[CBIAnnounce] upcoming physics talks

David Heeger david.heeger at nyu.edu
Wed Nov 26 12:16:45 EST 2008


There two upcoming talks in physics that might be of interest to some  
of you. Details below.

DH

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

December 2, 2008 Tuesday 2:00 PM  (I think that's a mistake, it is  
4:00 PM)
Meyer <http://physics.as.nyu.edu/object/physics.directions> 6th Floor  
Conference Room
*Soft Condensed Matter Seminars* (csmr <http://physics.nyu.edu/ 
events.php?EventsPage=csmr>)

*Dmitri Novikov*

*/ The Condensed Matter Physics of MRI /*

Magnetic resonance imaging (MRI) is a prime non-invasive medical  
diagnostic tool. It combines NMR physics of water protons with  
imaging techniques allowing the creation of anatomical maps of the  
human body. These maps, with millimeter-scale resolution attainable  
by existing human MRI technology, are yet too grainy for imaging  
cellular microstructure on a micrometer scale. Hence current research  
is focusing on extracting cellular-scale information indirectly, by  
analyzing the NMR signals from individual pixels of an MRI scan. In  
practice, this is a challenging inverse problem that requires the  
modeling of diffusion and relaxation in heterogeneous media. Here the  
connection with condensed matter physics naturally emerges. I will  
draw parallels with transport in disordered condensed matter systems  
and illustrate how one can quantify biophysical properties of  
tissues, such as cell size, magnetization, diffusivity, and membrane  
permeability. Correlating these properties with tissue physiology and  
pathology opens up wide opportunities to develop novel diagnostic  
methods, as well as to understand and quantify biological processes  
in-vivo.

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

December 4, 2008 Thursday 4:00 PM Meyer <http://physics.as.nyu.edu/ 
object/physics.directions> 122
*Physics Colloquia* (colloquia <http://physics.nyu.edu/events.php? 
EventsPage=colloquia>)


*Dmitri Chklovskii*

*/ Statistical Physics Meets Neurobiology: Is Your Brain Wired  
Optimally? /*

The human brain is a network containing a hundred billion neurons,  
each communicating with several thousand others. As the wiring for  
neuronal communication draws on limited space and energy resources,  
evolution had to optimize their use. This principle of minimizing  
wiring costs explains many features of brain architecture, including  
placement and shape of many neurons. However, the shape of some  
neurons and their synaptic properties remained unexplained. This led  
us to the principle of maximization of brain's ability to store  
information, which can be expressed as maximization of entropy.  
Combination of the two principles, analogous to the minimization of  
free energy in statistical physics, provides a systematic view of  
brain architecture, necessary to explain brain function.




More information about the CBIAnnounce mailing list