During the first day of the even, we invite you to choose a dataset of interest and to collaborate in groups to explore research questions based on that dataset. The datasets to choose from are described below
Prepare for the event!
The Dataset Leaders prepared documentation to assist you in setting up your laptop for effective analysis of the chosen dataset. Please check and follow the instructions for the dataset you choose:
Dataset 1 Setup Guide
Dataset 2 Access to the dataset and here you can find the Setup Guide
Dataset 3 Setup Guide
Datasets information
| Dataset | Data-type | Description | Type of analysis | Lead by |
|---|---|---|---|---|
| Dataset 1: Protein expression in Down’s syndrome mice model | Protein expression | The data set consists of the expression levels of 77 proteins/protein modifications that produced detectable signals in the nuclear fraction of cortex. There are 38 control mice and 34 trisomic mice (Down syndrome), for a total of 72 mice. In the experiments, 15 measurements were registered of each protein per sample/mouse. The dataset contains a total of 1080 measurements per protein. Each measurement was considered as an independent sample/mouse. The eight classes of mice are described based on features such as genotype, behavior, and treatment. According to genotype, mice can be control or trisomic. According to behavior, some mice have been stimulated to learn (context-shock) and others have not (shock-context) and in order to assess the effect of the drug memantine in recovering the ability to learn in trisomic mice, some mice have been injected with the drug and others have not. | Protein Expression Analysis | Aditya Nemali |
| Dataset 2: Neurons dataset from mice in decision-making task | Neuronal recording | The Steinmetz dataset contains 39 Neuropixels recordings of 400-700 neurons each from across the mouse brain during a visual behavior task. This dataset was used by the most groups last year, as it is great for exploratory analyses and is relatively well supported with code and many included experimental and behavioral variables. You should still try to ask specific questions, i.e.: “does the superior colliculus offer a parallel or complementary visual processing pathway to visual cortex?”. For more information click here. | Neurons Dataset in Colab | Anwesha Das |
| Dataset 3: Block-design human fMRI dataset | Haxby dataset (7T&3T) | This is a block-design fMRI dataset from a study on face and object representation in human ventral temporal cortex. It consists of 6 subjects with 12 runs per subject. In each run, the subjects passively viewed greyscale images of eight object categories, grouped in 24s blocks separated by rest periods. Each image was shown for 500ms and was followed by a 1500ms inter-stimulus interval. Full-brain fMRI data were recorded with a volume repetition time of 2.5s, thus, a stimulus block was covered by roughly 9 volumes. This dataset has been repeatedly reanalyzed. For a complete description of the experimental design, fMRI acquisition parameters, and previously obtained results see the Haxby et al. (2001). | Nilearn Decoding Tutorial | Avinash Kalyani |