1 1. Introduction to fMRI 2. Basic fMRI Physics 3. Data Analysis 4. Localisation 5. Cortical...
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Transcript of 1 1. Introduction to fMRI 2. Basic fMRI Physics 3. Data Analysis 4. Localisation 5. Cortical...
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1. Introduction to fMRI
2. Basic fMRI Physics
3. Data Analysis
4. Localisation
5. Cortical Anatomy
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1. Introduction to fMRI
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MRI studies brain anatomy.Functional MRI (fMRI) studies brain function.
MRI vs. fMRI
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Brain Imaging: Anatomy
Photography
CAT
PET
MRI
Source: modified from Posner & Raichle, Images of Mind
Brain Imaging: Anatomy
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MRI vs. fMRI
neural activity blood oxygen fMRI signal
MRI fMRI
one image
many images (e.g., every 2 sec for 5 mins)
high resolution(1 mm)
low resolution(~3 mm but can be better)
fMRI Blood Oxygenation Level Dependent (BOLD) signal
indirect measure of neural activity: active neurons shed oxygen and become more magnetic increasing the fMRI signal
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fMRI Activation
Time
BrainActivity
Source: Kwong et al., 1992
Flickering CheckerboardOFF (60 s) - ON (60 s) -OFF (60 s) - ON (60 s) - OFF (60 s)
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PET and fMRI Activation
Source: Posner & Raichle, Images of Mind
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fMRI Setup
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fMRI Experiment Stages: Prep
1) Prepare subject• Consent form• Safety screening• Instructions
2) Shimming • putting body in magnetic field makes it non-uniform• adjust 3 orthogonal weak magnets to make magnetic field as
homogenous as possible3) Sagittals
Take images along the midline to use to plan slices
Note: That’s one g, two t’s
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4) Take anatomical (T1) images• high-resolution images (e.g., 1x1x2.5 mm)• 3D data: 3 spatial dimensions, sampled at one point in time• 64 anatomical slices takes ~5 minutes
fMRI Experiment Stages: Anatomicals
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Slice Thicknesse.g., 6 mm
Number of Slicese.g., 10
SAGITTAL SLICE IN-PLANE SLICE
Field of View (FOV)e.g., 19.2 cm
VOXEL(Volumetric Pixel)
3 mm
3 mm 6
mm
Slice Terminology
Matrix Sizee.g., 64 x 64
In-plane resolutione.g., 192 mm / 64
= 3 mm
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first volume(2 sec to acquire)
fMRI Experiment Stages: Functionals5) Take functional (T2*) images
• images are indirectly related to neural activity• usually low resolution images (3x3x5 mm)• all slices at one time = a volume (sometimes also called an image)• sample many volumes (time points) (e.g., 1 volume every 2 seconds for 150
volumes = 300 sec = 5 minutes)• 4D data: 3 spatial, 1 temporal
…
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Statistical Mapsuperimposed on
anatomical MRI image
~2s
Functional images
Time
Condition 1
Condition 2 ...
~ 5 min
Time
fMRISignal
(% change)
ROI Time Course
Condition
Activation Statistics
Region of interest (ROI)
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Statistical Maps & Time Courses
Use stat maps to pick regions
Then extract the time course
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2D 3D
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Design Jargon: Runs
run (or scan): one continuous period of fMRI scanning (~5-7 min) session: all of the scans collected from one subject in one day
experiment: a set of conditions you want to compare to each othercondition: one set of stimuli or one task
4 stimulus conditions+ 1 baseline condition (fixation)
A session consists of one or more experiments.Each experiment consists of several (e.g., 1-8) runsMore runs/expt are needed when signal:noise is low or the effect is weak.Thus each session consists of numerous (e.g., 5-20) runs (e.g., 0.5 – 3 hours)
Note: Terminology can vary from one fMRI site to another (e.g., some places use “scan” to refer to what we’ve called a volume).
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Design Jargon: Paradigm
paradigm (or protocol): the set of conditions and their order used in a particular run
Time
volume #1(time = 0)
volume #105(time = 105 vol x 2 sec/vol = 210 sec = 3:30)
runepoch: one instance of a condition
first “objects right” epochsecond “objects right” epoch
epoch 8 vol x 2 sec/vol = 16 sec
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2. Basic fMRI Physics
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Recipe for MRI
1) Put subject in big magnetic field (leave him there)
2) Transmit radio waves into subject [about 3 ms]
3) Turn off radio wave transmitter
4) Receive radio waves re-transmitted by subject– Manipulate re-transmission with magnetic fields during this readout
interval [10-100 ms: MRI is not a snapshot]
5) Store measured radio wave data vs. time– Now go back to 2) to get some more data
6) Process raw data to reconstruct images
7) Allow subject to leave scanner (this is optional)
Source: Robert Cox’s web slides
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History of NMRNMR = nuclear magnetic resonance
Felix Block and Edward Purcell1946: atomic nuclei absorb and re-emit radio frequency energy1952: Nobel prize in physics
nuclear: properties of nuclei of atomsmagnetic: magnetic field requiredresonance: interaction between magnetic field and radio frequency
Bloch PurcellNMR MRI: Why the name change?
most likely explanation: nuclear has bad connotations
less likely but more amusing explanation: subjects got nervous when fast-talking doctors suggested an NMR
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History of fMRIMRI-1971: MRI Tumor detection (Damadian)-1973: Lauterbur suggests NMR could be used to form images-1977: clinical MRI scanner patented-1977: Mansfield proposes echo-planar imaging (EPI) to acquire images faster
fMRI-1990: Ogawa observes BOLD effect with T2*
blood vessels became more visible as blood oxygen decreased-1991: Belliveau observes first functional images using a contrast agent-1992: Ogawa et al. and Kwong et al. publish first functional images using BOLD signal
Ogawa
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Necessary Equipment
Magnet Gradient Coil RF Coil
Source: Joe Gati, photos
RF Coil
4T magnet
gradient coil(inside)
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x 80,000 =
4 Tesla = 4 x 10,000 0.5 = 80,000X Earth’s magnetic field
Robarts Research Institute 4T
The Big MagnetVery strong
Continuously on
Source: www.spacedaily.com
1 Tesla (T) = 10,000 Gauss
Earth’s magnetic field = 0.5 Gauss
Main field = B0
B0
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Magnet Safety
The whopping strength of the magnet makes safety essential.Things fly – Even big things!
Screen subjects carefullyMake sure you and all your students & staff are aware of hazzardsDevelop stratetgies for screening yourself every time you enter the magnet
Source: www.howstuffworks.com
Source: http://www.simplyphysics.com/flying_objects.html
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Subject SafetyAnyone going near the magnet – subjects, staff and visitors – must be thoroughly screened:
Subjects must have no metal in their bodies:• pacemaker• aneurysm clips• metal implants (e.g., cochlear implants)• interuterine devices (IUDs)• some dental work (fillings okay)
Subjects must remove metal from their bodies• jewellery, watch, piercings• coins, etc.• wallet• any metal that may distort the field (e.g., underwire bra)
Subjects must be given ear plugs (acoustic noise can reach 120 dB)
This subject was wearing a hair band with a ~2 mm copper clamp. Left: with hair band. Right: without.
Source: Jorge Jovicich
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Protons align with fieldOutside magnetic field
Inside magnetic field
• randomly oriented
• spins tend to align parallel or anti-parallel to B0
• net magnetization (M) along B0
• spins precess with random phase• no net magnetization in transverse plane• only 0.0003% of protons/T align with field
Source: Mark Cohen’s web slides
M
M = 0Source: Robert Cox’s web slides
longitudinalaxis
transverseplane
Longitudinalmagnetization
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fMRI Basics – The functional magnetic resonance imaging technique measures the amount of oxygen in the blood in small regions of the brain. These regions are called voxels. Neural activity uses up oxygen and the vasculature responds by providing more highly oxygenated blood to local brain regions. Thus a change in amount of oxygen in the blood is measured, and this is taken as a proxy for the amount of local neural activity. The measured signal is often called the BOLD signal (Blood Oxygen Level Dependent). Because neural activity is not measured directly, one needs to think about what the indirect signal really tells us, and how it’s spatial and temporal resolution are limited. Certainly, however,the BOLD signal tells us something about localization of neuralactivity in the brain.
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BOLD signal
Source: fMRIB Brief Introduction to fMRI
neural activity blood flow oxyhemoglobin T2* MR signal
Blood Oxygen Level Dependent signal
time
Mxy
SignalMo sin
T2* taskT2* control
TEoptimum
Stask
ScontrolS
Source: Jorge Jovicich
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BOLD signal
Source: Doug Noll’s primer
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3. DATA ANALYSIS
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Hypotheses vs. DataHypothesis-drivenExamples: t-tests, correlations, general linear model (GLM)
• a priori model of activation is suggested• data is checked to see how closely it matches components of the model• most commonly used approach
Data-drivenIndependent Component Analysis (ICA)
• no prior hypotheses are necessary• multivariate techniques determine the patterns in the data that account for the most variance across all voxels• can be used to validate a model (see if the math comes up with the components you would’ve predicted)• can be inspected to see if there are things happening in your data that you didn’t predict• can be used to identify confounds (e.g., head motion)• need a way to organize the many possible components • new and upcoming
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Comparing the two approaches
Source: Tootell et al., 1995
Whole Brain Analysis• Requires no prior hypotheses about areas involved • Includes entire brain • Can lose spatial resolution with intersubject averaging• Can produce meaningless “laundry lists of areas” that are difficult to
interpret • Depends highly on statistics and threshold selected• Popular in Europe
NOTE: Though different experimenters tend to prefer one method over the other, they are NOT mutually exclusive. You can check ROIs you predicted and then check the data for other areas.
Region of Interest (ROI) Analyses• Gives you more statistical power because you do not have to correct for
the number of comparisons • Hypothesis-driven • ROI is not smeared due to intersubject averaging• Easy to analyze and interpret • Neglects other areas which may play a fundamental role • Popular in North America
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Why do we need statistics?MR Signal intensities are arbitrary-vary from magnet to magnet, coil to coil, within a coil (especially surface coil), day to day, even run to run-may also vary from area to area (some areas may be more metabolically active)
We must always have a comparison condition within the same run
We need to know whether the “eyeball tests of significance” are real.
Because we do so many comparisons, we need a way to compensate.
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Two approaches: ROI
Source: Tootell et al., 1995
A. ROI approach
1. Do (a) localizer run(s) to find a region (e.g., show moving rings to find MT)2. Extract time course information from that region in separate independent runs3. See if the trends in that region are statistically significant
Because the runs that are used to generate the area are independent from those used to test the hypothesis, liberal statistics can be used
Localize “motion area” MT in a run comparing moving vs. stationary rings
Extract time courses from MT in subsequent runs while subjects see illusory motion (motion aftereffect)
Example study: Tootell et al, 1995, Motion Aftereffect
MT
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4. LOCALISATION
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BRAIN LOCALIZATION AND ANATOMY
with an emphasis on cortical areas
Why so corticocentric?•cortex forms the bulk of the brain•subcortical structures are hard to image (more vulnerable to motion artifacts) and resolve with fMRI•cortex is relevant to many cognitive processes•neuroanatomy texts typically devote very little information to cortex
Caveats of corticocentrism:•other structures like the cerebellum are undoubtedly very important (contrary to popular belief it not only helps you “walk and chew gum at the same time” but also has many cognitive functions) but unfortunately are poorly understood as yet•need to remember there may be lots of subcortical regions we’re neglecting
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How can we define regions?
1. Talairach coordinates
2. Anatomical localization
3. Functional localization• Region of interest (ROI) analyses
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Talairach Coordinate System
Source: Brain Voyager course slidesNote: That’s TalAIRach, not TAILarach!
Individual brains are different shapes and sizes… How can we compare or average brains?
Talairach & Tournoux, 1988• squish or stretch brain into “shoe box”• extract 3D coordinate (x, y, z) for each activation focus
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Rotate brain into ACPC plane
Find posterior commisure (PC)
Find anterior commisure (AC)
ACPC line= horizontal axis
Corpus Callosum
Fornix
Pineal Body“bent asparagus”
Note: official Tal sez use top of AC and bottom of PC
Source: Duvernoy, 1999
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Squish or stretch brain to fit in “shoebox” of Tal system
Deform brain into Talairach space
yAC=0 y>0y<0
ACPC=0
y>0
y<0
z
x
Extract 3 coordinates
Mark 8 points in the brain:• anterior commisure• posterior commisure• front• back• top• bottom (of temporal lobe)• left• right
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Left is what?!!!
Neurologic (i.e. sensible) convention• left is left, right is right
L R
Radiologic (i.e. stupid) convention• left is right, right is left
R L
Note: Make sure you know what your magnet and software are doing before publishing left/right info!
x = 0-+
x = 0
+-
Note: If you’re really unsure which side is which, tape a vitamin E capsule to the one side of the subject’s head. It will show up on the anatomical image.
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How to TalairachFor each subject:
• Rotate the brain to the ACPC Plane (anatomical)• Deform the brain into the shoebox (anatomical)• Perform the same transformations on the functional data
For the group:Eithera) Average all of the functionals together and perform stats on thatb) Perform the stats on all of the data (GLM) and superimpose the statmaps on an averaged
anatomical (or for SPM, a reference brain)
Averaged anatomical for 6 subjects Averaged functional for 7 subjects
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Talairach Atlas
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Brodmann’s Areas
Brodmann (1905):Based on cytoarchitectonics: study of differences in cortical layers between areasMost common delineation of cortical areasMore recent schemes subdivide Brodmann’s areas into many smaller regionsMonkey and human Brodmann’s areas not necessarily homologous
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Talairach Pros and Cons
Advantages• widespread system• allows averaging of fMRI data between subjects• allows researchers to compare activation foci• easy to use
Disadvantages• based on the squished brain of an elderly alcoholic woman (how representative is that?!)• not appropriate for all brains (e.g., Japanese brains don’t fit well)• activation foci can vary considerably – other landmarks like sulci may be more reliable
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Anatomical LocalizationSulci and Gyri
gray matter (dendrites & synapses)
white matter (axons)
FUNDUS
BA
NK
SU
LC
US
GY
RU
SS
ULC
US
gray
/whi
te b
orde
r
pial
sur
face
FISSURE
Source: Ludwig & Klingler, 1956 in Tamraz & Comair, 2000
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Variability of Sulci
Source: Szikla et al., 1977 in Tamraz & Comair, 2000
Variability of Sulci
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Variability of Functional Areas
Source: Watson et al. 1995
Watson et al., 1995-functional areas (e.g., MT) vary between subjects in their Talairach locations-the location relative to sulci is more consistent
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Cortical Surfacessegment gray-white
matter boundaryinflate cortical surface
sulci = concave = dark graygyri = convex = light gray
render cortical surface
Advantages
• surfaces are topologically more accurate
• alignment across sessions and experiments allows task comparisons
Source: Jody Culham
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Cortical Inflation Movie
Movie: unfoldorig.mpeghttp://cogsci.ucsd.edu/~sereno/unfoldorig.mpg
Source: Marty Sereno’s web page
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Cortical Flattening
Source: Brain Voyager Getting Started Guide
2) make cuts along the medial surface
(Note, one cut typically goes along the fundus of the calcarine sulcus though in this example the cut was placed below)
1) inflate the brain
3) unfold the medial surface so the cortical surface lies flat
4) correct for the distortions so that the true cortical distances are preserved
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Spherical Averaging
Source: Fischl et al., 1999
Future directions of fMRI: Use cortical surface mapping coordinates
Inflate the brain into a sphere
Use sulci and/or functional areas to match subject’s data to template
Cite “latitude” & “longitude” of spherical coordinates
Movie: brain2ellipse.mpeghttp://cogsci.ucsd.edu/~sereno/coord1.mpg
Source: Marty Sereno’s web page
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Spherical Averaging
Source: MIT HST583 online course notes
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5. CORTICAL ANATOMY
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14 Major SulciMain sulci are formed early in developmentFissures are really deep sulci
Typically continuous sulci•Interhemispheric fissure•Sylvian fissure•Parieto-occipital fissure •Collateral sulcus•Central sulcus•Calcarine Sulcus
Typically discontinuous sulci•Superior frontal sulcus•Inferior frontal sulcus•Postcentral sulcus•Intraparietal sulcus•Superior temporal sulcus•Inferior temporal sulcus•Cingulate sulcus•Precentral sulcus
Other minor sulci are much less reliableSource: Ono, 1990
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Interhemispheric Fissure-hugely deep (down to corpus callosum)-divides brain into 2 hemispheres
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Sylvian Fissure-hugely deep-mostly horizontal-insula (purple) is buried within it-separates temporal lobe from parietal and frontal lobes
Sylvian Fissure
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Parieto-occipital Fissure and Calcarine SulcusParieto-occipital fissure (red)-very deep-often Y-shaped from sagittal view, X-shaped in horizontal and coronal views
Calcarine sulcus (blue)-contains V1
Cuneus (pink)-visual areas on medial side above calcarine (lower visual field)
Lingual gyrus (yellow)-visual areas on medial side below calcarine and above collateral sulcus (upper visual field)
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Collateral Sulcus-divides lingual (yellow) and parahippocampal (green) gyri from fusiform gyrus (pink)
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Cingulate Sulcus-divides cingulate gyrus (turquoise) from precuneus (purple) and paracentral lobule (gold)
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Central, Postcentral and Precentral SulciCentral Sulcus (red)-usually freestanding (no intersections)-just anterior to ascending cingulate
Postcentral Sulcus (red)-often in two parts (superior and inferior)-often intersects with intraparietal sulcus-marks posterior end of postcentral gyrus (somatosensory strip, purple)
Precentral Sulcus (red)-often in two parts (superior and inferior)-intersects with superior frontal sulcus (T-junction)-marks anterior end of precentral gyrus (motor strip, yellow)
ascending bandof the cingulate
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Intraparietal Sulcus-anterior end usually intersects with inferior postcentral (some texts call inferior postcentral the ascending intraparietal sulcus)-posterior end usually forms a T-junction with the transverse occipital sulcus (just posterior to the parieto-occipital fissure)-IPS divides the superior parietal lobule from the inferior parietal lobule (angular gyrus, gold, and supramarginal gyrus, lime)
POF
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Slice Views
inverted omega= hand area of motor cortex
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Superior and Inferior Temporal SulciSuperior Temporal Sulcus (red)
-divides superior temporal gyrus (peach) from middle temporal gyrus (lime)
Inferior Temporal Sulcus (blue)-not usually very continuous-divides middle temporal gyrus from inferior temporal gyrus (lavender)
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Superior and Inferior Frontal SulciSuperior Frontal Sulcus (red)-divides superior frontal gyrus (mocha) from middle frontal gyrus (pink)
Inferior Frontal Sulcus (blue)-divides middle frontal gyrus from inferior frontal gyrus (gold)
orbital gyrus (green) and frontal pole (gray) also shown
Frontal Eye fields lie at this junction
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Medial Frontal-superior frontal gyrus continues on medial side-frontal pole (gray) and orbital gyrus (green) also shown