Visualization Brain

Visualization neuroscience data

1.visualization neuroscience

I had experience for molecular research, in studying this area period, I am very painful because I can't watch or notice what happened in my every step of the experiment, I really want to know to make my every step under my control and visualization what happened in real-time. But the fact is we don't know whether each step is right and until the last moment machine helps us visualization result, if we failed, actually, we normally waster more time and energy, but we don't get the good or expected experiment result.

In the neuroscience and neuroimaging, MRI has good spatial resolution and fMRI can make us visualization brain activity in real-time, so I think that visualization brain signal whatever for academic research and present your result both are very important. Combined with High-Performance-Computer(HPC) can help us visualization and simulation the neuron signal. We should grasp this opportunity to build a larger platform to visualization single cell to single neuron, neuron circuit, whole neuron activity, reconstruction neuron map etc based on machine learning, HPC etc technology. 

2.3D visualization fMRI data 

In this section, I will introduce some techniques that can help us 3D visualization fMRI data. All software and information from the literature "Creating 3D visualizations of MRI data: A brief guide". If you are interested in visualization fMRI data, you can read the raw paper.

2.1 Standard fMRI analysis and 3D visualization packages

1. SPM: http://www.fil.ion.ucl.ac.uk/spm/
2. AFNI: http://afni.nimh.nih.gov/afni/, with SUMA
3. FreeSurfer https://surfer.nmr.mgh.harvard.edu
4. MRIcroGL: http://www.mccauslandcenter.sc.edu/mricrogl/ 
5. 3D Slicer: http://www.slicer.org
6. Mango: http://ric.uthscsa.edu/mango/ 
7. ITK-SNAP: http://www.itksnap.org
8. ParaView: http://www.paraview.org
9. Statistical Map Database-NeuroSynth: http://www.neu rosynth.org

Above software, most based Matlab, Linux system, but some can both work under Windows and Linux/Mac version.

The pipeline can be shown as follows:

3D visualization fMRI pipeline( Christopher R. Madsen, 2015 )

2.1.1 Visualizing cluster maps in a glass brain

1st: Obtaining the anatomical ‘glass brain’ image

Standard preprocessing-GLM-Statistics inference- Activity map(fMRI)

Template(Anatomical)

2st: Obtaining the thresholded cluster image

Function: imcalc;  nii_threshreslicecluster

spm_imcalc_ui('statmap.nii' ,'statmapH.nii' ,'i1>12')

nii_threshreslicecluster ('statmapH.nii' ,'statmapH.nii',.5,400);

3st: Convert to VTK

4st: Render in 3D

2.1.2 Visualizing anatomical ROIs

1st: Obtain ROI volume

2st: Convert to VTK

3st: Render in 3D

2. Future 

My interesting on the machine learning, HPC, neural data visualization, computational neuroscience. In the next day, I will continue to focus on this research area. 

It's time to go to eat dinner. Have a good weekend.

3. Appendix information

Images of the anatomical ROIs used in Procedure 

Comparative neuroanatomy of whole-brain and hippocampal brain volumes

 3D renderings of MRI data