Bulletin of the American Physical Society
APS March Meeting 2019
Volume 64, Number 2
Monday–Friday, March 4–8, 2019; Boston, Massachusetts
Session K51: Information Processing in Sensory SystemsInvited
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Sponsoring Units: DBIO Chair: Thierry Emonet, Yale Univ Room: BCEC 253A |
Wednesday, March 6, 2019 8:00AM - 8:36AM |
K51.00001: Making an effort to listen: mechanical amplification by ion channels and myosin molecules in hair cells of the inner ear Invited Speaker: Jim Hudspeth As the gateway to human communication, the sense of hearing is of enormous importance. Hearing commences with the capture of sound energy by hair cells, the ear's sensory receptors, which convert that energy into electrical signals that the brain can then interpret. Each hair cell is a cylindrical epithelial cell surmounted by a hair bundle, an erect cluster of 20-300 rigid, actin-filled rods termed stereocilia. Mechanical force deflects the hair bundle and thereby excites the hair cell and its associated nerve fibers. |
Wednesday, March 6, 2019 8:36AM - 9:12AM |
K51.00002: Differential Resilience to Perturbation of Circuits with Similar Performance Invited Speaker: Eve Marder
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Wednesday, March 6, 2019 9:12AM - 9:48AM |
K51.00003: Algorithms and neural circuits in olfaction Invited Speaker: Venkatesh Murthy Animals sense the chemical world to guide their behaviors. Fluctuating mixtures of odorants, often transported in fluid environments, are detected by an array of chemical sensors and parsed by neural circuits to recognize odor objects that can inform behavioral decisions. Unlike other sensory systems, the olfactory system lacks an obvious topographic organization, and neural connectivity across brain regions is seemingly unstructured. These anomalies offer an opportunity to uncover common principles across different sensory systems. We exploit a variety of biophysical, neurophysiological and behavioral methods to understand how odorant features are encoded in the activity of neurons and transformed in different stages of processing. We then use conceptual and computational models to seek algorithmic explanations for how animals solve specific olfactory tasks. In an illustrative set of studies, we have found that mice can be trained to recognize individual odorants embedded in unpredictable and variable background mixtures with high degree of success [doi: 10.1038/nn.3775]. Despite nonlinear interactions and variability in the representations of odor mixtures by odorant receptors, a simple linear feedforward decoding is sufficient to explain the performance of mice in this task [doi: 10.1016/j.neuron.2016.08.007]. Current experiments are aimed at understanding how the mouse brain represents information about odor mixtures to aid odor object identification and categorization. |
Wednesday, March 6, 2019 9:48AM - 10:24AM |
K51.00004: Information Processing in the Somatosensory System Invited Speaker: Daniel O'Connor Touch perception arises from a closed-loop process in which animals move their sensors in order to actively seek out informative mechanical input, which is then processed to direct further movements. My laboratory uses the mouse whisker system to explore the neural basis of active touch perception, at essentially all levels of the nervous system. Information processing during active touch is constrained by the coding properties of neurons in the skin that transduce mechanical stimuli into action potentials. I will discuss recent work from my laboratory that addresses how specific types of mechanosensory neurons encode (a) mechanical features of the environment during active touch, and (b) self-motion kinematics. These two streams of information allow tactile input to be interpreted with respect to sensor position. After mechanical features of the environment are encoded into action potentials and sent to the central nervous system, multiple factors determine how these neural signals are routed within circuits of the brain to impact perception. I will discuss a second line of work in my lab that addresses how identically encoded sensory inputs can produce quite different perceptual outcomes. By monitoring and manipulating neural activity at multiple levels of the nervous system during behavior, we have gained insight into the mapping between mechanosensation and perception. |
Wednesday, March 6, 2019 10:24AM - 11:00AM |
K51.00005: Neural processing and computation in the visual system Invited Speaker: Damon Clark Visual systems detect many features of natural scenes, but one of the best studied is how they detect motion, which is a widespread computation across animals. To estimate visual motion speed and direction, the visual system must integrate information nonlinearly over space and over time. Models to estimate visual motion have two essential features: a delay step that delays certain signals with respect to others; and a nonlinear step that integrates signals over space and time to create the motion estimate. The computation itself can be framed as an inference problem, in which spatiotemporal light intensity measurements are combined to estimate a latent variable of image velocity. I will present recent work on understanding how motion is computed in the small brain of the fruit fly Drosophila, where genetic tools allow us to dissect the roles of individual neurons in circuit computations. I will focus on the mathematical operations that describe the transformation from light intensity to motion signals, and how that algorithm performs with different visual inputs. I will also focus on processing steps that appear similar across visual systems. These parallels suggest that there may be a narrow range of motion estimation algorithms that perform well given the constraints of biological systems and the regularities of natural scenes. |
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