Posterior cingulate cortex targeted real-time fMRI neurofeedback recalibrates functional connectivity with the amygdala, posterior insula, and default-mode network in PTSD.

BACKGROUND: Alterations within large-scale brain networks-namely, the default mode (DMN) and salience networks (SN)-are present among individuals with posttraumatic stress disorder (PTSD). Previous real-time functional magnetic resonance imaging (fMRI) and electroencephalography neurofeedback studies suggest that regulating posterior cingulate cortex (PCC; the primary hub of the posterior DMN) activity may reduce PTSD symptoms and recalibrate altered network dynamics. However, PCC connectivity to the DMN and SN during PCC-targeted fMRI neurofeedback remains unexamined and may help to elucidate neurophysiological mechanisms through which these symptom improvements may occur. METHODS: Using a trauma/emotion provocation paradigm, we investigated psychophysiological interactions over a single session of neurofeedback among PTSD (n = 14) and healthy control (n = 15) participants. We compared PCC functional connectivity between regulate (in which participants downregulated PCC activity) and view (in which participants did not exert regulatory control) conditions across the whole-brain as well as in a priori specified regions-of-interest. RESULTS: During regulate as compared to view conditions, only the PTSD group showed significant PCC connectivity with anterior DMN (dmPFC, vmPFC) and SN (posterior insula) regions, whereas both groups displayed PCC connectivity with other posterior DMN areas (precuneus/cuneus). Additionally, as compared with controls, the PTSD group showed significantly greater PCC connectivity with the SN (amygdala) during regulate as compared to view conditions. Moreover, linear regression analyses revealed that during regulate as compared to view conditions, PCC connectivity to DMN and SN regions was positively correlated to psychiatric symptoms across all participants. CONCLUSION: In summary, observations of PCC connectivity to the DMN and SN provide emerging evidence of neural mechanisms underlying PCC-targeted fMRI neurofeedback among individuals with PTSD. This supports the use of PCC-targeted neurofeedback as a means by which to recalibrate PTSD-associated alterations in neural connectivity within the DMN and SN, which together, may help to facilitate improved emotion regulation abilities in PTSD.

Increased top-down control of emotions during symptom provocation working memory tasks following a RCT of alpha-down neurofeedback in PTSD.

BACKGROUND: Posttraumatic stress disorder (PTSD) has been found to be associated with emotion under-modulation from the prefrontal cortex and a breakdown of the top-down control of cognition and emotion. Novel adjunct therapies such as neurofeedback (NFB) have been shown to normalize aberrant neural circuits that underlie PTSD psychopathology at rest. However, little evidence exists for NFB-linked neural improvements under emotionally relevant cognitive load. The current study sought to address this gap by examining the effects of alpha-down NFB in the context of an emotional n-back task. METHODS: We conducted a 20-week double-blind randomized, sham-controlled trial of alpha-down NFB and collected neuroimaging data before and after the NFB protocol. Participants performed an emotional 1-back and 2-back working memory task, with interleaved trauma-neutral and trauma-relevant cues in the fMRI scanner. Data from 35 participants with a primary diagnosis of PTSD were analyzed in this study (n = 18 in the experimental group undergoing alpha-down NFB, n = 17 in the sham-control group). RESULTS: Firstly, within-group analyses showed clinically significant reductions in PTSD symptom severity scores at the post-intervention timepoint and 3-month follow-up for the experimental group, and not for the sham-control group. The neuroimaging analyses revealed that alpha-down NFB enhanced engagement of top-down cognitive and emotional control centers, such as the dorsolateral prefrontal cortex (dlPFC), and improved integration of the anterior and posterior parts of the default mode network (DMN). Finally, our results also indicate that increased alpha-down NFB performance correlated with increased activity in brain regions involved in top-down control and bodily consciousness/embodied processing of self (TPJ and posterior insula). CONCLUSION: This is the first study to provide mechanistic insights into how NFB may normalize dysfunctional brain activity and connectivity in PTSD under cognitive load with simultaneous symptom provocation, adding to a growing body of evidence supporting the therapeutic neuromodulatory effects of NFB. This preliminary study highlights the benefits of alpha-down NFB training as an adjunctive therapy for PTSD and warrants further investigation into its therapeutic effects on cognitive and emotion control in those with PTSD.

Differential mechanisms of posterior cingulate cortex downregulation and symptom decreases in posttraumatic stress disorder and healthy individuals using real-time fMRI neurofeedback.

BACKGROUND: Intrinsic connectivity networks, including the default mode network (DMN), are frequently disrupted in individuals with posttraumatic stress disorder (PTSD). The posterior cingulate cortex (PCC) is the main hub of the posterior DMN, where the therapeutic regulation of this region with real-time fMRI neurofeedback (NFB) has yet to be explored. METHODS: We investigated PCC downregulation while processing trauma/stressful words over 3 NFB training runs and a transfer run without NFB (total n = 29, PTSD n = 14, healthy controls n = 15). We also examined the predictive accuracy of machine learning models in classifying PTSD versus healthy controls during NFB training. RESULTS: Both the PTSD and healthy control groups demonstrated reduced reliving symptoms in response to trauma/stressful stimuli, where the PTSD group additionally showed reduced symptoms of distress. We found that both groups were able to downregulate the PCC with similar success over NFB training and in the transfer run, although downregulation was associated with unique within-group decreases in activation within the bilateral dmPFC, bilateral postcentral gyrus, right amygdala/hippocampus, cingulate cortex, and bilateral temporal pole/gyri. By contrast, downregulation was associated with increased activation in the right dlPFC among healthy controls as compared to PTSD. During PCC downregulation, right dlPFC activation was negatively correlated to PTSD symptom severity scores and difficulties in emotion regulation. Finally, machine learning algorithms were able to classify PTSD versus healthy participants based on brain activation during NFB training with 80% accuracy. CONCLUSIONS: This is the first study to investigate PCC downregulation with real-time fMRI NFB in both PTSD and healthy controls. Our results reveal acute decreases in symptoms over training and provide converging evidence for EEG-NFB targeting brain networks linked to the PCC.

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.

Predictors of real-time fMRI neurofeedback performance and improvement - A machine learning mega-analysis.

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.

Consensus on the reporting and experimental design of clinical and cognitive-behavioural neurofeedback studies (CRED-nf checklist).

Neurofeedback has begun to attract the attention and scrutiny of the scientific and medical mainstream. Here, neurofeedback researchers present a consensus-derived checklist that aims to improve the reporting and experimental design standards in the field.

A randomized, controlled trial of alpha-rhythm EEG neurofeedback in posttraumatic stress disorder: A preliminary investigation showing evidence of decreased PTSD symptoms and restored default mode and salience network connectivity using fMRI.

OBJECTIVE: The default-mode network (DMN) and salience network (SN) have been shown to display altered connectivity in posttraumatic stress disorder (PTSD). Restoring aberrant connectivity within these networks with electroencephalogram neurofeedback (EEG-NFB) has been shown previously to be associated with acute decreases in symptoms. Here, we conducted a double-blind, sham-controlled randomized trial of alpha-rhythm EEG-NFB in participants with PTSD (n = 36) over 20-weeks. Our aim was to provide mechanistic evidence underlying clinical improvements by examining changes in network connectivity via fMRI. METHODS: We randomly assigned participants with a primary diagnosis of PTSD to either the experimental group (n = 18) or sham-control group (n = 18). We collected resting-state fMRI scans pre- and post-NFB intervention, for both the experimental and sham-control PTSD groups. We further compared baseline brain connectivity measures pre-NFB to age-matched healthy controls (n = 36). RESULTS: With regard to the primary outcome measure of PTSD severity, we found a significant main effect of time in the absence of a group × time interaction. Nevertheless, we found significantly decreased PTSD severity scores in the experimental NFB group only, when comparing post-NFB (dz = 0.71) and 3-month follow-up scores (dz = 0.77) to baseline measures. Interestingly, we found evidence to suggest a shift towards normalization of DMN and SN connectivity post-NFB in the experimental group only. Both decreases in PTSD severity and NFB performance were correlated to DMN and SN connectivity post-NFB in the experimental group. Critically, remission rates of PTSD were significant higher in the experimental group (61.1%) as compared to the sham-control group (33.3%). CONCLUSION: The current study shows mechanistic evidence for therapeutic changes in DMN and SN connectivity that are known to be associated with PTSD psychopathology with no patient dropouts. This preliminary investigation merits further research to demonstrate fully the clinical efficacy of EEG-NFB as an adjunctive therapy for PTSD.

Intrinsic connectivity network dynamics in PTSD during amygdala downregulation using real-time fMRI neurofeedback: A preliminary analysis.

Posttraumatic stress disorder (PTSD) has been associated with a disturbance in neural intrinsic connectivity networks (ICN), including the central executive network (CEN), default mode network (DMN), and salience network (SN). Here, we conducted a preliminary investigation examining potential changes in ICN recruitment as a function of real-time fMRI neurofeedback (rt-fMRI-NFB) during symptom provocation where we targeted the downregulation of neural response within the amygdala-a key region-of-interest in PTSD neuropathophysiology. Patients with PTSD (n = 14) completed three sessions of rt-fMRI-NFB with the following conditions: (a) regulate: decrease activation in the amygdala while processing personalized trauma words; (b) view: process trauma words while not attempting to regulate the amygdala; and (c) neutral: process neutral words. We found that recruitment of the left CEN increased over neurofeedback runs during the regulate condition, a finding supported by increased dlPFC activation during the regulate as compared to the view condition. In contrast, DMN task-negative recruitment was stable during neurofeedback runs, albeit was the highest during view conditions and increased (normalized) during rest periods. Critically, SN recruitment was high for both the regulate and the view conditions, a finding potentially indicative of CEN modality switching, adaptive learning, and increasing threat/defense processing in PTSD. In conclusion, this study provides provocative, preliminary evidence that downregulation of the amygdala using rt-fMRI-NFB in PTSD is associated with dynamic changes in ICN, an effect similar to those observed using EEG modalities of neurofeedback.