1
40
1
-
Text
A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text.
URL Address
<a href="http://doi.org/10.1016/j.jneumeth.2015.07.001" target="_blank" rel="noreferrer noopener">http://doi.org/10.1016/j.jneumeth.2015.07.001</a>
Pages
206–217
Volume
253
Dublin Core
The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.
Title
A name given to the resource
An improved approach to separating startle data from noise.
Publisher
An entity responsible for making the resource available
Journal of neuroscience methods
Date
A point or period of time associated with an event in the lifecycle of the resource
2015
2015-09
Subject
The topic of the resource
*Electronic Data Processing; *Noise; Acoustic startle reflex; Acoustic Stimulation/methods; Analysis of Variance; Animal locomotion; Animals; Auditory/*physiology; Automated classification; Evoked Potentials; Inbred CBA; Male; Mice; Reflex; Startle waveform analysis; Startle/*physiology; Time Factors; Video Recording
Creator
An entity primarily responsible for making the resource
Grimsley Calum A; Longenecker Ryan J; Rosen Merri J; Young Jesse W; Grimsley Jasmine M S; Galazyuk Alexander V
Description
An account of the resource
BACKGROUND: The acoustic startle reflex (ASR) is a rapid, involuntary movement to sound, found in many species. The ASR can be modulated by external stimuli and internal state, making it a useful tool in many disciplines. ASR data collection and interpretation varies greatly across laboratories making comparisons a challenge. NEW METHOD: Here we investigate the animal movement associated with a startle in mouse (CBA/CaJ). Movements were simultaneously captured with high-speed video and a piezoelectric startle plate. We also use simple mathematical extrapolations to convert startle data (force) into center of mass displacement ("height"), which incorporates the animal's mass. RESULTS: Startle plate force data revealed a stereotype waveform associated with a startle that contained three distinct peaks. This waveform allowed researchers to separate trials into 'startles' and 'no-startles' (termed 'manual classification). Fleiss' kappa and Krippendorff"s alpha (0.865 for both) indicate very good levels of agreement between researchers. Further work uses this waveform to develop an automated startle classifier. The automated classifier compares favorably with manual classification. A two-way ANOVA reveals no significant difference in the magnitude of the 3 peaks as classified by the manual and automated methods (P1: p=0.526, N1: p=0.488, P2: p=0.529). COMPARISON WITH EXISTING METHOD(S): The ability of the automated classifier was compared with three other commonly used classification methods; the automated classifier far outperformed these methods. CONCLUSIONS: The improvements made allow researchers to automatically separate startle data from noise, and normalize for an individual animal's mass. These steps ease inter-animal and inter-laboratory comparisons of startle data.
Identifier
An unambiguous reference to the resource within a given context
<a href="http://doi.org/10.1016/j.jneumeth.2015.07.001" target="_blank" rel="noreferrer noopener">10.1016/j.jneumeth.2015.07.001</a>
Rights
Information about rights held in and over the resource
Article information provided for research and reference use only. All rights are retained by the journal listed under publisher and/or the creator(s).
*Electronic Data Processing
*Noise
2015
Acoustic startle reflex
Acoustic Stimulation/methods
Analysis of Variance
Animal locomotion
Animals
Auditory/*physiology
Automated classification
Department of Anatomy & Neurobiology
Evoked Potentials
Galazyuk Alexander V
Grimsley Calum A
Grimsley Jasmine M S
Inbred CBA
Journal of neuroscience methods
Longenecker Ryan J
Male
Mice
NEOMED College of Medicine
Reflex
Rosen Merri J
Startle waveform analysis
Startle/*physiology
Time Factors
Video Recording
Young Jesse W