Neurofeedback Using Real-Time Near-Infrared Spectroscopy Enhances Motor Imagery Related Cortical Activation

Accumulating evidence indicates that motor imagery and motor execution share common neural networks. Accordingly, mental practices in the form of motor imagery have been implemented in rehabilitation regimes of stroke patients with favorable results. Because direct monitoring of motor imagery is difficult, feedback of cortical activities related to motor imagery (neurofeedback) could help to enhance efficacy of mental practice with motor imagery. To determine the feasibility and efficacy of a real-time neurofeedback system mediated by near-infrared spectroscopy (NIRS), two separate experiments were performed. Experiment 1 was used in five subjects to evaluate whether real-time cortical oxygenated hemoglobin signal feedback during a motor execution task correlated with reference hemoglobin signals computed off-line. Results demonstrated that the NIRS-mediated neurofeedback system reliably detected oxygenated hemoglobin signal changes in real-time. In Experiment 2, 21 subjects performed motor imagery of finger movements with feedback from relevant cortical signals and irrelevant sham signals. Real neurofeedback induced significantly greater activation of the contralateral premotor cortex and greater self-assessment scores for kinesthetic motor imagery compared with sham feedback. These findings suggested the feasibility and potential effectiveness of a NIRS-mediated real-time neurofeedback system on performance of kinesthetic motor imagery. However, these results warrant further clinical trials to determine whether this system could enhance the effects of mental practice in stroke patients

Functional magnetic resonance imaging neurofeedback-guided motor imagery training and motor training for Parkinson's Disease: randomized trial

Objective: Real-time functional magnetic resonance imaging (rt-fMRI) neurofeedback (NF) uses feedback of the patient’s own brain activity to self-regulate brain networks which in turn could lead to a change in behavior and clinical symptoms. The objective was to determine the effect of NF and motor training (MOT) alone on motor and non-motor functions in Parkinson’s Disease (PD) in a 10-week small Phase I randomized controlled trial. Methods: Thirty patients with Parkinson’s disease (PD; Hoehn and Yahr I-III) and no significant comorbidity took part in the trial with random allocation to two groups. Group 1 (NF: 15 patients) received rt-fMRI-NF with MOT. Group 2 (MOT: 15 patients) received MOT alone. The primary outcome measure was the Movement Disorder Society—Unified PD Rating Scale-Motor scale (MDS-UPDRS-MS), administered pre- and post-intervention “off-medication”. The secondary outcome measures were the “on-medication” MDS-UPDRS, the PD Questionnaire-39, and quantitative motor assessments after 4 and 10 weeks. Results: Patients in the NF group were able to upregulate activity in the supplementary motor area (SMA) by using motor imagery. They improved by an average of 4.5 points on the MDS-UPDRS-MS in the “off-medication” state (95% confidence interval: −2.5 to −6.6), whereas the MOT group improved only by 1.9 points (95% confidence interval +3.2 to −6.8). The improvement in the intervention group meets the minimal clinically important difference which is also on par with other non-invasive therapies such as repetitive Transcranial Magnetic Stimulation (rTMS). However, the improvement did not differ significantly between the groups. No adverse events were reported in either group. Interpretation: This Phase I study suggests that NF combined with MOT is safe and improves motor symptoms immediately after treatment, but larger trials are needed to explore its superiority over active control conditions

Basal ganglia-cortical connectivity underlies self-regulation of brain oscillations in humans

Brain-Computer Interface操作の得手不得手に関わる脳回路を発見 --操作を「考える」か「感じる」か、個人差に合わせた技術開発へ期待--. 京都大学プレスリリース. 2022-08-10.Brain-computer interfaces provide an artificial link by which the brain can directly interact with the environment. To achieve fine brain-computer interface control, participants must modulate the patterns of the cortical oscillations generated from the motor and somatosensory cortices. However, it remains unclear how humans regulate cortical oscillations, the controllability of which substantially varies across individuals. Here, we performed simultaneous electroencephalography (to assess brain-computer interface control) and functional magnetic resonance imaging (to measure brain activity) in healthy participants. Self-regulation of cortical oscillations induced activity in the basal ganglia-cortical network and the neurofeedback control network. Successful self-regulation correlated with striatal activity in the basal ganglia-cortical network, through which patterns of cortical oscillations were likely modulated. Moreover, basal ganglia-cortical network and neurofeedback control network connectivity correlated with strong and weak self-regulation, respectively. The findings indicate that the basal ganglia-cortical network is important for self-regulation, the understanding of which should help advance brain-computer interface technology

Insula as the Interface Between Body Awareness and Movement: A Neurofeedback-Guided Kinesthetic Motor Imagery Study in Parkinson’s Disease

Intentional movement is an internally driven process that requires the integration of motivational and sensory cues with motor preparedness. In addition to the motor cortical-basal ganglia circuits, the limbic circuits are also involved in the integration of these cues. Individuals with Parkinson’s disease (PD) have a particular difficulty with internally generating intentional movements and maintaining the speed, size, and vigor of movements. This difficulty improves when they are provided with external cues suggesting that there is a problem with the internal motivation of movement in PD. The prevailing view attributes this difficulty in PD to the dysfunction of motor cortical-basal ganglia circuits. First, we argue that the standard cortical-basal ganglia circuit model of motor dysfunction in PD needs to be expanded to include the insula which is a major hub within the limbic circuits. We propose a neural circuit model highlighting the interaction between the insula and dorsomedial frontal cortex which is involved in generating intentional movements. The insula processes a wide range of sensory signals arising from the body and integrates them with the emotional and motivational context. In doing so, it provides the impetus to the dorsomedial frontal cortex to initiate and sustain movement. Second, we present the results of our proof-of-concept experiment demonstrating that the functional connectivity of the insula-dorsomedial frontal cortex circuit can be enhanced with neurofeedback-guided kinesthetic motor imagery using functional magnetic resonance imaging in subjects with PD. Specifically, we found that the intensity and quality of body sensations evoked during motor imagery and the emotional and motivational context of motor imagery determined the direction (i.e., negative or positive) of the insula-dorsomedial frontal cortex functional connectivity. After 10–12 neurofeedback sessions and “off-line” practice of the successful motor imagery strategies all subjects showed a significant increase in the insula-dorsomedial frontal cortex functional connectivity. Finally, we discuss the implications of these results regarding motor function in patients with PD and propose suggestions for future studies

Power Spectral Density and Functional Connectivity Changes due to a Sensorimotor Neurofeedback Training: A Preliminary Study

Neurofeedback is a form of neuromodulation based on learning to modify some aspects of cortical activity. Sensorimotor rhythm (SMR) oscillation is one of the most used frequency bands in neurofeedback. Several studies have shown that subjects can learn to modulate SMR power to control output devices, but little is known about possible related changes in brain networks. The aim of this study was to investigate the enhanced performance and changes in EEG power spectral density at somatosensory cerebral areas due to a bidirectional modulation-based SMR neurofeedback training. Furthermore, we also analyzed the functional changes in somatosensory areas during resting state induced by the training as exploratory procedure. A six-session neurofeedback protocol based on learning to synchronize and desynchronize (modulate) the SMR was implemented. Moreover, half of the participants were enrolled in two functional magnetic resonance imaging resting-state sessions (before and after the training). At the end of the training, participants showed a successful performance enhancement, an increase in SMR power specific to somatosensory locations, and higher functional connectivity between areas associated with somatosensory activity in resting state. Our research increases the better understanding of the relation between EEG neuromodulation and functional changes and the use of SMR training in clinical practice.This work was supported by grants from Bial Foundation (#385-14), PSI2017-88388-C4-1-R (AEI/FEDER, UE), and the Spanish Ministerio de Economía, Industria y Competitividad (ref: PSI2013-48260-C3-1-R and PSI2014-57231-R)

Neurofeedback with fMRI: A Critical Systematic Review

Neurofeedback relying on functional magnetic resonance imaging (fMRI-nf) heralds new prospects for self-regulating brain and behavior. Here we provide the first comprehensive review of the fMRI-nf literature and the first systematic database of fMRI-nf findings. We synthesize information from 99 fMRI-nf experiments—the bulk of currently available data. The vast majority of fMRI-nf findings suggest that self-regulation of specific brain signatures seems viable; however, replication of concomitant behavioral outcomes remains sparse. To disentangle placebo influences and establish the specific effects of neurofeedback, we highlight the need for double-blind placebo-controlled studies alongside rigorous and standardized statistical analyses. Before fMRI-nf can join the clinical armamentarium, research must first confirm the sustainability, transferability, and feasibility of fMRI-nf in patients as well as in healthy individuals. Whereas modulating specific brain activity promises to mold cognition, emotion, thought, and action, reducing complex mental health issues to circumscribed brain regions may represent a tenuous goal. We can certainly change brain activity with fMRI-nf. However, it remains unclear whether such changes translate into meaningful behavioral improvements in the clinical domain

Real-time fMRI connectivity neurofeedback for modulation of the motor system

Advances in functional magnetic resonance imaging (fMRI) have enabled an understanding of the neural mechanisms underlying human brain functions such as motor functions. In recent decades fMRI, which is a non-invasive and highresolution technique, has been used to investigate the functions of the human brain using the blood oxygen level dependent (BOLD) response as an indirect measurement of brain neural activities. Real-time fMRI (rt-fMRI) has been used as neurofeedback to enable individuals to regulate their neural activity to achieve improvements in their health and performance, such as their motor performance. Neurofeedback can be defined as the measurement of the neural activity of a participant that is presented to them as visual or auditory signals that enable self-regulation of neural activity. Rt-fMRI has also been used to provide feedback about the connectivity between brain regions. Such connectivity neurofeedback can be a more effective feedback strategy than providing feedback from a single region. Recently, connectivity neurofeedback has been explored to examine how functional connectivity of cortical areas and subcortical areas of the brain can be modulated. Enhancing connectivity between cortical and subcortical regions holds promise for the improvement of performance, particularly motor function performance. The aim of this PhD research was to modulate connectivity neurofeedback by using real-time fMRI neurofeedback (rt-fMRI-NF) between brain regions and to investigate whether any possible enhancement in the activation due to a successful fMRI-NF will translate into changes in behavioural measures. The thesis research began with experimental work to establish the experimental paradigm. This included work, using fMRI, to develop and test localisers for different motor areas such as primary motor cortex (M1), supplementary motor cortex (SMA), the motor cerebellum and the motor thalamus. The results showed that the execution of actions, such as hand clenching, can be used to functionally activate many motor areas including M1, SMA and the cerebellum. The motor thalamus was localised using a motor thalamus mask that was created offline using the Talairach atlas. All localisers tested in this research were feasible and able to be used for applications such as rt-fMRI-NF research to define the regions of interest. The first rt-fMRI connectivity neurofeedback experimental study of this thesis was conducted to determine whether healthy participants can use neurofeedback to enhance the connectivity between M1 and the thalamus using rt-fMRI. It also aimed to investigate whether successful rt-fMRI-NF of M1- thalamus connectivity could translate into changes in behavioural measures. For this purpose, the behavioural tasks were conducted before and after each MRI session. Two behavioural tasks were used in this experiment: Go/No Go and switching tasks. The results of this experiment showed a significant increase in connectivity neurofeedback in the experimental group (M1-thalamus), hence, rt-fMRI-NF is a useful tool to modulate functional connectivity between M1 and the thalamus using motor imagery and it facilitates the learning by participants of new mental strategies to upregulate M1-thalamus connectivity. The behavioural tasks showed a significant reduction in the switching time in the experimental group while Go/No Go task did not show a significant reduction in the reaction time in the experimental group. The second rt-fMRI connectivity neurofeedback experimental study of this thesis was conducted to investigate the ability of neurofeedback to modulate M1-cerebellum connectivity using motor imagery based rt-fMRI-NF. The results of this research showed enhanced connectivity between M1 and the cerebellum in each participant. However, this enhancement was not statistically significant. In summary, this PhD thesis extends and validates the usefulness of connectivity neurofeedback using motor imagery based rt-fMRI to modulate the correlation between cortical and subcortical brain regions. Successful modulation using this technique has the potential to lead to an enhancement in motor functions. Thereby, the results of this PhD research may help to advance connectivity neurofeedback for use as a supplementary treatment for many brain disorders such as stroke recovery and Parkinson’s disease

Functional Magnetic Resonance Imaging Neurofeedback-guided Motor Imagery Training and Motor Training for Parkinson’s Disease: Randomized Trial

Objective: Real-time functional magnetic resonance imaging (rt-fMRI) neurofeedback (NF) uses feedback of the patient’s own brain activity to self-regulate brain networks which in turn could lead to a change in behaviour and clinical symptoms. The objective was to determine the effect of neurofeedback and motor training and motor training (MOT) alone on motor and non-motor functions in Parkinson’s disease (PD) in a 10-week small Phase I randomised controlled trial. Methods: 30 patients with PD (Hoehn & Yahr I-III) and no significant comorbidity took part in the trial with random allocation to two groups. Group 1 (NF: 15 patients) received rt-fMRI-NF with motor training. Group 2 (MOT: 15 patients) received motor training alone. The primary outcome measure was the Movement Disorder Society – Unified Parkinson’s Disease Rating Scale-Motor scale (MDS-UPDRS-MS), administered pre- and post-intervention ‘off-medication’. The secondary outcome measures were the ‘on-medication’ MDS-UPDRS, the Parkinson’s disease Questionnaire-39, and quantitative motor assessments after 4 and 10 weeks. Results: Patients in the NF group were able to upregulate activity in the supplementary motor area by using motor imagery. They improved by an average of 4.5 points on the MDS-UPDRS-MS in the ‘off-medication’ state (95% confidence interval: -2.5 to -6.6), whereas the MOT group improved only by 1.9 points (95% confidence interval +3.2 to -6.8). However, the improvement did not differ significantly between the groups. No adverse events were reported in either group. Interpretation: This Phase I study suggests that NF combined with motor training is safe and improves motor symptoms immediately after treatment, but larger trials are needed to explore its superiority over active control conditions. Clinical Trial website : Unique Identifier: NCT01867827 URL: https://clinicaltrials.gov/ct2/show/NCT01867827?term=NCT01867827&rank=

Real-time functional magnetic resonance imaging neurofeedback in motor neurorehabilitation

Purpose of review Recent developments in functional magnetic resonance imaging (fMRI) have catalyzed a new field of translational neuroscience. Using fMRI to monitor the aspects of task-related changes in neural activation or brain connectivity, investigators can offer feedback of simple or complex neural signals/patterns back to the participant on a quasireal-time basis [real-time-fMRI-based neurofeedback (rt-fMRI-NF)]. Here, we introduce some background methodology of the new developments in this field and give a perspective on how they may be used in neurorehabilitation in the future. Recent findings The development of rt-fMRI-NF has been used to promote self-regulation of activity in several brain regions and networks. In addition, and unlike other noninvasive techniques, rt-fMRI-NF can access specific subcortical regions and in principle any region that can be monitored using fMRI including the cerebellum, brainstem and spinal cord. In Parkinson’s disease and stroke, rt-fMRI-NF has been demonstrated to alter neural activity after the self-regulation training was completed and to modify specific behaviours. Summary Future exploitation of rt-fMRI-NF could be used to induce neuroplasticity in brain networks that are involved in certain neurological conditions. However, currently, the use of rt-fMRI-NF in randomized, controlled clinical trials is in its infancy

One session of fMRI-Neurofeedback training on motor imagery modulates whole-brain effective connectivity and dynamical complexity

In the past decade, several studies have shown that Neurofeedback (NFB) by functional magnetic resonance imaging can alter the functional coupling of targeted and non-targeted areas. However, the causal mechanisms underlying these changes remain uncertain. Here, we applied a whole-brain dynamical model to estimate Effective Connectivity (EC) profiles of resting-state data acquired before and immediately after a single-session NFB training for 17 participants who underwent motor imagery NFB training and 16 healthy controls who received sham feedback. Within-group and between-group classification analyses revealed that only for the NFB group it was possible to accurately discriminate between the 2 resting-state sessions. NFB training-related signatures were reflected in a support network of direct connections between areas involved in reward processing and implicit learning, together with regions belonging to the somatomotor, control, attention, and default mode networks, identified through a recursive-feature elimination procedure. By applying a data-driven approach to explore NFB-induced changes in spatiotemporal dynamics, we demonstrated that these regions also showed decreased switching between different brain states (i.e. metastability) only following real NFB training. Overall, our findings contribute to the understanding of NFB impact on the whole brain's structure and function by shedding light on the direct connections between brain areas affected by NFB training