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)
Dec 4
 David Mattingly (University of New Hampshire)
   

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?
 
Searching for spacetime structure with ultra-high energy cosmic rays
David Mattingly (University of New Hampshire), Dec 4
Some approaches to quantum gravity suggest that as a result of the microscopic structure of spacetime Poincare invariance is not an exact symmetry of local physics at low energies. In other words, special relativity is not quite correct. This possibility has spawned a tremendous amount of work on the 'phenomenology' of such approaches as there might be a testable consequence for at least some theories of quantum gravity. We straightforwardly discuss how the spectrum of ultra-high energy cosmic rays near the GZK cutoff as measured by the Pierre Auger Observatory places stringent limits on any deviation from special relativity. In a common scenario where only Lorentz boost symmetry is broken we show that special relativity is accurate to within one part in 10^19 even at the highest energies ever recorded, which poses a significant observational hurdle for these quantum gravity models.