1/33ISMRM Educational course – 10 th of May 2014 Functional connectivity: Diseases of connectivity Gwenaëlle Douaud FMRIB, University of Oxford.

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1/33ISMRM Educational course – 10 th of May 2014 Functional connectivity: Diseases of connectivity Gwenaëlle Douaud FMRIB, University of Oxford

2/33 schizophreniaAlzheimer’sParkinson’schronic paindepression Diseases of connectivity or 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 – 10 th of May 2014

3/33 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 ISMRM Educational course – 10 th of May 2014

4/33 Resting-state fMRI: advantages Covers the entire repertoire of functional networks used by the brain in “action” (Smith et al., 2009) RSN: 36 healthy subjectsfMRI: ~7,300 maps, ~30,000 subjects ISMRM Educational course – 10 th of May 2014

5/33 Resting-state fMRI: advantages 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 ISMRM Educational course – 10 th of May 2014

6/33 “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) ISMRM Educational course – 10 th of May 2014

7/33 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 ISMRM Educational course – 10 th of May 2014

8/33 Resting-state fMRI in disease: reviews Mild cognitive impairment/Alzheimer’s disease: - Dennis & Thompson, Sheline & Raichle, 2013 Movement disorders (esp. Parkinson’s disease): - Poston & Eidelberg, 2012 Psychiatric disorders (e.g., schizophrenia, ADHD, autism): - Greicius, Posner et al., 2014 ISMRM Educational course – 10 th of May 2014

9/33 Resting-state fMRI analysis: seed-based approach in Parkinson’s disease Seed-based approach - a priori knowledge/hypothesis Parkinson’s disease: Helmich et al., 2010 ISMRM Educational course – 10 th of May 2014

10/33 Seed-based approach - a priori knowledge/hypothesis Parkinson’s disease: Helmich et al., 2010 Resting-state fMRI analysis: seed-based approach in Parkinson’s disease ISMRM Educational course – 10 th of May 2014

11/33 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 Seed-based approach - a priori knowledge/hypothesis Parkinson’s disease: Helmich et al., 2010  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 Resting-state fMRI analysis: seed-based approach in Parkinson’s disease ISMRM Educational course – 10 th of May 2014

12/33 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 ISMRM Educational course – 10 th of May 2014

13/33 ICA-based approach – more exploratory (though can also be hypothesis-driven) Alzheimer’s disease: Zamboni et al., 2013 Resting-state fMRI analysis: ICA-based approach in Alzheimer’s disease ISMRM Educational course – 10 th of May 2014

14/33 ICA-based approach – more exploratory (though can also be hypothesis-driven) Alzheimer’s disease: Zamboni et al., 2013  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) Resting-state fMRI analysis: ICA-based approach in Alzheimer’s disease ISMRM Educational course – 10 th of May 2014

15/33 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 ISMRM Educational course – 10 th of May 2014

16/33 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 ISMRM Educational course – 10 th of May 2014

17/33 Combining information – diffusion tensor and tractography Amyotrophic lateral sclerosis: Douaud, Filippini et al., 2011 Resting-state fMRI analysis: Multi-modal approach in motor neuron disease Increase FC in ALS ISMRM Educational course – 10 th of May 2014

18/33 Combining information – diffusion tensor and tractography Amyotrophic lateral sclerosis: Douaud, Filippini et al., 2011 Disease duration Resting-state fMRI analysis: Multi-modal approach in motor neuron disease ISMRM Educational course – 10 th of May 2014 Careful registration (BBR + VBM)

19/33 Reconciling lower structural connectivity (SC) with higher functional connectivity? Combining information – diffusion tensor and tractography Amyotrophic lateral sclerosis: Douaud, Filippini et al., 2011  Higher functional connectivity not necessarily better Innocenti, 2009 corpus callosum GABAergic interneurons Resting-state fMRI analysis: Multi-modal approach in motor neuron disease ISMRM Educational course – 10 th of May 2014

20/33 Combining information – diffusion tensor and tractography Amyotrophic lateral sclerosis: Douaud, Filippini et al., 2011  Low SC + high FC in ALS = loss of GABA interneurons - GABA+ FC Resting-state fMRI analysis: Multi-modal approach in motor neuron disease ISMRM Educational course – 10 th of May 2014

21/33 Combining information – grey matter volume/structural covariance Array of neurodegenerative disorders: Seeley et al., 2009 Resting-state fMRI analysis: Multi-modal approach in neurodegenerative diseases ISMRM Educational course – 10 th of May 2014

22/33 Combining information – grey matter volume/structural covariance Array of neurodegenerative disorders: Seeley et al., 2009 Resting-state fMRI analysis: Multi-modal approach in neurodegenerative diseases  Dissociable networks for each disease ISMRM Educational course – 10 th of May 2014

23/33 Variability of results in fcMRI Fox & Greicius, 2010 ISMRM Educational course – 10 th of May 2014

24/33 Variability of results in fcMRI: some guidelines Fox & Greicius, 2010 Parkinson’s: Seeds in the striatum DMN as negative control Alzheimer’s: RSN (ICA) involving frontal areas auditory RSN as negative control ISMRM Educational course – 10 th of May 2014

25/33 Variability of results in fcMRI: some guidelines Fox & Greicius, 2010 ISMRM Educational course – 10 th of May careful registration

26/33 Variability of results in fcMRI: some guidelines Fox & Greicius, 2010 ISMRM Educational course – 10 th of May careful registration

27/33 Variability of results in fcMRI: movement Power et al., 2012  “Scrub” the data, add motion parameters, or use ICA+FIX ISMRM Educational course – 10 th of May 2014

28/33 Variability of results in fcMRI: movement  “Scrub” the data, add motion parameters, or use ICA+FIX Salimi-Khorshidi et al., 2014 ISMRM Educational course – 10 th of May 2014 Griffanti et al., 2014

29/33 Variability of results in fcMRI: some guidelines Fox & Greicius, 2010  Global signal regression, # of ICs etc. ISMRM Educational course – 10 th of May 2014

30/33 Variability of results in fcMRI: some guidelines Fox & Greicius, 2010 ISMRM Educational course – 10 th of May 2014

31/33 Variability of results in fcMRI: stability of networks Inter-subject variability is higher in higher-order regions (Mueller et al., 2013) ISMRM Educational course – 10 th of May 2014

32/33 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 ISMRM Educational course – 10 th of May 2014

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

34/33 FMRIB, University of Oxford - Steve Smith - Eugene Duff - Christian Beckmann - Reza Salimi-Khorshidi - Martin Turner - Giovanna Zamboni - Nicola Filippini - Marina Charquero Ballester THANK YOU FOR YOUR ATTENTION Special thanks to: ISMRM Educational course – 10 th of May 2014