"The Laboratory for Intelligent Imaging and Neural Computing (LIINC) was founded in September 2000 by Paul Sajda. The mission of LIINC is to study fundamental processing strategies and representations used by biological vision systems and apply these to develop artificial vision systems capable of sophisticated and adaptive image and scene analysis. Our laboratory pursues both basic and applied neuroscience research projects, with emphasis in the following:

Network models for visual processing
Neuroimaging
Statistical representation of natural signals
Machine Learning"

More on Neuromatters
"The human brain reacts to images of interest at a pace that is far faster than a person can consciously register. Researchers at Columbia University have developed a technology, “Cortically Coupled Computer Vision (C3Vision)”, that takes advantage of this near-subconscious ability and pairs it with the processing power and efficiency of computers for rapid identification of images that the brain finds relevant.

C3Vision relies on a suite of patented machine learning algorithms which are trained to recognize what is of interest to a human viewer in a given context. Wearing an electroencephalography (EEG) cap with electrodes that capture electrical activity of the brain, a person is shown a sequence of images at a rapid pace. Each time an image of interest is displayed, the brain emits a distinctive electrical signal which is captured and decoded by the technology. Based on the strength of these neural responses, images are ranked. Over time, the technology learns what types of images are of interest to the viewer, and can eventually identify such images on its own.

“Computer vision systems are good at crunching through lots of data, but rather poor at characterizing images and scenes based on abstract and subjective concepts such as ‘that’s interesting’ or ‘I like that’ ,” said Paul Sajda, PhD, Director of the Laboratory for Intelligent Imaging and Neural Computing and a Professor of Biomedical Engineering and of Radiology at Columbia University’s School of Engineering and Applied Science and Columbia University Medical Center, respectively. “In contrast, the human visual system is exceedingly good at abstract and subjective scene analysis and image understanding, though would obviously be overwhelmed by having to analyze information from millions of images.

With a combined $4.6 million of support from DARPA Neuromatters and Columbia are collaborating on the development of an integrated image triage system based on the C3Vision technology. The system will be used and evaluated in operational environments by government image analysts to examine vast areas of satellite imagery for specific physical characteristics. The system may also extend to video surveillance and security, where the aim is to identify suspicious activity."

Neuromatters is a neurotechnology research & development company designing and building neural signal processing and brain-computer interface systems for capturing and decoding brain activity. Founded by recognized neuroengineering and machine learning experts, Neuromatters' goal is to evolve brain-computer interface systems into application areas where information overload is prevalent.