A Protocol for the Administration of Real-Time fMRI Neurofeedback Training

Neurologic disorders are characterized by abnormal cellular-, molecular-, and circuit-level functions in the brain. New methods to induce and control neuroplastic processes and correct abnormal function, or even shift functions from damaged tissue to physiologically healthy brain regions, hold the potential to dramatically improve overall health. Of the current neuroplastic interventions in development, neurofeedback training (NFT) from functional Magnetic Resonance Imaging (fMRI) has the advantages of being completely non-invasive, non-pharmacologic, and spatially localized to target brain regions, as well as having no known side effects. Furthermore, NFT techniques, initially developed using fMRI, can often be translated to exercises that can be performed outside of the scanner without the aid of medical professionals or sophisticated medical equipment. In fMRI NFT, the fMRI signal is measured from specific regions of the brain, processed, and presented to the participant in real-time. Through training, self-directed mental processing techniques, that regulate this signal and its underlying neurophysiologic correlates, are developed. FMRI NFT has been used to train volitional control over a wide range of brain regions with implications for several different cognitive, behavioral, and motor systems. Additionally, fMRI NFT has shown promise in a broad range of applications such as the treatment of neurologic disorders and the augmentation of baseline human performance. In this article, we present an fMRI NFT protocol developed at our institution for modulation of both healthy and abnormal brain function, as well as examples of using the method to target both cognitive and auditory regions of the brain

Deep brain electrical neurofeedback allows Parkinson patients to control pathological oscillations and quicken movements

Parkinsonian motor symptoms are linked to pathologically increased beta-oscillations in the basal ganglia. While pharmacological treatment and deep brain stimulation (DBS) reduce these pathological oscillations concomitantly with improving motor performance, we set out to explore neurofeedback as an endogenous modulatory method. We implemented real-time processing of pathological subthalamic beta oscillations through implanted DBS electrodes to provide deep brain electrical neurofeedback. Patients volitionally controlled ongoing beta-oscillatory activity by visual neurofeedback within minutes of training. During a single one-hour training session, the reduction of beta-oscillatory activity became gradually stronger and we observed improved motor performance. Lastly, endogenous control over deep brain activity was possible even after removing visual neurofeedback, suggesting that neurofeedback-acquired strategies were retained in the short-term. Moreover, we observed motor improvement when the learnt mental strategies were applied 2 days later without neurofeedback. Further training of deep brain neurofeedback might provide therapeutic benefits for Parkinson patients by improving symptom control using strategies optimized through neurofeedback

Self-regulation of visual word form area activation with real-time fMRI neurofeedback

The Visual Word Form Area (VWFA) is a key region of the brain’s reading network and its activation has been shown to be strongly associated with reading skills. Here, for the first time, we investigated whether voluntary regulation of VWFA activation is feasible using real-time fMRI neurofeedback. 40 adults with typical reading skills were instructed to either upregulate (UP group, N = 20) or downregulate (DOWN group, N = 20) their own VWFA activation during six neurofeedback training runs. The VWFA target region was individually defined based on a functional localizer task. Before and after training, also regulation runs without feedback (“no-feedback runs”) were performed. When comparing the two groups, we found stronger activation across the reading network for the UP than the DOWN group. Further, activation in the VWFA was significantly stronger in the UP group than the DOWN group. Crucially, we observed a significant interaction of group and time (pre, post) for the no-feedback runs: The two groups did not differ significantly in their VWFA activation before neurofeedback training, but the UP group showed significantly stronger activation than the DOWN group after neurofeedback training. Our results indicate that upregulation of VWFA activation is feasible and that, once learned, successful upregulation can even be performed in the absence of feedback. These results are a crucial first step toward the development of a potential therapeutic support to improve reading skills in individuals with reading impairments

Meta-analysis of real-time fMRI neurofeedback studies using individual participant data: How is brain regulation mediated?

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-of-interest. 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

Can we predict real-time fMRI neurofeedback learning success from pretraining brain activity?

Neurofeedback training has been shown to influence behavior in healthy participants as well as to alleviate clinical symptoms in neurological, psychosomatic, and psychiatric patient populations. However, many real-time fMRI neurofeedback studies report large inter-individual differences in learning success. The factors that cause this vast variability between participants remain unknown and their identification could enhance treatment success. Thus, here we employed a meta-analytic approach including data from 24 different neurofeedback studies with a total of 401 participants, including 140 patients, to determine whether levels of activity in target brain regions during pretraining functional localizer or no-feedback runs (i.e., self-regulation in the absence of neurofeedback) could predict neurofeedback learning success. We observed a slightly positive correlation between pretraining activity levels during a functional localizer run and neurofeedback learning success, but we were not able to identify common brain-based success predictors across our diverse cohort of studies. Therefore, advances need to be made in finding robust models and measures of general neurofeedback learning, and in increasing the current study database to allow for investigating further factors that might influence neurofeedback learning

Can we predict real-time fMRI neurofeedback learning success from pretraining brain activity?

Neurofeedback training has been shown to influence behavior in healthy participants as well as to alleviate clinical symptoms in neurological, psychosomatic, and psychiatric patient populations. However, many real-time fMRI neurofeedback studies report large inter-individual differences in learning success. The factors that cause this vast variability between participants remain unknown and their identification could enhance treatment success. Thus, here we employed a meta-analytic approach including data from 24 different neurofeedback studies with a total of 401 participants, including 140 patients, to determine whether levels of activity in target brain regions during pretraining functional localizer or no-feedback runs (i.e., self-regulation in the absence of neurofeedback) could predict neurofeedback learning success. We observed a slightly positive correlation between pretraining activity levels during a functional localizer run and neurofeedback learning success, but we were not able to identify common brain-based success predictors across our diverse cohort of studies. Therefore, advances need to be made in finding robust models and measures of general neurofeedback learning, and in increasing the current study database to allow for investigating further factors that might influence neurofeedback learning

Real-time Neurofeedback Using Functional MRI Could Improve Down-Regulation of Amygdala Activity During Emotional Stimulation: A Proof-of-Concept Study

The amygdala is a central target of emotion regulation. It is overactive and dysregulated in affective and anxiety disorders and amygdala activity normalizes with successful therapy of the symptoms. However, a considerable percentage of patients do not reach remission within acceptable duration of treatment. The amygdala could therefore represent a promising target for real-time functional magnetic resonance imaging (rtfMRI) neurofeedback. rtfMRI neurofeedback directly improves the voluntary regulation of localized brain activity. At present, most rtfMRI neurofeedback studies have trained participants to increase activity of a target, i.e. up-regulation. However, in the case of the amygdala, down-regulation is supposedly more clinically relevant. Therefore, we developed a task that trained participants to down-regulate activity of the right amygdala while being confronted with amygdala stimulation, i.e. negative emotional faces. The activity in the functionally-defined region was used as online visual feedback in six healthy subjects instructed to minimize this signal using reality checking as emotion regulation strategy. Over a period of four training sessions, participants significantly increased down-regulation of the right amygdala compared to a passive viewing condition to control for habilitation effects. This result supports the concept of using rtfMRI neurofeedback training to control brain activity during relevant stimulation, specifically in the case of emotion, and has implications towards clinical treatment of emotional disorders

Improving motivation through real-time fMRI-based self-regulation of the nucleus accumbens.

OBJECTIVE: Impaired nucleus accumbens (NAcc) activation is associated with amotivation and anhedonia, which are resistant to treatment with antipsychotics and antidepressants in schizophrenia. In this study, healthy participants were trained to self-regulate the activation of their NAcc, a brain region that plays an important role in motivation, using real-time functional magnetic resonance imaging (fMRI) neurofeedback. METHOD: The experimental group (N = 19) received feedback from the NAcc, whereas the control group (N = 5) received "sham" feedback from the posterior parahippocampal gyrus, a control brain region not normally related to motivation. All participants were trained to use mental strategies to regulate their NAcc activations in a 3T MRI scanner. RESULTS: For the learning effect of NAcc regulation, we found that the majority of participants (74%) in the experimental group successfully learned to self-regulate the NAcc. They also showed improved behavioral performance in motivation and decreased functional connectivity between the NAcc and the ventral medial prefrontal cortex and an increase in small-world properties in the reward circuit after training, indicating improved information integration in reward processing. However, improvement in motivation and modification of function connectivity were not observed in the sham control group and the participants who failed to self-regulate the NAcc in the experimental group. Self-regulation was influenced by the baseline motivation. CONCLUSIONS: These findings suggest that the NAcc could be self-regulated using real-time fMRI neurofeedback and can result in improved motivation in cognitive tasks. (PsycINFO Database Recor

A Unifying Pathophysiological Account for Post-stroke Spasticity and Disordered Motor Control

Cortical and subcortical plastic reorganization occurs in the course of motor recovery after stroke. It is largely accepted that plasticity of ipsilesional motor cortex primarily contributes to recovery of motor function, while the contributions of contralesional motor cortex are not completely understood. As a result of damages to motor cortex and its descending pathways and subsequent unmasking of inhibition, there is evidence of upregulation of reticulospinal tract (RST) excitability in the contralesional side. Both animal studies and human studies with stroke survivors suggest and support the role of RST hyperexcitability in post-stroke spasticity. Findings from animal studies demonstrate the compensatory role of RST hyperexcitability in recovery of motor function. In contrast, RST hyperexcitability appears to be related more to abnormal motor synergy and disordered motor control in stroke survivors. It does not contribute to recovery of normal motor function. Recent animal studies highlight laterality dominance of corticoreticular projections. In particular, there exists upregulation of ipsilateral corticoreticular projections from contralesional premotor cortex (PM) and supplementary motor area (SMA) to medial reticular nuclei. We revisit and revise the previous theoretical framework and propose a unifying account. This account highlights the importance of ipsilateral PM/SMA-cortico-reticulospinal tract hyperexcitability from the contralesional motor cortex as a result of disinhibition after stroke. This account provides a pathophysiological basis for post-stroke spasticity and related movement impairments, such as abnormal motor synergy and disordered motor control. However, further research is needed to examine this pathway in stroke survivors to better understand its potential roles, especially in muscle strength and motor recovery. This account could provide a pathophysiological target for developing neuromodulatory interventions to manage spasticity and thus possibly to facilitate motor recovery