Designed especially for neurobiologists, FluoRender is an interactive tool for multi-channel fluorescence microscopy data visualization and analysis.
Deep brain stimulation
BrainStimulator is a set of networks that are used in SCIRun to perform simulations of brain stimulation such as transcranial direct current stimulation (tDCS) and magnetic transcranial stimulation (TMS).
Developing software tools for science has always been a central vision of the SCI Institute.
HBM Hackathon2013 newsCongratulations to Kris Zygmunt, Wei Liu, and Sean McKenna for winning the second challenge of the 2013 HBM Hackathon sponsored by Allen Institute for Brain Science and Amazon Web Services. The HBM Hackathon consisted of two challenges announced prior to the meeting and a third mystery challenge announced during the meeting. These challenges were:

1. Best imaging and gene expression relationship discovered via integration of imaging data with the Allen Human Brain Atlas.

2. Best neural systems model or visualization based on large-scale integration of resting state fMRI data with other HBM Hackathon accessible datasets.

3. MNI Mash-up: Most innovative map or aggregation of information in the MNI 152 standard.

Kris Zygmunt represented the SCI Institute team over the course of the four-day event. The team started by using Tom Fletcher's and Wei Liu's techniques for high-dimensional data analysis to explore the Allen Human Brain Atlas gene expression data consisting of nearly 60,000 gene probes sampled for each of almost 1,000 brain regions. After Wei preprocessed the expression data, Sean McKenna loaded the data into the iCorrPlot visualization tool developed by Miriah Meyer, Sam Gerber and Sean. This tool allowed the team to look at either the correlation of gene expression profiles across brain regions or the correlation of spatial brain location across gene probes. Finally, since the expression data had associated MNI 152 coordinates, the team was able to display the data colored by principal component level overlaid on a brain MR image.

On the third day of the contest, the teams gave their preliminary presentations to the judges. That evening, two finalists were chosen for each of the three challenges. The finalists had until noon the next day to prepare any new results for presentation. Wei, Sean and Kris worked quickly to repeat the analysis and visualization for a second brain in order to be able to compare the expression profiles across multiple brains. The team rapidly identified a way to combine the data from both brains within the same visualization to enable direct comparisons.

This project was a good example of collaboration between two of our main strengths at the SCI Institute: image/data analysis (Wei Liu, Tom Fletcher, Sam Gerber) and visualization (Sean McKenna, Miriah Meyer, Sam Gerber).

A list of winners for all three challenges and links to their presentations can be found on the hackathon blog - "Contest Winners Announced!"



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