Robert M. Shapley - US grants

Affiliations:

1987-

Center for Neural Science

New York University, New York, NY, United States

Area:

Visual cortex

Website:

http://www.cns.nyu.edu/corefaculty/Shapley.php

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Years	Recipients	Code	Title / Keywords	Matching score
1985 — 2011	Shapley, Robert M	R01Activity Code Description: To support a discrete, specified, circumscribed project to be performed by the named investigator(s) in an area representing his or her specific interest and competencies.	Spatial Summation and Dynamics of Visual Neurons @ New York University DESCRIPTION (provided by applicant): The overall goal of this project is to understand the function of cortical circuitry in macaque monkey primary visual cortex Vi, and how it contributes to visual perception. Experiments are designed to test models of the cortex. The crucial question in most models is, what is the nature of cortico-cortical interaction? I will pursue the following aims. 1. To measure the dependence of steady-state orientation selectivity on contrast. We have preliminary data that indicate there is some effect of contrast on selectivity for sine-grating. Also contrast invariance (or its absence) is crucially important for theories of orientation selectivity. Furthermore, I will measure orientation selectivity for flashed bars and edges on the same cells as for sine gratings, and also measure effects of contrast with these stimuli.2. To measure the dependence of orientation selectivity dynamics on contrast and context. Measuring orientation-tuning dynamics as a function of contrast will provide further strong constraints on models of orientation selectivity. Also, we will measure orientation dynamics for contours embedded (vs. not embedded) in visual objects, to probe whether perception-related signals are measurable in Vi with this technique. The dynamics of responses to step increases in contrast at preferred orientations will also be measured and compared with the reverse correlation results.3. To measure cross-orientation inhibition in plaids (and other 2D patterns). Another way to test whether or not there is recurrent interaction between orientation-tuned elements is to use a plaid stimulus (Wallach, 1935; Adelson and Movshon, 1982). In the particular plaid patterns I will use, the two 1-D components are near each other in orientation (say 20-300), but differ in temporal frequency.4. To examine the effect of random or natural-image backgrounds or other context on orientation selectivity. I want to measure tuning curves of stimuli placed on modulated backgrounds that will tend to elevate the cell's spike rate and get it away from threshold. There is the added question; will natural image backgrounds have a different effect from that of random noise? Steady state orientation tuning curves, as well as step responses, will be measured on these different backgrounds and compared with the dynamics from reverse correlation experiments on the same neurons. Show summary Hide summary	1
1987 — 1991	Shapley, Robert	N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information	Visual, Spatial and Temporal Filtering and Hyperacuity @ New York University Visual acuity is a measure of how well the eye can resolve very tiny targets, and is limited by the size and distribution of the photoreceoptor cells in the eye. However, a slight sideways displacement break in an otherwise straight line can be detected when the displacement is as much as five times less than the normal acuity would predict. This discriminability is known as hyperacuity, and can be demonstrated by this stimulus called vernier displacement, or by displacement of a grating pattern or by bisection of a pattern. Understanding hyperacuity is important for understanding visual information processing because hyperacuity reveals the ultimate precision of visual localization in space. This project will study how spatial and temporal properties of information channels in the eye and brain determine the limits of hyperacuity. Single neurons (nerve cells) in the visual system have particular response properties that preferentially filter particular frequencies in time (cycles/sec) or space (cycles/degree, of a grating, for example). Hyperacuity targets or vernier and grating displacement will be presented to human observers, and then these targets will be "masked" by the presence of flickering illumination, or superimposed gratings, or spatiotemporal noise. The discriminations will be compared for these different cases. To determine the dynamic characteristics of the neural mechanisms involved will require measurement of displacement thresholds as a function of luminance contrast, color contrast, mean luminance, and temporal frequency. Finally, a comparison will be attempted between human hyperacuity performance and the hyperacute capabilities of single neurons in the macaque monkey's visual pathway. The goal of this work is a comprehensive understanding of the neural basis for hyperacuity. The approach combining psychophysics, physiology and mathematical modelling is rare and powerful. Understanding this wonderful performance in terms of neural mechanisms will lead to a better theoretical basis for understanding the ultimate limits of visual performance. Show summary Hide summary	0.915
1989 — 1991	Shapley, Robert	N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information	Instrumentation (Eye-Tracker and Sun Workstations) For Studyof Neural Image @ New York University This instrumentation will support research in the following areas: 1) Networks in the Retina and Lateral Geniculate Nucleus, and 2) Information Processing in the Visual Cortex. Experimental results on neural mapping will be sought from single and multi- unit recording with microeletrodes placed in the optic pathway and cerebral cortex of anesthetized monkeys. The research plan includes exploitation of new mathematical and computational methodologies for mapping receptive fields. These use theories of nonlinear systems analysis and require the capability of generating complex, pseudorandom patterns and then analyzing neural responses with mathematical transforms that require substantial computing power. Other projects in the research plan required image stabilization for precise mapping from the retinal image to the neural image on the cerebral cortex. This proposal requests a workstation with graphics display hardware and software for creating complex visual images, and a Fourward Technologies eye-tracker and image stabilization instrument for precise control of image location and of stimulus dynamics. Show summary Hide summary	0.915
1992 — 1994	Shapley, Robert	N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information	Cone Signals and the Functional Anatomy of Visual Cortex @ New York University Experiments using a novel and innovative technique for mapping specific photoreceptor activities in the cerebral cortex are designed to provide answers to crucial questions about the way in which color information is processed at the highest levels of the visual pathway. These studies should help to resolve a long outstanding problem in human vision and pioneer a fairly straightforward technique for the study of most other visual systems that use color information in guiding behavior. This is the first such attempt to use cone photoreceptor-isolating stimuli to map activity in the primary visual cortex using the metabolic marker, 2- deoxyglucose and promises to be a very powerful new addition to understanding cortical mechanisms of color perception. Show summary Hide summary	0.915
1993 — 2002	Shapley, Robert M	T32Activity Code Description: To enable institutions to make National Research Service Awards to individuals selected by them for predoctoral and postdoctoral research training in specified shortage areas.	Training in Visual Neuroscience @ New York University	1
1996 — 1999	Mclaughlin, David Shapley, Robert	N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information	Cri: Theory and Experiments On the Function of Visual Cortex @ New York University IBN: 9634368 PI: McLaughlin This project will be supported under the NSF program on INTEGRATING ENABLING TECHNOLOGIES INTO NEUROSCIENCE RESEARCH; it is a collaboration of mathematicians and neuroscientists attacking the most important issues in brain research. In our view, the premier problem facing us is how to understand the function of the cerebral cortex of the brain as a functioning neural network. We study the part of the cerebral cortex that handles visual information--called the visual cortex. Cells in the visual cortex are selectively sensitive for the orientations of the visual boundaries of objects. We will develop and test neural network models for this selectivity, to see whether it is a property that emerges from interactions between nerve cells in the cerebral cortex, or whether it is a passive by-product of the connections to cortical cells from lower levels of the visual system of the brain. We believe that understanding the neural basis for orientation tuning in the visual cortex may be crucial for understanding the function of the entire cortex. If we find evidence that interaction between neighboring neurons in the cerebral cortex is essential for orientation tuning to work, then this will be crucial support for the idea that the cerebral cortex is a richly interconnected, interactive neural network that can be studied with available analytical tools. Show summary Hide summary	0.915
1997 — 2002	Ringach, Dario Tannenbaum, Allen (co-PI) [⬀] Sapiro, Guillermo (co-PI) [⬀] Rubin, Nava (co-PI) [⬀] Shapley, Robert	N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information	Learning and Intelligent Systems: Intelligent Visual Grouping: Basic Mechanisms, Models, and Applications @ New York University IBN-9720305 PI: SHAPLEY This project is being funded through the Learning & Intelligent Systems Initiative. The questions involve vision and learning in the central nervous system. The project investigates how the brain represents and processes perceptual information, and the adaptive changes that occur when the system learns and improves its performance. Here the visual system is used as a gateway into the workings of the brain, employing methods from psychophysics, neurophysiology, mathematics and engineering. The work focuses on visual grouping, which is the ability of the visual system to link together local elements of the visual image into coherent wholes. Grouping is one of the most fundamental aspects of human vision, and the goal of this work is to obtain a theory of visual grouping that will explain the physiological and psychophysical data, and lead to new technological ideas to be applied in intelligent artificial systems. Results will be important because understanding the computations in the brain that produce grouping would be a leap forward in our understanding of brain function, and of any systems that can adapt to experience. This work will therefore have an impact in designing learning materials and in the optimal methods of presenting information, and in the design of the next generation of computer vision systems and intelligent control systems. This project is supported in part by the NSF Office of Multidisciplinary Activities in the Directorate for Mathematical & Physical Sciences. Show summary Hide summary	0.915
2001 — 2010	Shapley, Robert M	T32Activity Code Description: To enable institutions to make National Research Service Awards to individuals selected by them for predoctoral and postdoctoral research training in specified shortage areas.	Computational Visual Neuroscience Training Program @ New York University	1
2003 — 2012	Mishra, Bhubaneswar (co-PI) [⬀] Shapley, Robert Osman, Roman Shelley, Michael [⬀] Greengard, Leslie (co-PI) [⬀] Schlick, Tamar (co-PI) [⬀]	N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information	Igert: Program in Computational Biology (Cob) @ New York University Many achievements in the biological and biomedical sciences are fueled by advances in technology and computational science. To address the complex challenges in the biological sciences in the 21st century, there is a growing need for professionals who can translate scientific problems in biology into mathematics and computations; for such productive work, familiarity with modern scientific computing approaches as well as key biological challenges is essential. Intellectual Merit: This IGERT award is for a multidisciplinary Computational Biology (COB) doctoral program at NYU and MSSM targeting students interested in pursuing research in biology/biomedicine who require a transition from/to the mathematical/computer/physical sciences to best meet scientific challenges and career goals. This experimental, bidirectional program will offer integrative training that exploits NYU's strengths in applied mathematics, computer science, biology, and biochemistry, and Sinai's leadership in biomedicine. The major COB research themes - macromolecular modeling, computational genomics, and physiological modeling - will train students to investigate biological systems spanning wide temporal and spatial scales, from atoms and macromolecules, to cells and organs, to organisms. Modeling biological systems across such scales is essential for a modern systems biology approach aimed at understanding physiological processes and diseases and applying this knowledge to biomedicine. To integrate training in biological and computational areas and provide trainees broad scientific perspectives and work experiences, the COB PhD program includes: (1) Dual faculty mentorship for thesis research; (2) Interdisciplinary training through flexible and background-tailored tracks in scientific computing and computational biology (courses in computer science, applied mathematics, biology, and biomedicine), trainee-led seminars, and ethics/research conduct courses, while ensuring competitive time to degree (5 years); (3) Summer internships in industry, academia, government (Agilent, IBM, Celera, Merck, Novasite and 3D Pharmaceuticals, supercomputing centers), or international laboratories; (4) Learning environments and activities that promote interdisciplinary interactions and broader collaborations within and outside NYU/MSSM, including: trainee-led COB seminars, annual COB retreat, and common COB lab/lounge; and (5) Mentoring and career development activities to ensure student retention, especially women and underrepresented groups, through student advisory committees, trainee-led support group, and partnerships with Burroughs Wellcome Fund and NYC's IGERT programs at CUNY and Columbia. The COB doctoral program will be evaluated and evolved continuously by its executive and internal/external advisors in close collaboration with the pedagogical experts of NYU's Center for Teaching Excellence (CTE). Broader Impacts: COB will train math/computer science students to successfully model biological systems and, in turn, provide biology students the grounding in computational techniques so they can tailor the model and algorithms to specific biological problems. To help bridge disciplinary gaps, we will design background-tailored short (non-credit) courses before Year 1 and promote peer learning by pairing students from complementary backgrounds. We expect that COB's activities will enable trainees to act as catalysts for novel interdisciplinary collaborations and to acquire expertise in cutting-edge research areas; these experiences will prepare them uniquely for research and education careers in academia, industry, and government. In addition, COB's program of integrating scientific grounding, experience in team-oriented multidisciplinary projects, mentoring, and career broadening activities will serve as a new model of graduate training at NYU/MSSM and beyond, promote the development of curricula for computational biology, and provide the opportunity to develop the COB doctoral degree at NYU based on the new model. Recognizing the urgent need for diversity in the sciences, we will make concerted efforts in conjunction with participating departments and with successful new minority initiatives at NYU to recruit and retain the brightest students, especially women and other underrepresented groups. IGERT is an NSF-wide program intended to meet the challenges of educating U.S. Ph.D. scientists and engineers with the interdisciplinary background, deep knowledge in a chosen discipline, and the technical, professional, and personal skills needed for the career demands of the future. The program is intended to catalyze a cultural change in graduate education by establishing innovative new models for graduate education and training in a fertile environment for collaborative research that transcends traditional disciplinary boundaries. In this sixth year of the program, awards are being made to institutions for programs that collectively span the areas of science and engineering supported by NSF. Show summary Hide summary	0.915
2005 — 2009	Shapley, Robert M	P30Activity Code Description: To support shared resources and facilities for categorical research by a number of investigators from different disciplines who provide a multidisciplinary approach to a joint research effort or from the same discipline who focus on a common research problem. The core grant is integrated with the center's component projects or program projects, though funded independently from them. This support, by providing more accessible resources, is expected to assure a greater productivity than from the separate projects and program projects.	Core--Mri @ New York University ABSTRACT NOT PROVIDED Show summary Hide summary	1
2008 — 2011	Shapley, Robert	N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information	Primary Visual Cortex: Sensitivity to Continuity and Discontinuity in Patterns @ New York University This project is about the electrical activity of cortical cells and cell populations in the macaque monkey's primary visual cortex, V1--as an animal model of human visual cortex. The investigators will study the cells' responses and cell population responses to visual images that are either continuous, or discontinuous in space. There is preliminary evidence that many V1 cells respond more to image discontinuity than to continuous contours. The proposed experiments, utilizing the technique of multi-microelectrode recording, will investigate more precisely the sensitivity of V1 to image-discontinuities. For instance, one experiment will measure the effect of spatial gaps in a visual image on cortical activity. The results of this experiment will define how much spatial separation is necessary for the V1 network to perceive it as a spatial discontinuity. It is known that local image features, like line endings and sharp corners, are important for human object recognition and form perception. The proposed project aims to advance scientific understanding of the function of V1 cortex in perception. Also, the experimental results of this project will be useful for realistic computational models of V1 cortex, and models of cerebral cortex generally. There will also be a broader impact. The project involves training of a postdoctoral fellow and also graduate students for their own future research in neuroscience. Also, the investigators will make the project's multi-electrode recording data available for use by other neuroscientists and by theorists. Furthermore, undergraduate and high school students will perform rotation projects in the investigators' laboratory and will receive training as part of this project. Show summary Hide summary	0.915
2016 — 2018	Shapley, Robert	N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information	Mechanisms of Color Perception: Dependences On Color Contrast and Spatial Pattern @ New York University Color perception is a primary aspect of visual experience for most people. This research project aims to resolve an apparent contradiction in human color perception. When a human observer is asked to detect a colored target that is barely visible, the visual system sums color signals across space to achieve maximum sensitivity to the weak stimulus. However, when one views a highly-colored scene, the visual system takes the difference between color signals at different locations, leading to color appearance that is highly dependent on contrasts in color. The apparent contradiction between adding and subtracting can be resolved by the hypothesis that color perception adds color signals at threshold, when they are barely visible, but subtracts color signals when color stimuli are well above threshold. This research tests this hypothesis by studying how color perception depends on the pattern of the color in space. Spacing has different effects on color perception if the visual system is adding or subtracting color signals. Better understanding of how the visual system processes color may translate to advances in fields such as lighting design or color graphics. The project involves training of young scientists in methods of studying human vision through measuring behavior and brain activity, as well as science outreach to public school students. The experiments will measure the spatial pattern dependence of suprathreshold color perception in humans and compare suprathreshold results with those at color threshold. Two different techniques for studying suprathreshold color perception are used: hue and saturation scaling, and reaction times. The project also includes measurements of the human cVEP (color-Visual Evoked Potential, an EEG measure of color responses in early visual cortex) and its dependence on spatial stimulus variables at different levels of color contrast. The aim of the cVEP experiments is to determine the cortical mechanisms that are the basis of color perception near threshold and suprathreshold. A computational model will be used to fit the psychophysics and cVEP data. Show summary Hide summary	0.915
2017 — 2020	Young, Lai-Sang (co-PI) [⬀] Shapley, Robert	N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information	Ncs-Fo: Data-Driven Modeling of Visual Cortex @ New York University One of the great challenges of modern neuroscience is a comprehensive theory of the function of the cerebral cortex. The overall aim of the present project is to answer this challenge with a new model of the visual cortex. The modeling process will lead to the discovery of common, canonical neural mechanisms behind a multitude of visual phenomena, giving special emphasis to canonical computations that are performed not just in the visual cortex but also in other regions of the cerebral cortex. The project aims to enhance understanding of cortical function by looking beyond structure to study the dynamics of cortical activity. An important part of the project's broader impact will be to provide interdisciplinary training for young researchers in response to society's need for an educated workforce with multi-disciplinary skills bridging mathematics and neurobiology. Additionally, the principal investigators will reach out to broad scientific audiences as well as high school students. Specifically, the results of this project will be disseminated by giving invited scientific lectures to national and international scientific meetings. The investigators also participate in university-sponsored outreach events for New York City-area high school students, such as the annual C-Splash lectures at the NYU Courant Institute of Mathematical Sciences. This project adopts an integrative strategy to apply ideas from dynamical systems theory to theoretical neuroscience. The project will construct a next-generation model of the visual cortex that is realistic and comprehensive in the way it reproduces the dynamics of cortex and its visual functions. The model will be constrained by hundreds of sets of visual neuroscience data and by all that is known about cortical neuroanatomy. Such a model is a tool to advance neuroscience and a step toward building robotic intelligent systems that emulate human perception. The visual cortex will be modeled as a large network of spiking, conductance-based neurons. It will be analyzed as a complex dynamical system. Specific projects are: 1) network models of local circuitries; 2) extended models of the visual cortex covering a substantial portion of the visual field, and 3) dynamical interactions on neuronal scale to perceptual organization of two- and three-dimensional objects. The modeling and analysis will have wide impact beyond visual cortex in studies of the functional, dynamical consequences of canonical computations that are performed throughout the cerebral cortex. This project is funded by Integrative Strategies for Understanding Neural and Cognitive Systems (NSF-NCS), a multidisciplinary program jointly supported by the Directorates for Computer and Information Science and Engineering (CISE), Education and Human Resources (EHR), Engineering (ENG), and Social, Behavioral, and Economic Sciences (SBE). This award is co-funded by the Division of Mathematical Sciences in the Directorate for Mathematical and Physical Sciences (MPS). Show summary Hide summary	0.915