Bulletin of the American Physical Society
APS March Meeting 2016
Volume 61, Number 2
Monday–Friday, March 14–18, 2016; Baltimore, Maryland
Session R41: Neural Control of BehaviorFocus
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Sponsoring Units: DBIO Chair: Gordon Berman, Emory University Room: 344 |
Thursday, March 17, 2016 8:00AM - 8:36AM |
R41.00001: Taking Action: How Small Brains Make Big Choices Invited Speaker: Gwyneth Card |
Thursday, March 17, 2016 8:36AM - 8:48AM |
R41.00002: Tracking C. elegans and its neuromuscular activity using NemaFlex Frank Van Bussel, Mizanur Rahman, Jennifer Hewitt, Jerzy Blawzdziewicz, Monica Driscoll, Nathaniel Szewczyk, Siva Vanapalli Recently, a novel platform has been developed for studying the behavior and physical characteristics of the nematode C.~elegans. This is NemaFlex, developed by the Vanapalli group at Texas Tech University to analyze movement and muscular strength of crawling C.~elegans. NemaFlex is a microfluidic device consisting of an array of deformable PDMS pillars, with which the C.~elegans interacts in the course of moving through the system. Deflection measurements then allow us to calculate the force exerted by the worm via Euler–Bernoulli beam theory. For the procedure to be fully automated a fairly sophisticated software analysis has to be developed in tandem with the physical device. In particular, the usefulness of the force calculations is highly dependent on the accuracy and volume of the deflection measurements, which would be prohibitively time-consuming if carried out by hand/eye. In order to correlate the force results with muscle activations the C.~elegans itself has to be tracked simultaneously, and pillar deflections precisely associated with mechanical-contact on the worm's body. Here we will outline the data processing and analysis routines that have been implemented in order to automate the calculation of these forces and muscular activations. [Preview Abstract] |
Thursday, March 17, 2016 8:48AM - 9:00AM |
R41.00003: High Throughput Interrogation of Behavioral Transitions in C. elegans Mochi Liu, Joshua Shaevitz, Andrew Leifer We present a high-throughput method to probe transformations from neural activity to behavior in \textit{Caenorhabditis elegans} to better understand how organisms change behavioral states. We optogenetically deliver white-noise stimuli to target sensory or inter neurons while simultaneously recording the movement of a population of worms. Using all the postural movement data collected, we computationally classify stereotyped behaviors in \textit{C. elegans} by clustering based on the spectral properties of the instantaneous posture. (Berman et al., 2014) Transitions between these behavioral clusters indicate discrete behavioral changes. To study the neural correlates dictating these transitions, we perform model-driven experiments and employ Linear-Nonlinear-Poisson cascades that take the white-noise stimulus as the input. The parameters of these models are fitted by reverse-correlation from our measurements. The parameterized models of behavioral transitions predict the worm's response to novel stimuli and reveal the internal computations the animal makes before carrying out behavioral decisions. Preliminary results are shown that describe the neural-behavioral transformation between neural activity in mechanosensory neurons and reversal behavior. [Preview Abstract] |
Thursday, March 17, 2016 9:00AM - 9:12AM |
R41.00004: Influence of the Enteric Nervous System on Gut Motility Patterns in Zebrafish Ryan Baker, Julia Ganz, Ellie Melancon, Judith Eisen, Raghuveer Parthasarathy The enteric nervous system (ENS), composed of diverse neuronal subtypes and glia, regulates essential gut functions including motility, secretion, and homeostasis. In humans and animals, decreased numbers of enteric neurons lead to a variety of types of gut dysfunction. However, surprisingly little is known about how the number, position, or subtype of enteric neurons affect the regulation of gut peristalsis, due to the lack of good model systems and the lack of tools for the quantitative characterization of gut motion. We have therefore developed a method of quantitative spatiotemporal mapping using differential interference contrast microscopy and particle image velocimetry, and have applied this to investigate intestinal dynamics in normal and mutant larval zebrafish. From movies of gut motility, we obtain a velocity vector field representative of gut motion, from which we can quantify parameters relating to gut peristalsis such as frequency, wave speed, deformation amplitudes, wave duration, and non-linearity of waves. We show that mutants with reduced neuron number have contractions that are more regular in time and reduced in amplitude compared to wild-type (normal) fish. We also show that feeding fish before their yolk is consumed leads to stronger motility patterns. [Preview Abstract] |
Thursday, March 17, 2016 9:12AM - 9:24AM |
R41.00005: Improved Software for Quantifying the Behavior of Drosophila Larvae Natalie Bernat, Marc Gershow A key advantage of small crawling organisms like C elegans and the Drosophila larva is that their behaviors may be assayed automatically using computer vision software. Current state of the art software is capable of detecting the positions and postures of crawling larvae and automatically categorize their behaviors in parallel. However, these algorithms, which are based on frame-by-frame analysis of thresholded black and white images, fail to correctly describe the postures of larvae executing sharp bends and have difficulty separating multiple larvae that are physically touching. We present new tracking software that uses intensity information in grayscale images and applies temporal smoothness constraints to positions and postures. We implemented this software as an ImageJ plugin, extending its portability and applicability. [Preview Abstract] |
Thursday, March 17, 2016 9:24AM - 9:36AM |
R41.00006: Development of a two photon microscope for tracking Drosophila larvae Doycho Karagyozov, Mirna Mihovilovic Skanata, Marc Gershow Current in vivo methods for measuring neural activity in Drosophila larva require immobilization of the animal. Although we can record neural signals while stimulating the sensory organs, we cannot read the behavioral output because we have prevented the animal from moving. Many research questions cannot be answered without observation of neural activity in behaving (freely-moving) animals. Our project aims to develop a tracking microscope that maintains the neurons of interest in the field of view and in focus during the rapid three dimensional motion of a free larva. [Preview Abstract] |
Thursday, March 17, 2016 9:36AM - 9:48AM |
R41.00007: Chemotaxis of \textit{Caenorhabditis elegans} in complex media: crawling, burrowing, 2D and 3D swimming, and controlled fluctuations hypothesis Amar Patel, Alejandro Bilbao, Mizanur Rahman, Siva Vanapalli, Jerzy Blawzdziewicz \textit{Caenorhabditis elegans} is a powerful genetic model, essential for studies in diverse areas ranging from behavior to neuroscience to aging, and locomotion and chemotaxis are the two key observables used. We combine our recently developed theory of nematode locomotion and turning maneuvers [Phys.\ Fluids 25, 081902 (2013)] with simple models of chemosensation to analyze nematode chemotaxis strategies in 2D and 3D environments. We show that the sharp-turn (pirouette) chemotaxis mechanism is efficient in diverse media; in particular, the nematode does not need to adjust the sensing or motion-control parameters to efficiently chemotax in 2D crawling, 3D burrowing, and 2D or 3D swimming. In contrast, the graduate-turn mechanism becomes inefficient in swimming, unless a phase-shift is introduced between the sensing signal and modulation of body wave to generate the gradual turn. We hypothesize that there exists a new ``controlled fluctuations'' chemotaxis mechanism, in which the nematode changes the intensity of undulation fluctuations to adjust the persistence length of the trajectory in response to a variation in chemoattractant concentration. [Preview Abstract] |
Thursday, March 17, 2016 9:48AM - 10:00AM |
R41.00008: Motor neurons in Drosophila flight control: could b1 be the one? Samuel Whitehead, Troy Shirangi, Itai Cohen Similar to balancing a stick on one’s fingertip, flapping flight is inherently unstable; maintaining stability is a delicate balancing act made possible only by near-constant, often-subtle corrective actions. For fruit flies, such corrective responses need not only be robust, but also fast: the \emph{Drosophila} flight control reflex has a response latency time of $\sim$5 ms, ranking it among the fastest reflexes in the animal kingdom. How is such rapid, robust control implemented physiologically? Here we present an analysis of a putatively crucial component of the \emph{Drosophila} flight control circuit: the b1 motor neuron. Specifically, we apply mechanical perturbations to freely-flying \emph{Drosophila} and analyze the differences in kinematics patterns between flies with manipulated and un-manipulated b1 motor neurons. Ultimately, we hope to identify the functional role of b1 in flight stabilization, with the aim of linking it to previously-proposed, reduced-order models for reflexive control. [Preview Abstract] |
Thursday, March 17, 2016 10:00AM - 10:12AM |
R41.00009: System identification and sensorimotor determinants of flight maneuvers in an insect Simon Sponberg, Robert Hall, Eatai Roth Locomotor maneuvers are inherently closed-loop processes. They are generally characterized by the integration of multiple sensory inputs and adaptation or learning over time. To probe sensorimotor processing we take a system identification approach treating the underlying physiological systems as dynamic processes and altering the feedback topology in experiment and analysis. As a model system, we use agile hawk moths (\emph{Manduca sexta}), which feed from real and robotic flowers while hovering in mid air. Moths rely on vision and mechanosensation to track floral targets and can do so at exceptionally low luminance levels despite hovering being a mechanically unstable behavior that requires neural feedback to stabilize. By altering the sensory environment and placing mechanical and visual signals in conflict we show a surprisingly simple linear summation of visual and mechanosensation produces a generative prediction of behavior to novel stimuli. Tracking performance is also limited more by the mechanics of flight than the magnitude of the sensory cue. A feedback systems approach to locomotor control results in new insights into how behavior emerges from the interaction of nonlinear physiological systems. [Preview Abstract] |
Thursday, March 17, 2016 10:12AM - 10:24AM |
R41.00010: Leveraging low-dimensional postures to resolve coiled shapes reveals new reorientation behaviors in the nematode \textit{C. elegans}. Greg Stephens, Onno Broekmans, William Ryu Low-dimensionality is both a fundamental property of many living systems and an aid in their quantitative analysis. Here, we exploit the low-dimensionality of \textit{C. elegans} body shape to develop a novel postural tracking algorithm which captures both simple worm shapes and also complex, self-occluding coils. We apply our algorithm to a thermally-evoked escape response with relatively simple coils and to more complex, spontaneous turns which occur during foraging. We divide the escape response into three post-stimulus phases, reversal, turn and post-turn, and find that the full distribution of reorientation angles is shaped by independent and significant contributions from all three phases, a result consistent with the release and presence of the monoamine tyramine during the entire response. In spontaneous coils we find two separable peaks of turning posture amplitudes, indicating distinct reorientation behaviors of large-amplitude ventral-side turns; large ventral bearing reorientations occur through a shape sequence similar to the escape response while large dorsal bearing reorientations are accomplished by overturning across the ventral side. We find that these large-amplitude turning events occur independently but with approximately matched rates that adapt on a similar timescale. [Preview Abstract] |
Thursday, March 17, 2016 10:24AM - 10:36AM |
R41.00011: Slithering on sand: kinematics and controls for success on granular media. Perrin E Schiebel, Tingnan Zhang, Jin Dai, Chaohui Gong, Miao Yu, Henry C Astley, Matthew Travers, Howie Choset, Daniel I Goldman Previously, we studied the \textit{subsurface }locomotion of undulatory sand-swimming snakes and lizards; using empirical drag response of GM to subsurface intrusion of simple objects allowed us to develop a granular resistive force theory (RFT) to model the locomotion and predict optimal movement patterns. However, our knowledge of the physics of GM at the surface is limited; this makes it impossible to determine how the desert-dwelling snake \textit{C. occipitalis} moves effectively (0.45$+$/-0.04 bodylengths/sec) on the surface of sand$. $We combine organism biomechanics studies, GM drag experiments, RFT calculations and tests of a physical model (a snake-like robot), to reveal how multiple factors acting together contribute to slithering on sandy surfaces. These include the kinematics---targeting an ideal waveform which maximizes speed while minimizing joint-level torque, the ability to modulate ground interactions by lifting body segments, and the properties of the GM. Based on the sensitive nature of the relationship between these factors, we hypothesize that having an element of force-based control, where the waveform is modulated in response to the forces acting between the body and the environment, is necessary for successful locomotion on yielding substrates. [Preview Abstract] |
Thursday, March 17, 2016 10:36AM - 10:48AM |
R41.00012: Dynamic Control of Walking and Paw-shaking in the Cat Jessica Green, Gennady Cymbalyuk Multistable central pattern generators (CPGs) are capable of producing multiple rhythmic patterns with different periods. We developed a model of a half center oscillator, consisting of two reciprocally inhibitory neurons. Each neuron contains two slow inward currents, a Na$^{\mathrm{+}}$current, and a Ca$^{\mathrm{++\thinspace }}$current. We found that a walking rhythm (1 Hz) and a paw-shaking rhythm (10 Hz) do coexist in this model . The kinetics of the inactivations of I$_{\mathrm{NaS}}$and I$_{\mathrm{CaS\thinspace }}$produce this multistability. A paw-shaking response can be demonstrated as a result of a switch in the multistable model or as a transient response of a nearby monostable model. The duration of this transient paw-shaking response depends on pulse duration and the phase of walking at which the pulse is initiated. We also developed a model of two populations with 20 neurons each, in which there are random inhibitory synapses across the two populations and random excitatory synapses within each population. This population model generates similar behavior as the two neuron model. [Preview Abstract] |
Thursday, March 17, 2016 10:48AM - 11:00AM |
R41.00013: Recovery methods of the dragonfly from irregular initial conditions. James Melfi, Anthony Leonardo, Jane Wang We release dragonflies from a magnetic tether in a wide range of initial orientations, which results in them utilizing multiple methods to regain their typical flight orientation. Special focus is placed on dropping them while upside down, as the recovery method used is a purely rolling motion. Filming this stereotypical motion with a trio of high speed cameras at 4000 fps, we capture detailed body and wing kinematics data to determine how the dragonfly generates this motion. By replaying the flights within a computer simulation, we can isolate the significant changes to wing kinematics, and find that it is an asymmetry in the wing pitch which generates the roll. Further investigation demonstrates that this choice is highly dependent upon the state of the dragonfly, and as such our results indicate the dragonfly both tracks its current state, and changes its mid-flight control mechanisms accordingly. [Preview Abstract] |
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