Henrique Ludwigh

ORCID: 0000-0003-2470-4574
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About
Contact & Profiles
Research Areas
  • Neurobiology and Insect Physiology Research
  • Insect and Arachnid Ecology and Behavior
  • Circadian rhythm and melatonin
  • Plant and animal studies
  • Animal Behavior and Reproduction
  • Retinal Development and Disorders
  • Visual perception and processing mechanisms
  • Non-Destructive Testing Techniques
  • Advanced Fluorescence Microscopy Techniques

University of Vermont
2024

Howard Hughes Medical Institute
2021-2024

Janelia Research Campus
2021-2024

Champalimaud Foundation
2024

Color and polarization provide complementary information about the world are detected by specialized photoreceptors. However, downstream neural circuits that process these distinct modalities incompletely understood in any animal. Using electron microscopy, we have systematically reconstructed synaptic targets of photoreceptors to detect color skylight Drosophila, used light microscopy confirm many our findings. We identified known novel selective for different wavelengths or polarized...

10.7554/elife.71858 article EN cc-by eLife 2021-12-16

Summary Many animals rely on vision to navigate through their environment. The pattern of changes in the visual scene induced by self-motion is optic flow 1 , which first estimated local patches directionally selective (DS) neurons 2–4 . But how should arrays DS neurons, each responsive motion a preferred direction at specific retinal position, be organized support robust decoding downstream circuits? Understanding this global organization challenging because it requires mapping fine,...

10.1101/2022.12.14.520178 preprint EN cc-by bioRxiv (Cold Spring Harbor Laboratory) 2022-12-15

Abstract Flying insects exhibit remarkable navigational abilities controlled by their compact nervous systems. Optic flow , the pattern of changes in visual scene induced locomotion, is a crucial sensory cue for robust self-motion estimation, especially during rapid flight. Neurons that respond to specific, large-field optic patterns have been studied decades, primarily large flies, such as houseflies, blowflies, and hover flies. The best-known optic-flow sensitive neurons are tangential...

10.1101/2023.10.16.562634 preprint EN cc-by bioRxiv (Cold Spring Harbor Laboratory) 2023-10-17

Flying insects exhibit remarkable navigational abilities controlled by their compact nervous systems. Optic flow , the pattern of changes in visual scene induced locomotion, is a crucial sensory cue for robust self-motion estimation, especially during rapid flight. Neurons that respond to specific, large-field optic patterns have been studied decades, primarily large flies, such as houseflies, blowflies, and hover flies. The best-known optic-flow sensitive neurons are tangential cells...

10.7554/elife.93659.1 preprint EN 2024-01-09

Flying insects exhibit remarkable navigational abilities controlled by their compact nervous systems. Optic flow , the pattern of changes in visual scene induced locomotion, is a crucial sensory cue for robust self-motion estimation, especially during rapid flight. Neurons that respond to specific, large-field optic patterns have been studied decades, primarily large flies, such as houseflies, blowflies, and hover flies. The best-known optic-flow sensitive neurons are tangential cells...

10.7554/elife.93659 preprint EN 2024-01-09

Abstract Color and polarization provide complementary information about the world are detected by specialized photoreceptors. However, downstream neural circuits that process these distinct modalities incompletely understood in any animal. Using electron microscopy, we have systematically reconstructed synaptic targets of photoreceptors to detect color skylight Drosophila , used light microscopy confirm many our findings. We identified known novel selective for different wavelengths or...

10.1101/2021.05.17.444480 preprint EN cc-by bioRxiv (Cold Spring Harbor Laboratory) 2021-05-17

In this protocol we describe the voxel-based classification of organelles and cellular substructures in volume electron microscopy data used to train deep learning networks for automated segmentation. This is centered around using Amira software ‘painting’ details how CellMap Project Team has defined [up to] 37 semantic segmentation tasks. was described Heinrich et al, Nature (2021).

10.17504/protocols.io.bp2l61rb5vqe/v3 preprint EN 2023-10-23
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