- Hans van Hateren
http://hlab.phys.rug.nl/
I am working on several aspects of visual processing. My current main interest is to use the statistics of natural stimuli (images, time series of intensities, video) for investigating and understanding the visual system.
- Gary Holt
http://lnc.usc.edu/~holt/
Our goal is to devise learning rules that can develop a feature-detector hierarchy similar to that proposed by Fukushima et al. (1983) in order to recognize objects independent of location, scale, or orientation.
- Christoph Kayser
http://www.ini.unizh.ch/~kayser/
The lab studies the statistical regularities of natural scenes, how they relate to the response properties of cortical cells and quantifies the impact of global stimulus structure on visual cortical activity.
- Peter König
http://www.ini.unizh.ch/~peterk/
Experimental and theoretical studies of sensory processing and sensory motor integration in the mammalian cortex under natural conditions.Thus, I investigate the role of top-down signals, their relation to the fast dynamics, learning and plasticity in the neuronal network. Insights obtained from this work are transferred to real-world applications.
- Ken Miller
http://phy.ucsf.edu/~ken/
My lab's interests focus on understanding the cerebral cortex. We use theoretical and computational methods, and theoretically motivated experimental methods, to unravel the circuitry of the cerebral cortex, the rules by which this circuitry develops or "self-organizes", and the computational functions of this circuitry.
- Klaus Obermayer
http://ni.cs.tu-berlin.de/
The NI group focuses on computational models of neuronal systems, on the mathematical analysis of neural networks, and on the development of ANN algorithms, in particular for image processing applications.
- Randall O'Reilly
http://psych.colorado.edu/~oreilly/
He develops computational and formal models of the biological bases of cognition , focusing on specialization of function in and interactions between hippocampus, prefrontal cortex, and posterior neocortex in learning, memory, attention, and controlled processing.
- Rajesh Rao
http://www.cnl.salk.edu/~rao/
The primary goal of my research is to discover the computational principles underlying the brain's remarkable ability to learn, process and store information, and to apply this knowledge to the task of building adaptive robotic systems and artificially intelligent agents.
- Maneesh Sahani
http://www.gatsby.ucl.ac.uk/~maneesh/
My research focuses on the statistical analysis of neural data and the design of experiments in neuroscience. The richness and density of information obtained from neural experiments is probably unrivalled in the history of experimental science. As such, new and creative methods are needed to collect sensible data and extract meaning from them.
- Eero Simoncelli
http://www.cns.nyu.edu/~eero/
The laboratory addresses a variety of basic issues in the analysis and representation of visual imagery. 1) construction of mathematical theories for the representation of visual information, 2) development of functional models for biological visual processing, and 3) creation of novel algorithms for image processing and computer vision applications.
- Tony Zador
http://www.cshl.org/public/SCIENCE/zador.html
At a cocktail party we can selectively attend to a single voice, effortlessly filtering out all the others that make up the banter that surrounds us; yet this task remains far beyond the capabilities of our most sophisticated computers. How do the neurons in our brains conspire to form such powerful computational engines?
- Dale Purves
http://www.purveslab.net
the Purves laboratory is studying visual perception and its neurobiological underpinnings. Shows a lot of interactive demos of psychophysical effects and optical illusions.
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Students and Postdocs