| 1. |
- Cunningham, Gregory, et al.
(author)
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Neural Correlates of Clinical Scores in Patients with Anterior Shoulder Apprehension
- 2015
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In: Medicine & Science in Sports & Exercise. - 0195-9131 .- 1530-0315. ; 47:12, s. 2612-2620
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Journal article (peer-reviewed)abstract
- Introduction Anterior shoulder apprehension is a commonly reported complaint in anterior shoulder instability, which may lead to patient morbidity and impede shoulder function. It is the result of a cognitively complex mechanism, which includes anxiety, salience, fear, and anticipation. Purpose The aim of this prospective case-control study was to correlate five clinically established scores using functional magnetic resonance imaging to assess brain activation patterns in patients with apprehension related to anterior shoulder instability. Methods This study includes 28 consecutive male right-handed patients ( mean +/- SEM, 26.8 +/- 1.2 yr) with positive shoulder apprehension test and 10 healthy matched control participants without apprehension or a history of instability. Task- related and functional connectivity functional magnetic resonance imaging activation patterns occurring during apprehension video cue stimulation were correlated with five clinical tests and scores: Visual Analog Scale ( VAS), Rowe score for instability, Simple Shoulder Test, Subjective Shoulder Value ( SSV), and Western Ontario Shoulder Instability ( WOSI). Results Rowe, pain VAS, and WOSI scores correlated with prefrontal cortex, dorsolateral prefrontal cortex, dorsomedial prefrontal cortex, somatosensory area, and parieto-occipital and temporal areas (default mode network). Rowe score additionally correlated with frontal pole, anterior midcingulate cortex, and visual areas. Moreover, SSV correlated with task-related brain activity in the bilateral precentral gyrus, bilateral postcentral gyrus, and bilateral superior parietal lobe. Conclusions Overall, Rowe score provides the strongest link between shoulder apprehension and brain level alterations as it correlates with the highest number of independent components involving areas responsible for both motor and cognitive functions, whereas pain VAS and WOSI occupy an intermediately strong link recruiting less brain networks. Finally, Simple Shoulder Test and SSV have the weakest link at the brain level.
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| 2. |
- Emmert, Kirsten, et al.
(author)
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Continuous vs. intermittent neurofeedback to regulate auditory cortex activity of tinnitus patients using real-time fMRI : A pilot study
- 2017
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In: NeuroImage. - : Elsevier BV. - 2213-1582. ; 14, s. 97-104
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Journal article (peer-reviewed)abstract
- The emerging technique of real-time fMRI neurofeedback trains individuals to regulate their own brain activity via feedback from an fMRI measure of neural activity. Optimum feedback presentation has yet to be determined, particularly when working with clinical populations. To this end, we compared continuous against intermittent feedback in subjects with tinnitus.Fourteen participants with tinnitus completed the whole experiment consisting of nine runs (3 runs × 3 days). Prior to the neurofeedback, the target region was localized within the auditory cortex using auditory stimulation (1 kHz tone pulsating at 6 Hz) in an ON-OFF block design. During neurofeedback runs, participants received either continuous (n = 7, age 46.84 ± 12.01, Tinnitus Functional Index (TFI) 49.43 ± 15.70) or intermittent feedback (only after the regulation block) (n = 7, age 47.42 ± 12.39, TFI 49.82 ± 20.28). Participants were asked to decrease auditory cortex activity that was presented to them by a moving bar. In the first and the last session, participants also underwent arterial spin labeling (ASL) and resting-state fMRI imaging. We assessed tinnitus severity using the TFI questionnaire before all sessions, directly after all sessions and six weeks after all sessions. We then compared neuroimaging results from neurofeedback using a general linear model (GLM) and region-of-interest analysis as well as behavior measures employing a repeated-measures ANOVA. In addition, we looked at the seed-based connectivity of the auditory cortex using resting-state data and the cerebral blood flow using ASL data.GLM group analysis revealed that a considerable part of the target region within the auditory cortex was significantly deactivated during neurofeedback. When comparing continuous and intermittent feedback groups, the continuous group showed a stronger deactivation of parts of the target region, specifically the secondary auditory cortex. This result was confirmed in the region-of-interest analysis that showed a significant down-regulation effect for the continuous but not the intermittent group. Additionally, continuous feedback led to a slightly stronger effect over time while intermittent feedback showed best results in the first session. Behaviorally, there was no significant effect on the total TFI score, though on a descriptive level TFI scores tended to decrease after all sessions and in the six weeks follow up in the continuous group. Seed-based connectivity with a fixed-effects analysis revealed that functional connectivity increased over sessions in the posterior cingulate cortex, premotor area and part of the insula when looking at all patients while cerebral blood flow did not change significantly over time.Overall, these results show that continuous feedback is suitable for long-term neurofeedback experiments while intermittent feedback presentation promises good results for single session experiments when using the auditory cortex as a target region. In particular, the down-regulation effect is more pronounced in the secondary auditory cortex, which might be more susceptible to voluntary modulation in comparison to a primary sensory region.
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| 3. |
- Emmert, Kirsten, et al.
(author)
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Meta-analysis of real-time fMRI neurofeedback studies using individual participant data : How is brain regulation mediated?
- 2016
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In: NeuroImage. - : Elsevier BV. - 1053-8119 .- 1095-9572. ; 124:Part A, s. 806-812
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Journal article (peer-reviewed)abstract
- An increasing number of studies using real-time fMRI neurofeedback have demonstrated that successful regulation of neural activity is possible in various brain regions. Since these studies focused on the regulated region(s), little is known about the target-independent mechanisms associated with neurofeedback-guided control of brain activation, i.e. the regulating network. While the specificity of the activation during self-regulation is an important factor, no study has effectively determined the network involved in self-regulation in general. In an effort to detect regions that are responsible for the act of brain regulation, we performed a post-hoc analysis of data involving different target regions based on studies from different research groups. We included twelve suitable studies that examined nine different target regions amounting to a total of 175 subjects and 899 neurofeedback runs. Data analysis included a standard first-(single subject, extracting main paradigm) and second-level (single subject, all runs) general linear model (GLM) analysis of all participants taking into account the individual timing. Subsequently, at the third level, a random effects model GLM included all subjects of all studies, resulting in an overall mixed effects model. Since four of the twelve studies had a reduced field of view (FoV), we repeated the same analysis in a subsample of eight studies that had a well-overlapping FoV to obtain a more global picture of self-regulation. The GLM analysis revealed that the anterior insula as well as the basal ganglia, notably the striatum, were consistently active during the regulation of brain activation across the studies. The anterior insula has been implicated in interoceptive awareness of the body and cognitive control. Basal ganglia are involved in procedural learning, visuomotor integration and other higher cognitive processes including motivation. The larger FoV analysis yielded additional activations in the anterior cingulate cortex, the dorsolateral and ventrolateral prefrontal cortex, the temporo-parietal area and the visual association areas including the temporo-occipital junction. In conclusion, we demonstrate that several key regions, such as the anterior insula and the basal ganglia, are consistently activated during self-regulation in real-time fMRI neurofeedback independent of the targeted region-ofinterest. Our results imply that if the real-time fMRI neurofeedback studies target regions of this regulation network, such as the anterior insula, care should be given whether activation changes are related to successful regulation, or related to the regulation process per se. Furthermore, future research is needed to determine how activation within this regulation network is related to neurofeedback success.
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| 4. |
- Kopel, Rotem, et al.
(author)
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Distributed Patterns of Brain Activity Underlying Real-Time fMRI Neurofeedback Training
- 2017
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In: IEEE Transactions on Biomedical Engineering. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 0018-9294 .- 1558-2531. ; 64:6, s. 1228-1237
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Journal article (peer-reviewed)abstract
- Neurofeedback (NF) based on real-time functional magnetic resonance imaging (rt-fMRI) is an exciting neuroimaging application. In most rt-fMRI NF studies, the activity level of a single region of interest (ROI) is provided as a feedback signal and the participants are trained to up or down regulate the feedback signal. NF training effects are typically analyzed using a confirmatory univariate approach, i.e., changes in the target ROI are explained by a univariate linear modulation. However, learning to self-regulate the ROI activity through NF is mediated by distributed changes across the brain. Here, we deploy a multivariate decoding model for assessing NF training effects across the whole brain. Specifically, we first explain the NF training effect by a posthoc multivariate model that leads to a pattern of coactivation based on 90 functional atlas regions. We then use cross validation to reveal the set of brain regions with the best fit. This novel approach was applied to the data from a rt-fMRI NF study where the participants learned to down regulate the auditory cortex. We found that the optimal model consisted of 16 brain regions whose coactivation patterns best described the training effect over the NF training days. Cross validation of the multivariate model showed that it generalized across the participants. Interestingly, the participants could be clustered into two groups with distinct patterns of coactivation, potentially reflecting different NF learning strategies. Overall, our findings revealed that multiple brain regions are involved in learning to regulate an activity in a single ROI, and thus leading to a better understanding of the mechanisms underlying NF training.
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| 5. |
- Zanchi, Davide, et al.
(author)
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Cigarette smoking leads to persistent and dose-dependent alterations of brain activity and connectivity in anterior insula and anterior cingulate
- 2015
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In: Addiction Biology. - : Wiley. - 1355-6215 .- 1369-1600. ; 20:6, s. 1033-1041
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Journal article (peer-reviewed)abstract
- Although many smokers try to quit smoking, only about 20-25 percent will achieve abstinence despite 6months or more of gold-standard treatment. This low success rate suggests long-term changes in the brain related to smoking, which remain poorly understood. We compared ex-smokers to both active smokers and non-smokers using functional magnetic resonance imaging (fMRI) to explore persistent modifications in brain activity and network organization. This prospective and consecutive study includes 18 non-smokers (29.5 +/- 6.7years of age, 11 women), 14 smokers (10 cigarettes a day >2years of smoking, 29.3 +/- 6.0years of age, 10 women) and 14 ex-smokers (>1year of quitting 30.5 +/- 5.7years of age, 10 women). Participants underwent a block-design fMRI study contrasting smoking cue with control (neutral cue) videos. Data analyses included task-related general linear model, seed-based functional connectivity, voxel-based morphometry (VBM) of gray matter and tract-based spatial statistics (TBSS) of white matter. Smoking cue videos versus control videos activated the right anterior insula in ex-smokers compared with smokers, an effect correlating with cumulative nicotine intake (pack-years). Moreover, ex-smokers had a persistent decrease in functional connectivity between right anterior insula and anterior cingulate cortex (ACC) compared with control participants, but similar to active smokers. Potentially confounding alterations in gray or white matter were excluded in VBM and TBSS analyses. In summary, ex-smokers with long-term nicotine abstinence have persistent and dose-dependent brain network changes notably in the right anterior insula and its connection to the ACC.
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