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3D-Printed Capacitive Sensor Objects for Object Recognition Assays
Object recognition tasks are widely used assays for studying learning and memory in rodents. Object recognition typically involves familiarizing mice with a set of objects and then presenting a novel object or displacing an object to a novel location or context. Learning and memory are inferred by a...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Society for Neuroscience
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7877456/ https://www.ncbi.nlm.nih.gov/pubmed/33446515 http://dx.doi.org/10.1523/ENEURO.0310-20.2020 |
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author | Spry, Kasey P. Fry, Sydney A. DeFillip, Jemma M.S. Drye, S. Griffin Stevanovic, Korey D. Hunnicutt, James Bernstein, Briana J. Thompson, Eric E. Cushman, Jesse D. |
author_facet | Spry, Kasey P. Fry, Sydney A. DeFillip, Jemma M.S. Drye, S. Griffin Stevanovic, Korey D. Hunnicutt, James Bernstein, Briana J. Thompson, Eric E. Cushman, Jesse D. |
author_sort | Spry, Kasey P. |
collection | PubMed |
description | Object recognition tasks are widely used assays for studying learning and memory in rodents. Object recognition typically involves familiarizing mice with a set of objects and then presenting a novel object or displacing an object to a novel location or context. Learning and memory are inferred by a relative increase in time investigating the novel/displaced object. These tasks are in widespread use, but there are many inconsistencies in the way they are conducted across labs. Two major contributors to this are the lack of consistency in the method of measuring object investigation and the lack of standardization of the objects that are used. Current video-based automated algorithms can often be unreliable whereas manual scoring of object investigation is time consuming, tedious, and more subjective. To resolve these issues, we sought to design and implement 3D-printed objects that can be standardized across labs and use capacitive sensing to measure object investigation. Using a 3D printer, conductive filament, and low-cost off-the-shelf components, we demonstrate that employing 3D-printed capacitive touch objects is a reliable and precise way to perform object recognition tasks. Ultimately, this approach will lead to increased standardization and consistency across labs, which will greatly improve basic and translational research into learning and memory mechanisms. |
format | Online Article Text |
id | pubmed-7877456 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Society for Neuroscience |
record_format | MEDLINE/PubMed |
spelling | pubmed-78774562021-02-12 3D-Printed Capacitive Sensor Objects for Object Recognition Assays Spry, Kasey P. Fry, Sydney A. DeFillip, Jemma M.S. Drye, S. Griffin Stevanovic, Korey D. Hunnicutt, James Bernstein, Briana J. Thompson, Eric E. Cushman, Jesse D. eNeuro Open Source Tools and Methods Object recognition tasks are widely used assays for studying learning and memory in rodents. Object recognition typically involves familiarizing mice with a set of objects and then presenting a novel object or displacing an object to a novel location or context. Learning and memory are inferred by a relative increase in time investigating the novel/displaced object. These tasks are in widespread use, but there are many inconsistencies in the way they are conducted across labs. Two major contributors to this are the lack of consistency in the method of measuring object investigation and the lack of standardization of the objects that are used. Current video-based automated algorithms can often be unreliable whereas manual scoring of object investigation is time consuming, tedious, and more subjective. To resolve these issues, we sought to design and implement 3D-printed objects that can be standardized across labs and use capacitive sensing to measure object investigation. Using a 3D printer, conductive filament, and low-cost off-the-shelf components, we demonstrate that employing 3D-printed capacitive touch objects is a reliable and precise way to perform object recognition tasks. Ultimately, this approach will lead to increased standardization and consistency across labs, which will greatly improve basic and translational research into learning and memory mechanisms. Society for Neuroscience 2021-01-25 /pmc/articles/PMC7877456/ /pubmed/33446515 http://dx.doi.org/10.1523/ENEURO.0310-20.2020 Text en Copyright © 2021 Spry et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed. |
spellingShingle | Open Source Tools and Methods Spry, Kasey P. Fry, Sydney A. DeFillip, Jemma M.S. Drye, S. Griffin Stevanovic, Korey D. Hunnicutt, James Bernstein, Briana J. Thompson, Eric E. Cushman, Jesse D. 3D-Printed Capacitive Sensor Objects for Object Recognition Assays |
title | 3D-Printed Capacitive Sensor Objects for Object Recognition Assays |
title_full | 3D-Printed Capacitive Sensor Objects for Object Recognition Assays |
title_fullStr | 3D-Printed Capacitive Sensor Objects for Object Recognition Assays |
title_full_unstemmed | 3D-Printed Capacitive Sensor Objects for Object Recognition Assays |
title_short | 3D-Printed Capacitive Sensor Objects for Object Recognition Assays |
title_sort | 3d-printed capacitive sensor objects for object recognition assays |
topic | Open Source Tools and Methods |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7877456/ https://www.ncbi.nlm.nih.gov/pubmed/33446515 http://dx.doi.org/10.1523/ENEURO.0310-20.2020 |
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