Article

Caria, A. et al. Regulation of anterior insular cortex activity using real-time fMRI. Neuroimage 35, 1238-1246

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.

Download full-text

Full-text

Available from: Ralf Veit
  • Source
    • "imotor areas while performing a simple finger tapping task. Since this seminal study , mounting evidence has established that healthy subjects and patients can gain control over activation of different specific brain areas , such as the amygdala ( Posse et al . , 2003 ) , anterior cingulate cortex ( deCharms et al . , 2005 ) , and insular cortex ( Caria et al . , 2007 ) , when receiving feedback about the activity in these regions . In the field of motor learning and rehabilitation , motor imagery ( MI ) – defined as a dynamic state during which a subject mentally simulates a given action ( for a review see Sharma et al . , 2006 ) – has been established effective in recruiting the motor control netwo"
    [Show abstract] [Hide abstract]
    ABSTRACT: Neurofeedback by functional magnetic resonance imaging (fMRI) is a technique of potential therapeutic relevance that allows individuals to be aware of their own neurophysiological responses and to voluntarily modulate the activity of specific brain regions, such as the premotor cortex (PMC), important for motor recovery after brain injury. We investigated (i) whether healthy human volunteers are able to up-regulate the activity of the left PMC during a right hand finger tapping motor imagery (MI) task while receiving continuous fMRI-neurofeedback, and (ii) whether successful modulation of brain activity influenced non-targeted motor control regions. During the MI task, participants of the neurofeedback group (NFB) received ongoing visual feedback representing the level of fMRI responses within their left PMC. Control (CTL) group participants were shown similar visual stimuli, but these were non-contingent on brain activity. Both groups showed equivalent levels of behavioral ratings on arousal and MI, before and during the fMRI protocol. In the NFB, but not in CLT group, brain activation during the last run compared to the first run revealed increased activation in the left PMC. In addition, the NFB group showed increased activation in motor control regions extending beyond the left PMC target area, including the supplementary motor area, basal ganglia and cerebellum. Moreover, in the last run, the NFB group showed stronger activation in the left PMC/inferior frontal gyrus when compared to the CTL group. Our results indicate that modulation of PMC and associated motor control areas can be achieved during a single neurofeedback-fMRI session. These results contribute to a better understanding of the underlying mechanisms of MI-based neurofeedback training, with direct implications for rehabilitation strategies in severe brain disorders, such as stroke.
    Full-text · Article · Dec 2015 · Frontiers in Behavioral Neuroscience
  • Source
    • "The localization criterion for the region serving as region-of-interest (ROI) for neurofeedback has been widely variable. Some studies focused on specific anatomically defined regions such as the somatomotor cortex (deCharms et al 2004), anterior cingulate cortex (Weiskopf et al 2003), amygdala (Posse et al 2003) and the insula (Posse et al 2003, Weiskopf et al 2003, deCharms et al 2004, 2005, Caria et al 2007, Hamilton et al 2011, Subramanian et al 2011, Ruiz et al 2013). Others preferred to use functionally defined ROIs as target for neuromodulation (deCharms et al 2005, Hamilton et al 2011, Subramanian et al 2011, Ruiz et al 2013, Greer et al 2014). "
    [Show abstract] [Hide abstract]
    ABSTRACT: Objective: Current approaches in neurofeedback/brain-computer interface research often focus on identifying, on a subject-by-subject basis, the neural regions that are best suited for self-driven modulation. It is known that the hMT+/V5 complex, an early visual cortical region, is recruited during explicit and implicit motion imagery, in addition to real motion perception. This study tests the feasibility of training healthy volunteers to regulate the level of activation in their hMT+/V5 complex using real-time fMRI neurofeedback and visual motion imagery strategies. Approach: We functionally localized the hMT+/V5 complex to further use as a target region for neurofeedback. An uniform strategy based on motion imagery was used to guide subjects to neuromodulate hMT+/V5. Main results: We found that 15/20 participants achieved successful neurofeedback. This modulation led to the recruitment of a specific network as further assessed by psychophysiological interaction analysis. This specific circuit, including hMT+/V5, putative V6 and medial cerebellum was activated for successful neurofeedback runs. The putamen and anterior insula were recruited for both successful and non-successful runs. Significance: Our findings indicate that hMT+/V5 is a region that can be modulated by focused imagery and that a specific cortico-cerebellar circuit is recruited during visual motion imagery leading to successful neurofeedback. These findings contribute to the debate on the relative potential of extrinsic (sensory) versus intrinsic (default-mode) brain regions in the clinical application of neurofeedback paradigms. This novel circuit might be a good target for future neurofeedback approaches that aim, for example, the training of focused attention in disorders such as ADHD.
    Full-text · Article · Sep 2015 · Journal of Neural Engineering
  • Source
    • "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). "
    [Show abstract] [Hide abstract]
    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.
    Full-text · Article · Jun 2015 · Frontiers in Behavioral Neuroscience
Show more