|
Physics Colloquia Fall 2009 (Fridays 1:00 PM in PS 227)
Titles link to the abstracts.
Date |
Speaker |
Title |
Sep 25 |
Viktor Jirsa (FAU) |
|
Oct 2 |
Armin Fuchs (FAU) |
|
Oct 16 |
Andy Lau (FAU) |
|
Nov 6 |
Dierdre Shoemaker (Georgia Tech) |
|
Nov 13 |
Vyacheslav Murzin (FAU) |
|
Nov 20 |
Caroline Simpson (FIU) |
|
| |
Colloquium Abstracts
Biological Intelligence-avenues, challenges, opportunities |
| Viktor Jirsa (FAU), Sep 25 |
|
Performing intelligent behavior has an intrinsic temporal component. We
posit that the study of the /temporal dynamics of intelligence /is
essential for any serious attempt of understanding intelligent sensing,
acting and behaving in biological systems. Over the past few years we
have developed at FAU and in collaboration with CNRS a framework that
systematically relates brain function as it is expressed in human
behavior and cognition to its representation in the brain network
dynamics. In particular, we have demonstrated that human timing
behavior
can be represented in terms of a particular class of dynamical systems,
so-called Structured Flows on Manifolds (SFM). We propose to expand
this research and systematically develop various cognitive
architectures on the basis of SFMs and their network representation.
Our concepts are tested explicitly in brain imaging studies in the
human and monkey and can be implemented in intelligent robot devices.
Given the current
reorganization of the research landscape at FAU, the theme of
biological intelligence offers a unifying framework providing testable,
more realistic and flexible, yet rigorous, psychological models with
direct connections to possible realizations in the biological brain as
well as in technical devices, thereby directly importing into the
philosophical debate of brain and mind.
|
| |
Structure, Dynamics and Function of the Human
Brain: Noninvasive Recording Techniques and Realistic
Models
|
| Armin Fuchs (FAU), Oct 2 |
|
Starting from the question: what are the basic requirements to describe and
understand a complex system, we give an overview on the modern noninvasive
imaging techniques that provide insight into the human brain's structure
and function. We discuss the effects that homogeneous (short-range) and
heterogeneous (long-range) connections within the system have on its
dynamical behavior based on simple models that include transmission delays.
Finally, we show how the folded cortical surface can be incorporated in
realistic models of structure, dynamics and function of the human brain.
|
| |
Soft matters: where physics and biology meet at the micron scale
|
| Andy Lau (FAU), Oct 16 |
|
Soft matter is an active research field of condensed matter, whose material
properties are characterized by the ease of response to external forces. A
particularly exciting reaearch area is the overlap of soft matter and
cellular biology. Indeed, the fundematal blocks of life - the plasma
membrane, the cytoskeleton, microtubule, DNA, and actin - are all soft
materials. However, biological systems such as living cells are
nonequilibrium systems that consume and dissipate energy. These active
systems exhibit phenomena that can be quite distinct from those of
conventional equilibrium soft materials. In this colloquium, we will survey
this emerging field of soft matter, with examples drawn from my own research.
|
| |
Numerical Relativity as a Tool for Gravitational Wave Astronomy
|
| Deirdre Shoemaker
(Georgia Institute of Technology), Nov 6 |
|
The detection of gravitational waves is expected with
advanced ground-based detectors, and advanced LIGO may be operational
as early as 2014. Once the detection is routine, gravitational physics
will become a data-driven field and the new field of gravitational wave
astronomy will be borne. The theoretical predictions of gravitational
wave sources play a fundamental role in the propsects for detecting
gravitational waves. We look at the detection of gravitational waves
and the characterization of their sources from the viewpoint of a
source theorist. In particular, we explore the role of numerical
relativity and it's advances in solving sources of compact object
binaries in today's detection schemes and tomorrow's gravitational wave
astronomy.
|
| |
Detecting the Spatiotemporal Dynamics of Neural Activity on
the Cortical Surface: Applying Anatomically Constrained
Beamforming to EEG
|
| Vyacheslav Murzin (FAU), Nov 13 |
|
The neurophysiological signals that are recorded in EEG
(electroencephalography) and MEG (magnetoencephalography) originate
from current flow perpendicular to the cortical surface due to the
columnar organization of pyramidal cells in the cortical gray matter.
These locations and directions can be used as anatomical constraints
for dipolar sources estimating neural activity from MEG recordings.
Here we extend anatomically constrained beamforming to EEG, which
requires a more sophisticated forward model than MEG due to the
blurring of the electric potential at tissue boundaries, but can
account for both tangential and radial sources. Using CT scans we
create a realistic three-layer head model consisting of tessellated
surfaces representing tissue boundaries cerebrospinal fluid-skull,
skull-scalp and scalp-air. The cortical gray matter surface, the
anatomical constraint for the source dipoles, is extracted from MRI
scans. EEG beamforming is implemented in a set of simulated data and
compared for three different head models: single sphere, multi-shell
sphere and realistic geometry multi-shell model that employed a
boundary element method. Beamformer performance was also analyzed and
evaluated for multiple sources and varying amounts of noise. We show
that using anatomical constraints with the beamforming algorithm
greatly reduces computation time while increasing the spatial accuracy
of the reconstructed sources of neural activity. Using the spatial
Laplacian instead of the electric potential in combination with
beamforming further improves the spatial resolution and allows for the
detection of highly correlated sources.
|
| |
Star Formation in Dwarf Galaxies: The LITTLE THINGS Project
|
| Caroline Simpson (FIU), Nov 20 |
|
The processes that lead to star formation on galactic scales are poorly
understood even in the simplest systems in the universe, dwarf galaxies. At
best we have incomplete knowledge of certain processes in certain
environments. To further our understanding of how star formation works, we
have recently completed high resolution observations of the hydrogen gas in
a sample of 41 dwarf galaxies chosen to span a range of luminosities. These
data are being combined with optical, UV, and IR data to trace stellar
populations, gas content, dynamics, and star formation indicators in our
dwarfs. With this unprecedented data set, we intend to answer the following
questions: 1) What regulates cloud/star formation in tiny galaxies? 2) How
is star formation occurring in the outer parts of dwarf galaxies, where the
gas is gravitationally stable? 3) What happens to the star formation process
at breaks in the exponential stellar light profiles? 4) And, what is going
on with Blue Compact Dwarfs?
|
| |
|