DOI: 10.5061/dryad.7hm1m
title: Data from: Neural evidence supports a dual sensory-motor role for insect wings

description: Flying insects use feedback from various sensory modalities including
 vision and mechanosensation to navigate through their environment. The
 rapid speed of mechanosensory information acquisition and processing
 compensates for the slower processing times associated with vision,
 particularly under low light conditions. While halteres in dipteran
 species are well known to provide such information for flight control,
 less is understood about the mechanosensory roles of their evolutionary
 antecedent, wings. The features that wing mechanosensory neurons
 (campaniform sensilla) encode remains relatively unexplored. We
 hypothesized that the wing campaniform sensilla of the hawkmoth, Manduca
 sexta, rapidly and selectively extract mechanical stimulus features in a
 manner similar to halteres. We used electrophysiological and computational
 techniques to characterize the encoding properties of wing campaniform
 sensilla. To accomplish this, we developed a novel technique for
 localizing receptive fields using a focused IR laser that elicits changes
 in the neural activity of mechanoreceptors. We found that (i) most wing
 mechanosensors encoded mechanical stimulus features rapidly and precisely,
 (ii) they are selective for specific stimulus features, and (iii) there is
 diversity in the encoding properties of wing campaniform sensilla. We
 found that the encoding properties of wing campaniform sensilla are
 similar to those for haltere neurons. Therefore, it appears that the
 neural architecture that underlies the haltere sensory function is present
 in wings, which lends credence to the notion that wings themselves may
 serve a similar sensory function. Thus, wings may not only function as the
 primary actuator of the organism but also as sensors of the inertial
 dynamics of the animal.
description: Calibration Object
 FileThe “20150615
 Calibration file_20pt.csv” file contains the physical measurements in
 millimeters of our 20-point calibration object (coordinate system based on
 an origin point) and is used to calibrate a volume of space in which the
 object of interest moves in.Calibration Object Digitized
 Volume.zipSpike Sorted Neural Data
 (time stamps of spiking)Each file contains the
 spike timestamps of the units isolated from the extracellular data of a
 particular moth (M# refers to a particular moth). Each column represents a
 unit and each row corresponds to a timestamp of when a unit spiked. The
 last column of each file contains the unsorted spike timestamps, and
 therefore, was not used for further analyses. Spike sorting was performed
 using Offline Sorter V4 and timestamp data was exported from NeuroExplorer
 V5.Spike
 Sorted Neural Data (Time stamps of
 spiking).zipSpike Train Data
 Structures Resulting From White Noise StimulusThe spike train data
 structure consists of a matrix in which each of the 30 columns represents
 the white noise stimulus segments and the 400,000 rows represent each of
 the sample indices (sample rate of 40kHz over 10 seconds results in
 400,000 sample points). Furthermore, this matrix is binary in which the
 value “one” indicates the sample index that this unit spiked and zeros
 represent non-spiking indices. The two folders, “Base Spike Trains” and
 “NonBase Spike Trains”, contain the spike train data for the corresponding
 wing base and non-localized units. These data structures were created
 using Matlab code.Spike Train Data Structures
 During White noise.zipWand Calibration
 DataWe verified the wing
 motion reconstruction data through cross validating that the measured
 length of a physical wand object can be reconstructed through 3D
 high-speed videography. The “20150615 Calibration file_20pt.csv” file
 contains the physical measurements of our calibration object and is used
 to calibrate the volume of space that the wand moved through. The
 “cal01_WandDLTcoefs.csv” file contains the calibrated volume coefficients.
 “M1_Wand.cine” and “M2_Wand.cine” are the recorded video files (using
 phantom software) that capture the wand movement through the calibrated
 space. “Digitized_Wandxyzpts.csv” contains the 3D coordinates of the wand
 position at each frame. The cameras were set at 1000 fps.The remaining
 files are output files not used in further analyses. Calibration and
 Digitization was performed with custom matlab codes by the Hedrick
 laboratory at UNC.Wing Video and
 Reconstruction DataThe
 “UpSampled_Generalized Base Displacement.mat” and “Generalized Base
 Displacement.mat” files contain the generalized wing base displacement
 transformed from the wing tip displacement. The first file is upsampled so
 that the sampling rate of the data is 40 kHz, while the later file is
 sampled at 1 kHz. The “Tip Motor Stim.mat” and “Motor Tip
 Displacement.mat” files contain the wing tip displacements of one
 10-second white noise segement (first file) and for 10 10-second white
 noise repeats (later file). Each tip displacement file is sample at 40
 kHz. Each “Moth Wing Video” folder contains the 3D high-speed videography
 data of that moth wing. A total of four moth wings (2 males (files labeled
 with M16 or M27) and 2 females (files labeled with M26 or M28)) were used
 to transform their wing base and tip displacements into a generalizable
 wing base displacement. Each “Moth Wing Video” folder contains a
 “DLTcoefs.csv” file (calibration file), two “.cine” files (Video data of
 each camera sampled at 1000 fps), and a “xyzpts.csv” file that contains
 the reconstructed 3D coordinates of the digitized points at each frame.
 The remaining files are output files not used in further analyses.
 Calibration and Digitization was performed with custom matlab codes by the
 Hedrick laboratory at UNC. High-speed videography was conducted using
 phantom software.Raw Extracellular Neural
 Data and Stimulus DataColumn one and two for
 the files labeled M1 through M25 are the raw neural voltage data and the
 corresponding motor voltage stimulus sampled at 40 kHz. M# indicates the
 particular moth used for experimentation. The raw neural data and stimulus
 data for M26 through M33 (both sampled at 40 kHz) were split into two
 files respectively called “M#_Raw Neural Data.txt” and “M#_ Stimulus
 Data.txt”. Files labeled M13, M15, M18, M19, and M20 had an additional
 step stimulus preceding the delivery of the white noise stimulus. A 0.2 Hz
 square wave stimulus of 4 V amplitude was interjected between the
 sinusoidal and white noise stimulus segments. The duration of the step
 stimulus was 16 seconds (640000 samples). There was a rest period of 1
 second between the sinusoidal and the step function as well as between the
 step and white noise stimulus. Moreover, the Raw Neural Data files for
 M26, M28, M31, M32, and M33 contained multiple columns. Each column
 represented the neural data recorded from a particular recording site on
 the multi-site extracellular electrode. Having neural data from multiple
 recoding sites on the electrode improved spike sorting. These Data were
 acquired and saved in Matlab. Moreover, these data consisted of multiple
 chunks (6 chunks), which were concatenated together.