Reaching towards a visual target is ubiquitous in daily life. The task seems effortless, yet requires substantial processing to accomplish. Our goal is to better understand the visuospatial information processing underlying action. For this purpose, we use visually-guided reaching in the non-human primate as a model system.
Our first aim i s to determine the specific contributions of posterior parietal areas to the kinematics and dynamics of visually-guided reaching. We will use a novel method to precisely localize the sites of reversible injections placed throughout the intraparietal sulcus. After each injection we will test animals on a panel of tasks (reaches, saccades and visual search) and then image the site of inactivation. This method is comprehensive and better indicates the true functional contributions of parietal areas than can be achieved through single unit recording.
Our second aim i s to identify and quantify components of activity in posterior parietal cortex that are related to bimanual coordination. Primates commonly use the two arms together to accomplish tasks that are difficult or impossible to perform with a one arm. Clinical evidence suggests a role of the parietal cortex in bimanual coordination. Our results will help distinguish between two specific models of how bimanual coordination might be manifest at the level of individual neurons.
Our third aim i s to quantify the activity of posterior parietal neurons during evaluation of targets and decision-making in performing reaches, and to compare that activity to that observed during decision-making for saccadic eye movements. Recent work has suggested a specific model for decision-making for saccadic eye movements. Our results will indicate whether parietal circuits for target evaluation and decision circuits are the same or different for different kinds of action (reaches versus saccades). Achieving these aims will help us understand the early processes involved in sensory to motor transformation, motor coordination, and decision-making. The results will critically inform the devise of rational strategies for aiding recovery from strokes and other central damage, as well as the design of optimal brain interfaces for a new generation of prosthetic devices.

Public Health Relevance

The central goal of this proposal is to understand the early processing of visuospatial information for visually- guided reaching. Achieving this goal will help clinicians to understand and ultimately reverse the damage caused by parietal and occipital strokes and other brain trauma. Understanding how the brain generates and represents plans for movement is also critical to the development of promising neuroprosthetics for patients with amputations, spinal cord injuries, and disorders such as amyotrophic lateral sclerosis.

National Institute of Health (NIH)
National Eye Institute (NEI)
Research Project (R01)
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Central Visual Processing Study Section (CVP)
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Steinmetz, Michael A
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Washington University
Schools of Medicine
Saint Louis
United States
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Papadimitriou, Charalampos; White 3rd, Robert L; Snyder, Lawrence H (2016) Ghosts in the Machine II: Neural Correlates of Memory Interference from the Previous Trial. Cereb Cortex :
Chang, Steve W C; Calton, Jeffrey L; Lawrence, Bonnie M et al. (2016) Region-Specific Summation Patterns Inform the Role of Cortical Areas in Selecting Motor Plans. Cereb Cortex 26:2154-66
Kubanek, Jan; Li, Jingfeng M; Snyder, Lawrence H (2015) Motor role of parietal cortex in a monkey model of hemispatial neglect. Proc Natl Acad Sci U S A 112:E2067-72
Patel, Gaurav H; Yang, Danica; Jamerson, Emery C et al. (2015) Functional evolution of new and expanded attention networks in humans. Proc Natl Acad Sci U S A 112:9454-9
Kubanek, Jan; Snyder, Lawrence H; Abrams, Richard A (2015) Reward and punishment act as distinct factors in guiding behavior. Cognition 139:154-67
Kubanek, Jan; Snyder, Lawrence H (2015) Reward Size Informs Repeat-Switch Decisions and Strongly Modulates the Activity of Neurons in Parietal Cortex. Cereb Cortex :
Kubanek, Jan; Snyder, Lawrence H (2015) Matching Behavior as a Tradeoff Between Reward Maximization and Demands on Neural Computation. F1000Res 4:147
Papadimitriou, Charalampos; Ferdoash, Afreen; Snyder, Lawrence H (2015) Ghosts in the machine: memory interference from the previous trial. J Neurophysiol 113:567-77
Kubanek, Jan; Hill, N Jeremy; Snyder, Lawrence H et al. (2015) Cortical alpha activity predicts the confidence in an impending action. Front Neurosci 9:243
Kubanek, Jan; Snyder, Lawrence H (2015) Reward-based decision signals in parietal cortex are partially embodied. J Neurosci 35:4869-81

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