4.6 Article

The Morphology of the Rat Vibrissal Array: A Model for Quantifying Spatiotemporal Patterns of Whisker-Object Contact

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PLOS COMPUTATIONAL BIOLOGY
卷 7, 期 4, 页码 -

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PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pcbi.1001120

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资金

  1. NSF [IOB-0446391, IIS-0613568, IOS-0818414, IOS-08090000]
  2. NRSA [F31 NS065630, 5 F31 NS061488]
  3. Northwestern Presidential Fellowship
  4. Direct For Biological Sciences
  5. Division Of Integrative Organismal Systems [0846088, 0818414] Funding Source: National Science Foundation

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In all sensory modalities, the data acquired by the nervous system is shaped by the biomechanics, material properties, and the morphology of the peripheral sensory organs. The rat vibrissal (whisker) system is one of the premier models in neuroscience to study the relationship between physical embodiment of the sensor array and the neural circuits underlying perception. To date, however, the three-dimensional morphology of the vibrissal array has not been characterized. Quantifying array morphology is important because it directly constrains the mechanosensory inputs that will be generated during behavior. These inputs in turn shape all subsequent neural processing in the vibrissal-trigeminal system, from the trigeminal ganglion to primary somatosensory (barrel) cortex. Here we develop a set of equations for the morphology of the vibrissal array that accurately describes the location of every point on every whisker to within +/- 5% of the whisker length. Given only a whisker's identity (row and column location within the array), the equations establish the whisker's two-dimensional (2D) shape as well as three-dimensional (3D) position and orientation. The equations were developed via parameterization of 2D and 3D scans of six rat vibrissal arrays, and the parameters were specifically chosen to be consistent with those commonly measured in behavioral studies. The final morphological model was used to simulate the contact patterns that would be generated as a rat uses its whiskers to tactually explore objects with varying curvatures. The simulations demonstrate that altering the morphology of the array changes the relationship between the sensory signals acquired and the curvature of the object. The morphology of the vibrissal array thus directly constrains the nature of the neural computations that can be associated with extraction of a particular object feature. These results illustrate the key role that the physical embodiment of the sensor array plays in the sensing process.

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