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- U19 – brief description overall project goals, competing circuit theories being developed/studied/integrated:
- We are collecting multimodal (physiology, imaging, genomics, behavior) and multiregional (epithelium, olfactory bulb, cortex) to data about the mouse and human olfactory systems to understand how the olfactory world is encoded and transformed in the brain. We are especially interested in testing the "primacy theory" of olfaction, a sparse-coding theory with preliminary theoretical and experimental evidence suggesting that only the earliest, strongest signals inform olfactory perception and behavior, and that the olfactory system has evolved accordingly.
- Description of how Data Science Core is complying to the criteria of the FAIR principles:
- We are creating reproducible pipelines for all data collection and analysis, using free open-source software and adopting community standards wherever possible. We are committed to sharing data and code collected and developed in public repositories.
- List of Data Types in U19:
- Extracellular electrophyiology, Calcium imaging, Behavior (human and mouse), RNA-Seq.
- Common Data Elements in U19:
- Data Sharing goals in U19:
- Data science tools being used in project:
- Python, Git, GitHub, Jupyter, JupyterHub, NWB, DataJoint, SciUnit, Papermill
- Data science tools being developed for project:
- Pyrfume, DataJointTools, SciUnit-dependent libraries
- Data science approaches to be shared with other U19’s:
- SciUnit, DataJointTools
- Data science challenges that could benefit from discussion with other U19’s:
- Common DataJoint schemas for common tasks; NWB use cases
Available abstracts for Data Reuse Project:
High-speed volumetric imaging of piriform cortex during odor stimulation (Datta Lab)
High-speed volumetric multiphoton imaging data of piriform cortex layers 2 and 3 were collected using a 16kHz resonant galvo in paralyzed but awake mice being exposed to different odor sets, in which each set parametrically varied odor distance at a particular scale (as measured in an odor space defined by more than 5,000 known odorants, using a PCA reduction of a set of more than 4,000 physiochemical features). These three sets were defined as “global” “tiled” and “clustered” depending upon inter-odor distances. Acquisition volumes spanned 210 mm in the Z axis across PCx L2 and L3. Volumes were split into 6 optical slices each spanning 35 mm of cortex. Volumes were positioned such that 2 slices resided in L2 and 4 slices resided in L3. This allowed us to monitor similarly sized populations of neurons in L2 and L3 given the approximately 3-fold lower cell density of L3 in posterior PCx. For experiments involving the global, clustered and tiled odor sets in odor-naïve animals, data was analyzed from 3 animals per odor set. In independent experiments, olfactory bulb inputs to the piriform (which reside in layer 1) were imaged in the same configuration (via homogenous viral delivery of GCaMP6s to bulb projection neurons); these experiments yielded >500 boutons per imaging field (x 3 mice) for the tiled odor set only.
Automated segmentation of ROIs in odor-evoked glomerular imaging (Rinberg Lab)
We collected spatiotemporal patterns of activity in the olfactory bulb glomeruli across multiple odors with one-photon calcium imaging. Data is the stack of 256 x 256 pixel fluorescent images collected with CCD or CMOS camera at 100hz. Odors used for a single set of experiments contains 8-10 monomolecular odors and 16-25 binary odor mixtures at two different concentration levels. Although there exist multiple algorithms used for automated segmentation of ROIs in calcium imaging data, application of those algorithms is challenging due to multiple factors that are unique to our experimental preparation. The challenges include densely packed spatial organization of glomeruli, scattering of fluorescence to neighboring ROIs and strong hemodynamics signal that contaminates neuronal activity dependent fluorescence changes.
Link to Data/Model Reuse abstract, [Abstract 1 - Link]
Link to Data/Model Reuse abstract, [Abstract 2 - Link]
2021 Brain PI Meeting
Link to Poster:
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