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Research Summary
Our research interests lie in the areas of Computational Neuroscience and Neural Engineering. Most of the work in my lab involves the use of computer models to study brain function. Some of our goals are of a primarily scientific nature. For example, we use detailed biophysiical modeling studies to study synaptic integration in active dendritic trees, and explore how dendritic trees could contribute to the sensory and memory-related functions of nerve cells. To do this work, we use simulation packages such as NEURON and a variety of custom software developed by members of the lab.
Some of our work combines scientific and engineering goals. For example, we are interested in the massively parallel computations carried out in the visual cortex which allow us to recognize objects with a speed, accuracy, and robustness that are far beyond the technical state of the art. How does this amazing neural technology work? We have developed a number of models of this process, and have applied them to various types of visual recognition problems. In one of our ongoing projects, we are attempting to understand the mechanisms used by the brain to learn which features are best for recognizing objects and scenes. Our hope is to someday be able to construct high performance artificial vision systems which could be used to power intelligent machines.
Our research interests lie in the areas of Computational Neuroscience and Neural Engineering. Most of the work in my lab involves the use of computer models to study brain function. Some of our goals are of a primarily scientific nature. For example, we use detailed biophysiical modeling studies to study synaptic integration in active dendritic trees, and explore how dendritic trees could contribute to the sensory and memory-related functions of nerve cells. To do this work, we use simulation packages such as NEURON and a variety of custom software developed by members of the lab.
Some of our work combines scientific and engineering goals. For example, we are interested in the massively parallel computations carried out in the visual cortex which allow us to recognize objects with a speed, accuracy, and robustness that are far beyond the technical state of the art. How does this amazing neural technology work? We have developed a number of models of this process, and have applied them to various types of visual recognition problems. In one of our ongoing projects, we are attempting to understand the mechanisms used by the brain to learn which features are best for recognizing objects and scenes. Our hope is to someday be able to construct high performance artificial vision systems which could be used to power intelligent machines.
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