Post on 11-Jun-2020
AlexFornito
BrainandMentalHealthLabMonashInstituteofCognitiveandClinicalNeurosciences
MonashUniversity
e:alex.fornito@monash.edu@AFornito
Anintroductiontobrainnetworks
Felleman &VanEssen,Cereb Cortex,1991
segregation integration
two fundamental principles of brain organization
Broca’s Leborgne (akaTan)
Scoville &Milner’sHM
Harlow’sPhineasGagePolyak, 1957
Huth etal.Nature,2015
Nature,1993
1990-1992discovery of BOLD
contrast
Ogawaetal.PNAS,1992
Conturo etal.PNAS,1999
1999 development of
diffusion tractography
nanoscalenm
microscalenmto𝜇m
meso𝜇m to mm
macroscalemmtocm
connectome:
a comprehensivestructuraldescriptionofthenetworkofelementsandconnections
formingthehumanbrain.
Sporns,Tononi,Kötter,PLoS CompBiol,2005
modellingbrainnetworksasgraphs
any network can be modelled as a graph of nodes connected by edgesnodes represent fundamental processing units
edges represent the interactions between nodes
nodeedge
LeonhardEuler(1707-1783)
a briefhistoryofgraphtheory
PaulErdős(1913-1996)
Alfréd Rényi(1921-1970)
a briefhistoryofgraphtheory
random scalefree
Barabasi &Albert,Science,1999;Barabasi &Oltvai,NatRevGenet,2004
realnetworkshavehubs realnetworksaresmall-world
WattsandStrogatz,Nature,1999
realnetworksaremodular
Girvan&Newman,PNAS,2004;Clauset,Moore&Newman,Nature,2008
definingnodes
Brainnodesshouldhave:1. Intrinsicconsistency2. Extrinsicdifferentiation3. Spatiallyconstrained
vandenHeuvel etal.NeuroImage,2009Hayasaka &Laurienti,NeuroImage,2010
voxel-based
Glasser &VanEssenJNeurosci 2011
myeloarchitecture
Dosenbach,etal.Science,2010Fornitoetal.PNAS,2012
functional
Hagmann,etal.PLoS One,2007Zalesky,etal.NeuroImage,2010
Fornitoetal.FontSysNeurosci,2010
random
Tzuorio-Mazoyer,etal.NeuroImage,2002Desikan,etal.NeuroImage,2006
anatomical
Eickhoff etal.NeuroImage,2007
chemoarchitecture
Brodmann,1909
cytoarchitecture
Eickhoff etal.NeuroImage,2006
probabilistic
Fornitoetal.NeuroImage,2013
Yeoetal.JNeurophysiol,2011Craddocketal.HumBrainMapp,2012
Poweretal.Neuron,2011
data-driven multimodal
Glasser etal.Nature,2016
definingedges
FunctionalconnectivityAstatisticaldependencebetweenspatiallydistinctneurophysiologicalsignals
EstimatedatlevelofmeasuredsignalsCanbedirectedorundirected
EffectiveconnectivityTheinfluencethatoneneuronalsystemexertsoveranother
Usuallymodel-basedDescribescausalinteractionsattheneuronallevel
Friston etal,1994,HumBrainMapping;Fornitoetal,2015,NatRevNeurosci
StructuralconnectivityThephysical(anatomical)connectionsbetweenbrainregions
IntrinsicallydirectedDirectionalitycannotberesolvedwithMRI
definingedges
Modha &SinghPNAS,2010Shanahanetal.Fron CompNeurosci,2013
http://cocomac.org
informatics
Bocketal.Nature,2011Whiteetal.PTRS,1986
electronmicroscopy
Ohetal.Nature,2014http://connectivity.brain-map.org
tract-tracing
Axer,etal.NeuroImage,2011
PLI
Hagmann etal.PLoS One,2007
DWI
Chiangetal.Curr Biol,2011www.flycircuit.tw
geneticlabelling
structural functional
electrophysiology
Yuetal.Cereb Cortex,2008
calciumimaging
Ahrensetal.NatMethods,2013
ECoG
Bastos etal.Neuron,2015Brovelli,etal.PNAS,2004
M/EEG fMRI
Engeletal.Neuron,2013 Smithetal.NeuroImage,2011
mappingstructuralconnectivityinhumanswithDWI
Johansen-Berg&Rushworth,AnnRevNeurosci,2014;Mori&Zhang,Neuron,2008;Tournier etal.Magn ResMed,2011;Isenberg,2011;Thomas,etal.PNAS,2014
measuringconnectionweightswithdiffusionMRI
connectionweightstypicallyestimatedas:numberofconnectingstreamlines
averagetractFAorotherdiffusivityindex
but:
emergingapproachesinclude:axondiameter&density(Assaf etal.NeuroImage,2013)
trackdensityimaging(Calamante,etal.NeuroImage,2011)myelincontent(Deoni etal.Magn ResMed,2008)
definingedges
Modha &SinghPNAS,2010Shanahanetal.Fron CompNeurosci,2013
http://cocomac.org
collated
Bocketal.Nature,2011Whiteetal.PTRS,1986
electronmicroscopy
Ohetal.Nature,2014http://connectivity.brain-map.org
tract-tracing
Axer,etal.NeuroImage,2011
PLI
Hagmann etal.PLoS One,2007
DWI
Chiangetal.Curr Biol,2011www.flycircuit.tw
geneticlabelling
structural functional
electrophysiology
Yuetal.Cereb Cortex,2008
calciumimaging
Ahrensetal.NatMethods,2013
ECoG
Bastos etal.Neuron,2015Brovelli,etal.PNAS,2004
M/EEG fMRI
Engeletal.Neuron,2013 Fornitoetal.NeuroImage,2013Smithetal.NeuroImage,2011
mappingfunctionalconnectivitywithfMRI
rest task
Fox&Raichle,NatRevNeurosci,2002Achard etal.JNeurosci,2005Smithetal.NeuroImage,2011
Fornitoetal.PNAS,2012Fornitoetal.Biol Psychiatry,2012Coleetal.NatNeurosci,2013
statisticaldependence
correlationpartialcorrelationmutualinformation
…etc
dynamicsZalesky etal.PNAS,2014
Hutchison,etal.NeuroImage,2013
Fornito, Zalesky & Bullmore, 2016, Fundamentals of Brain Network Analysis
topologicalbiasesofcommonfunctionalconnectivitymeasures
Zalesky, Fornito, Bullmore, NeuroImage, 2012
functionalconnectivity
structuralconnectivity
adjacencymatrix
braingraph
fromdatatograph
definenodes&edges buildgraph
Fornito, Zalesky, & Breakspear. 2015, Nat Rev Neurosci
matricesandgraphsareformallyequivalent
Fornito, Zalesky & Bullmore, 2016, Fundamentals of Brain Network Analysis
whichgraphbestrepresentsthebrain?
binary weighted
heterogeneousedgesheterogeneousnodes
directed
hybrid
Fornito, Zalesky, & Breakspear. 2013, NeuroImage; Fornito, Zalesky, Bullmore, 2016, Fundamentals of Brain Network Analysis
whichgraphbestrepresentsthebrain?
functionalconnectivity
structuralconnectivity
adjacencymatrix
braingraph
fromdatatograph
connectivity
topology
definenodes&edges networkanalysisbuildgraph
Fornito, Zalesky, & Breakspear. 2015, Nat Rev Neurosci
functionalconnectivity
structuralconnectivity
adjacencymatrix
braingraph
fromdatatograph
connectivity
topology
definenodes&edges networkanalysisbuildgraph
Fornito, Zalesky, & Breakspear. 2015, Nat Rev Neurosci
Networkthresholding&statisticsAndrewZalesky
Paths,diffusion&communicationBratislav Misic
Modularity(static&dynamic)SarahMuldoon
Centrality&hubsMartijn vandenHeuvel
Null&generativemodelsPetraVertes
Graphs provide useful models of brain networksA unified framework for representing multiscale organization
summary
There are different methods for defining brain nodes and edgesEach has pros and cons; constrains interpretation of findings
Brain networks can be analysed at the level of connectivity or topologyEffects can be mapped at individual edges, nodes, or globally
Brain networks can be directed/undirected and weighted/unweightedNode/edge heterogeneity and dynamics can also be accomodated
resources
Amazonhttp://amzn.to/1MLgMhU
Elsevierhttp://bit.ly/1Hp29OZ
graphtheory/networkscience
Newman(2010)Networks:Anintroduction.
Newman(2003)SIAMRev.
Albert&Barabasi (2002)RevModernPhysics
graphtheoryandthebrain
Sporns (2011)Networksofthebrain.
Sporns (2012)Discoveringthehumanconnectome.
Bullmore &Sporns (2009)NatRevNeurosci.
Bullmore &Bassett(2011)Annu RevClin Psychol.
Fornito,Zalesky &Breakspear (2013)NeuroImage.
software
Brainconnectivitytoolbox:https://sites.google.com/site/bctnet/
Graphanalysistoolbox:https://www.nitrc.org/projects/gat/
Network-basedstatistic:http://www.nitrc.org/projects/nbs/
Task-relatedfunctionalconnectivity(cPPI):http://www.nitrc.org/projects/cppi_toolbox/
Networkvisualizationhttp://immersive.erc.monash.edu.au/neuromarvl/
Anopen-accessjournalfornetworkneuroscienceatalllevels,
frommoleculartomacroscales
http://www.mitpressjournals.org/netn