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Welcome to the Brain Mapping Unit wiki

This is a wiki, a user-editable Web site. You can treat it as a perfectly ordinary Web site (read it), but you are also able to make changes to any page that has an edit link at the top of it. The more or you contribute, the more useful this page will become for current and future members of our group, so please feel free to add any relevant information!

The relationship between BMU, BCNI and CBU wikis

When you first join the BMU, you may wonder how the BMU, BCNI and CBU are related. Broadly speaking, the BMU (Brain Mapping Unit) is a constituent unit within the Department of Psychiatry, the BCNI (Behavioural and Clinical Neuroscience Institute) links six basic-science and clinical departments within the university and has a focus on translational research, and the CBU (Cognition and Brain Sciences Unit) is a standalone non-university-affiliated centre for cognitive science research.

There are many resources that the BMU, BCNI and CBU have in common and it therefore makes sense for you to explore the BCNI and CBU websites and wikis when you have time (see details below). However, too much information can be problematic when you arrive in a new group. The aim of this wiki is therefore to concentrate on the key knowledge and resources that you are most likely to need when starting out at the BMU. We aim to present these in a clear, well-organized and easy-to-navigate way. This wiki will also include some more specialized in-house knowledge such as network analysis and visualisation tools often used in the group. For more general fMRI and MEG image analysis methods, the CBU wiki is probably the place to go.

CBU The CBU Imaging Wikis (one for fMRI and another for MEG) host a wealth of information on the design and analysis of imaging studies including highly popular tutorials.

Become a Contributor

If you have just joined the BMU, it is the ideal time to become a wiki contributor. You can 'keep notes' of what you are learning by adding it to the wiki. This will both help you remember and help others learn faster. To learn how to edit the wiki just click on the link at the bottom of the page (it's dead easy and will only take 5 to 10 minutes). In order to be able to edit these pages, you first need to log in (top right corner) via raven.

For your first wiki-edit, try adding your name to this list of contributors: Lisa Ronan, Petra Vertes, Mika Rubinov, Prantik Kundu, Ameera Patel, Kirstie Whitaker, Rachel Moseley...

General Information

Introductory papers

The first thing to do if you are starting out at the BMU is probably to read a couple of easy introductory papers on network science in general, as well as applied to neuroscience. Some useful papers to start with can be found at Introductory Papers

Publications by the BMU

You can see a list of the group's publications on the relevant page of the BMU group website

A non-exhaustive list of journals you may find interesting

Nature, Science, Nature Neuroscience, PNAS, Journal of Neuroscience, Brain, NeuroImage, Biological Psychiatry, PLoS Computational Biology, Cerebral Cortex, Frontiers in Systems Neuroscience...

Keeping up with new literature

Most scientific journals allow you to sign up for 'e-alerts'. These are regular emails with either the journal's Table of Content (each time a new issue is published) or alerts about new papers from specific authors or containing specific keywords that you indicate you wish to follow. Just visit the webpage of your journal of interest and follow instructions to set up your e-alerts.

Courses, seminars and groups

Cambridge Neuroscience Talks

Most neuroscience-related talks in Cambridge are advertised on this neat list.

Statistics, Programming and Neuroimaging Courses

The Department of Experimental Psychology has a useful list of courses on statistics, programming and neuroimaging here.

Tuesday Meetings - The Networks Group

Our weekly seminars are held on Tuesday mornings (11:00-12:00). These are principally for Ed Bullmore's students but also for other people within the BMU and associated groups with an interest in using networks to study the brain. For details about the structure of these meetings, see Lab meeting.

Cambridge Networks Network (CNN)

CNN aims to bring together researchers from many different departments across Cambridge who share an interest in Complex Networks. You can learn more about it and join the CNN mailing list here.

Cambridge Training

A database of training courses run across departments. For BMU members, courses on programming (e.g.: Matlab, R, Python) or a crash course on neuroscience should be of particular interest. However, there are also courses on public engagement, writing and communication skills, and many other useful topics. For a schedule of events, see here.

Conferences and Workshops

Relevant events

Large conferences

The annual meeting of the Organization for Human Brain Mapping (OHBM) [1], held yearly around June.

The annual meeting of the Society for Neuroscience (SfN) [2], held yearly in the US around October/November.

Smaller workshops

The Brain Connectivity Workshop [3], usually held in (spatial and temporal) proximity to OHBM.

The biennial conference on Resting State and Brain Connectivity [4].

A one-off symposium on Connectomics across scales, held in New Mexico in March 2017 [5].

A yearly conference on networks (not necessarily brain networks) [6]

Sources of funding

The Guarantors of Brain (also behind Brain, the journal) provide a range of fellowships. The main is a conference travel fellowship provided to PhD students and postdoctoral fellows working in the UK. Awards range from a maximum of £400 (UK meetings) through £600 (Europe) to £800 (rest of world). Applications must be submitted at least 8 weeks before the meeting, through the website. For more information on these travel grants, see here. For general information about the charity and all of the grants they provide, see links on their main page.

The University of Cambridge Graduate School of Life Sciences (GSLS) has a few options available - especially the E. G. Earnside fund, which provides a maximum of £600 for conferences in Europe and £1000 for conferences beyond. For more information, see their website.

Sharing Data

In principle, we could put links to data located on the server so as to make it available to others in the group. Please make sure the data in question is free for you to share before doing this. Also, please try to document the data (a link to a paper describing the same dataset should do) and maybe add the name of the person that originally sourced the data.

Here are some existing public datasets (in matrix form) to get started: [7]

Data Preprocessing and Analysis

Other

Other useful bits if information in the great adventure of graph analyses

Useful Unix Commands

Kirstie has started a list of useful linux commands on her GitHub wiki. Please feel free to suggest additions!

Network Construction

In brain functional networks, each node corresponds to a different brain region, $i$, and edges or connections between nodes represent statistical associations, e.g., correlations, between the time series, $S_i(t)$, recorded at each of these regions. Once the $N x N$ association matrix of correlation coefficients has been evaluated (for $N$ brain regions), it is possible to draw a fully connected, weighted network where the weight of each link corresponds to the correlation strength between the pair $i,j$ of nodes it connects. This network, however, is not easy to analyze and contains many spurious connections resulting from noise rather than genuine correlations. It is therefore usually replaced by a sparser, unweighted network where, following the application of some filtering technique, only the most important connections have been retained as edges in a binary adjacency matrix. One difficulty arises from the fact that the method for filtering out less important connections is arbitrary and has a strong influence on the results obtained.

Beyond Correlations

This section discusses the various forms of statistical association that networks can be based on.

Thresholding Methods

This section discusses the various thresholding methods that can be used.

Network Analysis

All commonly used network measures have been implemented in MATLAB and bundled into a wonderful toolbox called the Brain Connectivity Toolbox by Olaf Sporns and collaborators. [8] They also welcome any additions to their toolbox, so feel free to contribute.

For people more inclined to just point and click, GAT provides and interface for the Brain Connectivity Toolbox, mostly aimed at use for structural covariance analysis (includes covariates , some plotting and permutation testing [9]. Note that for fine-grained parcellations the current implementation (03-2016) is sub-optimal as it attempts to store all permuted matrices in one big mat file and tries to keep most of it in working memory (resulting in a nodes*nodes*permutations*densities 4D file).

Visualization Tools

Network Visualization

A variety of tools have been developed to generate efficient and pleasing graphical representations of networks:

• PAJEK is one of the most commonly used ones: [10]
• Gephi is looking increasingly polished: [11]
• GUESS is my personal favourite [12]
• BrainNet Viewer for visualising nodal and edge structures on brain meshes [13] and a short matlab wrapper for getting your data from matlab into the correct format along with a file containing the nodal information in matlab format [14]

Other Visualization tools

• Caret allows the creation of beautiful brain surface maps: [15]

Using The High Performance Computing Service

If you're looking for some helpful hints on how to use the HPC [16] please see High Performance Computing Service.

Alternatively, Ian Luff has also set up a Sun Grid Engine that everybody can use to submit jobs for parallel processing on the BCNI servers.

How To Edit the Wiki

• You can find some help on editing this wiki on HowToEdit
• Provided by Computing Service, University of Cambridge