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Last Name
Institution

Gabriel Kreiman, Ph.D.

TitleAssociate Professor of Ophthalmology
InstitutionChildren's Hospital Boston
DepartmentOphthalmology
AddressChildren's Hospital
Karp 11217
1 Blackfan Circle
Boston MA 02115
Phone6179192530
Fax617/667-2767
Other Positions
TitleAssistant Professor of Neurology
InstitutionChildren's Hospital Boston
DepartmentNeurology


 Biography 
 awards and honors
1990 - National Math Olympiads
1997 - Argentine Chemistry Associtation
2002 - Milton Clauser Doctoral Prize
2002 - Lawrence Ferguzon Prize
2003 - 2006MIT Dean of Science Whiteman Award
2007 - 2008Career Development Award
2008 - Klingenstein Fund Award
2008 - Whitehall Foundation Award
2009 - 2014NIH New Innovator Award

 Overview 
 overview
Kreiman Lab Web Site
http://klab.tch.harvard.edu
gabriel.kreiman@tch.harvard.edu


 Mentoring 
 current student opportunities
Available: 09/01/13, Expires: 12/31/14

1) Study the neuronal circuits involved in visual recognition 2) Develop biophysically inspired models of visual recognition Visit http://kreiman.hms.harvard.edu for more details

Available: 09/01/13, Expires: 12/31/14

Applications are invited for a Research Assistant position in the Kreiman lab. We are looking for an innovative and enthusiastic researcher person with experience and interest in Neuroscience research. The research efforts will involve conducting neurophysiological and psychophysics studies in human subejcts. To be considered for this position please submit your application including • CV • list of publications • names of three people that are familiar with your work Gabriel Kreiman gabriel.kreiman@tch.harvard.edu For more information about the lab and recent publications, see: http://klab.tch.harvad.edu/

Available: 09/01/13, Expires: 12/31/14

The Kreiman Lab [kreiman.hms.harvard.edu] combines neurophysiological measurements, psychophysics and computational modeling to study the neuronal circuits and mechanisms underlying cognition. The lab has open positions for enthusiastic students interested in research: 1) Neurophysiology and psychophysics of visual recognition. Our visual system has the remarkable ability of recognizing patterns (e.g. faces) in spite of major changes in the image (e.g. changes in illumination, rotation, etc.). The aim of this project is to combine neurophysiological recordings and quantitative study of behavioral recognition performance to understand how we can recognize objects in a transformation-tolerant manner. 2) Towards an artificial vision system. The aim of this project is to develop a computational model and algorithm that can mimic and capture the essential principles behind visual recognition in the primate brain. The performance of the computational algorithm will be compared against quantitative behavioral measurements, neurophysiology and will also be tested in real-world recognition applications. 3) Development of the visual recognition machinery. For publications and more information about the lab, please visit us at: http://klab.tch.harvard.edu Sample publications: Neuron (2011). 69: 548-562. Current Biology (2010) 20:872-879. Nature (2010). 465:182-187. Neuron (2009) 62:281-290. Current Opinion in Neurobiology (2007) 17:471-475 Progress In Brain Research (2007)165C:33-56. Science (2005) 310:863-866. Nature (2005) 435:1102-

Available: 09/01/13, Expires: 12/31/14

Understand the neuronal circuits and mechanisms for memory formation in the human brain Visit http://kreiman.hms.harvard.edu for more information

Visual Object Recognition[login at prompt]
Available: 09/01/13, Expires: 12/31/14

Investigate the mechanisms of visual object recognition. The student will perform research in the lab, investigating the neuronal circuits and mechanisms involved in visual object recognition. The research efforts involve one or more of the following: 1) psychophysics of visual object recognition whereby we investigate how well subjects can recognize objects in transformation-invariant manner and the development of visual recognition skills 2) use of computational tools to model human visual recognition and compare computer vision versus human vision 3) neurophysiological studies to investigate the circuits in the human temporal lobe involved in visual recognition.

Available: 11/01/12, Expires: 10/01/14

This project involves studying the mechanisms underlying transcriptional control by combining computational/mathematical modeling, analyses of genomic and other data sets and development of quantitative models. The student will investigate several aspects of transcriptional control including the histone code, alternative splicing, promoters and transcription factor interactions. The student will work together with researchers in the lab including the PI to enhance his/her learning experience. The goal is for the student to become increasingly independent and lead the project including publication of the results. The student will acquire several skills including machine learning, programming, computational modeling, bioinformatics, computational/systems biology.


 Bibliographic 
 selected publications
Publications listed below are automatically derived from MEDLINE/PubMed and other sources, which might result in incorrect or missing publications. Faculty can login to make corrections and additions.
List All   |   Timeline
  1. Murugan R, Kreiman G. Theory on the coupled stochastic dynamics of transcription and splice-site recognition. PLoS Comput Biol. 2012 Nov; 8(11):e1002747.
    View in: PubMed
  2. Bansal AK, Singer JM, Anderson WS, Golby A, Madsen JR, Kreiman G. Temporal stability of visually selective responses in intracranial field potentials recorded from human occipital and temporal lobes. J Neurophysiol. 2012 Dec; 108(11):3073-86.
    View in: PubMed
  3. Hemberg M, Gray JM, Cloonan N, Kuersten S, Grimmond S, Greenberg ME, Kreiman G. Integrated genome analysis suggests that most conserved non-coding sequences are regulatory factor binding sites. Nucleic Acids Res. 2012 Sep; 40(16):7858-69.
    View in: PubMed
  4. Burbank KS, Kreiman G. Depression-biased reverse plasticity rule is required for stable learning at top-down connections. PLoS Comput Biol. 2012; 8(3):e1002393.
    View in: PubMed
  5. Kreiman G, Maunsell JH. Nine criteria for a measure of scientific output. Front Comput Neurosci. 2011; 5:48.
    View in: PubMed
  6. Tang H, Kreiman G. Face recognition: vision and emotions beyond the bubble. Curr Biol. 2011 Nov 8; 21(21):R888-90.
    View in: PubMed
  7. Murugan R, Kreiman G. On the minimization of fluctuations in the response times of autoregulatory gene networks. Biophys J. 2011 Sep 21; 101(6):1297-306.
    View in: PubMed
  8. Hemberg M, Kreiman G. Conservation of transcription factor binding events predicts gene expression across species. Nucleic Acids Res. 2011 Sep 1; 39(16):7092-102.
    View in: PubMed
  9. Fried I, Mukamel R, Kreiman G. Internally generated preactivation of single neurons in human medial frontal cortex predicts volition. Neuron. 2011 Feb 10; 69(3):548-62.
    View in: PubMed
  10. Anderson WS, Kreiman G. Neuroscience: what we cannot model, we do not understand. Curr Biol. 2011 Feb 8; 21(3):R123-5.
    View in: PubMed
  11. Kreiman G. Decoding ensemble activity from neurophysiological recordings in the temporal cortex. Conf Proc IEEE Eng Med Biol Soc. 2011; 2011:5904-7.
    View in: PubMed
  12. Blumberg J, Kreiman G. How cortical neurons help us see: visual recognition in the human brain. J Clin Invest. 2010 Sep; 120(9):3054-63.
    View in: PubMed
  13. Agam Y, Liu H, Papanastassiou A, Buia C, Golby AJ, Madsen JR, Kreiman G. Robust selectivity to two-object images in human visual cortex. Curr Biol. 2010 May 11; 20(9):872-9.
    View in: PubMed
  14. Kim TK, Hemberg M, Gray JM, Costa AM, Bear DM, Wu J, Harmin DA, Laptewicz M, Barbara-Haley K, Kuersten S, Markenscoff-Papadimitriou E, Kuhl D, Bito H, Worley PF, Kreiman G, Greenberg ME. Widespread transcription at neuronal activity-regulated enhancers. Nature. 2010 May 13; 465(7295):182-7.
    View in: PubMed
  15. Quian Quiroga R, Kreiman G. Measuring sparseness in the brain: comment on Bowers (2009). Psychol Rev. 2010 Jan; 117(1):291-7.
    View in: PubMed
  16. Singer J, Kreiman G. Toward unmasking the dynamics of visual perception. Neuron. 2009 Nov 25; 64(4):446-7.
    View in: PubMed
  17. Rasch M, Logothetis NK, Kreiman G. From neurons to circuits: linear estimation of local field potentials. J Neurosci. 2009 Nov 4; 29(44):13785-96.
    View in: PubMed
  18. Liu H, Agam Y, Madsen JR, Kreiman G. Timing, timing, timing: fast decoding of object information from intracranial field potentials in human visual cortex. Neuron. 2009 Apr 30; 62(2):281-90.
    View in: PubMed
  19. Meyers EM, Freedman DJ, Kreiman G, Miller EK, Poggio T. Dynamic population coding of category information in inferior temporal and prefrontal cortex. J Neurophysiol. 2008 Sep; 100(3):1407-19.
    View in: PubMed
  20. Kreiman G. Single unit approaches to human vision and memory. Curr Opin Neurobiol. 2007 Aug; 17(4):471-5.
    View in: PubMed
  21. Leamey CA, Glendining KA, Kreiman G, Kang ND, Wang KH, Fassler R, Sawatari A, Tonegawa S, Sur M. Differential gene expression between sensory neocortical areas: potential roles for Ten_m3 and Bcl6 in patterning visual and somatosensory pathways. Cereb Cortex. 2008 Jan; 18(1):53-66.
    View in: PubMed
  22. Serre T, Kreiman G, Kouh M, Cadieu C, Knoblich U, Poggio T. A quantitative theory of immediate visual recognition. Prog Brain Res. 2007; 165:33-56.
    View in: PubMed
  23. Tropea D, Kreiman G, Lyckman A, Mukherjee S, Yu H, Horng S, Sur M. Gene expression changes and molecular pathways mediating activity-dependent plasticity in visual cortex. Nat Neurosci. 2006 May; 9(5):660-8.
    View in: PubMed
  24. Kreiman G, Hung CP, Kraskov A, Quiroga RQ, Poggio T, DiCarlo JJ. Object selectivity of local field potentials and spikes in the macaque inferior temporal cortex. Neuron. 2006 Feb 2; 49(3):433-45.
    View in: PubMed
  25. Hung CP, Kreiman G, Poggio T, DiCarlo JJ. Fast readout of object identity from macaque inferior temporal cortex. Science. 2005 Nov 4; 310(5749):863-6.
    View in: PubMed
  26. Quiroga RQ, Reddy L, Kreiman G, Koch C, Fried I. Invariant visual representation by single neurons in the human brain. Nature. 2005 Jun 23; 435(7045):1102-7.
    View in: PubMed
  27. Yeo G, Holste D, Kreiman G, Burge CB. Variation in alternative splicing across human tissues. Genome Biol. 2004; 5(10):R74.
    View in: PubMed
  28. Crick F, Koch C, Kreiman G, Fried I. Consciousness and neurosurgery. Neurosurgery. 2004 Aug; 55(2):273-281; discussion 281-2.
    View in: PubMed
  29. Kreiman G. Identification of sparsely distributed clusters of cis-regulatory elements in sets of co-expressed genes. Nucleic Acids Res. 2004; 32(9):2889-900.
    View in: PubMed
  30. Su AI, Wiltshire T, Batalov S, Lapp H, Ching KA, Block D, Zhang J, Soden R, Hayakawa M, Kreiman G, Cooke MP, Walker JR, Hogenesch JB. A gene atlas of the mouse and human protein-encoding transcriptomes. Proc Natl Acad Sci U S A. 2004 Apr 20; 101(16):6062-7.
    View in: PubMed
  31. Kreiman G, Fried I, Koch C. Single-neuron correlates of subjective vision in the human medial temporal lobe. Proc Natl Acad Sci U S A. 2002 Jun 11; 99(12):8378-83.
    View in: PubMed
  32. Rees G, Kreiman G, Koch C. Neural correlates of consciousness in humans. Nat Rev Neurosci. 2002 Apr; 3(4):261-70.
    View in: PubMed
  33. Krahe R, Kreiman G, Gabbiani F, Koch C, Metzner W. Stimulus encoding and feature extraction by multiple sensory neurons. J Neurosci. 2002 Mar 15; 22(6):2374-82.
    View in: PubMed
  34. Zirlinger M, Kreiman G, Anderson DJ. Amygdala-enriched genes identified by microarray technology are restricted to specific amygdaloid subnuclei. Proc Natl Acad Sci U S A. 2001 Apr 24; 98(9):5270-5.
    View in: PubMed
  35. Kreiman G, Koch C, Fried I. Imagery neurons in the human brain. Nature. 2000 Nov 16; 408(6810):357-61.
    View in: PubMed
  36. Kreiman G, Koch C, Fried I. Category-specific visual responses of single neurons in the human medial temporal lobe. Nat Neurosci. 2000 Sep; 3(9):946-53.
    View in: PubMed
  37. Ouyang Y, Rosenstein A, Kreiman G, Schuman EM, Kennedy MB. Tetanic stimulation leads to increased accumulation of Ca(2+)/calmodulin-dependent protein kinase II via dendritic protein synthesis in hippocampal neurons. J Neurosci. 1999 Sep 15; 19(18):7823-33.
    View in: PubMed
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