All Hands Meeting 2005

Human Morphometry and Function BIRN Testbeds

Christine Fennema-Notestine, Ph.D.

Jessica Turner, Ph.D.

CBiO/BIRN Workshop 2006

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”

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

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 mm6 mm

Slice Terminology

Matrix Sizee.g., 64 x 64

In-plane resolutione.g., 192 mm / 64

= 3 mm

From: http://defiant.ssc.uwo.ca/Jody_web/fmri4dummies.htm

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

Normal Elderly Control Alzheimer’s IndividualNormal Elderly Control Alzheimer’s Individual

Imaging Methods Derived data:

• Cortical thickness• Volumes of subcortical and

cortical gray and white matter• Shape derived metrics • Diffusion metrics of anisotropy

Bayesian segmentation using Gibbs priors. Temporal Lobe Left: coronal, right: sagittal.

Ventricle Thalamus Pallidum

Putamen

Cortical WM Amygdala

Hippocampus

Cortical GM

Cerebellar GM

Cerebellar WM

Common studies of structural data

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

UCSDMGH/BWHWashU

Site

60 70 80 90

AGE

2000

3000

4000

5000

Lef

t-H

ipp

oca

mp

us

Hippocampal Volume Loss in Normal Aging

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

Existing neuroanatomical ontology

Need to create related “function”-based ontology

Brain

Cerebellum Cerebrum

Cerebral white matter …

Frontal cortex Temporal cortex

Superior temporal Mesial temporal

Amygdala Hippocampus

…

Cerebral cortex

…

…

…

Memory

CVLT

Brain

Cerebrum

Temporal

Mesial temporal

Hippocampus

Cerebral cortex

CVLT

Task and score description

Frontal Cognitiveimpairment

Cognition

Assessment

Neuropsychology

Amnesia

Memory Learning

Memory

Recognition

Recall

Free recall Cued Recall

CVLT

Retrieval

Hippocampus Frontal lobe

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

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)

From http://defiant.ssc.uwo.ca/Jody_web/fmri4newbies.htm

30s-R30s-R30s-R30s-R Tap Tap TapTask

Image

Box-car Design: Comparing Active to Rest States

Stimulus (3Hz)...

Individual Time Courses

• Remove linear trends

• Scale as a percentage of the baseline

Learn

3t

1t

5t

3t

5t

1t

Encode 14 probes

37.8 + .2 at end”

Sample Run……(total time = 360”, including DDAs)Order of WM blocks randomized

0 2 1 3 8 9 7 2 4 . . .

7 * 5 * 4

* * 9 * *

Prompt

1.5” + .5”

Learn5t

3t

1t

+ + +…

Learn

fixfixfix fix fix

6”

2.7” each, 1.1 appearance, 1.6 jitter,minimum pre .300,response time for each probe =~1.5s

Average 12”, minimum 4”, max 20”,multiple of 2’’, randomized

total fix time = 78”

= 46”q block

2 blocks @ each WM load6 blocks = 276”

DDAs (6sec)

fix(14s)fix6

Cognitive working memory task (SIRP)

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

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

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

Clinical research questions define structure

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

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…

Highly complex assessment example

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.

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

Brain

Cerebrum

Temporal

Mesial temporal

Hippocampus

Cerebral cortex

CVLT

Task and score description

Frontal Cognitiveimpairment

Cognition

Assessment

Neuropsychology

Amnesia

Memory Learning

Memory

Recognition

Recall

Free recall Cued Recall

CVLT

Retrieval

Hippocampus Frontal lobe

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)

Taxonomy of fMRI Experiments (from BrainMap)

Taxonomy of Experiments

Brain

Cerebellum Cerebrum

Cerebral white matter …

Frontal cortex Temporal cortex

Superior temporal Mesial temporal

Amygdala Hippocampus

…

Cerebral cortex

…

…

…

Memory

CVLT SIRP

Assessment

Behavioral Paradigm

Memory

CVLT SIRP

Assessment

Behavioral Paradigm

Cognitive Process

Attention

Working memory Long Term memory

SCID-Patient

Breathhold

Action

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)

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.

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

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

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

Brain

Cerebrum

Temporal cortex

Mesial temporal

Hippocampus

Cerebral cortex

MMSE

Cognitiveimpairment

Dementiaseverity

Cognition

Assessment

Neuropsychology

Alzheimer’s

Task and score description