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Record W4310213323 · doi:10.1007/s10071-022-01720-7

Varieties of visual navigation in insects

2022· review· en· W4310213323 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAnimal Cognition · 2022
Typereview
Languageen
FieldNeuroscience
TopicNeurobiology and Insect Physiology Research
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaMacquarie University
KeywordsHeading (navigation)Spatial cognitionSensory cueOrientation (vector space)CognitionPath integrationCognitive psychologyCognitive mapSpatial memoryEcologyComputer scienceCommunicationCognitive scienceBiologyPsychologyNeuroscienceGeography

Abstract

fetched live from OpenAlex

The behaviours and cognitive mechanisms animals use to orient, navigate, and remember spatial locations exemplify how cognitive abilities have evolved to suit a number of different mobile lifestyles and habitats. While spatial cognition observed in vertebrates has been well characterised in recent decades, of no less interest are the great strides that have also been made in characterizing and understanding the behavioural and cognitive basis of orientation and navigation in invertebrate models and in particular insects. Insects are known to exhibit remarkable spatial cognitive abilities and are able to successfully migrate over long distances or pinpoint known locations relying on multiple navigational strategies similar to those found in vertebrate models-all while operating under the constraint of relatively limited neural architectures. Insect orientation and navigation systems are often tailored to each species' ecology, yet common mechanistic principles can be observed repeatedly. Of these, reliance on visual cues is observed across a wide number of insect groups. In this review, we characterise some of the behavioural strategies used by insects to solve navigational problems, including orientation over short-distances, migratory heading maintenance over long distances, and homing behaviours to known locations. We describe behavioural research using examples from a few well-studied insect species to illustrate how visual cues are used in navigation and how they interact with non-visual cues and strategies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.928
Threshold uncertainty score0.667

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.142
GPT teacher head0.403
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it