Form follows func-on. Which one of them can fly? And why? Why would anyone bother about brain structure, when we can do func5onal imaging?

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2 Why would anyone bother about brain structure, when we can do func5onal imaging? Form follows func-on Which one of them can fly? And why? h;p://animals.na5onalgeographic.com

3 Why would anyone bother about brain structure, when we can do func5onal imaging? h;p://orthoinfo.aaos.org Similarly: Func5on follows form Imaging can help assess differences and track changes

4 The brain: Fixed or ever- changing? Aplysia Brain Plas-city: Kempermann (1997), Nature The brain s ability to adapt in structure and func5on to external demands. From Brooks, online publication (

5 The ever adap5ng brain Brain Plas-city: Func5onal demand Stronger connec5on: - synap5c increase - glial increase - neurogenesis Func5onal demand [ ] [ ] Pruning: - synap5c decrease - glial decrease - neural pruning Func5onal demand [ ] [ ]

6 Example (brain plas5city in taxi drivers) Taxi drivers in London - serve ~ 30,000 streets - are trained for several years - need to pass difficult test Compare licensed London Taxi drivers to controls Are there significant differences in brain structure?

7 Example (brain plas5city in taxi drivers) Correla5on between 5me as taxi driver and hippocampal size Taxi drivers > controls Maguire et al. (2000), PNAS

8 Morphometric Analyses - Differences in brain structure between groups - Correla5ons of brain structure with variables of interest - Sta5s5cal analysis is like group analysis in fmri ( so we already know a lot about it)

9 Morphometry methods: what can we measure? White ma;er volume Grey ma;er volume Cor5cal thickness Bias correc5on Vertex Curvature Segmenta5on ROI Callosal thickness Radial distance Voxel- based morphometry Template Total intracranial volume Mesh Modula5on CSF Tensor- based morphometry Deforma5ons Jacobian determinant Gray ma;er density Whole- brain volume

10 Morphometry methods: what can we measure? Volumes: Region of Interest (ROI) Whole- brain volume Local volume (VBM / TBM) Distances: Callosal thickness Cor5cal thickness Radial distance Shapes: Curvature

11 Morphometry methods: what can we measure? Volumes: Region of Interest (ROI) Whole- brain volume Local volume (VBM / TBM) Distances: Callosal thickness Cor5cal thickness Radial distance Shapes: Curvature

12 Volumes

13 Morphometry methods: what can we measure? Volumes: Region of Interest (ROI) Whole- brain volume Local volume (VBM / TBM) Distances: Callosal thickness Cor5cal thickness Radial distance Shapes: Curvature

14 Volume ROI analysis ROIs: - Allow a direct comparison of a region s metrics - Are extremely specific at least in theory - Manual or automated genera5on Freesurfer Tutorial Quality of result depends on quality of ROI Manual tracing: - Requires extremely detailed rules - Time consuming h;p:// - S5ll considered to be a gold standard

15 ROIs Benefits: - Focus on structure you are interested in - Measurement of different a;ributes (size, shape, length, volume ) Rendering of right hippocampus (lateral view)

16 ROIs PiJalls: - Misclassifica5on - Missing rules and unclear / incomplete protocols - Func5onal relevance Kurth et al. (2010), Brain Structure and Func5on Kurth et al. (2010), Cerebral Cortex Brodmann K (1909). Vergleichende Lokalisa5on der Grosshirnrinde

17 Morphometry methods: what can we measure? Volumes: Region of Interest (ROI) Whole- brain volume Local volume (VBM / TBM) Distances: Callosal thickness Cor5cal thickness Radial distance Shapes: Curvature

18 Whole- brain volume Whole brain volume: - Global measurement Differences / changes can be observed in: - Neurodevelopment - Sex differences - Normal ageing - Neurodegenera5ve diseases - Different psychiatric disorders - [ ]

19 Whole- brain volume? Why does that maler? - Hippocampal volume scales with total brain volume Assume hippocampal volume loss in Alzheimer s: A big brain may have decreased hippocampal volume However, compared to smaller brains, the absolute hippocampal volume would s5ll be in the normal range

20 Whole- brain volume Whole- brain volume: - Frequently approximated by calcula5ng the total intracranial volume (TIV) - TIV can be calculated as GM+WM+CSF used to covary for different brain sizes

21 Morphometry methods: what can we measure? Volumes: Region of Interest (ROI) Whole- brain volume Local volume (VBM / TBM) Distances: Callosal thickness Cor5cal thickness Radial distance Shapes: Curvature

22 Local volume - Where in the brain is the difference? - Is this specific to a certain 5ssue type? Voxelwise comparison

23 Local volume Voxelwise comparisons: - Not limited to a predefined structure - High spa5al resolu5on Kurth et al. (2012), Human Brain Mapping We need to - Segment our brain into GM, WM, and CSF - Get the segments into a common space

24 Tissue segmenta5on Frequency Background CSF Gray Matter White Matter Brightness Tissue segmenta5on works on brightness informa5on in the image

25 Tissue segmenta5on

26 Morphometry methods: Local volume Kurth et al. (2012), Human Brain Mapping Voxelwise comparisons: - We now have successfully segmented the brains - Get segments into common space?

27 Spa5al transforma5on II Linear (same for every voxel): - rigid body: 6 parameter (3 x transla5on and 3 x rota5on) - affine: 12 parameter (rigid body + 3 x scaling + 3 x shearing) Na5ve space GM segments Affine registered GM segments

28 Spa5al transforma5on II Linear (same for every voxel): - rigid body: 6 parameter (3 x transla5on and 3 x rota5on) - affine: 12 parameter (rigid body + 3 x scaling + 3 x shearing) Non- linear (different for every voxel): Source Target Deforma5on Field From: Ashburner and Friston (2007), In: Sta5s5cal Parametric Mapping. The Methods

29 Spa5al transforma5on II What if spa5al registra5on is not 100% exact? - Spa5al uncertainty remains - This introduces noise (less sensi5ve) - Smoothing can account for small spa5al uncertain5es - Smoothing is required for sta5s5cal analysis anyway Smoothed voxel

30 VBM na5ve affine + non- linear + smoothed Voxel- based Morphometry (VBM) - The smoothed image is the input for classic VBM analyses Gray Ma;er Concentra5on or Gray Ma;er Density

31 Morphometry methods: Local volume Example: Does learning / training to juggle change brain structure? 12 subjects: - Learning and training for 3 months - Then no training for 3 months 12 Controls: - No juggling - Segment brains - Warp GM segments to MNI space (linearly + non- linearly) - Check if preprocessing worked - Smooth the warped segments - Enter them in a sta5s5cal model Grey ma;er increase in hmt / V5 Draganski et al. (2004), Nature Tissue increases with training, decreases in absence of training

32 Morphometry methods: Local volume How to interpret differences? Folding Thickness Misclassifica5on Quality Control Misregistra5on Less GM More GM From: Ashburner and Friston (2007), In: Sta5s5cal Parametric Mapping. The Methods

33 Morphometry methods: Volume changes Mapping local deforma5ons encodes volume and shape differences ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( x p h x p h x p h x p h x p h x p h x p h x p h x p h p J = Jacobian Determinant

34 Morphometry methods: Volume changes Voxel volume increased to match template Voxel volume decreased to match template

35 Morphometry methods: TBM Alzheimer s Hua et al. (2008) Neuroimage Fragile X Lee et al. (2007) Neuroimage FTO gene Ho et al. (2010) PNAS

36 Preserving the volume -ssue- specific - Tissue segments render rela5ve volume - Jacobians encode volume changes Morphometry methods: VBM Mul5ply segments with volume change modula5on Voxel- based Morphometry (VBM) (part 2) - Warped Tissues are modulated with their Jacobians - Frequently described as Gray Ma;er Volume (Volume is preserved)

37 Morphometry methods: what can we measure? Volumes: Region of Interest (ROI) Whole- brain volume Local volume (VBM / TBM) Distances: Callosal thickness Cor5cal thickness Radial distance Shapes: Curvature

38 Distances

39 Distance A B A B A B Resolu5on Distance between any two points - in any dimension Distance between two lines - length of lines does not ma;er Callosal Thickness

40 Morphometry methods: what can we measure? Volumes: Region of Interest (ROI) Whole- brain volume Local volume (VBM / TBM) Distances: Callosal thickness Cor5cal thickness Radial distance Shapes: Curvature

41 Cor5cal Thickness Thompson et al. (2005) J.Neurosci. Distance between WM / GM boundary and pial surface

42 Vertex Cor5cal Thickness

43 Cor5cal Thickness White Ma;er Surface Pial Surface Freesurfer Tutorial 2010 Ver5ces

44 Cor5cal Thickness How to interpret differences? Folding Thickness Misclassifica5on Quality Control Misregistra5on Thinner Cortex Thicker Cortex Modified awer: Ashburner and Friston (2007), In: Sta5s5cal Parametric Mapping. The Methods

45 Morphometry methods: what can we measure? Volumes: Region of Interest (ROI) Whole- brain volume Local volume (VBM / TBM) Distances: Callosal thickness Cor5cal thickness Radial distance Shapes: Curvature

46 Radial Thickness x Measure distance from core Hippocampus: shape with core

47 Morphometry methods: what can we measure? Volumes: Region of Interest (ROI) Whole- brain volume Local volume (VBM / TBM) Distances: Callosal thickness Cor5cal thickness Radial distance Shapes: Curvature

48 Shape

49 Gyrifica5on Gyrifica-on Index = Inner Contour Length (following the sulci / gyri) Outer Countour Length (connec5ng the tops of the gyri) Zilles et al. (1988), Anat Embryol (Berl) Fractal Dimension The rate at which the measured contour increases as the spa5al detail is increased. Thompson et al. (1996), J Neurosci

50 Curvature Mean Curvature Gaser C

51 Summary White ma;er volume Grey ma;er volume Cor5cal thickness Bias correc5on Vertex Curvature Segmenta5on ROI Callosal thickness Radial distance Voxel- based morphometry Template Total intracranial volume Mesh Modula5on CSF Tensor- based morphometry Deforma5ons Jacobian determinant Gray ma;er density Whole- brain volume

52 Thank you Eileen Luders Chris5an Gaser Katherine Narr Paul Thompson