Unreliability of putative fMRI biomarkers during emotional face processing

Network and state specificity in connectivity-based predictions of individual behavior

Predicting individual behavior from brain functional connectivity (FC) patterns can contribute to our understanding of human brain functioning. This may apply in particular if predictions are based on features derived from circumscribed, a priori defined functional networks, which improves interpretability. Furthermore, some evidence suggests that task-based FC data may yield more successful predictions of behavior than resting-state FC data. Here, we comprehensively examined to what extent the correspondence of functional network priors and task states with behavioral target domains influences the predictability of individual performance in cognitive, social, and affective tasks. To this end, we used data from the Human Connectome Project for large-scale out-of-sample predictions of individual abilities in working memory (WM), theory-of-mind cognition (SOCIAL), and emotion processing (EMO) from FC of corresponding and non-corresponding states (WM/SOCIAL/EMO/resting-state) and networks (WM/SOCIAL/EMO/whole-brain connectome). Using root mean squared error and coefficient of determination to evaluate model fit revealed that predictive performance was rather poor overall. Predictions from whole-brain FC were slightly better than those from FC in task-specific networks, and a slight benefit of predictions based on FC from task versus resting state was observed for performance in the WM domain. Beyond that, we did not find any significant effects of a correspondence of network, task state, and performance domains. Together, these results suggest that multivariate FC patterns during both task and resting states contain rather little information on individual performance levels, calling for a reconsideration of how the brain mediates individual differences in mental abilities.

Free-viewing gaze patterns reveal a mood-congruency bias in MDD during an affective fMRI/eye-tracking task

Major depressive disorder (MDD) has been related to abnormal amygdala activity during emotional face processing. However, a recent large-scale study (n = 28,638) found no such correlation, which is probably due to the low precision of fMRI measurements. To address this issue, we used simultaneous fMRI and eye-tracking measurements during a commonly employed emotional face recognition task. Eye-tracking provide high-precision data, which can be used to enrich and potentially stabilize fMRI readouts. With the behavioral response, we additionally divided the active task period into a task-related and a free-viewing phase to explore the gaze patterns of MDD patients and healthy controls (HC) and compare their respective neural correlates. Our analysis showed that a mood-congruency attentional bias could be detected in MDD compared to healthy controls during the free-viewing phase but without parallel amygdala disruption. Moreover, the neural correlates of gaze patterns reflected more prefrontal fMRI activity in the free-viewing than the task-related phase. Taken together, spontaneous emotional processing in free viewing might lead to a more pronounced mood-congruency bias in MDD, which indicates that combined fMRI with eye-tracking measurement could be beneficial for our understanding of the underlying psychopathology of MDD in different emotional processing phases.Trial Registration: The BeCOME study is registered on ClinicalTrials (gov: NCT03984084) by the Max Planck Institute of Psychiatry in Munich, Germany.

Brain age prediction across the human lifespan using multimodal MRI data

Measuring differences between an individual's age and biological age with biological information from the brain have the potential to provide biomarkers of clinically relevant neurological syndromes that arise later in human life. To explore the effect of multimodal brain magnetic resonance imaging (MRI) features on the prediction of brain age, we investigated how multimodal brain imaging data improved age prediction from more imaging features of structural or functional MRI data by using partial least squares regression (PLSR) and longevity data sets (age 6-85 years). First, we found that the age-predicted values for each of these ten features ranged from high to low: cortical thickness (R = 0.866, MAE = 7.904), all seven MRI features (R = 0.8594, MAE = 8.24), four features in structural MRI (R = 0.8591, MAE = 8.24), fALFF (R = 0.853, MAE = 8.1918), gray matter volume (R = 0.8324, MAE = 8.931), three rs-fMRI feature (R = 0.7959, MAE = 9.744), mean curvature (R = 0.7784, MAE = 10.232), ReHo (R = 0.7833, MAE = 10.122), ALFF (R = 0.7517, MAE = 10.844), and surface area (R = 0.719, MAE = 11.33). In addition, the significance of the volume and size of brain MRI data in predicting age was also studied. Second, our results suggest that all multimodal imaging features, except cortical thickness, improve brain-based age prediction. Third, we found that the left hemisphere contributed more to the age prediction, that is, the left hemisphere showed a greater weight in the age prediction than the right hemisphere. Finally, we found a nonlinear relationship between the predicted age and the amount of MRI data. Combined with multimodal and lifespan brain data, our approach provides a new perspective for chronological age prediction and contributes to a better understanding of the relationship between brain disorders and aging.

Effect of a centric stabilization splint on masticatory muscles in patients with temporomandibular disorders: An electromyographic study

AIM

Occlusal splint treatment is commonly used to treat a variety of temporomandibular disorders (TMDs), with efficacy ranging between 70% and 90%. Centric splints are effective in relieving muscular soreness in individuals with TMD. Electromyography (EMG) quantifies muscle activity and can be used as an accessory diagnostic tool to evaluate the efficiency of the splint on the masticatory complex. Electromyography is used for assessing patients with TMD and observing muscle electromyography. TMD patients have altered electromyographic (EMG) masticatory muscle activity because of its change in electrical activity index or because of the compensatory mechanism for the disorder. Therefore, this study serves to evaluate the efficacy of the centric stabilization splint on TMD using EMG.

SETTINGS AND DESIGN

This cross-sectional study enrolled Ten TMD Patients with TMD, who underwent treatment with centric stabilization splint.

MATERIALS AND METHODS

The study involved ten young adults with TMD aged 18-45 years who were recruited without regard to sex, religion, caste, or socioeconomic background. The participants were randomized to receive a flat-contact upper stabilization splint and pregelled EMG electrodes to assess the immediate impact of centric splints on TMDs. After 3 months of follow-up, muscle activity and muscle symmetrical activity were measured to assess improvement in the symptoms of TMD.

STATISTICAL ANALYSIS USED

The Shapiro-Wilk test was used to assess the normality of the variables' distribution using SPSS 26.0. Symmetrical activity and treatment response were investigated using the Wilcoxon signed-rank test.

RESULTS

It showed an improvement in the temporalis, masseter, and sternocleidomastoid muscles' resting EMG activity. A statistically significant improvement was seen in the EMG activity of the bilateral temporalis, right masseter, right sternocleidomastoid, and left digastric muscles while clenching. The masseter, sternocleidomastoid, and digastric muscles all displayed significantly enhanced symmetrical activity (P < 0.05).

CONCLUSIONS

This research concludes that a centric stabilizing splint assists in relieving TMD symptoms. There was enhanced masticatory muscle activity both at rest and during function. Furthermore, there was an improvement in symmetrical activity of the masticatory muscles, which improved balance and enhanced the effective functioning of the masticatory complex.

Network and State Specificity in Connectivity-Based Predictions of Individual Behavior

Predicting individual behavior from brain functional connectivity (FC) patterns can contribute to our understanding of human brain functioning. This may apply in particular if predictions are based on features derived from circumscribed, a priori defined functional networks, which improves interpretability. Furthermore, some evidence suggests that task-based FC data may yield more successful predictions of behavior than resting-state FC data. Here, we comprehensively examined to what extent the correspondence of functional network priors and task states with behavioral target domains influences the predictability of individual performance in cognitive, social, and affective tasks. To this end, we used data from the Human Connectome Project for large-scale out-of-sample predictions of individual abilities in working memory (WM), theory-of-mind cognition (SOCIAL), and emotion processing (EMO) from FC of corresponding and non-corresponding states (WM/SOCIAL/EMO/resting-state) and networks (WM/SOCIAL/EMO/whole-brain connectome). Using root mean squared error and coefficient of determination to evaluate model fit revealed that predictive performance was rather poor overall. Predictions from whole-brain FC were slightly better than those from FC in task-specific networks, and a slight benefit of predictions based on FC from task versus resting state was observed for performance in the WM domain. Beyond that, we did not find any significant effects of a correspondence of network, task state, and performance domains. Together, these results suggest that multivariate FC patterns during both task and resting states contain rather little information on individual performance levels, calling for a reconsideration of how the brain mediates individual differences in mental abilities.

Challenges and Solutions to the Measurement of Neurocognitive Mechanisms in Developmental Settings

Identifying early neurocognitive mechanisms that confer risk for mental health problems is one important avenue as we seek to develop successful early interventions. Currently, however, we have limited understanding of the neurocognitive mechanisms involved in shaping mental health trajectories from childhood through young adulthood, and this constrains our ability to develop effective clinical interventions. In particular, there is an urgent need to develop more sensitive, reliable, and scalable measures of individual differences for use in developmental settings. In this review, we outline methodological shortcomings that explain why widely used task-based measures of neurocognition currently tell us little about mental health risk. We discuss specific challenges that arise when studying neurocognitive mechanisms in developmental settings, and we share suggestions for overcoming them. We also propose a novel experimental approach-which we refer to as "cognitive microscopy"-that involves adaptive design optimization, temporally sensitive task administration, and multilevel modeling. This approach addresses some of the methodological shortcomings outlined above and provides measures of stability, variability, and developmental change in neurocognitive mechanisms within a multivariate framework.

Anxiety Shapes Amygdala-Prefrontal Dynamics During Movie Watching

Background

A well-characterized amygdala-dorsomedial prefrontal circuit is thought to be crucial for threat vigilance during anxiety. However, engagement of this circuitry within relatively naturalistic paradigms remains unresolved.

Methods

Using an open functional magnetic resonance imaging dataset (Cambridge Centre for Ageing Neuroscience; n = 630), we sought to investigate whether anxiety correlates with dynamic connectivity between the amygdala and dorsomedial prefrontal cortex during movie watching.

Results

Using an intersubject representational similarity approach, we saw no effect of anxiety when comparing pairwise similarities of dynamic connectivity across the entire movie. However, preregistered analyses demonstrated a relationship between anxiety, amygdala-prefrontal dynamics, and anxiogenic features of the movie (canonical suspense ratings). Our results indicated that amygdala-prefrontal circuitry was modulated by suspense in low-anxiety individuals but was less sensitive to suspense in high-anxiety individuals. We suggest that this could also be related to slowed habituation or amplified anticipation. Moreover, a measure of threat-relevant attentional bias (accuracy/reaction time to fearful faces) demonstrated an association with connectivity and suspense.

Conclusions

Overall, this study demonstrated the presence of anxiety-relevant differences in connectivity during movie watching, varying with anxiogenic features of the movie. Mechanistically, exactly how and when these differences arise remains an opportunity for future research.

Functional neuroimaging of resilience to trauma: convergent evidence and challenges for future research

Resilience is broadly defined as the ability to adapt successfully following stressful life events. Here, we review functional MRI studies that investigated key psychological factors that have been consistently linked to resilience to severe adversity and trauma exposure. These domains include emotion regulation (including cognitive reappraisal), reward responsivity, and cognitive control. Further, we briefly review functional imaging evidence related to emerging areas of study that may potentially facilitate resilience: namely social cognition, active coping, and successful fear extinction. Finally, we also touch upon ongoing issues in neuroimaging study design that will need to be addressed to enable us to harness insight from such studies to improve treatments for - or, ideally, guard against the development of - debilitating post-traumatic stress syndromes.

Reliability of Decision-Making and Reinforcement Learning Computational Parameters

Computational models can offer mechanistic insight into cognition and therefore have the potential to transform our understanding of psychiatric disorders and their treatment. For translational efforts to be successful, it is imperative that computational measures capture individual characteristics reliably. Here we examine the reliability of reinforcement learning and economic models derived from two commonly used tasks. Healthy individuals (N = 50) completed a restless four-armed bandit and a calibrated gambling task twice, two weeks apart. Reward and punishment learning rates from the reinforcement learning model showed good reliability and reward and punishment sensitivity from the same model had fair reliability; while risk aversion and loss aversion parameters from a prospect theory model exhibited good and excellent reliability, respectively. Both models were further able to predict future behaviour above chance within individuals. This prediction was better when based on participants' own model parameters than other participants' parameter estimates. These results suggest that reinforcement learning, and particularly prospect theory parameters, as derived from a restless four-armed bandit and a calibrated gambling task, can be measured reliably to assess learning and decision-making mechanisms. Overall, these findings indicate the translational potential of clinically-relevant computational parameters for precision psychiatry.

The Role of fMRI in Drug Development: An Update

Functional magnetic resonance imaging (fMRI) of the brain is a technology that holds great potential for increasing the efficiency of drug development for the central nervous system (CNS). In preclinical studies and both early- and late-phase human trials, fMRI has the potential to improve cross-species translation of drug effects, help to de-risk compounds early in development, and contribute to the portfolio of evidence for a compound's efficacy and mechanism of action. However, to date, the utilization of fMRI in the CNS drug development process has been limited. The purpose of this chapter is to explore this mismatch between potential and utilization. This chapter provides introductory material related to fMRI and drug development, describes what is required of fMRI measurements for them to be useful in a drug development setting, lists current capabilities of fMRI in this setting and challenges faced in its utilization, and ends with directions for future development of capabilities in this arena. This chapter is the 5-year update of material from a previously published workshop summary (Carmichael et al., Drug DiscovToday 23(2):333-348, 2018).

Exaggerated amygdala response to threat and association with immune hyperactivity in depression

BACKGROUND

Depression is characterized by altered neurobiological responses to threat and inflammation may be involved in the development and maintenance of symptoms. However, the mechanistic pathways underlying the relationship between the neural underpinnings of threat, inflammation and depressive symptoms remain unknown.

METHODS

Twenty participants with major depressive disorder (MDD) and 17 healthy controls (HCs) completed this study. Peripheral blood mononuclear cells (PBMCs) were collected and stimulated ex vivo with lipopolysaccharide (LPS). We then measured a broad array of secreted proteins and performed principal component analysis to compute an aggregated immune reactivity score. Subjects completed a well-validated emotional face processing task during functional magnetic resonance imaging (fMRI). Amygdala activation was measured during perception of threat for the main contrast of interest: fear > happy face. Participants completed the Mood and Anxiety Symptom Questionnaire (MASQ) and the Perceived Stress Scale (PSS). Correlation analyses between amygdala activation, the aggregate immune score, and symptom were computed across groups. A mediation analysis was also performed across groups to further explore the relationship between these three variables.

RESULTS

In line with our hypotheses and with prior work, the MDD group showed greater amygdala activation in response to threat compared to the HC group [t35 = -2.038, p = 0.049]. Internal consistency of amygdala activation to threat was found to be moderate. Response to an ex vivo immune challenge was greater in MDD than HC based on the computed immune reactivity score (PC1; t35 = 2.674, p = 0.011). Amygdala activation was positively correlated with the immune score (r = 0.331, p = 0.045). Moreover, higher amygdala activation was associated with greater anxious arousal measured by the MASQ (r = 0.390, p = 0.017). Exploring the role of stress, we found that higher perceived stress was positively associated with both inflammatory response (r = 0.367, p = 0.026) and amygdala response to threat (r = 0.325, p = 0.050). Mediation analyses showed that perceived stress predicted anxious arousal, but neither inflammation nor amygdala activation fully accounted for the effect of perceived stress on anxious arousal.

CONCLUSION

These data highlight the potential importance of threat circuitry hyperactivation in MDD, consistent with prior reports. We found that higher levels of inflammatory biomarkers were associated with higher amygdala activation, which in turn was associated with anxious arousal. Future research utilizing larger sample sizes are needed to replicate these preliminary results.

A Biologically Inspired Neural Network Model to Gain Insight Into the Mechanisms of Post-Traumatic Stress Disorder and Eye Movement Desensitization and Reprocessing Therapy

Eye movement desensitization and reprocessing (EMDR) therapy is a well-established therapeutic method to treat post-traumatic stress disorder (PTSD). However, how EMDR exerts its therapeutic action has been studied in many types of research but still needs to be completely understood. This is in part due to limited knowledge of the neurobiological mechanisms underlying EMDR, and in part to our incomplete understanding of PTSD. In order to model PTSD, we used a biologically inspired computational model based on firing rate units, encompassing the cortex, hippocampus, and amygdala. Through the modulation of its parameters, we fitted real data from patients treated with EMDR or classical exposure therapy. This allowed us to gain insights into PTSD mechanisms and to investigate how EMDR achieves trauma remission.

Age-related change in task-evoked amygdala-prefrontal circuitry: A multiverse approach with an accelerated longitudinal cohort aged 4-22 years

The amygdala and its connections with medial prefrontal cortex (mPFC) play central roles in the development of emotional processes. While several studies have suggested that this circuitry exhibits functional changes across the first two decades of life, findings have been mixed - perhaps resulting from differences in analytic choices across studies. Here we used multiverse analyses to examine the robustness of task-based amygdala-mPFC function findings to analytic choices within the context of an accelerated longitudinal design (4-22 years-old; N = 98; 183 scans; 1-3 scans/participant). Participants recruited from the greater Los Angeles area completed an event-related emotional face (fear, neutral) task. Parallel analyses varying in preprocessing and modeling choices found that age-related change estimates for amygdala reactivity were more robust than task-evoked amygdala-mPFC functional connectivity to varied analytical choices. Specification curves indicated evidence for age-related decreases in amygdala reactivity to faces, though within-participant changes in amygdala reactivity could not be differentiated from between-participant differences. In contrast, amygdala-mPFC functional connectivity results varied across methods much more, and evidence for age-related change in amygdala-mPFC connectivity was not consistent. Generalized psychophysiological interaction (gPPI) measurements of connectivity were especially sensitive to whether a deconvolution step was applied. Our findings demonstrate the importance of assessing the robustness of findings to analysis choices, although the age-related changes in our current work cannot be overinterpreted given low test-retest reliability. Together, these findings highlight both the challenges in estimating developmental change in longitudinal cohorts and the value of multiverse approaches in developmental neuroimaging for assessing robustness of results.

'That Time of the Month' - Investigating the Influence of the Menstrual Cycle and Oral Contraceptives on the Brain Using Magnetic Resonance Imaging

The stereotypic and oversimplified relationship between female sex hormones and undesirable behavior dates to the earliest days of human society, as already the ancient Greek word for the uterus, "hystera" indicated an aversive connection. Remaining and evolving throughout the centuries, transcending across cultures and various aspects of everyday life, its perception was only recently reframed. Contemporarily, the complex interaction of hormonal phases (i. e., the menstrual cycle), hormonal medication (i. e., oral contraceptives), women's psychological well-being, and behavior is the subject of multifaceted and more reflected discussions. A driving force of this ongoing paradigm shift was the introduction of this highly interesting and important topic into the realm of scientific research. This refers to neuroscientific research as it enables a multimodal approach combining aspects of physiology, medicine, and psychology. Here a growing body of literature points towards significant alterations of both brain function, such as lateralization of cognitive functions, and structure, such as gray matter concentrations, due to fluctuations and changes in hormonal levels. This especially concerns female sex hormones. However, the more research is conducted within this field, the less reliable these observations and derived insights appear. This may be due to two particular factors: measurement inconsistencies and diverse hormonal phases accompanied by interindividual differences. The first factor refers to the prominent unreliability of one of the primarily utilized neuroscientific research instruments: functional magnetic resonance imaging (fMRI). This unreliability is seemingly present in paradigms and analyses, and their interplay, and is additionally affected by the second factor. In more detail, hormonal phases and levels further influence neuroscientific results obtained through fMRI as outcomes vary drastically across different cycle phases and medication. This resulting vast uncertainty thus tremendously hinders the further advancement of our understanding of how female sex hormones might alter brain structure and function and, ultimately, behavior.This review summarizes parts of the current state of research and outlines the essential requirements to further investigate and understand the female brain's underlying physiological and anatomical features.

Reliability and stability challenges in ABCD task fMRI data

Trait stability of measures is an essential requirement for individual differences research. Functional MRI has been increasingly used in studies that rely on the assumption of trait stability, such as attempts to relate task related brain activation to individual differences in behavior and psychopathology. However, recent research using adult samples has questioned the trait stability of task-fMRI measures, as assessed by test-retest correlations. To date, little is known about trait stability of task fMRI in children. Here, we examined within-session reliability and long-term stability of individual differences in task-fMRI measures using fMRI measures of brain activation provided by the adolescent brain cognitive development (ABCD) Study Release v4.0 as an individual's average regional activity, using its tasks focused on reward processing, response inhibition, and working memory. We also evaluated the effects of factors potentially affecting reliability and stability. Reliability and stability (quantified as the ratio of non-scanner related stable variance to all variances) was poor in virtually all brain regions, with an average value of 0.088 and 0.072 for short term (within-session) reliability and long-term (between-session) stability, respectively, in regions of interest (ROIs) historically-recruited by the tasks. Only one reliability or stability value in ROIs exceeded the 'poor' cut-off of 0.4, and in fact rarely exceeded 0.2 (only 4.9%). Motion had a pronounced effect on estimated reliability/stability, with the lowest motion quartile of participants having a mean reliability/stability 2.5 times higher (albeit still 'poor') than the highest motion quartile. Poor reliability and stability of task-fMRI, particularly in children, diminishes potential utility of fMRI data due to a drastic reduction of effect sizes and, consequently, statistical power for the detection of brain-behavior associations. This essential issue urgently needs to be addressed through optimization of task design, scanning parameters, data acquisition protocols, preprocessing pipelines, and data denoising methods.

Anxiety and amygdala connectivity during movie-watching

Rodent and human studies have implicated an amygdala-prefrontal circuit during threat processing. One possibility is that while amygdala activity underlies core features of anxiety (e.g. detection of salient information), prefrontal cortices (i.e. dorsomedial prefrontal/anterior cingulate cortex) entrain its responsiveness. To date, this has been established in tightly controlled paradigms (predominantly using static face perception tasks) but has not been extended to more naturalistic settings. Consequently, using ‘movie fMRI’—in which participants watch ecologically-rich movie stimuli rather than constrained cognitive tasks—we sought to test whether individual differences in anxiety correlate with the degree of face-dependent amygdala-prefrontal coupling in two independent samples. Analyses suggested increased face-dependent superior parietal activation and decreased speech-dependent auditory cortex activation as a function of anxiety. However, we failed to find evidence for anxiety-dependent connectivity, neither in our stimulus-dependent or -independent analyses. Our findings suggest that work using experimentally constrained tasks may not replicate in more ecologically valid settings and, moreover, highlight the importance of testing the generalizability of neuroimaging findings outside of the original context.

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Using ‘movie fMRI’, we tested whether trait anxiety correlates with face-dependent amygdala-prefrontal coupling.

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We observed altered superior parietal activation to faces and auditory cortex activation to speech as a function of anxiety.

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We failed to find evidence for anxiety-dependent amygdala-dmPFC connectivity in stimulus-dependent or -independent analyses.

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Our findings highlight the importance of testing the generalizability of neuroimaging findings outside of the original context.

Effect sizes and test-retest reliability of the fMRI-based neurologic pain signature

Identifying biomarkers that predict mental states with large effect sizes and high test-retest reliability is a growing priority for fMRI research. We examined a well-established multivariate brain measure that tracks pain induced by nociceptive input, the Neurologic Pain Signature (NPS). In N = 295 participants across eight studies, NPS responses showed a very large effect size in predicting within-person single-trial pain reports (d = 1.45) and medium effect size in predicting individual differences in pain reports (d = 0.49). The NPS showed excellent short-term (within-day) test-retest reliability (ICC = 0.84, with average 69.5 trials/person). Reliability scaled with the number of trials within-person, with ≥60 trials required for excellent test-retest reliability. Reliability was tested in two additional studies across 5-day (N = 29, ICC = 0.74, 30 trials/person) and 1-month (N = 40, ICC = 0.46, 5 trials/person) test-retest intervals. The combination of strong within-person correlations and only modest between-person correlations between the NPS and pain reports indicate that the two measures have different sources of between-person variance. The NPS is not a surrogate for individual differences in pain reports but can serve as a reliable measure of pain-related physiology and mechanistic target for interventions.

Altered effective connectivity of the extended face processing system in depression and its association with treatment response: findings from the YoDA-C randomized controlled trial

BACKGROUND

Depression is commonly associated with fronto-amygdala dysfunction during the processing of emotional face expressions. Interactions between these regions are hypothesized to contribute to negative emotional processing biases and as such have been highlighted as potential biomarkers of treatment response. This study aimed to investigate depression associated alterations to directional connectivity and assess the utility of these parameters as predictors of treatment response.

METHODS

Ninety-two unmedicated adolescents and young adults (mean age 20.1; 56.5% female) with moderate-to-severe major depressive disorder and 88 healthy controls (mean age 19.8; 61.4% female) completed an implicit emotional face processing fMRI task. Patients were randomized to receive cognitive behavioral therapy for 12 weeks, plus either fluoxetine or placebo. Using dynamic causal modelling, we examined functional relationships between six brain regions implicated in emotional face processing, comparing both patients and controls and treatment responders and non-responders.

RESULTS

Depressed patients demonstrated reduced inhibition from the dlPFC to vmPFC and reduced excitation from the dlPFC to amygdala during sad expression processing. During fearful expression processing patients showed reduced inhibition from the vmPFC to amygdala and reduced excitation from the amygdala to dlPFC. Response was associated with connectivity from the amygdala to dlPFC during sad expression processing and amygdala to vmPFC connectivity during fearful expression processing.

CONCLUSIONS

Our study clarifies the nature of face processing network alterations in adolescents and young adults with depression, highlighting key interactions between the amygdala and prefrontal cortex. Moreover, these findings highlight the potential utility of these interactions in predicting treatment response.

Neuroimaging correlates and predictors of response to repeated-dose intravenous ketamine in PTSD: preliminary evidence

Promising initial data indicate that the glutamate N-methyl-D-aspartate (NMDA) receptor antagonist ketamine may be beneficial in post-traumatic stress disorder (PTSD). Here, we explore the neural correlates of ketamine-related changes in PTSD symptoms, using a rich battery of functional imaging data (two emotion-processing tasks and one task-free scan), collected from a subset of participants of a randomized clinical trial of repeated-dose intravenous ketamine vs midazolam (total N = 21). In a pre-registered analysis, we tested whether changes in an a priori set of imaging measures from a target neural circuit were predictive of improvement in PTSD symptoms, using leave-one-out cross-validated elastic-net regression models (regions of interest in the target circuit consisted of the dorsal and rostral anterior cingulate cortex, ventromedial prefrontal cortex, anterior hippocampus, anterior insula, and amygdala). Improvements in PTSD severity were associated with increased functional connectivity between the ventromedial prefrontal cortex (vmPFC) and amygdala during emotional face-viewing (change score retained in model with minimum predictive error in left-out subjects, standardized regression coefficient [β] = 2.90). This effect was stronger in participants who received ketamine compared to midazolam (interaction β = 0.86), and persisted following inclusion of concomitant change in depressive symptoms in the analysis model (β = 0.69). Improvement following ketamine was also predicted by decreased dorsal anterior cingulate activity during emotional conflict regulation, and increased task-free connectivity between the vmPFC and anterior insula (βs = -2.82, 0.60). Exploratory follow-up analysis via dynamic causal modelling revealed that whilst improvement in PTSD symptoms following either drug was associated with decreased excitatory modulation of amygdala→vmPFC connectivity during emotional face-viewing, increased top-down inhibition of the amygdala by the vmPFC was only observed in participants who improved under ketamine. Individuals with low prefrontal inhibition of amygdala responses to faces at baseline also showed greater improvements following ketamine treatment. These preliminary findings suggest that, specifically under ketamine, improvements in PTSD symptoms are accompanied by normalization of hypofrontal control over amygdala responses to social signals of threat.

Face Processing in Developmental Prosopagnosia: Altered Neural Representations in the Fusiform Face Area

Rationale: Face expertise is a pivotal social skill. Developmental prosopagnosia (DP), i.e., the inability to recognize faces without a history of brain damage, affects about 2% of the general population, and is a renowned model system of the face-processing network. Within this network, the right Fusiform Face Area (FFA), is particularly involved in face identity processing and may therefore be a key element in DP. Neural representations within the FFA have been examined with Representational Similarity Analysis (RSA), a data-analytical framework in which multi-unit measures of brain activity are assessed with correlation analysis. Objectives: Our study intended to scrutinize modifications of FFA-activation during face encoding and maintenance based on RSA. Methods: Thirteen participants with DP (23-70 years) and 12 healthy control subjects (19-62 years) participated in a functional MRI study, including morphological MRI, a functional FFA-localizer and a modified Sternberg paradigm probing face memory encoding and maintenance. Memory maintenance of one, two, or four faces represented low, medium, and high memory load. We examined conventional activation differences in response to working memory load and applied RSA to compute individual correlation-matrices on the voxel level. Group correlation-matrices were compared via Donsker's random walk analysis. Results: On the functional level, increased memory load entailed both a higher absolute FFA-activation level and a higher degree of correlation between activated voxels. Both aspects were deficient in DP. Interestingly, control participants showed a homogeneous degree of correlation for successful trials during the experiment. In DP-participants, correlation levels between FFA-voxels were significantly lower and were less sustained during the experiment. In behavioral terms, DP-participants performed poorer and had longer reaction times in relation to DP-severity. Furthermore, correlation levels were negatively correlated with reaction times for the most demanding high load condition. Conclusion: We suggest that participants with DP fail to generate robust and maintained neural representations in the FFA during face encoding and maintenance, in line with poorer task performance and prolonged reaction times. In DP, alterations of neural coding in the FFA might therefore explain curtailing in working memory and contribute to impaired long-term memory and mental imagery.

Childhood maltreatment results in altered deactivation of reward processing circuits in depressed patients: A functional magnetic resonance imaging study of a facial emotion recognition task

Importance and objectives

Childhood adversity is a strong risk factor for the development of various psychopathologies including major depressive disorder (MDD). However, not all depressed patients experience early life trauma. Functional magnetic resonance imaging (fMRI) studies using facial emotion processing tasks have documented altered blood-oxygen-level-dependent (BOLD) responses in specific cortico-limbic networks both in MDD patients and in individuals with a history of childhood maltreatment (CM). Therefore, a history of maltreatment may represent a key modulating factor responsible for the altered processing of socio-affective stimuli. To test this hypothesis, we recruited MDD patients with and without of maltreatment history to study the long-term consequences of childhood trauma and examined the impact of CM on brain activity using a facial emotion recognition fMRI task.

Methods

MDD patients with childhood maltreatment (MDD + CM, n = 21), MDD patients without maltreatment (MDD, n = 19), and healthy controls (n = 21) matched for age, sex and intelligence quotient underwent fMRI while performing a block design facial emotion matching task with images portraying negative emotions (fear, anger and sadness). The history of maltreatment was assessed with the 28-item Childhood Trauma Questionnaire.

Results

Both MDD and MDD + CM patients displayed impaired accuracy to recognize sad faces. Analysis of brain activity revealed that MDD + CM patients had significantly reduced negative BOLD signals in their right accumbens, subcallosal cortex, and anterior paracingulate gyrus compared to controls. Furthermore, MDD + CM patients had a significantly increased negative BOLD response in their right precentral and postcentral gyri compared to controls. We found little difference between MDD and MDD + CM patients, except that MDD + CM patients had reduced negative BOLD response in their anterior paracingulate gyrus relative to the MDD group.

Conclusions

Our present data provide evidence that depressed patients with a history of maltreatment are impaired in facial emotion recognition and that they display altered functioning of key reward-related fronto-striatal circuits during a facial emotion matching task.

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History of childhood maltreatment (CM) can alter socio-cognitive functioning in adults.

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We studied depressed patients with and without CM with age, gender and IQ matched controls.

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Brain activity was assessed with fMRI using a facial emotion matching task.

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CM patients had impaired accuracy to recognize facial emotions, especially sadness.

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CM patients had altered negative BOLD signals in their fronto-striatal circuits.

Using genetic algorithms to uncover individual differences in how humans represent facial emotion

Emotional facial expressions critically impact social interactions and cognition. However, emotion research to date has generally relied on the assumption that people represent categorical emotions in the same way, using standardized stimulus sets and overlooking important individual differences. To resolve this problem, we developed and tested a task using genetic algorithms to derive assumption-free, participant-generated emotional expressions. One hundred and five participants generated a subjective representation of happy, angry, fearful and sad faces. Population-level consistency was observed for happy faces, but fearful and sad faces showed a high degree of variability. High test-retest reliability was observed across all emotions. A separate group of 108 individuals accurately identified happy and angry faces from the first study, while fearful and sad faces were commonly misidentified. These findings are an important first step towards understanding individual differences in emotion representation, with the potential to reconceptualize the way we study atypical emotion processing in future research.

Effects of testosterone administration on fMRI responses to executive function, aggressive behavior, and emotion processing tasks during severe exercise- and diet-induced energy deficit

BACKGROUND

Clinical administration of testosterone is widely used due to a variety of claimed physical and cognitive benefits. Testosterone administration is associated with enhanced brain and cognitive function, as well as mood, in energy-balanced males, although such relationships are controversial. However, the effects of testosterone administration on the brains of energy-deficient males, whose testosterone concentrations are likely to be well below normal, have not been investigated.

METHODS

This study collected functional magnetic resonance imaging (fMRI) data from 50 non-obese young men before (PRE) and shortly after (POST) 28 days of severe exercise-and-diet-induced energy deficit during which testosterone (200 mg testosterone enanthate per week in sesame oil, TEST) or placebo (sesame seed oil only, PLA) were administered. Scans were also collected after a post-energy-deficit weight regain period (REC). Participants completed five fMRI tasks that assessed aspects of: 1) executive function (Attention Network Task or ANT; Multi-Source Interference Task or MSIT; AXE Continuous Processing Task or AXCPT); 2) aggressive behavior (Provoked Aggression Task or AGG); and 3) latent emotion processing (Emotional Face Processing or EMO).

RESULTS

Changes over time in task-related fMRI activation in a priori defined task-critical brain regions during performance of 2 out of 5 tasks were significantly different between TEST and PLA, with TEST showing greater levels of activation during ANT in the right anterior cingulate gyrus at POST and during MSIT in several brain regions at REC. Changes over time in objective task performance were not statistically significant; testosterone-treated volunteers had greater self-reported anger during AGG at POST.

CONCLUSIONS

Testosterone administration can alter some aspects of brain function during severe energy deficit and increase levels of anger.

Affective brain patterns as multivariate neural correlates of cardiovascular disease risk

This study tested whether brain activity patterns evoked by affective stimuli relate to individual differences in an indicator of pre-clinical atherosclerosis: carotid artery intima-media thickness (CA-IMT). Adults (aged 30-54 years) completed functional magnetic resonance imaging (fMRI) tasks that involved viewing three sets of affective stimuli. Two sets included facial expressions of emotion, and one set included neutral and unpleasant images from the International Affective Picture System (IAPS). Cross-validated, multivariate and machine learning models showed that individual differences in CA-IMT were partially predicted by brain activity patterns evoked by unpleasant IAPS images, even after accounting for age, sex and known cardiovascular disease risk factors. CA-IMT was also predicted by brain activity patterns evoked by angry and fearful faces from one of the two stimulus sets of facial expressions, but this predictive association did not persist after accounting for known cardiovascular risk factors. The reliability (internal consistency) of brain activity patterns evoked by affective stimuli may have constrained their prediction of CA-IMT. Distributed brain activity patterns could comprise affective neural correlates of pre-clinical atherosclerosis; however, the interpretation of such correlates may depend on their psychometric properties, as well as the influence of other cardiovascular risk factors and specific affective cues.

A systematic review of studies that used NIRS to measure neural activation during emotion processing in healthy individuals

Functional neuroimaging provides an avenue for earlier diagnosis and tailored treatment of psychological disorders characterised by emotional impairment. Near-infrared spectroscopy (NIRS) offers ecological advantages compared to other neuroimaging techniques and suitability of measuring regions involved in emotion functions. A systematic review was conducted to evaluate the capacity of NIRS to detect activation during emotion processing and to provide recommendations for future research. Following a comprehensive literature search, we reviewed 85 journal articles, which compared activation during emotional experience, regulation or perception with either a neutral condition or baseline period among healthy participants. The quantitative synthesis of outcomes was limited to thematical analysis, owing to the lack of standardisation between studies. Although most studies found increased prefrontal activity during emotional experience and regulation, the findings were more inconsistent for emotion perception. Some researchers reported increased activity during the task, some reported decreases, some no significant changes, and some reported mixed findings depending on the valence and region. We propose that variations in the cognitive task and stimuli, recruited sample, and measurement and analysis of data are the primary causes of inconsistency. Recommendations to improve consistency in future research by carefully considering the choice of population, cognitive task and analysis approach are provided.

Predicting Response to Brain Stimulation in Depression: a Roadmap for Biomarker Discovery

PURPOSE OF REVIEW

Clinical response to brain stimulation treatments for depression is highly variable. A major challenge for the field is predicting an individual patient's likelihood of response. This review synthesises recent developments in neural predictors of response to targeted brain stimulation in depression. It then proposes a framework to evaluate the clinical potential of putative 'biomarkers'.

RECENT FINDINGS

Largely, developments in identifying putative predictors emerge from two approaches: data-driven, including machine learning algorithms applied to resting state or structural neuroimaging data, and theory-driven, including task-based neuroimaging. Theory-driven approaches can also yield mechanistic insight into the cognitive processes altered by the intervention.

SUMMARY

A pragmatic framework for discovery and testing of biomarkers of brain stimulation response in depression is proposed, involving (1) identification of a cognitive-neural phenotype; (2) confirming its validity as putative biomarker, including out-of-sample replicability and within-subject reliability; (3) establishing the association between this phenotype and treatment response and/or its modifiability with particular brain stimulation interventions via an early-phase randomised controlled trial RCT; and (4) multi-site RCTs of one or more treatment types measuring the generalisability of the biomarker and confirming the superiority of biomarker-selected patients over randomly allocated groups.

Investigating the neural substrates of Antagonistic Externalizing and social-cognitive Theory of Mind: an fMRI examination of functional activity and synchrony

Recently developed quantitative models of psychopathology (i.e., Hierarchical Taxonomy of Psychopathology) identify an Antagonistic Externalizing spectrum that captures the psychological disposition toward criminal and antisocial behavior. The purpose of the present study was to examine relations between Antagonistic psychopathology (and associated Five-Factor model Antagonism/Agreeableness) and neural functioning related to social-cognitive Theory of Mind using a large sample (N = 973) collected as part of the Human Connectome Project (Van Essen et al., 2013a). No meaningful relations between Antagonism/Antagonistic Externalizing and Theory of Mind-related neural activity or synchrony were observed (p < .005). We conclude by outlining methodological considerations (e.g., validity of social cognition task and low test-retest reliability of functional biomarkers) that may account for these null results, and present recommendations for future research.

Asymmetry of amygdala resting-state functional connectivity in healthy human brain

Lateral asymmetry is one of the fundamental properties of the functional anatomy of the human brain. Amygdala (AMYG) asymmetry was also reported in clinical studies of resting-state functional connectivity (rsFC) but rarely in healthy groups. To explore this issue, we investigated the reproducibility of the data on rsFC of the left and right AMYG using functional MRI twice a week in 20 healthy volunteers with mild-to-moderate anxiety. We found a resting-state network of the AMYG, which included regions involved in emotional processing and several other brain areas associated with memory and motor inhibition. The AMYG network was stable in time and within subjects, but the right AMYG had more significant connections with anatomical brain regions. The rsFC values of the right AMYG were also more sustained across the week than the left AMYG rsFC. Subjective ratings of anxiety did not correlate significantly with the patterns of seed-based AMYG connectivity. Our findings indicate that, for healthy subjects, rsFC may differ for the right and left AMYG. Moreover, the AMYG functional connectivity is variable in short-term observations, which may also influence the results of longitude studies.

Internal reliability of blame-related functional MRI measures in major depressive disorder

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Self-blame-related fMRI measures were previously validated in depressive disorders.

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Reproducibility and internal consistency as a measure of reliability were examined.

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Whilst simple fMRI measures exhibited fair reliability, complex measures did not.

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Yet, complex measures showed reproducible clinical validity at the group level.

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Connectivity measures, that balance reliability and validity better, are needed.

Background

Methods

Results

Conclusions

Novel polygenic risk score as a translational tool linking depression-related changes in the corticolimbic transcriptome with neural face processing and anhedonic symptoms

Convergent data from imaging and postmortem brain transcriptome studies implicate corticolimbic circuit (CLC) dysregulation in the pathophysiology of depression. To more directly bridge these lines of work, we generated a novel transcriptome-based polygenic risk score (T-PRS), capturing subtle shifts toward depression-like gene expression patterns in key CLC regions, and mapped this T-PRS onto brain function and related depressive symptoms in a nonclinical sample of 478 young adults (225 men; age 19.79 +/- 1.24) from the Duke Neurogenetics Study. First, T-PRS was generated based on common functional SNPs shifting CLC gene expression toward a depression-like state. Next, we used multivariate partial least squares regression to map T-PRS onto whole-brain activity patterns during perceptual processing of social stimuli (i.e., human faces). For validation, we conducted a comparative analysis with a PRS summarizing depression risk variants identified by the Psychiatric Genomics Consortium (PGC-PRS). Sex was modeled as moderating factor. We showed that T-PRS was associated with widespread reductions in neural response to neutral faces in women and to emotional faces and shapes in men (multivariate p < 0.01). This female-specific reductions in neural response to neutral faces was also associated with PGC-PRS (multivariate p < 0.03). Reduced reactivity to neutral faces was further associated with increased self-reported anhedonia. We conclude that women with functional alleles mimicking the postmortem transcriptomic CLC signature of depression have blunted neural activity to social stimuli, which may be expressed as higher anhedonia.

A combined fMRI and EMG study of emotional contagion following partial sleep deprivation in young and older humans

Sleep deprivation is proposed to inhibit top-down-control in emotion processing, but it is unclear whether sleep deprivation affects emotional mimicry and contagion. Here, we aimed to investigate effects of partial sleep deprivation on emotional contagion and mimicry in young and older humans. Participants underwent partial sleep deprivation (3 h sleep opportunity at the end of night), crossed-over with a full sleep condition in a balanced order, followed by a functional magnetic resonance imaging and electromyography (EMG) experiment with viewing of emotional and neutral faces and ratings of emotional responses. The final sample for main analyses was n = 69 (n = 36 aged 20–30 years, n = 33 aged 65–75 years). Partial sleep deprivation caused decreased activation in fusiform gyri for angry faces and decreased ratings of happiness for all stimuli, but no significant effect on the amygdala. Older participants reported more anger compared to younger participants, but no age differences were seen in brain responses to emotional faces or sensitivity to partial sleep deprivation. No effect of the sleep manipulation was seen on EMG. In conclusion, emotional contagion, but not mimicry, was affected by sleep deprivation. Our results are consistent with the previously reported increased negativity bias after insufficient sleep.

The Stockholm sleepy brain study: effects of sleep deprivation on cognitive and emotional processing in young and old. https://clinicaltrials.gov/ct2/show/NCT02000076.

Normative range parenting and the developing brain: A scoping review and recommendations for future research

Studies of early adversity such as trauma, abuse, and neglect highlight the critical importance of quality caregiving in brain development and mental health. However, the impact of normative range variability in caregiving on such biobehavioral processes remains poorly understood. Thus, we lack an essential foundation for understanding broader, population-representative developmental mechanisms of risk and resilience. Here, we conduct a scoping review of the extant literature centered on the question, "Is variability in normative range parenting associated with variability in brain structure and function?" After removing duplicates and screening by title, abstract, and full-text, 23 records were included in a qualitative review. The most striking outcome of this review was not only how few studies have explored associations between brain development and normative range parenting, but also how little methodological consistency exists across published studies. In light of these limitations, we propose recommendations for future research on normative range parenting and brain development. In doing so, we hope to facilitate evidence-based research that will help inform policies and practices that yield optimal developmental trajectories and mental health as well as extend the literature on the neurodevelopmental impact of early life stress.

The neural basis of hot and cold cognition in depressed patients, unaffected relatives, and low-risk healthy controls: An fMRI investigation

BACKGROUND

Modern cognitive neuropsychological models of depression posit that negatively biased emotional ("hot") processing confers risk for depression, while preserved executive function ("cold") cognition promotes resilience.

METHODS

We compared neural responses during hot and cold cognitive tasks in 99 individuals: those at familial risk for depression (N = 30 unaffected first-degree relatives of depressed individuals) and those currently experiencing a major depressive episode (N = 39 unmedicated depressed patients) with low-risk healthy controls (N = 30). Primary analyses assessed neural activation on two functional magnetic resonance imaging tasks previously associated with depression: dorsolateral prefrontal cortex (DLPFC) responsivity during the n-back working memory task; and amygdala and subgenual anterior cingulate cortex (sgACC) responsivity during incidental emotional face processing.

RESULTS

Depressed patients exhibited significantly attenuated working memory-related DLPFC activation, compared to low-risk controls and unaffected relatives; unaffected relatives did not differ from low-risk controls. We did not observe a complementary pattern during emotion processing. However, we found preliminary support that greater DLPFC activation was associated with lower amygdala response during emotion processing.

LIMITATIONS

These findings require confirmation in a longitudinal study to observe each individual's risk of developing depression; without this, we cannot identify the true risk level of the first-degree relative or low-risk control group.

CONCLUSIONS

These findings have implications for understanding the neural mechanisms of risk and resilience in depression: they are consistent with the suggestion that preserved executive function might confer resilience to developing depression in first-degree relatives of depressed patients.

Electromyography as a Means of Assessing Masticatory Muscle Activity in Patients with Pain-Related Temporomandibular Disorders

Aim

The aim of this study was to evaluate masticatory muscle electrical activity in patients with pain-related and pain-free temporomandibular disorders (TMDs) as well as in subjects with no TMD.

Methods

Ninety children with mixed dentition were recruited to the study. Of this total, 30 subjects were diagnosed with pain-related TMD (TMD-P), 30 with pain-free TMD (TMD-PF), and 30 without TMD. We used Axis I of the Research Diagnostic Criteria for TMD (RDC/TMD) to assess the presence of TMD in the examined children. The electromyographical (EMG) potentials of the temporalis and masseter muscles were measured with a DAB-Bluetooth Instrument (Zebris Medical GmbH, Germany) at rest and during maximum voluntary clenching (MVC).

Results

An analysis of the EMG recordings showed statistically significant intergroup differences in masticatory muscle electrical activity at rest and during MVC. Significantly higher rest temporalis muscle activity was noted in pain-related TMD subjects compared with that children from the pain-free TMD and non-TMD groups, as well as in TMD-PF children in relation to those without TMD. The EMG potentials of the temporalis muscle during MVC were much lower in patients with TMD-P than in pain-free TMD and non-TMD subjects. Masseter muscle activity at rest in the TMD-pain group was significantly greater, and masseter muscle EMG potentials during clenching were markedly lower than in patients with no TMD diagnosis.

Conclusion

The use of electromyography to assess masticatory muscle function revealed alterations in the pattern of temporalis and masseter muscle activity in patients with pain-related TMD compared with the pain-free subjects.

Visual cortical regions show sufficient test-retest reliability while salience regions are unreliable during emotional face processing

Functional magnetic resonance imaging studies frequently use emotional face processing tasks to probe neural circuitry related to psychiatric disorders and treatments with an emphasis on regions within the salience network (e.g., amygdala). Findings across previous test-retest reliability studies of emotional face processing have shown high variability, potentially due to differences in data analytic approaches. The present study comprehensively examined the test-retest reliability of an emotional faces task utilizing multiple approaches to region of interest (ROI) analysis and by examining voxel-wise reliability across the entire brain for both neural activation and functional connectivity. Analyses included 42 healthy adult participants who completed an fMRI scan concurrent with an emotional faces task on two separate days with an average of 25.52 days between scans. Intraclass correlation coefficients (ICCs) were calculated for the 'FACES-SHAPES' and 'FACES' (compared to implicit baseline) contrasts across the following: anatomical ROIs identified from a publicly available brain atlas (i.e., Brainnetome), functional ROIs consisting of 5-mm spheres centered on peak voxels from a publicly available meta-analytic database (i.e., Neurosynth), and whole-brain, voxel-wise analysis. Whole-brain, voxel-wise analyses of functional connectivity were also conducted using both anatomical and functional seed ROIs. While group-averaged neural activation maps were consistent across time, only one anatomical ROI and two functional ROIs showed good or excellent individual-level reliability for neural activation. The anatomical ROI was the right medioventral fusiform gyrus for the FACES contrast (ICC ​= ​0.60). The functional ROIs were the left and the right fusiform face area (FFA) for both FACES-SHAPES and FACES (Left FFA ICCs ​= ​0.69 & 0.79; Right FFA ICCs ​= ​0.68 & 0.66). Poor reliability (ICCs ​< ​0.4) was identified for almost all other anatomical and functional ROIs, with some exceptions showing fair reliability (ICCs ​= ​0.4-0.59). Whole-brain voxel-wise analysis of neural activation identified voxels with good (ICCs ​= ​0.6-0.74) to excellent reliability (ICCs ​> ​0.75) that were primarily located in visual cortex, with several clusters in bilateral dorsal lateral prefrontal cortex (DLPFC). Whole-brain voxel-wise analyses of functional connectivity for amygdala and fusiform gyrus identified very few voxels with good to excellent reliability using both anatomical and functional seed ROIs. Exceptions included clusters in right cerebellum and right DLPFC that showed reliable connectivity with left amygdala (ICCs ​> ​0.6). In conclusion, results indicate that visual cortical regions demonstrate good reliability at the individual level for neural activation, but reliability is generally poor for salience regions often focused on within psychiatric research (e.g., amygdala). Given these findings, future clinical neuroimaging studies using emotional faces tasks to examine individual differences might instead focus on visual regions and their role in psychiatric disorders.

What Is the Test-Retest Reliability of Common Task-Functional MRI Measures? New Empirical Evidence and a Meta-Analysis

Identifying brain biomarkers of disease risk is a growing priority in neuroscience. The ability to identify meaningful biomarkers is limited by measurement reliability; unreliable measures are unsuitable for predicting clinical outcomes. Measuring brain activity using task functional MRI (fMRI) is a major focus of biomarker development; however, the reliability of task fMRI has not been systematically evaluated. We present converging evidence demonstrating poor reliability of task-fMRI measures. First, a meta-analysis of 90 experiments (N = 1,008) revealed poor overall reliability-mean intraclass correlation coefficient (ICC) = .397. Second, the test-retest reliabilities of activity in a priori regions of interest across 11 common fMRI tasks collected by the Human Connectome Project (N = 45) and the Dunedin Study (N = 20) were poor (ICCs = .067-.485). Collectively, these findings demonstrate that common task-fMRI measures are not currently suitable for brain biomarker discovery or for individual-differences research. We review how this state of affairs came to be and highlight avenues for improving task-fMRI reliability.

Reliability of a functional magnetic resonance imaging task of emotional conflict in healthy participants

Task-based functional neuroimaging methods are increasingly being used to identify biomarkers of treatment response in psychiatric disorders. To facilitate meaningful interpretation of neural correlates of tasks and their potential changes with treatment over time, understanding the reliability of the blood-oxygen-level dependent (BOLD) signal of such tasks is essential. We assessed test-retest reliability of an emotional conflict task in healthy participants collected as part of the Canadian Biomarker Integration Network in Depression. Data for 36 participants, scanned at three time points (weeks 0, 2, and 8) were analyzed, and intra-class correlation coefficients (ICC) were used to quantify reliability. We observed moderate reliability (median ICC values between 0.5 and 0.6), within occipital, parietal, and temporal regions, specifically for conditions of lower cognitive complexity, that is, face, congruent or incongruent trials. For these conditions, activation was also observed within frontal and sub-cortical regions, however, their reliability was poor (median ICC < 0.2). Clinically relevant prognostic markers based on task-based fMRI require high predictive accuracy at an individual level. For this to be achieved, reliability of BOLD responses needs to be high. We have shown that reliability of the BOLD response to an emotional conflict task in healthy individuals is moderate. Implications of these findings to further inform studies of treatment effects and biomarker discovery are discussed.

Longitudinal changes in DLPFC activation during childhood are related to decreased aggression following social rejection

Regulating aggression after social feedback is an important prerequisite for developing and maintaining social relations, especially in the current times with larger emphasis on online social evaluation. Studies in adults highlighted the role of the dorsolateral prefrontal cortex (DLPFC) in regulating aggression. Little is known about the development of aggression regulation following social feedback during childhood, while this is an important period for both brain maturation and social relations. The current study used a longitudinal design, with 456 twins undergoing two functional MRI sessions across the transition from middle (7 to 9 y) to late (9 to 11 y) childhood. Aggression regulation was studied using the Social Network Aggression Task. Behavioral aggression after social evaluation decreased over time, whereas activation in the insula, dorsomedial PFC and DLPFC increased over time. Brain-behavior analyses showed that increased DLPFC activation after negative feedback was associated with decreased aggression. Change analyses further revealed that children with larger increases in DLPFC activity from middle to late childhood showed stronger decreases in aggression over time. These findings provide insights into the development of social evaluation sensitivity and aggression control in childhood.

Resting-state connectivity stratifies premanifest Huntington's disease by longitudinal cognitive decline rate

Patient stratification is critical for the sensitivity of clinical trials at early stages of neurodegenerative disorders. In Huntington’s disease (HD), genetic tests make cognitive, motor and brain imaging measurements possible before symptom manifestation (pre-HD). We evaluated pre-HD stratification models based on single visit resting-state functional MRI (rs-fMRI) data that assess observed longitudinal motor and cognitive change rates from the multisite Track-On HD cohort (74 pre-HD, 79 control participants). We computed longitudinal performance change on 10 tasks (including visits from the preceding TRACK-HD study when available), as well as functional connectivity density (FCD) maps in single rs-fMRI visits, which showed high test-retest reliability. We assigned pre-HD subjects to subgroups of fast, intermediate, and slow change along single tasks or combinations of them, correcting for expectations based on aging; and trained FCD-based classifiers to distinguish fast- from slow-progressing individuals. For robustness, models were validated across imaging sites. Stratification models distinguished fast- from slow-changing participants and provided continuous assessments of decline applicable to the whole pre-HD population, relying on previously-neglected white matter functional signals. These results suggest novel correlates of early deterioration and a robust stratification strategy where a single MRI measurement provides an estimate of multiple ongoing longitudinal changes.

Psychoradiological Biomarkers for Psychopharmaceutical Effects

The application of personalized medicine to psychiatry is challenging. Psychoradiology could provide biomarkers based on objective tests in support of the diagnostic classifications and treatment planning. We review potential psychoradiological biomarkers for psychopharmaceutical effects. Although none of the biomarkers reviewed are yet of sufficient clinical utility to inform the selection of a specific pharmacologic compound for an individual patient, there is strong consensus that advanced multimodal approaches will contribute to discovery of novel treatment predictors in psychiatric disorders. Progress has been sufficient to warrant enthusiasm, in which application of neuroimaging-based biomarkers would represent a paradigm shift and modernization of psychiatric practice.

Maternal overprotection in childhood is associated with amygdala reactivity and structural connectivity in adulthood

Recently, we reported that variability in early-life caregiving experiences maps onto individual differences in threat-related brain function. Here, we extend this work to provide further evidence that subtle variability in specific features of early caregiving shapes structural and functional connectivity between the amygdala and medial prefrontal cortex (mPFC) in a cohort of 312 young adult volunteers. Multiple regression analyses revealed that participants who reported higher maternal overprotection exhibited increased amygdala reactivity to explicit signals of interpersonal threat but not implicit signals of broad environmental threat. While amygdala functional connectivity with regulatory regions of the mPFC was not significantly associated with maternal overprotection, participants who reported higher maternal overprotection exhibited relatively decreased structural integrity of the uncinate fasciculus (UF), a white matter tract connecting these same brain regions. There were no significant associations between structural or functional brain measures and either maternal or paternal care ratings. These findings suggest that an overprotective maternal parenting style during childhood is associated with later functional and structural alterations of brain regions involved in generating and regulating responses to threat.

Assessing inter-individual differences with task-related functional neuroimaging

Explaining and predicting individual behavioural differences induced by clinical and social factors constitutes one of the most promising applications of neuroimaging. In this Perspective, we discuss the theoretical and statistical foundations of the analyses of inter-individual differences in task-related functional neuroimaging. Leveraging a five-year literature review (July 2013-2018), we show that researchers often assess how activations elicited by a variable of interest differ between individuals. We argue that the rationale for such analyses, typically grounded in resource theory, offers an over-large analytical and interpretational flexibility that undermines their validity. We also recall how, in the established framework of the general linear model, inter-individual differences in behaviour can act as hidden moderators and spuriously induce differences in activations. We conclude with a set of recommendations and directions, which we hope will contribute to improving the statistical validity and the neurobiological interpretability of inter-individual difference analyses in task-related functional neuroimaging.

Neural predictors of treatment response to brain stimulation and psychological therapy in depression: a double-blind randomized controlled trial

Standard depression treatments, including antidepressant medication and cognitive behavioural therapy (CBT), are ineffective for many patients. Prefrontal transcranial direct current stimulation (tDCS) has been proposed as an alternative treatment, but has shown inconsistent efficacy for depression, and its mechanisms are poorly understood. We recruited unmedicated patients with major depressive disorder (N = 71 approached; N = 39 randomised) for a mechanistic, double-blind, randomized controlled trial consisting of eight weekly sessions of prefrontal tDCS administered to the left prefrontal cortex prior to CBT. We probed (1) whether tDCS improved the efficacy of CBT relative to sham stimulation; and (2) whether neural measures predicted clinical response. We found a modest and non-significant effect of tDCS on clinical outcome over and above CBT (active: 50%; sham: 31.6%; odds ratio: 2.16, 95% CI = 0.59-7.99), but a strong relationship, predicted a priori, between baseline activation during a working memory task in the stimulated prefrontal region and symptom improvement. Repeating our analyses of symptom outcome splitting the sample according to this biomarker revealed that tDCS was significantly superior to sham in individuals with high left prefrontal cortex activation at baseline; we also show 86% accuracy in predicting clinical response using this measure. Exploratory analyses revealed several other regions where activation at baseline was associated with subsequent response to CBT, irrespective of tDCS. This mechanistic trial revealed variable, but predictable, clinical effects of prefrontal tDCS combined with CBT for depression. We have discovered a potential explanation for this variability: individual differences in baseline activation of the region stimulated. Such a biomarker could potentially be used to pre-select patients for trials and, eventually, in the clinic.

Neural correlates of weighted reward prediction error during reinforcement learning classify response to cognitive behavioral therapy in depression

While cognitive behavioral therapy (CBT) is an effective treatment for major depressive disorder, only up to 45% of depressed patients will respond to it. At present, there is no clinically viable neuroimaging predictor of CBT response. Notably, the lack of a mechanistic understanding of treatment response has hindered identification of predictive biomarkers. To obtain mechanistically meaningful fMRI predictors of CBT response, we capitalize on pretreatment neural activity encoding a weighted reward prediction error (RPE), which is implicated in the acquisition and processing of feedback information during probabilistic learning. Using a conventional mass-univariate fMRI analysis, we demonstrate that, at the group level, responders exhibit greater pretreatment neural activity encoding a weighted RPE in the right striatum and right amygdala. Crucially, using multivariate methods, we show that this activity offers significant out-of-sample classification of treatment response. Our findings support the feasibility and validity of neurocomputational approaches to treatment prediction in psychiatry.

Self-rated amygdala activity: an auto-biological index of affective distress

Auto-biological beliefs—beliefs about one’s own biology—are an understudied component of personal identity. Research participants who are led to believe they are biologically vulnerable to affective disorders report more symptoms and less ability to control their mood; however, little is known about the impact of self-originating beliefs about risk for psychopathology, and whether such beliefs correspond to empirically derived estimates of actual vulnerability. Participants in a neuroimaging study (n = 1256) completed self-report measures of affective symptoms, perceived stress, and neuroticism, and an emotional face processing task in the scanner designed to elicit threat responses from the amygdala. A subsample (n = 63) additionally rated their own perceived neural response to threat (i.e., amygdala activity) compared to peers. Self-ratings of neural threat response were uncorrelated with actual threat-related amygdala activity measured via BOLD fMRI. However, self-ratings predicted subjective distress across a variety of self-report measures. In contrast, in the full sample, threat-related amygdala activity was uncorrelated with self-report measures of affective distress. These findings suggest that beliefs about one’s own biological threat response—while unrelated to measured neural activation—may be informative indicators of psychological functioning.

Reliability of Fronto-Amygdala Coupling during Emotional Face Processing

One of the most exciting translational prospects for brain imaging research is the potential use of functional magnetic resonance imaging (fMRI) 'biomarkers' to predict an individual's risk of developing a neuropsychiatric disorder or the likelihood of responding to a particular intervention. This proposal depends critically on reliable measurements at the level of the individual. Several previous studies have reported relatively poor reliability of amygdala activation during emotional face processing, a key putative fMRI 'biomarker'. However, the reliability of amygdala connectivity measures is much less well understood. Here, we assessed the reliability of task-modulated coupling between three seed regions (left and right amygdala and the subgenual anterior cingulate cortex) and the dorsomedial frontal/cingulate cortex (DMFC), measured using a psychophysiological interaction analysis in 29 healthy individuals scanned approximately two weeks apart. We performed two runs on each day of three different emotional face-processing tasks: emotion identification, emotion matching, and gender classification. We tested both between-day reliability and within-day (between-run) reliability. We found good-to-excellent within-subject reliability of amygdala-DMFC coupling, both between days (in two tasks), and within day (in one task). This suggests that disorder-relevant regional coupling may be sufficiently reliable to be used as a predictor of treatment response or clinical risk in future clinical studies.