Bulletin of the American Physical Society
APS March Meeting 2013
Volume 58, Number 1
Monday–Friday, March 18–22, 2013; Baltimore, Maryland
Session W44: Focus Session: The Physics of Behavior |
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Sponsoring Units: DBIO Chair: Greg J. Stephens, Vrije Universiteit Amsterdam and Okinawa Institute of Science and Technology Room: Hilton Baltimore Holiday Ballroom 1 |
Thursday, March 21, 2013 2:30PM - 3:06PM |
W44.00001: Computational and physiological mechanisms of sensory-motor processing Invited Speaker: Leslie Osborne |
Thursday, March 21, 2013 3:06PM - 3:18PM |
W44.00002: Dimentionality and behavior of swimming Zebrafish: ``The EigenFish'' Kiran Girdhar, Martin Gruebele, Yann Chemla How simple is the underlying control mechanism for the complex locomotion of vertebrates? To answer this question, we study the swimming behavior of zebrafish larvae. A dimensionality reduction method (singular value decomposition), in analogy to previous studies of worms, is used to analyze swimming movies of fish. That way, the animals can directly provide us with a minimal set of shapes to describe their motion, rather than us imposing arbitrary coordinates. We show that two low imensional attractors (an ellipse and a distorted ellipse) embedded in a threedimensional space of motion coordinates are sufficient to describe \textgreater\ 95{\%} of the locomotion. We also show that scoots and R-turns, previously thought to be independent behaviors based on qualitative studies, are in fact just extremes of a~continuous family of motions bounded by~the two attractors. [Preview Abstract] |
Thursday, March 21, 2013 3:18PM - 3:30PM |
W44.00003: Controlling neural activity in \textit{Caenorhabditis elegans} to evoke chemotactic behavior Askin Kocabas, Ching-Han Shen, Zengcai V. Guo, Sharad Ramanathan Animals locate and track chemoattractive gradients in the environment to find food. With its simple nervous system, \textit{Caenorhabditis elegans} is a good model system in which to understand how the dynamics of neural activity control this search behavior. To understand how the activity in its interneurons coordinate different motor programs to lead the animal to food, here we used optogenetics and new optical tools to manipulate neural activity directly in freely moving animals to evoke chemotactic behavior. By deducing the classes of activity patterns triggered during chemotaxis and exciting individual neurons with these patterns, we identified interneurons that control the essential locomotory programs for this behavior. Notably, we discovered that controlling the dynamics of activity in just one interneuron pair was sufficient to force the animal to locate, turn towards and track virtual light gradients. [Preview Abstract] |
Thursday, March 21, 2013 3:30PM - 3:42PM |
W44.00004: Quantification of Nociceptive Escape Response in \textit{C.elegans} Kawai Leung, Aylia Mohammadi, William Ryu, Ilya Nemenman Animals cannot rank and communicate their pain consciously. Thus in pain studies on animal models, one must infer the pain level from high precision experimental characterization of behavior. This is not trivial since behaviors are very complex and multidimensional. Here we explore the feasibility of \textit{C.elegans} as a model for pain transduction. The nematode has a robust neurally mediated noxious escape response, which we show to be partially decoupled from other sensory behaviors. We develop a nociceptive behavioral response assay that allows us to apply controlled levels of pain by locally heating worms with an IR laser. The worms' motions are captured by machine vision programming with high spatiotemporal resolution. The resulting behavioral quantification allows us to build a statistical model for inference of the experienced pain level from the behavioral response. Based on the measured nociceptive escape of over 400 worms, we conclude that none of the simple characteristics of the response are reliable indicators of the laser pulse strength. Nonetheless, a more reliable statistical inference of the pain stimulus level from the measured behavior is possible based on a complexity-controlled regression model that takes into account the entire worm behavioral output. [Preview Abstract] |
Thursday, March 21, 2013 3:42PM - 3:54PM |
W44.00005: Discovery of stereotypy through behavioral space embedding Gordon Berman, Daniel Choi, William Bialek, Joshua Shaevitz Most experiments in the neurobiology of behavior rely upon the concept that animals frequently engage in stereotyped movements -- behaviors that an animal performs often and with great similarly. While these actions are often the basis for mapping neural circuits and understanding the effects of genetic manipulations, stereotypy is usually defined in an ad hoc manner, thereby limiting the sensitivity and repeatability of subsequent analyses. Moreover, the underlying assumption that an animal's behavior can be described in terms of discrete states typically remains unverified. In this talk, I will describe our novel method for the identification and characterization of stereotyped behaviors. Using the fruit fly \emph{Drosophila melanogaster} as a model organism, we show that it is possible to start from raw videos of a freely-behaving animal and statistically isolate stereotyped movements. Our method achieves this through leveraging ideas from statistical physics, non-linear dynamics, and information theory. The rigorous behavioral metrics resulting from this technique allow us to explore questions in animal behavior ranging from speciation, to aging, to the control of locomotion, thus providing further insight in the interplay between genes, neurons, and behavior. [Preview Abstract] |
Thursday, March 21, 2013 3:54PM - 4:06PM |
W44.00006: Swarming in disordered environments Ajay Gopinathan, David A. Quint The emergence of collective motion over a wide range of length scales in biology has inspired research in a multitude of disciplines. Possessing only local information, a group of moving individuals can form crowds, swarms or flocks which can traverse the entire system forming a self organized co-moving collective. An important question that arises is: how do these groups deal with environmental disorder? It is rare that perfectly connected homogeneous environments exist in nature and more often biological environments are intrinsically spatially disordered. We investigate the effects of intrinsic disorder or \textit{topological noise} on the formation of collective motion by studying interacting agents on a $2d$ percolated lattice with bond occupation probability $p$. We find that the existence of collective motion depends critically on $p$ and disappears completely for rather small amounts of disorder. Furthermore, we show that repulsive forces between agents within the swarm can rescue collective motion even for large amounts of topological disorder, suggesting that nearest neighbor alignment alone is not enough for swarms to navigate a disordered environment. [Preview Abstract] |
Thursday, March 21, 2013 4:06PM - 4:18PM |
W44.00007: Physical limits to gradient sensing by swimming cells Nicholas Licata The chemotactic motion of cells relies on their ability to infer the location of a chemical source from the random arrival of molecules at chemical receptors on the cell surface. Small organisms like bacterial cells generally employ a temporal sensing mechanism to measure spatial gradients in concentration. For example, the bacterium Escherichia coli compares concentrations in time as it swims, and modulates its swimming behavior accordingly to swim up the concentration gradient. Slightly larger eukaryotic cells are able to directly sense spatial gradients of chemicals across their surface. Previous studies have demonstrated that the physical process of diffusion sets a fundamental limit to the accuracy with which cells can sense spatial gradients. However, most of these studies neglect the intrinsic coupling between the sensory task and the behavioral response of swimming. The swimming cell stirs the surrounding fluid, which in turn affects the arrival location of molecules at the cell surface, and hence the inferred spatial gradient. By considering the appropriate advection-diffusion equation for the arrival of molecules at the cell surface, we determine the fundamental physical limit to the accuracy of direct gradient sensing by swimming cells. [Preview Abstract] |
Thursday, March 21, 2013 4:18PM - 4:54PM |
W44.00008: Measurement of Behavioral Evolution in Bacterial Populations Invited Speaker: Robert Austin A curious aspect of bacterial behavior under stress is the induction of filamentation: the anomalous growth of certain bacteria in which cells continue to elongate but do not divide into progeny. We show that {\em E.coli} under the influence of the genotoxic antibiotic ciprofloxacin have robust filamentous growth, which provides individual bacteria a mesoscopic niche for evolution until resistant progeny can bud off and propagate. Hence, filamentation is a form of genomic amplification where even a single, isolated bacteria can have access to multiple genomes. We propose a model that predicts that the first arrival time of the normal sized progeny should follow a Gompertz distribution with the mean first arrival time proportional to the elongation rate of filament. These predictions agree with our experimental measurements. Finally, we suggest bacterial filament growth and budding has many similarities to tumor growth and metastasis and can serve as a simpler model to study those complicated processes. [Preview Abstract] |
Thursday, March 21, 2013 4:54PM - 5:06PM |
W44.00009: Environmental engineering simplifies subterranean locomotion control Nick Gravish, Darya Monaenkova, Michael A.D. Goodisman, Daniel I. Goldman We hypothesize that ants engineer habitats which reduce locomotion control requirements. We studied tunnel construction, and locomotion, in fire ants ({\em Solenopsis invicta}, body length $L = 0.35 \pm 0.05$). In their daily life, ants forage for food above ground and return resources to the nest. This steady-state tunnel traffic enables high-throughput biomechanics studies of tunnel climbing. In a laboratory experiment we challenged fire ants to climb through 8 cm long glass tunnels (D = 0.1 - 0.9 cm) that separated a nest from an open arena with food and water. During ascending and descending climbs we induced falls by a motion-activated rapid, short, downward translation of the tunnels. Normalized tunnel diameter ($D/L$) determined the ability of ants to rapidly recover from perturbations. Fall arrest probability was unity for small $D/L$, and zero for large $D/L$. The transition from successful to unsuccessful arrest occurred at $D/L = 1.4 \pm 0.3$. Through X-Ray computed tomography study we show that the diameter of ant-excavated tunnels is independent of soil-moisture content (studied from 1-20\%) and particle size (50-595 $\mu m$ diameter), and has a mean value of $D/L = 1.06 \pm 0.23$. Thus fire ants construct tunnels of diameter near the onset of fall instability. [Preview Abstract] |
Thursday, March 21, 2013 5:06PM - 5:18PM |
W44.00010: Mosh pits and Circle pits: Collective motion at heavy metal concerts Matthew Bierbaum, Jesse L. Silverberg, James P. Sethna, Itai Cohen Heavy metal concerts present an extreme environment in which large crowds ($\sim 10^2- 10^5$) of humans experience very loud music ($\sim130\rm{dB}$) in sync with bright, flashing lights, often while intoxicated. In this setting, we find two types of collective motion: mosh pits, in which participants collide with each other randomly in a manner resembling an ideal gas, and circle pits, in which participants run collectively in a circle forming a vortex of people. We model these two collective behaviors using a flocking model and find qualitative and quantitative agreement with the behaviors found in videos of metal concerts. Futhermore, we find a phase diagram showing the transition from a mosh pit to a circle pit as well as a predicted third phase, lane formation. [Preview Abstract] |
Thursday, March 21, 2013 5:18PM - 5:30PM |
W44.00011: Lift-off dynamics in a simple jumping robot Jeffrey Aguilar, Alex Lesov, Kurt Wiesenfeld, Daniel I. Goldman Jumping is an important behavior utilized by animals to escape predation, hunt, reach higher ground, and as a primary mode of locomotion. Many mathematical and physical robot models use numerous parameters and multi-link legs to accurately model jumping dynamics. However, a simple robot model can reveal important principles of high performance jumping. We study vertical jumping in a simple robot comprising an actuated mass-spring arrangement. The actuator frequency and phase are systematically varied to find optimal performance. Optimal jumps occur above and below (but not at) the robot's resonant frequency f$_{0}$. Two distinct jumping modes emerge: a simple jump which is optimal above f$_{0}$ is achievable with a squat maneuver, and a peculiar stutter jump which is optimal below f$_{0}$ is generated with a counter-movement. A simple dynamical model reveals how optimal lift-off results from non-resonant transient dynamics. An expanded explanation of this work is provided at http://crablab.gatech.edu/pages/jumpingrobot/index.html [Preview Abstract] |
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