engaged in movement decisions, planning, execution and evaluation. This network brings together new technology and novel analytic methods to determine what can be learned from fine-grained measurement of movement of the body, the face, and the eyes. LMN investigators working in cross-functional teams will share methods and data to capture the subtleties of movement and create a signature for a learner at any point in time. The three core projects in the network bring together theories and analytical methods from different fields to identify movement-based commonalities across seemingly different learning problems and potentially also identify movement-based differences across seemingly similar learning problems. The LMN network will leverage the fact that the motor system is quite trainable, and aims to use this plasticity as a tool to improve cognitive functioning for better learning opportunities in the future. In addition, LMN investigator links to local public schools and sites for informal science learning will allow the group to engage in blended research and outreach events highlighting the importance of physical activity in the development of motor skill for cognitive fitness.

The award is from the Science of Learning-Collaborative Networks (SL-CN) Program, with funding from the SBE Division of Behavioral and Cognitive Sciences (BCS) and the SBE Office of Multidisciplinary Activities (SMA).

The proposed workshop will bring together awardees of the NSF Science of Learning Program. It seeks to capitalize on NSF investments in the Science of Learning to build community among diverse interdisciplinary researchers studying learning, and to build capacity so that investigators can readily reconfigure and mobilize collaborations to capture new opportunities offered by NSF priority areas. As examples, how technology impacts the way we learn and work, as well as how we might harness Big Data to gain greater insight into real-world learning are areas of relevance to the NSF's 10 Big Ideas (https://www.nsf.gov/about/congress/reports/nsf_big_ideas.pdf).

This gathering will include researchers from several disciplines under one large umbrella, including neuroscience, cognitive, behavioral and social sciences, computer and information sciences, engineering and education. The proposed effort is needed as there is currently no professional society meeting to support this interdisciplinary Science of Learning community of investigators and their trainees. The gathering seeks to foster information exchange and resource sharing, and to build trust among community members for successful interdisciplinary research. The workshop format will include small group discussions on topics that include new insights and methodologies that offer opportunities to make transformative advances in fundamental knowledge about learning over the lifespan, and intersections in interdisciplinary research that offer opportunities for convergence research in support of NSF's Big Ideas. In this way, the workshop will leverage the group's collective interdisciplinary intelligence for "Big Idea" problem-solving and the unique opportunity to work on problems that are larger than any taken on by individual laboratories. A survey of the research and other needs of the Science of Learning community will be conducted. The diverse disciplinary representation of the participants and the requirement to communicate and discuss science across a broad audience will have broader impacts in building an active and vibrant community capable of addressing complex societal problems through collaborative efforts. In addition, and as part of the workshop, plans will be developed to promote better communication of research findings to educational practitioners, policy makers, and the public. This will help to bridge the gap in understanding between basic research findings and their relevance to social challenges.