1/33ISMRM Educational course – 10 th of May 2014 Functional connectivity: Diseases of connectivity...

1/33ISMRM Educational course – 10th of May 2014

Functional connectivity:Diseases of connectivity

Gwenaëlle DouaudFMRIB, University of Oxford

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schizophreniaAlzheimer’sParkinson’schronic paindepression

Diseases of connectivityor disconnection?

• Lesion/degeneration/synaptic malfunction structural connectivity functional connectivity (e.g., Cabral et al., 2012): Abnormal functional connectivity in

• Functional connectivity impairment disconnection syndrome, where “damage to the connection results in deficit that is dinstinct both from damage to the target and source regions” (Kleinschmidt & Vuilleumier, 2013)

Rusconi et al., 2009

Gerstmann syndrome:

acalculia +finger agnosia+left-right

disorientation+agraphia

ISMRM Educational course – 10th of May 2014

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Resting-state fMRI: advantages

• Increased signal-to-noise ratio (Fox & Greicius, Review 2010): - at best, task-related modulation explains 20% of BOLD variance- spontaneous ongoing activity explains 50-80% of BOLD variance


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• Covers the entire repertoire of functional networks used by the brain in “action”(Smith et al., 2009)

RSN: 36 healthy subjects

fMRI: ~7,300 maps, ~30,000 subjects


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• Allows for a broader sampling of patient populations asleep, sedated, too impaired for task-based fMRI scanning, etc.

• Is not confounded by task performance, effort, practice effects, etc.

Greicius et al., 2008


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• “Rest” is a task state in itself, with potential performance differences, rather than differences in the underlying, stable brain organisation (Buckner et al., 2008, 2013)

Might still reveal some meaningful differences, just need careful interpretation

Resting-state fMRI: inconvenients

• “Rest” is a task state in itself, with potential performance differences, rather than differences in the underlying, stable brain organisation (Buckner et al., 2008, 2013)

Might still reveal some meaningful differences, just need careful interpretation

• More susceptible to movement confounds: add motion parameters as covariate use ICA+FIX (automatic denoising using FSL tools: Salimi-Khorshidi et al., 2014, Griffanti et al., 2014)


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• Interpretation:- no causality information (yet) effective functional connectivity- no easy interpretation what (a change in) + and – correlations mean

Resting-state fMRI: inconvenients

Smith et al., 2013


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Resting-state fMRI in disease:reviews

• Mild cognitive impairment/Alzheimer’s disease: - Dennis & Thompson, 2014- Sheline & Raichle, 2013

• Movement disorders (esp. Parkinson’s disease): - Poston & Eidelberg, 2012

• Psychiatric disorders (e.g., schizophrenia, ADHD, autism): - Greicius, 2008- Posner et al., 2014


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Resting-state fMRI analysis:seed-based approach in Parkinson’s disease

• Seed-based approach - a priori knowledge/hypothesisParkinson’s disease: Helmich et al., 2010


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• Very careful study:- negative control with DMN- corrected for motion (higher in patients)- checked for the effect of tremor: no tremor versus tremor spatial map, regressing out muscle activity (electromyography)

• Very careful study:- negative control with DMN

• Very careful study:- negative control with DMN- corrected for motion (higher in patients)- checked for the effect of tremor: no tremor versus tremor spatial map, regressing out muscle activity (electromyography)- checked effect of medication- checked for grey matter volume differences of seeds and whole-brain VBM

• Very careful study:- negative control with DMN- corrected for motion (higher in patients)- checked for the effect of tremor: no tremor versus tremor spatial map, regressing out muscle activity (electromyography)- checked effect of medication


Functional compensation with anterior putamen “taking over” connections to IPC: increased connectivity between IPC and anterior putamen in Parkinson’s was larger for the least-affected side



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• ICA-based approach – more exploratory (though can also be hypothesis-driven)Alzheimer’s disease: Zamboni et al., 2013

Dual regression for group comparisons

Resting-state fMRI analysis:ICA-based approach in Alzheimer’s disease


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Resting-state fMRI less confounds, task fMRI more interpretable: “Increased frontal activity during a memory task overlaps with increased frontal connectivity during rest in AD patients, suggesting that residual cognitive ability can be assessed using resting fMRI.”

• Very careful study:- same number of healthy and AD participants for ICA- negative control with auditory RSN- corrected for GM volume- checked for the effect of physiological fluctuations (respiratory + cardiac activity)



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• Graph theory – exploratory (though mostly no basal ganglia or cerebellum)Schizophrenia: van den Heuvel et al., 2013

Resting-state fMRI analysis:Graph-based approach in schizophrenia


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• Careful study:- includes basal ganglia- used Freesurfer parcellation for ROIs (as opposed to AAL)- replication dataset effects not specific to Rich Club- but: “This study did not reveal a clear association between clinical metrics of patients and rich club organization”

• Careful study:- includes basal ganglia- used Freesurfer parcellation for ROIs (as opposed to AAL)

• Graph theory – exploratory (though mostly no basal ganglia or cerebellum)Schizophrenia: van den Heuvel et al., 2013

“Reduced level of rich club interconnectivity in patients with schizophrenia (…), potentially resulting in decreased global communication capacity and altered functional brain dynamics”

Resting-state fMRI analysis:Graph-based approach in schizophrenia


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• Combining information – diffusion tensor and tractographyAmyotrophic lateral sclerosis: Douaud, Filippini et al., 2011

Resting-state fMRI analysis:Multi-modal approach in motor neuron disease

Increase FC in ALS


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Disease duration



• Careful registration (BBR + VBM)

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• Reconciling lower structural connectivity (SC) with higher functional connectivity?


Higher functional connectivity not necessarily better

Innocenti, 2009

corpuscallosum

GABAergicinterneurons



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Low SC + high FC in ALS = loss of GABA interneurons

- GABA+ FC



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• Combining information – grey matter volume/structural covarianceArray of neurodegenerative disorders: Seeley et al., 2009

Resting-state fMRI analysis:Multi-modal approach in neurodegenerative diseases


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• Combining information – grey matter volume/structural covarianceArray of neurodegenerative disorders: Seeley et al., 2009

Resting-state fMRI analysis:Multi-modal approach in neurodegenerative diseases

Dissociable networks for each disease


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Variability of results in fcMRI

Fox & Greicius, 2010


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Variability of results in fcMRI: some guidelines


Parkinson’s: Seeds in the striatum

DMN as negative control

Alzheimer’s: RSN (ICA) involving frontal areasauditory RSN as negative control


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+ careful registration

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+ careful registration

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Variability of results in fcMRI: movement

Power et al., 2012

“Scrub” the data, add motion parameters, or use ICA+FIX


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Variability of results in fcMRI: movement

“Scrub” the data, add motion parameters, or use ICA+FIX

Salimi-Khorshidi et al., 2014


Griffanti et al., 2014

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Global signal regression, # of ICs etc.


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Variability of results in fcMRI: stability of networks

• Inter-subject variability is higher in higher-order regions (Mueller et al., 2013)


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Interpretation of functional connectivity results

• Higher not necessarily better

• Always check for each contrast what happens in each cluster

• Some RSN are more stable than others

Absolute values of correlations matter


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• Higher not necessarily better

• Some RSN are more stable than others

• Bear in mind that change in correlations can be observed even in the absence of a change in coupling (Friston, 2011)

Changes in correlation between A and B could be caused by a change in correlation elsewhere

• Always check for each contrast what happens in each cluster

It’s the absolute values of correlations that matter

Changes in correlation could be caused by a change in SNR (e.g., heart rate variability differs between two populations)

Changes in correlation could be caused by a change in the amplitude of the fluctuations

• Bear in mind that “resting” is to some extent also a task

Interpretation of functional connectivity results


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FMRIB, University of Oxford

- Steve Smith- Eugene Duff- Christian Beckmann- Reza Salimi-Khorshidi- Martin Turner- Giovanna Zamboni- Nicola Filippini- Marina Charquero Ballester

THANK YOUFOR YOUR ATTENTION

Special thanks to:


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1/33ISMRM Educational course – 10 th of May 2014 Functional connectivity: Diseases of connectivity...

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