BACKGROUND:Ibogaine was recently found to result in significant functional improvements in treating the sequelae of traumatic brain injury (TBI) among Special Operations Forces veterans (SOVs). In the current study, we used multimodal neuroimaging to elucidate the neural correlates of ibogaine in 30 male SOVs who received ibogaine treatment. METHODS:Arterial spin labeling and blood oxygen level-dependent functional magnetic resonance imaging data were collected before and immediately after ibogaine treatment and at 1-month follow-up. A whole-brain exploratory analysis was conducted to examine the effects of ibogaine on resting-state regional cerebral blood flow (rCBF) and functional connectivity. RESULTS:The results revealed gradual increases in rCBF in the cortical, limbic, and striatal subregions and changes in functional connectivity across a wide range of functional networks. The magnitude of treatment-induced rCBF changes in the left insula and the left anterior cingulate cortex correlated significantly with improvements in TBI-related disability symptoms. CONCLUSIONS:Our results suggest that ibogaine may involve widespread reorganization of functional connections in the brain and that persisting regional changes in metabolic activity after ibogaine treatment, particularly within paralimbic brain regions, may be related to the observed therapeutic effects of ibogaine. Our findings serve to generate future hypotheses for larger, controlled neuroimaging studies of ibogaine in humans-necessary to validate these initial findings.

Ibogaine is a psychoactive alkaloid with therapeutic potential that may promote neuroplasticity. Its effects on human brain morphometry are unknown. Thirty Special Operations Forces veterans with prior blast-induced TBI participated in an observational study in which they received ibogaine co-administered with magnesium. Structural MRIs were collected at baseline (n = 25), initial post-treatment (n = 25), and 1-month post (n = 22). Longitudinal analyses assessed cortical thickness, subcortical volume, and predicted brain age (pBA), estimated from T1 scans. pBA was significantly reduced at 1 month relative to baseline (-1.3 years). Cortical thickness analysis revealed post-treatment increases in 11 regions. Subcortical analyses revealed significant volumetric expansion in 8 regions. Magnesium-ibogaine therapy was associated with increased cortical thickness, subcortical expansion, and reduced pBA at 1 month. Although T1s are sensitive to nonstructural changes, the overall direction of effect is consistent with neuroplastic change.

Traumatic brain injury can lead to chronic psychiatric and cognitive symptoms, coupled with changes to the nature of cortical oscillations and neural complexity. Treatment with magnesium-ibogaine was recently found to improve the sequelae of traumatic brain injury, yet the effects of ibogaine on human cortical oscillations and complexity are unknown. Resting-state electroencephalography was performed prospectively before, 3.5 days after and 1 month after magnesium-ibogaine therapy in an observational, open-label study of 30 combat veterans. We assessed the effects of ibogaine on cortical oscillations and complexity and how these neurophysiological effects relate to psychiatric and cognitive outcomes of ibogaine treatment. After treatment, slower oscillations (theta-alpha) increased in power, and power at higher frequencies (beta-gamma) decreased. Accordingly, the theta/beta ratio increased post-treatment, which correlated with improved cognitive inhibition. Peak alpha frequency and neural complexity were lower after treatment, which persisted at 1-month follow-up. These neurophysiological markers correlated with improved executive function, post-traumatic stress disorder and anxiety after ibogaine. Altogether, these findings suggest reduced spatiotemporal complexity of brain activity and 'slowing' of cortical oscillations in the brain at rest after magnesium-ibogaine therapy, which may relate to psychiatric and cognitive improvements after ibogaine, thus providing key insight into the effects of ibogaine on brain function in humans. Follow-up controlled clinical trials are needed to confirm the findings from this initial single-arm trial.

Neurofeedback (NF) has emerged as a promising avenue for demonstrating process-related neuroplasticity, enabling self-regulation of brain function. NF targeting the amygdala has drawn attention to therapeutic potential in psychiatry, by potentially harnessing emotion-regulation processes. However, not all individuals respond equally to NF training, possibly owing to varying self-regulation abilities. This underscores the importance of understanding the mechanisms behind successful neuromodulation (i.e. capacity). This study aimed to investigate the establishment and neural correlates of neuromodulation capacity using data from repeated sessions of amygdala electrical fingerprint (Amyg-EFP)-NF and post-training functional magnetic resonance imaging (fMRI)-NF sessions. Results from 97 participants (healthy controls and post-traumatic stress disorder and fibromyalgia patients) revealed increased Amyg-EFP neuromodulation capacity over training, associated with post-training amygdala-fMRI modulation capacity and improvements in alexithymia. Individual differenaces in this capacity were associated with pre-training amygdala reactivity and initial neuromodulation success. Additionally, amygdala downregulation during fMRI-NF co-modulated with other regions such as the posterior insula and parahippocampal gyrus. This combined modulation better explained EFP-modulation capacity and improvement in alexithymia than the amygdala modulation alone, suggesting the relevance of this broader network to gained capacity. These findings support a network-based approach for NF and highlight the need to consider individual differences in brain function and modulation capacity to optimize NF interventions. This article is part of the theme issue ‘Neurofeedback: new territories and neurocognitive mechanisms of endogenous neuromodulation’.

Traumatic brain injury (TBI) is a leading cause of disability. Sequelae can include functional impairments and psychiatric syndromes such as post-traumatic stress disorder (PTSD), depression and anxiety. Special Operations Forces (SOF) veterans (SOVs) may be at an elevated risk for these complications, leading some to seek underexplored treatment alternatives such as the oneirogen ibogaine, a plant-derived compound known to interact with multiple neurotransmitter systems that has been studied primarily as a treatment for substance use disorders. Ibogaine has been associated with instances of fatal cardiac arrhythmia, but coadministration of magnesium may mitigate this concern. In the present study, we report a prospective observational study of the Magnesium–Ibogaine: the Stanford Traumatic Injury to the CNS protocol (MISTIC), provided together with complementary treatment modalities, in 30 male SOVs with predominantly mild TBI. We assessed changes in the World Health Organization Disability Assessment Schedule from baseline to immediately (primary outcome) and 1 month (secondary outcome) after treatment. Additional secondary outcomes included changes in PTSD (Clinician-Administered PTSD Scale for DSM-5), depression (Montgomery–Åsberg Depression Rating Scale) and anxiety (Hamilton Anxiety Rating Scale). MISTIC resulted in significant improvements in functioning both immediately ( P corrected < 0.001, Cohen’s d = 0.74) and 1 month ( P corrected < 0.001, d = 2.20) after treatment and in PTSD ( P corrected < 0.001, d = 2.54), depression ( P corrected < 0.001, d = 2.80) and anxiety ( P corrected < 0.001, d = 2.13) at 1 month after treatment. There were no unexpected or serious adverse events. Controlled clinical trials to assess safety and efficacy are needed to validate these initial open-label findings. ClinicalTrials.gov registration: NCT04313712 .

OBJECTIVE:The weak link between subjective symptom-based diagnostic methods for posttraumatic psychopathology and objectively measured neurobiological indices forms a barrier to the development of effective personalized treatments. To overcome this problem, recent studies have aimed to stratify psychiatric disorders by identifying consistent subgroups based on objective neural markers. Along these lines, a promising 2021 study by Stevens et al. identified distinct brain-based biotypes associated with different longitudinal patterns of posttraumatic symptoms. Here, the authors conducted a conceptual nonexact replication of that study using a comparable data set from a multimodal longitudinal study of recent trauma survivors.METHODS:A total of 130 participants (mean age, 33.61 years, SD=11.21; 48% women) admitted to a general hospital emergency department following trauma exposure underwent demographic, clinical, and neuroimaging assessments 1, 6, and 14 months after trauma. All analyses followed the pipeline outlined in the original study and were conducted in collaboration with its authors.RESULTS:Task-based functional MRI conducted 1 month posttrauma was used to identify four clusters of individuals based on profiles of neural activity reflecting threat and reward reactivity. These clusters were not identical to the previously identified brain-based biotypes and were not associated with prospective symptoms of posttraumatic psychopathology.CONCLUSIONS:Overall, these findings suggest that the original brain-based biotypes of trauma resilience and psychopathology may not generalize to other populations. Thus, caution is warranted when attempting to define subtypes of psychiatric vulnerability using neural indices before treatment implications can be fully realized. Additional replication studies are needed to identify more stable and generalizable neuroimaging-based biotypes of posttraumatic psychopathology.

BackgroundThe modulation of brain circuits of emotion is a promising pathway to treat borderline personality disorder (BPD). Precise and scalable approaches have yet to be established. Two studies investigating the amygdala-related electrical fingerprint (Amyg-EFP) in BPD are presented: one study addressing the deep-brain correlates of Amyg-EFP, and a second study investigating neurofeedback (NF) as a means to improve brain self-regulation.MethodsStudy 1 combined electroencephalography (EEG) and simultaneous functional magnetic resonance imaging to investigate the replicability of Amyg-EFP-related brain activation found in the reference dataset (N = 24 healthy subjects, 8 female; re-analysis of published data) in the replication dataset (N = 16 female individuals with BPD). In the replication dataset, we additionally explored how the Amyg-EFP would map to neural circuits defined by the research domain criteria. Study 2 investigated a 10-session Amyg-EFP NF training in parallel to a 12-weeks residential dialectical behavior therapy (DBT) program. Fifteen patients with BPD completed the training, N = 15 matched patients served as DBT-only controls.ResultsStudy 1 replicated previous findings and showed significant amygdala blood oxygenation level dependent activation in a whole-brain regression analysis with the Amyg-EFP. Neurocircuitry activation (negative affect, salience, and cognitive control) was correlated with the Amyg-EFP signal. Study 2 showed Amyg-EFP modulation with NF training, but patients received reversed feedback for technical reasons, which limited interpretation of results.ConclusionsRecorded via scalp EEG, the Amyg-EFP picks up brain activation of high relevance for emotion. Administering Amyg-EFP NF in addition to standardized BPD treatment was shown to be feasible. Clinical utility remains to be investigated.

Background: Amygdala activity dysregulation plays a central role in post-traumatic stress disorder (PTSD). Hence learning to self-regulate one's amygdala activity may facilitate recovery. PTSD is further characterized by abnormal contextual processing related to the traumatic memory. Therefore, provoking the personal traumatic narrative while training amygdala down-regulation could enhance clinical efficacy. We report the results of a randomized controlled trial (NCT02544971) of a novel self-neuromodulation procedure (i.e. NeuroFeedback) for PTSD, aimed at down-regulating limbic activity while receiving feedback from an auditory script of a personal traumatic narrative. To scale-up applicability, neural activity was probed by an fMRI-informed EEG model of amygdala activity, termed Amygdala Electrical Finger-Print (AmygEFP). Methods: Fifty-nine adults meeting DSM-5 criteria for PTSD were randomized between three groups: Trauma script feedback interface (Trauma-NF) or Neutral feedback interface (Neutral-NF), and a control group of No NF (to control for spontaneous recovery). Before and immediately after 15 NF training sessions patients were blindly assessed for PTSD symptoms and underwent one session of amygdala fMRI-NF for transferability testing. Follow-up clinical assessment was performed at 3-and 6-months following NF treatment. Results: Patients in both NF groups learned to volitionally down-regulate AmygEFP signal and demonstrated a greater reduction in PTSD symptoms and improved down-regulation of the amygdala during fMRI-NF, compared to the No-NF group. The Trauma-NF group presented the largest immediate clinical improvement. Conclusions: This proof-of-concept study indicates the feasibility of the AmygEFP-NF process-driven as a scalable intervention for PTSD and illustrates its clinical potential. Further investigation is warranted to elucidate the contribution of AmygEFP-NF beyond exposure and placebo effects.

Real-time fMRI neurofeedback is an increasingly popular neuroimaging technique that allows an individual to gain control over his/her own brain signals, which can lead to improvements in behavior in healthy participants as well as to improvements of clinical symptoms in patient populations. However, a considerably large ratio of participants undergoing neurofeedback training do not learn to control their own brain signals and, consequently, do not benefit from neurofeedback interventions, which limits clinical efficacy of neurofeedback interventions. As neurofeedback success varies between studies and participants, it is important to identify factors that might influence neurofeedback success. Here, for the first time, we employed a big data machine learning approach to investigate the influence of 20 different design-specific (e.g. activity vs. connectivity feedback), region of interest-specific (e.g. cortical vs. subcortical) and subject-specific factors (e.g. age) on neurofeedback performance and improvement in 608 participants from 28 independent experiments. With a classification accuracy of 60% (considerably different from chance level), we identified two factors that significantly influenced neurofeedback performance: Both the inclusion of a pre-training no-feedback run before neurofeedback training and neurofeedback training of patients as compared to healthy participants were associated with better neurofeedback performance. The positive effect of pre-training no-feedback runs on neurofeedback performance might be due to the familiarization of participants with the neurofeedback setup and the mental imagery task before neurofeedback training runs. Better performance of patients as compared to healthy participants might be driven by higher motivation of patients, higher ranges for the regulation of dysfunctional brain signals, or a more extensive piloting of clinical experimental paradigms. Due to the large heterogeneity of our dataset, these findings likely generalize across neurofeedback studies, thus providing guidance for designing more efficient neurofeedback studies specifically for improving clinical neurofeedback-based interventions. To facilitate the development of data-driven recommendations for specific design details and subpopulations the field would benefit from stronger engagement in open science research practices and data sharing.

Amygdala dysregulation is core to multiple psychiatric disorders. Real-time fMRI enables Amygdala self-modulation through NeuroFeedback (NF). Despite a surge in Amygdala-NF studies, a systematic quantification of self-modulation is lacking. Amygdala-NF dissemination is further restricted by absence of unifying framework dictating design choices and insufficient understanding of neural changes underlying successful self-modulation. The current meta-analysis of Amygdala-NF literature found that real-time feedback facilitates learned self-modulation more than placebo. Intriguingly, while we found that variability in design choices could be explained by the targeted domain, this was rarely highlighted by authors. Lastly, reanalysis of six fMRI data-sets (n=151), revealed that successful Amygdala down-modulation is coupled with deactivation of posterior insula and Default-Mode-Network major nodes, pointing to regulation related processes. While findings point to Amygdala self-modulation as a learned skill that could modify brain functionality, further placebo-controlled trials are necessary to prove clinical efficacy. We further suggest that studies should explicitly target neuro-behavioral domain, design studies accordingly and include 'target engagement' measures. We exemplify this idea through a 'process-based' NF approach for PTSD.

Neurofeedback training has been shown to influence behavior in healthy participants as well as to alleviate clinical symptoms in neurological, psychosomatic, and psychiatric patient populations. However, many real-time fMRI neurofeedback studies report large inter-individual differences in learning success. The factors that cause this vast variability between participants remain unknown and their identification could enhance treatment success. Thus, here we employed a meta-analytic approach including data from 24 different neurofeedback studies with a total of 401 participants, including 140 patients, to determine whether levels of activity in target brain regions during pretraining functional localizer or no-feedback runs (i.e., self-regulation in the absence of neurofeedback) could predict neurofeedback learning success. We observed a slightly positive correlation between pretraining activity levels during a functional localizer run and neurofeedback learning success, but we were not able to identify common brain-based success predictors across our diverse cohort of studies. Therefore, advances need to be made in finding robust models and measures of general neurofeedback learning, and in increasing the current study database to allow for investigating further factors that might influence neurofeedback learning.

The original and corrected figures, and the Editorial Summary, are shown in the accompanying Publisher Correction. An amendment to this paper has been published and can be accessed via a link at the top of the paper.

The original and corrected Acknowledgements are shown in the accompanying Author Correction.

Real-time functional magnetic resonance imaging (rt-fMRI) has revived the translational perspective of neurofeedback (NF)(1). Particularly for stress management, targeting deeply located limbic areas involved in stress processing(2) has paved new paths for brain-guided interventions. However, the high cost and immobility of fMRI constitute a challenging drawback for the scalability (accessibility and cost-effectiveness) of the approach, particularly for clinical purposes(3). The current study aimed to overcome the limited applicability of rt-fMRI by using an electroencephalography (EEG) model endowed with improved spatial resolution, derived from simultaneous EEG-fMRI, to target amygdala activity (termed amygdala electrical fingerprint (Amyg-EFP))(4-6). Healthy individuals (n = 180) undergoing a stressful military training programme were randomly assigned to six Amyg-EFP-NF sessions or one of two controls (control-EEG-NF or NoNF), taking place at the military training base. The results demonstrated specificity of NF learning to the targeted Amyg-EFP signal, which led to reduced alex-ithymia and faster emotional Stroop, indicating better stress coping following Amyg-EFP-NF relative to controls. Neural target engagement was demonstrated in a follow-up fMRI-NF, showing greater amygdala blood-oxygen-level-dependent downregulation and amygdala-ventromedial prefrontal cortex functional connectivity following Amyg-EFP-NF relative to NoNF. Together, these results demonstrate limbic specificity and efficacy of Amyg-EFP-NF during a stressful period, pointing to a scalable non-pharmacological yet neuroscience-based training to prevent stress-induced psychopathology.

Amygdala hyper-activation among a-priori healthy individuals, was previously found to predict more post-traumatic symptoms following exposure. Pharmacological and behavioral approaches however do not specifically target the amygdala, possibly explaining the low efficacy of existing therapeutics. The current work tested whether amygdala targeted neurofeedback prior to- or immediately after- traumatic exposure may facilitate emotion-regulation and reduce stress vulnerability. We present results from a large scale (n=160) field study conducted with a-priori healthy Israeli soldiers and preliminary results from a clinical trial conducted with recent trauma survivors.

This paper discusses the exclusion of veterans with combat PTSD (CPTSD) from eligibility for the Purple Heart (PH). The main argument is that this exclusion is unjustified and that it strengthens the stigma attached to the traumatized veterans, with detrimental implications to their wellbeing. In the context of the politics of recognition, the history of the term PTSD, and with support evidence from brain studies, the paper contends that in the case of combat veterans, posttraumatic stress should be termed PTSI (posttraumatic stress injury) rather than PTSD (posttraumatic stress disorder). The proposed alteration in terminology may enable eligibility of posttraumatic combat veterans’ for the Purple Heart, and consequently mitigate the stigma of their wounds, help to deconstruct their misrecognition as inferior to physiologically wounded, increase their willingness to seek aid, and improve their chances to heal.