Gabriel Kreiman, Ph.D.

Assistant Professor of Ophthalmology

Kirby Neurobiology Center
Children's Hospital
Center for Life Science Building
3 Blackfan Circle
Boston, MA 02115
Telephone: 617 919-2530

Email: gabriel.kreiman@tch.harvard.edu
Lab website:  The Kreiman Lab

Our lab is interested in the neuronal circuits and algorithms responsible for visual object recognitionand memory formation. Visual object recognition is crucial for most everyday tasks including face identification, reading and navigation. In addition, many Machine Vision applications such as surveillance, biomedical image interpretation and automatic navigation rely strongly on visual pattern recognition. Through millions of years of evolution, the primate visual system has achieved a highly selective, rapid and robust recognition machinery. Selectivity refers to discriminating among multiple similar objects (e.g. face identification). Robustness refers to recognizing an object in spite of transformations at the pixel level (e.g. changes in viewpoint, scale, position, clutter, contrast, color, illumination, etc.). Remarkably, visual selectivity and robustness can be achieved in only ~150 ms of processing, placing a strong constraint on the number of computations that the cortical circuitry can perform to achieve immediate visual recognition. Our lab combines neurophysiology, psychophysics and theoretical/computational modeling to understand the neuronal circuits, algorithms and computations performed by the visual system and we use this knowledge to develop biophysically-inspired computational approaches to machine vision.

References:

• Liu H, Agam Y, Madsen JR, Kreiman G. (2009). Timing, timing, timing: Fast decoding of object information from intracranial field potentials in human visual cortex. Neuron 62:281-290.
• Rasch M, Logothetis N, Kreiman G. From neurons to circuits: linear estimation of local field potentials. Journal of Neuroscience, In Press.
• Meyers E, Freedman D, Kreiman G, Miller E, Poggio T (2008). Dynamic Population Coding of Category Information in ITC and PFC J. Neurophys. 100: 1407-1419
• Quian Quiroga R, Kreiman G, Koch C, Fried I (2008). Sparse but not grandmother –cell coding in the medial temporal lobe. Trends in Cognitive Science 12, 87-91.
• Kreiman G (2007). Single neuron approaches to human vision and memories. Current Opinion in Neurobiology, (2007). 17: 471-475.
• Serre T, Kreiman G, Kouh M, Cadieu C, Knoblich U, Poggio T, A quantitative theory of immediate visual recognition. Progr. In Brain Research, (2007). 165C: 33-56.
• Tropea D, Kreiman G, Lyckman A, Mukherjee S, Yu H, Horng S, Sur M. (2006) Distinct gene systems mediating activity-dependent plasticity in visual cortex. Nature Neuroscience 9:660-668
• Kreiman G*, Hung C*, Quiroga R, Kraskov A, Poggio T., DiCarlo J. (2006). Selectivity of local field potentials in inferior temporal cortex. Neuron 49:433-445
• Hung C*, Kreiman G*, Poggio T, DiCarlo J. (2005) Fast read-out of object information in inferior temporal cortex. Science, 310:863-866.
• Quian Quiroga R, Reddy L, Kreiman G, Koch C, Fried I (2005) Invariant visual representation by single neurons in the human brain. Nature, 435:1102-1107
• Crick F, Koch C, Kreiman G, Fried I (2004) Consciousness and Neurosurgery. Neurosurgery 55:272-282

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