Clinical Response to Neurofeedback in Major Depression Relates to Subtypes of Whole-Brain Activation Patterns During Training.

Major Depressive Disorder (MDD) poses a significant public health challenge due to its high prevalence and the substantial burden it places on individuals and healthcare systems. Real-time functional magnetic resonance imaging neurofeedback (rtfMRI-NF) shows promise as a treatment for this disorder, although its mechanisms of action remain unclear. This study investigated whole-brain response patterns during rtfMRI-NF training to explain interindividual variability in clinical efficacy in MDD. We analyzed data from 95 participants (67 active, 28 control) with MDD from previous rtfMRI-NF studies designed to increase left amygdala activation through positive autobiographical memory recall. Significant symptom reduction was observed in the active group (t=-4.404, d=-0.704, p<0.001) but not in the control group (t=-1.609, d=-0.430, p=0.111). However, left amygdala activation did not account for the variability in clinical efficacy. To elucidate the brain training process underlying the clinical effect, we examined whole-brain activation patterns during two critical phases of the neurofeedback procedure: activation during the self-regulation period, and transient responses to feedback signal presentations. Using a systematic process involving feature selection, manifold extraction, and clustering with cross-validation, we identified two subtypes of regulation activation and three subtypes of brain responses to feedback signals. These subtypes were significantly associated with the clinical effect (regulation subtype: F=8.735, p=0.005; feedback response subtype: F=5.326, p=0.008; subtypes' interaction: F=3.471, p=0.039). Subtypes associated with significant symptom reduction were characterized by selective increases in control regions, including lateral prefrontal areas, and decreases in regions associated with self-referential thinking, such as default mode areas. These findings suggest that large-scale brain activity during training is more critical for clinical efficacy than the level of activation in the neurofeedback target region itself. Tailoring neurofeedback training to incorporate these patterns could significantly enhance its therapeutic efficacy.

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.

Recall of Autobiographical Memories Following Odor vs Verbal Cues Among Adults With Major Depressive Disorder.

Importance: Major depressive disorder (MDD) is associated with deficits in autobiographical memory (AM) recall, which is thought to stem from disruptions in effortful recall. Understanding whether these deficits are mitigated when recall is stimulated more directly, such as by odor cues, could inform therapeutic interventions for MDD. Objective: To evaluate whether deficits in specific AM recall in MDD are mitigated when odor cues vs word cues are used to prompt memory. Design, Setting, and Participants: This cross-sectional study assessed recall of specific AMs in response to both odor cues and word cues (in a randomized, counterbalanced order) in a repeated measures design. Data were collected between September 2021 and November 2022. The study took place at the University of Pittsburgh School of Medicine in Pennsylvania and included adults with a primary diagnosis of MDD, according to the Mini International Neuropsychiatric Interview. Data were analyzed from January to June 2023. Main Outcomes and Measures: The primary outcome measure was the percentage of specific AMs recalled in response to odor-cued memories vs word-cued memories. Additional outcome measures included ratings of arousal, vividness, repetition, and recall response time for odor-cued memories vs word-cued memories. Results: Thirty-two adults (mean [SD] age, 30.0 [10.1] years; 26 [81.3%] female; 6 [18.8%] male) with a primary diagnosis of MDD completed the study. Participants recalled more specific AMs for odor cues than word cues (mean [SD], 68.4% [20.4%] vs 52.1% [23.3%]; Cohen d, 0.78; P < .001). Additionally, odor-cued recall was rated more arousing (mean [SD], 3.0 [0.8] vs 2.6 [0.7]; Cohen d, 1.28; P < .001) and vivid (mean [SD], 3.3 [0.7] vs 3.0 [0.7]; Cohen d, 0.67; P < .001), and was slower than word-cued recall (mean [SD], 14.5 [3.6] vs 8.9 [3.4] seconds; Cohen d, 1.18; P < .001). When compared with the population mean for word cues in healthy controls (80%), participants recalled fewer specific memories in response to words (Cohen d, 1.18; P < .001), supporting the presence of overgenerality. Notably, the percentage of specific memories recalled in response to odor cues did not differ from the healthy control population mean (Cohen d, 0.26; P = .15). Conclusions and Relevance: In this cross-sectional study, adults with MDD recalled more specific AMs in response to odor cues compared with word cues. This study suggests that AM deficits may only be observed when verbal cues are used and provides a potential new method for increasing specific AM recall in patients with MDD.

Enhanced efficacy of CBT following augmentation with amygdala rtfMRI neurofeedback in depression.

BACKGROUND: Despite cognitive behavioral therapy (CBT) being a standard treatment in major depressive disorder (MDD), nearly half of patients do not respond. As one of the predictors of CBT's efficacy is amygdala reactivity to positive information, which is often decreased in MDD, we explored whether real-time fMRI neurofeedback (rtfMRI-nf) training to increase amygdala responses during positive memory recall prior CBT would enhance its efficacy. METHODS: In a double-blind, placebo controlled, randomized clinical trial, 35 adults with MDD received two sessions of rtfMRI-nf training to increase their amygdala (experimental group, n = 16) or parietal (control group, n = 19) responses during positive memory neurofeedback prior to receiving 10 CBT sessions. Depressive symptomatology was monitored between the rtfMRI sessions, the first three, 9th and 10th sessions of CBT and at 6 months and 1 year follow-up. RESULTS: Participants in the experimental group showed decreased depressive symptomatology and higher remission rates at 6 months and 1 year follow-up than the control group. Analysis of CBT content highlighted that participants in the experimental group focused more on positive thinking and behaviors than the control group. LIMITATIONS: The study was relatively small and not sufficiently powered to detect small effects. CONCLUSIONS: CBT, when combined with amygdala neurofeedback, results in sustained clinical changes and leads to long-lasting clinical improvement, potentially by increasing focus on positive memories and cognitions.

Real-time functional magnetic resonance imaging neurofeedback training of amygdala upregulation increases affective flexibility in depression.

BACKGROUND: Decreased affective flexibility is associated with depression symptoms, and it has been suggested that common interventions may target this mechanism. To explore this hypothesis, we evaluated whether real-time functional magnetic resonance imaging neurofeedback (rtfMRI-nf) training to increase the amygdala responses during positive memory recall resulted in both symptom improvements, as has been observed previously, and flexibility to decrease amygdala reactivity in response to a cognitive task among patients with major depressive disorder (MDD). METHODS: In a double-blind, placebo-controlled, randomized clinical trial, adults with MDD received 2 sessions of rtfMRI-nf training to increase their amygdala (experimental group) or parietal (control group) responses during positive autobiographical memory recall. We evaluated signal changes in the amygdala during both the positive memory neurofeedback and a subsequent counting condition. RESULTS: We included 38 adults with MDD, including 16 in the experimental group and 22 in the control group. In the experimental group, amygdala activity increased (t > 2.01, df < 27, p < 0.05, d > 0.5) and depressive symptoms decreased (-8.57, 95 % confidence interval [CI] -15.12 to -2.59; t 13 = -3.06, p = 0.009, d = 1). Amygdala activity during the count condition decreased after rtfMRI-nf (-0.16, 95 % CI -0.23 to -0.09; t 396 = 4.73, p < 0.001, d = 0.48) and was correlated with decreased depression scores (r = 0.46, p = 0.01). We replicated previous results and extended them to show decreased amygdala reactivity to a cognitive task during which no neurofeedback was provided. LIMITATIONS: The count condition was reported by participants as negative, but emotionality or accuracy during this condition was not assessed. CONCLUSION: These results suggest that nominally targeting unidimensional change in neural mechanisms could have implications for bidirectional control, increasing the likely reach and explanatory framework for how common depression interventions work.Trial registration: ClinicalTrials.gov NCT02709161.

Cingulate prediction of response to antidepressant and cognitive behavioral therapies for depression: Meta-analysis and empirical application.

We sought to identify baseline (pre-treatment) neural markers associated with treatment response in major depressive disorder (MDD), specific to treatment type, Cognitive Behavioral Therapy (CBT) or pharmacotherapy (selective serotonin reuptake inhibitors; SSRI). We conducted a meta-analysis of functional magnetic resonance imaging (fMRI) studies to identify neural prognostic indicators of response to CBT or SSRI. To verify the regions derived from literature, the meta-analytic regions were used to predict clinical change in a verification sample of participants with MDD who received either CBT (n = 60) or an SSRI (n = 19) as part of prior clinical trials. The meta-analysis consisted of 21 fMRI studies that used emotion-related tasks. It yielded prognostic regions of the perigenual (meta pgACC) and subgenual anterior cingulate cortex (meta sgACC), associated with SSRI and CBT response, respectively. When applying the meta-analytic regions to predict treatment response in the verification sample, reactivity of the meta pgACC was prognostic for SSRI response, yet the effect direction was opposite of most prior studies. Meta sgACC reactivity failed to be prognostic for CBT response. Results confirm the prognostic potential of neural reactivity of ACC subregions in MDD but further research is necessary for clinical translation.

Neurophysiological correlates of disorder-related autobiographical memory in anorexia nervosa.

BACKGROUND: Anorexia nervosa (AN) is characterized by an overgeneralization of food/body-related autobiographical memories (AM). This is regarded as an emotion regulation strategy with adverse long-term effects implicated in disorder maintenance and treatment resistance. Therefore, we aimed to examine neural correlates of food/body-related AM-recall in AN. METHODS: Twenty-nine female patients with AN and 30 medication-free age-sex-matched normal-weight healthy controls (HC) underwent functional magnetic resonance imaging while recalling AMs in response to food/body-related and neutral cue words. To control for general knowledge retrieval, participants engaged in a semantic generation and riser detection task. RESULTS: In comparison to HC, patients with AN generated fewer and less specific AMs in response to food/body-related words, but not for neutral cue words. Group comparisons revealed reduced activation in regions associated with self-referential processing and memory retrieval (precuneus and angular gyrus) during the retrieval of specific food/body-related AM in patients with AN. Brain connectivity in regions associated with memory functioning and executive control was reduced in patients with AN during the retrieval of specific food/body-related AM. Finally, resting-state functional connectivity analysis revealed no differences between groups, arguing against a general underlying disconnection of brain networks implicated in memory and emotional processing in AN. CONCLUSIONS: These results indicate impaired neural processing of food/body-related AM in AN, with a reduced involvement of regions involved in self-referential processing. Our findings are discussed as possible neuronal correlates of emotional avoidance in AN and provide new insights of AN-pathophysiology underscoring the importance of targeting dysfunctional emotion regulation strategies during treatment.

Importance of test-retest reliability for promoting fMRI based screening and interventions in major depressive disorder.

Proponents of personalized medicine have promoted neuroimaging in three areas of clinical application for major depression: clinical prediction, outcome evaluation, and treatment, via neurofeedback. Whereas psychometric considerations such as test-retest reliability are basic precursors to clinical adoption for most clinical instruments, we show, in this article, that basic psychometrics have not been regularly attended to in fMRI of depression. For instance, no fMRI neurofeedback study has included measures of test-retest reliability, despite the implicit assumption that brain signals are stable enough to train. We consider several factors that could be useful to aid clinical translation, including (1) attending to how the BOLD response is parameterized, (2) identifying and promoting regions or voxels with stronger psychometric properties, (3) accounting for within-individual changes (e.g., in symptomatology) across time, and (4) focusing on tasks and clinical populations that are relevant for the intended clinical application. We apply these principles to published prognostic and neurofeedback data sets. The broad implication of this work is that attention to psychometrics is important for clinical adoption of mechanistic assessment, is feasible, and may improve the underlying science.

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.

Low Cost MR Compatible Haptic Stimulation with Application to fMRI Neurofeedback.

The most common feedback displays in the fMRI environment are visual, e.g., in which participants try to increase or decrease the level of a thermometer. However, haptic feedback is increasingly valued in computer interaction tasks, particularly for real-time fMRI feedback. fMRI-neurofeedback is a clinical intervention that has not yet taken advantage of this trend. Here we describe a low-cost, user-friendly, MR-compatible system that can provide graded haptic vibrotactile stimulation in an initial application to fMRI neurofeedback. We also present a feasibility demonstration showing that we could successfully set up the system and obtain data in the context of a neurofeedback paradigm. We conclude that vibrotactile stimulation using this low-cost system is a viable method of feedback presentation, and encourage neurofeedback researchers to incorporate this type of feedback into their studies.

Response to SSRI intervention and amygdala activity during self-referential processing in major depressive disorder.

There are conflicting reports on the impact of antidepressants on neural reactions for positive information. We thus hypothesized that there would be clinically important individual differences in neural reactivity to positive information during SSRI therapy. We further predicted that only those who responded to SSRIs would show increased amygdala reactivity to positive information following treatment to a level similar to that seen in healthy participants. Depressed individuals (n = 17) underwent fMRI during performance of a task involving rating the self-relevance of emotionally positive and negative cue words before and after receiving 12 weeks of SSRI therapy. At post-treatment, SSRI responders (n = 11) had increased amygdala activity in response to positive stimuli, and decreased activity in response to negative stimuli, compared to non-responders (n = 6). Results suggest that normalizing amygdala responses to salient information is a correlate of SSRI efficacy. Second line interventions that modulate amygdala activity, such as fMRI neurofeedback, may be beneficial in those who do not respond to SSRI medications.

Can we predict real-time fMRI neurofeedback learning success from pretraining brain activity?

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.

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.

Effect of deactivation of activity patterns related to smoking cue reactivity on nicotine addiction.

With approximately 75% of smokers resuming cigarette smoking after using the Gold Standard Programme for smoking cessation, investigation into novel therapeutic approaches is warranted. Typically, smoking cue reactivity is crucial for smoking behaviour. Here we developed a novel closed-loop, smoking cue reactivity patterns EEG-based neurofeedback protocol and evaluated its therapeutic efficacy on nicotine addiction. During an evoked smoking cue reactivity task participants' brain activity patterns corresponding to smoking cues were obtained with multivariate pattern analysis of all EEG channels data, then during neurofeedback the EEG activity patterns of smoking cue reactivity were continuously deactivated with adaptive closed-loop training. In a double-blind, placebo-controlled, randomized clinical trial, 60 nicotine-dependent participants were assigned to receive two neurofeedback training sessions (∼1 h/session) either from their own brain (n = 30, real-feedback group) or from the brain activity pattern of a matched participant (n = 30, yoked-feedback group). Cigarette craving and craving-related P300 were assessed at pre-neurofeedback and post-neurofeedback. The number of cigarettes smoked per day was assessed at baseline, 1 week, 1 month, and 4 months following the final neurofeedback visit. In the real-feedback group, participants successfully deactivated EEG activity patterns of smoking cue reactivity. The real-feedback group showed significant decrease in cigarette craving and craving-related P300 amplitudes compared with the yoked-feedback group. The rates of cigarettes smoked per day at 1 week, 1 month and 4 months follow-up decreased 30.6%, 38.2%, and 27.4% relative to baseline in the real-feedback group, compared to decreases of 14.0%, 13.7%, and 5.9% in the yoked-feedback group. The neurofeedback effects on craving change and smoking amount at the 4-month follow-up were further predicted by neural markers at pre-neurofeedback. This novel neurofeedback training approach produced significant short-term and long-term effects on cigarette craving and smoking behaviour, suggesting the neurofeedback protocol described herein is a promising brain-based tool for treating addiction.

Control freaks: Towards optimal selection of control conditions for fMRI neurofeedback studies.

fMRI Neurofeedback research employs many different control conditions. Currently, there is no consensus as to which control condition is best, and the answer depends on what aspects of the neurofeedback-training design one is trying to control for. These aspects can range from determining whether participants can learn to control brain activity via neurofeedback to determining whether there are clinically significant effects of the neurofeedback intervention. Lack of consensus over criteria for control conditions has hampered the design and interpretation of studies employing neurofeedback protocols. This paper presents an overview of the most commonly employed control conditions currently used in neurofeedback studies and discusses their advantages and disadvantages. Control conditions covered include no control, treatment-as-usual, bidirectional-regulation control, feedback of an alternative brain signal, sham feedback, and mental-rehearsal control. We conclude that the selection of the control condition(s) should be determined by the specific research goal of the study and best procedures that effectively control for relevant confounding factors.

Linguistic analysis of the autobiographical memories of individuals with major depressive disorder.

BACKGROUND: Major depressive disorder (MDD) is characterized by biases in memory, attention, and cognition. The present study utilized the Linguistic Inquiry and Word Count (LIWC) to examine the content of specific autobiographical memories (AMs) recalled by individuals with MDD during an autobiographical memory task. METHODS: We examined various features of the text (including use of affective, cognitive, and self-referential terms), as well as their associations with clinical and cognitive features of MDD (depression severity, autobiographical memory specificity, amygdala activity), in 45 unmedicated adults with MDD compared to 61 healthy controls. RESULTS: When recalling positive memories MDD individuals used the word "I" less, fewer positive words, more words indicating present focus (present tense verbs), and fewer words overall to describe memories compared to controls. When recalling negative memories, MDD individuals used "I" more, more words indicating present focus, and more words overall to describe memories relative to controls. Depression severity was correlated with word count, the use of "I", and words indicating present focus in negative memories and inversely correlated with word count and the use of "I" in positive memories. Autobiographical memory specificity was correlated with word count, the use of "I", and words indicating present focus for positive memories and inversely correlated with the use of "I" and words indicating present focus for negative memories. LIMITATIONS: Due to the nature of AM recall, we could not control for the number of memories which participants recalled in each mnemonic category. CONCLUSIONS: Results align with literature implicating rumination and intensive self-focus in depression and suggest that interventions targeting specific word use may be therapeutically beneficial in the treatment of MDD.