fMRI Neurofeedback Research Articles

Online self-evaluation of fMRI-based neurofeedback performance.

This study explores the subjective evaluation of supplementary motor area (SMA) regulation performance in a real-time functional magnetic resonance imaging neurofeedback (fMRI-NF) task. In fMRI-NF, people learn how to self-regulate their brain activity by performing mental actions to achieve a certain target level (TL) of blood-oxygen-level-dependent (BOLD) activation. Here, we studied two types of self-evaluation: performance predictions and perceived confidence in the prediction judgement. Participants completed three sessions of SMA regulation in a 7 T fMRI scanner, performing a mental drawing task. During each trial, they modulated their imagery strategy to achieve one of two different levels of SMA activation and reported a performance prediction and their confidence in the prediction before receiving delayed BOLD-activation feedback. Results show that participants' performance predictions improved with learning throughout the three sessions, and that these improvements were not driven exclusively by their knowledge of previous performance. Confidence reports on the other hand showed no change throughout training and did not correlate with better and worse predictions. In addition to shedding light on mechanisms of internal self-evaluation during neurofeedback training, these results also point to a dissociation between predictions of performance and confidence reports in the presence of feedback. This article is part of the theme issue 'Neurofeedback: new territories and neurocognitive mechanisms of endogenous neuromodulation'.

Effects of fMRI neurofeedback of right inferior frontal cortex on inhibitory brain activation in children with ADHD.

We aimed to replicate previous effects of functional magnetic resonance imaging neurofeedback (fMRI-NF) in right inferior frontal cortex (rIFC) on IFC activation during a Stop Task in a larger group of boys with attention-deficit/hyperactivity disorder (ADHD). The present double-blind, randomized controlled trial tested the effects of 15 runs of active versus sham fMRI-NF of rIFC on performance and activation associated with successful and failed inhibition versus Go trials during a tracking Stop task in 88 boys with ADHD (44 active; 44 sham), controlling for age and medication status. No significant group-by-time interaction effects were observed for performance or brain activation during the successful stop trials, and post hoc analysis showed very low numbers of active fMRI-NF learners. Nevertheless, during error monitoring, there was a significant group-by-time interaction effect on post-error reaction time slowing and in left IFC activation, which were both increased after active compared to sham fMRI-NF. The findings are in line with our previous observation of left IFC upregulation after fMRI-NF of rIFC relative to active fMRI-NF of parahippocampal gyrus. This highlights the potentially wider regional effects that fMRI-NF of a particular self-control target region has on other self-regulatory regions in ADHD. This article is part of the theme issue 'Neurofeedback: new territories and neurocognitive mechanisms of endogenous neuromodulation'.

Regulation of craving for real-time fMRI neurofeedback based on individual classification.

In previous real-time functional magnetic resonance imaging neurofeedback (rtfMRI-NF) studies on smoking craving, the focus has been on within-region activity or between-region connectivity, neglecting the potential predictive utility of broader network activity. Moreover, there is debate over the use and relative predictive power of individual-specific and group-level classifiers. This study aims to further advance rtfMRI-NF for substance use disorders by using whole-brain rtfMRI-NF to assess smoking craving-related brain patterns, evaluate the performance of group-level or individual-level classification (n = 31) and evaluate the performance of an optimized classifier across repeated NF runs. Using real-time individual-level classifiers derived from whole-brain support vector machines, we found that classification accuracy between crave and no-crave conditions and between repeated NF runs increased across repeated runs at both individual and group levels. In addition, individual-level accuracy was significantly greater than group-level accuracy, highlighting the potential increased utility of an individually trained whole-brain classifier for volitional control over brain patterns to regulate smoking craving. This study provides evidence supporting the feasibility of using whole-brain rtfMRI-NF to modulate smoking craving-related brain responses and the potential for learning individual strategies through optimization across repeated feedback runs. This article is part of the theme issue 'Neurofeedback: new territories and neurocognitive mechanisms of endogenous neuromodulation'.

Semantic fMRI neurofeedback of emotions: from basic principles to clinical applications.

During fMRI neurofeedback participants learn to self-regulate activity in relevant brain areas and networks based on ongoing feedback extracted from measured responses in those regions. This closed-loop approach has been successfully applied to reduce symptoms in mood disorders such as depression by showing participants a thermometer-like display indicating the strength of activity in emotion-related brain areas. The hitherto employed conventional neurofeedback is, however, 'blind' with respect to emotional content, i.e. patients instructed to engage in a specific positive emotion could drive the neurofeedback signal by engaging in a different (positive or negative) emotion. In this future perspective, we present a new form of neurofeedback that displays semantic information of emotions to the participant. Semantic information is extracted online using real-time representational similarity analysis of emotion-specific activity patterns. The extracted semantic information can be provided to participants in a two-dimensional semantic map depicting the current mental state as a point reflecting its distance to pre-measured emotional mental states (e.g. 'happy', 'content', 'sad', 'angry'). This new approach provides transparent feedback during self-regulation training, and it has the potential to enable more specific training effects for future therapeutic applications such as clinical interventions in mood disorders.This article is part of the theme issue 'Neurofeedback: new territories and neurocognitive mechanisms of endogenous neuromodulation'.

Modulating subjective pain perception with decoded Montreal Neurological Institute-space neurofeedback: a proof-of-concept study.

Pain is a complex emotional experience that still remains challenging to manage. Previous functional magnetic resonance imaging (fMRI) studies have associated pain with distributed patterns of brain activity (i.e. brain decoders), but it is still unclear whether these observations reflect causal mechanisms. To address this question, we devised a new neurofeedback approach using real-time decoding of fMRI data to test if modulating pain-related multivoxel fMRI patterns could lead to changes in subjective pain experience. We first showed that subjective pain ratings can indeed be accurately predicted using a real-time decoding approach based on the stimulus intensity independent pain signature (SIIPS) and the neurologic pain signature (NPS). Next, we trained participants (n = 16) in a double-blinded decoded fMRI neurofeedback experiment to up- or downregulate the SIIPS. Our results indicate that participants can learn to downregulate the expression of SIIPS independently from NPS expression. Importantly, the success of this neurofeedback training was associated with the perceived intensity of painful stimulation following the intervention. Taken together, these results indicate that closed-loop brain imaging can be efficiently conducted using a priori fMRI decoders of pain, potentially opening up a new range of applications for decoded neurofeedback, both for clinical and basic science purposes. This article is part of the theme issue 'Neurofeedback: new territories and neurocognitive mechanisms of endogenous neuromodulation'.

FMRI neurofeedback for the modulation of the neural networks associated with depression

ObjectivesFunctional magnetic resonance imaging (fMRI) neurofeedback has emerged as a potential treatment modality for depression, but little is known about its mechanism of action. This study aims to investigate the efficacy of fMRI neurofeedback in modulating neural networks in depression. MethodsFollowing PRISMA guidelines, a systematic review was conducted focusing on fMRI neurofeedback interventions in depression. A comprehensive search across multiple databases yielded 16 eligible studies for review. ResultsThe review demonstrated that fMRI neurofeedback can modulate BOLD activity even in strategy-free protocols and within a single session, with a significant learning effect evident over sessions. Neurofeedback targeting specific regions led to changes in connectivity across broad neural networks, including the default-mode and executive control networks, with effects being region-specific. However, methodological diversity and the absence of standardized protocols in the reviewed studies highlighted the need for more uniform research approaches. ConclusionsfMRI neurofeedback shows promise as a modulatory technique for depression, with the potential to induce significant changes in neural activity and connectivity of networks implicated in depression. SignificanceThe review underscores the necessity for standardized, reproducible neurofeedback protocols with control groups to enhance research comparability and generalizability.

Real-Time fMRI Neurofeedback Training of Selective Attention in Older Adults.

Selective attention declines with age, due to age-related functional changes in dorsal anterior cingulate cortex (dACC). Real-time functional magnetic resonance imaging (rtfMRI) neurofeedback has been used in young adults to train volitional control of brain activity, including in dACC. For the first time, this study used rtfMRI neurofeedback to train 19 young and 27 older adults in volitional up- or down-regulation of bilateral dACC during a selective attention task. Older participants in the up-regulation condition (experimental group) showed greater reward points and dACC BOLD signal across training sessions, reflective of neurofeedback training success; and faster reaction time and better response accuracy, suggesting behavioral benefits on selective attention. These effects were not observed for older participants in the down-regulation condition (inverse condition control group), supporting specificity of volitional dACC up-regulation training in older adults. These effects were, unexpectedly, also not observed for young participants in the up-regulation condition (age control group), perhaps due to a lack of motivation to continue the training. These findings provide promising first evidence of functional plasticity in dACC in late life via rtfMRI neurofeedback up-regulation training, enhancing selective attention, and demonstrate proof of concept of rtfMRI neurofeedback training in cognitive aging.

Real-time fMRI neurofeedback modulates induced hallucinations and underlying brain mechanisms

Hallucinations can occur in the healthy population, are clinically relevant and frequent symptoms in many neuropsychiatric conditions, and have been shown to mark disease progression in patients with neurodegenerative disorders where antipsychotic treatment remains challenging. Here, we combine MR-robotics capable of inducing a clinically-relevant hallucination, with real-time fMRI neurofeedback (fMRI-NF) to train healthy individuals to up-regulate a fronto-parietal brain network associated with the robotically-induced hallucination. Over three days, participants learned to modulate occurrences of and transition probabilities to this network, leading to heightened sensitivity to induced hallucinations after training. Moreover, participants who became sensitive and succeeded in fMRI-NF training, showed sustained and specific neural changes after training, characterized by increased hallucination network occurrences during induction and decreased hallucination network occurrences during a matched control condition. These data demonstrate that fMRI-NF modulates specific hallucination network dynamics and highlights the potential of fMRI-NF as a novel antipsychotic treatment in neurodegenerative disorders and schizophrenia.

Whole-brain mechanism of neurofeedback therapy: predictive modeling of neurofeedback outcomes on repetitive negative thinking in depression

Real-time fMRI neurofeedback (rtfMRI-NF) has emerged as a promising intervention for psychiatric disorders, yet its clinical efficacy remains underexplored due to an incomplete mechanistic understanding. This study aimed to delineate the whole-brain mechanisms underpinning the effects of rtfMRI-NF on repetitive negative thinking in depression. In a double-blind randomized controlled trial, forty-three depressed individuals underwent NF training targeting the functional connectivity (FC) between the posterior cingulate cortex and the right temporoparietal junction, linked to rumination severity. Participants were randomly assigned to active or sham groups, with the sham group receiving synthesized feedback mimicking real NF signal patterns. The active group demonstrated a significant reduction in brooding rumination scores (d = −1.52, p < 0.001), whereas the sham group did not (d = −0.23, p = 0.503). While the target FC did not show discernible training effects or group differences, connectome-based predictive modeling (CPM) analysis revealed that the interaction between brain activity during regulation and brain response to the feedback signal was the critical factor in explaining treatment outcomes. The model incorporating this interaction successfully predicted rumination changes across both groups. The FCs significantly contributing to the prediction were distributed across brain regions, notably the frontal control, salience network, and subcortical reward processing areas. These results underscore the importance of considering the interplay between brain regulation activities and brain response to the feedback signal in understanding the therapeutic mechanisms of rtfMRI-NF. The study affirms rtfMRI-NF’s potential as a therapeutic intervention for repetitive negative thinking and highlights the need for a nuanced understanding of the whole-brain mechanisms contributing to its efficacy.

Translation of monosynaptic circuits underlying amygdala fMRI neurofeedback training.

fMRI neurofeedback using autobiographical memory recall to upregulate the amygdala is associated with resting-state functional connectivity (rsFC) changes between the amygdala and the salience and default mode networks (SN and DMN, respectively). We hypothesize the existence of anatomical circuits underlying these rsFC changes. Using a cross-species brain parcellation, we identified in non-human primates locations homologous to the regions of interest (ROIs) from studies showing pre-to-post-neurofeedback changes in rsFC with the left amygdala. We injected bidirectional tracers in the basolateral, lateral, and central amygdala nuclei of adult macaques and used bright- and dark-field microscopy to identify cells and axon terminals in each ROI (SN: anterior cingulate, ventrolateral, and insular cortices; DMN: temporal pole, middle frontal gyrus, angular gyrus, precuneus, posterior cingulate cortex, parahippocampal gyrus, hippocampus, and thalamus). We also performed additional injections in specific ROIs to validate the results following amygdala injections and delineate potential disynaptic pathways. Finally, we used high-resolution diffusion MRI data from four post-mortem macaque brains and one in vivo human brain to translate our findings to the neuroimaging domain. Different amygdala nuclei had significant monosynaptic connections with all the SN and DMN ipsilateral ROIs. Amygdala connections with the DMN contralateral ROIs are disynaptic through the hippocampus and parahippocampal gyrus. Diffusion MRI in both species benefitted from using the ground-truth tracer data to validate its findings, as we identified false-negative ipsilateral and false-positive contralateral connectivity results. This study provides the foundation for future causal investigations of amygdala neurofeedback modulation of the SN and DMN through these anatomic connections.

Self-Regulation of the Posterior-Frontal Brain Activity with Real-Time fMRI Neurofeedback to Influence Perceptual Discrimination.

The Global Neuronal Workspace (GNW) hypothesis states that the visual percept is available to conscious awareness only if recurrent long-distance interactions among distributed brain regions activate neural circuitry extending from the posterior areas to prefrontal regions above a certain excitation threshold. To directly test this hypothesis, we trained 14 human participants to increase blood oxygenation level-dependent (BOLD) signals with real-time functional magnetic resonance imaging (rtfMRI)-based neurofeedback simultaneously in four specific regions of the occipital, temporal, insular and prefrontal parts of the brain. Specifically, we hypothesized that the up-regulation of the mean BOLD activity in the posterior-frontal brain regions lowers the perceptual threshold for visual stimuli, while down-regulation raises the threshold. Our results showed that participants could perform up-regulation (Wilcoxon test, session 1: p = 0.022; session 4: p = 0.041) of the posterior-frontal brain activity, but not down-regulation. Furthermore, the up-regulation training led to a significant reduction in the visual perceptual threshold, but no substantial change in perceptual threshold was observed after the down-regulation training. These findings show that the up-regulation of the posterior-frontal regions improves the perceptual discrimination of the stimuli. However, further questions as to whether the posterior-frontal regions can be down-regulated at all, and whether down-regulation raises the perceptual threshold, remain unanswered.

The Clinical Impact of Real-Time fMRI Neurofeedback on Emotion Regulation: A Systematic Review.

Emotion dysregulation has long been considered a key symptom in multiple psychiatric disorders. Difficulties in emotion regulation have been associated with neural dysregulation in fronto-limbic circuits. Real-time fMRI-based neurofeedback (rt-fMRI-NFB) has become increasingly popular as a potential treatment for emotional dysregulation in psychiatric disorders, as it is able to directly target the impaired neural circuits. However, the clinical impact of these rt-fMRI-NFB protocols in psychiatric populations is still largely unknown. Here we provide a comprehensive overview of primary studies from 2010 to 2023 that used rt-fMRI-NFB to target emotion regulation. We assessed 41 out of 4001 original studies for methodological quality and risk of bias and synthesised concerning the frequency of significant rt-fMRI-NFB-related effects on the neural and behaviour level. Successful modulation of brain activity was reported in between 25 and 50 percent of study samples, while neural effects in clinical samples were more diverse than in healthy samples. Interestingly, the frequency of rt-fMRI-NFB-related behavioural improvement was over 75 percent in clinical samples, while healthy samples showed behavioural improvements between 0 and 25 percent. Concerning clinical subsamples, rt-fMRI-NFB-related behavioural improvement was observed in up to 100 percent of major depressive disorder (MDD) and post-traumatic stress disorder (PTSD) samples. Substance use samples showed behavioural benefits ranging between 50 and 75 percent. Neural effects appeared to be less frequent than behavioural improvements: most neural outcomes ranged between 25 and 50 percent for MDD and substance use and between 0 and 25 percent for PTSD. Using multiple individualised regions of interest (ROIs) for rt-fMRI-NFB training resulted in more frequent behavioural benefits than rt-fMRI-NFB solely based on the amygdala or the prefrontal cortex. While a significant improvement in behavioural outcomes was reported in most clinical studies, the study protocols were heterogeneous, which limits the current evaluation of rt-fMRI-NFB as a putative treatment for emotional dysregulation.

Neurofeedback training of executive function in autism spectrum disorder: distinct effects on brain activity levels and compensatory connectivity changes

BackgroundDeficits in executive function (EF) are consistently reported in autism spectrum disorders (ASD). Tailored cognitive training tools, such as neurofeedback, focused on executive function enhancement might have a significant impact on the daily life functioning of individuals with ASD. We report the first real-time fMRI neurofeedback (rt-fMRI NF) study targeting the left dorsolateral prefrontal cortex (DLPFC) in ASD.MethodsThirteen individuals with autism without intellectual disability and seventeen neurotypical individuals completed a rt-fMRI working memory NF paradigm, consisting of subvocal backward recitation of self-generated numeric sequences. We performed a region-of-interest analysis of the DLPFC, whole-brain comparisons between groups and, DLPFC-based functional connectivity.ResultsThe ASD and control groups were able to modulate DLPFC activity in 84% and 98% of the runs. Activity in the target region was persistently lower in the ASD group, particularly in runs without neurofeedback. Moreover, the ASD group showed lower activity in premotor/motor areas during pre-neurofeedback run than controls, but not in transfer runs, where it was seemingly balanced by higher connectivity between the DLPFC and the motor cortex. Group comparison in the transfer run also showed significant differences in DLPFC-based connectivity between groups, including higher connectivity with areas integrated into the multidemand network (MDN) and the visual cortex.ConclusionsNeurofeedback seems to induce a higher between-group similarity of the whole-brain activity levels (including the target ROI) which might be promoted by changes in connectivity between the DLPFC and both high and low-level areas, including motor, visual and MDN regions.

Functional and structural connectivity success predictors of real-time fMRI neurofeedback targeting DLPFC: Contributions from central executive, salience, and default mode networks.

Real-time functional magnetic resonance imaging (rt-fMRI) neurofeedback (NF), a training method for the self-regulation of brain activity, has shown promising results as a neurorehabilitation tool, depending on the ability of the patient to succeed in neuromodulation. This study explores connectivity-based structural and functional success predictors in an NF n-back working memory paradigm targeting the dorsolateral prefrontal cortex (DLPFC). We established as the NF success metric the linear trend on the ability to modulate the target region during NF runs and performed a linear regression model considering structural and functional connectivity (intrinsic and seed-based) metrics. We found a positive correlation between NF success and the default mode network (DMN) intrinsic functional connectivity and a negative correlation with the DLPFC-precuneus connectivity during the 2-back condition, indicating that success is associated with larger uncoupling between DMN and the executive network. Regarding structural connectivity, the salience network emerges as the main contributor to success. Both functional and structural classification models showed good performance with 77% and 86% accuracy, respectively. Dynamic switching between DMN, salience network and central executive network seems to be the key for neurofeedback success, independently indicated by functional connectivity on the localizer run and structural connectivity data.

Ventromedial prefrontal cortex activation and neurofeedback modulation during episodic future thinking for individuals with suicidal thoughts and behaviors

Individuals experiencing suicidal thoughts and behaviors (STBs) show less specificity and positivity during episodic future thinking (EFT). Here, we present findings from two studies aiming to (1) further our understanding of how STBs may relate to neural responsivity during EFT and (2) examine the feasibility of modulating EFT-related activation using real-time fMRI neurofeedback (rtfMRI-nf). Study 1 involved 30 individuals with major depressive disorder (MDD; half with STBs) who performed an EFT task during fMRI, for which they imagined personally-relevant future positive, negative, or neutral events. Positive EFT elicited greater ventromedial prefrontal cortex (vmPFC) activation compared to negative EFT. Importantly, the MDD + STB group exhibited reduced vmPFC activation across all EFT conditions compared to MDD-STB; although EFT fluency and subjective experience remained consistent across groups. Study 2 included rtfMRI-nf focused on vmPFC modulation during positive EFT for six participants with MDD + STBs. Results support the feasibility and acceptability of the rtfMRI-nf protocol and quantitative and qualitative observations are provided to help inform future, larger studies aiming to examine similar neurofeedback protocols. Results implicate vmPFC blunting as a promising treatment target for MDD + STBs and suggest rtfMRI-nf as one potential technique to explore for enhancing vmPFC engagement.

Amygdala real-time fMRI neurofeedback upregulation in treatment resistant depression: Proof of concept and dose determination

Previous work has shown that adults suffering from major depressive disorder (MDD) can increase their amygdala reactivity while recalling positive memories via real-time neurofeedback (rt-fMRI-nf) training, which is associated with reduction in depressive symptoms. This study investigated if this intervention could also be considered for patients suffering from MDD who do not respond to standard psychological and pharmacological interventions, i.e., treatment resistant (TR-MDD).15 participants received 5 neurofeedback sessions. Outcome measures were depressive symptoms assessed by BDI scores up to 12 weeks following acute intervention, and amygdala activity changes from initial baseline to final transfer run during neurofeedback sessions (neurofeedback success).Participants succeeded in increasing their amygdala activity. A main effect of visit on BDI scores indicated a significant reduction in depressive symptomatology. Percent signal change in the amygdala showed a learning curve during the first session only. Neurofeedback success computed by session was significantly positive only during the second session. When examining the baseline amygdala response, baseline activity stabilized/asymptoted by session 3.This proof-of-concept study suggests that only two neurofeedback sessions are necessary to enable those patients to upregulate their amygdala activity, warranting a future RCT. Over the course of the rtfMRI-nf intervention, participants also reported reduced depressive symptomatology.Clinical trial registration number: NCT03428828 on ClinicalTrials.gov.

Validation of real-time fMRI neurofeedback procedure for cognitive training using counterbalanced active-sham study design

Investigation of neural mechanisms of real-time functional MRI neurofeedback (rtfMRI-nf) training requires an efficient study control approach. A common rtfMRI-nf study design involves an experimental group, receiving active rtfMRI-nf, and a control group, provided with sham rtfMRI-nf. We report the first study in which rtfMRI-nf procedure is controlled through counterbalancing training runs with active and sham rtfMRI-nf for each participant. Healthy volunteers (n = 18) used rtfMRI-nf to upregulate fMRI activity of an individually defined target region in the left dorsolateral prefrontal cortex (DLPFC) while performing tasks that involved mental generation of a random numerical sequence and serial summation of numbers in the sequence. Sham rtfMRI-nf was provided based on fMRI activity of a different brain region, not involved in these tasks. The experimental procedure included two training runs with the active rtfMRI-nf and two runs with the sham rtfMRI-nf, in a randomized order. The participants achieved significantly higher fMRI activation of the left DLPFC target region during the active rtfMRI-nf conditions compared to the sham rtfMRI-nf conditions. fMRI functional connectivity of the left DLPFC target region with the nodes of the central executive network was significantly enhanced during the active rtfMRI-nf conditions relative to the sham conditions. fMRI connectivity of the target region with the nodes of the default mode network was similarly enhanced. fMRI connectivity changes between the active and sham conditions exhibited meaningful associations with individual performance measures on the Working Memory Multimodal Attention Task, the Approach-Avoidance Task, and the Trail Making Test. Our results demonstrate that the counterbalanced active-sham study design can be efficiently used to investigate mechanisms of active rtfMRI-nf in direct comparison to those of sham rtfMRI-nf. Further studies with larger group sizes are needed to confirm the reported findings and evaluate clinical utility of this study control approach.

Facing emotions: real-time fMRI-based neurofeedback using dynamic emotional faces to modulate amygdala activity.

Maladaptive functioning of the amygdala has been associated with impaired emotion regulation in affective disorders. Recent advances in real-time fMRI neurofeedback have successfully demonstrated the modulation of amygdala activity in healthy and psychiatric populations. In contrast to an abstract feedback representation applied in standard neurofeedback designs, we proposed a novel neurofeedback paradigm using naturalistic stimuli like human emotional faces as the feedback display where change in the facial expression intensity (from neutral to happy or from fearful to neutral) was coupled with the participant's ongoing bilateral amygdala activity. The feasibility of this experimental approach was tested on 64 healthy participants who completed a single training session with four neurofeedback runs. Participants were assigned to one of the four experimental groups (n = 16 per group), i.e., happy-up, happy-down, fear-up, fear-down. Depending on the group assignment, they were either instructed to "try to make the face happier" by upregulating (happy-up) or downregulating (happy-down) the amygdala or to "try to make the face less fearful" by upregulating (fear-up) or downregulating (fear-down) the amygdala feedback signal. Linear mixed effect analyses revealed significant amygdala activity changes in the fear condition, specifically in the fear-down group with significant amygdala downregulation in the last two neurofeedback runs as compared to the first run. The happy-up and happy-down groups did not show significant amygdala activity changes over four runs. We did not observe significant improvement in the questionnaire scores and subsequent behavior. Furthermore, task-dependent effective connectivity changes between the amygdala, fusiform face area (FFA), and the medial orbitofrontal cortex (mOFC) were examined using dynamic causal modeling. The effective connectivity between FFA and the amygdala was significantly increased in the happy-up group (facilitatory effect) and decreased in the fear-down group. Notably, the amygdala was downregulated through an inhibitory mechanism mediated by mOFC during the first training run. In this feasibility study, we intended to address key neurofeedback processes like naturalistic facial stimuli, participant engagement in the task, bidirectional regulation, task congruence, and their influence on learning success. It demonstrated that such a versatile emotional face feedback paradigm can be tailored to target biased emotion processing in affective disorders.

Exploring protocol development: Implementing systematic contextual memory to enhance real-time fMRI neurofeedback.

The goal of this study was to explore the development and implementation of a protocol for real-time fMRI neurofeedback (rtfMRI-nf) and to assess the potential for enhancing the selective brain activation using stimuli from Virtual Reality (VR). In this study we focused on two specific brain regions, supplementary motor area (SMA) and right inferior frontal gyrus (rIFG). Publications by other study groups have suggested impaired function in these specific brain regions in patients with the diagnoses Attention Deficit Hyperactivity Disorder (ADHD) and Tourette's Syndrome (TS). This study explored the development of a protocol to investigate if attention and contextual memory may be used to systematically strengthen the procedure of rtfMRI-nf. We used open-science software and platforms for rtfMRI-nf and for developing a simulated repetition of the rtfMRI-nf brain training in VR. We conducted seven exploratory tests in which we updated the protocol at each step. During rtfMRI-nf, MRI images are analyzed live while a person is undergoing an MRI scan, and the results are simultaneously shown to the person in the MRI-scanner. By focusing the analysis on specific regions of the brain, this procedure can be used to help the person strengthen conscious control of these regions. The VR simulation of the same experience involved a walk through the hospital toward the MRI scanner where the training sessions were conducted, as well as a subsequent simulated repetition of the MRI training. The VR simulation was a 2D projection of the experience.The seven exploratory tests involved 19 volunteers. Through this exploration, methods for aiming within the brain (e.g. masks/algorithms for coordinate-system control) and calculations for the analyses (e.g. calculations based on connectivity versus activity) were updated by the project team throughout the project. The final procedure involved three initial rounds of rtfMRI-nf for learning brain strategies. Then, the volunteers were provided with VR headsets and given instructions for one week of use. Afterward, a new session with three rounds of rtfMRI-nf was conducted. Through our exploration of the indirect effect parameters - brain region activity (directed oxygenated blood flow), connectivity (degree of correlated activity in different regions), and neurofeedback score - the volunteers tended to increase activity in the reinforced brain regions through our seven tests. Updates of procedures and analyses were always conducted between pilots, and never within. The VR simulated repetition was tested in pilot 7, but the role of the VR contribution in this setting is unclear due to underpowered testing. This proof-of-concept protocol implies how rtfMRI-nf may be used to selectively train two brain regions (SMA and rIFG). The method may likely be adapted to train any given region in the brain, but readers are advised to update and adapt the procedure to experimental needs.

Amygdala fMRI-A Critical Appraisal of the Extant Literature.

Even before the advent of fMRI, the amygdala occupied a central space in the affective neurosciences. Yet this amygdala-centred view on emotion processing gained even wider acceptance after the inception of fMRI in the early 1990s, a landmark that triggered a goldrush of fMRI studies targeting the amygdala in vivo. Initially, this amygdala fMRI research was mostly confined to task-activation studies measuring the magnitude of the amygdala's response to emotional stimuli. Later, interest began to shift more towards the study of the amygdala's resting-state functional connectivity and task-based psychophysiological interactions. Later still, the test-retest reliability of amygdala fMRI came under closer scrutiny, while at the same time, amygdala-based real-time fMRI neurofeedback gained widespread popularity. Each of these major subdomains of amygdala fMRI research has left its marks on the field of affective neuroscience at large. The purpose of this review is to provide a critical assessment of this literature. By integrating the insights garnered by these research branches, we aim to answer the question: What part (if any) can amygdala fMRI still play within the current landscape of affective neuroscience? Our findings show that serious questions can be raised with regard to both the reliability and validity of amygdala fMRI. These conclusions force us to cast doubt on the continued viability of amygdala fMRI as a core pilar of the affective neurosciences.