Sunghyon  Kyeong

National Institute for Mathematical Sciences, Computational Neuroscience Team

Physics,  Network,  Brain

Saturday  Cogni.ve  Science  Mee.ngSogang  University,  Korea,  17th  March  2012

starinphysics@gmail.com

Contents

• Physics-­‐  Physics  in  Magnetic  Resonance  Imaging  (MRI)  -­‐  Principle  of  BOLD  signal  of  fMRI

• Complex  Network-­‐  Introduction  to  Graph  Theory  /  Example-­‐  Social  Network  with  Twitter  Streamline

• Brain  and  Neuroscience-­‐  Studying  complex  network  in  Human  Brain-­‐  Network  alteration  during  motor  task-­‐  TMS  for  motor  function  recovery

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Physics in Magnetic Resonance Imaging (MRI)

Philips  3T  Scanner

Siemens  3T  Scanner

Philips  0.6T  Open  Scanner

4

Components  of  MRI

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1.  Magnetic  :  Static  Magnetic  Field  Coils

2.  Resonance  :  Radio  frequency  Coil

3.  Imaging  :  Gradient  Field  Coils                                    spatial  encoding  of  the  MR  signal

-­‐  Shimming  Coils-­‐  Data  transfer  and  storage  computers

• Let’s  recall  the  resonance  frequency  when  you  learn  in  high  school  physics.

• By  applying  small  pushes  at  the  resonance  (      )  frequency  of  the  swing  set  ...

• In  MRI,  amplitude  of  RF  is  very  small  compared  to  B0.

What  is  Resonance  ?

�0 =r

g

l

!0

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• Nuclei  have  two  properties:-­‐  spin,  charge  

• Nuclei  are  made  of  protons  and  neutrons:-­‐  both  have  spin  value  of  1/2-­‐  protons  have  charge

• Pairs  of  spins  tend  to  cancel,  so  only  atoms  with  an  odd  number  of  protons  or  neutron  have  spin.

• The  spinning  particle  generates  an  angular  momentum  J.

Properties  of  Atomic  Nuclei

⇥µ = � ⇥J

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• Most  common  in  out  bodies:-­‐  Carbon,  Oxygen,  Hydrogen,  Nitrogen

• Of  these,  only  Hydrogen  has  the  nuclear  magnetic  resonance  (NMR)  property.

• Hydrogen  is  the  most  abundant  atom  in  the  body-­‐  Mostly  in  water  molecular  (H2O).

What  nuclei  can  we  measure?

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MRI  Signal:    T1  and  T2

• Applying  RF  pulse  to  tip  down  bulk  magnetization  (Mz)  to  the  transverse  plane.

• Mz  tends  to  align  the  external  magnetic  Tield  as  time  goes  on  (T1  recovery).

• Mz  decays  in  the  transverse  plane  as  time  goes  on  (T2  decay).  

Good  ContrastGood  Contrast

T2*  Decay  in  Presence  of  B0

• The  time  constant  of  the  decay  is  called  T2.  • However,  in  physiological  tissue  the  transverse  relaxation  is  more  rapid  because  of  local  Vield  inhomogeneities.

• When  the  Vield  inhomogeneities  are  present,  the  decay  constant  is  called  T2*.

1T ⇤

2

=1T2

+ ��B0

• T1  recovery  and  T2  decay  time  ranges  from  tens  to  thousands  of  milliseconds  for  protons  in  human  tissue  over  the  main  Tield.  Typical  values  for  various  tissues  are  shown  in  following  table.

• Applying  the  pulse  sequences,  we  can  discriminate  brain  tissues;  The  different  sequences  should  be  applied  to  obtain  the  speciTic  image,  for  example,  anatomic,  functional,  angio  images.

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Tissue T1(ms) T2(ms)  Gray  matter  (GM) 950 100  White  matter  (WM) 600 80  Muscle 900 50  Cerebrospinal  Tluid  (CSF) 4500 2200  Fat 250 60  Blood 1200 100~300

Tissue  SpeciGic  T1  and  T2

B0 = 1.5 T

T = 37�C

obtained  at

       Principles  of  

   Blood  Oxygen  Level              Dependent      Signal  for  fMRI

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Structural  vs.  Func4onal  MRI

Structural  MRI  studies  brain  anatomy

Functional  MRI  (fMRI)  studies  brain  function

by  Eunha  Limshoresilence@naver.com

• The  abbreviation  BOLD  fMRI  stands  for  Blood  Oxygen  Level  Dependent  functional  MRI.

• The  BOLD  contrast  mechanism  alters  the  T2*  parameter  mainly  through  neural  activity–dependent  changes  in  the  relative  concentration  of  oxygenated  and  deoxygenated  blood.  

• Deoxyhemoglobin  is  paramagnetic  and  inTluences  the  MR  signal  unlike  oxygenated  hemoglobin.

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Detecting  fMRI  Signal

• DeTinition  :  Substances  that  alter  magnetic  susceptibility  of  tissue  of  blood,  leading  to  changes  in  MR  signal-­‐  Affects  local  magnetic  homogeneity:  decrease  in  T2*

• Two  types-­‐  Exogenous  :  Externally  applied,  non-­‐biological  compounds.-­‐  Endogenous  :  Internally  generated  biological  compound  (e.g.,  dHb)

• BOLD  functional  magnetic  imaging  method  doesn’t  need  the  external  contrast  agents.

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Contrast  Agents  for  fMRI  ?

• BOLD  contrast  measures  inhomogeneities  in  magnetic  Vield  due  to  changes  in  the  level  of  O2  in  the  blood.

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Measuring  O2  Ratios  in  Brain

High  ratio  deoxy  :→  deoxygenated  blood  →  fast  decrease  in  MRI  signal

Low  ratio  deoxy  :→  oxygenated  blood  →  slow  decrease  in  MRI  signal

deoxyhemoglobin  (paramagnetic)  

Hb dHb

Normal  blood  *low High  blood  *low

oxyhemoglobin(non-­‐magnetic)

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Mechanism  of  BOLD  Signal

Time

Signal

Mo sinθ

T2* task

T2* control

TEoptimum

Stask

Scontrol ΔS

↑  Neural  Activity ↑  Blood  Flow ↑  Oxyhemoglobin

↑  T2*

↑  MR  Signal

• %  Signal  Change=  (point-­‐baseline)/baseline

• Time  to  Risesignal  begins  to  rise  after  stimuli  begin.

• Time  to  Peaksignal  peaks  approximately  6  seconds  after  stimulus  begins.

• Post  Stimulus  Undershootsignal  suppressed  after  stimulation  ends.

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Hemodynamic  Response

0 5 10 15 20 25 30−0.01

0

0.01

0.02

0.03

−0.01

0

0.01

0.02

time (sec)

Arb

itrar

y U

nits

   Complex  Network          -­‐    Graph  Theore.cal  Approach

C

B

A

D

1. What  is  degree?  2. betweenness  centrality?3. global/local  network  ef*iciency?

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Types  of  Graph

undirected  binary  graph

directed  binary  graph

directed  weighted  graph

1

3

6

5

2

4

0 1 1 0 0 0

1 0 1 0 1 0

1 1 0 0 0 0

0 0 0 0 1 0

0 0 0 1 0 1

0 0 0 0 1 0

Aij  =

AdjacencyMatrix

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• A  network  is  a  set  of  nodes  connected  by  edges.

• Types  of  Networks:

-­‐ Social  networks:  Facebook,  Twitter,  business  relations  between  companies,  

-­‐ Information  networks:  network  of  citations  between  academic  papers,  World  Wide  Web  (web  pages  are  linked  from  one  page  to  other),  semantic  (how  words  or  concepts  link  to  each  other)

-­‐ Biological  networks:  Food  web,  (functional/structural)  brain  network

Networks  in  the  Real  World

Network  Analysis  Example

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co-­‐authorship  network  formed  by  author  list

semantic  networkformed  by  free  association

Steyvers,  Cognitive  Science  29  (2005)  41–78Neumann,  PNAS  101  (2004)  5200-­‐5205  

Informa.on  Flow  Through  TwiLer  Data    Measuring  centrality  (hub  of  informa.on  flow)

project  members:

https://www.facebook.com/LeeSeongjoohttps://www.facebook/com/sunghyon.kyeong

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• Objective:  measuring  the  centrality  of  the  twitter  status  Vlow  (i.e.  information  propagation  via  retweet)  by  complex  network  analysis.

• By  streaming  the  tweet  timeline  data  with  keyword  (i.e.  “총선”,  “화이트  데이”,  and  etc),    

• Issues  for  this  project:  (1)  how  to  deal  with  the  large  data  set  (retweet  explosion  for  the  special  events,  i.e.,  “화이트  데이관련”  RT  at  midnight  3/14,  (2)  how  to  deVine  ‘node’  and  ‘edge’  to  measure  tweet  status  Vlow,  (3)  how  to  connect  other  social  networks  (FB,  blog)

Measure  Social-­‐InfoGlow

Facebook Twitter정보 공유 대상 상호 친구 관계를 맺은 사용자들 정보 구독 대상으로 설정한 사용

자의 새소식을 받아봄.

특징 친구 관계 또는 확장된 친구 관계 내에서 정보 공유.

하나의 게시물은 140자 이내로 작성됨.

정보 접근성 본인과 친구들의 정보 외에는 외부 네트워크에서 정보를 조회할 수 없음.

계정명을 알면 게시물을 조회하거나 해당 계정에 메시지를 보낼 수 있음.

전세계 등록 계정수 (2011년)

약 8억 개 약 2억 개

한국 등록 계정수 (2011년) 약 6백만 개 약 3백만 개

Facebook  vs.  Twitter

• 트위터의 게시물은 온라인에 공개된 정보

• 게시물이 140자 이내로 작성되기 때문에 실시간으로 수많은 데이터들이 생성됨

• 9일 이내 데이터에 대해 제한적으로 검색 가능

http://www.bloter.net/wp-content/bloter_html/2011/09/74422.html

Collecting  Tweet  Data

3313ahn:  full  of  RTmisunmoon1215:  대학생,  상품  소개.  이벤트  소개.  등  트윗minjungseo88:  유용한  정보  다량  소개

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out degree

betweenness centrality

• Tweet  streamline  data  collected  with  keyword  =  [‘화이트데이’,  ‘화이트  데이’]

• Retweeted  at  least  one  time.

ahn3313:  full  of  RT  (뉴스관련)Trend_bot:    세계적으로  중요한  이슈  RTjeonYH153:  유용한  정보  RTbatrobas:  정치  사회적  RT

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in degree out degree

betweenness centrality

• Tweet  streamline  data  collected  with  keyword  =  [‘총선’,  ‘411’]

• Retweeted  at  least  one  time.

Complex  Network  in  Human  Brainbetweenness  centrality  to  iden.fy  default  mode  network

...

...

Spatial  Preprocessing-­‐  realign,  coreg,  norm,  smooth

Seed-­‐based  connectivity  (PCC)

time  course  for  voxel  based  analysis

AAL  map

Parcellation  into  116  brain  regions

Adjacent  Matrix

Networkproperties

Network  Construc4on

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• Brain  network  at  resting  state  (within  low  frequency  0.009~0.08  Hz)  including  posterior  cingulate  cortex,  lateral  parietal  area,  medial  frontal  cortex.

• Patient  having  a  psychiatric  disease  shows  different  patterns  of  default  mode  network.

• Node  betweenness  centrality  might  be  used  to  detect  default  mode  network  

Default  Mode  Network

node  betweenness  centralityseed  based  connectivity

free  download  the  brain  connectivity  matlab  toolbox:  https://sites.google.com/a/brain-­‐connectivity-­‐toolbox.net/bct/Home

Altera'on  of  

Motor  Networkduring  Finger  Tapping

• Data  Preprocessing  &  Network  Construction

• Results  on  network  alteration  study  during  the  Tinger  tapping  tasks.

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• Subjects  were  asked  to  keep  resting  state  with  their  eyes  closed  but  not  sleep.

• The  resting  state  fMRI  data  has  both  spatial  and  temporal  characteristic.  However,  it  doesn’t  have  design  matrices.

• To  analyze  the  resting  state  fMRI  data,  we  calculate  the  correlation  coefTicients  between  a  region  of  interest  (ROI)  and  the  whole  brain.

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Resting  State  fMRI

• Every  movements  depend  on  how  the  brain  networks  are  modulated  to  execute  a  speciTic  movement  tasks.

• The  precentral  gyrus  plays  a  key  role  in  movement  task.  When  we  move  hands,  feet,  and  facial  parts,  the  corresponding  cortical  areas  in  the  precentral  gyrus  are  associated.

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UnderstandingMotor  Cortex by  Eunha  Lim

shoresilence@naver.com

Modula'on  of  

Motor  Networksby  Brain  S4mula4on

• Why  do  we  need  the  Brain  s.mula.on?  The  fMRI  data  describes  BOLD  acJvity  preKy  well.  However,  we  don’t  really  know  causality  of  the  network.

• TMS  enables  us  to  study  the  brain  plasJcity  or  the  recovery  of  the  brain  funcJon.

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• TangenJal  component  of  the  magneJc  field  is  generated  beneath  the  figure-­‐of-­‐eight  coil.

• Time  varying  B-­‐field  generates  E-­‐field  (Faraday’s  Law).

• TMS  generates  the  localized  magneJc  field  along  the  x-­‐direcJon  not  along  the  z  direcJon.

illustraJon  by  Eunha  Lim

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Magne4c  S4mula4on

• UC  Berkeley  researchers  (Oliveira,  et  al.  2010)    revealed  that  the  right-­‐handed  volunteers  were  more  likely  to  use  their  leZ  hand  to  perform  simple  one-­‐handed  tasks  when  the  leZ  posterior  parietal  cortex  of  the  brain  received  TMS.  

• By  sJmulaJng  the  parietal  cortex,  which  plays  a  key  role  in  processing  spaJal  relaJonships  and  planning  movement,  the  neurons  that  govern  motor  skills  were  disrupted.

Altera.on  ofHandedness  by  TMS

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[Journal  Review]

• Ten  daily  rTMS  sessions  over  the  dorsolateral  prefrontal  cortex  (DLPFC)  reduced  cigareKe  consumpJon  and  nicoJne  dependence  (Amiaz,  et  al.  2009).

• The  rTMS  of  the  DLPFC  might  alter  the  brain  networks  leading  to  reduced  impulsivity  and  enhance  inhibitory  control.

Reduce  CigareHe  Craving  Consump4on  by  TMS

[Journal  Review]

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Thank  you