4/25/2014. Real-time fmri. Real-time fmri Methods. What is special about real-time fmri? ... data analysis keeps up with image acquisition!

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1 Non-invasive imaging technique : Methods and applications Functional MRI PET Magnetic Resonance Imaging (MRI) Structural MRI Perfusion MRI Diffusion MRI NIRS EEG MEG MR angiography Frank Scharnowski Real-time fmri First described in 1995 (Cox, Magnetic Resonance Imaging)... faster algorithms... faster computers... better image quality First real implementation in 2003 (Weiskopf, NeuroImage)... data analysis kept up with data acquisition! Conventional fmri analysis fmri image acquisition 1-3 seconds Has to keep up with... Real-time fmri data analysis hours, days, weeks, seconds 3 hours 2 seconds Real-time fmri Methods signal (image) quality artefact control online statistical analysis data acquisition magnetic field strength image resolution (spatial & temporal) image reconstruction head motion instruct to not move the head padding the head robust and fast rigidbody motion correction magnetic field inhomogeneities focus on areas which do not exhibit strong susceptibility effects Respiration instruct to breath regularly monitor breathing during the experiment GLM, pattern recognition,... sliding window cumulative What is special about real-time fmri?... data analysis keeps up with image acquisition! How is real-time fmri accomplished?... Fast image acquisition!... Robust artefact control!... Purpose-made statistical analysis algorithms! 1

2 We have got the tools What can they be used for? Intra-operative real-time (f)mri The usefulness of pre-operative structural MRI is well established (e.g. planning tumor resection, navigating during the operation). BUT: During the operation, brain tissue shifts in position (due to craniotomy & tissue resection). Intra-operative real-time (f)mri The usefulness of pre-operative structural MRI is well established (e.g. planning tumor resection, navigating during the operation). BUT: During the operation, brain tissue shifts in position (due to craniotomy & tissue resection). Intra-operative structural MRI allows to guide surgery while taking shifts in tissue position into account. 2

3 Intra-operative real-time fmri BUT: functional brain networks can change (acute plasticity due to tissue resection). Intra-operative real-time fmri allows to track functional changes and thereby to avoid resection of functionally relevant areas. for Teaching. allows to cover all essential parts of an fmri experiment with a relatively short hands-on course,... immediately observe the effects of experimental design, hemodynamic delay, head motion artifacts, specific pulse sequences, and different statistical analysis, provide a coherent picture of all the different parts of an fmri experiment. Quality Assurance System allows to... for Quality Assurance. Continuously updated display of the current images. High-intensitiy (4x) windowing to make ghosting visible.... monitor the progress of an fmri experiment,... detect problems as early as possible,... increase reliability and facilitate troubleshooting. Example: Real-time quality assurance system at the Wellome Trust Centre for Neuroimaging (developed by Bob Turner, Nik Weiskopf, Oliver Josephs, Chloe Hutton)... Difference image: current previous image. Time course plot of the variance for the whole volume. Time series of RF noise for each slice (spikes). Time [vols] Mean signal variance over the previous 10 images (sliding window variance map). 3

4 Quality Assurance System RF spike artifact due to malfunction of stimulus equipment: Spikes not visible in the images. Instability! Head Motion? Technical Problem? RF noise plot indicates two spikes seen as high-intensity peaks in autoscaled plot (lower-level RF noise is suppressed). Reveals artifacts and their location due to head motion, cardiorespiratory activity, and scanner instability. Brain-Computer-Interface Invasive Brain-Computer-Interface Non-muscular channel for sending messages and commands to the external world. Measure brain activity, process the brain signal, and translate it into a control command. Hochberg, 2006, Nature. Non-invasive Brain-Computer-Interface: EEG Controlling a wheel chair. Non-invasive Brain-Computer-Interface: EEG Letter spelling. Modulate EEG-activity select letters on a computer screen Time-consuming language support programme Excessive training necessary positive reinforcement Birbaumer, 1999, Nature. 4

5 Non-invasive Brain-Computer-Interface: EEG Non-invasive Brain-Computer-Interface: fmri Letter spelling. Limitations of BCIs based on EEG: low spatial resolution no whole brain coverage excessive training necessary Advantages of fmri: high spatial resolution (target specific areas) deep brain structures accessible easy to learn...! Non-invasive Brain-Computer-Interface: fmri Non-invasive Brain-Computer-Interface: fmri Spatial navigation by thought. Yoo, 2004, Neuroreport. Non-invasive Brain-Computer-Interface: fmri How to increase the information transfer? 4 choices every few seconds... Non-invasive Brain-Computer-Interface: fmri How to increase the information transfer: spatial-temporal pattern! 2 patterns X 2 times 4 choices Presentation rate. Information transfer per presentation. More choices? Classification accuracy drops! Sorger, 2009, Progress in Brain Research. 5

6 Non-invasive Brain-Computer-Interface: fmri How to increase the information transfer: spatial-temporal pattern! Non-invasive Brain-Computer-Interface: fmri Why to use BCIs based on fmri at all? fmri-bcis are slower than EEG-based BCIs. fmri-bcis are very expensive. fmri-bcis are not portable. motor imagery ROI mental calculation ROI Sorger, 2009, Progress in Brain Research. > 95% accuracy! Owen, 2006, Science. Vegetative state patients might be able to communicate with fmri-based BCIs, i.e. they might benefit from the ease of learning to control a real-time fmri-based BCI. Applications Applications What are the applications of real-time fmri?... Intra-operative real-time fmri to guide surgery... Quality assurance to improve the reliability of conventional fmri experiments.... Interactive teaching.... Brain-Computer-Interfaces.... to learn voluntary control over brain activity. Why is intra-operative real-time fmri necessary?... During the surgery, brain tissue shifts in position.... Functional brain networks can change during surgery due to acute plasticity. What are the pros & cons of a real-time fmri BCI?... Easy to learn.... Multiple focal brain areas can be targeted simultaneously (including deep brain areas).... Slow information transfer rate.... Expensive and not portable.... No direct measure of neural activity. 6

7 ... causality correlational techniques EEG fmri MEG Voluntary control over brain activity. brain activity... causes manipulate... perception / behaviour. measure How does voluntary control over brain activity affect perception or behaviour? causal techniques TMS lesions pharmacology neurofeedback Brain activity as the independent variable! (Brain activity dependent on behaviour) -1 manipulate brain activity... causes measure... perception / behaviour. general setup and data flow. Real-time analysis software: Turbo-BrainVoyager Experimental Paradigm ROI time courses Statistical Maps Motion Correction target areas so far. 7

8 target areas so far. Spontaneous activity in the visual cortex at rest: Even in the absence of external stimulation, fluctuations in spontaneous brain activity predict whether or not a stimulus will be perceived. (Fox & Raichle, 2007; Hesselmann et al., 2008; Ress et al., 2000) X Study Objectives: Hypothesis: Train participants to explicitly clamp visual cortex activity at high or low levels using neurofeedback. When the level of ongoing activity in early visual cortex is increased, participants will become better at detecting a visual stimulus. How is learning mediated?... Why do some learn and others fail? Visual ROI Cognitive strategies... Behavior follows BOLD. Self-regulation and improved perception were spatially specific. 8

9 How is learning mediated?... Why do some learn and others fail? Psychological factors... How is learning mediated?... Why do some learn and others fail? Peripheral-physiological factors... Attention Rating: Visual Imagery Rating: Heart Rate: Respiration: Neural substrate of the learning effect... Psychophysiological Interaction analysis (PPI): Neural substrate of the learning effect... Dynamic Causal Modeling analysis (DCM): During up-regulation, the visual ROI of the learners was progressively more correlated with the contralateral superior parietal lobe (SPL). is involved in directing covert visual-spatial attention and cognitive control. The learners showed increasing top-down control of the superior parietal lobe over the visual cortex, and at the same time reduced bottom-up processing. Voluntary self-regulation of early visual cortex can be learned with neurofeedback, and has a causal effect on the detectability of visual stimuli.... from single ROI to multiple ROI training studies. 9

10 beta estimates [a.u.] Modulating inter-hemispheric visual cortex balance. Modulating inter-hemispheric visual cortex balance. Pilot study in 14 healthy participants: learning curve: Feedback signal: Activity difference between the corresponding homologue left and right visual ROI (L-R, R-L). Transfer run: Can control over the differential feedback signal be maintained in the absence of neurofeedback session = 1h training (on separate days) No difference in heart rate, respiration, and eye movements between the conditions. No difference between learners and non-learners in terms of size of ROIs, vividness of visual imagery, cognitive strategy. Modulating inter-hemispheric visual cortex balance. Modulating inter-hemispheric visual cortex balance. Contributions of ROI target and ROI opposite : Maintenance of learned self-regulation (work in progress): N = 4 (learners) similar results for a 12 month follow-up. 3 neurofeedback training sessions 6 month follow-up Learners activated the ROI target, but no reduction in the ROI opposite. Non-learners did not achieve a consistent activation of the ROI target, that exceeded those of the ROI opposite. Learned self-regulation is maintained even in the absence of neurofeedback for at least 12 months. Modulating inter-hemispheric visual cortex balance. Applying neurofeedback to patients with hemispatial neglect. Cause: damage to the right parietal lobe. Symptoms: lack of awareness for the contralesional left side of space. Normal Neglect Parietal cortices normally serve to enhance visual processing. Voluntary control over the inter-hemispheric visual cortex balance can be learned with neurofeedback, and is maintained without further training for at least a year. The absence of such parietal influences due to the lesion cause attention-dependent pathological changes in the intact visual cortex. 10

11 beta estimates [a.u.] Applying neurofeedback to patients with hemispatial neglect. Applying neurofeedback to patients with hemispatial neglect. Treatment: caloric vestibular stimulation (Bottini et al., 2001) neck vibration (Schindler et al., 2002) TMS (Muri et al., 2013) prism adaptation (Saj et al., 2013) Compensate altered interhemispheric asymmetries, but associated with patient discomfort and short lasting effects. Pilot study in 7 stroke patients with left hemispatial neglect (ongoing work): intact visual fields mean 8 months after stroke onset mean age 60.3 (SD ± 10.9 years) Normal Neglect Increase visual cortex activity P1-P4 feedback from only the right visual cortex. P5-P7 differential feedback: right-left visual cortex. Applying neurofeedback to patients with hemispatial neglect. Applying neurofeedback to patients with hemispatial neglect. learning curve: Behavioral outcomes: ongoing work neurofeedback training sessions Those patients who were trained to upregulate their right visual cortex learned control within 3 x ~1.5 h of neurofeedback training sessions. 8 months 3 weeks training They showed an overall reduction in standardized global neglect severity scores (composed of line bisection, Bell s cancellation, and Odgen s scene copy tasks). Patients can learn voluntary control over their visual cortex activity, which caused a reduction in neglect symptoms. Similarly encouraging results have been obtained by colleagues in patients suffering from tinnitus, chronic pain, schizophrenia, and depression. Summary ROI-based neurofeedback. Connectivity-based neurofeedback. ROI based neurofeedback to manipulate visual perception and visual neglect. Most mental functions and most mental disorders are associated with activity in functional brain networks. Visual processing: Depression: Differential neurofeedback to manipulate inter-hemispheric visual cortex balance. Stuhrmann et al van Essen et al In order to directly target such functional brain networks, we developed connectivity-based neurofeedback. This new approach allows us to directly manipulate brain connectivity in health and disease. 11

12 regulation performance failed successful Connectivity-based neurofeedback... DCM. DCM for neurofeedback. Dynamic Causal Modelling (DCM): - Is a hypothesis-driven approach based on a priori connectivity models. - Allows to infer how brain regions interact with each other. Conventional DCM: Compares which model describes the data best. DCM for neurofeedback: Change brain connectivity to fit a target model best. For example, visual-spatial attention: - SPL: superior parietal lobe - VC: visual cortex - attention drives the SPL - attention drives the SPL-VC connection attention attention baseline baseline baseline given: fmri data target model find the best model change data to fit target model goal: model evidence target other model model maximize! DCM for neurofeedback... feasibility study. DCM for neurofeedback... feasibility study... design. Can healthy participants control the feedback signal in a well-known visual-spatial attention paradigm? 1 Functional localizers (12 min): VC SPL experimental paradigm ROI data Bayesian model comparison feedback signal 2 Structural scan and ROI selection (20 min) SPL L SPL R M ar vs. log Bayes Factor = log(m al ) log(m ar ) logbf > 0 correct! 3 4 runs (3 x 21 min): resting state acquisition...x 4 VC L VC R M al M al 5 Total experiment duration: ~2 hours (including screening) 7 healthy volunteers feedback presentation feedback presentation DCM for neurofeedback... optimization. DCM for neurofeedback... results. Optimization of the trade-off between the DCM convergence precision and the length of the sliding window over which the data is integrated : The participants were able to control the connectivity-based neurofeedback signal: Across the group, the log Bayes factors were significantly correct (z = 1.93, p = 0.027). TR = 1s The exceedance probability of M al during al was higher than those of M ar, and vice versa during ar: Computational speed (Standard laptop, Intel Core i7-2620m, 2.7 GHz, 4 GB RAM): On average, 4.6 ± 1.3 successful and 3.4 ± 1.3 failed trials: participant 12

13 DCM for neurofeedback... summary. DCM was optimized for real-time fmri. Participants were able to control the connectivity-based neurofeedback signal. Our new approach allows to non-pharmacologically train brain connectivity directly. Uuufff DCM for neurofeedback... outlook. a) Train healthy pilot subjects to increase top-down control of pre-frontal areas over limbic regions. b) Apply to patients suffering from depression: Stuhrmann et al Uuufff Aha! is intuitive! Ways to press some buttons: or what would you do when you get a VCR without a manual? Pressing buttons and seeing what happens! 13

14 LEARN! learning is not an easy task. Learned self-regulation of brain activity is not a permanent condition but can be voluntarily switched on/off by the participant! It requires the cooperation of the participant. Without being motivated and without being focused, a participant will not be able to learn self-regulation of brain activity. You cannot force a participant to learn self-regulation of brain activity. Methods Methods What is real-time fmri-based neurofeedback good for? to learn voluntary control over spatially localized brain activity!... to address causal links between brain activity and mental functions! What is special about real-time fmri?... data analysis keeps up with image acquisition! How to cancel out that self-regulation is artefactual (non-neuronal)? use differential feedback!... carefully analyse physiological noise after the real-time experiment, i.e. respiration, heart rate, head motion! How is real-time fmri accomplished?... Fast image acquisition!... Robust artefact control!... Purpose-made statistical analysis algorithms! Applications Applications What are the applications of real-time fmri?... Intra-operative real-time fmri to guide surgery... Quality assurance to improve the reliability of conventional fmri experiments.... Interactive teaching.... Brain-Computer-Interfaces.... to learn voluntary control over brain activity. Why is intra-operative real-time fmri necessary?... During the surgery, brain tissue shifts in position.... Functional brain networks can change during surgery due to acute plasticity. What are the pros & cons of a real-time fmri BCI?... Easy to learn.... Multiple focal brain areas can be targeted simultaneously (including deep brain areas).... Slow information transfer rate.... Expensive and not portable.... No direct measure of neural activity. 14

15 Further reading (review articles) Sulzer J., Haller S., Scharnowski F., Weiskopf N., Birbaumer N., Blefari M., Brühl A., Cohen L., decharms R.C., Gassert R., Göbel R., Herwig U., LaConte S., Linden D., Luft A., Seifritz E., Sitaram R. (2013): Realtime fmri neurofeedback: progress and challenges. Neuroimage, 76(1), decharms (2008): Applications of real-time fmri. Nature Reviews Neuroscience. LaConte (2010): Decoding fmri brain states in real-time. NeuroImage. Weiskopf (2007): Real-time functional magnetic resonance imaging: Methods and applications. Magnetic Resonance Imaging. 15