Understanding the human brain is one of the greatest and most challenging scientific frontiers of our time. CCN’s mission is to develop models, principles and conceptual frameworks that deepen our knowledge of brain function — both in health and in disease.
With the new model, researchers reveal how memories and learned behaviors can remain strong, even in the face of shifting neural representations.
CCN takes a “systems" neuroscience approach, building models that are motivated by fundamental principles, that are constrained by properties of neural circuits and responses, and that provide insights into perception, cognition and behavior. This cross-disciplinary approach not only leads to the design of new model-driven scientific experiments, but also encapsulates current functional descriptions of the brain that can spur the development of new engineered computational systems, especially in the realm of machine learning. CCN currently has research groups in Computational Vision and Neural Circuits and Algorithms, and will launch research groups in NeuroAI and Geometry and Statistical Analysis of Neural Data in January 2022.
News & Announcements
March 09, 2023
February 16, 2023
February 10, 2023
Workshop 9:00 a.m. - 6:00 p.m.
CCN Junior Theoretical Neuroscientist’s Workshop 2023
- Workshop 9:00 a.m. - 6:00 p.m.
Computational mechanisms of distributed value representations and mixed learning strategies
Learning appropriate representations of the reward environment is challenging in the real world where there are many options, each with…Nature Communications
Neural optimal feedback control with local learning rules
A major problem in motor control is understanding how the brain plans and executes proper movements in the face of…NeurIPS
Bridging the Gap: Point Clouds for Merging Neurons in Connectomics
In the field of Connectomics, a primary problem is that of 3D neuron segmentation. Although deep learning-based methods have achieved…arXiv:2112.02039
Eero P. Simoncelli, Ph.D.Alumni
Eero P. Simoncelli is the inaugural director of the Center for Computational Neuroscience. Eero P. Simoncelli’s research interests span a wide range of topics in the representation and analysis of visual images and sounds in both machine and biological vision systems.Read more
Dmitri ‘Mitya’ Chklovskii, Ph.D.Group Leader, Neural Circuits and Algorithms
The goal of Mitya Chklovskii’s research is to reverse engineer the brain on the algorithmic level. Informed by anatomical and physiological neuroscience data, his group develops algorithms that model brain computation and solve machine learning tasks.Read more
SueYeon Chung, Ph.D.Associate Research Scientist / Project Leader, CCN
SueYeon Chung is an Assistant Professor in the Center for Neural Science at New York University and an Associate Research Scientist / Project Leader at the Flatiron Institute. Her research interests span a variety of topics in theoretical neuroscience and theory of neural computation, ranging…Read more
Computational toolbox for large scale Calcium Imaging Analysis, including movie handling, motion correction, source extraction, spike deconvolution and result visualization.
Complete Matlab pipeline for large scale calcium imaging data analysis.
Modern imaging methods, such as Light, Electron, and synchrotron X-ray, have enabled 3D imaging for large samples with high resolution.
Due to the string-like nature of neurons and blood vessels, they could be abstracted as curved tubes with center lines and radii.