Neural network classification of Barnes maze search strategy utilization

The Barnes maze is a commonly used test of allocentric spatial reference memory, consisting of an elevated circular table with holes around the perimeter. Spatial cues surrounding the maze are intended to allow the animal on the maze to locate a target hole from which they can escape and return to t...

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Main Authors: Scott Ferguson, Coral Hahn-Townsend, Benoit Mouzon, Salina Yathiraj, Giovanni Brunetti, Nicole Saltiel, Cillian E. Lynch, Michael Mullan, Fiona Crawford
Format: Article
Language:English
Published: Elsevier 2025-10-01
Series:Brain Research Bulletin
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Online Access:http://www.sciencedirect.com/science/article/pii/S0361923025002953
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author Scott Ferguson
Coral Hahn-Townsend
Benoit Mouzon
Salina Yathiraj
Giovanni Brunetti
Nicole Saltiel
Cillian E. Lynch
Michael Mullan
Fiona Crawford
author_facet Scott Ferguson
Coral Hahn-Townsend
Benoit Mouzon
Salina Yathiraj
Giovanni Brunetti
Nicole Saltiel
Cillian E. Lynch
Michael Mullan
Fiona Crawford
author_sort Scott Ferguson
collection DOAJ
description The Barnes maze is a commonly used test of allocentric spatial reference memory, consisting of an elevated circular table with holes around the perimeter. Spatial cues surrounding the maze are intended to allow the animal on the maze to locate a target hole from which they can escape and return to their home cage during a period of acquisition trials. Following the acquisition period, the target box under the target hole is removed and a probe trial is performed to test spatial memory. One of the limitations of Barnes maze testing is that non-spatial strategies can be employed to locate the target hole, such as systematic serial searching hole to hole, which may mask the signal of spatial learning or memory deficits on gross outcome measures, such as the latency to find the target hole. Quantifying the search strategies used during Barnes maze testing can provide a more direct measurement of spatial memory impairments, and even allow for the detection of impairments to executive functioning and working memory that may impact the ability to utilize non-spatial systematic search strategies. We have developed a machine learning algorithm to automatically quantify search strategy utilization in an unbiased manner. Traumatic brain injury (TBI) is known to cause impairments in spatial learning and memory, and in our testing with a model of repetitive mild TBI we have found significant deficits in the utilization of both spatial and systematic non-spatial search strategies 3 months after TBI. Understanding the factors driving gross outcome measures on the Barnes maze may provide greater insight into the effectiveness of potential treatment strategies designed to mitigate the chronic effects of TBI and other neurodegenerative diseases.
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spelling doaj-art-57864a66d8c14a769ea6c4d2b3775cf02025-08-20T03:58:35ZengElsevierBrain Research Bulletin1873-27472025-10-0123011148310.1016/j.brainresbull.2025.111483Neural network classification of Barnes maze search strategy utilizationScott Ferguson0Coral Hahn-Townsend1Benoit Mouzon2Salina Yathiraj3Giovanni Brunetti4Nicole Saltiel5Cillian E. Lynch6Michael Mullan7Fiona Crawford8Corresponding author.; Roskamp Institute, Sarasota, FL, United StatesRoskamp Institute, Sarasota, FL, United StatesRoskamp Institute, Sarasota, FL, United StatesRoskamp Institute, Sarasota, FL, United StatesRoskamp Institute, Sarasota, FL, United StatesRoskamp Institute, Sarasota, FL, United StatesRoskamp Institute, Sarasota, FL, United StatesRoskamp Institute, Sarasota, FL, United StatesRoskamp Institute, Sarasota, FL, United StatesThe Barnes maze is a commonly used test of allocentric spatial reference memory, consisting of an elevated circular table with holes around the perimeter. Spatial cues surrounding the maze are intended to allow the animal on the maze to locate a target hole from which they can escape and return to their home cage during a period of acquisition trials. Following the acquisition period, the target box under the target hole is removed and a probe trial is performed to test spatial memory. One of the limitations of Barnes maze testing is that non-spatial strategies can be employed to locate the target hole, such as systematic serial searching hole to hole, which may mask the signal of spatial learning or memory deficits on gross outcome measures, such as the latency to find the target hole. Quantifying the search strategies used during Barnes maze testing can provide a more direct measurement of spatial memory impairments, and even allow for the detection of impairments to executive functioning and working memory that may impact the ability to utilize non-spatial systematic search strategies. We have developed a machine learning algorithm to automatically quantify search strategy utilization in an unbiased manner. Traumatic brain injury (TBI) is known to cause impairments in spatial learning and memory, and in our testing with a model of repetitive mild TBI we have found significant deficits in the utilization of both spatial and systematic non-spatial search strategies 3 months after TBI. Understanding the factors driving gross outcome measures on the Barnes maze may provide greater insight into the effectiveness of potential treatment strategies designed to mitigate the chronic effects of TBI and other neurodegenerative diseases.http://www.sciencedirect.com/science/article/pii/S0361923025002953Barnes mazeSearch strategyTraumatic brain injuryAIMachine learning
spellingShingle Scott Ferguson
Coral Hahn-Townsend
Benoit Mouzon
Salina Yathiraj
Giovanni Brunetti
Nicole Saltiel
Cillian E. Lynch
Michael Mullan
Fiona Crawford
Neural network classification of Barnes maze search strategy utilization
Brain Research Bulletin
Barnes maze
Search strategy
Traumatic brain injury
AI
Machine learning
title Neural network classification of Barnes maze search strategy utilization
title_full Neural network classification of Barnes maze search strategy utilization
title_fullStr Neural network classification of Barnes maze search strategy utilization
title_full_unstemmed Neural network classification of Barnes maze search strategy utilization
title_short Neural network classification of Barnes maze search strategy utilization
title_sort neural network classification of barnes maze search strategy utilization
topic Barnes maze
Search strategy
Traumatic brain injury
AI
Machine learning
url http://www.sciencedirect.com/science/article/pii/S0361923025002953
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AT salinayathiraj neuralnetworkclassificationofbarnesmazesearchstrategyutilization
AT giovannibrunetti neuralnetworkclassificationofbarnesmazesearchstrategyutilization
AT nicolesaltiel neuralnetworkclassificationofbarnesmazesearchstrategyutilization
AT cillianelynch neuralnetworkclassificationofbarnesmazesearchstrategyutilization
AT michaelmullan neuralnetworkclassificationofbarnesmazesearchstrategyutilization
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