{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T16:26:24Z","timestamp":1772727984210,"version":"3.50.1"},"update-to":[{"DOI":"10.12688\/f1000research.20352.1","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2020,6,15]],"date-time":"2020-06-15T00:00:00Z","timestamp":1592179200000}}],"reference-count":62,"publisher":"F1000 Research Ltd","license":[{"start":{"date-parts":[[2020,6,15]],"date-time":"2020-06-15T00:00:00Z","timestamp":1592179200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000038","name":"Natural Sciences and Engineering Research Council of Canada","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000038","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000024","name":"Canadian Institutes of Health Research","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000024","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000245","name":"Michael Smith Foundation for Health Research","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000245","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["f1000research.com"],"crossmark-restriction":false},"short-container-title":["F1000Res"],"abstract":"<ns4:p>Spatial navigation is a universal behavior that varies depending on goals, experience and available sensory stimuli. Spatial navigational tasks are routinely used to study learning, memory and goal-directed behavior, in both animals and humans. One popular paradigm for testing spatial memory is the Morris water maze, where subjects learn the location of a hidden platform that offers escape from a pool of water. Researchers typically express learning as a function of the latency to escape, though this reveals little about the underlying navigational strategies. Recently, a number of studies have begun to classify water maze search strategies in order to clarify the precise spatial and mnemonic functions of different brain regions, and to identify which aspects of spatial memory are disrupted in disease models. However, despite their usefulness, strategy analyses have not been widely adopted due to the lack of software to automate analyses. To address this need we developed Pathfinder, an open source application for analyzing spatial navigation behaviors. In a representative dataset, we show that Pathfinder effectively characterizes the development of highly-specific spatial search strategies as male and female mice learn a standard spatial water maze. Pathfinder can read data files from commercially- and freely-available software packages, is optimized for classifying search strategies in water maze paradigms, and can also be used to analyze 2D navigation by other species, and in other tasks, as long as timestamped xy coordinates are available. Pathfinder is simple to use, can automatically determine pool and platform geometry, generates heat maps, analyzes navigation with respect to multiple goal locations, and can be updated to accommodate future developments in spatial behavioral analyses. Given these features, Pathfinder may be a useful tool for studying how navigational strategies are regulated by the environment, depend on specific neural circuits, and are altered by pathology.<\/ns4:p>","DOI":"10.12688\/f1000research.20352.2","type":"journal-article","created":{"date-parts":[[2020,6,15]],"date-time":"2020-06-15T07:40:08Z","timestamp":1592206808000},"page":"1521","update-policy":"https:\/\/doi.org\/10.12688\/f1000research.crossmark-policy","source":"Crossref","is-referenced-by-count":7,"title":["Pathfinder: open source software for analyzing spatial navigation search strategies"],"prefix":"10.12688","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7632-0324","authenticated-orcid":false,"given":"Matthew B.","family":"Cooke","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Timothy 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Cooke","year":"2019","journal-title":"Zenodo."}],"container-title":["F1000Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/f1000research.com\/articles\/8-1521\/v2\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/f1000research.com\/articles\/8-1521\/v2\/pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/f1000research.com\/articles\/8-1521\/v2\/iparadigms","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,6,15]],"date-time":"2020-06-15T07:40:11Z","timestamp":1592206811000},"score":1,"resource":{"primary":{"URL":"https:\/\/f1000research.com\/articles\/8-1521\/v2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,6,15]]},"references-count":62,"URL":"https:\/\/doi.org\/10.12688\/f1000research.20352.2","relation":{"has-review":[{"id-type":"doi","id":"10.5256\/f1000research.27222.r64767","asserted-by":"object"}]},"ISSN":["2046-1402"],"issn-type":[{"value":"2046-1402","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,6,15]]},"assertion":[{"value":"Indexed","URL":"https:\/\/f1000research.com\/articles\/8-1521\/v2#article-reports","order":0,"name":"referee-status","label":"Referee status","group":{"name":"current-referee-status","label":"Current Referee Status"}},{"value":"10.5256\/f1000research.22365.r56738, Matthew Holahan, Department of Neuroscience, Carleton University, Ottawa, ON, Canada, 02 Dec 2019, version 1, indexed","URL":"https:\/\/f1000research.com\/articles\/8-1521\/v1#referee-response-56738","order":0,"name":"referee-response-56738","label":"Referee Report","group":{"name":"article-reports","label":"Article Reports"}},{"value":"<b>Jason Snyder<\/b>; \n<i>Posted: 06 Jun 2020<\/i>; Matthew \u2013 thank you for the feedback. Our response is a little delayed, because we have timed it to coincide with a software\/manuscript update, which took longer than anticipated.&nbsp;With respect to your points, we were unaware that any commercial software packages offer strategy-based analyses. There are some other free programs created by researchers, and it would definitely be interesting to do a comparison. It certainly would have been nice to validate it using an established model of hippocampal deficits, like a lesion. I do think it would pick up deficits that have been described, since hippocampal-lesioned rodents are typically thigmotactic and less spatially accurate, which Pathfinder clearly captures in the early stages of training in our experiment. We have validated it with neurogenesis-deficient rats (Yu, Behav Brain Res, 2019), where these rats displayed a strategy phenotype that was probably relatively subtle compared to hippocampal-lesioned animals. Finally, I do think it could be used to detect behavioral changes that other programs cannot. For this to work, it will be important for the user to understand their subject\u2019s behavior and adjust the parameters accordingly such that the strategies are captured. This will increase strategy detection accuracy and sensitivity but users always need to be cautious when interpreting the output, and assess whether finely-tuned parameters are detecting meaningful differences or not. In any case, there should be lots of existing navigational datasets out there that could be run with Pathfinder to address these exact questions. We look forward to seeing what people find.","URL":"https:\/\/f1000research.com\/articles\/8-1521\/v2#referee-comment-5587","order":1,"name":"referee-comment-5587","label":"Referee Comment","group":{"name":"article-reports","label":"Article Reports"}},{"value":"10.5256\/f1000research.22365.r56564, Robert McDonald, Nancy S. Hong, Department of Neuroscience, Canadian Center for Behavioural Neuroscience, Lethbridge University, Lethbridge, AB, Canada, 21 Jan 2020, version 1, indexed","URL":"https:\/\/f1000research.com\/articles\/8-1521\/v1#referee-response-56564","order":2,"name":"referee-response-56564","label":"Referee Report","group":{"name":"article-reports","label":"Article Reports"}},{"value":"<b>Jason Snyder<\/b>; \n<i>Posted: 06 Jun 2020<\/i>; Robert and Nancy \u2013 thank you for your detailed and thoughtful review. The additional background information and interpretations will be useful for those wishing to use Pathfinder when designing and analyzing their water maze experiments. We generally agree with the points you raise and would like to comment on a few of them specifically.&nbsp;We understand that it may have sounded like we imply that early water maze work was primitive. We would like to clarify that we in fact tried to emphasize the opposite! Our take is similar to yours, which is that the early work by Morris, Sutherland, Whishaw etc performed quite extensive analyses which were essential to validate the water maze. Ultimately, as behavioral testing has become much more common, and since latency and path length are decent measures of basic performance, they soon dominated and detailed analyses became less common. Of course, even the early work did not conduct strategy analyses that are comparable to those offered by Pathfinder, but certainly the quality of those original papers cannot be understated. We have made some minor adjustments to the text to clarify our view.&nbsp;You also raise some questions about how Pathfinder could be employed to detect strategies related to competing goals. We attempted to describe a few situations where rodents are tasked with deciding between spatial vs cued goals and multiple possible spatial goals. We cite these papers for the readers\u2019 reference and feel that these provide a good illustration of how the water maze can be used to study decision-making , conflict between multiple strategies\/brain regions and the like. But the possibilities are endless and so ultimately it will depend on the creativity of the users.&nbsp;We appreciate your comments about the importance of validating automated software with manual analyses. We agree that this is critical at the outset. Only when the user trusts their parameter settings should they proceed with the full analysis.&nbsp;Finally, the issue of hybrid strategies is one that Pathfinder currently cannot address, unless one is willing to bin their trials prior to importing into Pathfinder. For a hybrid approach one may want to try the software described in Vourous, 2018, Scientific Reports since it can detect multiple strategies in a single trial.","URL":"https:\/\/f1000research.com\/articles\/8-1521\/v2#referee-comment-5588","order":3,"name":"referee-comment-5588","label":"Referee Comment","group":{"name":"article-reports","label":"Article Reports"}},{"value":"This work was funded by the Canadian Institutes of Health Research (JSS), the Natural Sciences and Engineering Research Council (JSS, REB), and the Michael Smith Foundation for Health Research (JSS, TPO). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.","order":4,"name":"grant-information","label":"Grant Information"},{"value":"This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.","order":0,"name":"copyright-info","label":"Copyright"}]}}