Transforming representations of movement from body- to world-centric space

Lu, Jenny; Behbahani, Amir H.; Hamburg, Lydia; Westeinde, Elena A.; Dawson, Paul M.; Lyu, Cheng; Maimon, Gaby; Dickinson, Michael H.; Druckmann, Shaul; Wilson, Rachel I.

doi:10.1038/s41586-021-04191-x

Cited by 79 publications

(94 citation statements)

References 73 publications

(85 reference statements)

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“…It is thus tempting to hypothesize that flies have in mind a model of the interacting conspecific that can be referred to when necessary to guide behavior, possibly using a vector-based mechanism. [95][96][97] Model-based object recognition approaches have been used in machine learning. 98 Article hierarchical networks, both biological and artificial, can be used for the recognition of complex objects by view integration, 1,99 possibly via learning.…”

Section: Discussionmentioning

confidence: 99%

“…110 It has been shown that dragonflies use internal models for prey interception. 111 Recent physiological and anatomical evidence point toward central complex circuits for egocentric and allocentric coordinate transformation in flies when heading and traveling directions differ, [95][96][97] a defining character of circling. Interestingly, we identified male circling via coordinate transformation with a female-centered reference frame (Figures 1, 2, and 3), raising the possibility of alternative, possibly othercentric, coordinates beyond egocentric and allocentric maps.…”

Section: Discussionmentioning

confidence: 99%

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Behavioral signatures of structured feature detection during courtship in Drosophila

Ning¹,

Zhou²,

Zhang³

et al. 2022

Current Biology

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Behavioral signatures of structured feature detection during courtship in Drosophila

Ning¹,

Zhou²,

Zhang³

et al. 2022

Current Biology

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“…Wind direction signals are strongest in PFNs targeting ventral layers of the FB (PFNa, p, and m in the hemibrain connectome 22 ). PFNs targeting more dorsal layers (PFNd and v) encode both optic flow 23 and self-motion during walking 24 in a similar vector format. PFNs of all types show little sensitivity to odor stimuli 21 suggesting that this pathway mostly encodes flow and self-motion information independent of odor.…”

Section: Introductionmentioning

confidence: 99%

A neural circuit for wind-guided olfactory navigation

et al. 2022

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To navigate towards a food source, animals frequently combine odor cues about source identity with wind direction cues about source location. Where and how these two cues are integrated to support navigation is unclear. Here we describe a pathway to the Drosophila fan-shaped body that encodes attractive odor and promotes upwind navigation. We show that neurons throughout this pathway encode odor, but not wind direction. Using connectomics, we identify fan-shaped body local neurons called h∆C that receive input from this odor pathway and a previously described wind pathway. We show that h∆C neurons exhibit odor-gated, wind direction-tuned activity, that sparse activation of h∆C neurons promotes navigation in a reproducible direction, and that h∆C activity is required for persistent upwind orientation during odor. Based on connectome data, we develop a computational model showing how h∆C activity can promote navigation towards a goal such as an upwind odor source. Our results suggest that odor and wind cues are processed by separate pathways and integrated within the fan-shaped body to support goal-directed navigation.

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“…However, an allocentric (or world-centric) heading signal is needed for the path integration process. Recent studies characterized a neuronal circuit that performs a series of vector calculations in the PB − fan-shaped body network based on translational visual cues to compute the allocentric traveling direction ( Lu et al, 2021 ; Lyu et al, 2021 ). Finally, the polarization cue can be used for determining the flight direction ( Weir and Dickinson, 2012 ; Hardcastle et al, 2021 ), and the underlying neural circuit has been dissected thoroughly, from the retina to the CX ( Weir and Dickinson, 2012 ; Hardcastle et al, 2021 ).…”

Section: Vision-based Spatial Navigationmentioning

confidence: 99%

From Photons to Behaviors: Neural Implementations of Visual Behaviors in Drosophila

Ryu

Kim

2022

Front. Neurosci.

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Neural implementations of visual behaviors in Drosophila have been dissected intensively in the past couple of decades. The availability of premiere genetic toolkits, behavioral assays in tethered or freely moving conditions, and advances in connectomics have permitted the understanding of the physiological and anatomical details of the nervous system underlying complex visual behaviors. In this review, we describe recent advances on how various features of a visual scene are detected by the Drosophila visual system and how the neural circuits process these signals and elicit an appropriate behavioral response. Special emphasis was laid on the neural circuits that detect visual features such as brightness, color, local motion, optic flow, and translating or approaching visual objects, which would be important for behaviors such as phototaxis, optomotor response, attraction (or aversion) to moving objects, navigation, and visual learning. This review offers an integrative framework for how the fly brain detects visual features and orchestrates an appropriate behavioral response.

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Transforming representations of movement from body- to world-centric space

Cited by 79 publications

References 73 publications

Behavioral signatures of structured feature detection during courtship in Drosophila

Behavioral signatures of structured feature detection during courtship in Drosophila

A neural circuit for wind-guided olfactory navigation

From Photons to Behaviors: Neural Implementations of Visual Behaviors in Drosophila

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