Correlation between amygdala BOLD activity and frontal EEG asymmetry during real-time fMRI neurofeedback training in patients with depression

Real-time fMRI neurofeedback (rtfMRI-nf) is an emerging approach for studies and novel treatments of major depressive disorder (MDD). EEG performed simultaneously with an rtfMRI-nf procedure allows an independent evaluation of rtfMRI-nf brain modulation effects. Frontal EEG asymmetry in the alpha band is a widely used measure of emotion and motivation that shows profound changes in depression. However, it has never been directly related to simultaneously acquired fMRI data. We report the first study investigating electrophysiological correlates of the rtfMRI-nf procedure, by combining rtfMRI-nf with simultaneous and passive EEG recordings. In this pilot study, MDD patients in the experimental group (n=13) learned to upregulate BOLD activity of the left amygdala using an rtfMRI-nf during a happy emotion induction task. MDD patients in the control group (n=11) were provided with a sham rtfMRI-nf. Correlations between frontal EEG asymmetry in the upper alpha band and BOLD activity across the brain were examined. Average individual changes in frontal EEG asymmetry during the rtfMRI-nf task for the experimental group showed a significant positive correlation with the MDD patients' depression severity ratings, consistent with an inverse correlation between the depression severity and frontal EEG asymmetry at rest. Temporal correlations between frontal EEG asymmetry and BOLD activity were significantly enhanced, during the rtfMRI-nf task, for the amygdala and many regions associated with emotion regulation. Our findings demonstrate an important link between amygdala BOLD activity and frontal EEG asymmetry. Our EEG asymmetry results suggest that the rtfMRI-nf training targeting the amygdala is beneficial to MDD patients, and that alpha-asymmetry EEG-nf would be compatible with the amygdala rtfMRI-nf. Combination of the two could enhance emotion regulation training and benefit MDD patients.Comment: 28 pages, 16 figures, to appear in NeuroImage: Clinica

Individual Variations in Nucleus Accumbens Responses Associated with Major Depressive Disorder Symptoms

Abnormal reward-related responses in the nucleus accumbens (NAcc) have been reported for major depressive disorder (MDD) patients. However, variability exists in the reported results, which could be due to heterogeneity in neuropathology of depression. To parse the heterogeneity of MDD we investigated variation of NAcc responses to gain and loss anticipations using fMRI. We found NAcc responses to monetary gain and loss were significantly variable across subjects in both MDD and healthy control (HC) groups. The variations were seen as a hyperactive response subtype that showed elevated activation to the anticipation of both gain and loss, an intermediate response with greater activation to gain than loss, and a suppressed-activity with reduced activation to both gain and loss compared to a non-monetary condition. While these response variability were seen in both MDD and HC subjects, specific symptoms were significantly associated with the right NAcc variation in MDD. Both the hyper- and suppressed-activity subtypes of MDD patients had severe suicidal ideation and anhedonia symptoms. The intermediate subjects had less severity in these symptoms. These results suggest that differing propensities in reward responsiveness in the NAcc may affect the development of specific symptoms in MDD

Real-time fMRI neurofeedback training of the amygdala activity with simultaneous EEG in veterans with combat-related PTSD

Posttraumatic stress disorder (PTSD) is a chronic and disabling neuropsychiatric disorder characterized by insufficient top-down modulation of the amygdala activity by the prefrontal cortex. Real-time fMRI neurofeedback (rtfMRI-nf) is an emerging method with potential for modifying the amygdala-prefrontal interactions. We report the first controlled emotion self-regulation study in veterans with combat-related PTSD utilizing rtfMRI-nf of the amygdala activity. PTSD patients in the experimental group (EG, n=20) learned to upregulate BOLD activity of the left amygdala (LA) using rtfMRI-nf during a happy emotion induction task. PTSD patients in the control group (CG, n=11) were provided with a sham rtfMRI-nf. The study included three rtfMRI-nf training sessions, and EEG recordings were performed simultaneously with fMRI. PTSD severity was assessed using the Clinician-Administered PTSD Scale (CAPS). The EG participants showed a significant reduction in total CAPS ratings, including significant reductions in avoidance and hyperarousal symptoms. Overall, 80% of the EG participants demonstrated clinically meaningful reductions in CAPS ratings, compared to 38% in the CG. During the first session, fMRI connectivity of the LA with the orbitofrontal cortex and the dorsolateral prefrontal cortex (DLPFC) was progressively enhanced, and this enhancement significantly and positively correlated with initial CAPS ratings. Left-lateralized enhancement in upper alpha EEG coherence also exhibited a significant positive correlation with the initial CAPS. Reduction in PTSD severity between the first and last rtfMRI-nf sessions significantly correlated with enhancement in functional connectivity between the LA and the left DLPFC. Our results demonstrate that the rtfMRI-nf of the amygdala activity has the potential to correct the amygdala-prefrontal functional connectivity deficiencies specific to PTSD.Comment: 26 pages, 16 figures, to appear in NeuroImage: Clinica

Predicting Age From Brain EEG Signals—A Machine Learning Approach

Objective: The brain age gap estimate (BrainAGE) is the difference between the estimated age and the individual chronological age. BrainAGE was studied primarily using MRI techniques. EEG signals in combination with machine learning (ML) approaches were not commonly used for the human age prediction, and BrainAGE. We investigated whether age-related changes are affecting brain EEG signals, and whether we can predict the chronological age and obtain BrainAGE estimates using a rigorous ML framework with a novel and extensive EEG features extraction.Methods: EEG data were obtained from 468 healthy, mood/anxiety, eating and substance use disorder participants (297 females) from the Tulsa-1000, a naturalistic longitudinal study based on Research Domain Criteria framework. Five sets of preprocessed EEG features across channels and frequency bands were used with different ML methods to predict age. Using a nested-cross-validation (NCV) approach and stack-ensemble learning from EEG features, the predicted age was estimated. The important features and their spatial distributions were deduced.Results: The stack-ensemble age prediction model achieved R2 = 0.37 (0.06), Mean Absolute Error (MAE) = 6.87(0.69) and RMSE = 8.46(0.59) in years. The age and predicted age correlation was r = 0.6. The feature importance revealed that age predictors are spread out across different feature types. The NCV approach produced a reliable age estimation, with features consistent behavior across different folds.Conclusion: Our rigorous ML framework and extensive EEG signal features allow a reliable estimation of chronological age, and BrainAGE. This general framework can be extended to test EEG association with and to predict/study other physiological relevant responses

TEAMwork: Testing Emotional Attunement and Mutuality During Parent-Adolescent fMRI.

The parent-child relationship and family context influence the development of emotion regulation (ER) brain circuitry and related skills in children and adolescents. Although both parents' and children's ER neurocircuitry simultaneously affect how they interact with one another, neuroimaging studies of parent-child relationships typically include only one member of the dyad in brain imaging procedures. The current study examined brain activation related to parenting and ER in parent-adolescent dyads during concurrent fMRI scanning with a novel task - the Testing Emotional Attunement and Mutuality (TEAM) task. The TEAM task includes feedback trials indicating the other dyad member made an error, resulting in a monetary loss for both participants. Results indicate that positive parenting practices as reported by the adolescent were positively correlated with parents' hemodynamic activation of the ventromedial prefrontal cortex, a region related to empathy, during these error trials. Additionally, during feedback conditions both parents and adolescents exhibited fMRI activation in ER-related regions, including the dorsolateral prefrontal cortex, anterior insula, fusiform gyrus, thalamus, caudate, precuneus, and superior parietal lobule. Adolescents had higher left amygdala activation than parents during the feedback condition. These findings demonstrate the utility of dyadic fMRI scanning for investigating relational processes, particularly in the parent-child relationship

Always on my mind: Cross-brain associations of mental health symptoms during simultaneous parent-child scanning.

How parents manifest symptoms of anxiety or depression may affect how children learn to modulate their own distress, thereby influencing the children's risk for developing an anxiety or mood disorder. Conversely, children's mental health symptoms may impact parents' experiences of negative emotions. Therefore, mental health symptoms can have bidirectional effects in parent-child relationships, particularly during moments of distress or frustration (e.g., when a parent or child makes a costly mistake). The present study used simultaneous functional magnetic resonance imaging (fMRI) of parent-adolescent dyads to examine how brain activity when responding to each other's costly errors (i.e., dyadic error processing) may be associated with symptoms of anxiety and depression. While undergoing simultaneous fMRI scans, healthy dyads completed a task involving feigned errors that indicated their family member made a costly mistake. Inter-brain, random-effects multivariate modeling revealed that parents who exhibited decreased medial prefrontal cortex and posterior cingulate cortex activation when viewing their child's costly error response had children with more symptoms of depression and anxiety. Adolescents with increased anterior insula activation when viewing a costly error made by their parent had more anxious parents. These results reveal cross-brain associations between mental health symptomatology and brain activity during parent-child dyadic error processing