Localization & Normalization fMRI: Theory and Practice Spring 2010

Brain Localization and Anatomy - with 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

How can we define regions? Talairach coordinates Anatomical localization Functional localization Region of interest (ROI) analyses already covered in Design lectures so will not be reconsidered here

Talairach Coordinate System 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 Note: That’s TalAIRach, not TAILarach! Source: Brain Voyager course slides

Rotate brain into ACPC plane Find anterior commisure (AC) Corpus Callosum Fornix Find posterior commisure (PC) ACPC line = horizontal axis Pineal Body “bent asparagus” Note: official Tal sez use top of AC and bottom of PC Source: Duvernoy, 1999

Deform brain into Talairach space Mark 8 points in the brain: anterior commisure posterior commisure front back top bottom (of temporal lobe) left right Squish or stretch brain to fit in “shoebox” of Tal system ACPC=0 y>0 y<0 z y AC=0 y>0 y<0 x Extract 3 coordinates

Left is what?!!! L R R L Neurologic (i.e. sensible) convention left is left, right is right L R x = 0 - + Note: Make sure you know what your magnet and software are doing before publishing left/right info! Radiologic (i.e. stupid) convention left is right, right is left R L 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.

How to Talairach For each subject: For the group: 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: Either Average all of the functionals together and perform stats on that 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

Talairach Atlas

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

MNI Space There are several reasons the Talairach brain is suboptimal (the brain was from an alcoholic older woman and became somewhat deformed sitting around) Researchers at the Montreal Neurological Institute created a better template based on a morphed average of hundreds of brains (not just one brain like Talairach) The MNI brain is more representative of average brain shape; however, it does not provide Brodmann areas The MNI alignment is more complex than Talairach: SPM uses it but many software packages still use Talairach CAVEAT: The MNI and Talairach coordinate are similar but not identical -- careful comparison requires a transformation Source: http://www.mrc-cbu.cam.ac.uk/personal/matthew.brett/abstracts/MNITal/mniposter.pdf

Brodmann’s Areas Brodmann (1905): Based on cytoarchitectonics: study of differences in cortical layers between areas Most common delineation of cortical areas More recent schemes subdivide Brodmann’s areas into many smaller regions Monkey and human Brodmann’s areas not necessarily homologous

Anatomical Localization Sulci and Gyri gray matter (dendrites & synapses) white matter (axons) FUNDUS BANK GYRUS SULCUS pial surface gray/white border SULCUS FISSURE GYRUS Source: Ludwig & Klingler, 1956 in Tamraz & Comair, 2000

Variability of Sulci Source: Szikla et al., 1977 in Tamraz & Comair, 2000

Variability of Functional Areas Watson et al., 1995 -functional areas (e.g., MT) vary between subjects in their Talairach locations -the location relative to sulci is more consistent Source: Watson et al. 1995

Cortical Surfaces Advantages surfaces are topologically more accurate segment gray-white matter boundary render cortical surface inflate cortical surface sulci = concave = dark gray gyri = convex = light gray Advantages surfaces are topologically more accurate alignment across sessions and experiments allows task comparisons Source: Jody Culham

Cortical Flattening 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 4) correct for the distortions so that the true cortical distances are preseved 3) unfold the medial surface so the cortical surface lies flat Source: Brain Voyager Getting Started Guide

Spherical Averaging 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.mpeg http://cogsci.ucsd.edu/~sereno/coord1.mpg Source: Marty Sereno’s web page Source: Fischl et al., 1999

How can we define regions? Talairach coordinates Example: The FFA is at x = 40, y = -55, z = -10 Anatomical localization Example: The FFA is in the right fusiform gyrus at the level of the occipitotemporal junction Functional localization Example: The FFA includes all voxels around the fusiform gyrus that are activated by the comparison between faces and objects Kanwisher, McDermott & Chun, 1997, J Neurosci