Article

Regulation of anterior insular cortex activity using real-time fMRI

Institute of Medical Psychology and Behavioral Neurobiology, Eberhard-Karls-University of Tübingen, Tübingen, Germany. <>
NeuroImage (Impact Factor: 6.36). 05/2007; 35(3):1238-46. DOI: 10.1016/j.neuroimage.2007.01.018
Source: PubMed

ABSTRACT Recent advances in functional magnetic resonance imaging (fMRI) data acquisition and processing techniques have made real-time fMRI (rtfMRI) of localized brain areas feasible, reliable and less susceptible to artefacts. Previous studies have shown that healthy subjects learn to control local brain activity with operant training by using rtfMRI-based neurofeedback. In the present study, we investigated whether healthy subjects could voluntarily gain control over right anterior insular activity. Subjects were provided with continuously updated information of the target ROI's level of activation by visual feedback. All participants were able to successfully regulate BOLD-magnitude in the right anterior insular cortex within three sessions of 4 min each. Training resulted in a significantly increased activation cluster in the anterior portion of the right insula across sessions. An increased activity was also found in the left anterior insula but the percent signal change was lower than in the target ROI. Two different control conditions intended to assess the effects of non-specific feedback and mental imagery demonstrated that the training effect was not due to unspecific activations or non feedback-related cognitive strategies. Both control groups showed no enhanced activation across the sessions, which confirmed our main hypothesis that rtfMRI feedback is area-specific. The increased activity in the right anterior insula during training demonstrates that the effects observed are anatomically specific and self-regulation of right anterior insula only is achievable. This is the first group study investigating the volitional control of emotionally relevant brain region by using rtfMRI training and confirms that self-regulation of local brain activity with rtfMRI is possible.

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    • "This has been suggested as a method to modulate specific functions of neural networks (Yoo et al., 2006). Several studies have demonstrated that healthy participants can learn the control Abbreviations: ACC, anterior cingulate cortex; BCI, brain-computer interface; EEG, electroencephalography; EPI, echo planar image; NF, neurofeedback; ROI, region of interest; rt-fMRI, real-time functional magnetic resonance imaging; SPM, Statistical Parametric Mapping. of circumscribed brain regions using fMRI-based NF (Yoo et al., 2006; Caria et al., 2007; Rota et al., 2009; Hamilton et al., 2011; Scharnowski et al., 2012; Lawrence et al., 2013). Moreover, first attempts of using fMRI-NF as a therapeutic intervention have been made (e.g., Subramanian et al., 2011). "
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    ABSTRACT: Cognitive functioning is impaired in patients with schizophrenia, leading to significant disabilities in everyday functioning. Its improvement is an important treatment target. Neurofeedback (NF) seems a promising method to address the neural dysfunctions underlying those cognitive impairments. The anterior cingulate cortex (ACC), a central hub for cognitive processing, is one of the brain regions known to be dysfunctional in schizophrenia. Here we conducted NF training based on real-time functional magnetic resonance imaging (fMRI) in patients with schizophrenia to enable them to control their ACC activity. Training was performed over 3 days in a group of 11 patients with schizophrenia and 11 healthy controls. Social feedback was provided in accordance with the evoked activity in the selected region of interest (ROI). Neural and cognitive strategies were examined off-line. Both groups learned to control the activity of their ACC but used different neural strategies: patients activated the dorsal and healthy controls the rostral subdivision. Patients mainly used imagination of music to elicit activity and the control group imagination of sports. In a stepwise regression analysis, the difference in neural control did not result from the differences in cognitive strategies but from diagnosis alone. Based on social reinforcers, patients with schizophrenia can learn to regulate localized brain activity. However, cognitive strategies and neural network location differ from healthy controls. These data emphasize that for therapeutic interventions in patients with schizophrenia compensatory strategies may emerge. Specific cognitive skills or specific dysfunctional networks should be addressed to train impaired skills. Social NF based on fMRI may be one method to accomplish precise learning targets.
    Frontiers in Behavioral Neuroscience 06/2015; 9:169. DOI:10.3389/fnbeh.2015.00169 · 4.16 Impact Factor
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    • "These designs include brain–computer interface (BCI) [18–20,21] or the provision of neurofeedback. In the latter application, the user receives a measure of their own brain activity in real-time, often for the purposes of neurorehabilitation [22] [23] [24]. "
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    ABSTRACT: Neurofeedback- and brain-computer interface (BCI)-based interventions can be implemented using real-time analysis of magnetoencephalographic (MEG) recordings. Head movement during MEG recordings, however, can lead to inaccurate estimates of brain activity, reducing the efficacy of the intervention. Most real-time applications in MEG have utilized analyses that do not correct for head movement. Effective means of correcting for head movement are needed to optimize the use of MEG in such applications. Here we provide preliminary validation of a novel analysis technique, real-time source estimation (rtSE), that measures head movement and generates corrected current source time course estimates in real-time. rtSE was applied while recording a calibrated phantom to determine phantom position localization accuracy and source amplitude estimation accuracy under stationary and moving conditions. Results were compared to off-line analysis methods to assess validity of the rtSE technique. The rtSE method allowed for accurate estimation of current source activity at the source-level in real-time, and accounted for movement of the source due to changes in phantom position. The rtSE technique requires modifications and specialized analysis of the following MEG work flow steps.•Data acquisition•Head position estimation•Source localization•Real-time source estimationThis work explains the technical details and validates each of these steps.
    11/2014; 1. DOI:10.1016/j.mex.2014.10.008
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    • "In comparison to the low success rate of psychopathic criminals to up-regulate the anterior insula in this study, an earlier study in our lab in 15 healthy participants showed significant increase in the BOLD signal in the anterior insula with five neurofeedback training runs (Caria et al., 2007). Linear regression across all runs showed significant increase of activity in the anterior insula [y = 0.174 + 0.127, P < 0.012]. "
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    ABSTRACT: This pilot study aimed to explore whether criminal psychopaths can learn volitional regulation of the left anterior insula with real-time fMRI neurofeedback. Our previous studies with healthy volunteers showed that learned control of the blood oxygenation-level dependent (BOLD) signal was specific to the target region, and not a result of general arousal and global unspecific brain activation, and also that successful regulation modulates emotional responses, specifically to aversive picture stimuli but not neutral stimuli. In this pilot study, four criminal psychopaths were trained to regulate the anterior insula by employing negative emotional imageries taken from previous episodes in their lives, in conjunction with contingent feedback. Only one out of the four participants learned to increase the percent differential BOLD in the up-regulation condition across training runs. Subjects with higher Psychopathic Checklist-Revised (PCL:SV) scores were less able to increase the BOLD signal in the anterior insula than their lower PCL:SV counterparts. We investigated functional connectivity changes in the emotional network due to learned regulation of the successful participant, by employing multivariate Granger Causality Modeling (GCM). Learning to up-regulate the left anterior insula not only increased the number of connections (causal density) in the emotional network in the single successful participant but also increased the difference between the number of outgoing and incoming connections (causal flow) of the left insula. This pilot study shows modest potential for training psychopathic individuals to learn to control brain activity in the anterior insula.
    Frontiers in Behavioral Neuroscience 10/2014; 8:344. DOI:10.3389/fnbeh.2014.00344 · 4.16 Impact Factor
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