Toward clinically useful neuroimaging in depression treatment: prognostic utility of subgenual cingulate activity for determining depression outcome in cognitive therapy across studies, scanners, and patient characteristics

Subcallosal area 25: Its responsivity to the stress hormone cortisol and its opposing effects on appetitive motivation in marmosets

Aberrant activity in caudal subcallosal anterior cingulate cortex (scACC) is implicated in depression and anxiety symptomatology, with its normalisation a putative biomarker of successful treatment response. The function of scACC in emotion processing and mental health is not fully understood despite its known influence on stress-mediated processes through its rich expression of mineralocorticoid and glucocorticoid receptors. Here we examine the causal interaction between area 25 within scACC (scACC-25) and the stress hormone, cortisol, in the context of anhedonia and anxiety-like behaviour. In addition, the overall role of scACC-25 in hedonic capacity and motivation is investigated under transient pharmacological inactivation and overactivation. The results suggest that a local increase of cortisol in scACC-25 shows a rapid induction of anticipatory anhedonia and increased responsiveness to uncertain threat. Separate inactivation and overactivation of scACC-25 increased and decreased motivation and hedonic capacity, respectively, likely through different underlying mechanisms. Together, these data show that area scACC-25 has a causal role in consummatory and motivational behaviour and produces rapid responses to the stress hormone cortisol, that mediates anhedonia and anxiety-like behaviour.

Trying to name what doesn't change: Neural nonresponse to Cognitive Therapy for depression

BACKGROUND

Theoretical models of neural mechanisms underlying Cognitive Behavior Therapy (CBT) for major depressive disorder (MDD) propose that psychotherapy changes neural functioning of prefrontal cortical structures associated with cognitive-control processes (DeRubeis, Siegle, & Hollon, ); however, MDD is persistent and characterized by long-lasting vulnerabilities to recurrence after intervention, suggesting that underlying neural mechanisms of MDD remain despite treatment. It follows that identification of treatment-resistant aberrant neural processes in MDD may inform clinical and research efforts targeting sustained remission. Thus, we sought to identify brain regions showing aberrant neural functioning in MDD that either (1) fail to exhibit substantive change (nonresponse) or (2) exhibit functional changes (response) following CBT.

METHODS

To identify treatment-resistant neural processes (as well as neural processes exhibiting change after treatment), we collected functional magnetic resonance imaging (fMRI) data of MDD patients (n = 58) before and after CBT as well as never-depressed controls (n = 35) before and after a similar amount of time. We evaluated fMRI data using conjunction analyses, which utilized several contrast-based criteria to characterize brain regions showing both differences between patients and controls at baseline and nonresponse or response to CBT.

RESULTS

Findings revealed nonresponse in a cerebellar region and response in prefrontal and parietal regions.

CONCLUSIONS

Results are consistent with prior theoretical models of CBT's direct effect on cortical regulatory processes but expand on them with identification of additional regions (and associated neural systems) of response and nonresponse to CBT.

Temporally specific patterns of neural activity in interconnected corticolimbic structures during reward anticipation

Functional neuroimaging studies indicate that interconnected parts of the subcallosal anterior cingulate cortex (ACC), striatum, and amygdala play a fundamental role in affect in health and disease. Yet, although the patterns of neural activity engaged in the striatum and amygdala during affective processing are well established, especially during reward anticipation, less is known about subcallosal ACC. Here, we recorded neural activity in non-human primate subcallosal ACC and compared this with interconnected parts of the basolateral amygdala and rostromedial striatum while macaque monkeys performed reward-based tasks. Applying multiple analysis approaches, we found that neurons in subcallosal ACC and rostromedial striatum preferentially signal anticipated reward using short bursts of activity that form temporally specific patterns. By contrast, the basolateral amygdala uses a mixture of both temporally specific and more sustained patterns of activity to signal anticipated reward. Thus, dynamic patterns of neural activity across populations of neurons are engaged in affect, especially in subcallosal ACC.

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.

Subgenual Anterior Cingulate Cortex Reactivity to Rejection Vs. Acceptance Predicts Depressive Symptoms among Adolescents with an Anxiety History

OBJECTIVE

The goal of this study was to examine whether neural sensitivity to negative peer evaluation conveys risk for depression among youth with a history of anxiety. We hypothesized that brain activation in regions that process affective salience in response to rejection, relative to acceptance, from virtual peers would predict depressive symptoms 1 year later and would be associated with ecological momentary assessment (EMA) reports of peer connectedness.

METHOD

Participants were 38 adolescents ages 11-16 (50% female) with a history of anxiety, recruited from a previous clinical trial. The study was a prospective naturalistic follow-up of depressive symptoms assessed 2 years (Wave 2) and 3 years (Wave 3) following treatment. At Wave 2, participants completed the Chatroom Interact Task during neuroimaging and 16 days of EMA.

RESULTS

Controlling for depressive and anxiety symptoms at Wave 2, subgenual anterior cingulate (sgACC; β = .39, p = .010) activation to peer rejection (vs. acceptance) predicted depressive symptoms at Wave 3. SgACC activation to rejection (vs. acceptance) was highly negatively correlated with EMA reports of connectedness with peers in daily life (r = - .71, p < .001).

CONCLUSION

Findings suggest that elevated sgACC activation to negative, relative to positive, peer evaluation may serve as a risk factor for depressive symptoms among youth with a history of anxiety, perhaps by promoting vigilance or reactivity to social evaluative threats. SgACC activation to simulated peer evaluation appears to have implications for understanding how adolescents experience their daily social environments in ways that could contribute to depressive symptoms.

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.

Can neuroimaging measures differentiate the disease course of anorexia nervosa? A systematic review

Anorexia nervosa (AN) entails many uncertainties regarding the clinical outcome, due to large heterogeneity in the disease course. AN is associated with global decrease in brain volumes and altered brain functioning during acute illness. However, it is unclear whether structural and functional brain alterations can predict clinical outcome. We aimed to systematically review the predictive value of volumetric and functional brain outcome measures of structural and functional brain magnetic resonance imaging (MRI) on the disease course of AN. Four databases (Embase, Medline, Psycinfo, and Cochrane Central Register) were systematically searched. A total of 15 studies (structural MRI: n = 6, functional MRI: n = 9) were reviewed. In total 464 unique AN patients, and 328 controls were included. Follow-up time ranged between 1 and 43 months. Structural neuroimaging studies showed that lower brain volumes of the cerebellum, subcortical grey matter, and cortical white matter at admission predicted a worse clinical outcome. A smaller increase of the anterior cingulate cortex volume in the early phase of the disease predicted a worse clinical outcome. Lower overall gyrification, and a higher clustering coefficient predicted a worse clinical outcome. Functional MRI studies showed that frontal, parietal and temporal activity during task-based algorithms predicted follow-up body mass index, although results were bidirectional possibly due to the large heterogeneity in methodological approaches. Neuroimaging measures may predict the clinical outcome of AN. However, there is a lack of replication studies. Future studies are needed to validate the prognostic utility of neuroimaging measures in AN patients, and should harmonize demographic, clinical and neuroimaging features in order to enhance comparability.

Reduced anhedonia following internet-based cognitive-behavioral therapy for depression is mediated by enhanced reward circuit activation

BACKGROUND

Major depressive disorder (MDD) is a highly prevalent psychiatric condition, yet many patients do not receive adequate treatment. Novel and highly scalable interventions such as internet-based cognitive-behavioral-therapy (iCBT) may help to address this treatment gap. Anhedonia, a hallmark symptom of MDD that refers to diminished interest and ability to experience pleasure, has been associated with reduced reactivity in a neural reward circuit that includes medial prefrontal and striatal brain regions. Whether iCBT can reduce anhedonia severity in MDD patients, and whether these therapeutic effects are accompanied by enhanced reward circuit reactivity has yet to be examined.

METHODS

Fifty-two MDD patients were randomly assigned to either 10-week iCBT (n = 26) or monitored attention control (MAC, n = 26) programs. All patients completed pre- and post-treatment assessments of anhedonia (Snaith-Hamilton Pleasure Scale; SHAPS) and reward circuit reactivity [monetary incentive delay (MID) task during functional magnetic resonance imaging (fMRI)]. Healthy control participants (n = 42) also underwent two fMRI scans while completing the MID task 10 weeks apart.

RESULTS

Both iCBT and MAC groups exhibited a reduction in anhedonia severity post-treatment. Nevertheless, only the iCBT group exhibited enhanced nucleus accumbens (Nacc) and subgenual anterior cingulate cortex (sgACC) activation and functional connectivity from pre- to post-treatment in response to reward feedback. Enhanced Nacc and sgACC activations were associated with reduced anhedonia severity following iCBT treatment, with enhanced Nacc activation also mediating the reduction in anhedonia severity post-treatment.

CONCLUSIONS

These findings suggest that increased reward circuit reactivity may contribute to a reduction in anhedonia severity following iCBT treatment for depression.

Associations between resting-state neural connectivity and positive affect in social anxiety disorder

INTRODUCTION

Social anxiety disorder (SAD) has been characterized by deficits in social motivation and lack of reactivity to pleasurable stimuli (i.e., positive affect; [PA]). Recent neuroimaging work has shifted toward examining positively valenced motivational systems in SAD focused on reward responses. However, little is known about the associations of reward connectivity and PA in individuals with SAD. As such, the purpose of the current study was to determine whether connectivity among key units of reward neurocircuitry meaningfully relate to PA and whether these key units are more heterogeneous in SAD as compared to controls.

METHODS

Thirty-one participants who met diagnostic criteria for SAD and 33 control participants were included (Mage = 24.8, SD = 6.9; 55% cisgender man). Seed-based timeseries correlations were conducted in NiTime to extract region of interest (ROI) coupling correlation strength values. ANOVAs were carried out to assess whether individuals with SAD differed in ROI-to-ROI connectivity strength as compared to controls. Correlations and variance analyses were also conducted to examine the relationship between ROI-to-ROI connectivity strength and PA, as well as heterogeneity in connectivity strength and PA expression.

RESULTS

Weaker connectivity between the left and right orbital frontal cortex was observed when comparing the SAD to the control group. Within the SAD group, PA was associated with several reward-related ROI couplings; however, these links were not observed among controls. Results further demonstrated that individuals with SAD had significantly more variability in reward connectivity strength as compared to controls.

CONCLUSION

Overall, these results provide emergent evidence for the association between reward regions and PA in individuals with SAD. Additionally, these findings show that individuals with SAD demonstrate greater heterogeneity in reward connectivity.

The timing of transcranial magnetic stimulation relative to the phase of prefrontal alpha EEG modulates downstream target engagement

BACKGROUND

The communication through coherence model posits that brain rhythms are synchronized across different frequency bands and that effective connectivity strength between interacting regions depends on their phase relation. Evidence to support the model comes mostly from electrophysiological recordings in animals while evidence from human data is limited.

METHODS

Here, an fMRI-EEG-TMS (fET) instrument capable of acquiring simultaneous fMRI and EEG during noninvasive single pulse TMS applied to dorsolateral prefrontal cortex (DLPFC) was used to test whether prefrontal EEG alpha phase moderates TMS-evoked top-down influences on subgenual, rostral and dorsal anterior cingulate cortex (ACC). Six runs (276 total trials) were acquired in each participant. Phase at each TMS pulse was determined post-hoc using single-trial sorting. Results were examined in two independent datasets: healthy volunteers (HV) (n = 11) and patients with major depressive disorder (MDD) (n = 17) collected as part of an ongoing clinical trial.

RESULTS

In both groups, TMS-evoked functional connectivity between DLPFC and subgenual ACC (sgACC) depended on the EEG alpha phase. TMS-evoked DLPFC to sgACC fMRI-derived effective connectivity (EC) was modulated by EEG alpha phase in healthy volunteers, but not in the MDD patients. Top-down EC was inhibitory for TMS pulses during the upward slope of the alpha wave relative to TMS timed to the downward slope of the alpha wave. Prefrontal EEG alpha phase dependent effects on TMS-evoked fMRI BOLD activation of the rostral anterior cingulate cortex were detected in the MDD patient group, but not in the healthy volunteer group.

DISCUSSION

Results demonstrate that TMS-evoked top-down influences vary as a function of the prefrontal alpha rhythm, and suggest potential clinical applications whereby TMS is synchronized to the brain's internal rhythms in order to more efficiently engage deep therapeutic targets.

Personalized Repetitive Transcranial Magnetic Stimulation for Depression

Personalized treatments are gaining momentum across all fields of medicine. Precision medicine can be applied to neuromodulatory techniques, in which focused brain stimulation treatments such as repetitive transcranial magnetic stimulation (rTMS) modulate brain circuits and alleviate clinical symptoms. rTMS is well tolerated and clinically effective for treatment-resistant depression and other neuropsychiatric disorders. Despite its wide stimulation parameter space (location, angle, pattern, frequency, and intensity can be adjusted), rTMS is currently applied in a one-size-fits-all manner, potentially contributing to its suboptimal clinical response (∼50%). In this review, we examine components of rTMS that can be optimized to account for interindividual variability in neural function and anatomy. We discuss current treatment options for treatment-resistant depression, the neural mechanisms thought to underlie treatment, targeting strategies, stimulation parameter selection, and adaptive closed-loop treatment. We conclude that a better understanding of the wide and modifiable parameter space of rTMS will greatly improve the clinical outcome.

Changes in neural activity following a randomized trial of cognitive behavioral therapy for hoarding disorder

OBJECTIVE

Cognitive behavioral therapy (CBT) is efficacious for hoarding disorder (HD), though results are modest. HD patients show an increase in activity in the dorsal anterior cingulate cortex (dACC) when making decisions. The aim of this study is to determine whether CBT's benefits follow improvements in dACC dysfunction or abnormalities previously identified in other brain regions.

METHOD

In this randomized clinical trial of 64 treatment-seeking HD patients, patients received group CBT, delivered weekly for 16 weeks, versus wait list. Functional magnetic resonance imaging was used to examine neural activity during simulated decisions about whether to acquire and discard objects.

RESULTS

During acquiring decisions, activity decreased in several regions, including right dorsolateral prefrontal, right anterior intraparietal area, both right and left medial intraparietal areas, left and right amygdala, and left accumbens. During discarding decisions, activity decreased in right and left dorsolateral prefrontal, right and left rostral cingulate, left anterior ventral insular cortex, and right medial intraparietal areas. None of the a priori brain parcels of interest significantly mediated symptom reduction. Moderation effects were found for left rostral cingulate, right and left caudal cingulate, and left medial intraparietal parcels.

CONCLUSIONS

Therapeutic benefits of CBT for HD do not appear to be mediated by changes in dACC activation. However, pretreatment dACC activation predicts outcome. Findings suggest the need to re-evaluate emerging neurobiological models of HD and our understanding of how CBT affects the brain in HD, and perhaps shift focuses to new neural target discovery and target engagement trials. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Pupillary motility responses to affectively salient stimuli in individuals with depression or elevated risk of depression: A systematic review and meta-analysis

Elaborative affective processing is observed in depression, and pupillary reactivity, a continuous, sensitive, and reliable indicator of physiological arousal and neurocognitive processing, is increasingly utilized in studies of depression-related characteristics. As a first attempt to quantitively summarize existing evidence on depression-related pupillary reactivity alterations, this review and meta-analysis evaluated the direction, magnitude, and specificity of pupillary indices of affective processing towards positively, negatively, and neutrally-valenced stimuli among individuals diagnosed with depression or with elevated risk of depression. Studies on pupillary responses to affective stimuli in the target groups were identified in PsycINFO and PubMed databases. Twenty-two articles met inclusion criteria for the qualitative review and 16 for the quantitative review. Three-level frequentist and Bayesian models were applied to summarize pooled effects from baseline-controlled stimuli-induced average changes in pupillary responses. In general, compared to non-depressed individuals, individuals with depression or elevated risk of depression exhibited higher pupillary reactivity (d =0.15) towards negatively-valenced stimuli during affective processing. Pupillary motility towards negatively-valenced stimuli may be a promising trait-like marker for depression vulnerability.

Evaluating depression- and anxiety-like behaviors in non-human primates

Depression and anxiety are some of the most prevalent and debilitating mental health conditions in humans. They can present on their own or as co-morbidities with other disorders. Like humans, non-human primates (NHPs) can develop depression- and anxiety-like signs. Here, we first define human depression and anxiety, examine equivalent species-specific behaviors in NHPs, and consider models and current methods to identify and evaluate these behaviors. We also discuss knowledge gaps, as well as the importance of evaluating the co-occurrence of depression- and anxiety-like behaviors in animal models of human disease. Lastly, we consider ethical challenges in depression and anxiety research on NHPs in order to ultimately advance the understanding and the personalized treatment of these disorders.

Neural correlates of psychodynamic and non-psychodynamic therapies in different clinical populations through fMRI: A meta-analysis and systematic review

Background

The COVID-19 pandemic has exacerbated the ongoing crisis in psychiatric and psychological care, contributing to what we have identified as a new psychological and psychiatric pandemic. Psychotherapy is an effective method for easing the psychological suffering experienced also by the various impacts of COVID-19. This treatment can be examined from a neurological perspective, through the application of brain imaging techniques. Specifically, the meta-analysis of imaging studies can aid in expanding researchers' understanding of the many beneficial applications of psychotherapy.

Objectives

We examined the functional brain changes accompanying different mental disorders with functional Magnetic Resonance Imaging (fMRI), through a meta-analysis, and systematic review in order to better understand the general neural mechanism involved in psychotherapy and the potential neural difference between psychodynamic and non-psychodynamic approaches.

Data sources

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were employed for our systematic review and meta-analysis. We conducted a computer-based literature search, following the Population, Intervention, Comparison and Outcomes (PICO) approach, to retrieve all published articles in English regarding the above-described topics from PubMed (MEDLINE), Scopus, and Web of Science.

Study eligibility criteria participants and interventions

We combined terms related to psychotherapy and fMRI: ("psychotherapy" [All Fields] OR "psychotherapy" [MeSH Terms] OR "psychotherapy" [All Fields] OR "psychotherapies" [All Fields] OR "psychotherapy s" [All Fields]) AND ("magnetic resonance imaging" [MeSH Terms]) OR ("magnetic"[All Fields] AND "resonance"[All Fields] AND "imaging"[All Fields]) OR ("magnetic resonance imaging"[All Fields] OR "fmri"[All Fields]). We considered (1) whole brain fMRI studies; (2) studies in which participants have been involved in a clinical trial with psychotherapy sessions, with pre/post fMRI; (3) fMRI results presented in coordinate-based (x, y, and z) in MNI or Talairach space; (4) presence of neuropsychiatric patients. The exclusion criteria were: (1) systematic review or meta-analysis; (2) behavioral study; (3) single-case MRI or fMRI study; and (4) other imaging techniques (i.e., PET, SPECT) or EEG.

Results

After duplicates removal and assessment of the content of each published study, we included 38 sources. The map including all studies that assessed longitudinal differences in brain activity showed two homogeneous clusters in the left inferior frontal gyrus, and caudally involving the anterior insular cortex (p < 0.0001, corr.). Similarly, studies that assessed psychotherapy-related longitudinal changes using emotional or cognitive tasks (TASK map) showed a left-sided homogeneity in the anterior insula (p < 0.000) extending to Broca's area of the inferior frontal gyrus (p < 0.0001) and the superior frontal gyrus (p < 0.0001). Studies that applied psychodynamic psychotherapy showed Family-Wise Error (FWE) cluster-corrected (p < 0.05) homogeneity values in the right superior and inferior frontal gyri, with a small cluster in the putamen. No FWE-corrected homogeneity foci were observed for Mindful- based and cognitive behavioral therapy psychotherapy. In both pre- and post-therapy results, studies showed two bilateral clusters in the dorsal anterior insulae (p = 0.00001 and p = 0.00003, respectively) and involvement of the medial superior frontal gyrus (p = 0.0002).

Limitations

Subjective experiences, such as an individual's response to therapy, are intrinsically challenging to quantify as objective, factual realities. Brain changes observed both pre- and post-therapy could be related to other factors, not necessary to the specific treatment received. Therapeutic modalities and study designs are generally heterogeneous. Differences exist in sample characteristics, such as the specificity of the disorder and number and duration of sessions. Moreover, the sample size is relatively small, particularly due to the paucity of studies in this field and the little contribution of PDT.

Conclusions and implications of key findings

All psychological interventions seem to influence the brain from a functional point of view, showing their efficacy from a neurological perspective. Frontal, prefrontal regions, insular cortex, superior and inferior frontal gyrus, and putamen seem involved in these neural changes, with the psychodynamic more linked to the latter three regions.

Increased sensitivity of insula to supraliminal faces in adults with histories of mood disorders and self-injury

BACKGROUND

Mood disorders are associated with neurobiological disruptions in subliminal and supraliminal emotion processing. There may be additional variation based on sex and the presence of self-injurious thoughts and behaviors (SITBs). Examining individuals in remission allows us to understand trait-like emotion processing characteristics that persist in the absence of symptoms. This study investigates neural processing in response to supraliminal and subliminal emotional stimuli based upon mood disorder diagnosis, sex, and SITBs.

METHODS

Seventy-five participants with a history of any mood disorder (AMD; 52 female) and 27 healthy controls (HC; 14 female) completed a fMRI task presenting subliminal and supraliminal facial stimuli. Within the AMD group, 20 had no history of SITBs, 26 had histories of suicidal ideation only, and 27 had histories of both SI and self-injurious behavior. We examined activation of salience network regions of interest including the amygdala, insula, and subgenual anterior cingulate cortex (sgACC) during the task.

RESULTS

AMD showed greater insula activation in response to happy faces relative to sad faces, which was not seen in the HC group. Males exhibited lower insula activation in response to sad faces relative happy faces, a pattern not seen in females. Individuals with SITBs demonstrated a lack of sgACC blunting during supraliminal versus subliminal trials.

CONCLUSIONS

We found different patterns of neural responses related to mood disorder status, sex, and SITBs. Findings highlight the importance of considering heterogeneity within diagnoses and examining neurobiological features in the context of remission.

The effect of early cognitive behavior therapy for first-episode treatment-naive major depressive disorder

BACKGROUND

Major depressive disorder (MDD) is one of the most prevalent psychiatric disorders. Cognitive behavioral therapy (CBT) has been widely applied in MDD treatment, yet mechanistic understanding toward CBT remains limited.

METHODS

Twenty-two MDD patients and twenty-seven matched healthy controls were enrolled. Patients with MDD were given structural early CBT treatment once a week for 6 weeks. Cognitive reconstruction, emotional transformation and behavioral training were included in the treatment process. Local and long-range brain functional connectivity densities (FCD) were obtained to identify abnormal connectivity of MDD by using resting-state functional magnetic resonance imaging (RS-fMRI).

RESULTS

After CBT treatment, MDD patients showed increased FCD in the bilateral dorsolateral prefrontal cortex (dlPFC). Functional connectivity (FC) was used to further explore the role of dlPFC in CBT. The results revealed that by the completion of CBT treatment course, the FC between the dlPFC and hippocampus was enhanced.

CONCLUSIONS

Cognitive behavioral therapy played significant role in alleviating depressive symptoms of MDD patients, evidenced by improved brain connectivity between dlPFC and hippocampus. Further study of dlPFC pathophysiology is needed to better understand these abnormalities in patients with depressive symptoms and the effect of early CBT treatment.

The functional and structural associations of aberrant microglial activity in major depressive disorder

BACKGROUND

Major depressive disorder (MDD) is a debilitating mental illness that has been linked to increases in markers of inflammation, as well as to changes in brain functional and structural connectivity, particularly between the insula and the subgenual anterior cingulate cortex (sgACC). In this study, we directly related inflammation and dysconnectivity in treatment-resistant MDD by concurrently measuring the following: microglial activity with [¹⁸F]N-2-(fluoroethoxyl)benzyl-N-(4phenoxypyridin-3-yl)acetamide ([¹⁸F]FEPPA) positron emission tomography (PET); the severity of MDD; and functional or structural connectivity among insula or sgACC nodes.

METHODS

Twelve patients with treatment-resistant MDD (8 female, 4 male; mean age ± standard deviation 54.9 ± 4.5 years and 23 healthy controls (11 female, 12 male; 60.3 ± 8.5 years) completed a hybrid [¹⁸F]FEPPA PET and MRI acquisition. From these, we extracted relative standardized uptake values for [¹⁸F]FEPPA activity and Pearson r-to-z scores representing functional connectivity from our regions of interest. We extracted diffusion tensor imaging metrics from the cingulum bundle, a key white matter bundle in MDD. We performed regressions to relate microglial activity with functional connectivity, structural connectivity and scores on the 17-item Hamilton Depression Rating Scale.

RESULTS

We found significantly increased [¹⁸F]FEPPA uptake in the left sgACC in patients with treatment-resistant MDD compared to healthy controls. Patients with MDD also had a reduction in connectivity between the sgACC and the insula. The [¹⁸F]FEPPA uptake in the left sgACC was significantly related to functional connectivity with the insula, and to the structural connectivity of the cingulum bundle. [¹⁸F]FEPPA uptake also predicted scores on the Hamilton Depression Rating Scale.Limitations: A relatively small sample size, lack of functional task data and concomitant medication use may have affected our findings.

CONCLUSION

We present preliminary evidence linking a network-level dysfunction relevant to the pathophysiology of depression and related to increased microglial activity in MDD.

Anterior cingulate cortex activation during attentional control as a transdiagnostic marker of psychotherapy response: a randomized clinical trial

Anterior cingulate cortex (ACC) response during attentional control in the context of task-irrelevant emotional faces is a promising biomarker of cognitive behavioral therapy (CBT) outcome in patients with social anxiety disorder (SAD). However, it is unclear whether this biomarker extends to major depressive disorder (MDD) and is specific to CBT outcome. In the current study, 72 unmedicated patients with SAD (n = 39) or MDD (n = 33) completed a validated emotional interference paradigm during functional magnetic resonance imaging before treatment. Participants viewed letter strings superimposed on task-irrelevant threat and neutral faces under low perceptual load (high interference) and high perceptual load (low interference). Biomarkers comprised anatomy-based rostral ACC (rACC) and dorsal ACC (dACC) response to task-irrelevant threat (>neutral) faces under low and high perceptual load. Patients were randomly assigned to 12 weeks of CBT or supportive therapy (ST) (ClinicalTrials.gov identifier: NCT03175068). Clinician-administered measures of social anxiety and depression severity were obtained at baseline and every 2 weeks throughout treatment (7 assessments total) by an assessor blinded to the treatment arm. A composite symptom severity score was submitted to latent growth curve models. Results showed more baseline rACC activity to task-irrelevant threat>neutral faces under low, but not high, perceptual load predicted steeper trajectories of symptom improvement throughout CBT or ST. Post-hoc analyses indicated this effect was driven by subgenual ACC (sgACC) activation. Findings indicate ACC activity during attentional control may be a transdiagnostic neural predictor of general psychotherapy outcome.

Using Brain Imaging to Improve Spatial Targeting of Transcranial Magnetic Stimulation for Depression

Transcranial magnetic stimulation (TMS) is an effective treatment for depression but is limited in that the optimal therapeutic target remains unknown. Early TMS trials lacked a focal target and thus positioned the TMS coil over the prefrontal cortex using scalp measurements. Over time, it became clear that this method leads to variation in the stimulation site and that this could contribute to heterogeneity in antidepressant response. Newer methods allow for precise positioning of the TMS coil over a specific brain location, but leveraging these precise methods requires a more precise therapeutic target. We review how neuroimaging is being used to identify a more focal therapeutic target for depression. We highlight recent studies showing that more effective TMS targets in the frontal cortex are functionally connected to deep limbic regions such as the subgenual cingulate cortex. We review how connectivity might be used to identify an optimal TMS target for use in all patients and potentially even a personalized target for each individual patient. We address the clinical implications of this emerging field and highlight critical questions for future research.

Differential patterns of dynamic functional connectivity variability in major depressive disorder treated with cognitive behavioral therapy

BACKGROUND

Numerous studies have shown that major depressive disorder (MDD) is characterized by a range of impairments in emotional and cognitive functions that are closely related to abnormalities in brain structure and function. Cognitive behavioral therapy (CBT) can be used as treatment for mild to moderate MDD, which can assist with ameliorating the symptoms. Previous studies have assumed that the internal fluctuations throughout the entire scan are static. However, it has recently been suggested that the brain connectivity is dynamic and relative to continuous rhythmic activity. The effect of dynamic changes in CBT on MDD patients is unknown.

METHODS

Nineteen first-episode, unmedicated MDD patients and twenty-two healthy controls (HC) participated in the study. The patients received early CBT treatment once a week for 6 weeks. Symptom examinations and magnetic resonance imaging (MRI) scans were performed pre and post treatment. Degree centrality (DC) was used to investigate the whole-brain connectivity differences between patients with MDD and healthy controls, and sliding window correlation analysis was applied to investigate the dynamic changes of functional connectivity among MDD patients treated with CBT. The variance of dynamic functional connectivity (dFC) was calculated to evaluate the temporal variability along the time.

RESULTS

Patients with MDD showed abnormal DC in dorsolateral prefrontal cortex (dlPFC), insula and postcentral gyrus. Correlation analysis revealed that degree centrality of dlPFC was negatively correlated with the course of disease in patients with MDD. Results of dynamic functional connectivity showed that, compared to HC, MDD patients-remained excessively stable in dlPFC and precuneus connectivity, which is associated with emotional cognitive symptoms. After CBT, patients showed increased dFC variability in dlPFC and precuneus (p < 0.01, GRF corrected).

CONCLUSION

DLPFC plays an important role in pathophysiological mechanism of MDD. CBT helped patients suppress redundant thoughts and negative self-focus. As a connecting node, dlPFC participates in the mechanism of action of CBT.

Sex-Specific Abnormalities and Treatment-Related Plasticity of Subgenual Anterior Cingulate Cortex Functional Connectivity in Chronic Pain

The subgenual anterior cingulate cortex (sgACC) is a key node of the descending antinociceptive system with sex differences in its functional connectivity (FC). We previously reported that, in a male-prevalent chronic pain condition, sgACC FC is abnormal in women but not in men. This raises the possibility that, within a sex, sgACC FC may be either protective or represent a vulnerability to develop a sex-dominant chronic pain condition. The aim of this study was to characterize sgACC FC in a female-dominant chronic pain condition, carpal tunnel syndrome (CTS), to investigate whether sgACC abnormalities are a common feature in women with chronic pain or unique to individuals with pain conditions that are more prevalent in the opposite sex. We used fMRI to determine the resting state FC of the sgACC in healthy controls (HCs, n = 25, 18 women; 7 men) and people with CTS before (n = 25, 18 women; 7 men) and after (n = 17, 13 women; 4 men) successful surgical treatment. We found reduced sgACC FC with the medial pre-frontal cortex (mPFC) and temporal lobe in CTS compared with HCs. The group-level sgACC-mPFC FC abnormality was driven by men with CTS, while women with CTS did not have sgACC FC abnormalities compared with healthy women. We also found that age and sex influenced sgACC FC in both CTS and HCs, with women showing greater FC with bilateral frontal poles and men showing greater FC with the parietal operculum. After surgery, there was reduced sgACC FC with the orbitofrontal cortex, striatum, and premotor areas and increased FC with the posterior insula and precuneus compared with pre-op scans. Abnormally reduced sgACC-mPFC FC in men but not women with a female-prevalent chronic pain condition suggests pain-related sgACC abnormalities may not be specific to women but rather to individuals who develop chronic pain conditions that are more dominant in the opposite sex. Our data suggest the sgACC plays a role in chronic pain in a sex-specific manner, and its communication with other regions of the dynamic pain connectome undergoes plasticity following pain-relieving treatment, supporting it as a potential therapeutic target for neuromodulation in chronic pain.

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.

Combining transcranial magnetic stimulation with functional magnetic resonance imaging for probing and modulating neural circuits relevant to affective disorders

Combining transcranial magnetic stimulation (TMS) with functional magnetic resonance imaging offers an unprecedented tool for studying how brain networks interact in vivo and how repetitive trains of TMS modulate those networks among patients diagnosed with affective disorders. TMS compliments neuroimaging by allowing the interrogation of causal control among brain circuits. Together with TMS, neuroimaging can provide valuable insight into the mechanisms underlying treatment effects and downstream circuit communication. Here we provide a background of the method, review relevant study designs, consider methodological and equipment options, and provide statistical recommendations. We conclude by describing emerging approaches that will extend these tools into exciting new applications. This article is categorized under: Psychology > Emotion and Motivation Psychology > Theory and Methods Neuroscience > Clinical Neuroscience.

Using Neuroscience to Augment Behavioral Interventions for Depression

Depression is both prevalent and costly, and many individuals do not adequately respond to existing psychopharmacological and behavioral interventions. The current article describes the use of neuroscience in augmenting behavioral interventions for depression in two primary areas: anhedonia and cognitive deficits/biases. Neuroscience research has increased our understanding of the neural bases of reward processing and regulation of positive affect, and anhedonia among depressed samples can be related to deficits in each of these domains. Treatments that specifically target reward processing and regulation of positive affect in order to reduce anhedonia represent a recent advance in the field. Depression is also associated with aberrant processes relating to working memory, autobiographical memory, attentional bias, and interpretive bias. Neuroscience findings have increasingly been leveraged to augment the efficacy of cognitive-training and bias-modification interventions in these domains. The use of neuroscience to inform the development and augmentation of behavioral interventions for depression is a promising avenue of continued research.

Prolonged ketamine infusion modulates limbic connectivity and induces sustained remission of treatment-resistant depression

Ketamine produces a rapid antidepressant response in over 50% of adults with treatment-resistant depression. A long infusion of ketamine may provide durable remission of depressive symptoms, but the safety, efficacy, and neurobiological correlates are unknown. In this open-label, proof-of-principle study, adults with treatment-resistant depression (N = 23) underwent a 96-h infusion of intravenous ketamine (0.15 mg/kg/h titrated toward 0.6 mg/kg/h). Clonidine was co-administered to reduce psychotomimetic effects. We measured clinical response for 8 weeks post-infusion. Resting-state functional magnetic resonance imaging was used to assess functional connectivity in patients pre- and 2 weeks post-infusion and in matched non-depressed controls (N = 27). We hypothesized that responders to therapy would demonstrate response-dependent connectivity changes while all subjects would show treatment-dependent connectivity changes. Most participants completed infusion (21/23; mean final dose 0.54 mg/kg/h, SD 0.13). The infusion was well tolerated with minimal cognitive and psychotomimetic side effects. Depressive symptoms were markedly reduced (MADRS 29 ± 4 at baseline to 9 ± 8 one day post-infusion), which was sustained at 2 weeks (13 ± 8) and 8 weeks (15 ± 8). Imaging demonstrated a response-dependent decrease in hyperconnectivity of the subgenual anterior cingulate cortex to the default mode network, and a treatment-dependent decrease in hyperconnectivity within the limbic system (hippocampus, amygdala, medial thalamus, nucleus accumbens). In exploratory analyses, connectivity was increased between the limbic system and frontal areas, and smaller right hippocampus volume at baseline predicted larger MADRS change. A single prolonged infusion of ketamine provides a tolerated, rapid, and sustained response in treatment-resistant depression and normalizes depression-related hyperconnectivity in the limbic system and frontal lobe. ClinicalTrials.gov : Treatment Resistant Depression (Pilot), NCT01179009.

Magnetic resonance imaging for individual prediction of treatment response in major depressive disorder: a systematic review and meta-analysis

No tools are currently available to predict whether a patient suffering from major depressive disorder (MDD) will respond to a certain treatment. Machine learning analysis of magnetic resonance imaging (MRI) data has shown potential in predicting response for individual patients, which may enable personalized treatment decisions and increase treatment efficacy. Here, we evaluated the accuracy of MRI-guided response prediction in MDD. We conducted a systematic review and meta-analysis of all studies using MRI to predict single-subject response to antidepressant treatment in patients with MDD. Classification performance was calculated using a bivariate model and expressed as area under the curve, sensitivity, and specificity. In addition, we analyzed differences in classification performance between different interventions and MRI modalities. Meta-analysis of 22 samples including 957 patients showed an overall area under the bivariate summary receiver operating curve of 0.84 (95% CI 0.81-0.87), sensitivity of 77% (95% CI 71-82), and specificity of 79% (95% CI 73-84). Although classification performance was higher for electroconvulsive therapy outcome prediction (n = 285, 80% sensitivity, 83% specificity) than medication outcome prediction (n = 283, 75% sensitivity, 72% specificity), there was no significant difference in classification performance between treatments or MRI modalities. Prediction of treatment response using machine learning analysis of MRI data is promising but should not yet be implemented into clinical practice. Future studies with more generalizable samples and external validation are needed to establish the potential of MRI to realize individualized patient care in MDD.

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.

Translational application of neuroimaging in major depressive disorder: a review of psychoradiological studies

Major depressive disorder (MDD) causes great decrements in health and quality of life with increments in healthcare costs, but the causes and pathogenesis of depression remain largely unknown, which greatly prevent its early detection and effective treatment. With the advancement of neuroimaging approaches, numerous functional and structural alterations in the brain have been detected in MDD and more recently attempts have been made to apply these findings to clinical practice. In this review, we provide an updated summary of the progress in translational application of psychoradiological findings in MDD with a specified focus on potential clinical usage. The foreseeable clinical applications for different MRI modalities were introduced according to their role in disorder classification, subtyping, and prediction. While evidence of cerebral structural and functional changes associated with MDD classification and subtyping was heterogeneous and/or sparse, the ACC and hippocampus have been consistently suggested to be important biomarkers in predicting treatment selection and treatment response. These findings underlined the potential utility of brain biomarkers for clinical practice.

How developmental neuroscience can help address the problem of child poverty

Nearly 1 in 5 children in the United States lives in a household whose income is below the official federal poverty line, and more than 40% of children live in poor or near-poor households. Research on the effects of poverty on children's development has been a focus of study for many decades and is now increasing as we accumulate more evidence about the implications of poverty. The American Academy of Pediatrics recently added "Poverty and Child Health" to its Agenda for Children to recognize what has now been established as broad and enduring effects of poverty on child development. A recent addition to the field has been the application of neuroscience-based methods. Various techniques including neuroimaging, neuroendocrinology, cognitive psychophysiology, and epigenetics are beginning to document ways in which early experiences of living in poverty affect infant brain development. We discuss whether there are truly worthwhile reasons for adding neuroscience and related biological methods to study child poverty, and how might these perspectives help guide developmentally based and targeted interventions and policies for these children and their families.

Development of Neuroimaging-Based Biomarkers in Major Depression

A leading goal in the field of biological psychiatry for depression is to find a promising diagnostic biomarker and selection of specific psychiatric treatment mode that is most likely to benefit patients with depression. Recent neuroimaging studies have characterized the pathophysiology of major depressive disorder (MDD) with functional and structural alterations in the neural circuitry involved in emotion or reward processing. Particularly, structural and functional magnetic resonance imaging (MRI) studies have reported that the brain structures deeply involved in emotion regulation or reward processing including the amygdala, prefrontal cortex (PFC), anterior cingulate cortex (ACC), ventral striatum, and hippocampus are key regions that provide useful information about diagnosis and treatment outcome prediction in MDD. For example, it has been consistently reported that elevated activity of the ACC is associated with better antidepressant response in patients with MDD. This chapter will discuss a growing body of evidence that suggests that diagnosis or prediction of outcome for specific treatment can be assisted by a neuroimaging-based biomarker in MDD.

A Synthetic Literature Review on the Management of Emerging Treatment Resistance in First Episode Psychosis: Can We Move towards Precision Intervention and Individualised Care?

Treatment resistance is prevalent in early intervention in psychosis services, and causes a significant burden for the individual. A wide range of variables are shown to contribute to treatment resistance in first episode psychosis (FEP). Heterogeneity in illness course and the complex, multidimensional nature of the concept of recovery calls for an evidence base to better inform practice at an individual level. Current gold standard treatments, adopting a ‘one-size fits all’ approach, may not be addressing the needs of many individuals. This following review will provide an update and critical appraisal of current clinical practices and methodological approaches for understanding, identifying, and managing early treatment resistance in early psychosis. Potential new treatments along with new avenues for research will be discussed. Finally, we will discuss and critique the application and translation of machine learning approaches to aid progression in this area. The move towards ‘big data’ and machine learning holds some prospect for stratifying intervention-based subgroups of individuals. Moving forward, better recognition of early treatment resistance is needed, along with greater sophistication and precision in predicting outcomes, so that effective evidence-based treatments can be appropriately tailored to the individual. Understanding the antecedents and the early trajectory of one’s illness may also be key to understanding the factors that drive illness course.

Predicting response to psychiatric surgery: a systematic review of neuroimaging findings

BACKGROUND

Psychiatric surgery, including deep brain stimulation and stereotactic ablation, is an important treatment option in severe refractory psychiatric illness. Several large trials have demonstrated response rates of approximately 50%, underscoring the need to identify and select responders preoperatively. Recent advances in neuroimaging have brought this possibility into focus. We systematically reviewed the psychiatric surgery neuroimaging literature to assess the current state of evidence for preoperative imaging predictors of response.

METHODS

We performed this study in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and Meta-analysis of Observational Studies in Epidemiology (MOOSE) frameworks, and preregistered it using PROSPERO. We systematically searched the Medline, Embase and Cochrane databases for studies reporting preoperative neuroimaging analyses correlated with clinical outcomes in patients who underwent psychiatric surgery. We recorded and synthesized the methodological details, imaging results and clinical correlations from these studies.

RESULTS

After removing duplicates, the search yielded 8388 unique articles, of which 7 met the inclusion criteria. The included articles were published between 2001 and 2018 and reported on the outcomes of 101 unique patients. Of the 6 studies that reported significant findings, all identified clusters of hypermetabolism, hyperconnectivity or increased size in the frontostriatal limbic circuitry.

LIMITATIONS

The included studies were few and highly varied, spanning 2 decades.

CONCLUSION

Although few studies have analyzed preoperative imaging for predictors of response to psychiatric surgery, we found consistency among the reported results: most studies implicated overactivity in the frontostriatal limbic network as being correlated with clinical response. Larger prospective studies are needed.

REGISTRATION

www.crd.york.ac.uk/prospero/display_record.php?RecordID=131151.

Enriching CBT by Neuroscience: Novel Avenues to Achieve Personalized Treatments

Although cognitive behavioral therapy (CBT) is an established and efficient treatment for a variety of common mental disorders, a considerable number of patients do not respond to treatment or relapse after successful CBT. Recent findings and approaches from neuroscience could pave the way for clinical developments to enhance the outcome of CBT. Herein, we will present how neuroscience can offer novel perspectives to better understand (a) the biological underpinnings of CBT, (b) how we can enrich CBT with neuroscience-informed techniques (augmentation of CBT), and (c) why some patients may respond better to CBT than others (predictors of therapy outcomes), thus paving the way for more personalized and effective treatments. We will introduce some key topics and describe a selection of findings from CBT-related research using tools from neuroscience, with the hope that this will provide clinicians and clinical researchers with a brief and comprehensible overview of the field.

Metabolic activity in subcallosal cingulate predicts response to deep brain stimulation for depression

Subcallosal cingulate (SCC) deep brain stimulation (DBS) is a promising therapy for treatment-resistant depression (TRD), but response rates in open-label studies were not replicated in a large multicenter trial. Identifying biomarkers of response could improve patient selection and outcomes. We examined SCC metabolic activity as both a predictor and marker of SCC DBS treatment response. Brain glucose metabolism (CMRGlu) was measured with [18F] FDG-PET at baseline and 6 months post DBS in 20 TRD patients in a double-blind randomized controlled trial where two stimulation types (long pulse width (LPW) n = 9 and short pulse width (SPW) n = 11) were used. Responders (n = 10) were defined by a ≥48% reduction in Hamilton Depression Rating Scale scores after 6 months. The response rates were similar with five responders in each stimulation group: LPW (55.6%) and SPW (44.5%). First, differences in SCC CMRGlu in responders and non-responders were compared at baseline. Then machine learning analysis was performed with a leave-one-out cross-validation using a Gaussian naive Bayes classifier to test whether baseline CMRGlu in SCC could categorize responders. Finally, we compared 6-month change in metabolic activity with change in depression severity. All analyses were controlled for age. Baseline SCC CMRGlu was significantly higher in responders than non-responders. The machine learning analysis predicted response with 80% accuracy. Furthermore, reduction in SCC CMRGlu 6 months post DBS correlated with symptom improvement (r(17) = 0.509; p = 0.031). This is the first evidence of an image-based treatment selection biomarker that predicts SCC DBS response. Future studies could utilize SCC metabolic activity for prospective patient selection.

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

•

Examined whether SSRIs normalize amygdala activity or dampen responsiveness.

•

Responders and non-responders did not differ in amygdala activity prior to treatment.

•

SSRI responders had increased amygdala activation to positive stimuli after treatment.

•

SSRI responders also had decreased amygdala activation to negative stimuli after treatment.

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.

Translating research findings into clinical practice: a systematic and critical review of neuroimaging-based clinical tools for brain disorders

A pivotal aim of psychiatric and neurological research is to promote the translation of the findings into clinical practice to improve diagnostic and prognostic assessment of individual patients. Structural neuroimaging holds much promise, with neuroanatomical measures accounting for up to 40% of the variance in clinical outcome. Building on these findings, a number of imaging-based clinical tools have been developed to make diagnostic and prognostic inferences about individual patients from their structural Magnetic Resonance Imaging scans. This systematic review describes and compares the technical characteristics of the available tools, with the aim to assess their translational potential into real-world clinical settings. The results reveal that a total of eight tools. All of these were specifically developed for neurological disorders, and as such are not suitable for application to psychiatric disorders. Furthermore, most of the tools were trained and validated in a single dataset, which can result in poor generalizability, or using a small number of individuals, which can cause overoptimistic results. In addition, all of the tools rely on two strategies to detect brain abnormalities in single individuals, one based on univariate comparison, and the other based on multivariate machine-learning algorithms. We discuss current barriers to the adoption of these tools in clinical practice and propose a checklist of pivotal characteristics that should be included in an "ideal" neuroimaging-based clinical tool for brain disorders.

Depression-related anterior cingulate prefrontal resting state connectivity normalizes following cognitive behavioral therapy

Background.

Aberrant activity of the subcallosal cingulate (SCC) is a common theme across pharmacologic treatment efficacy prediction studies. The functioning of the SCC in psychotherapeutic interventions is relatively understudied, as are functional differences among SCC subdivisions. We conducted functional connectivity analyses (rsFC) on resting-state functional magnetic resonance imaging (fMRI) data, collected before and after a course of cognitive behavioral therapy (CBT) in patients with major depressive disorder (MDD), using seeds from three SCC subdivisions.

Methods.

Resting-state data were collected from unmedicated patients with current MDD (Hamilton Depression Rating Scale-17 > 16) before and after 14-sessions of CBT monotherapy. Treatment outcome was assessed using the Beck Depression Inventory (BDI). Rostral anterior cingulate (rACC), anterior subcallosal cingulate (aSCC), and Brodmann’s area 25 (BA25) masks were used as seeds in connectivity analyses that assessed baseline rsFC and symptom severity, changes in connectivity related to symptom improvement after CBT, and prediction of treatment outcomes using whole-brain baseline connectivity.

Results.

Pretreatment BDI negatively correlated with pretreatment rACC ~ dorsolateral prefrontal cortex and aSCC ~ lateral prefrontal cortex rsFC. In a region-of-interest longitudinal analysis, rsFC between these regions increased post-treatment (p < 0.05_FDR). In whole-brain analyses, BA25 ~ paracentral lobule and rACC ~ paracentral lobule connectivities decreased post-treatment. Whole-brain baseline rsFC with SCC did not predict clinical improvement.

Conclusions.

rsFC features of rACC and aSCC, but not BA25, correlated inversely with baseline depression severity, and increased following CBT. Subdivisions of SCC involved in top-down emotion regulation may be more involved in cognitive interventions, while BA25 may be more informative for interventions targeting bottom-up processing. Results emphasize the importance of subdividing the SCC in connectivity analyses.

Predicting individual clinical trajectories of depression with generative embedding

•

Patients with major depressive disorder (MDD) show variable clinical trajectories.

•

Generative embedding (GE) is used to predict clinical trajectories in MDD patients.

•

GE classifies patients with chronic depression vs. fast remission with 79% accuracy.

•

GE provides mechanistic interpretability and outperforms conventional measures.

•

Proof-of-concept that illustrates the potential of GE for clinical prediction.

Patients with major depressive disorder (MDD) show heterogeneous treatment response and highly variable clinical trajectories: while some patients experience swift recovery, others show relapsing-remitting or chronic courses. Predicting individual clinical trajectories at an early stage is a key challenge for psychiatry and might facilitate individually tailored interventions. So far, however, reliable predictors at the single-patient level are absent. Here, we evaluated the utility of a machine learning strategy – generative embedding (GE) – which combines interpretable generative models with discriminative classifiers. Specifically, we used functional magnetic resonance imaging (fMRI) data of emotional face perception in 85 MDD patients from the NEtherlands Study of Depression and Anxiety (NESDA) who had been followed up over two years and classified into three subgroups with distinct clinical trajectories. Combining a generative model of effective (directed) connectivity with support vector machines (SVMs), we could predict whether a given patient would experience chronic depression vs. fast remission with a balanced accuracy of 79%. Gradual improvement vs. fast remission could still be predicted above-chance, but less convincingly, with a balanced accuracy of 61%. Generative embedding outperformed classification based on conventional (descriptive) features, such as functional connectivity or local activation estimates, which were obtained from the same data and did not allow for above-chance classification accuracy. Furthermore, predictive performance of GE could be assigned to a specific network property: the trial-by-trial modulation of connections by emotional content. Given the limited sample size of our study, the present results are preliminary but may serve as proof-of-concept, illustrating the potential of GE for obtaining clinical predictions that are interpretable in terms of network mechanisms. Our findings suggest that abnormal dynamic changes of connections involved in emotional face processing might be associated with higher risk of developing a less favorable clinical course.

Attentional bias modification is associated with fMRI response toward negative stimuli in individuals with residual depression: a randomized controlled trial

BACKGROUND

Attentional bias modification (ABM) may lead to more adaptive emotion perception and emotion regulation. Understanding the neural basis of these effects may lead to greater precision for the development of future treatments. Task-related functional MRI (fMRI) after ABM training has not been investigated in depression so far. The main aim of this randomized controlled trial was to explore differences in brain activity after ABM training, in response to emotional stimuli.

METHODS

A total of 134 people with previous depression, who had been treated for depression and had various degrees of residual symptoms, were randomized to 14 days of active ABM or a closely matched placebo training, followed by an fMRI emotion regulation task. The training procedure was a classical dot–probe task with emotional face stimuli. In the active ABM condition, the probes replaced the more positively valenced face of a given pair. As participants implicitly learned to predict the probe location, this would be likely to induce a more positive attentional bias. The placebo condition was identical, except for the contingency of the probe, which appeared equally behind positive and negative stimuli. We compared depression symptoms and subjective ratings of perceived negativity during fMRI between the training groups. We explored brain activation in predefined regions of interest and across the whole brain. We explored activation in areas associated with changes in attentional bias and degree of depression.

RESULTS

Compared with the placebo group, the ABM group showed reduced activation in the amygdala and the anterior cingulate cortex when passively viewing negative images. We found no group differences in predefined regions of interest associated with emotion regulation strategies. Response in the temporal cortices was associated with the degree of change in attentional bias and the degree of depressive symptoms in ABM versus placebo.

LIMITATIONS

These findings should be replicated in other samples of patients with depression, and in studies using fMRI designs that allow analyses of within-group variability from baseline to follow-up.

CONCLUSION

Attentional bias modification training has an effect on brain function in the circuitry associated with emotional appraisal and the generation of affective states.

CLINICALTRIALS.GOV IDENTIFIER

NCT02931487

Long versus short pulse width subcallosal cingulate stimulation for treatment-resistant depression: a randomised, double-blind, crossover trial

BACKGROUND

Stimulation adjustment is required to optimise outcomes of deep brain stimulation (DBS) for treatment-resistant depression, but controlled data for ideal stimulation parameters are poor or insufficient. We aimed to establish the efficacy and safety of short pulse width (SPW) and long pulse width (LPW) subcallosal cingulate DBS in depression.

METHODS

We did a double-blind, randomised, crossover trial in an academic hospital in Calgary, AB, Canada. Patients had DSM IV-defined major depressive disorder and bipolar depression (20-70 years old, both sexes) and did not respond to treatment for more than 1 year, with a score of 20 or more on the 17-item Hamilton Depression Rating Scale (HDRS) at recruitment. Patients underwent bilateral DBS implantation into the subcallosal cingulate white matter using diffusion tensor imaging tractography. Patients were randomly assigned 1:1 without stratification using a computerised list generator to receive either SPW (90 μs) or LPW (210-450 μs) stimulation for 6 months. Patients and the clinician assessing outcomes were masked to the stimulation group. Keeping frequency constant (130 Hz), either pulse width or voltage was increased monthly, based on response using the HDRS. Patients who did not respond to treatment (<50% reduction in HDRS from baseline) at 6 months crossed over to the opposite stimulation for another 6 months. All patients received individualised cognitive behavioural therapy (CBT) for 12 weeks. The primary outcome was change in HDRS at 6 months and 12 months using intention-to-treat analysis. This study is registered with ClinicalTrials.gov, NCT01983904.

FINDINGS

Between Dec 5, 2013, and Sept 30, 2016, of 225 patients screened for eligibility, 23 patients were selected for DBS surgery. After one patient withdrew, 22 (mean age 46·4 years, SEM 3·1; 10 [45%] female, 12 [55%] male) were randomly assigned, ten (45%) to LPW stimulation and 12 (55%) to SPW stimulation. Patients were followed up at 6 months and 12 months. There was a significant reduction in HDRS scores (p<0·0001) with no difference between SPW and LPW groups (p=0·54) in the randomisation phase at 6 months. Crossover groups did not show a significant decrease in HDRS within groups (p=0·15) and between groups (p=0·21) from 6-12 months. Adverse events were equal between groups. Worsening anxiety and depression were the most common psychological adverse events. One patient in the SPW group died by suicide.

INTERPRETATION

Both LPW and SPW stimulation of subcallosal cingulate white matter tracts carried similar risks and were equally effective in reducing depressive symptoms, suggesting a role for both pulse width and amplitude titration in optimising clinical outcomes in patients with treatment-resistant depression.

FUNDING

Alberta Innovates Health Solutions.

Brain structural effects of treatments for depression and biomarkers of response: a systematic review of neuroimaging studies

Antidepressive pharmacotherapy (AD), electroconvulsive therapy (ECT) and cognitive behavioural therapy (CBT) are effective treatments for major depressive disorder. With our review, we aim to provide a systematic overview of neuroimaging studies that investigate the effects of AD, ECT and CBT on brain grey matter volume (GMV) and biomarkers associated with response. After a systematic database research on PubMed, we included 50 studies using magnetic resonance imaging and investigating (1) changes in GMV, (2) pre-treatment GMV biomarkers associated with response, or (3) the accuracy of predictions of response to AD, ECT or CBT based on baseline GMV data. The strongest evidence for brain structural changes was found for ECT, showing volume increases within the temporal lobe and subcortical structures - such as the hippocampus-amygdala complex, anterior cingulate cortex (ACC) and striatum. For AD, the evidence is heterogeneous as only 4 of 11 studies reported significant changes in GMV. The results are not sufficient in order to draw conclusions about the structural brain effects of CBT. The findings show consistently that higher pre-treatment ACC volume is associated with response to AD, ECT and CBT. An association of higher pre-treatment hippocampal volume and response has only been reported for AD. Machine learning approaches based on pre-treatment whole brain patterns reach accuracies of 64-90% for predictions of AD or ECT response on the individual patient level. The findings underline the potential of brain biomarkers for the implementation in clinical practice as an additive feature within the process of treatment selection.

From bed to bench side: Reverse translation to optimize neuromodulation for mood disorders

The advent of neuroimaging has provided foundational insights into the neural basis of psychiatric conditions, such as major depression. Across countless studies, dysfunction has been localized to distinct parts of the limbic system. Specific knowledge about affected locations has led to the development of circuit modulation therapies to correct dysfunction, notably deep brain stimulation (DBS). This and other emerging neuromodulation approaches have shown great promise, but their refinement has been slow and fundamental questions about their mechanisms of action remain. Here, we argue that their continued development requires reverse translation to animal models with close homology to humans, namely, nonhuman primates. With a particular focus on DBS approaches for depression, we highlight the parts of the brain that have been targeted by neuromodulation in humans, their efficacy, and why nonhuman primates are the most suitable model in which to conduct their refinement. We finish by highlighting key gaps in our knowledge that need to be filled to allow more rapid progress toward effective therapies in patients for whom all other treatment attempts have failed.

Functional connectivity of the anterior cingulate cortex predicts treatment outcome for rTMS in treatment-resistant depression at 3-month follow-up

BACKGROUND AND OBJECTIVE

Repetitive transcranial magnetic stimulation (rTMS) is a first-line treatment for treatment-resistant depression (TRD). The mechanisms of action of rTMS are not fully understood, and no biomarkers are available to assist in clinical practice to predict response to rTMS. This study aimed to demonstrate that after-rTMS clinical improvement is associated with functional connectivity (FC) changes of the subgenual cingulate cortex (sgACC) and rostral anterior cingulate (rACC), and FC of sgACC and rACC might serve as potential predictors for treatment response.

METHODS

Resting-state functional magnetic resonance imaging (rs-fMRI) data were collected within 1 week before rTMS initiation in 50 TRD patients to predict subsequent response to rTMS on the left dorsolateral prefrontal cortex (DLPFC). Follow-up rs-fMRI was obtained 12 weeks after completion of rTMS and neural correlates of rTMS in sgACC- and rACC-related FC patterns were compared to before rTMS data and with rs-fMRI from healthy participants.

RESULTS

Treatment response was associated with lower FC of sgACC to right DLPFC and higher FC of rACC to left lateral parietal cortex (IPL) measured at baseline. Using sgACC-DLPFC and rACC-IPL connectivity as features, responder-nonresponder classification accuracies of 84% and 76% (end-of-treatment), 88% and 81% (3-month follow-up), respectively were achieved. Longitudinal rs-fMRI data analyses revealed that the hyperconnectivity between sgACC and visual cortex was normalized to a level which was comparable to that of healthy participants.

CONCLUSIONS

Brain activity patterns in depression are predictive of treatment response to rTMS, and longitudinal change of brain activity in relevant brain circuits after rTMS is associated with treatment response in depression. Target engagement paradigms may offer opportunities to increase the efficacy of rTMS in TRD by optimal selection of patients for treatment.

TRIAL REGISTRATION

ClinicalTrials.gov Identifiers: NCT01887782 and NCT02800226.

Association of rs7688285 allelic variation coding for GLRB with fear reactivity and exposure-based therapy in patients with panic disorder and agoraphobia

The gene coding for glycine receptor β subunits (GLRB) has been found to be related to panic disorder and agoraphobia (PD/AG) and to be associated with altered insular BOLD activation during fear conditioning, as an intermediate phenotype of defensive system reactivity in healthy subjects. In a multicenter clinical trial on PD/AG patients we investigated in three sub-samples whether GLRB allelic variation (A/G; A-allele identified as «risk») in the single nucleotide polymorphism rs7688285 was associated with autonomic (behavioral avoidance test BAT; n = 267 patients) and neural (differential fear conditioning; n = 49 patients, n = 38 controls) measures, and furthermore with responding towards exposure-based cognitive behavioral therapy (CBT, n = 184 patients). An interaction of genotype with current PD/AG diagnosis (PD/AG vs. controls; fMRI data only) and their modification after CBT was tested as well. Exploratory fMRI results prior to CBT, revealed A-allele carriers irrespective of diagnostic status to show overall higher BOLD activation in the hippocampus, motor cortex (MC) and insula. Differential activation in the MC, anterior cingulate cortex (ACC) and insula was found in the interaction genotype X diagnosis. Differential activation in ACC and hippocampus was present in differential fear learning. ACC activation was modified after treatment, while no overall rs7688285 dependent effect on clinical outcomes was found. On the behavioral level, A-allele carriers showed pronounced fear reactivity prior to CBT which partially normalized afterwards. In sum, rs7688285 variation interacts in a complex manner with PD/AG on a functional systems level and might be involved in the development of PD/AG but not in their treatment.

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.

Multidimensional imaging techniques for prediction of treatment response in major depressive disorder

A large number of studies have attempted to use neuroimaging tools to aid in treatment prediction models for major depressive disorder (MDD). Most such studies have reported on only one dimension of function and prediction at a time. In this study, we used three different tasks across domains of function (emotion processing, reward anticipation, and cognitive control, plus resting state connectivity completed prior to start of medication to predict treatment response in 13-36 adults with MDD. For each experiment, adults with MDD were prescribed only label duloxetine (all experiments), whereas another subset were prescribed escitalopram. We used a KeyNet (both Task derived masks and Key intrinsic Network derived masks) approach to targeting brain systems in a specific match to tasks. The most robust predictors were (Dichter et al., 2010) positive response to anger and (Gong et al., 2011) negative response to fear within relevant anger and fear TaskNets and Salience and Emotion KeyNet (Langenecker et al., 2018) cognitive control (correct rejections) within Inhibition TaskNet (negative) and Cognitive Control KeyNet (positive). Resting state analyses were most robust for Cognitive control Network (positive) and Salience and Emotion Network (negative). Results differed by whether an -fwhm or -acf (more conservative) adjustment for multiple comparisons was used. Together, these results implicate the importance of future studies with larger sample sizes, multidimensional predictive models, and the importance of using empirically derived masks for search areas.