[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