- Moshe Bar (Neuroscientist)
"Moshe Bar" was born in Beer-Sheva, Israel. He is an Associate Professor in Radiology at Harvard Medical School and an Assistant in Neuroscience at the [http://www.nmr.mgh.harvard.edu/martinos/flashHome.php Martinos Center for Biomedical Imaging] at MGH. Dr. Bar uses a Cognitive Neuroscience approach to study the underlying cortical and behavioral mechanisms. Specifically, combining cognitive methods with neuroimaging technology (functional magnetic resonance imaging, fMRI and magnetoencephalography, MEG), his laboratory addresses this goal from multiple directions. His long-term goal is to define and test individual unifying principles that would provide an overarching explanation for many of the astonishing feats of the cognitive brain in simple terms.
Dr. Bar received his B.Sc. degree in Electrical Engineering from Ben-Gurion University, Israel in 1988, and his M.Sc. degree in Computer Science and Applied Mathematics from The Weizmann Institute of Science, Israel in 1994. He went on to obtain his Ph.D. in Cognitive Neuroscience Program from the
University of Southern Californiain 1998. He then completed a post-doctoral research fellowship in the Department of Radiology at Martinos (NMR) Center for Biomedical Imaging and at Harvard University from 1988 to 2001. Dr. Moshe Bar is an Associate Professor in Radiology at Harvard Medical School and an Assistant in Neuroscience at the [http://www.nmr.mgh.harvard.edu/martinos/flashHome.php Martinos Center for Biomedical Imaging] at MGH.
Major Research Interests
"Cortical Mechanisms of Object Recognition and Top-Down Facilitation in Visual Processing"
Dr. Bar and his group used fMRI to study the cortical mechanisms subserving the ability to recognize visual objects (Bar et al., 2001  ). This experiment revealed a focus in the fusiform gyrus where activation was directly modulated by level of recognition success. These data further indicated that visual consciousness of an object’s identity is achieved gradually, rather than being an abrupt event. In addition, unlike the traditional view, the findings demonstrated that the prefrontal cortex is an integral component in the network mediating object recognition. Subsequently, Dr. Bar proposed that coarse visual information (i.e., low spatial frequencies) is projected rapidly from early visual cortex to the prefrontal cortex, where it triggers top-down facilitation of object recognition (Bar, 2003  ). Three recent studies in his lab strongly support this model (Bar et al., 2006  ).
"Contextual Analysis and Scene Perception"
While much has already been revealed about the cognitive and cortical mechanisms mediating recognition of individual objects, surprisingly little is available with regard to the neural underpinnings of contextual analysis and scene perception. Objects in our environment rarely appear in isolation, however, but rather tend to be grouped in typical contexts. Dr. Bar and his group recently revealed the components of the cortical network mediating contextual processing of everyday objects (Bar & Aminoff, 2003  ). In a subsequent study combining event-related fMRI with MEG to achieve superior spatial and temporal resolutions (i.e., a spatial accuracy of 1 mm and a temporal resolution of a few milliseconds), they characterized the cortical dynamics mediating contextual analysis. Their combined findings have led to the global hypothesis that contextual information facilitates object recognition by being extracted rapidly to generate predictions about the most likely interpretation of the input (Bar, 2004  ). This hypothesis is currently being tested in his laboratory, as well as in other laboratories, with an underlying proposal linking contextual processing with a general top-down facilitation of visual cognition. Especially exciting are new collaborations with other labs in the area that offer an application of Dr. Bar’s findings to clinical populations such as patients with Depression and Alzheimer’s disease.
Recognizing a previously seen object is generally easier than recognizing the same object when it is first encountered. This facilitation, termed priming, has been associated with physiological findings where familiar stimuli elicit a relatively reduced cortical response. However, no direct evidence for this connection has been reported so far. By showing that priming and the corresponding fMRI signal have highly similar dynamics (Zago et al, 2005  ), Dr. Bar’s group provided a critical link between the two. Furthermore, they demonstrated that behavioral priming and the corresponding reduction in cortical response maximized for a limited range of previous exposure duration, and was significantly less pronounced for shorter or longer exposure durations. This counter-intuitive finding has led them to propose a mechanism for selective and efficient object encoding where only the essential properties of a visual object remain represented. This proposal is currently being tested in his lab within the broader context of visual memory.
*M. Bar, R. Tootell, D. Schacter, D. Greve, B. Fischl, J. Mendola, B. Rosen and A. M. Dale (2001). Cortical mechanisms of explicit visual object recogntion. Neuron, 29, 529-535. 
*M. Bar (2003). A cortical mechanism for triggering top-down facilitation in visual object recognition. Journal of Cognitive Neuroscience, 15, 600-609. 
*M. Bar, K.S. Kassam, A.S. Ghuman, J. Boshyan, A.M. Schmidt, A.M. Dale, M.S. Hamalainen, K. Marinkovic, D.L. Schacter, B.R. Rosen and E. Halgren (2006). Top-down facilitation of visual recognition. Proceedings of the National Academy of Science, 103(2), 449-454. 
*M. Bar and E. Aminoff (2003). Cortical analysis of visual context. Neuron, 38, 347-358. 
*M. Bar (2004). Visual objects in context. Nature Reviews: Neuroscience, 5, 617-629. 
*L. Zago, M.J. Fenske, E. Aminoff and M. Bar (2005). The rise and fall of priming: How visual exposure shapes cortical representations of objects. Cerebral Cortex, 15, 1655-1665. 
*M. Bar (2007). The Proactive Brain: Using analogies and associations to generate predictions. Trends in Cognitive Sciences, 11(7), 280-289. 
* [http://barlab.mgh.harvard.edu/index.htm BarLab]
* [http://www.nmr.mgh.harvard.edu/martinos/flashHome.php Martinos Center for Biomedical Imaging]
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