Causal interaction following the alteration of target region activation during motor imagery training using real-time fMRI

Upregulation of Supplementary Motor Area Activation with fMRI Neurofeedback during Motor Imagery

Functional magnetic resonance imaging (fMRI) neurofeedback (NF) is a promising tool to study the relationship between behavior and brain activity. It enables people to self-regulate their brain signal. Here, we applied fMRI NF to train healthy participants to increase activity in their supplementary motor area (SMA) during a motor imagery (MI) task of complex body movements while they received a continuous visual feedback signal. This signal represented the activity of participants’ localized SMA regions in the NF group and a prerecorded signal in the control group (sham feedback). In the NF group only, results showed a gradual increase in SMA-related activity across runs. This upregulation was largely restricted to the SMA, while other regions of the motor network showed no, or only marginal NF effects. In addition, we found behavioral changes, i.e., shorter reaction times in a Go/No-go task after the NF training only. These results suggest that NF can assist participants to develop greater control over a specifically targeted motor region involved in motor skill learning. The results contribute to a better understanding of the underlying mechanisms of SMA NF based on MI with a direct implication for rehabilitation of motor dysfunctions.

Higher-order Brain Areas Associated with Real-time Functional MRI Neurofeedback Training of the Somato-motor Cortex

Neurofeedback (NFB) allows subjects to learn self-regulation of neuronal brain activation based on information about the ongoing activation. The implementation of real-time functional magnetic resonance imaging (rt-fMRI) for NFB training now facilitates the investigation into underlying processes. Our study involved 16 control and 16 training right-handed subjects, the latter performing an extensive rt-fMRI NFB training using motor imagery. A previous analysis focused on the targeted primary somato-motor cortex (SMC). The present study extends the analysis to the supplementary motor area (SMA), the next higher brain area within the hierarchy of the motor system. We also examined transfer-related functional connectivity using a whole-volume psycho-physiological interaction (PPI) analysis to reveal brain areas associated with learning. The ROI analysis of the pre- and post-training fMRI data for motor imagery without NFB (transfer) resulted in a significant training-specific increase in the SMA. It could also be shown that the contralateral SMA exhibited a larger increase than the ipsilateral SMA in the training and the transfer runs, and that the right-hand training elicited a larger increase in the transfer runs than the left-hand training. The PPI analysis revealed a training-specific increase in transfer-related functional connectivity between the left SMA and frontal areas as well as the anterior midcingulate cortex (aMCC) for right- and left-hand trainings. Moreover, the transfer success was related with training-specific increase in functional connectivity between the left SMA and the target area SMC. Our study demonstrates that NFB training increases functional connectivity with non-targeted brain areas. These are associated with the training strategy (i.e., SMA) as well as with learning the NFB skill (i.e., aMCC and frontal areas). This detailed description of both the system to be trained and the areas involved in learning can provide valuable information for further optimization of NFB trainings.

The potential of real-time fMRI neurofeedback for stroke rehabilitation: A systematic review

Real-time functional magnetic resonance imaging (rt-fMRI) neurofeedback aids the modulation of neural functions by training self-regulation of brain activity through operant conditioning. This technique has been applied to treat several neurodevelopmental and neuropsychiatric disorders, but its effectiveness for stroke rehabilitation has not been examined yet. Here, we systematically review the effectiveness of rt-fMRI neurofeedback training in modulating motor and cognitive processes that are often impaired after stroke. Based on predefined search criteria, we selected and examined 33 rt-fMRI neurofeedback studies, including 651 healthy individuals and 15 stroke patients in total. The results of our systematic review suggest that rt-fMRI neurofeedback training can lead to a learned modulation of brain signals, with associated changes at both the neural and the behavioural level. However, more research is needed to establish how its use can be optimized in the context of stroke rehabilitation.

Brain correlates to facial motor imagery and its somatotopy in the primary motor cortex

Motor imagery (MI) has attracted increased interest for motor rehabilitation as many studies have shown that MI shares the same neural networks as motor execution (ME). Nevertheless, MI in terms of facial movement has not been studied extensively; thus, in the present study, we investigated shared neural networks between facial motor imagery (FMI) and facial motor execution (FME). In addition, FMI somatotopy within-face was investigated between the forehead and the mouth. Functional MRI was used to examine 34 healthy individuals with ME and MI paradigms for the forehead and the mouth. The general linear model and a paired t-test were performed to define the facial area in the primary motor cortex (M1) and this area has been used to investigate somatotopy between the forehead and mouth FMI. FMI recruited similar brain motor areas as FME, but showed less neural activity in all activated regions. The facial areas in M1 were distinguishable from other body movements such as finger movement. Further investigation of this area showed that forehead and mouth imagery tended to lack a somatotopic representation for position on M1, and yet had distinct characteristics in terms of neural activity level. FMI showed different characteristics from general MI as the former exclusively activated facial processing areas. In addition, FME and FMI showed different characteristics in terms of BOLD signal level, while sharing the same neural areas. The results imply a potential usefulness of MI training for rehabilitation of facial motor disease considering that forehead and mouth somatotopy showed no clear position difference, and yet showed a significant BOLD signal intensity variation.

Impact of real-time fMRI working memory feedback training on the interactions between three core brain networks

Working memory (WM) refers to the temporary holding and manipulation of information during the performance of a range of cognitive tasks, and WM training is a promising method for improving an individual’s cognitive functions. Our previous work demonstrated that WM performance can be improved through self-regulation of dorsal lateral prefrontal cortex (PFC) activation using real-time functional magnetic resonance imaging (rtfMRI), which enables individuals to control local brain activities volitionally according to the neurofeedback. Furthermore, research concerning large-scale brain networks has demonstrated that WM training requires the engagement of several networks, including the central executive network (CEN), the default mode network (DMN) and the salience network (SN), and functional connectivity within the CEN and DMN can be changed by WM training. Although a switching role of the SN between the CEN and DMN has been demonstrated, it remains unclear whether WM training can affect the interactions between the three networks and whether a similar mechanism also exists during the training process. In this study, we investigated the dynamic functional connectivity between the three networks during the rtfMRI feedback training using independent component analysis (ICA) and correlation analysis. The results indicated that functional connectivity within and between the three networks were significantly enhanced by feedback training, and most of the changes were associated with the insula and correlated with behavioral improvements. These findings suggest that the insula plays a critical role in the reorganization of functional connectivity among the three networks induced by rtfMRI training and in WM performance, thus providing new insights into the mechanisms of high-level functions and the clinical treatment of related functional impairments.

Functional connectivity alteration after real-time fMRI motor imagery training through self-regulation of activities of the right premotor cortex

Background

Real-time functional magnetic resonance imaging technology (real-time fMRI) is a novel method that can be used to investigate motor imagery training, it has attracted increasing attention in recent years, due to its ability to facilitate subjects in regulating the activities of specific brain regions to influence their behaviors. Lots of researchers have demonstrated that the right premotor area play critical roles during real-time fMRI motor imagery training. Thus, it has been hypothesized that modulating the activity of right premotor area may result in an alteration of the functional connectivity between the premotor area and other motor-related regions.

Results

The results indicated that the functional connectivity between the bilateral premotor area and right posterior parietal lobe significantly decreased during the imagination task.

Conclusions

This finding is new evidence that real-time fMRI is effective and can provide a theoretical guidance for the alteration of the motor function of brain regions associated with motor imagery training.

Electronic supplementary material

The online version of this article (doi:10.1186/s12868-015-0167-1) contains supplementary material, which is available to authorized users.

Improvement in precision grip force control with self-modulation of primary motor cortex during motor imagery

Motor imagery (MI) has shown effectiveness in enhancing motor performance. This may be due to the common neural mechanisms underlying MI and motor execution (ME). The main region of the ME network, the primary motor cortex (M1), has been consistently linked to motor performance. However, the activation of M1 during motor imagery is controversial, which may account for inconsistent rehabilitation therapy outcomes using MI. Here, we examined the relationship between contralateral M1 (cM1) activation during MI and changes in sensorimotor performance. To aid cM1 activity modulation during MI, we used real-time fMRI neurofeedback-guided MI based on cM1 hand area blood oxygen level dependent (BOLD) signal in healthy subjects, performing kinesthetic MI of pinching. We used multiple regression analysis to examine the correlation between cM1 BOLD signal and changes in motor performance during an isometric pinching task of those subjects who were able to activate cM1 during motor imagery. Activities in premotor and parietal regions were used as covariates. We found that cM1 activity was positively correlated to improvements in accuracy as well as overall performance improvements, whereas other regions in the sensorimotor network were not. The association between cM1 activation during MI with performance changes indicates that subjects with stronger cM1 activation during MI may benefit more from MI training, with implications toward targeted neurotherapy.

Neurofeedback of the difference in activation of the anterior cingulate cortex and posterior insular cortex: two functionally connected areas in the processing of pain

The aim of this study was the analysis of the effect of a learned increase in the dissociation between the rostral anterior cingulate cortex (rACC) and the left posterior insula (pInsL) on pain intensity and unpleasantness and the contribution of each region to the effect, exploring the possibility to influence the perception of pain with neurofeedback methods. We trained ten healthy subjects to increase the difference in the blood oxygenation level-dependent response between the rACC and pInsL to painful electric stimuli. Subjects learned to increase the dissociation with either the rACC (state 1) or the pInsL (state 2) being higher. For feedback we subtracted the signal of one region from the other and provided feedback in four conditions with six trials each yielding two different states: [rACC-pInsL increase (state 1), rACC-pInsL decrease (state 2), pInsL-rACC increase (state 2), pInsL-rACC decrease (state 1)]. Significant changes in the dissociation from trial one to six were seen in all conditions. There were significant changes from trial one to six in the pInsL in three of the four conditions, the rACC showed no significant change. Pain intensity or unpleasantness ratings were unrelated to the dissociation between the regions and the activation in each region. Learning success in the conditions did not significantly correlate and there was no significant correlation between the two respective conditions of one state, i.e., learning to achieve a specific state is not a stable ability. The pInsL seems to be the driving force behind changes in the learned dissociation between the regions. Despite successful differential modulation of activation in areas responsive to the painful stimulus, no corresponding changes in the perception of pain intensity or unpleasantness emerged. Learning to induce different states of dissociation between the areas is not a stable ability since success did not correlate overall or between two conditions of the the same state.

Real-time functional MRI neurofeedback: a tool for psychiatry

PURPOSE OF REVIEW

The aim of this review is to provide a critical overview of recent research in the field of neuroscientific and clinical application of real-time functional MRI neurofeedback (rtfMRI-nf).

RECENT FINDINGS

RtfMRI-nf allows self-regulating activity in circumscribed brain areas and brain systems. Furthermore, the learned regulation of brain activity has an influence on specific behaviors organized by the regulated brain regions. Patients with mental disorders show abnormal activity in certain regions, and simultaneous control of these regions using rtfMRI-nf may affect the symptoms of related behavioral disorders.

SUMMARY

The promising results in clinical application indicate that rtfMRI-nf and other metabolic neurofeedback, such as near-infrared spectroscopy, might become a potential therapeutic tool. Further research is still required to examine whether rtfMRI-nf is a useful tool for psychiatry because there is still lack of knowledge about the neural function of certain brain systems and about neuronal markers for specific mental illnesses.

Online spatial normalization for real-time FMRI

Real-time functional magnetic resonance imaging (rtfMRI) is a recently emerged technique that demands fast data processing within a single repetition time (TR), such as a TR of 2 seconds. Data preprocessing in rtfMRI has rarely involved spatial normalization, which can not be accomplished in a short time period. However, spatial normalization may be critical for accurate functional localization in a stereotactic space and is an essential procedure for some emerging applications of rtfMRI. In this study, we introduced an online spatial normalization method that adopts a novel affine registration (AFR) procedure based on principal axes registration (PA) and Gauss-Newton optimization (GN) using the self-adaptive β parameter, termed PA-GN(β) AFR and nonlinear registration (NLR) based on discrete cosine transform (DCT). In AFR, PA provides an appropriate initial estimate of GN to induce the rapid convergence of GN. In addition, the β parameter, which relies on the change rate of cost function, is employed to self-adaptively adjust the iteration step of GN. The accuracy and performance of PA-GN(β) AFR were confirmed using both simulation and real data and compared with the traditional AFR. The appropriate cutoff frequency of the DCT basis function in NLR was determined to balance the accuracy and calculation load of the online spatial normalization. Finally, the validity of the online spatial normalization method was further demonstrated by brain activation in the rtfMRI data.

Optimizing real time fMRI neurofeedback for therapeutic discovery and development

While reducing the burden of brain disorders remains a top priority of organizations like the World Health Organization and National Institutes of Health, the development of novel, safe and effective treatments for brain disorders has been slow. In this paper, we describe the state of the science for an emerging technology, real time functional magnetic resonance imaging (rtfMRI) neurofeedback, in clinical neurotherapeutics. We review the scientific potential of rtfMRI and outline research strategies to optimize the development and application of rtfMRI neurofeedback as a next generation therapeutic tool. We propose that rtfMRI can be used to address a broad range of clinical problems by improving our understanding of brain–behavior relationships in order to develop more specific and effective interventions for individuals with brain disorders. We focus on the use of rtfMRI neurofeedback as a clinical neurotherapeutic tool to drive plasticity in brain function, cognition, and behavior. Our overall goal is for rtfMRI to advance personalized assessment and intervention approaches to enhance resilience and reduce morbidity by correcting maladaptive patterns of brain function in those with brain disorders.

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Guidelines are proposed for studies of rtfMRI neurofeedback for clinical therapeutics.

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Evidence-based guidelines are needed for clinical trials of rtfMRI neurofeedback.

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These guidelines will shape the design of future clinical trials.