During natural vision humans and non-human primates make several saccadic eye movements each second that result in large changes in the retinal input. Despite these often dramatic changes, our visual percept remains remarkably stable and we can readily attend to and direct motor actions towards objects in our visual environment. This project will use a model-driven approach to investigate the neural circuits linking vision, attention and oculomotor planning that stabilize perceptual and attentional representations during natural vision. Experimental data will be collected and used to design a detailed computational model of the visual and oculomotor areas involved in saccade compensation. The proposed collaboration between a computational (DE) and experimental neurophysiological (US) laboratories leverages the power of both disciplines. Biologically accurate models of visually guided behavior and trans-saccadic integration developed in the Hamker lab will guide the design of and interpretation of data obtained from neurophysiological experiments in awake, behaving primates performed in the Mazer lab in an iterative fashion, with experimental results informing model revisions and new model predictions altering experimental designs. The proposed studies will characterize both dorsal and ventral stream visual area contributions to stabilizing visual and attentional representations in the primate brai. Data obtained from these experiments will identify the neural circuits responsible for integrating oculomotor commands, bottom-up visual inputs and top-down attention signals. This approach will yield novel insights into interactions between the dorsal and ventral streams during natural vision and facilitate our understanding of goal-directed, active visual perception, a defining feature of human and non-human primate natural vision. A critical component of this project is the highly collaborative nature of the planned research. We expect great benefits from this interdisciplinary approach, which depends critically on computational models that strictly adhere to the known physiological and anatomical constraints to guide our neurophysiological experiments. 1. Training. The proposal includes a detailed training plan intended to facilitate international training of future modelers and neurophysiologists. Specifically, we will train students and post-doctoral researchers to be experts in both experimental and theoretical approaches in order to advance the field using the hybrid approach outlined in the proposal. 2. Education and Outreach. We plan to organize two in-depth workshops on attention and eye movements. These events (one in Germany and one in the US) will bring together investigators from other institutions and related scientific disciplines to advance the field. In addition investigators will organize and chair 1-2 workshops/symposia at annual meetings (e.g., SFN and COSYNE) during the funding period. Finally, we will participate in science education for underrepresented groups through Yale?s STARS program by providing training, research and mentoring opportunities in the Mazer lab. 3. Data Sharing. The software tools generated and behavioral and neurophysiological data collected during this project will be distributed to the neuroscience community to facilitate data mining and secondary analyses of experimental data. 4. Impact in other scientific fields. Efficient allocation of limited sensor resources is also a important problem faced by computer vision and robotics researchers. Understanding how the primate brain efficiently allocates visual resources using an active-sensing approach will guide development of biologically inspired computer vision algorithms and humanoid cognitive robots. 5. Translational Implications. Although the proposed research is not translational, there is a growing body of evidence suggesting that several clinically important conditions, including Autism Spectrum Disorder, Attention Deficit Hyperactivity Disorder and Schizophrenia, are associated with impaired behavioral links between saccade planning and visual attention. The proposed basic science studies could have significant implications for future translational research potentially leading to improved understanding disease etiology, development of early diagnostic tools and possible interventional strategies.

Agency
National Institute of Health (NIH)
Type
Research Project (R01)
Project #
1R01EY025103-01
Application #
8837252
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Araj, Houmam H
Project Start
Project End
Budget Start
Budget End
Support Year
1
Fiscal Year
2014
Total Cost
Indirect Cost
Name
Yale University
Department
Neurosciences
Type
Schools of Medicine
DUNS #
City
New Haven
State
CT
Country
United States
Zip Code
06510