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(A) Overview of the cross-modal registration pipeline. After dcFLF imaging and brain reconstruction, the 3D volumes in the red and green channels are first aligned. The same brain was then imaged using 3D two-photon microscopy, and the acquired two-photon volume was used as a reference to align the dcFLF volumes. By collecting a dataset of two-photon volumes from many brains and aligning all brains to a common space, a two-photon dataset template is obtained. Then, all the abovementioned volumes are aligned to the two-photon dataset template. Finally, the two-photon dataset template is aligned to the publicly available Functional Drosophila Atlas (FDA). And all the abovementioned volumes are again aligned to the FDA. (B) Overview of the pipeline for anatomical and functional segmentation. Firstly, time series dual-channel 3D volumes collected by dcFLF imaging are aligned to the FDA using cross-modal registration, as shown in A. For anatomical segmentation, an atlas containing anatomical region information is applied to the registered volumes. For functional segmentation, <t>the</t> <t>IPCA-ICA</t> approach is utilized for voxel-based segmentation in each channel.
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(A) Overview of the cross-modal registration pipeline. After dcFLF imaging and brain reconstruction, the 3D volumes in the red and green channels are first aligned. The same brain was then imaged using 3D two-photon microscopy, and the acquired two-photon volume was used as a reference to align the dcFLF volumes. By collecting a dataset of two-photon volumes from many brains and aligning all brains to a common space, a two-photon dataset template is obtained. Then, all the abovementioned volumes are aligned to the two-photon dataset template. Finally, the two-photon dataset template is aligned to the publicly available Functional Drosophila Atlas (FDA). And all the abovementioned volumes are again aligned to the FDA. (B) Overview of the pipeline for anatomical and functional segmentation. Firstly, time series dual-channel 3D volumes collected by dcFLF imaging are aligned to the FDA using cross-modal registration, as shown in A. For anatomical segmentation, an atlas containing anatomical region information is applied to the registered volumes. For functional segmentation, <t>the</t> <t>IPCA-ICA</t> approach is utilized for voxel-based segmentation in each channel.
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(A) Overview of the cross-modal registration pipeline. After dcFLF imaging and brain reconstruction, the 3D volumes in the red and green channels are first aligned. The same brain was then imaged using 3D two-photon microscopy, and the acquired two-photon volume was used as a reference to align the dcFLF volumes. By collecting a dataset of two-photon volumes from many brains and aligning all brains to a common space, a two-photon dataset template is obtained. Then, all the abovementioned volumes are aligned to the two-photon dataset template. Finally, the two-photon dataset template is aligned to the publicly available Functional Drosophila Atlas (FDA). And all the abovementioned volumes are again aligned to the FDA. (B) Overview of the pipeline for anatomical and functional segmentation. Firstly, time series dual-channel 3D volumes collected by dcFLF imaging are aligned to the FDA using cross-modal registration, as shown in A. For anatomical segmentation, an atlas containing anatomical region information is applied to the registered volumes. For functional segmentation, <t>the</t> <t>IPCA-ICA</t> approach is utilized for voxel-based segmentation in each channel.
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(A) Overview of the cross-modal registration pipeline. After dcFLF imaging and brain reconstruction, the 3D volumes in the red and green channels are first aligned. The same brain was then imaged using 3D two-photon microscopy, and the acquired two-photon volume was used as a reference to align the dcFLF volumes. By collecting a dataset of two-photon volumes from many brains and aligning all brains to a common space, a two-photon dataset template is obtained. Then, all the abovementioned volumes are aligned to the two-photon dataset template. Finally, the two-photon dataset template is aligned to the publicly available Functional Drosophila Atlas (FDA). And all the abovementioned volumes are again aligned to the FDA. (B) Overview of the pipeline for anatomical and functional segmentation. Firstly, time series dual-channel 3D volumes collected by dcFLF imaging are aligned to the FDA using cross-modal registration, as shown in A. For anatomical segmentation, an atlas containing anatomical region information is applied to the registered volumes. For functional segmentation, <t>the</t> <t>IPCA-ICA</t> approach is utilized for voxel-based segmentation in each channel.
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(A) Overview of the cross-modal registration pipeline. After dcFLF imaging and brain reconstruction, the 3D volumes in the red and green channels are first aligned. The same brain was then imaged using 3D two-photon microscopy, and the acquired two-photon volume was used as a reference to align the dcFLF volumes. By collecting a dataset of two-photon volumes from many brains and aligning all brains to a common space, a two-photon dataset template is obtained. Then, all the abovementioned volumes are aligned to the two-photon dataset template. Finally, the two-photon dataset template is aligned to the publicly available Functional Drosophila Atlas (FDA). And all the abovementioned volumes are again aligned to the FDA. (B) Overview of the pipeline for anatomical and functional segmentation. Firstly, time series dual-channel 3D volumes collected by dcFLF imaging are aligned to the FDA using cross-modal registration, as shown in A. For anatomical segmentation, an atlas containing anatomical region information is applied to the registered volumes. For functional segmentation, <t>the</t> <t>IPCA-ICA</t> approach is utilized for voxel-based segmentation in each channel.
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(A) Overview of the cross-modal registration pipeline. After dcFLF imaging and brain reconstruction, the 3D volumes in the red and green channels are first aligned. The same brain was then imaged using 3D two-photon microscopy, and the acquired two-photon volume was used as a reference to align the dcFLF volumes. By collecting a dataset of two-photon volumes from many brains and aligning all brains to a common space, a two-photon dataset template is obtained. Then, all the abovementioned volumes are aligned to the two-photon dataset template. Finally, the two-photon dataset template is aligned to the publicly available Functional Drosophila Atlas (FDA). And all the abovementioned volumes are again aligned to the FDA. (B) Overview of the pipeline for anatomical and functional segmentation. Firstly, time series dual-channel 3D volumes collected by dcFLF imaging are aligned to the FDA using cross-modal registration, as shown in A. For anatomical segmentation, an atlas containing anatomical region information is applied to the registered volumes. For functional segmentation, <t>the</t> <t>IPCA-ICA</t> approach is utilized for voxel-based segmentation in each channel.
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(A) Overview of the cross-modal registration pipeline. After dcFLF imaging and brain reconstruction, the 3D volumes in the red and green channels are first aligned. The same brain was then imaged using 3D two-photon microscopy, and the acquired two-photon volume was used as a reference to align the dcFLF volumes. By collecting a dataset of two-photon volumes from many brains and aligning all brains to a common space, a two-photon dataset template is obtained. Then, all the abovementioned volumes are aligned to the two-photon dataset template. Finally, the two-photon dataset template is aligned to the publicly available Functional Drosophila Atlas (FDA). And all the abovementioned volumes are again aligned to the FDA. (B) Overview of the pipeline for anatomical and functional segmentation. Firstly, time series dual-channel 3D volumes collected by dcFLF imaging are aligned to the FDA using cross-modal registration, as shown in A. For anatomical segmentation, an atlas containing anatomical region information is applied to the registered volumes. For functional segmentation, <t>the</t> <t>IPCA-ICA</t> approach is utilized for voxel-based segmentation in each channel.
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Image Search Results


(A) Overview of the cross-modal registration pipeline. After dcFLF imaging and brain reconstruction, the 3D volumes in the red and green channels are first aligned. The same brain was then imaged using 3D two-photon microscopy, and the acquired two-photon volume was used as a reference to align the dcFLF volumes. By collecting a dataset of two-photon volumes from many brains and aligning all brains to a common space, a two-photon dataset template is obtained. Then, all the abovementioned volumes are aligned to the two-photon dataset template. Finally, the two-photon dataset template is aligned to the publicly available Functional Drosophila Atlas (FDA). And all the abovementioned volumes are again aligned to the FDA. (B) Overview of the pipeline for anatomical and functional segmentation. Firstly, time series dual-channel 3D volumes collected by dcFLF imaging are aligned to the FDA using cross-modal registration, as shown in A. For anatomical segmentation, an atlas containing anatomical region information is applied to the registered volumes. For functional segmentation, the IPCA-ICA approach is utilized for voxel-based segmentation in each channel.

Journal: bioRxiv

Article Title: Dual-channel whole-brain imaging reveals distinct dopamine and calcium dynamics in walking Drosophila

doi: 10.64898/2026.05.29.728103

Figure Lengend Snippet: (A) Overview of the cross-modal registration pipeline. After dcFLF imaging and brain reconstruction, the 3D volumes in the red and green channels are first aligned. The same brain was then imaged using 3D two-photon microscopy, and the acquired two-photon volume was used as a reference to align the dcFLF volumes. By collecting a dataset of two-photon volumes from many brains and aligning all brains to a common space, a two-photon dataset template is obtained. Then, all the abovementioned volumes are aligned to the two-photon dataset template. Finally, the two-photon dataset template is aligned to the publicly available Functional Drosophila Atlas (FDA). And all the abovementioned volumes are again aligned to the FDA. (B) Overview of the pipeline for anatomical and functional segmentation. Firstly, time series dual-channel 3D volumes collected by dcFLF imaging are aligned to the FDA using cross-modal registration, as shown in A. For anatomical segmentation, an atlas containing anatomical region information is applied to the registered volumes. For functional segmentation, the IPCA-ICA approach is utilized for voxel-based segmentation in each channel.

Article Snippet: Using the IPCA-ICA pipeline, we segmented the brain into 200 functional units for both calcium and dopamine channels independently ( , see Methods).

Techniques: Imaging, Microscopy, Functional Assay