Statistical structure of locomotion and its modulation by odors Article Swipe
L. Y. Tao
,
Siddhi Ozarkar
,
Jeffrey Beck
,
Vikas Bhandawat
·
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.1101/404772
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.1101/404772
Most behaviors such as making tea are not stereotypical but have an obvious structure. However, analytical methods to objectively extract structure from non-stereotyped behaviors are immature. In this study, we analyze the locomotion of fruit flies and show that this non-stereotyped behavior is well-described by a Hierarchical Hidden Markov Model (HHMM). HHMM shows that a fly’s locomotion can be decomposed into a small number of locomotor features, and odors modulate locomotion by altering the time a fly spends performing different locomotor features. Importantly, although all flies in our dataset use the same set of locomotor features, individual flies vary considerably in how often they employ a given locomotor feature, and how this usage is modulated by odor. This variation is so large that the behavior of individual flies is best understood as being grouped into at least 3-5 distinct clusters, rather than variations around an average fly.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/404772
- https://www.biorxiv.org/content/biorxiv/early/2018/10/05/404772.full.pdf
- OA Status
- green
- Cited By
- 8
- References
- 52
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2890350330
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2890350330Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1101/404772Digital Object Identifier
- Title
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Statistical structure of locomotion and its modulation by odorsWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2018Year of publication
- Publication date
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2018-09-10Full publication date if available
- Authors
-
L. Y. Tao, Siddhi Ozarkar, Jeffrey Beck, Vikas BhandawatList of authors in order
- Landing page
-
https://doi.org/10.1101/404772Publisher landing page
- PDF URL
-
https://www.biorxiv.org/content/biorxiv/early/2018/10/05/404772.full.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://www.biorxiv.org/content/biorxiv/early/2018/10/05/404772.full.pdfDirect OA link when available
- Concepts
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Set (abstract data type), Locomotor activity, Odor, Contrast (vision), Feature (linguistics), Computer science, Communication, Biology, Artificial intelligence, Pattern recognition (psychology), Neuroscience, Psychology, Programming language, Linguistics, Philosophy, EndocrinologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
8Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1, 2024: 1, 2023: 1, 2022: 2, 2021: 1Per-year citation counts (last 5 years)
- References (count)
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52Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| referenced_works | https://openalex.org/W2036691323, https://openalex.org/W2004609551, https://openalex.org/W2150099374, https://openalex.org/W2118691301, https://openalex.org/W1638739080, https://openalex.org/W2135563396, https://openalex.org/W1977591411, https://openalex.org/W2362300820, https://openalex.org/W2154723612, https://openalex.org/W2219858099, https://openalex.org/W1993695976, https://openalex.org/W2074759798, https://openalex.org/W2736783045, https://openalex.org/W2143604818, https://openalex.org/W2142273372, https://openalex.org/W2131629809, https://openalex.org/W1971892419, https://openalex.org/W1996720572, https://openalex.org/W2185428930, https://openalex.org/W1991828159, https://openalex.org/W2088029930, https://openalex.org/W1636244751, https://openalex.org/W1984295865, https://openalex.org/W2604812607, https://openalex.org/W1980070248, https://openalex.org/W2616071181, https://openalex.org/W2161874168, https://openalex.org/W2130393353, https://openalex.org/W1554272899, https://openalex.org/W1680265720, https://openalex.org/W2614915054, https://openalex.org/W2754385040, https://openalex.org/W2417735520, https://openalex.org/W2115203443, https://openalex.org/W2020498731, https://openalex.org/W2115581315, https://openalex.org/W2122746506, https://openalex.org/W2126376762, https://openalex.org/W2093753070, https://openalex.org/W2462649686, https://openalex.org/W1539597651, https://openalex.org/W2032024800, https://openalex.org/W2083332831, https://openalex.org/W1990432147, https://openalex.org/W2059668389, https://openalex.org/W2132047598, https://openalex.org/W2048701474, https://openalex.org/W1899462954, https://openalex.org/W2007321142, https://openalex.org/W2089763487, https://openalex.org/W2903950532, https://openalex.org/W4300858224 |
| referenced_works_count | 52 |
| abstract_inverted_index.a | 46, 55, 62, 76, 106 |
| abstract_inverted_index.In | 27 |
| abstract_inverted_index.an | 12, 145 |
| abstract_inverted_index.as | 4, 132 |
| abstract_inverted_index.at | 136 |
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| abstract_inverted_index.by | 45, 72, 116 |
| abstract_inverted_index.in | 87, 101 |
| abstract_inverted_index.is | 43, 114, 120, 129 |
| abstract_inverted_index.of | 34, 65, 94, 126 |
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| abstract_inverted_index.we | 30 |
| abstract_inverted_index.3-5 | 138 |
| abstract_inverted_index.all | 85 |
| abstract_inverted_index.and | 37, 68, 110 |
| abstract_inverted_index.are | 7, 25 |
| abstract_inverted_index.but | 10 |
| abstract_inverted_index.can | 58 |
| abstract_inverted_index.fly | 77 |
| abstract_inverted_index.how | 102, 111 |
| abstract_inverted_index.not | 8 |
| abstract_inverted_index.our | 88 |
| abstract_inverted_index.set | 93 |
| abstract_inverted_index.tea | 6 |
| abstract_inverted_index.the | 32, 74, 91, 124 |
| abstract_inverted_index.use | 90 |
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| abstract_inverted_index.best | 130 |
| abstract_inverted_index.fly. | 147 |
| abstract_inverted_index.from | 22 |
| abstract_inverted_index.have | 11 |
| abstract_inverted_index.into | 61, 135 |
| abstract_inverted_index.same | 92 |
| abstract_inverted_index.show | 38 |
| abstract_inverted_index.such | 3 |
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| abstract_inverted_index.that | 39, 54, 123 |
| abstract_inverted_index.they | 104 |
| abstract_inverted_index.this | 28, 40, 112 |
| abstract_inverted_index.time | 75 |
| abstract_inverted_index.vary | 99 |
| abstract_inverted_index.Model | 50 |
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| abstract_inverted_index.flies | 36, 86, 98, 128 |
| abstract_inverted_index.fruit | 35 |
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| abstract_inverted_index.Hidden | 48 |
| abstract_inverted_index.Markov | 49 |
| abstract_inverted_index.around | 144 |
| abstract_inverted_index.employ | 105 |
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| abstract_inverted_index.spends | 78 |
| abstract_inverted_index.study, | 29 |
| abstract_inverted_index.(HHMM). | 51 |
| abstract_inverted_index.analyze | 31 |
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| abstract_inverted_index.dataset | 89 |
| abstract_inverted_index.extract | 20 |
| abstract_inverted_index.fly’s | 56 |
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| abstract_inverted_index.methods | 17 |
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| abstract_inverted_index.behaviors | 2, 24 |
| abstract_inverted_index.clusters, | 140 |
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| abstract_inverted_index.features. | 82 |
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| abstract_inverted_index.stereotypical | 9 |
| abstract_inverted_index.well-described | 44 |
| abstract_inverted_index.non-stereotyped | 23, 41 |
| cited_by_percentile_year.max | 96 |
| cited_by_percentile_year.min | 89 |
| corresponding_author_ids | https://openalex.org/A5014939653 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 4 |
| corresponding_institution_ids | https://openalex.org/I170897317 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/2 |
| sustainable_development_goals[0].score | 0.4399999976158142 |
| sustainable_development_goals[0].display_name | Zero hunger |
| citation_normalized_percentile.value | 0.83645892 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |