Real-Time Functional MRI in the Treatment of Mental Health Disorders

Taschereau-Dumouchel, Vincent; Cushing, Cody; Lau, Hakwan

doi:10.1146/annurev-clinpsy-072220-014550

Cited by 17 publications

(8 citation statements)

References 138 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Increasingly, research shows that rtfMRI-NF's promise has at least partly been realized in a variety of applications. Several qualitative reviews have demonstrated that volitional control over a variety of brain region(s) and networks mediating a variety of cognitive, behavioral, and pathophysiological processes can be gained through rtfMRI-NF in psychiatric and non-psychiatric samples (Martz et al, 2020;Pindi et al, 2021;Scharnowski & Weiskopf, 2015;Sitaram et al, 2017;Taschereau-Dumouchel et al, 2022;Thibault et al, 2018;Tursic et al, 2020;Watanabe et al, 2017). A recent quantitative review of randomized controlled trials of rtfMRI-NF for psychiatric disorders demonstrated a mediumsized effect (g=.59) on the targeted brain region while actively receiving neurofeedback, and a large-sized effect (g=.84) on tests of generalization when no neurofeedback is provided .…”

Section: Introductionmentioning

confidence: 99%

Training volitional control of the theory of mind network with real-time fMRI neurofeedback

Saxena¹,

Shovestul²,

Dudek³

et al. 2023

Preprint

View full text Add to dashboard Cite

Is there a way improve our ability to understand the minds of others? Towards addressing this question, here, we conducted a single-arm, proof-of-concept study to evaluate whether real-time fMRI neurofeedback (rtfMRI-NF) from the temporo-parietal junction (TPJ) leads to volitional control of the neural network subserving theory of mind (ToM; the process by which we attribute and reason about the mental states of others). As additional aims, we evaluated the strategies used to self-regulate the network and whether volitional control of the ToM network was moderated by participant characteristics and associated with improved performance on behavioral measures. Sixteen participants underwent fMRI while completing a task designed to individually-localize the TPJ, and then three separate rtfMRI-NF scans during which they completed multiple runs of a training task while receiving intermittent, activation-based feedback from the TPJ, and one run of a transfer task in which no neurofeedback was provided. A priori region-of-interest analyses demonstrated volitional control in most regions during the training tasks and during the transfer task, although the effects were smaller in magnitude and not observed in one of the neurofeedback targets for the transfer task. Text analysis demonstrated that volitional control was most strongly associated with thinking about prior social experiences when up-regulating the neural signal. Analysis of behavioral performance and brain-behavior associations largely did not reveal behavior changes except for a positive association between volitional control in RTPJ and changes in performance on one ToM task. Together, this study demonstrates the feasibility of training volitional control of a social cognitive brain network, which may have clinical applications.

show abstract

Section: Introductionmentioning

confidence: 99%

Training volitional control of the theory of mind network with real-time fMRI neurofeedback

Saxena¹,

Shovestul²,

Dudek³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Due to these treatment difficulties, neurofeedback has been explored as a way of directly regulating brain activity in a number of mental health disorders (4)(5)(6)(7)(8)(9)(10). A promising new fMRI method called multi-voxel neuro-reinforcement (11)(12)(13) has demonstrated the ability to lessen physiological defensive responses to both laboratory-conditioned fears and pre-existing fears through a kind of 'unconscious exposure' (14)(15)(16)(17). By using a machine-learning classifier (also referred to as a 'decoder'), neuro-reinforcement can be provided based on a specific stimulus category (e.g.…”

Section: Introductionmentioning

confidence: 99%

“…By using a machine-learning classifier (also referred to as a 'decoder'), neuro-reinforcement can be provided based on a specific stimulus category (e.g. spider) rather than average brain activity alone (17). Importantly, this can be accomplished at an implicit level as participants undergoing neuro-reinforcement are simply trying to make a feedback disc on the screen grow in size with no specific instruction as to what makes the disc grow (18,19).…”

Section: Introductionmentioning

confidence: 99%

A pre-registered decoded neurofeedback intervention for specific phobias

Cushing¹,

Lau

Kawato

et al. 2023

Preprint

Self Cite

View full text Add to dashboard Cite

BackgroundTreatment attrition rates can be high for specific phobia, partly due to the subjectively aversive nature of exposure therapy that involves direct exposure to fear- and panic-inducing stimuli. A new closed-loop fMRI method called multi-voxel neuro-reinforcement has the potential to alleviate the subjective aversiveness of interventions by directly inducing phobic representations in the brain, outside of conscious awareness. The current study seeks to test this method as an intervention for specific phobia.MethodsIn a pre-registered clinical trial, individuals (N=18) with at least two animal subtype specific phobias underwent double-blind multi-voxel neuro-reinforcement for one of the two feared animals, with the untargeted one serving as control. Unaware of the target of neuro-reinforcement (i.e., the target animal), participants were guided with visual feedback and rewarded for implicit activation of the target representation. Amygdala response to phobic stimuli was assessed pre-treatment and post-treatment using photographic image presentations. Attentional capture to phobic stimuli was assessed using an affective Stroop task.ResultsConfirming our pre-registered hypothesis, a significant interaction between phobia type (target/control) and time (pre-treatment/post-treatment) was found for amygdala response. There was also a nonsignificant trend (p=0.055) for the hypothesized attentional capture during the affective Stroop. In both measures, responding to the phobia targeted with neuro-reinforcement was selectively reduced compared to the placebo control.ConclusionsResults suggest multi-voxel neuro-reinforcement has the potential to be a successful intervention for specific phobia. Multi-voxel neuro-reinforcement decreased physiological and behavioral responses to specific phobia through reduced amygdala activation and attentional capture by phobic stimuli. Consequently, multi-voxel neuro-reinforcement may complement current conventional psychotherapy approaches while providing a non-distressing experience for patients seeking treatment.

show abstract

“…Neurofeedback training has been associated with behavioral changes, which makes it an interesting approach for studying brain–behavior relationships (Sitaram et al., 2017; Sulzer, Haller et al., 2013). Neurofeedback training has also produced clinical benefits, which makes it a promising clinical intervention for the treatment of neurological and psychiatric disorders (e.g., Linhartová et al., 2019; Martz et al., 2020; Sokunbi, 2017; Sulzer, Haller et al., 2013; Taschereau‐Dumouchel et al., 2022; Wang et al., 2018). The reported effects of neurofeedback training include transient as well as lasting changes.…”

Section: Introductionmentioning

confidence: 99%

Preliminary findings on long‐term effects of fMRI neurofeedback training on functional networks involved in sustained attention

Pamplona,

Heldner,

Langner

et al. 2023

Brain and Behavior

View full text Add to dashboard Cite

IntroductionNeurofeedback based on functional magnetic resonance imaging allows for learning voluntary control over one's own brain activity, aiming to enhance cognition and clinical symptoms. We previously reported improved sustained attention temporarily by training healthy participants to up‐regulate the differential activity of the sustained attention network minus the default mode network (DMN). However, the long‐term brain and behavioral effects of this training have not yet been studied. In general, despite their relevance, long‐term learning effects of neurofeedback training remain under‐explored.MethodsHere, we complement our previously reported results by evaluating the neurofeedback training effects on functional networks involved in sustained attention and by assessing behavioral and brain measures before, after, and 2 months after training. The behavioral measures include task as well as questionnaire scores, and the brain measures include activity and connectivity during self‐regulation runs without feedback (i.e., transfer runs) and during resting‐state runs from 15 healthy individuals.ResultsNeurally, we found that participants maintained their ability to control the differential activity during follow‐up sessions. Further, exploratory analyses showed that the training increased the functional connectivity between the DMN and the occipital gyrus, which was maintained during follow‐up transfer runs but not during follow‐up resting‐state runs. Behaviorally, we found that enhanced sustained attention right after training returned to baseline level during follow‐up.ConclusionThe discrepancy between lasting regulation‐related brain changes but transient behavioral and resting‐state effects raises the question of how neural changes induced by neurofeedback training translate to potential behavioral improvements. Since neurofeedback directly targets brain measures to indirectly improve behavior in the long term, a better understanding of the brain–behavior associations during and after neurofeedback training is needed to develop its full potential as a promising scientific and clinical tool.

show abstract

Real-Time Functional MRI in the Treatment of Mental Health Disorders

Cited by 17 publications

References 138 publications

Training volitional control of the theory of mind network with real-time fMRI neurofeedback

Training volitional control of the theory of mind network with real-time fMRI neurofeedback

A pre-registered decoded neurofeedback intervention for specific phobias

Preliminary findings on long‐term effects of fMRI neurofeedback training on functional networks involved in sustained attention

Contact Info

Product

Resources

About