AllenNeuralDynamics / AllenNeuralDynamics/lamf-analysis
Intro & figure layout
- 主要言語
- Jupyter Notebook
- スター
- 1
- フォーク
- 2
- 平均マージ
- 5時間 28分
- マージ済み PR(30日)
- 2
説明
1st draft of intro & figure layout:
https://alleninstitute.sharepoint.com/:w:/s/LearningmFISH/EZ7hqkqpQRtCpTAq4tiTcUgBqc_zvTUjAkvwspy5xKdWcQ?e=kmKNmf
Analysis goals:
1. Familiarization index (Figure 2)
- Image responses to familiar images across training + novel image response
- The same with omission responses
2. Functional clustering (Figure 3)
- Clustering using coding score (with improved encoding model)
- Clustering using traces
3. Functional interaction (Figure 4)
- Target specific known potential disinhibitory circuit (L2/3 VIP-SST, L4 SST-PV)
- Noise correlation (with better encoding model to subtract)
Stand-up meetings (Jinho & Matt):
- Quick updates and issue sharing
- Mon/Thu 10.30 am
- Optional: Arielle & Marina
Data:
1. First test with GCaMP pilot data
2. Then use most recent GAD2 or VGAT-Cre data
3. Once having co-registered data, focus on them.
- Power analysis (for number of cells and mice)
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