Visual imagery during real-time fMRI neurofeedback from occipital and superior parietal cortex

Abstract Visual imagery has been suggested to recruit occipital cortex via feedback projections from fronto-parietal regions, suggesting that these feedback projections might be exploited to boost recruitment of occipital cortex by means of real-time neurofeedback. To test this prediction, we instructed a group of healthy participants to perform peripheral visual imagery while they received real-time auditory feedback based on the BOLD signal from either early visual cortex or the medial superior parietal lobe. We examined the amplitude and temporal aspects of the BOLD response in the two regions. Moreover, we compared the impact of self-rated mental focus and vividness of visual imagery on the BOLD responses in these two areas. We found that both early visual cortex and the medial superior parietal cortex are susceptible to auditory neurofeedback within a single feedback session per region. However, the signal in parietal cortex was sustained for a longer time compared to the signal in occipital cortex. Moreover, the BOLD signal in the medial superior parietal lobe was more affected by focus and vividness of the visual imagery than early visual cortex. Our results thus demonstrate that (a) participants can learn to self-regulate the BOLD signal in early visual and parietal cortex within a single session, (b) that different nodes in the visual imagery network respond differently to neurofeedback, and that (c) responses in parietal, but not in occipital cortex are susceptible to self-rated vividness of mental imagery. Together, these results suggest that medial superior parietal cortex might be a suitable candidate to provide real-time feedback to patients suffering from visual field defects

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

Applications of realtime fMRI for non-invasive brain computer interface-decoding and neurofeedback

Non-invasive brain-computer interfaces (BCIs) seek to enable or restore brain function by using neuroimaging e.g. functional magnetic resonance imaging (fMRI), to engage brain activations without the need for explicit behavioural output or surgical implants. Brain activations are converted into output signals, for use in communication interfaces, motor prosthetics, or to directly shape brain function via a feedback loop. The aim of this thesis was to develop cognitive BCIs using realtime fMRI (rt-fMRI), with the potential for use as a communication interface, or for initiating neural plasticity to facilitate neurorehabilitation. Rt-fMRI enables brain activation to be manipulated directly to produce changes in function, such as perception. Univariate and multivariate classification approaches were used to decode brain activations produced by the deployment of covert spatial attention to simple visual stimuli. Primary and higher order visual areas were examined, as well as potential control regions. The classification platform was then developed to include the use of real-world visual stimuli, exploiting the use of category-specific visual areas, and demonstrating real-world applicability as a communications interface. Online univariate classification of spatial attention was successfully achieved, with individual classification accuracies for 4-quadrant spatial attention reaching 70%. Further, a novel implementation of m-sequences enabled the use of the timing of stimuli presentation to enhance signal characterisation. An established rt-fMRI analysis loop was then used for neurofeedback-led manipulation of category-specific visual brain regions, modulating their functioning, and, as a result, biasing visual perception during binocular rivalry. These changes were linked with functional and effective connectivity changes in trained regions, as well as in a putative top-down control region. The work presented provides proof-of-principle for non-invasive BCIs using rt-fMRI, with the potential for translation into the clinical environment. Decoding and 4 neurofeedback applied to non-invasive and implantable BCIs form an evolving continuum of options for enabling and restoring brain function

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

A tale of two targets: examining the differential effects of posterior cingulate cortex- and amygdala-targeted fMRI-neurofeedback in a PTSD pilot study

IntroductionReal-time fMRI-based neurofeedback (rt-fMRI-NFB) is a non-invasive technology that enables individuals to self-regulate brain activity linked to neuropsychiatric symptoms, including those associated with post-traumatic stress disorder (PTSD). Selecting the target brain region for neurofeedback-mediated regulation is primarily informed by the neurobiological characteristics of the participant population. There is a strong link between PTSD symptoms and multiple functional disruptions in the brain, including hyperactivity within both the amygdala and posterior cingulate cortex (PCC) during trauma-related processing. As such, previous rt-fMRI-NFB studies have focused on these two target regions when training individuals with PTSD to regulate neural activity. However, the differential effects of neurofeedback target selection on PTSD-related neural activity and clinical outcomes have not previously been investigated.MethodsHere, we compared whole-brain activation and changes in PTSD symptoms between PTSD participants (n = 28) that trained to downregulate activity within either the amygdala (n = 14) or the PCC (n = 14) while viewing personalized trauma words.ResultsFor the PCC as compared to the amygdala group, we observed decreased neural activity in several regions implicated in PTSD psychopathology – namely, the bilateral cuneus/precuneus/primary visual cortex, the left superior parietal lobule, the left occipital pole, and the right superior temporal gyrus/temporoparietal junction (TPJ) – during target region downregulation using rt-fMRI-NFB. Conversely, for the amygdala as compared to the PCC group, there were no unique (i.e., over and above that of the PCC group) decreases in neural activity. Importantly, amygdala downregulation was not associated with significantly improved PTSD symptoms, whereas PCC downregulation was associated with reduced reliving and distress symptoms over the course of this single training session. In this pilot analysis, we did not detect significant between-group differences in state PTSD symptoms during neurofeedback. As a critical control, the PCC and amygdala groups did not differ in their ability to downregulate activity within their respective target brain regions. This indicates that subsequent whole-brain neural activation results can be attributed to the effects of the neurofeedback target region selection in terms of neurophysiological function, rather than as a result of group differences in regulatory success.ConclusionIn this study, neurofeedback-mediated downregulation of the PCC was differentially associated with reduced state PTSD symptoms and simultaneous decreases in PTSD-associated brain activity during a single training session. This novel analysis may guide researchers in choosing a neurofeedback target region in future rt-fMRI-NFB studies and help to establish the clinical efficacy of specific neurofeedback targets for PTSD. A future multi-session clinical trial of rt-fMRI-NFB that directly compares between PCC and amygdala target regions is warranted

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

Motor Imagery and Action Observation as Effective Tools for Physical Therapy

Motor imagery and action observation facilitate motor recovery of patients because both the motor imagery and the action observation share the activation of cortical neural networks implicated in movement execution. Specifically, imagery, observation, and execution activate the medial parietal area of the brain located between the parieto‐occipital sulcus and the posterior end of the cingulate sulcus. This chapter reviews the neural mechanisms and clinical studies of motor imagery and action observation and discusses the applications in physical therapy

Progressive modulation of resting‑state brain activity during neurofeedback of positive‑social emotion regulation networks

Neurofeedback allows for the self-regulation of brain circuits implicated in specific maladaptive behaviors, leading to persistent changes in brain activity and connectivity. Positive-social emotion regulation neurofeedback enhances emotion regulation capabilities, which is critical for reducing the severity of various psychiatric disorders. Training dorsomedial prefrontal cortex (dmPFC) to exert a top-down influence on bilateral amygdala during positive-social emotion regulation progressively (linearly) modulates connectivity within the trained network and induces positive mood. However, the processes during rest that interleave the neurofeedback training remain poorly understood. We hypothesized that short resting periods at the end of training sessions of positive-social emotion regulation neurofeedback would show alterations within emotion regulation and neurofeedback learning networks. We used complementary model-based and data-driven approaches to assess how resting-state connectivity relates to neurofeedback changes at the end of training sessions. In the experimental group, we found lower progressive dmPFC self-inhibition and an increase of connectivity in networks engaged in emotion regulation, neurofeedback learning, visuospatial processing, and memory. Our findings highlight a large-scale synergy between neurofeedback and resting-state brain activity and connectivity changes within the target network and beyond. This work contributes to our understanding of concomitant learning mechanisms post training and facilitates development of efficient neurofeedback training.publishedVersio