Human Morphometry and Function BIRN Testbeds

1. Human Morphometry and Function BIRN Testbeds Christine Fennema-Notestine, Ph.D. Jessica Turner, Ph.D. CBiO/BIRN Workshop 2006

2. MBIRN/FBIRN “Ontology” Needs • GOAL: User will employ BIRN interface and Mediator to perform scientific queries on data from • structural and functional MRI experiments, • clinical assessments, • psychiatric interviews, • and/or behavioral experiments • BIRN needs for common vocabularies • Mediator needs to talk across databases to find relevant/similar information; this requires linking of concepts to table columns and values • Query interface needs semantic network to find related information • Example queries: • “Find all datasets of schizophrenics with structural and functional imaging data related to working memory” • “Find the correlation between hippocampal volume and working memory performance in AD subjects”

3. MRI Scanner • Structural images, such as T1, PD, T2 • Measures of function, e.g., Blood Oxygenation Level Dependent (BOLD) signal FMRI: • Measures the ratio of oxygenated/deoxygenated hemoglobin in the blood • Neurons fire -> blood flows in -> the ratio changes

4. VOXEL (Volumetric Pixel) Slice Thickness e.g., 6 mm In-plane resolution e.g., 192 mm / 64 = 3 mm 3 mm 6 mm SAGITTAL SLICE IN-PLANE SLICE 3 mm Number of Slices e.g., 10 Matrix Size e.g., 64 x 64 Field of View (FOV) e.g., 19.2 cm Slice Terminology From: http://defiant.ssc.uwo.ca/Jody_web/fmri4dummies.htm

5. Clinical Neuroimaging Problems of mBIRN • To develop the capability to analyze as a single data set MRI and associated data acquired across multiple sites, using tools developed at multiple sites • Examine clinical, demographic, and genetic correlates of human neuroanatomical data • Emphasis on depression, mild cognitive impairment, and AD

6. Imaging Methods Derived data: • Cortical thickness • Volumes of subcortical and cortical gray and white matter • Shape derived metrics • Diffusion metrics of anisotropy

7. Common studies of structural data Hippocampal Volume Loss in Normal Aging Site 5000 A A A A A A A A A UCSD A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A 4000 A A MGH/BWH A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A Left-Hippocampus A A A A A A A A A A A A A A A A A A A A A A A A A A A A WashU A A A A A A A A A A A A A A A A A A 3000 A A A A A A A A A A A A A 2000 60 70 80 90 AGE • Examine the relationship between normal aging and hippocampal volume • Using a combination of volumetric measures and clinical data, predict classification of individuals as healthy controls or individuals with AD

8. MBIRN priorities To relate clinical assessments, cognitive function, and neuroanatomy within mBIRN’s multi-site AD sample, with future branching into neuropsychiatric measures (e.g., fBIRN schizophrenia interviews, etc.). • The common acronym for the "California Verbal Learning Test" (a neuropsychological assessment of learning and memory) "CVLT" needed to be added as a synonym. • More importantly, the CVLT concept only has defined relationships with the concept "Assessment Scales" and links to other assessments scales; no meaningful relationships are between this measure and the concepts for cognitive (memory), anatomical (hippocampus), or disease (AD) terms

9. Existing neuroanatomical ontology Brain Need to create related “function”-based ontology … Cerebellum Cerebrum CVLT Cerebral white matter … Cerebral cortex … Frontal cortex Temporal cortex Memory … Mesial temporal Superior temporal … Amygdala Hippocampus

10. Assessment Brain Neuropsychology Cerebrum Amnesia Cognition Cerebral cortex Frontal Temporal Cognitive impairment Memory Learning Mesial temporal CVLT Hippocampus Task and score description

11. Memory CVLT Recognition Retrieval Recall Free recall Cued Recall Frontal lobe Hippocampus

12. Functional Imaging Methods • T2*-weighted, gradient-echo echo-planar imaging sequence • TE: 40 ms, TR: 3 sec, Flip Angle: 90° • Acquisition matrix: 141 x 64, interpolated to 256 x 256 • Final in-plane pixel size: 0.94 x 0.94 mm2 • Slice thickness: 5 mm • 14-16 axial slices covering the superior half of the cortex • Image acquisitions: 70

13. ROI Time Course fMRI Signal (% change) ~2s Condition Time Condition 1 Statistical Map superimposed on anatomical MRI image Condition 2 ... Region of interest (ROI) ~ 5 min Activation Statistics Functional images Time From http://defiant.ssc.uwo.ca/Jody_web/fmri4newbies.htm

14. Box-car Design: Comparing Active to Rest States Stimulus (3Hz)... Task Tap Tap Tap 30s-R 30s-R 30s-R 30s-R Image

15. Individual Time Courses • Remove linear trends • Scale as a percentage of the baseline

16. Cognitive working memory task (SIRP) 37.8 + .2 at end” 1.5” + .5” = 46”q block 6” Encode 14 probes Prompt 2 blocks @ each WM load 6 blocks = 276” 0 2 1 389 7 2 4 . . . Learn 5t Learn 2.7” each, 1.1 appearance, 1.6 jitter, minimum pre .300, response time for each probe =~1.5s 7 * 5 * 4 3t Learn * * 9 * * 1t 5t 5t 3t 3t DDAs (6sec) 1t 1t fix fix fix fix fix fix fix(14s) 6 + + +… Sample Run…… (total time = 360”, including DDAs) Order of WM blocks randomized Average 12”, minimum 4”, max 20”, multiple of 2’’, randomized total fix time = 78”

17. SIRP Recall Probe Contrasts (N=1) P<.001, uncorrected, ext Green = Set 5 – Set 3 Red = Set 3 – Set 1 Results or “derived data” storage still being standardized. --with fMRI, can analyze a single subject, or groups of subjects

18. Human BIRN data includes • Participant demographics such as age, gender, … • Clinical and psychiatric information • Assessments used, data type • Diagnostic information • Behavioral data during fMRI tasks • Need to know how to interpret that (“is a button 1 response a yes or a no?”) • Raw structural and functional images • Need information about data collection and preprocessing methods • Single-subject and group level analyses and results • Need information about analytic methods used

19. Clinical research questions define structure • Bottom-up: ? When reviewing data, user questions what a given assessment measures and what the score means. • Must include assessment name as a term that will link to clinical data provenance information (task description and score interpretation) • Must provide link to term for assessed function(s) (cognitive, behavioral, psychiatric domain) • Must provide link to potentially related brain regions • User could then simply enter assessment name to find description and related clinical and anatomical terms

20. Top-down: ? User investigates brain-behavior relationships, e.g., between the hippocampus and memory performance • Must include cognitive terms such as: cognitive assessment, memory, recognition, recall • Link terms to existing assessment terms (e.g., CVLT) • Link as appropriate to neuroanatomical ontology (e.g., hippocampus) • User could then search via specific cognitive domain or through “hippocampus” to reach relevant assessments

21. Highly complex assessment example • California Verbal Learning Test (CVLT) • Comprehensive assessment of memory and learning • Widely used, often in head injury including frontal lobe damage, amnesia, dementia (e.g., Alzheimer’s), depression, learning disorders, etc. • Provides numerous measures including: • Recognition discriminability  memory disorders, hippocampus, … • Measurement of retention across time  amnesia, Alzheimer’s, … • Free recall of information  retrieval, frontal lobe, Huntington’s,… • Cued recall of information  memory disorders, Alzheimer’s, … • Response bias  malingering, depression, motivation, … • Serial position effects  short term memory, primacy & recency effects, … • Single trial learning learning disorders, attention, frontal lobe, … • Learning over several trials  retention, frontal lobe, hippocampus, … • Semantic organization  association cortex, superior temporal lobe, … • and more…

22. Bottom-up search: User’s dataset contains the CVLT – what does it measure? • Search for CVLT • Related to PARENT concepts like “Neuropsychological tests” or “Assessment Scales” or SIBLING concepts of other tests • What is the CVLT? This doesn’t answer the user’s question. • Need relationship links to function: memory and learning • Addition of terms covered under memory and learning such as recognition, recall, attention, motivation, serial position effects, episodic memory, semantic memory, … will be related to various subscores of this test • Need relationship links to structure: anatomical regions reflected in change of performance on this measure  hippocampus • Link by subscore and/or by overall measure E.g., CVLT can assess recognition memory, usually linked to hippocampus, but also retrieval of information, often linked to frontal lobe function.

23. Top-down search: User interested in studying the relationship between hippocampal volume and memory performance in Alzheimer’s disease. • Search for measures of memory • Would like to see memory linked to CVLT • Would like to see memory linked to hippocampus at a very basic level • Would like to see links to potential disorders assessed, e.g., amnesia or AD

24. Assessment Brain Neuropsychology Cerebrum Amnesia Cognition Cerebral cortex Frontal Temporal Cognitive impairment Memory Learning Mesial temporal CVLT Hippocampus Task and score description

25. Memory CVLT Recognition Retrieval Recall Free recall Cued Recall Frontal lobe Hippocampus

26. Data gathering from federated databases • “Find all the schizophrenic subjects with fMRI data doing a working memory task.” • This involves • Demographics: Find database tables which contain Age, Gender, Handedness, Diagnosis, etc. • Clinical aspects: What clinical assessments were used to measure schizophrenia symptoms? • Cognitive taxonomies: Which tasks are ‘working memory tasks’? • Scanning parameters: • Type of scan: structural, functional • If structural, what kind of scan: SPGR? Other? • If functional: Transversal of k-space: Linear? Spiral? Other? • And other imaging parameters, e.g.: TR, TE, Number of slices? (whole brain or single-slab?), Slice thickness/gap thickness, Slice acquisition order (interleaved or serial)

27. Taxonomy of fMRI Experiments (from BrainMap)

28. Taxonomy of Experiments

30. Brain Behavioral Paradigm Assessment … Cerebellum Cerebrum SIRP CVLT Cerebral white matter … Cerebral cortex … Frontal cortex Temporal cortex Memory … Mesial temporal Superior temporal … Amygdala Hippocampus

31. Behavioral Paradigm Assessment SCID-Patient SIRP CVLT Breathhold Long Term memory Working memory Memory Attention Cognitive Process Action

32. The issue of multiple identifiers • A cerebellum cannot be a thalamus • But a cognitive task can be • a measure of both working memory and attention (e.g., SIRP) • a measure of both recognition memory and executive retrieval (e.g., CVLT) • and reflected then by more than one anatomical region • Other issues crossing domains: • “memory” is associated with the hippocampus, generically, but is much more complex requiring neural circuits • working memory activation patterns from the SIRP are not found in the hippocampus (and everyone knows that)

34. Ontology Experiences • Derived fMRI data: Mean activations or some such summary data (z-scores, e.g.) for various cortical regions (ROIs) may be stored as a result of single-subject analysis. • That way, the activation in various cortical areas can be summarized and data mining and other techniques then can be applied. • In the short-term, users will probably download the data or analyses and extract the results using their preferred methods. • In the long term, however, that will become infeasible • the databases will have to be made interoperable with standard datamining software. • This is where the neuroanatomy ontologies come in. • We will need to know what the ROI is and which naming scheme it came from (e.g., a Brodmann’s area, or a sulcal/gyral area, etc.). We’ll need to know how it was defined (Talairach atlas? MNI atlas? LONI atlas? Or subject-specific regions?) and what the statistic is.

35. Basic clinical assessment example: • Mini-mental State Examination (MMSE; Folstein et al., 1975 ) • Brief standardized measure of cognitive status • to monitor progression/stabilization in medical setting • to screen research participants • Often used in cognitive disorders and dementia (e.g., Alzheimer’s) or other illnesses; not disease specific • Relatively non-specific relationship to general brain changes • Usually reflected as a single score • Based on brief assessment of orientation, attention, immediate recall, short term recall, language, ability to follow simple verbal commands

36. Bottom-up search: User’s resultant dataset contains the MMSE – the user asks what does it measure? • Search for MMSE concept • Related to PARENT concepts like “Neuropsychological tests” or “Assessment Scales” or SIBLING concepts of other tests • What is the MMSE? This doesn’t answer the user’s question. • Need relationship links to function: general cognitive ability, cognitive impairment, dementia severity, brain damage … • Need relationship links to structure: anatomical regions reflected in change of performance on this measure, although a relatively non-specific measure  brain

37. Top-down search: What variables exist that would provide a measure of general cognitive function and dementia severity? • Search for measures of (general) cognitive function • Would like to see general cognitive ability, cognitive impairment, dementia severity linked to MMSE • Would like to see general cognitive ability, cognitive impairment, dementia severity linked to neuroanatomical regions, simply brain in this case • Would like to see links to potential disorders measured, e.g., AD

38. Assessment Brain Cognition Neuropsychology Cerebrum Cerebral cortex Alzheimer’s Temporal cortex Dementia severity Cognitive impairment Mesial temporal MMSE Hippocampus Task and score description