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

Systematic balance exercises influence cortical activation and serum BDNF levels in older adults

We sought to investigate whether systematic balance training modulates brain area activity responsible for postural control and influence brain-derived neurotrophic factor (BDNF) mRNA protein expression. Seventy-four older adults were randomly divided into three groups (mean age 65.34 ± 3.79 years, 30 females): Classic balance exercises (CBT), virtual reality balance exercises (VBT), and control (CON). Neuroimaging studies were performed at inclusion and after completion of the training or 12 weeks later (CON). Blood samples were obtained to measure BDNF expression. The study revealed significant interaction of sessions and groups: In the motor imagery (MI) condition for supplementary motor area (SMA) activity (Fat peak = 5.25, p < 0.05); in the action observation (AO) condition for left and right supramarginal gyrus/posterior insula (left: Fat peak = 6.48, p < 0.05; right: Fat peak = 6.92, p < 0.05); in the action observation together with motor imagery (AOMI) condition for the middle occipital gyrus (laterally)/area V5 (left: Fat peak = 6.26, p < 0.05; right: Fat peak = 8.37, p < 0.05), and in the cerebellum–inferior semilunar lobule/tonsil (Fat peak = 5.47, p < 0.05). After the training serum BDNF level has increased in CBT (p < 0.001) and in CBT compared to CON (p < 0.05). Systematic balance training may reverse the age-related cortical over-activations and appear to be a factor mediating neuroplasticity in older adults

Probing fMRI brain connectivity and activity changes during emotion regulation by EEG neurofeedback

Despite the existence of several emotion regulation studies using neurofeedback, interactions among a small number of regions were evaluated, and therefore, further investigation is needed to understand the interactions of the brain regions involved in emotion regulation. We implemented electroencephalography (EEG) neurofeedback with simultaneous functional magnetic resonance imaging (fMRI) using a modified happiness-inducing task through autobiographical memories to upregulate positive emotion. Then, an explorative analysis of whole brain regions was done to understand the effect of neurofeedback on brain activity and the interaction of whole brain regions involved in emotion regulation. The participants in the control and experimental groups were asked to do emotion regulation while viewing positive images of autobiographical memories and getting sham or real (based on alpha asymmetry) EEG neurofeedback, respectively. The proposed multimodal approach quantified the effects of EEG neurofeedback in changing EEG alpha power, fMRI blood oxygenation level-dependent (BOLD) activity of prefrontal, occipital, parietal, and limbic regions (up to 1.9% increase), and functional connectivity in/between prefrontal, parietal, limbic system, and insula in the experimental group. New connectivity links were identified by comparing the brain functional connectivity between experimental conditions (Upregulation and View blocks) and also by comparing the brain connectivity of the experimental and control groups. Psychometric assessments confirmed significant changes in positive and negative mood states in the experimental group by neurofeedback. Based on the exploratory analysis of activity and connectivity among all brain regions involved in emotion regions, we found significant BOLD and functional connectivity increases due to EEG neurofeedback in the experimental group, but no learning effect was observed in the control group. The results reveal several new connections among brain regions as a result of EEG neurofeedback which can be justified according to emotion regulation models and the role of those regions in emotion regulation and recalling positive autobiographical memories

Rehabilitation Strategies and Key Related Mechanisms Involved in Stroke Recovery

Poststroke rehabilitation requires a thorough understanding of the neural mechanisms underlying motor function recovery. This chapter outlines these mechanisms and also discusses the corresponding rehabilitation strategies based on the functional characteristics of the brain. The main topics we discuss are as follows: Although ipsilateral brain region activity is inhibited when using the limbs under normal conditions, it is thought that a decrease in this inhibition and the subsequent increased ipsilateral brain area activity post-injury promote recovery in the damaged contralateral neural network. For optimal poststroke motor function recovery, it is important to normalize the resulting imbalance in brain activity. Therefore, increased corticomotor excitation in the injured hemisphere or decreased excitation in the non-injured hemisphere must be promoted. Rehabilitation strategies include reducing non-paretic limb somatosensory input to decrease excitation in the non-injured hemisphere, increasing paretic limb somatosensory input to increase excitation in the injured hemisphere, increasing excitation in the injured hemisphere through movement training of the paretic hand and anesthesia of the paretic upper arm, increasing excitation in the injured hemisphere, or reducing excitation in the non-injured hemisphere. Considering the functional characteristics of the primary motor area, during the early stages after stroke, it is important to increase the somatosensory input to the paralyzed side and combine mental practices using motor imagery

Real‐time biofeedback integrated into neuromuscular training reduces high‐risk knee biomechanics and increases functional brain connectivity: A preliminary longitudinal investigation

Prospective evidence indicates that functional biomechanics and brain connectivity may predispose an athlete to an anterior cruciate ligament injury, revealing novel neural linkages for targeted neuromuscular training interventions. The purpose of this study was to determine the efficacy of a real‐time biofeedback system for altering knee biomechanics and brain functional connectivity. Seventeen healthy, young, physically active female athletes completed 6 weeks of augmented neuromuscular training (aNMT) utilizing real‐time, interactive visual biofeedback and 13 served as untrained controls. A drop vertical jump and resting state functional magnetic resonance imaging were separately completed at pre‐ and posttest time points to assess sensorimotor adaptation. The aNMT group had a significant reduction in peak knee abduction moment (pKAM) compared to controls (p = .03, d = 0.71). The aNMT group also exhibited a significant increase in functional connectivity between the right supplementary motor area and the left thalamus (p = .0473 after false discovery rate correction). Greater percent change in pKAM was also related to increased connectivity between the right cerebellum and right thalamus for the aNMT group (p = .0292 after false discovery rate correction, r2 = .62). No significant changes were observed for the controls (ps > .05). Our data provide preliminary evidence of potential neural mechanisms for aNMT‐induced motor adaptations that reduce injury risk. Future research is warranted to understand the role of neuromuscular training alone and how each component of aNMT influences biomechanics and functional connectivity.Emergent evidence indicates that the risk of anterior cruciate ligament (ACL) injury is, in part, due to central nervous system alterations that could be targeted using neural mechanistic sensorimotor‐based treatments. Young female athletes completed 6 weeks of neuromuscular training while interacting with a real‐time, visual biofeedback stimulus. Our training was designed to reduce the risk of by (a) promoting injury‐resistant movement and (b) strengthening brain functional connectivity. Our data not only indicated that athletes’ biomechanics and brain connectivity were improved following training, but the observed biomechanical improvements were related to distinct, strengthened connectivity within regions important for sensorimotor control. This study supports the use of real‐time biofeedback systems to reduce the risk of ACL injury by leveraging neuroplasticity.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154933/1/psyp13545_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154933/2/psyp13545.pd

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

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