Anterior cingulate activity as a predictor of degree of treatment response in major depression: evidence from brain electrical tomography analysis

Cingulate microstimulation induces negative decision-making via reduced top-down influence on primate fronto-cingulo-striatal network

The dorsolateral prefrontal cortex (dlPFC) is crucial for regulation of emotion that is known to aid prevention of depression. The broader fronto-cingulo-striatal (FCS) network, including cognitive dlPFC and limbic cingulo-striatal regions, has been associated with a negative evaluation bias often seen in depression. The mechanism by which dlPFC regulates the limbic system remains largely unclear. Here we have successfully induced a negative bias in decision-making in female primates performing a conflict decision-making task, by directly microstimulating the subgenual cingulate cortex while simultaneously recording FCS local field potentials (LFPs). The artificially induced negative bias in decision-making was associated with a significant decrease in functional connectivity from cognitive to limbic FCS regions, represented by a reduction in Granger causality in beta-range LFPs from the dlPFC to the other regions. The loss of top-down directional influence from cognitive to limbic regions, we suggest, could underlie negative biases in decision-making as observed in depressive states.

Are big five personality traits associated to suicidal behaviour in adolescents? A systematic review and meta-analysis

BACKGROUND

Suicidal behaviour is one of the main causes of death worldwide, especially among teenagers, and its development is potentially associated with the development of personality. The aim of this systematic review and meta-analysis is to describe the association between the Big Five Personality Traits and suicidal behaviour in adolescents.

METHODS

Seven databases were systematically searched between June 2022 and July 2022 with no language or year restrictions. We searched for a combination of the following search items (suicid* OR suicidal behaviour OR suicidal ideation OR suicide attempts OR self injury OR self-destructive behaviour OR self-harm OR suicidal risk) AND (personality OR personality traits OR temperament OR neuroticism OR extraversion OR agreeableness OR openness to experience OR conscientiousness) AND (adolescents OR youth OR teenagers OR young adults). Meta-analysis procedures were performed using the R software. A random-effect-model was performed for the models through the incorporation of τ2, based on the DerSimonion Lard method.

RESULTS

Seven studies met all inclusion criteria and were included in this systematic review. Our meta-analysis showed that higher neuroticism are both associated and a risk factor for suicidal behaviour. Higher levels of openness to experience and agreeableness, and lower levels of extraversion and conscientiousness, were linked to suicidal behaviour, especially self-harm.

LIMITATIONS

Due to the heterogeneity of the studies, we were only able to perform meta-analysis regarding neuroticism.

CONCLUSION

The present study may help professionals to identify adolescents in higher risk for suicidal behaviour, enabling the development of early interventions to prevent suicidality in this population.

A stress-sensitive frontostriatal circuit supporting effortful reward-seeking behavior

Effort valuation-a process for selecting actions based on the anticipated value of rewarding outcomes and expectations about the work required to obtain them-plays a fundamental role in decision-making. Effort valuation is disrupted in chronic stress states and is supported by the anterior cingulate cortex (ACC), but the circuit-level mechanisms by which the ACC regulates effort-based decision-making are unclear. Here, we show that ACC neurons projecting to the nucleus accumbens (ACC-NAc) play a critical role in effort valuation behavior in mice. Activity in ACC-NAc cells integrates both reward- and effort-related information, encoding a reward-related signal that scales with effort requirements and is necessary for supporting future effortful decisions. Chronic corticosterone exposure reduces motivation, suppresses effortful reward-seeking, and disrupts ACC-NAc signals. Together, our results delineate a stress-sensitive ACC-NAc circuit that supports effortful reward-seeking behavior by integrating reward and effort signals and reinforcing effort allocation in the service of maximizing reward.

Major depressive disorder associated alterations in the effective connectivity of the face processing network: a systematic review

Major depressive disorder (MDD) is marked by altered processing of emotional stimuli, including facial expressions. Recent neuroimaging research has attempted to investigate how these stimuli alter the directional interactions between brain regions in those with MDD; however, methodological heterogeneity has made identifying consistent effects difficult. To address this, we systematically examined studies investigating MDD-associated differences present in effective connectivity during the processing of emotional facial expressions. We searched five databases: PsycINFO, EMBASE, PubMed, Scopus, and Web of Science, using a preregistered protocol (registration number: CRD42021271586). Of the 510 unique studies screened, 17 met our inclusion criteria. These studies identified that compared with healthy controls, participants with MDD demonstrated (1) reduced connectivity from the dorsolateral prefrontal cortex to the amygdala during the processing of negatively valenced expressions, and (2) increased inhibitory connectivity from the ventromedial prefrontal cortex to amygdala during the processing of happy facial expressions. Most studies investigating the amygdala and anterior cingulate cortex noted differences in their connectivity; however, the precise nature of these differences was inconsistent between studies. As such, commonalities observed across neuroimaging modalities warrant careful investigation to determine the specificity of these effects to particular subregions and emotional expressions. Future research examining longitudinal connectivity changes associated with treatment response may provide important insights into mechanisms underpinning therapeutic interventions, thus enabling more targeted treatment strategies.

Deciphering the neural mechanisms of miR-134 in major depressive disorder with population-based and person-specific imaging transcriptomic techniques

MiR-134 has emerged as a potential molecular biomarker for the detection and management of major depressive disorder (MDD). Nevertheless, the specific effects of miR-134 as a regulatory element on brain function and its implications for the clinical presentation of MDD are not yet fully understood. In order to investigate the potential neural mechanisms that contribute to the relationship between miR-134 and MDD, we employed a parallel two-stage cross-scale multi-omics approach. This involved utilizing the anterior cingulate cortex (ACC) functional connectivity as a means to connect microscopic molecular structures with macroscopic brain function in two separate cohorts: the MDD-I dataset (56 MDD patients and 51 healthy controls) and the MDD-II dataset (57 MDD patients and 52 healthy controls). We found a stable ACC functional dysconnectivity pattern of MDD and established the hierarchical cross-scale association from molecular organizations of miR-134 target genes to macroscopic brain functional dysconnectivity and associated behavior, as revealed by population-based analysis. Additionally, our person-specific imaging transcriptomic study revealed that individual exosomal miR-134 expression levels impact on individual clinical symptoms of MDD by modulating ACC-related functional dysconnectivity. Together, our findings provide compelling evidence of the correlation between miR-134 and depression across multi scales within the gene-brain-behavior context.

Rostral Anterior Cingulate Cortex Oscillatory Power Indexes Treatment-Resistance to Multiple Therapies in Major Depressive Disorder

INTRODUCTION

High rostral anterior cingulate cortex (rACC) activity is proposed as a nonspecific prognostic marker for treatment response in major depressive disorder, independent of treatment modality. However, other studies report a negative association between baseline high rACC activation and treatment response. Interestingly, these contradictory findings were also found when focusing on oscillatory markers, specifically rACC-theta power. An explanation could be that rACC-theta activity dynamically changes according to number of previous treatment attempts and thus is mediated by level of treatment-resistance.

METHODS

Primarily, we analyzed differences in rACC- and frontal-theta activity in large national cross-sectional samples representing various levels of treatment-resistance and resistance to multimodal treatments in depressed patients (psychotherapy [n = 175], antidepressant medication [AD; n = 106], repetitive transcranial magnetic stimulation [rTMS; n = 196], and electroconvulsive therapy [ECT; n = 41]), and the respective difference between remitters and non-remitters. For exploratory purposes, we also investigated other frequency bands (delta, alpha, beta, gamma).

RESULTS

rACC-theta activity was higher (p < 0.001) in the more resistant rTMS and ECT patients relative to the less resistant psychotherapy and AD patients (psychotherapy-rTMS: d = 0.315; AD-rTMS: d = 0.320; psychotherapy-ECT: d = 1.031; AD-ECT: d = 1.034), with no difference between psychotherapy and AD patients. This association was even more pronounced after controlling for frontal-theta. Post hoc analyses also yielded effects for delta, beta, and gamma bands.

CONCLUSION

Our findings suggest that by factoring in degree of treatment-resistance during interpretation of the rACC-theta biomarker, its usefulness in treatment selection and prognosis could potentially be improved substantially in future real-world practice. Future research should however also investigate specificity of the theta band.

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.

Resting-state EEG delta and alpha power predict response to cognitive behavioral therapy in depression: a Canadian biomarker integration network for depression study

Cognitive behavioral therapy (CBT) is often recommended as a first-line treatment in depression. However, access to CBT remains limited, and up to 50% of patients do not benefit from this therapy. Identifying biomarkers that can predict which patients will respond to CBT may assist in designing optimal treatment allocation strategies. In a Canadian Biomarker Integration Network for Depression (CAN-BIND) study, forty-one adults with depression were recruited to undergo a 16-week course of CBT with thirty having resting-state electroencephalography (EEG) recorded at baseline and week 2 of therapy. Successful clinical response to CBT was defined as a 50% or greater reduction in Montgomery-Åsberg Depression Rating Scale (MADRS) score from baseline to post-treatment completion. EEG relative power spectral measures were analyzed at baseline, week 2, and as early changes from baseline to week 2. At baseline, lower relative delta (0.5-4 Hz) power was observed in responders. This difference was predictive of successful clinical response to CBT. Furthermore, responders exhibited an early increase in relative delta power and a decrease in relative alpha (8-12 Hz) power compared to non-responders. These changes were also found to be good predictors of response to the therapy. These findings showed the potential utility of resting-state EEG in predicting CBT outcomes. They also further reinforce the promise of an EEG-based clinical decision-making tool to support treatment decisions for each patient.

Effects of Neurofeedback on Cognitive Function, Productive Activity, and Quality of Life in Patients With Traumatic Brain Injury: A Randomized Controlled Trial

BACKGROUND

Cognitive impairment is common in patients with traumatic brain injury (TBI). Studies that have examined the effectiveness of neurofeedback (NFB) on cognitive function following TBI have had poor study designs and small sample sizes.

OBJECTIVES

This randomized controlled trial assessed the effects of low-resolution tomography Z-score NFB (LZNFB) and theta/beta NFB on cognitive impairment, return to productive activity, and quality of life in patients with TBI.

METHODS

We randomly assigned 87 patients with TBI with cognitive impairment to LZNFB, theta/beta NFB, or usual care (UC) groups. Patients in both NFB groups received weekly 60-minute treatment for 10 weeks, and those in the control group received UC and telephone interviews for 10 weeks. The primary outcome was cognitive function as measured by performance on cognitive tasks; the secondary outcomes included productive activity and quality of life based on the Community Integration Questionnaire-revised (CIQ-R) and the Quality of Life after Brain Injury (QOLIBRI), respectively, at baseline and immediately after the last intervention.

RESULTS

The LZNFB group exhibited significantly greater improvements in immediate recall, delayed recall, recognition memory, and selective attention compared with the UC group; the theta/beta NFB group exhibited improvements in only immediate memory and selective attention (P < .05). The total CIQ-R scores of the LZNFB group after treatment were significantly improved than those of the UC group were.

CONCLUSION

Consecutive LZNFB achieved therapeutic effects in memory, attention, and productive activity, whereas theta/beta NFB improved memory and attention in patients with TBI.This trial was prospectively registered at ClinicalTrial.gov (registration number: NCT03515317; https://clinicaltrials.gov/ct2/show/NCT03515317).

Guidelines for successful motor cortex ultrasonic neurostimulation in mice

BACKGROUND

Ultrasound neurostimulation (USNS) is a non-invasive neuromodulation technique that might hold promise for treating neuropsychiatric disorders with regards to its noninvasiveness, penetration depth, and high resolution.

OBJECTIVE

We sought in this experimental study to provide detailed and optimized protocol and methodology for a successful ultrasonic neurostimulation of the Primary Motor Cortex (M1) in mice addressed to young researchers/students beginning their research in the field of ultrasonic neurostimulation and encountering practical challenges.

METHODS

A 500 kHz single-element transducer was used for stimulating the primary motor cortex at different acoustic pressures in C57BL/6 mice at various anesthesia levels. To further illustrate the effect of anesthesia, real time visual observations of motor responses validated with video recordings as well as electromyography were employed for evaluating the success and reliability of the stimulations.

RESULTS

Detailed experimental procedure for a successful stimulations including targeting and anesthesia is presented. Our study demonstrates that we can achieve high stimulation success rates (91 % to 100 %) at acoustic pressures ranging from 330 kPa to 550 kPa at anesthesia washout period.

CONCLUSIONS

This study shows a reliable and detailed methodology for successful USNS in mice addressed to beginners in ultrasonic brain stimulation topic. We showed an effective USNS protocol. We offered a simple and consistent non-invasive technique for locating and targeting brain zones. Moreover, we illustrated the acoustic pressure and stimulation success relationship and focused on the effect of anesthesia level for successful stimulation.

The Aversive Lens: Stress effects on the prefrontal-cingulate cortical pathways that regulate emotion

ARNSTEN, A.F.T., M.K.P. Joyce and A.C. Roberts. The Aversive Lens: Stress effects on the prefrontal-cingulate cortical pathways that regulate emotion. NEUROSCI BIOBEHAV REV XXX-XXX, 2022. The symptoms of major-depressive-disorder include psychic pain and anhedonia, i.e. seeing the world through an "aversive lens". The neurobiology underlying this shift in worldview is emerging. Here these data are reviewed, focusing on how activation of subgenual cingulate (BA25) induces an "aversive lens", and how higher prefrontal cortical (PFC) areas (BA46/10/32) provide top-down regulation of BA25 but are weakened by excessive dopamine and norepinephrine release during stress exposure, and dendritic spine loss with chronic stress exposure. These changes may generate an attractor state, which maintains the brain under the control of BA25, requiring medication or neuromodulatory treatments to return connectivity to a more flexible state. In line with this hypothesis, effective anti-depressant treatments reduce the activity of BA25 and restore top-down regulation by higher circuits, e.g. as seen with SSRI medications, ketamine, deep brain stimulation of BA25, or rTMS to strengthen dorsolateral PFC. This research has special relevance in an era of chronic stress caused by the COVID19 pandemic, political unrest and threat of climate change.

The Location Reliability of the Resting-State fMRI FC of Emotional Regions Towards rTMS Therapy

Resting-state magnetic resonance imaging (RS-fMRI) studies indicated that the repetitive transcranial magnetic stimulation (rTMS) exerts antidepression effect through the functional connectivity (FC) of the DLPFC with the subgenual anterior cingulate cortex (sgACC), pregneual ACC (pgACC), or nucleus accumbens (NAc). It is proposed that the FC-guided individualized precise stimulation on the DLPFC would be more effective. The current study systematically investigated the reliability of the RS-fMRI FC location as well as the FC strength with multiple potential factors. We aimed to provide a stable stimulation target for future FC-guided TMS therapy for affective related disorders. Twenty-one subjects under RS-fMRI conditions with the first two times (V1, V2) scanned on a GE 3 T scanner and the third visit (V3) on a Siemens 3 T scanner. Then the FC strength and location reliability were assessed by using intra-class correlation (ICC) and intra-individual distance, respectively. The factors included deep seed ROIs (midline (mid-) sgACC, left pgACC, mid-pgACC, and left NAc), eyes closed (EC) vs eyes open (EO), frequency bands, FC algorithm (Pearson vs Spearman), scanning length (half a session vs whole session), and location method (FC peak vs center of gravity (COG)). The reliability of the voxel-wise FC strength was low to moderate. The intra-individual distances of the COG were 3.8-7.3 mm across all factors, much smaller than that of FC peak (approximately 30 mm). The COG of seed-based FC might be a potential rTMS stimulation target. Anyway, all potential stimulation targets should be tested in future rTMS treatment studies.

Resting and TMS-EEG markers of treatment response in major depressive disorder: A systematic review

Electroencephalography (EEG) is a non-invasive method to identify markers of treatment response in major depressive disorder (MDD). In this review, existing literature was assessed to determine how EEG markers change with different modalities of MDD treatments, and to synthesize the breadth of EEG markers used in conjunction with MDD treatments. PubMed and EMBASE were searched from 2000 to 2021 for studies reporting resting EEG (rEEG) and transcranial magnetic stimulation combined with EEG (TMS-EEG) measures in patients undergoing MDD treatments. The search yielded 966 articles, 204 underwent full-text screening, and 51 studies were included for a narrative synthesis of findings along with confidence in the evidence. In rEEG studies, non-linear quantitative algorithms such as theta cordance and theta current density show higher predictive value than traditional linear metrics. Although less abundant, TMS-EEG measures show promise for predictive markers of brain stimulation treatment response. Future focus on TMS-EEG measures may prove fruitful, given its ability to target cortical regions of interest related to MDD.

Rostral anterior cingulate network effective connectivity in depressed adolescents and associations with treatment response in a randomized controlled trial

The rostral anterior cingulate cortex (rACC) is consistently implicated in the neurobiology of depression. While the functional connectivity of the rACC has been previously associated with treatment response, there is a paucity of work investigating the specific directional interactions underpinning these associations. We compared the fMRI resting-state effective connectivity of 94 young people with major depressive disorder and 91 healthy controls. Following the fMRI scan, patients were randomized to receive cognitive behavioral therapy for 12 weeks, plus either fluoxetine or a placebo. Using spectral dynamic causal modelling, we examined the effective connectivity of the rACC with eight other regions implicated in depression: the left and right anterior insular cortex (AIC), amygdalae, and dorsolateral prefrontal cortex (dlPFC); and in the midline, the subgenual (sgACC) and dorsal anterior cingulate cortex (dACC). Parametric empirical Bayes was used to compare baseline differences between controls and patients and responders and non-responders to treatment. Depressed patients demonstrated greater inhibitory connectivity from the rACC to the dlPFC, AIC, dACC and left amygdala. Moreover, treatment responders illustrated greater inhibitory connectivity from the rACC to dACC, greater excitatory connectivity from the dACC to sgACC and reduced inhibitory connectivity from the sgACC to amygdalae at baseline. The inhibitory hyperconnectivity of the rACC in depressed patients aligns with hypotheses concerning the dominance of the default mode network over other intrinsic brain networks. Surprisingly, treatment responders did not demonstrate connectivity which was more similar to healthy controls, but rather distinct alterations that may have predicated their enhanced treatment response.

Electrophysiological correlates and predictors of the antidepressant response to repeated ketamine infusions in treatment-resistant depression

BACKGROUND

Sub-anesthetic ketamine doses rapidly reduce depressive symptoms, although additional investigations of the underlying neural mechanisms and the prediction of response outcomes are needed. Electroencephalographic (EEG)-derived measures have shown promise in predicting antidepressant response to a variety of treatments, and are sensitive to ketamine administration. This study examined their utility in characterizing changes in depressive symptoms following single and repeated ketamine infusions.

METHODS

Recordings were obtained from patients with treatment-resistant major depressive disorder (MDD) (N = 24) enrolled in a multi-phase clinical ketamine trial. During the randomized, double-blind, crossover phase (Phase 1), patients received intravenous ketamine (0.5 mg/kg) and midazolam (30 μg/kg), at least 1 week apart. For each medication, three resting, eyes-closed recordings were obtained per session (pre-infusion, immediately post-infusion, 2 h post-infusion), and changes in power (delta, theta1/2/total, alpha1/2/total, beta, gamma), alpha asymmetry, theta cordance, and theta source-localized anterior cingulate cortex activity were quantified. The relationships between ketamine-induced changes with early (Phase 1) and sustained (Phases 2,3: open-label repeated infusions) decreases in depressive symptoms (Montgomery-Åsberg Depression Rating Score, MADRS) and suicidal ideation (MADRS item 10) were examined.

RESULTS

Both medications decreased alpha and theta immediately post-infusion, however, only midazolam increased delta (post-infusion), and only ketamine increased gamma (immediately post- and 2 h post-infusion). Regional- and frequency-specific ketamine-induced EEG changes were related to and predictive of decreases in depressive symptoms (theta, gamma) and suicidal ideation (alpha). Early and sustained treatment responders differed at baseline in surface-level and source-localized theta.

CONCLUSIONS

Ketamine exerts frequency-specific changes on EEG-derived measures, which are related to depressive symptom decreases in treatment-resistant MDD and provide information regarding early and sustained individual response to ketamine.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov: Action of Ketamine in Treatment-Resistant Depression, NCT01945047.

White matter markers and predictors for subject-specific rTMS response in major depressive disorder

Repetitive transcranial magnetic stimulation (rTMS) has established therapeutic efficacy for major depressive disorder (MDD). While translational research has focused primarily on understanding the mechanism of action of TMS on functional activation and connectivity, the effects on structural connectivity remain largely unknown especially when rTMS is applied using subject-specific brain targets. This study aims to use novel diffusion magnetic resonance imaging (dMRI) analysis to examine microstructural changes related to rTMS treatment response using a unique cohort of 21 patients with MDD treated using rTMS with subject-specific targets. White matter dMRI microstructural measures and clinical scores were captured before and after the full course of treatment. We defined disease-relevant fiber bundles connected to different subregions of the left prefrontal cortex and analyzed changes in diffusion properties as well as correlations between the changes of dMRI measures and the changes in Hamilton Depression Rating Scale (HAMD). No significant changes were observed in tracts connected to the TMS targets. rTMS significantly increased the extra-axonal free-water volume, fractional anisotropy and decreased the radial diffusivity in anterior-medial prefrontal fiber bundles but did not lead to raw changes in lateral prefrontal tracts. That said, the microstructural changes in the lateral prefrontal white matter were significantly correlated with treatment response. Moreover, pre-rTMS dMRI measures of the dorsal anterior cingulate cortex and lateral prefrontal cortex connections are correlated with changes in HAMD scores. Microstructural changes in the anterior-medial and lateral prefrontal white matter are potentially involved in treatment response to TMS, though further investigation is needed using larger datasets.

Habenular Involvement in Response to Subcallosal Cingulate Deep Brain Stimulation for Depression

The habenula (Hb) is a small, evolutionarily conserved epithalamic structure implicated in functions such as reward and mood regulation. Prior imaging work suggests that Hb's structural and functional properties may relate to treatment response in depression and other mood disorders. We used multimodal MRI techniques to investigate the potential involvement of Hb in response to subcallosal cingulate area deep brain stimulation (SCC-DBS) for treatment-resistant mood disorders. Using an automated segmentation technique, we compared Hb volume at baseline and at a subsequent post-operative timepoint (4.4 ± 3.0 years after surgery) in a cohort of 32 patients who received SCC-DBS. Clinical response to treatment (≥50% decrease in HAMD-17 from baseline to 12 months post-operation) was significantly associated with longitudinal Hb volume change: responders tended to have increased Hb volume over time, while non-responders showed decreased Hb volume (t = 2.4, p = 0.021). We additionally used functional MRI (fMRI) in a subcohort of SCC-DBS patients (n = 12) to investigate immediate within-patient changes in Hb functional connectivity associated with SCC-DBS stimulation. Active DBS was significantly associated with increased Hb connectivity to several prefrontal and corticolimbic regions (TFCE-adjusted p _Bonferroni < 0.0001), many of which have been previously implicated in the neurocircuitry of depression. Taken together, our results suggest that Hb may play an important role in the antidepressant effect of SCC-DBS.

3 T MRI of rapid brain activity changes driven by subcallosal cingulate deep brain stimulation

Deep brain stimulation targeting the subcallosal cingulate area (SCC-DBS), a hub with multiple axonal projections, has shown therapeutic potential for treatment-resistant mood disorders. While SCC-DBS drives long-term metabolic changes in corticolimbic circuits, the brain areas that are directly modulated by electrical stimulation of this region are not known. We used 3.0 Tesla functional MRI to map the topography of acute brain changes produced by stimulation in an initial cohort of twelve patients with fully implanted SCC-DBS devices. Four additional SCC-DBS patients were also scanned and employed as a validation cohort. Participants underwent resting state scans (n=78 acquisitions overall) during i) inactive DBS; ii) clinically optimal active DBS; iii) suboptimal active DBS. All scans were acquired within a single MRI session, each separated by a 5-minute washout period. Analysis of the amplitude of low frequency fluctuations (ALFF) in each sequence indicated that clinically optimal SCC-DBS reduced spontaneous brain activity in several areas, including bilateral dorsal anterior cingulate cortex (dACC), posterior cingulate cortex (PCC), precuneus, and left inferior parietal lobule (pBonferroni<0.0001). Stimulation-induced dACC signal reduction correlated with immediate within-session mood fluctuations, was greater at optimal versus suboptimal settings, and related to local cingulum bundle engagement. Moreover, linear modelling showed that immediate changes in dACC, PCC, and precuneus activity could predict individual long-term antidepressant improvement. A model derived from the primary cohort that incorporated ALFF changes in these three areas (along with pre-operative symptom severity) explained 55% of the variance in clinical improvement in that cohort. The same model also explained 93% of the variance in the out-of-sample validation cohort. Additionally all three brain areas exhibited significant changes in functional connectivity between active and inactive DBS states (pBonferroni<0.01). These results provide insight into the network-level mechanisms of SCC-DBS and point towards potential acute biomarkers of clinical response that could help to optimize and personalize this therapy.

Suppressed activity of the rostral anterior cingulate cortex as a biomarker for depression remission

BACKGROUND

Suppression of the rostral anterior cingulate cortex (rACC) has shown promise as a prognostic biomarker for depression. We aimed to use machine learning to characterise its ability to predict depression remission.

METHODS

Data were obtained from 81 15- to 25-year-olds with a major depressive disorder who had participated in the YoDA-C trial, in which they had been randomised to receive cognitive behavioural therapy plus either fluoxetine or placebo. Prior to commencing treatment patients performed a functional magnetic resonance imaging (fMRI) task to assess rACC suppression. Support vector machines were trained on the fMRI data using nested cross-validation, and were similarly trained on clinical data. We further tested our fMRI model on data from the YoDA-A trial, in which participants had completed the same fMRI paradigm.

RESULTS

Thirty-six of 81 (44%) participants in the YoDA-C trial achieved remission. Our fMRI model was able to predict remission status (AUC = 0.777 [95% confidence interval (CI) 0.638-0.916], balanced accuracy = 67%, negative predictive value = 74%, p < 0.0001). Clinical models failed to predict remission status at better than chance levels. Testing the model on the alternative YoDA-A dataset confirmed its ability to predict remission (AUC = 0.776, balanced accuracy = 64%, negative predictive value = 70%, p < 0.0001).

CONCLUSIONS

We confirm that rACC activity acts as a prognostic biomarker for depression. The machine learning model can identify patients who are likely to have difficult-to-treat depression, which might direct the earlier provision of enhanced support and more intensive therapies.

Critical role of rhythms in prefrontal transcranial magnetic stimulation for depression: A randomized sham-controlled study

Repetitive transcranial magnetic stimulation (rTMS) is an alternative treatment for depression, but the neural correlates of the treatment are currently inconclusive, which might be a limit of conventional analytical methods. The present study aimed to investigate the neurophysiological evidence and potential biomarkers for rTMS and intermittent theta burst stimulation (iTBS) treatment. A total of 61 treatment‐resistant depression patients were randomly assigned to receive prolonged iTBS (piTBS; N = 19), 10 Hz rTMS (N = 20), or sham stimulation (N = 22). Each participant went through a treatment phase with resting state electroencephalography (EEG) recordings before and after the treatment phase. The aftereffects of stimulation showed that theta‐alpha amplitude modulation frequency (f_am) was associated with piTBS_Responder, which involves repetitive bursts delivered in the theta frequency range, whereas alpha carrier frequency (f_c) was related to 10 Hz rTMS, which uses alpha rhythmic stimulation. In addition, theta‐alpha amplitude modulation frequency was positively correlated with piTBS antidepressant efficacy, whereas the alpha frequency was not associated with the 10 Hz rTMS clinical outcome. The present study showed that TMS stimulation effects might be lasting, with changes of brain oscillations associated with the delivered frequency. Additionally, theta‐alpha amplitude modulation frequency may be as a function of the degree of recovery in TRD with piTBS treatment and also a potential EEG‐based predictor of antidepressant efficacy of piTBS in the early treatment stage, that is, first 2 weeks.

Correlation between Post-Acute Electroconvulsive Therapy Alpha-Band Spectrum Power Increase and Improvement of Psychiatric Symptoms

The results of quantitative electroencephalography (qEEG) studies on electroconvulsive therapy (ECT) have been inconsistent, and indicators of the efficacy of ECT have not been clearly identified. In this study, we examined whether qEEG could be used as an indicator of the effect of ECT by measuring it during the course of treatment. We analyzed qEEG data before and after acute-phase ECT in 18 patients with schizophrenia, mood disorders, and other psychiatric disorders. We processed the qEEG data and compared the spectral power between the data acquired before and after ECT. The spectral power increased significantly after ECT in the delta, theta, and alpha bands. There was a strong significant correlation between the increase in the spectral power of the alpha band after acute ECT and improvement in the Brief Psychiatric Rating Scale score. Our results suggest that an increase in the alpha-band spectral power may be useful as an objective indicator of the treatment effect of acute ECT.

Coordinate-Based Network Mapping of Brain Structure in Major Depressive Disorder in Younger and Older Adults: A Systematic Review and Meta-Analysis

OBJECTIVE

Structural neuroimaging findings in younger and older adults with major depressive disorder (MDD) are highly heterogeneous, possibly as a result of methodological limitations, lack of distinction between MDD and late-life depression (LLD), or clinical moderators. Using a novel meta-analytic network mapping approach, the authors sought to identify the circuits affected in different clinical subtypes of MDD.

METHODS

The authors identified all voxel-based and surface-based morphometry studies published through October 2020 that compared younger adults with MDD or older adults with LLD to nonpsychiatric control participants. An activation likelihood estimation (ALE) analysis and a novel coordinate-based network mapping approach were used to identify brain circuits affected in MDD and LLD. Meta-regressions examined the impact of age at onset in older patients with LLD and treatment with antidepressants in younger patients with MDD.

RESULTS

The authors analyzed 145 comparisons from 143 articles, including a total of 14,318 participants (MDD: N=6,362; LLD: N=535; control subjects: N=7,421). Significant ALE results confirmed previous findings implicating the left and right parahippocampus and anterior cingulate in MDD and the anterior cingulate in LLD. In contrast, coordinate-based network mapping showed differences in the frontoparietal, dorsal attention, and visual networks both in MDD and LLD. Meta-regressions showed that late onset was significantly associated with widespread structural abnormalities in LLD, and treatment with antidepressants showed a significant association with abnormalities in the anterior cingulate (Brodmann's area 32) and dorsolateral prefrontal cortex (Brodmann's area 9) in MDD.

CONCLUSIONS

These findings help to clarify the shared circuitry of depression across the adult lifespan and highlight some unique circuitry relevant to late-onset depression, which may explain some of the risk for cognitive decline and dementia.

Cognitive Decline Risk Stratification in People with Late-Onset Epilepsy of Unknown Etiology: An Electroencephalographic Connectivity and Graph Theory Pilot Study

BACKGROUND

Although people with late onset epilepsy of unknown etiology (LOEU) are at higher risk of cognitive decline compared to the general population, we still lack affordable tools to predict and stratify their risk of dementia.

OBJECTIVE

This pilot-study investigates the potential application of electroencephalography (EEG) network small-world (SW) properties in predicting cognitive decline among patients with LOEU.

METHODS

People diagnosed with LOEU and normal cognitive examination at the time of epilepsy diagnosis were included. Cerebrospinal fluid biomarkers, brain imaging, and neuropsychological assessment were performed at the time of epilepsy diagnosis. Baseline EEG was analyzed for SW properties. Patients were followed-up over time with neuropsychological testing to define the trajectory of cognitive decline.

RESULTS

Over 5.1 years of follow-up, among 24 patients diagnosed with LOEU, 62.5% were female, mean age was 65.3 years, thirteen developed mild cognitive impairment (MCI), and four developed dementia. Patients with LOEU developing MCI had lower values of SW coefficients in the delta (p = 0.03) band and higher SW values in the alpha frequency bands (p = 0.02) compared to patients having normal cognition at last follow-up. The two separate ANOVAs, for low and alpha bands, confirmed an interaction between SW and cognitive decline at follow-up. A similar gradient was confirmed for patients developing dementia compared to those with normal cognitive function as well as to those developing MCI.

CONCLUSION

Baseline EEG analysis through SW is worth investigating as an affordable, widely available tool to stratify LOEU patients for their risk of cognitive decline.

Characterizing Sex Differences in Depressive-Like Behavior and Glial Brain Cell Changes Following Peripheral Nerve Injury in Mice

Chronic pain and depression are intimately linked; the combination of the two leads to higher health care costs, lower quality of life, and worse treatment outcomes with both conditions exhibiting higher prevalence among women. In the current study, we examined the development of depressive-like behavior in male and female mice using the spared nerve injury (SNI) model of neuropathic pain. Males displayed increased immobility on the forced-swim test - a measure of depressive-like behavior - 2 weeks following injury, while females developed depressive-like behavior at 3-week. Since the pathogenesis of chronic pain and depression may involve overlapping mechanisms including the activation of microglial cells, we explored glial cell changes in brain regions associated with pain processing and affect. Immunohistochemical analyses revealed that microglial cells were more numerous in female SNI mice in the contralateral ventral anterior cingulate cortex (ACC), a brain region important for pain processing and affect behavior, 2-week following surgery. Microglial cell activation was not different between any of the groups for the dorsal ACC or nucleus accumbens. Analysis of astrocyte density did not reveal any significant changes in glial fibrillary acidic protein (GFAP) staining in the ACC or nucleus accumbens. Overall, the current study characterized peripheral nerve injury induced depression-like behavior in male and female mice, which may be associated with different patterns of glial cell activation in regions important for pain processing and affect.

Is the posterior cingulate cortex an on-off switch for tinnitus?: A comparison between hearing loss subjects with and without tinnitus

As the human brain works in a Bayesian manner to minimize uncertainty toward external stimuli, the deafferented brain may generate tinnitus in an attempt to fill in missing auditory information, e.g. due to hearing loss. However, not everybody with hearing loss develops tinnitus. Understanding the differences between people with hearing loss who develop tinnitus versus those who do not offers a unique opportunity to unravel critical brain areas involved in the generation of a phantom sound. In this study, we compared resting-state quantitative electroencephalography between hearing loss patients with (HL-T) and without tinnitus (HL-NT) to identify cortical oscillatory signatures that may reveal prerequisites for the selective development of tinnitus in subjects with hearing loss. We enrolled 65 subjects with HL-NT and 65 subjects with HL-T whose tinnitus handicap inventory scores were <16 (grade 1) to minimize the bias induced by distress-induced cortical activity changes. Subjects in the HL-T and HL-NT groups were matched in terms of the bilateral hearing threshold (0.25-8 kHz) using nearest neighbor method. Compared to the HL-NT group, the HL-T group showed significantly higher activity in the right parahippocampus for the beta 1 frequency band, in the left inferior parietal lobule (IPL) for the beta 2 frequency band, and in the right IPL for the beta 3- and gamma frequency bands. Functional connectivity analyses revealed that the HL-T group had significantly higher connectivity than the HL-NT group between both parahippocampal gyri and the right IPL for the delta frequency band, and between the left posterior cingulate cortex (PCC) and right IPL for the beta 2 frequency band. These results suggest that tinnitus may be perceived only if auditory memory stored in the parahippocampus is actively linked to the IPL-based "circuit breaker" system and the circuit breaker signal is connected to the PCC-based default mode network (DMN). Thus, when the circuit breaker system regards tinnitus secondary to peripheral deafferentation as a salient event and then the DMN regards tinnitus as a norm, subjects with hearing loss may consciously perceive tinnitus. The results of this study further refine the recently proposed Bayesian model and decipher the neurobiological mechanism of the selective development of tinnitus in subjects with hearing loss.

Resting posterior alpha power and adolescent major depressive disorder

For several decades, resting electroencephalogram (EEG) alpha oscillations have been used to characterize neurophysiological alterations related to major depressive disorder. Prior research has generally focused on frontal alpha power and asymmetry despite resting alpha being maximal over posterior electrode sites. Research in depressed adults has shown evidence of hemispheric asymmetry for posterior alpha power, however, the resting posterior alpha-depression link among adolescents remains unclear. To clarify the role of posterior alpha among depressed adolescents, the current study acquired eyes-closed 128-channel resting EEG data from 13 to 18 year-old depressed (n = 31) and healthy (n = 35) female adolescents. Results indicated a significant group by hemisphere interaction, as depressed adolescents exhibited significantly larger posterior alpha (i.e., lower brain activity) over the right versus left hemisphere, whereas healthy adolescents showed no hemispheric differences. Relatively greater alpha over the right versus left hemisphere correlated with depression symptoms, anhedonia symptoms, rumination, and self-criticism. Further, depressed adolescents had reduced overall posterior alpha compared to healthy youth; though, no associations with symptoms and related traits emerged. Resting posterior alpha may be a promising neurophysiological index of adolescent depression, and more broadly, may relate to risk factors characterized by enhanced perseveration.

Pretreatment qEEG biomarkers for predicting pharmacological treatment outcome in major depressive disorder: Independent validation from the NeuroPharm study

Several electroencephalogram (EEG) biomarkers for prediction of drug response in major depressive disorder (MDD) have been proposed, but validations in larger independent datasets are missing. In the current study, we investigated the prognostic value of previously suggested EEG biomarkers. We gathered data that matched prior studies in terms of EEG methodology, clinical criteria for MDD, and statistical approach as closely as possible. The NeuroPharm study is a non-randomized and open label prospective clinical trial. One hundred antidepressant free patients with MDD were enrolled in the study and 79 (57 female) were included in the per-protocol analysis. The biomarkers candidates for cross-validation were derived from prior studies such as iSPOT-D and EMBARC and include frontal and occipital alpha power and asymmetry and delta and theta activity at anterior cingulate cortex (ACC). The alpha asymmetry, reported in two out of six prior studies, could be partially validated. We found that in female patients, larger right than left frontal alpha power prior to drug treatment was associated with better clinical outcome 8 weeks later. Moreover, female non-responder had higher central left alpha power relative to the right. In contrast to prior reports, we found that lower theta activity at ACC was present in remitters and was associated with greater improvement at week 8. We provide evidence that in women with MDD, alpha asymmetry seems to be the most promising EEG biomarker for prediction of treatment response. Registration number: NCT02869035.

Structuro-functional surrogates of response to subcallosal cingulate deep brain stimulation for depression

Subcallosal cingulate deep brain stimulation (SCC-DBS) produces long-term clinical improvement in approximately half of patients with severe treatment-resistant depression (TRD). We hypothesized that both structural and functional brain attributes may be important in determining responsiveness to this therapy. In a TRD SCC-DBS cohort, we retrospectively examined baseline and longitudinal differences in MRI-derived brain volume (n = 65) and 18F-fluorodeoxyglucose-PET glucose metabolism (n = 21) between responders and non-responders. Support-vector machines (SVMs) were subsequently trained to classify patients' response status based on extracted baseline imaging features. A machine learning model incorporating pre-operative frontopolar, precentral/frontal opercular, and orbitofrontal local volume values classified binary response status (12 months) with 83% accuracy (leave-one-out cross-validation (LOOCV): 80% accuracy) and explained 32% of the variance in continuous clinical improvement. It was also predictive in an out-of-sample SCC-DBS cohort (n = 21) with differing primary indications (bipolar disorder/anorexia nervosa) (76% accuracy). Adding pre-operative glucose metabolism information from rostral anterior cingulate cortex and temporal pole improved model performance, enabling it to predict response status in the TRD cohort with 86% accuracy (LOOCV: 81% accuracy) and explain 67% of clinical variance. Response-related patterns of metabolic and structural post-DBS change were also observed, especially in anterior cingulate cortex and neighbouring white matter. Areas where responders differed from non-responders - both at baseline and longitudinally - largely overlapped with depression-implicated white matter tracts, namely uncinate fasciculus, cingulum bundle, and forceps minor/rostrum of corpus callosum. The extent of patient-specific engagement of these same tracts (according to electrode location and stimulation parameters) also served as a predictor of TRD response status (72% accuracy; LOOCV: 70% accuracy) and augmented performance of the volume-based (88% accuracy; LOOCV: 82% accuracy) and combined volume/metabolism-based SVMs (100% accuracy; LOOCV: 94% accuracy). Taken together, these results indicate that responders and non-responders to SCC-DBS exhibit differences in brain volume and metabolism, both pre- and post-surgery. Baseline imaging features moreover predict response to treatment (particularly when combined with information about local tract engagement) and could inform future patient selection and other clinical decisions.

Neural correlates of citalopram and placebo response in acute bipolar depression: A randomized trial

While serotonin reuptake inhibitors are sometimes used in clinical practice to treat acute bipolar depression, the neurophysiological substrates underlying their efficacy are little studied. In the context of a larger clinical efficacy trial, the present study explored neural mechanisms associated with citalopram versus placebo treatment for bipolar depression. FDG-PET imaging examined whole-brain metabolic changes before and after treatment. Clinical efficacy was similar for citalopram versus placebo. Neuroimaging results demonstrated greater glucose metabolism in the left orbitofrontal cortex (OFC) before treatment (combined citalopram and placebo subjects) relative to after treatment, but did not correlate with clinical recovery. Glucose metabolism in the left OFC was also a predictor of depression severity when baseline scans were regressed with baseline MADRS scores. Despite of our small sample size and possibly underpowered whole-brain analysis approach, these preliminary results suggest the OFC, a key region involved in reward circuity, may be a neural substrate for depressive symptom improvement in bipolar depression, regardless of whether due to active treatment or placebo.

Psychiatric Neural Networks and Precision Therapeutics by Machine Learning

Learning and environmental adaptation increase the likelihood of survival and improve the quality of life. However, it is often difficult to judge optimal behaviors in real life due to highly complex social dynamics and environment. Consequentially, many different brain regions and neuronal circuits are involved in decision-making. Many neurobiological studies on decision-making show that behaviors are chosen through coordination among multiple neural network systems, each implementing a distinct set of computational algorithms. Although these processes are commonly abnormal in neurological and psychiatric disorders, the underlying causes remain incompletely elucidated. Machine learning approaches with multidimensional data sets have the potential to not only pathologically redefine mental illnesses but also better improve therapeutic outcomes than DSM/ICD diagnoses. Furthermore, measurable endophenotypes could allow for early disease detection, prognosis, and optimal treatment regime for individuals. In this review, decision-making in real life and psychiatric disorders and the applications of machine learning in brain imaging studies on psychiatric disorders are summarized, and considerations for the future clinical translation are outlined. This review also aims to introduce clinicians, scientists, and engineers to the opportunities and challenges in bringing artificial intelligence into psychiatric practice.

Impaired posterior cingulate cortex-parahippocampus connectivity is associated with episodic memory retrieval problems in amnestic mild cognitive impairment

Episodic memory retention and retrieval decline are the most common impairments observed in amnestic mild cognitive impairment (aMCI) patients who progress to Alzheimer's disease (AD). Clinical electroencephalography research shows that patients with dementia due to AD exhibit a slowing of neural electrical activity in the parietal cortex. Memory research has further suggested that successful memory performance is associated with changes in a posterior cingulate-parahippocampal cortical network together with increased θ-γ oscillatory coupling, where θ oscillations act as carrier waves for γ oscillations, which contain the actual information. However, the neurophysiological link between the memory research and clinical studies investigating aMCI and AD is lacking. In this study, we look at brain activity in aMCI and how it relates to memory performance. We demonstrate decreased γ power in the posterior cingulate cortex and the left and right parahippocampus in aMCI patients in comparison to control participants. This goes together with reduced θ coherence between the posterior cingulate cortex and parahippocampus associated with altered memory performance aMCI patients in comparison to control participants. In addition, comparing patients with aMCI to control participants reveals an effect for θ-γ coupling for the posterior cingulate cortex, and the left and right parahippocampus. Taken together, our results show that parahippocampus and posterior cingulate cortex interact via θ-γ coupling, which is associated with memory recollection and is altered in aMCI patients, offering a potential candidate mechanism for memory decline in aMCI.

EEG biomarker informed prescription of antidepressants in MDD: a feasibility trial

Using pre-treatment biomarkers to guide patients to the preferred antidepressant medication treatment could be a promising approach to enhance its current modest response and remission rates. This open-label prospective study assessed the feasibility of using such pre-treatment biomarkers, by using previously identified EEG features (paroxysmal activity; alpha peak frequency; frontal alpha asymmetry) to inform the clinician in selecting among three different antidepressants (ADs; escitalopram, sertraline, venlafaxine) as compared to Treatment As Usual (TAU). EEG data were obtained from 195 outpatients with major depressive disorder prior to eight weeks of AD treatment. Primary outcome measure was the percentage change between before and after treatment on the Beck Depression Inventory-II (BDI-II). We compared TAU and EEG-informed prescription through AN(C)OVAs. Recruitment started with patients receiving TAU to establish baseline effectiveness, after which we recruited patients receiving EEG-informed prescription. 108 patients received EEG-informed prescription and 87 patients received TAU. Clinicians and patients were satisfied with the protocol. Overall, 70 (65%) of the EEG-informed clinicians followed recommendations (compared to 52 (60%) following prescriptions in the TAU group), establishing feasibility. We here confirm that treatment allocation informed by EEG variables previously reported in correlational studies, was feasible.

Brain Activation Imaging in Emotional Decision Making and Mental Health: A Review-Part 1

In part 1 of this article, we describe an approach and methodology that bridges 2 worlds: the internal, subjective experience of emotions and thoughts, and the external world of brain electrical activity. Using a novel event-related brain activation imaging method, we demonstrate that within single trials, short-term mental processes, on the order of 100 ms, can be clearly related to observed brain activation in controlled experiments. We use an ipsative assessment validation process that combines self-report with real-time EEG recordings to provide a combined picture of both the mental and the brain activity, during short-term reactions, emotions, and decisions regarding controlled information. Part 2 provides a detailed description of the emerging emotional decision-making model.

Functional connectivity between the amygdala and subgenual cingulate gyrus predicts the antidepressant effects of ketamine in patients with treatment-resistant depression

Aim

Approximately one‐third of patients with major depressive disorder develop treatment‐resistant depression. One‐third of patients with treatment‐resistant depression demonstrate resistance to ketamine, which is a novel antidepressant effective for this disorder. The objective of this study was to examine the utility of resting‐state functional magnetic resonance imaging for the prediction of treatment response to ketamine in treatment‐resistant depression.

Methods

An exploratory seed‐based resting‐state functional magnetic resonance imaging analysis was performed to examine baseline resting‐state functional connectivity differences between ketamine responders and nonresponders before treatment with multiple intravenous ketamine infusions.

Results

Fifteen patients with treatment‐resistant depression received multiple intravenous subanesthetic (0.5 mg/kg/40 minutes) ketamine infusions, and nine were identified as responders. The exploratory resting‐state functional magnetic resonance imaging analysis identified a cluster of significant baseline resting‐state functional connectivity differences associating ketamine response between the amygdala and subgenual anterior cingulate gyrus in the right hemisphere. Using anatomical region of interest analysis of the resting‐state functional connectivity, ketamine response was predicted with 88.9% sensitivity and 100% specificity. The resting‐state functional connectivity of significant group differences between responders and nonresponders retained throughout the treatment were considered a trait‐like feature of heterogeneity in treatment‐resistant depression.

Conclusion

This study suggests the possible clinical utility of resting‐state functional magnetic resonance imaging for predicting the antidepressant effects of ketamine in treatment‐resistant depression patients and implicated resting‐state functional connectivity alterations to determine the trait‐like pathophysiology underlying treatment response heterogeneity in treatment‐resistant depression.

This study illustrates that the alteration in the RSFC within the right AN in TRD patients reflects the antidepressant response to ketamine at baseline. The alteration remained throughout the 2‐week treatment with multiple ketamine infusions and seemed to reflect the trait‐like features underlying treatment heterogeneity in TRD. By employing an anatomical ROI of the sc/sgACC, the present study also suggests the possible clinical utility of the rsfMRI to predict the treatment response to ketamine in TRD patients.

Increased functional connectivity within alpha and theta frequency bands in dysphoria: A resting-state EEG study

BACKGROUND

The understanding of neurophysiological correlates underlying the risk of developing depression may have a significant impact on its early and objective identification. Research has identified abnormal resting-state electroencephalography (EEG) power and functional connectivity patterns in major depression. However, the entity of dysfunctional EEG dynamics in dysphoria is yet unknown.

METHODS

32-channel EEG was recorded in 26 female individuals with dysphoria and in 38 age-matched, female healthy controls. EEG power spectra and alpha asymmetry in frontal and posterior channels were calculated in a 4-minute resting condition. An EEG functional connectivity analysis was conducted through phase locking values, particularly mean phase coherence.

RESULTS

While individuals with dysphoria did not differ from controls in EEG spectra and asymmetry, they exhibited dysfunctional brain connectivity. Particularly, in the theta band (4-8 Hz), participants with dysphoria showed increased connectivity between right frontal and central areas and right temporal and left occipital areas. Moreover, in the alpha band (8-12 Hz), dysphoria was associated with increased connectivity between right and left prefrontal cortex and between frontal and central-occipital areas bilaterally.

LIMITATIONS

All participants belonged to the female gender and were relatively young. Mean phase coherence did not allow to compute the causal and directional relation between brain areas.

CONCLUSIONS

An increased EEG functional connectivity in the theta and alpha bands characterizes dysphoria. These patterns may be associated with the excessive self-focus and ruminative thinking that typifies depressive symptoms. EEG connectivity patterns may represent a promising measure to identify individuals with a higher risk of developing depression.

A developmental perspective on personality and psychopathology across the life span

Taking a developmental perspective, guided by core principles of developmental science and developmental psychopathology, is necessary to move the fields of personality science and psychopathology forward. Personality and psychopathology can be delineated using hierarchical models of individual differences, as evidenced by decades of converging evidence across community and psychiatric samples, countries and cultures, and ages and developmental periods. A large body of empirical research likewise documents associations between personality and various forms of psychopathology. Cross-sectional investigations of personality-psychopathology links in samples of adults now yield diminishing returns. Prospective, longitudinal investigations that assess personality, psychopathology, and their co-development across the life span are needed to determine their temporal ordering, capture dynamic associations over time and development, and elucidate causal origins and underlying mechanisms. We lay out a developmental framework that integrates across the developmental, personality, and psychopathology literatures in order to further understanding and guide future investigations of the nature of personality-psychopathology links.

EEG Correlates of Cognitive Functions and Neuropsychiatric Disorders: A Review of Oscillatory Activity and Neural Synchrony Abnormalities

Background:

A large body of evidence suggested that disruption of neural rhythms and synchronization of brain oscillations are correlated with a variety of cognitive and perceptual processes. Cognitive deficits are common features of psychiatric disorders that complicate treatment of the motivational, affective and emotional symptoms.

Objective:

Electrophysiological correlates of cognitive functions will contribute to understanding of neural circuits controlling cognition, the causes of their perturbation in psychiatric disorders and developing novel targets for the treatment of cognitive impairments.

Methods:

This review includes a description of brain oscillations in Alzheimer’s disease, bipolar disorder, attention-deficit/hyperactivity disorder, major depression, obsessive compulsive disorders, anxiety disorders, schizophrenia and autism.

Results:

The review clearly shows that the reviewed neuropsychiatric diseases are associated with fundamental changes in both spectral power and coherence of EEG oscillations.

Conclusion:

In this article, we examined the nature of brain oscillations, the association of brain rhythms with cognitive functions and the relationship between EEG oscillations and neuropsychiatric diseases. Accordingly, EEG oscillations can most likely be used as biomarkers in psychiatric disorders.

From affective to cognitive processing: Functional organization of the medial frontal cortex

The medial wall of the primate frontal lobe encompasses multiple anatomical subregions. Based on distinct neurophysiological correlates and effects of lesions, individual areas are thought to play unique roles in behavior. Further, evidence suggests that dysfunction localized to specific subregions is commonly found in different neuropsychiatric disorders. The neurobiological underpinnings of these disorders, however, remain far from clear. Here, to better understand the functions of medial frontal cortex (MFC) and its role in psychiatric disease, we focus on its functional organization. We describe the emerging pattern in which more dorsal regions subserve temporally extended cognitive functions and more ventral regions predominantly subserve affective functions. We focus on two specific domains, decision-making and social cognition, that require integration across emotion and cognition. In each case, we discuss the current understanding of the functions believed to depend on subregions of MFC as a stepping-stone to speculate on how they might work in unison. We conclude with an overview of how symptoms of certain psychiatric disorders relate to our understanding of MFC functional organization and how further discovery could fuel advances in circuit-based therapies.

Relationship Between Abnormalities in Resting-State Quantitative Electroencephalogram Patterns and Poststroke Depression

PURPOSE

Spectral power analysis of quantitative EEG has gained popularity in the assessment of depression, but findings across studies concerning poststroke depression (PSD) have been inconsistent. The goal of this study was to determine the extent to which abnormalities in quantitative EEG differentiate patients with PSD from poststroke nondepressed (PSND) subjects.

METHODS

Resting-state EEG signals of 34 participants (11 patients with PSD and 23 PSND subjects) were recorded, and then the spectral power analysis for six frequency bands (alpha1, alpha2, beta1, beta2, delta, and theta) was conducted at 16 electrodes. Pearson linear correlation analysis was used to investigate the association between depression severity measured with the Hamilton Depression Rating Scale (HDRS) total score and absolute power values. In addition, receiver operating characteristic curves were used to assess the sensitivity and specificity of quantitative EEG in discriminating PSD.

RESULTS

In comparison with PSND patients, PSD patients showed significantly higher alpha1 power in left temporal region and alpha2 power at left frontal pole. Higher theta power in central, temporal, and occipital regions was observed in patients with PSD. The results of Pearson linear correlation analysis showed significant association between HDRS total score and the absolute alpha1 power in frontal, temporal, and parietal regions.

CONCLUSIONS

Absolute powers of alpha and theta bands significantly distinguish between PSD patients and PSND subjects. Besides, absolute alpha1 power is positively associated with the severity of depression.

Using EEG to Predict Clinical Response to Electroconvulsive Therapy in Patients With Major Depression: A Comprehensive Review

Introduction: An important approach to improve the therapeutic effect of electroconvulsive therapy (ECT) may be to early characterize patients who are more likely to respond. Our objective was to explore whether baseline electroencephalography (EEG) settings before the beginning of ECT treatment can predict future clinical response to ECT in patients with depressive disorder. Methods: We conducted a systematic search in the MEDLINE, EMBASE, PsycINFO, Web of Science, and Cochrane Central Register of Controlled Trials (CENTRAL) databases to identify studies using EEG in adults with depressive disorder treated by ECT. To investigate the predictive value of baseline EEG on clinical outcomes of ECT, we extracted from the retrieved studies and qualitatively described the association between the baseline EEG markers characteristics and the rates of future responders and/or remitters to ECT. Results: The primary search yielded 2,531 potentially relevant citations, and 12 articles were selected according to inclusion criteria. Most of the studies were prospective studies with small sample size. Sociodemographic and clinical characteristics of patients, ECT settings, EEG settings, and outcomes were heterogeneous. Event-related potential (ERP) paradigms were used in three studies, polysomnography was used in three studies, and the six other studies used EEG to measure cerebral connectivity and activity. Conclusions: P300 amplitude, coherence, and connectivity measures were correlated with remission in patients with depression treated by ECT. Sleep EEG recordings seemed not to be correlated with remission after ECT. Further prospective studies with large sample size are needed to determine optimal EEG parameters associated with clinical response to ECT in depressive disorder. Systematic Review Registration: PROSPERO CRD42020181978.

Resting EEG theta connectivity and alpha power to predict repetitive transcranial magnetic stimulation response in depression: A non-replication from the ICON-DB consortium

OBJECTIVE

Our previous research showed high predictive accuracy at differentiating responders from non-responders to repetitive transcranial magnetic stimulation (rTMS) for depression using resting electroencephalography (EEG) and clinical data from baseline and one-week following treatment onset using a machine learning algorithm. In particular, theta (4-8 Hz) connectivity and alpha power (8-13 Hz) significantly differed between responders and non-responders. Independent replication is a necessary step before the application of potential predictors in clinical practice. This study attempted to replicate the results in an independent dataset.

METHODS

We submitted baseline resting EEG data from an independent sample of participants who underwent rTMS treatment for depression (N = 193, 128 responders) (Krepel et al., 2018) to the same between group comparisons as our previous research (Bailey et al., 2019).

RESULTS

Our previous results were not replicated, with no difference between responders and non-responders in theta connectivity (p = 0.250, Cohen's d = 0.1786) nor alpha power (p = 0.357, η_p² = 0.005).

CONCLUSIONS

These results suggest that baseline resting EEG theta connectivity or alpha power are unlikely to be generalisable predictors of response to rTMS treatment for depression.

SIGNIFICANCE

These results highlight the importance of independent replication, data sharing and using large datasets in the prediction of response research.

The Changes of qEEG Approximate Entropy during Test of Variables of Attention as a Predictor of Major Depressive Disorder

Evaluating brain function through biosignals remains challenging. Quantitative electroencephalography (qEEG) outcomes have emerged as a potential intermediate biomarker for diagnostic clarification in psychological disorders. The Test of Variables of Attention (TOVA) was combined with qEEG to evaluate biomarkers such as absolute power, relative power, cordance, and approximate entropy from covariance matrix images to predict major depressive disorder (MDD). EEG data from 18 healthy control and 18 MDD patients were monitored during the resting state and TOVA. TOVA was found to provide aspects for the evaluation of MDD beyond resting electroencephalography. The results showed that the prefrontal qEEG theta cordance of the control and MDD groups were significantly different. For comparison, the changes in qEEG approximate entropy (ApEn) patterns observed during TOVA provided features to distinguish between participants with or without MDD. Moreover, ApEn scores during TOVA were a strong predictor of MDD, and the ApEn scores correlated with the Beck Depression Inventory (BDI) scores. Between-group differences in ApEn were more significant for the testing state than for the resting state. Our results provide further understanding for MDD treatment selection and response prediction during TOVA.

Altered miRNA landscape of the anterior cingulate cortex is associated with potential loss of key neuronal functions in depressed brain

MicroRNAs (miRNAs), a family of non-coding RNAs, have recently gained a considerable attention in neuropsychiatric disorders. Being a pleiotropic modulator of target gene(s), miRNA has been recognized as central to downstream gene regulatory networks. In the recent past, reports have suggested their role in changing the epigenetic landscape in brain of subjects with major depressive disorder (MDD). Anterior cingulate cortex (ACC) is a brain area implicated in several complex cognitive functions, such as impulse control, emotion, and decision-making and is associated with psychopathology associated with mood regulation. In this study, we examined whether MDD is associated with altered miRNA transcriptome in ACC and whether altered miRNA landscape is associated with modifications in specific gene network(s) at the functional level. Using next generation sequencing (NGS), it was observed that 117 miRNAs (4.61%) were significantly upregulated and 54 (2.13%) were downregulated in MDD subjects (n = 22) compared with non-psychiatric controls (n = 25). Using 24 most significantly upregulated miRNAs in the MDD group, we determined functional enrichment of target genes and found them to be associated with long-term potentiation, neurotrophin signaling, and axon guidance. Intra- and inter-cluster similarities of enriched terms based on overrepresented gene list showed neurobiological functions associated with neuronal growth and survival. Web centric parameters and ontology enrichment functions identified two major domains related to phosphatidyl signaling, GTPase signaling, neuronal migration, and neurotrophin signaling. Our findings of altered miRNA landscape along with a shift in targetome relate to previously reported morphometric changes and neuronal atrophy in ACC of MDD subjects.

Serial Prefrontal Pathways Are Positioned to Balance Cognition and Emotion in Primates

The delicate balance among primate prefrontal networks is necessary for homeostasis and behavioral flexibility. Dorsolateral prefrontal cortex (dlPFC) is associated with cognition, while the most ventromedial subgenual cingulate area 25 (A25) is associated with emotion and emotional expression. Yet A25 is weakly connected with dlPFC, and it is unknown how the two regions communicate. In rhesus monkeys of both sexes, we investigated how these functionally distinct areas may interact through pregenual anterior cingulate area 32 (A32), which is strongly connected with both. We found that dlPFC innervated the deep layers of A32, while A32 innervated all layers of A25, mostly targeting spines of excitatory neurons. Approximately 20% of A32 terminations formed synapses on inhibitory neurons in A25, notably the powerful parvalbumin inhibitory neurons in the deep layers, and the disinhibitory calretinin neurons in the superficial layers. By innervating distinct inhibitory microenvironments in laminar compartments, A32 is positioned to tune activity in columns of A25. The circuitry of the sequential pathway indicates that when dlPFC is engaged, A32 can dampen A25 output through the parvalbumin inhibitory microsystem in the deep layers of A25. A32 thus may flexibly recruit or reduce activity in A25 to maintain emotional equilibrium, a process that is disrupted in depression. Moreover, pyramidal neurons in A25 had a heightened density of NMDARs, which are the targets of novel rapid-acting antidepressants. Pharmacologic antagonism of NMDARs in patients with depression may reduce excitability in A25, mimicking the effects of the neurotypical serial pathway identified here.SIGNIFICANCE STATEMENT The anterior cingulate is a critical hub in prefrontal networks through connections with functionally distinct areas. Dorsolateral and polar prefrontal areas that are associated with complex cognition are connected with the anterior cingulate in a pattern that allows them to indirectly control downstream activity from the anterior cingulate to the subgenual cingulate, which is associated with heightened activity and negative affect in depression. This set of pathways provides a circuit mechanism for emotional regulation, with the anterior cingulate playing a balancing role for integration of cognitive and emotional processes. Disruption of these pathways may perturb network function and the ability to regulate cognitive and affective processes based on context.

Stop! - The automatic tendency of action, inhibition and frontal activation in individuals with alcohol-use disorder in abstinence

Studying the functioning of the frontal lobe during the performance of an inhibitory activity according to automatic tendency of action would allow a better understanding of the relationship between the reflexive and impulsive system described in the dual-process models. This study aims to prove which is the inhibitory capacity and the underlying brain activity of people with alcohol-use disorder in abstinence with a greater avoidance tendency compared to those with a higher approach tendency and healthy controls. In order to group participants with AUD, the total approach/avoidance index (TAAI) - obtained from the modified alcohol approach/avoidance task - was used, therefore resulting in three groups: TAAI- (TAAI < Percentile 35: n = 20), TAAI± (TAAI = Percentile 35-65: n = 20) and TAAI+ (TAAI > Percentile 65: n = 20). In addition to this, 15 healthy controls were recruited. They all had an electroencephalographic recording while completing the modified stop-signal task. The results showed that the TAAI+ group had a worse inhibition compared to healthy controls. Moreover, the TAAI+ group showed a hyperactivation of the inferior frontal gyrus, precentral gyrus and orbital gyrus compared to the healthy controls group and the TAAI- group. The results obtained reflect that those people with AUD with a tendency to approach alcohol have a worse inhibitory capacity and a frontal hyperactivation. Moreover, people with AUD with an avoidance tendency to alcohol have also been found to have a similar inhibitory capacity and frontal activation to healthy controls.

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.

Resting-state hyperconnectivity within the default mode network impedes the ability to initiate cognitive performance in first-episode schizophrenia patients

Among multiple cognitive impairments present in schizophrenia, a decline in fast information processing is one of the most severe neuropsychological deficit. Reduced ability to efficiently launch a coherent cognitive activity might be a significant factor contributing to poor results in time-limited tasks obtained by schizophrenia patients. The aim of this study was to identify neurophysiological predictors of expected cognitive initiation failures in a group of first-episode schizophrenia individuals (SZ). To evaluate the effectiveness of initiation, a dynamic analysis of design fluency test was applied, assessing to what extent the productivity was focused within the first interval of the performance, what is a typical way healthy subjects execute this task. Resting-state EEG recordings were obtained from SZ patients (n = 34) and controls (n = 30) to examine functional connectivity between 84 intra-cortical current sources determined by eLORETA (exact low-resolution brain electromagnetic tomography) for six conventionally analyzed frequencies. The nonparametric randomization approach was used to identify hypo- and hyper-connections, i.e. synchronizations significantly differentiating the studied samples in terms of connectivity strength. Generally, SZ patients obtained poor outcomes in fluency test and dynamic analysis of performance confirmed the presence of initiation deficit in clinical sample, which was a single factor explaining the intergroup difference regarding the entire task. In the majority of frequencies, the arrangement of synchronizations in SZ group was dominated by hypo-connections, except for the theta band, in which the strength of synchronizations between posterior cingulate cortex, cuneus and precuneus was significantly higher for SZ group. These theta-band hyper-connections turned out to be significant predictors of cognitive initiation failure in the clinical sample. Additionally, theta hyper-connections correlated negatively with the total number of unique designs generated by patients, however, the strength of this correlation was weaker than regarding initiation index. The results of this study suggest that baseline hyperconnectivity within the posterior hub of the Default Mode Network, containing posterior cingulate gyrus and precuneus, might disturb effective cognitive outcome, not only by interfering with task-positive functional networks but also by delaying the starting phase of performance, which might be specifically deleterious for the execution of time-limited tests.

The effect of mGlu2/3 receptors on synaptic activities to different types of GABAergic interneurons in the anterior cingulate cortex

Antagonists of the group II metabotropic glutamate (mGlu) 2/3 receptors have been shown to have a rapid antidepressant effect. GABAergic interneurons play a crucial role in major depressive disorder (MDD) and possibly mediate the rapid antidepressant effect. However, how mGlu2/3 receptors regulate synaptic activities to GABAergic interneurons is not fully understood. In the present work, we studied the effect of mGlu2/3 receptors on excitatory and inhibitory synaptic activities to somatostatin (SST)- and parvalbumin (PV)-expressing interneurons, two major types of GABAergic interneurons, in the anterior cingulate cortex (ACC) that is strongly indicated in MDD. We found that activation of mGlu2/3 receptors by (2S,2'R,3'R)-2-(2',3'-dicarboxycyclopropyl) glycine (DCG-IV), an agonist of mGlu2/3 receptors, remarkably reduced the frequency, but not the amplitude, of spontaneous and miniature excitatory postsynaptic currents (sEPSCs and mEPSCs) and the amplitude of evoked EPSCs in both types. The reduction in the frequency of sEPSCs and the amplitude of evoked EPSCs was more pronounced in SST interneurons. DCG-IV, however, did not affect spontaneous and miniature inhibitory postsynaptic currents (sIPSCs and mIPSCs) and evoked IPSCs in both types. LY341495, an antagonist of mGlu2/3 receptors, enhanced the amplitude of evoked EPSCs without affecting sEPSCs and mEPSCs in both types. It also did not affect sIPSCs and evoked IPSCs except slightly increasing the frequency of mIPSCs in SST interneurons. Our results indicate that mGlu2/3 receptors primarily regulate excitatory synaptic activities to the two types of GABAergic interneurons in the ACC.

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.