2019 China Neuroscience Related Conference or Summer School Information Short List

南京 “脑-智” 国际研讨会 Nanjing International Symposium on Brain-Mind-Intelligence

Time:
Conference: 6 22-6 23, 2019
Skill Training: 6 24-6 25, 2019
Address: Nanjing

IBRO-ICPBR Summer School of Primate Neurobiology

Time:
Lectures: July 8th to July 14th, 2019
Internships: July 1st to August 31st, 2019
Address: Institute of Neuroscience, Chinese Academy of Sciences 320 Yue Yang Road, Shanghai 200031, China
The online application will be closed on **April 30th, 2019 (11:59 p.m. GMT+8)**


2019年《脑的真相》国际暑期学校 2019 SJTU Brain Facts International Summer School

时间：2019年7月1日-7月19日
地点：上海交通大学及上海周边地区等
教学内容和实践活动
Course A：2周    Course B：1周

开展海内外名师课程及讲座、学生报告研讨会、实验室工作坊、参观访问校外研究机构及企业、中国文化采风等活动。学生中期总结研讨会后，部分学员可选择进入相应课题组实验室开展科研见习，并最终递交一份实验报告，教学部分和科研见习将分别颁发结业证书。

报名方式及截止时间:

通过在线报名系统报名http://apply.sjtu.edu.cn，报名截至2019年5月31日。


2019第一届中国计算与认知神经科学会议

Time: 2019年6月14日-16日
Address: Chengdu

会议注册与缴费:

     现场注册：1500 元（5月15日后及现场)

    提前注册（5月15日及之前）：注册费1200元；学生（凭学生证或研究生证）600 元


The 4th International Conference on Basic and Clinical Multimodal Imaging (BaCI)

Time: September 10 to September 14, 2019
Address: Chengdu, China
**Status: Submitted Abstract, Waiting**

The Short Introduction of The Neurome Project

The Short Introduction of The Neurome Project
I am keen to visualize the brain connectome by HPC.  Here is a classical example for brain connectome research by Dr. Larry W. Swanson. The short introduction of the neurome project, link here. 

Adapted from neurome project

Adapted from neurome project

Adapted from neurome project

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

Computational Neuroscience-small section

Computational neuroscience is always my favorite research subject, I noticed some interesting information about introduction computational neuroscience, it mainly comes from neurosimlab. The part of the section you can link here.