NBE-E4530 Special Course in Human Neuroscience
Human brain
connectivity
(Spring 2017)
Enrico Glerean – twitter: @eglerean
The brain connectivity secret society
manifesto
•  Learning means you finding time to dive into this
topic, with the support of Enrico
•  Enrico might be wrong, we are all learners
•  After the course you must feel confident about
brain networks, methods and tools
•  Nobody is forcing you to be who you aren’t
•  We are strangers with a common goal, let’s “use”
each other to maximize the outcome
•  You define your own path, although you might not
know it yet
How to pass this
course
Who wants a 5?
Evaluation of your learning experience
1. 
2. 
3. 
4. 
Contact sessions (20 points)
Pre-assignments (25 points)
Project/practical work (30 points)
Final essay (25 points)
Evaluation of your learning experience
1.  Contact sessions (20 points)
1.  If you cannot make it, there will be a substitute
assignment so that you can catch up with others
(min 50% attendance)
2.  Active participation in class and/or forum gives you
maximum points (10 points)
3.  I am a Brit at heart, so please be punctual
2.  Pre-assignments (25 points)
3.  Project/practical work (30 points)
4.  Final essay (25 points)
Evaluation of your learning experience
1.  Contact sessions (20 points)
2.  Pre-assignments (25 points)
1.  Not too demanding, but needed for the activity in
the classroom
2.  It is enough to do everything to get maximum points
3.  Project/practical work (30 points)
4.  Final essay (25 points)
Evaluation of your learning experience
1.  Contact sessions (20 points)
2.  Pre-assignments (25 points)
3.  Project/practical work (30 points)
1.  You can decide your own project (especially PhD
students) or work on a standard one
2.  What matters is the learning not the outcome
3.  5 points from participation to afternoon sessions, with
extra 5 points for active helpers, but project work is not
done done in classroom
4.  15 points based on: shared code and tutorials
5.  5 points based on amount of tools tested
6.  To be done in pairs, but reports are individual
4.  Final essay (25 points)
Evaluation of your learning experience
1.  Contact sessions (20 points)
2.  Pre-assignments (25 points)
3.  Project/practical work (30 points)
4.  Final essay (25 points)
1.  A 1500 words IMRaD paper that describes your
project work
2.  Pass/fail (15 points)
3.  10 points for high achievers (e.g. outstanding
figures, code to re-run all analysis, code to generate
figures, insightful discussion of results)
Evaluation of your learning experience:
Feedback!
•  Feedback will give you those extra points to
round up to the next number.
•  Please provide constructive feedback from the
usual Aalto form, as well as via form I will
distribute.
•  Always find (at least) one positive thing, one
negative thing and how you would have done it
differently
•  Decide two course representatives
Asking for help
•  Email Enrico for a personal issue (e.g. I cannot
come to the lecture)
•  Ask for help in the forum for a technical issue
(How do I do this? I cannot connect to X, help?
Matlab gave this error? My operating system is
saying I cannot do this?)
Pre-assignment
•  Who had troubles with mycourses?
•  Are you on Oodi?
•  Who had troubles with GIT?
Why?"
1. WHY BRAIN NETWORKS?"
Enrico Glerean"
www.glerean.com | @eglerean"
"
The Brain according to wikipedia"
"
…The brain is the most
complex organ in a
vertebrate's body…"
"
Enrico Glerean"
www.glerean.com | @eglerean"
"
The Brain according to wikipedia"
…In a typical human the cerebral cortex (the largest part)
is estimated to contain "
15–33 billion (10^9!!) neurons "
each connected by synapses to
several thousand other neurons…"
""
Enrico Glerean"
www.glerean.com | @eglerean"
"
http://www.ted.com/talks/sebastian_seung.html"
Why do we want to study brain networks?"
•  The brain is a network with ~10^10 neurons and ~10^4 connections per neuron"
•  As for genomics in the 20th century, many authors are
now praising the connectomics as the current revolution
in neuroscience"
•  Other modelling methods focus on localised activity
(GLM), or distributed patterns (MVPA), but in my opinion
only by modelling the brain as a network we can get
meaningful insights"
•  Some people criticise this approach"
""
Enrico Glerean"
www.glerean.com | @eglerean"
"
What?"
2. WHAT IS A CONNECTOME?"
Enrico Glerean"
www.glerean.com | @eglerean"
"
The connectome"
The connectome is the complete
description of the structural
connectivity (the physical wiring) of an
organismʼs nervous system."
"
Olaf Sporns (2010), Scholarpedia, 5(2):5584.!
Enrico Glerean"
www.glerean.com | @eglerean"
"
What?"
3. WHAT IS A NETWORK?"
Enrico Glerean"
www.glerean.com | @eglerean"
"
A (complex) network, a graph"
Newman, M. E. J., Networks: An introduction. Oxford University Press, Oxford,
March 2010."
Enrico Glerean"
www.glerean.com | @eglerean"
"
Directed and undirected graphs"
Newman, M. E. J., Networks: An introduction. Oxford University Press, Oxford,
March 2010."
Enrico Glerean"
www.glerean.com | @eglerean"
"
Representation of networks"
Source: Jari Saramäkiʼs course slides"
Adjacency list"
Adjacency matrix"
Enrico Glerean"
www.glerean.com | @eglerean"
"
Many types of networks"
•  Physical networks"
-  Power grid network!
-  Physical layer of the internet!
-  Transportation networks (roads, rails)!
•  Non-physical networks"
-  Social networks (Facebook, Twitter, etc.)!
-  Stock Market!
-  IP layer of the internet!
Enrico Glerean"
www.glerean.com | @eglerean"
"
What?"
4. WHAT IS BRAIN CONNECTIVITY?"
Enrico Glerean"
www.glerean.com | @eglerean"
"
Connectivity in neuroscience"
•  Structural connectivity (estimating actual connections)"
-  Invasive (tract tracing methods, 2 photon calcium imaging)"
-  Non invasive (Diffusion Tensor and Diffusion Spectral Imaging)"
•  Functional connectivity
(based on temporal “co-variance”)"
-  Invasive (intracranial recordings)"
-  Non invasive (fMRI, M/EEG, simulated data)
"
Craddock, et al. (2013). Imaging human connectomes at the macroscale. Nature
Methods, 10(6), 524–539. (*)"
Enrico Glerean"
www.glerean.com | @eglerean"
"
How?"
5. HOW DO WE ESTIMATE STRUCTURAL
BRAIN NETWORKS NON INVASIVELY?"
Enrico Glerean"
www.glerean.com | @eglerean"
"
Diffusion Magnetic Resonance Imaging"
http://www.humanconnectomeproject.org/gallery/"
Diffusion MRI"
•  For every cube mm we measure the diffusion of water"
•  We can determine the main direction(s) along which the
fibre is going "
Enrico Glerean"
www.glerean.com | @eglerean"
"
Diffusion MRI"
•  By following the
directions of
diffusion we can
reconstruct the
tracts"
Enrico Glerean"
www.glerean.com | @eglerean"
"
Wakana, S., et al. (2004). Fiber tractbased atlas of human white matter
anatomy. Radiology, 230(1), 77–87."
How?"
6. HOW DO WE ESTIMATE FUNCTIONAL
BRAIN NETWORKS NON INVASIVELY?"
Enrico Glerean"
www.glerean.com | @eglerean"
"
Functional magnetic resonance
imaging (fMRI)"
•  We measure multiple time
series at once"
•  We can consider them
independently (e.g. GLM) or
we can look at mutual
relationships"
Blood Oxygen Level signal"
Enrico Glerean"
www.glerean.com | @eglerean"
"
Functional connectivity is multivariate"
•  Functionally connected = there is a relationship
between two or more voxel time series"
•  Pairwise (bivariate / multivariate) = we consider two
time series and compute their relationship to build a
network. Repeat for all pairs and then use multivariate
approaches e.g. network science."
•  Multivariate = consider multiple voxels at once (PCA,
ICA, MVPA)"
Enrico Glerean"
www.glerean.com | @eglerean"
"
Definitions
Functional and effective connectivity"
•  Functional connectivity = statistical dependencies
among remote neurophysiological events"
-  Pairwise and “data driven”"
-  No “direction” in the estimated connections"
•  Effective connectivity = the influence that one neural
system exerts over another"
-  Estimates the direction of influence between nodes in the network"
-  Lag based methods (Granger causality)"
-  Model based (Bayesian methods such as Dynamic Causal
Modelling"
-  Higher order statistics via ICA (e.g. LiNGAM)"
Enrico Glerean"
www.glerean.com | @eglerean"
"
Paradigms for functional connectivity
"
•  Resting state FC
Looking at spontaneous BOLD activity while the subject is
in the scanner
Correlated with anatomy"
•  Task related FC
The subject is performing a task with multiple conditions
(usually block design or naturalistic design, i.e. a block
design with longer blocks)"
Enrico Glerean"
www.glerean.com | @eglerean"
"
Building a functional network"
"
At each node we measure a time series
We compute their similarity"
b1(t)"
b2(t)"
Enrico Glerean"
www.glerean.com | @eglerean"
"
Building a functional network"
Similarity value used as weight of the edge between the
two nodes. Repeat for each pair of nodes."
r12!
b1(t)"
r12!
e.g. Pearsonʼs correlation:"
r12 = corr(b1(t),b2(t))"
b2(t)"
Enrico Glerean"
www.glerean.com | @eglerean"
"
Building a functional network"
Repeat for all pairs of nodes and we get the full
functional network"
Enrico Glerean"
www.glerean.com | @eglerean"
"
Nodes in fMRI
connectivity"
WHAT IS THE BEST CANDIDATE FOR A
NODE?"
Enrico Glerean"
www.glerean.com | @eglerean"
"
What is a node? [20 mins]
• 
• 
• 
• 
Let’s rearrange and divide us in 5 groups
Think of all brain networks in humans and animals,
but focus on functional networks
Write down definition of nodes, use the papers
you had check or search the internet using google
scholar or pubmed
Post your group work on the forum under the
thread “what is a node?”
Check answers in the forum"
Nodes in fMRI FC"
•  A node is a voxel"
-  At 2mm isotropic voxels we have ~160K nodes, i.e. 12.8e9 links!"
-  At 6mm isotropic voxels we have ~6K nodes, i.e. 18e6 links"
•  A node is a region of interest (ROI)"
-  We consider multiple voxels that are anatomically defined and
derive one time series (using average or first PC) [e.g. atlas based:
AAL atlas, Harvard Oxford atlas, UCLA atlas, Brainnettome]"
-  We consider a seed: a sphere centred at a specific location (usual
size of diameter is 1cm) [based on literature, or nodes templates
e.g. “Functional network organization of the human brain” Power
JD, et al. Neuron. 2011 Nov 17; 72(4):665-78."
-  WARNING: selection of ROIs can introduce bias"
Enrico Glerean"
www.glerean.com | @eglerean"
"
Links in fMRI
connectivity"
WHAT IS THE BEST CANDIDATE FOR A
LINK?"
Enrico Glerean"
www.glerean.com | @eglerean"
"
What is a link? [20 mins]
• 
• 
• 
• 
Let’s rearrange and divide us in 5 groups
Task is about finding ways to compute similarity of
time series for functional data
Write down methods to compute similarity, use
the papers you had check or search the internet
using google scholar or pubmed
Post your group work on the forum under the
thread “what is a link?”
Check answers in the forum"
Methods for similarity between time
series"
•  Pearsonʼs correlation: simple correlation"
•  Partial correlation: choose a pair of nodes, regress out
all other nodes (more towards a multivariate than
bivariate)"
•  Regularised inverse covariance: useful for short sess. "
•  Mutual information: (non)linear share of information"
•  Coherence: looking at cross-spectral similarity between a
frequency representation of the time serience"
Enrico Glerean"
www.glerean.com | @eglerean"
"
Which one is the best method?"
•  The answer is: it depends."
•  If you are looking for subtle differences e.g. between
groups or between conditions, some more refined
measures could perform better (Smith et al. showed
partial correlation, inverse covariance and Bayes-net
methods as winners)"
•  However, in most cases simple linear correlation is
enough, see Hlinka, J., et al (2011). Functional
connectivity in resting-state fMRI: is linear correlation
sufficient? NeuroImage, 54(3), 2218–25. doi:10.1016/
j.neuroimage.2010.08.042"
Enrico Glerean"
www.glerean.com | @eglerean"
"