Cerebral metabolic correlates as potential predictors of response to anterior cingulotomy for treatment of major depression

Explainable multimodal prediction of treatment-resistance in patients with depression leveraging brain morphometry and natural language processing

Although 20 % of patients with depression receiving treatment do not achieve remission, predicting treatment-resistant depression (TRD) remains challenging. In this study, we aimed to develop an explainable multimodal prediction model for TRD using structured electronic medical record data, brain morphometry, and natural language processing. In total, 247 patients with a new depressive episode were included. TRD-predictive models were developed based on the combination of following parameters: selected tabular dataset features, independent components-map weightings from brain T1-weighted magnetic resonance imaging (MRI), and topic probabilities from clinical notes. All models applied the extreme gradient boosting (XGBoost) algorithm via five-fold cross-validation. The model using all data sources showed the highest area under the receiver operating characteristic of 0.794, followed by models that used combined brain MRI and structured data, brain MRI and clinical notes, clinical notes and structured data, brain MRI only, structured data only, and clinical notes only (0.770, 0.762, 0.728, 0.703, 0.684, and 0.569, respectively). Classifications of TRD were driven by several predictors, such as previous exposure to antidepressants and antihypertensive medications, sensorimotor network, default mode network, and somatic symptoms. Our findings suggest that a combination of clinical data with neuroimaging and natural language processing variables improves the prediction of TRD.

Neurobiological Underpinnings of Hyperarousal in Depression: A Comprehensive Review

Patients with major depressive disorder (MDD) exhibit an abnormal physiological arousal pattern known as hyperarousal, which may contribute to their depressive symptoms. However, the neurobiological mechanisms linking this abnormal arousal to depressive symptoms are not yet fully understood. In this review, we summarize the physiological and neural features of arousal, and review the literature indicating abnormal arousal in depressed patients. Evidence suggests that a hyperarousal state in depression is characterized by abnormalities in sleep behavior, physiological (e.g., heart rate, skin conductance, pupil diameter) and electroencephalography (EEG) features, and altered activity in subcortical (e.g., hypothalamus and locus coeruleus) and cortical regions. While recent studies highlight the importance of subcortical-cortical interactions in arousal, few have explored the relationship between subcortical-cortical interactions and hyperarousal in depressed patients. This gap limits our understanding of the neural mechanism through which hyperarousal affects depressive symptoms, which involves various cognitive processes and the cerebral cortex. Based on the current literature, we propose that the hyperconnectivity in the thalamocortical circuit may contribute to both the hyperarousal pattern and depressive symptoms. Future research should investigate the relationship between thalamocortical connections and abnormal arousal in depression, and explore its implications for non-invasive treatments for depression.

Invasive Neuromodulation Techniques for Treatment-Resistant Depression

Surgically implanted neurostimulation devices for the treatment of depression have been studied for the last three decades. While the surgical risk associated with these treatment approaches clearly limits their use to the most severely impacted depressed patients, they offer a unique opportunity to better understand the impact of relatively localized alteration of neural activity in patient groups. As a result, these approaches provide a strict test of the role of individual neural structures or networks in mechanistic models of depression. In this chapter, we review the proposed mechanisms of action and evidence for clinical efficacy of vagal nerve stimulation, deep brain stimulation, and epidural cortical stimulation in patients with depression. The evidence for efficacy remains limited for all three modalities, but the long-term follow-up studies of treated patients have highlighted the importance of interactions between neural regions in determining therapeutic response, and suggest that personalized approaches to stimulation are likely to be required.

Functional brain network features specify DBS outcome for patients with treatment resistant depression

Deep brain stimulation (DBS) has shown therapeutic benefits for treatment resistant depression (TRD). Stimulation of the subcallosal cingulate gyrus (SCG) aims to alter dysregulation between subcortical and cortex. However, the 50% response rates for SCG-DBS indicates that selection of appropriate patients is challenging. Since stimulation influences large-scale network function, we hypothesized that network features can be used as biomarkers to inform outcome. In this pilot project, we used resting-state EEG recorded longitudinally from 10 TRD patients with SCG-DBS (11 at baseline). EEGs were recorded before DBS-surgery, 1-3 months, and 6 months post surgery. We used graph theoretical analysis to calculate clustering coefficient, global efficiency, eigenvector centrality, energy, and entropy of source-localized EEG networks to determine their topological/dynamical features. Patients were classified as responders based on achieving a 50% or greater reduction in Hamilton Depression (HAM-D) scores from baseline to 12 months post surgery. In the delta band, false discovery rate analysis revealed that global brain network features (segregation, integration, synchronization, and complexity) were significantly lower and centrality of subgenual anterior cingulate cortex (ACC) was higher in responders than in non-responders. Accordingly, longitudinal analysis showed SCG-DBS increased global network features and decreased centrality of subgenual ACC. Similarly, a clustering method separated two groups by network features and significant correlations were identified longitudinally between network changes and depression symptoms. Despite recent speculation that certain subtypes of TRD are more likely to respond to DBS, in the SCG it seems that underlying brain network features are associated with ability to respond to DBS. SCG-DBS increased segregation, integration, and synchronizability of brain networks, suggesting that information processing became faster and more efficient, in those patients in whom it was lower at baseline. Centrality results suggest these changes may occur via altered connectivity in specific brain regions especially ACC. We highlight potential mechanisms of therapeutic effect for SCG-DBS.

Functional connectivity signatures of major depressive disorder: machine learning analysis of two multicenter neuroimaging studies

The promise of machine learning has fueled the hope for developing diagnostic tools for psychiatry. Initial studies showed high accuracy for the identification of major depressive disorder (MDD) with resting-state connectivity, but progress has been hampered by the absence of large datasets. Here we used regular machine learning and advanced deep learning algorithms to differentiate patients with MDD from healthy controls and identify neurophysiological signatures of depression in two of the largest resting-state datasets for MDD. We obtained resting-state functional magnetic resonance imaging data from the REST-meta-MDD (N = 2338) and PsyMRI (N = 1039) consortia. Classification of functional connectivity matrices was done using support vector machines (SVM) and graph convolutional neural networks (GCN), and performance was evaluated using 5-fold cross-validation. Features were visualized using GCN-Explainer, an ablation study and univariate t-testing. The results showed a mean classification accuracy of 61% for MDD versus controls. Mean accuracy for classifying (non-)medicated subgroups was 62%. Sex classification accuracy was substantially better across datasets (73-81%). Visualization of the results showed that classifications were driven by stronger thalamic connections in both datasets, while nearly all other connections were weaker with small univariate effect sizes. These results suggest that whole brain resting-state connectivity is a reliable though poor biomarker for MDD, presumably due to disease heterogeneity as further supported by the higher accuracy for sex classification using the same methods. Deep learning revealed thalamic hyperconnectivity as a prominent neurophysiological signature of depression in both multicenter studies, which may guide the development of biomarkers in future studies.

Personalized Definition of Surgical Targets in Major Depression and Obsessive-Compulsive Disorder: A Potential Role for Low-Intensity Focused Ultrasound?

Major Depressive Disorder (MDD) and Obsessive-Compulsive Disorder (OCD) are common and potentially incapacitating conditions. Even when recognized and adequately treated, in over a third of patients with these conditions the response to first-line pharmacological and psychotherapeutic measures is not satisfactory. After more assertive measures including pharmacological augmentation (and in the case of depression, transcranial magnetic stimulation, electroconvulsive therapy, or treatment with ketamine or esketamine), a significant number of individuals remain severely symptomatic. In these persons, different ablation and deep-brain stimulation (DBS) psychosurgical techniques have been employed. However, apart from the cost and potential morbidity associated with surgery, on average only about half of patients show adequate response, which limits the widespread application of these potentially life-saving interventions. Possible reasons are considered for the wide variation in outcomes across different series of patients with MDD or OCD exposed to ablative or DBS psychosurgery, including interindividual anatomical and etiological variability. Low-intensity focused ultrasound (LIFU) is an emerging technique that holds promise in its ability to achieve anatomically circumscribed, noninvasive, and reversible neuromodulation of deep brain structures. A possible role for LIFU in the personalized presurgical definition of neuromodulation targets in the individual patient is discussed, including a proposed roadmap for clinical trials addressed at testing whether this technique can help to improve psychosurgical outcomes.

Aberrant pattern of cerebral blood flow in patients with major depressive disorder: A meta-analysis of arterial spin labelling studies

BACKGROUND

Accumulating evidence has suggested that patients with major depressive disorder (MDD) could exhibit resting-state cerebral blood flow (CBF) abnormalities. However, findings across studies are controversial.

METHODS

Our study aimed at identifying replicable CBF changes in MDD by conducting a case-control meta-analysis and meta-regression of arterial spin labelling studies using seed-based d mapping software. Fourteen studies encompassing 505 patients with MDD and 443 healthy controls were included.

RESULTS

We found increased CBF in the inferior parietal lobule, the striatum, and the bilateral thalamus in all patients with MDD relative to healthy controls. While decreased CBF was observed in the inferior frontal gyrus, the insula, the middle occipital gyrus and the bilateral superior temporal gyrus in patients with MDD. Moreover, increased CBF of the bilateral thalamus was associated with more severe depressive symptoms in patients with MDD. The subgroup meta-analysis showed that patients with acute phase had increased CBF in the bilateral thalamus, and decreased CBF in the left middle occipital gyrus and the left middle frontal gyrus. Chronic patients had decreased CBF in the left insula, the right calcarine sulcus, the right inferior frontal gyrus, and the left parahippocampal gyrus. Patients with medication-free had increased CBF in the right anterior cingulate cortex/medial prefrontal cortex, and decreased CBF in the left middle occipital gyrus, the left inferior frontal gyrus, and the left precentral gyrus.

CONCLUSIONS

These findings suggest an aberrant cerebral blood flow pattern of MDD involving the cortico-striatal-thalamic circuit, which may facilitate understanding of pathophysiology and suggest potential neural biomarkers for clinical assessment, monitoring and interventions of MDD. One important limitation is that eight recruited studies in our meta-analysis have recruited more males than females, which may have a selection bias of patients.

Whole-Brain Functional Connectivity Dynamics Associated With Electroconvulsive Therapy Treatment Response

BACKGROUND

Depressive episodes (DEPs), characterized by abnormalities in cognitive functions and mood, are a leading cause of disability. Electroconvulsive therapy (ECT), which involves a brief electrical stimulation of the anesthetized brain, is one of the most effective treatments used in patients with DEP due to its rapid efficacy.

METHODS

In this work, we investigated how dynamic brain functional connectivity responds to ECT and whether the dynamic responses are associated with treatment outcomes and side effects in patients. We applied a fully automated independent component analysis-based pipeline to 110 patients with DEP (including diagnosis of unipolar depression or bipolar depression) and 60 healthy control subjects. The dynamic functional connectivity was analyzed by a combination of the sliding window approach and clustering analysis.

RESULTS

Five recurring connectivity states were identified, and patients with DEPs had fewer occurrences in one brain state (state 1) with strong positive and negative connectivity. Patients with DEP changed the occupancy of two states (states 3 and 4) after ECT, resulting in significantly different occurrences of one additional state (state 3) compared with healthy control subjects. We further found that patients with DEP had diminished global metastate dynamism, two of which recovered to normal after ECT. The changes in dynamic connectivity characteristics were associated with the changes in memory recall and Hamilton Depression Rating Scale of DEP after ECT.

CONCLUSIONS

These converging results extend current findings on subcortical-cortical dysfunction and dysrhythmia in DEP and demonstrate that ECT might cause remodeling of brain functional dynamics that enhance the neuroplasticity of the diseased brain.

DTI Connectometry Analysis Reveals White Matter Changes in Cognitively Impaired World Trade Center Responders at Midlife

BACKGROUND

More than 8% of responders who participated in the search and rescue efforts at the World Trade Center (WTC) following 9/11 developed early-onset cognitive impairment (CI). Approximately 23% were also diagnosed with chronic post-traumatic stress disorder (PTSD).

OBJECTIVE

To shed light on the pathophysiology of these WTC-related conditions, we examined diffusion connectometry to identify altered white matter tracts in WTC responders with CI and/or PTSD compared to unaffected responders.

METHODS

99 WTC responders (mean age 56 years) consisting of CI-/PTSD- (n = 27), CI+/PTSD- (n = 25), CI-/PTSD+ (n = 24), and CI+/PTSD+ (n = 23) were matched on age, sex, occupation, race, and education. Cognitive status was determined using the Montreal Cognitive Assessment and PTSD status was determined using the DSM-IV SCID. Diffusion tensor imaging was acquired on a 3T Siemens Biograph mMR scanner. Connectometry analysis was used to examine whole-brain tract-level differences in white matter integrity as reflected by fractional anisotropy (FA) values after adjusting for confounders.

RESULTS

Analyses identified that FA was negatively correlated with CI and PTSD status in the fornix, cingulum, forceps minor of the corpus callosum and the right uncinate fasciculus. Furthermore, FA was negatively correlated with PTSD status, regardless of CI status in the superior thalamic radiation and the cerebellum.

CONCLUSION

This is the first connectometry study to examine altered white matter tracts in a sample of WTC responders with CI and/or PTSD. Results from this study suggest that WTC responders with early-onset CI may be experiencing an early neurodegenerative process characterized by decreased FA in white matter tracts.

A New Way Forward: How Brain SPECT Imaging Can Improve Outcomes and Transform Mental Health Care Into Brain Health Care

In the past three decades, brain single-photon-emission-computed-tomography (SPECT) imaging has garnered a significant, evidence-based foundation for a wide array of indications relevant to the field of clinical psychiatry, including dementia, traumatic brain injuries, seizures, cerebrovascular disease, complex neuropsychiatric presentations, and treatment-resistant disorders. In clinical psychiatric practice, however, SPECT remains underutilized. Only a small percentage of psychiatric clinicians use brain imaging technology. In this article, the authors provide a rationale for shifting the paradigm to one that includes broader use of SPECT in the clinical psychiatric setting, primarily for patients with complex conditions. This paper will outline seven specific clinical applications. Adding neuroimaging tools like SPECT to day-to-day clinical practice can help move psychiatry forward by transforming mental health care, which can be stigmatizing and often shunned by the general public, to brain health care, which the authors argue will be more likely to be embraced by a larger group of people in need.

Neuronal correlates underlying the role of the zinc sensing receptor (GPR39) in passive-coping behaviour

The Zn²⁺ receptor GPR39 is proposed to be involved in the pathophysiology of depression. GPR39 knockout (KO) animals show depressive- and anxiety-like behaviour, and resistance to conventional monoamine-based antidepressants. However, it is unclear as to which brain regions are involved in the pro-depressive phenotype of GPR39KO mice and the resistance to monoamine-targeting antidepressant treatment. Our current study confirmed previous results, showing that mice lacking GPR39 display enhanced passive coping-like behaviour compared with their wild-type controls. Furthermore, this study shows for the first time that GPR39KO displayed aberrant challenge-induced neuronal activity in key brain regions associated with passive coping behaviour. Imipramine induced only a marginal reduction in the enhanced passive coping behaviour in GPR39KO mice, which was associated with attenuation of the hyperactive prefrontal cortex. Similarly, the aberrant activity within the amygdalar subregions was normalized following imipramine treatment in the GPR39KO mice, indicating that imipramine mediates these effects independently of GPR39 in the prefrontal cortex and amygdala. However, imipramine failed to modulate the aberrant brain activity in other brain regions, such as the anterior CA3 and the dentate gyrus, in GPR39KO mice. Normalization of aberrant activity in these areas has been shown previously to accompany successful behavioural effects of antidepressants. Taken together, our data suggest that monoamine-based antidepressants such as imipramine exert their action via GPR39-dependent and -independent pathways. Failure to modulate passive-coping related aberrant activity in important brain areas of the depression circuitry is proposed to mediate/contribute to the greatly reduced antidepressant action of monoamine-based antidepressants in GPR39KO mice.

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.

NMDAR Neurotransmission Needed for Persistent Neuronal Firing: Potential Roles in Mental Disorders

The dorsolateral prefrontal cortex (dlPFC) generates the mental representations that are the foundation of abstract thought, and provides top-down regulation of emotion through projections to the medial PFC and cingulate cortices. Physiological recordings from dlPFC Delay cells have shown that the generation of mental representations during working memory relies on NMDAR neurotransmission, with surprisingly little contribution from AMPAR. Systemic administration of low "antidepressant" doses of the NMDAR antagonist, ketamine, erodes these representations and reduces dlPFC Delay cell firing. In contrast to the dlPFC, V1 neuronal firing to visual stimuli depends on AMPAR, with much less contribution from NMDAR. Similarly, neurons in the dlPFC that respond to sensory events (cue cells, response feedback cells) rely on AMPAR, and systemic ketamine increases their firing. Insults to NMDAR transmission, and the impaired ability for dlPFC to generate mental representations, may contribute to cognitive deficits in schizophrenia, e.g., from genetic insults that weaken NMDAR transmission, or from blockade of NMDAR by kynurenic acid. Elevated levels of kynurenic acid in dlPFC may also contribute to cognitive deficits in other disorders with pronounced neuroinflammation (e.g., Alzheimer's disease), or peripheral infections where kynurenine can enter brain (e.g., delirium from sepsis, "brain fog" in COVID19). Much less is known about NMDAR actions in the primate cingulate cortices. However, NMDAR neurotransmission appears to process the affective and visceral responses to pain and other aversive experiences mediated by the cingulate cortices, which may contribute to sustained alterations in mood state. We hypothesize that the very rapid, antidepressant effects of intranasal ketamine may involve the disruption of NMDAR-generated aversive mood states by the anterior and subgenual cingulate cortices, providing a "foot in the door" to allow the subsequent return of top-down regulation by higher PFC areas. Thus, the detrimental vs. therapeutic effects of NMDAR blockade may be circuit dependent.

Advanced Imaging in Psychiatric Neurosurgery: Toward Personalized Treatment

OBJECTIVES

Our aim is to review several recent landmark studies discussing the application of advanced neuroimaging to guide target selection in deep brain stimulation (DBS) for psychiatric disorders.

MATERIALS AND METHODS

We performed a PubMed literature search of articles related to psychiatric neurosurgery, DBS, diffusion tensor imaging, probabilistic tractography, functional magnetic resonance imaging (MRI), and blood oxygen level-dependent activation. Relevant articles were included in the review.

RESULTS

Recent advances in neuroimaging, namely the use of diffusion tensor imaging, probabilistic tractography, functional MRI, and Positron emission tomography have provided higher resolution depictions of structural and functional connectivity between regions of interest. Applying these imaging modalities to DBS has increased understanding of the mechanism of action of DBS from the single structure to network level, allowed for new DBS targets to be discovered, and allowed for individualized DBS targeting for psychiatric indications.

CONCLUSIONS

Advanced neuroimaging techniques may be especially important to guide personalized DBS targeting in psychiatric disorders such as treatment-resistant depression and obsessive-compulsive disorder where symptom profiles and underlying disordered circuitry are more heterogeneous. These articles suggest that advanced imaging can help to further individualize and optimize DBS, a promising next step in improving its efficacy.

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.

Variability of white matter anatomy in the subcallosal cingulate area

The subcallosal cingulate (SCC) area is a putative hub in the brain network underlying depression. Deep brain stimulation (DBS) targeting a particular subregion of SCC, identified as the intersection of forceps minor (FM), uncinate fasciculus (UCF), cingulum and fronto-striatal fiber bundles, may be critical to a therapeutic response in patients with severe, treatment-resistant forms of major depressive disorder (MDD). The pattern and variability of the white matter anatomy and organization within SCC has not been extensively characterized across individuals. The goal of this study is to investigate the variability of white matter bundles within the SCC that structurally connect this region with critical nodes in the depression network. Structural and diffusion data from 100 healthy subjects from the Human Connectome Project database were analyzed. Anatomically defined SCC regions were used as seeds to perform probabilistic tractography and to estimate the connectivity from the SCC to subject-specific target areas believed to be involved in the pathology of MDD including ventral striatum (VS), UCF, anterior cingulate cortex (ACC), and medial prefrontal cortex (mPFC). Four distinct areas of connectivity were identified within SCC across subjects: (a) postero-lateral SCC connectivity to medial temporal regions via UCF, (b) postero-medial connectivity to VS, (c) superior-medial connectivity to ACC via cingulum bundle, and (d) antero-lateral connectivity to mPFC regions via forceps minor. Assuming white matter connectivity is critical to therapeutic response, the improved anatomic understanding of SCC as well as an appreciation of the intersubject variability are critical to developing optimized therapeutic targeting for SCC DBS.

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.

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.

Minimally Invasive Bilateral Anterior Cingulotomy via Open Minicraniotomy Using a Novel Multiport Cisternoscope: A Cadaveric Demonstration

BACKGROUND

Bilateral anterior cingulotomy has been used to treat chronic pain, obsessive compulsive disorder, and addictions. Lesioning of the target area is typically performed using bilateral stereotactic electrode placement and target ablation, which involves transparenchymal access through both hemispheres.

OBJECTIVE

To evaluate an endoscopic direct-vision lesioning using a unilateral parasagittal minicraniotomy for minimally invasive bilateral anterior cingulotomy using a novel multiport endoscope through the anterior interhemispheric fissure.

METHODS

A novel multiport magnetic resonance imaging (MRI)-compatible neuroendoscope prototype is used to demonstrate cadaveric cingulate lesioning through a lateral imaging port while simultaneously viewing the pericallosal arteries as landmarks through a tip imaging port. The lateral port enables extended lesioning of the gyrus while rotation of the endoscope about its axis provides access to homologous areas of both hemispheres.

RESULTS

Cadaver testing confirmed the capability to navigate the multiport neuroendoscope between the hemispheres using concurrent imaging from the tip and lateral ports. The lateral port enabled exploration of the gyrus, visualization of lesioning, and subsequent inspection of lesions. Tip-port imaging provided navigational cues and allowed the operator to ensure that the endoscope tip did not contact tissue. The multiport design required instrument rotation in the coronal plane of only 20° to lesion both gyri, while a standard endoscope necessitated a rotation of 54°.

CONCLUSION

Multiport MRI-compatible endoscopy can be effectively used in cisternal endoscopy, whereby a unilateral parasagittal minicraniotomy can be used for endoscopic interhemispheric bilateral anterior cingulotomy.

Functional Connectivity of the Anterior Cingulate Cortex in Depression and in Health

The first voxel-level resting-state functional connectivity (FC) neuroimaging analysis of depression of the anterior cingulate cortex (ACC) showed in 282 patients with major depressive disorder compared with 254 controls, some higher, and some lower FCs. However, in 125 unmedicated patients, primarily increases of FC were found: of the subcallosal anterior cingulate with the lateral orbitofrontal cortex, of the pregenual/supracallosal anterior cingulate with the medial orbitofrontal cortex, and of parts of the anterior cingulate with the inferior frontal gyrus, superior parietal lobule, and with early cortical visual areas. In the 157 medicated patients, these and other FCs were lower than in the unmedicated group. Parcellation was performed based on the FC of individual ACC voxels in healthy controls. A pregenual subdivision had high FC with medial orbitofrontal cortex areas, and a supracallosal subdivision had high FC with lateral orbitofrontal cortex and inferior frontal gyrus. The high FC in depression between the lateral orbitofrontal cortex and the subcallosal parts of the ACC provides a mechanism for more non-reward information transmission to the ACC, contributing to depression. The high FC between the medial orbitofrontal cortex and supracallosal ACC in depression may also contribute to depressive symptoms.

The relationship between sleep efficiency and clinical symptoms is mediated by brain function in major depressive disorder

BACKGROUND

Sleep disturbance is a common and key symptom that affects most of patients with major depressive disorder (MDD). However, neural substrates underlying sleep disturbance and their clinical relevance in depression remain unclear.

METHODS

Ninety-six MDD patients underwent resting-state functional MRI. Fractional amplitude of low-frequency fluctuation (fALFF) and resting-state functional connectivity (rsFC) were used to measure brain function. Overnight polysomnography was performed to objectively measure sleep efficiency (SE), which was used to classify patients into normal sleep efficiency (NSE) and low sleep efficiency (LSE) groups. Between-group differences in fALFF and rsFC were examined using two-sample t-tests. Moreover, correlation and mediation analyses were conducted to test for potential associations between SE, brain functional changes, and clinical variables.

RESULTS

LSE group showed decreased fALFF in right cuneus, thalamus, and middle temporal gyrus compared to NSE group. MDD patients with low SE also exhibited lower rsFC of right cuneus to right lateral temporal cortex, which was associated with more severe depression and anxiety symptoms. More importantly, mediation analyses revealed that the relationships between SE and severity of depression and anxiety symptoms were significantly mediated by the altered rsFC. In addition, these low SE-related brain functional alterations were not affected by antidepressant medication and were independent of structural changes.

LIMITATIONS

The lack of healthy controls because of "first-night effect".

CONCLUSION

These findings not only may expand existing knowledge about neuropathology of sleep disturbance in depression, but also may inform real-world clinical practice by improving depression and anxiety symptoms through sleep regulation.

Individualized Connectome-Targeted Transcranial Magnetic Stimulation for Neuropsychiatric Sequelae of Repetitive Traumatic Brain Injury in a Retired NFL Player

OBJECTIVE

The recent advent of individualized resting-state network mapping (RSNM) has revealed substantial interindividual variability in anatomical localization of brain networks identified by using resting-state functional MRI (rsfMRI). RSNM enables personalized targeting of focal neuromodulation techniques such as repetitive transcranial magnetic stimulation (rTMS). rTMS is believed to exert antidepressant efficacy by modulating connectivity between the stimulation site, the default mode network (DMN), and the subgenual anterior cingulate cortex (sgACC). Personalized rTMS may be particularly useful after repetitive traumatic brain injury (TBI), which is associated with neurodegenerative tauopathy in medial temporal limbic structures. These degenerative changes are believed to be related to treatment-resistant neurobehavioral disturbances observed in many retired athletes.

METHODS

The authors describe a case in which RSNM was successfully used to target rTMS to treat these neuropsychiatric disturbances in a retired NFL defensive lineman whose symptoms were not responsive to conventional treatments. RSNM was used to identify left-right dorsolateral prefrontal rTMS targets with maximal difference between dorsal attention network and DMN correlations. These targets were spatially distinct from those identified by prior methods. Twenty sessions of left-sided excitatory and right-sided inhibitory rTMS were administered at these targets.

RESULTS

Treatment led to improvement in Montgomery-Åsberg Depression Rating Scale (72%), cognitive testing, and headache scales scores. Compared with healthy individuals and subjects with TBI-associated depression, baseline rsfMRI revealed substantially elevated DMN connectivity with the medial temporal lobe (MTL). Serial rsfMRI scans revealed gradual improvement in MTL-DMN connectivity and stimulation site connectivity with sgACC.

CONCLUSIONS

These results highlight the possibility of individualized neuromodulation and biomarker-based monitoring for neuropsychiatric sequelae of repetitive TBI.

Altered directed functional connectivity of the right amygdala in depression: high-density EEG study

The cortico-striatal-pallidal-thalamic and limbic circuits are suggested to play a crucial role in the pathophysiology of depression. Stimulation of deep brain targets might improve symptoms in treatment-resistant depression. However, a better understanding of connectivity properties of deep brain structures potentially implicated in deep brain stimulation (DBS) treatment is needed. Using high-density EEG, we explored the directed functional connectivity at rest in 25 healthy subjects and 26 patients with moderate to severe depression within the bipolar affective disorder, depressive episode, and recurrent depressive disorder. We computed the Partial Directed Coherence on the source EEG signals focusing on the amygdala, anterior cingulate, putamen, pallidum, caudate, and thalamus. The global efficiency for the whole brain and the local efficiency, clustering coefficient, outflow, and strength for the selected structures were calculated. In the right amygdala, all the network metrics were significantly higher (p < 0.001) in patients than in controls. The global efficiency was significantly higher (p < 0.05) in patients than in controls, showed no correlation with status of depression, but decreased with increasing medication intake (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${{\bf{R}}}^{{\bf{2}}}{\boldsymbol{=}}{\bf{0.59}}\,{\bf{and}}\,{\bf{p}}{\boldsymbol{=}}{\bf{1.52}}{\bf{e}}{\boldsymbol{ \mbox{-} }}{\bf{05}}$$\end{document}R2=0.59andp=1.52e‐05). The amygdala seems to play an important role in neurobiology of depression. Practical treatment studies would be necessary to assess the amygdala as a potential future DBS target for treating depression.

A preliminary study of resting brain metabolism in treatment-resistant depression before and after treatment with olanzapine-fluoxetine combination

Treatment-resistant depression (TRD) occurs in many patients and causes high morbidity and mortality. Because TRD subjects are particularly difficult to study especially longitudinally, biological data remain very limited. In a preliminary study to judge feasibility and power, 25 TRD patients were referred from specialty psychiatric practices. All were severely and chronically depressed and mostly had comorbid psychiatric disorders as is typical in TRD. Nine patients were able to complete all required components of the protocol that included diagnostic interview; rating scales; clinical magnetic resonance imaging; medication washout; treatment with maximally tolerated olanzapine-fluoxetine combination for 8 weeks; and pre- and post-treatment fluorodeoxyglucose positron emission tomography. This drug combination is an accepted standard of treatment for TRD. Dropouts arose from worsening depression, insomnia, and anxiety. One patient remitted; three responded. A priori regions of interest included the amygdala and subgenual cingulate cortex (sgACC; Brodmann area BA25). Responders showed decreased metabolism with treatment in the right amygdala that correlated with clinical response; no significant changes in BA25; better response to treatment the higher the baseline BA25 metabolism; and decreased right ventromedial prefrontal metabolism (VMPFC; broader than BA25) with treatment which did not correlate with depression scores. The baseline metabolism of all individuals showed heterogeneous patterns when compared to a normative metabolic database. Although preliminary given the sample size, this study highlights several issues important for future work: marked dropout rate in this study design; need for large sample size for adequate power; baseline metabolic heterogeneity of TRD requiring careful subject characterization for future studies of interventions; relationship of amygdala activity decreases with response; and the relationship between baseline sgACC and VMPFC activity with response. Successful treatment of TRD with olanzapine-fluoxetine combination shows changes in cerebral metabolism like those seen in treatment-responsive major depression.

Spatial and temporal joint, partially-joint and individual sources in independent component analysis: Application to social brain fMRI dataset

absectionBackground Three types of sources can be considered in the analysis of multi-subject datasets: (i) joint sources which are common among all subjects, (ii) partially-joint sources which are common only among a subset of subjects, and (iii) individual sources which belong to each subject and represent the specific conditions of that subject. Extracting spatial and temporal joint, partially-joint, and individual sources of multi-subject datasets is of significant importance to analyze common and cross information of multiple subjects.

NEW METHOD

We present a new framework to extract these three types of spatial and temporal sources in multi-subject functional magnetic resonance imaging (fMRI) datasets. In this framework, temporal and spatial independent component analysis are utilized, and a weighted sum of higher-order cumulants is maximized.

RESULTS

We evaluate the presented algorithm by analyzing simulated data and one real multi-subject fMRI dataset. Our results on the real dataset are consistent with the existing meta-analysis studies. We show that spatial and temporal jointness of extracted joint and partially-joint sources in the theory of mind regions of brain increase with the age of subjects.

COMPARISON WITH EXISTING METHOD

In Richardson et al. (2018), predefined regions of interest (ROI) have been used to analyze the real dataset, whereas our unified algorithm simultaneously extracts activated and uncorrelated ROIs, and determines their spatial and temporal jointness without additional computations.

CONCLUSIONS

Extracting temporal and spatial joint and partially-joint sources in a unified algorithm improves the accuracy of joint analysis of the multi-subject fMRI dataset.

Functional Neuroimaging in Psychiatry-Aiding in Diagnosis and Guiding Treatment. What the American Psychiatric Association Does Not Know

While early efforts in psychiatry were focused on uncovering the neurobiological basis of psychiatric symptoms, they made little progress due to limited ability to observe the living brain. Today, we know a great deal about the workings of the brain; yet, none of this neurobiological awareness has translated into the practice of psychiatry. The categorical system which dominates psychiatric diagnosis and thinking fails to match up to the real world of genetics, sophisticated psychological testing, and neuroimaging. Nevertheless, the American Psychiatric Association (APA) recently published a position paper stating that neuroimaging provided no benefit to the diagnosis and treatment of psychiatric disorders. Using the diagnosis of depression as a model, we illustrate how setting aside the unrealistic expectation of a pathognomonic "fingerprint" for categorical diagnoses, we can avoid missing the biological and, therefore, treatable contributors to psychopathology which can and are visualized using functional neuroimaging. Infection, toxicity, inflammation, gut-brain dysregulation, and traumatic brain injury can all induce psychiatric manifestations which masquerade as depression and other psychiatric disorders. We review these and provide illustrative clinical examples. We further describe situations for which single photon emission computed tomography (SPECT) and positron emission tomography (PET) functional neuroimaging already meet or exceed the criteria set forth by the APA to define a neuroimaging biomarker, including the differential diagnosis of Alzheimer's disease and other dementias, the differential diagnosis of ADHD, and the evaluation of traumatic brain injury. The limitations, both real and perceived, of SPECT and PET functional neuroimaging in the field of psychiatry are also elaborated. An important overarching concept for diagnostic imaging in all its forms, including functional neuroimaging, is that imaging allows a clinician to eliminate possibilities, narrow the differential diagnosis, and tailor the treatment plan. This progression is central to any medical diagnostic process.

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.

Thalamic volume, resting-state activity, and their association with the efficacy of electroconvulsive therapy

Electroconvulsive therapy (ECT) is the most effective antidepressant treatment. Biological predictors of clinical outcome to ECT are valuable. We aimed to examine multimodal magnetic resonance imaging (MRI) data that correlates to the efficacy of ECT. Structural and resting-state functional MRI data were acquired from 46 individuals (25 depressed individuals who received ECT, and 21 healthy controls). Whole-brain grey matter volume (GMV) and fractional amplitude of low frequency fluctuations (fALFF) were investigated to identify brain regions associated with post-ECT Hamilton Depression Rating Scale (HAM-D) total scores. GMV and fALFF values were compared with those in healthy controls using analysis of covariance (ANCOVA). Remission was defined by HAM-D ≤7. A multiple regression analysis revealed that pretreatment smaller GMV in the left thalamus was associated with worse response to ECT (i.e. higher post-ECT HAM-D). Pretreatment higher fALFF in the right anterior insula, and lower fALFF in the left thalamus and the cerebellum were associated with worse outcomes. The left thalamus was identified in both GMV and fALFF analyses. Nonremitters showed significantly smaller thalamic GMV compared to remitters and controls. We found that pretreatment thalamic volume and resting-state activity were associated with the efficacy of ECT. Our results highlight the importance of the thalamus as a possible biological predictor and its role in the underlying mechanisms of ECT action.

Repetitive Transcranial Magnetic Stimulation with Resting-State Network Targeting for Treatment-Resistant Depression in Traumatic Brain Injury: A Randomized, Controlled, Double-Blinded Pilot Study

Repetitive transcranial magnetic stimulation (rTMS) has demonstrated antidepressant efficacy but has limited evidence in depression associated with traumatic brain injury (TBI). Here, we investigate the use of rTMS targeted with individualized resting-state network mapping (RSNM) of dorsal attention network (DAN) and default mode network (DMN) in subjects with treatment-resistant depression associated with concussive or moderate TBI. The planned sample size was 50 with first interim analysis planned at 20, but only 15 were enrolled before the study was terminated for logistical reasons. Subjects were randomized to 20 sessions of bilateral rTMS (4000 left-sided excitatory pulses, 1000 right-sided inhibitory pulses) or sham. Treatment was targeted to the dorsolateral prefrontal cluster with maximal difference between DAN and DMN correlations based on resting-state functional magnetic resonance imaging with individualized RSNM. Mean improvement in the primary outcome, Montgomery-Asberg Depression Rating Scale (MADRS), was 56% ± 14% (n = 9) with active treatment and 27% ± 25% (n = 5) with sham (Cohen's d = 1.43). One subject randomized to sham withdrew before starting treatment. There were no seizures or other significant adverse events. MADRS improvement was inversely correlated with functional connectivity between the right-sided stimulation site and the subgenual anterior cingulate cortex (sgACC; r = -0.68, 95% confidence interval 0.03-0.925). Active treatment led to increased sgACC-DMN connectivity (d = 1.55) and increased sgACC anti-correlation with the left- and right-sided stimulation sites (d = -1.26 and -0.69, respectively). This pilot study provides evidence that RSNM-targeted rTMS is feasible in TBI patients with depression. Given the dearth of existing evidence-based treatments for depression in this patient population, these preliminarily encouraging results indicate that larger controlled trials are warranted.

Resting state functional connectivity predictors of treatment response to electroconvulsive therapy in depression

There is increasing focus on use of resting-state functional connectivity (RSFC) analyses to subtype depression and to predict treatment response. To date, identification of RSFC patterns associated with response to electroconvulsive therapy (ECT) remain limited, and focused on interactions between dorsal prefrontal and regions of the limbic or default-mode networks. Deficits in visual processing are reported in depression, however, RSFC with or within the visual network have not been explored in recent models of depression. Here, we support prior studies showing in a sample of 18 patients with depression that connectivity between dorsal prefrontal and regions of the limbic and default-mode networks serves as a significant predictor. In addition, however, we demonstrate that including visual connectivity measures greatly increases predictive power of the RSFC algorithm (>80% accuracy of remission). These exploratory results encourage further investigation into visual dysfunction in depression, and use of RSFC algorithms incorporating the visual network in prediction of response to both ECT and transcranial magnetic stimulation (TMS), offering a new framework for the development of RSFC-guided TMS interventions in depression.

Deep brain stimulation targets for treating depression

Deep brain stimulation (DBS) is a new therapeutic approach for treatment-resistant depression (TRD). There is a preliminary evidence of the efficacy and safety of DBS for TRD in the subgenual anterior cingulate cortex, the ventral capsule/ventral striatum, the nucleus accumbens, the lateral habenula, the inferior thalamic peduncle, the medial forebrain bundle, and the bed nucleus of the stria terminalis. Optimal stimulation targets, however, have not yet been determined. Here we provide updated knowledge substantiating the suitability of each of the current and potential future DBS targets for treating depression. In this review, we discuss the future outlook for DBS treatment of depression in light of the fact that antidepressant effects of DBS can be achieved using different targets.

The cingulum bundle: Anatomy, function, and dysfunction

The cingulum bundle is a prominent white matter tract that interconnects frontal, parietal, and medial temporal sites, while also linking subcortical nuclei to the cingulate gyrus. Despite its apparent continuity, the cingulum's composition continually changes as fibres join and leave the bundle. To help understand its complex structure, this review begins with detailed, comparative descriptions of the multiple connections comprising the cingulum bundle. Next, the impact of cingulum bundle damage in rats, monkeys, and humans is analysed. Despite causing extensive anatomical disconnections, cingulum bundle lesions typically produce only mild deficits, highlighting the importance of parallel pathways and the distributed nature of its various functions. Meanwhile, non-invasive imaging implicates the cingulum bundle in executive control, emotion, pain (dorsal cingulum), and episodic memory (parahippocampal cingulum), while clinical studies reveal cingulum abnormalities in numerous conditions, including schizophrenia, depression, post-traumatic stress disorder, obsessive compulsive disorder, autism spectrum disorder, Mild Cognitive Impairment, and Alzheimer's disease. Understanding the seemingly diverse contributions of the cingulum will require better ways of isolating pathways within this highly complex tract.

Charting the road forward in psychiatric neurosurgery: proceedings of the 2016 American Society for Stereotactic and Functional Neurosurgery workshop on neuromodulation for psychiatric disorders

OBJECTIVE

Refractory psychiatric disease is a major cause of morbidity and mortality worldwide, and there is a great need for new treatments. In the last decade, investigators piloted novel deep brain stimulation (DBS)-based therapies for depression and obsessive-compulsive disorder (OCD). Results from recent pivotal trials of these therapies, however, did not demonstrate the degree of efficacy expected from previous smaller trials. To discuss next steps, neurosurgeons, neurologists, psychiatrists and representatives from industry convened a workshop sponsored by the American Society for Stereotactic and Functional Neurosurgery in Chicago, Illinois, in June of 2016.

DESIGN

Here we summarise the proceedings of the workshop. Participants discussed a number of issues of importance to the community. First, we discussed how to interpret results from the recent pivotal trials of DBS for OCD and depression. We then reviewed what can be learnt from lesions and closed-loop neurostimulation. Subsequently, representatives from the National Institutes of Health, the Food and Drug Administration and industry discussed their views on neuromodulation for psychiatric disorders. In particular, these third parties discussed their criteria for moving forward with new trials. Finally, we discussed the best way of confirming safety and efficacy of these therapies, including registries and clinical trial design. We close by discussing next steps in the journey to new neuromodulatory therapies for these devastating illnesses.

CONCLUSION

Interest and motivation remain strong for deep brain stimulation for psychiatric disease. Progress will require coordinated efforts by all stakeholders.

Prospective Validation That Subgenual Connectivity Predicts Antidepressant Efficacy of Transcranial Magnetic Stimulation Sites

BACKGROUND

The optimal target in the dorsolateral prefrontal cortex for treating depression with repetitive transcranial magnetic stimulation (rTMS) remains unknown. Better efficacy has been associated with stimulation sites that are 1) more anterior and lateral and 2) more functionally connected to the subgenual cingulate. Here we prospectively test whether these factors predict response in individual patients.

METHODS

A primary cohort (Boston, n = 25) with medication-refractory depression underwent conventional open-label rTMS to the left dorsolateral prefrontal cortex. A secondary cohort (Michigan, n = 16) underwent 4 weeks of sham followed by open-label rTMS for nonresponders (n = 12). In each patient, the location of the stimulation site was recorded with frameless stereotaxy. Connectivity between each patient's stimulation site and the subgenual cingulate was assessed using resting-state functional connectivity magnetic resonance imaging from a cohort of healthy subjects (n = 1000) and confirmed using connectivity from patients with depression (n = 38).

RESULTS

In our primary cohort, antidepressant efficacy was predicted by stimulation sites that were both more anterolateral (r = .51, p < .01) and more negatively correlated with the subgenual cingulate (r = -.55, p < .005). However, subgenual connectivity was the only independent predictor of response and the only factor to predict response to active (r = -.52, p < .05) but not sham rTMS in our secondary cohort.

CONCLUSIONS

This study provides prospective validation that functional connectivity between an individual's rTMS cortical target and the subgenual cingulate predicts antidepressant response. Implications for improving the cortical rTMS target for depression are discussed.

Initial Unilateral Exposure to Deep Brain Stimulation in Treatment-Resistant Depression Patients Alters Spectral Power in the Subcallosal Cingulate

Background: High-frequency Deep Brain Stimulation (DBS) of the subcallosal cingulate (SCC) region is an emerging strategy for treatment-resistant depression (TRD). This study examined changes in SCC local field potentials (LFPs). The LFPs were recorded from the DBS leads following transient, unilateral stimulation at the neuroimaging-defined optimal electrode contact. The goal was identifying a putative electrophysiological measure of target engagement during implantation. Methods: Fourteen consecutive patients underwent bilateral SCC DBS lead implantation. LFP recordings were collected from all electrodes during randomized testing of stimulation on each DBS contact (eight total). Analyses evaluated changes in spectral power before and after 3 min of unilateral stimulation at the contacts that later facilitated antidepressant response, as a potential biomarker of optimal contact selection in each hemisphere. Results: Lateralized and asymmetric power spectral density changes were detected in the SCC with acute unilateral SCC stimulation at those contacts subsequently selected for chronic, therapeutic stimulation. Left stimulation induced broadband ipsilateral decreases in theta, alpha, beta and gamma bands. Right stimulation effects were restricted to ipsilateral beta and gamma decreases. These asymmetric effects contrasted with identical white matter stimulation maps used in each hemisphere. More variable ipsilateral decreases were seen with stimulation at the adjacent "suboptimal" contacts, but changes were not statistically different from the "optimal" contact in either hemisphere despite obvious differences in impacted white matter bundles. Change in theta power was, however, most robust and specific with left-sided optimal stimulation, which suggested a putative functional biomarker on the left with no such specificity inferred on the right. Conclusion: Hemisphere-specific oscillatory changes can be detected from the DBS lead with acute intraoperative testing at contacts that later engender antidepressant effects. Our approach defined potential target engagement signals for further investigation, particularly left-sided theta decreases following initial exposure to stimulation. More refined models combining tractography, bilateral SCC LFP, and cortical recordings may further improve the precision and specificity of these putative biomarkers. It may also optimize and standardize the lead implantation procedure and provide input signals for next generation closed-loop therapy and/or monitoring technologies for TRD.

Can we increase the speed and efficacy of antidepressant treatments? Part II. Glutamatergic and RNA interference strategies

In the second part we focus on two treatment strategies that may overcome the main limitations of current antidepressant drugs. First, we review the experimental and clinical evidence supporting the use of glutamatergic drugs as fast-acting antidepressants. Secondly, we review the involvement of microRNAs (miRNAs) in the pathophysiology of major depressive disorder (MDD) and the use of small RNAs (e.g.., small interfering RNAs or siRNAs) to knockdown genes in monoaminergic and non-monoaminergic neurons and induce antidepressant-like responses in experimental animals. The development of glutamatergic agents is a promising venue for antidepressant drug development, given the antidepressant properties of the non-competitive NMDA receptor antagonist ketamine. Its unique properties appear to result from the activation of AMPA receptors by a metabolite [(2S,6S;2R,6R)-hydroxynorketamine (HNK)] and mTOR signaling. These effects increase synaptogenesis in prefrontal cortical pyramidal neurons and enhance serotonergic neurotransmission via descending inputs to the raphe nuclei. This view is supported by the cancellation of ketamine's antidepressant-like effects by inhibition of serotonin synthesis. We also review existing evidence supporting the involvement of miRNAs in MDD and the preclinical use of RNA interference (RNAi) strategies to target genes involved in antidepressant response. Many miRNAs have been associated to MDD, some of which e.g., miR-135 targets genes involved in antidepressant actions. Likewise, SSRI-conjugated siRNA evokes faster and/or more effective antidepressant-like responses. Intranasal application of sertraline-conjugated siRNAs directed to 5-HT_1A receptors and SERT evoked much faster changes of pre- and postsynaptic antidepressant markers than those produced by fluoxetine.

A Computational Model of Major Depression: the Role of Glutamate Dysfunction on Cingulo-Frontal Network Dynamics

Major depression disease (MDD) is associated with the dysfunction of multinode brain networks. However, converging evidence implicates the reciprocal interaction between midline limbic regions (typified by the ventral anterior cingulate cortex, vACC) and the dorso-lateral prefrontal cortex (dlPFC), reflecting interactions between emotions and cognition. Furthermore, growing evidence suggests a role for abnormal glutamate metabolism in the vACC, while serotonergic treatments (selective serotonin reuptake inhibitor, SSRI) effective for many patients implicate the serotonin system. Currently, no mechanistic framework describes how network dynamics, glutamate, and serotonin interact to explain MDD symptoms and treatments. Here, we built a biophysical computational model of 2 areas (vACC and dlPFC) that can switch between emotional and cognitive processing. MDD networks were simulated by slowing glutamate decay in vACC and demonstrated sustained vACC activation. This hyperactivity was not suppressed by concurrent dlPFC activation and interfered with expected dlPFC responses to cognitive signals, mimicking cognitive dysfunction seen in MDD. Simulation of clinical treatments (SSRI or deep brain stimulation) counteracted this aberrant vACC activity. Theta and beta/gamma oscillations correlated with network function, representing markers of switch-like operation in the network. The model shows how glutamate dysregulation can cause aberrant brain dynamics, respond to treatments, and be reflected in EEG rhythms as biomarkers of MDD.

From Engrams to Pathologies of the Brain

Memories are the experiential threads that tie our past to the present. The biological realization of a memory is termed an engram—the enduring biochemical and physiological processes that enable learning and retrieval. The past decade has witnessed an explosion of engram research that suggests we are closing in on boundary conditions for what qualifies as the physical manifestation of memory. In this review, we provide a brief history of engram research, followed by an overview of the many rodent models available to probe memory with intersectional strategies that have yielded unprecedented spatial and temporal resolution over defined sets of cells. We then discuss the limitations and controversies surrounding engram research and subsequently attempt to reconcile many of these views both with data and by proposing a conceptual shift in the strategies utilized to study memory. We finally bridge this literature with human memory research and disorders of the brain and end by providing an experimental blueprint for future engram studies in mammals. Collectively, we believe that we are in an era of neuroscience where engram research has transitioned from ephemeral and philosophical concepts to provisional, tractable, experimental frameworks for studying the cellular, circuit and behavioral manifestations of memory.

Glial GLT-1 blockade in infralimbic cortex as a new strategy to evoke rapid antidepressant-like effects in rats

Ketamine and deep brain stimulation produce rapid antidepressant effects in humans and rodents. An increased AMPA receptor (AMPA-R) signaling in medial prefrontal cortex (mPFC) has been suggested to mediate these responses. However, little research has addressed the direct effects of enhancing glutamate tone or AMPA-R stimulation in mPFC subdivisions. The current study investigates the behavioral and neurochemical consequences of glutamate transporter-1 (GLT-1) blockade or s-AMPA microinfusion in the infralimbic (IL) and prelimbic (PrL) cortex. Owing to the connectivity between the mPFC and raphe nuclei, the role of serotonin is also explored. The bilateral microinfusion of the depolarizing agent veratridine into IL -but not PrL- of rats evoked immediate antidepressant-like responses. The same regional selectivity was observed after microinfusion of dihydrokainic acid (DHK), a selective inhibitor of GLT-1, present in astrocytes. The DHK-evoked antidepressant-like responses appear to be mediated by an AMPA-R-driven enhancement of serotonergic activity, as (i) they were prevented by NBQX 2,3-dioxo-6-nitro-1,2,3,4-tetrahydrobenzo[f]quinoxaline-7-sulfonamide disodium salt) and mimicked by s-AMPA; (ii) DHK and s-AMPA elevated similarly extracellular glutamate in IL and PrL, although extracellular 5-HT and c-fos expression in the midbrain dorsal raphe increased only when these agents were applied in IL; and (iii) DHK antidepressant-like responses were prevented by 5-HT synthesis inhibition and mimicked by citalopram microinfusion in IL. These results indicate that an acute increase of glutamatergic neurotransmission selectively in IL triggers immediate antidepressant-like responses in rats, likely mediated by the activation of IL-raphe pathways, which then results in a fast increase of serotonergic activity.

Disappearance of treatment-resistant depression after damage to the orbitofrontal cortex and subgenual cingulate area: a case study

Background

Although post-stroke depression is a well-characterized disorder, there is less understanding of how pre-existence of depression is affected by a stroke.

Case presentation

We describe a patient with treatment-resistant major depression, which had been ongoing for 14 years but disappeared shortly after onset of a subarachnoid hemorrhage. Her cognitive function and functional status were mostly unaffected by the stroke. However, she no longer excessively regretted past events. Lesions were found in the orbitofrontal cortex, which is involved in feeling regret, and in the adjacent subgenual cingulate area, which is metabolically hyperactive in treatment-resistant depression and is the target for deep-brain stimulation for relief of treatment-resistant depression. The lesions from the stroke may have caused the disappearance of the patient’s treatment-resistant depression by alleviating excessive regret and decreasing the elevated activity in these areas.

Conclusions

This patient’s clinical course may shed light on the neuropsychological and neurophysiological mechanisms of major depression of the melancholic subtype.

Activation of AMPA Receptors Mediates the Antidepressant Action of Deep Brain Stimulation of the Infralimbic Prefrontal Cortex

Although deep brain stimulation (DBS) has been used with success in treatment-resistant depression, little is known about its mechanism of action. We examined the antidepressant-like activity of short (1 h) DBS applied to the infralimbic prefrontal cortex in the forced swim test (FST) and the novelty-suppressed feeding test (NSFT). We also used in vivo microdialysis to evaluate the release of glutamate, γ-aminobutyric acid, serotonin, dopamine, and noradrenaline in the prefrontal cortex and c-Fos immunohistochemistry to determine the brain regions activated by DBS. One hour of DBS of the infralimbic prefrontal cortex has antidepressant-like effects in FST and NSFT, and increases prefrontal efflux of glutamate, which would activate AMPA receptors (AMPARs). This effect is specific of the infralimbic area since it is not observed after DBS of the prelimbic subregion. The activation of prefrontal AMPARs would result in a stimulation of prefrontal output to the brainstem, thus increasing serotonin, dopamine, and noradrenaline in the prefrontal cortex. Further, the activation of prefrontal AMPARs is necessary and sufficient condition for the antidepressant response of 1 h DBS.

Biophysical changes in subcortical nuclei: the impact of diabetes and major depression

Magnetization transfer (MT) is a neuroimaging technique that is frequently used to characterize the biophysical abnormalities in both gray and white matter regions of the brain. In our study, we used MT to examine the integrity of key nodes in frontal-subcortical circuits in four subject groups: patients diagnosed with type 2 diabetes with and without major depression (MDD), a healthy control group, and a group diagnosed with MDD without diabetes. In the MDD group, MT studies demonstrated lower magnetization transfer ratios (MTR), a marker of abnormalities in the macromolecular protein pool, in the thalami when compared with the control groups. The group with diabetes and MDD showed lower MTR in the globus pallidus when compared with the group with MDD. Biophysical measures, in subcortical nuclei, correlated inversely with measures of glycemic control, cerebrovascular burden and depression scores. These findings have broad implications for the underlying neuronal circuitry and neurobiology of mood disorders.

Neuroimaging-based biomarkers for treatment selection in major depressive disorder

The use of neuroimaging approaches to identify likely treatment outcomes in patients with major depressive disorder is developing rapidly. Emerging work suggests that resting state pretreatment metabolic activity in the fronto-insular cortex may distinguish between patients likely to respond to psychotherapy or medication and may function as a treatment-selection biomarker. In contrast, high metabolic activity in the subgenual anterior cingulate cortex may be predictive of poor outcomes to both medication and psychotherapy, suggesting that nonstandard treatments may be pursued earlier in the treatment course. Although these findings will require replication before clinical adoption, they provide preliminary support for the concept that brain states can be measured and applied to the selection of a specific treatment most likely to be beneficial for an individual patient.

Repetition-Related Reductions in Neural Activity during Emotional Simulations of Future Events

Simulations of future experiences are often emotionally arousing, and the tendency to repeatedly simulate negative future outcomes has been identified as a predictor of the onset of symptoms of anxiety. Nonetheless, next to nothing is known about how the healthy human brain processes repeated simulations of emotional future events. In this study, we present a paradigm that can be used to study repeated simulations of the emotional future in a manner that overcomes phenomenological confounds between positive and negative events. The results show that pulvinar nucleus and orbitofrontal cortex respectively demonstrate selective reductions in neural activity in response to frequently as compared to infrequently repeated simulations of negative and positive future events. Implications for research on repeated simulations of the emotional future in both non-clinical and clinical populations are discussed.

Frontal and rostral anterior cingulate (rACC) theta EEG in depression: implications for treatment outcome?

In major depressive disorder (MDD), elevated theta current density in the rostral anterior cingulate (rACC), as estimated by source localization of scalp-recorded electroencenphalogram (EEG), has been associated with response to antidepressant treatments, whereas elevated frontal theta has been linked to non-response. This study used source localization to attempt to integrate these apparently opposite results and test, whether antidepressant response is associated with elevated rACC theta and non-response with elevated frontal theta and whether theta activity is a differential predictor of response to different types of commonly used antidepressants. In the international Study to Predict Optimized Treatment in Depression (iSPOT-D), a multi-center, international, randomized, prospective practical trial, 1008 MDD participants were randomized to escitalopram, sertraline or venlafaxine-XR. The study also recruited 336 healthy controls. Treatment response and remission were established after eight weeks using the 17-item Hamilton Rating Scale for Depression (HRSD17). The resting-state EEG was assessed at baseline with eyes closed and source localization (eLORETA) was employed to extract theta from the rACC and frontal cortex. Patients with MDD had elevated theta in both frontal cortex and rACC, with small effect sizes. High frontal and rACC theta were associated with treatment non-response, but not with non-remission, and this effect was most pronounced in a subgroup with previous treatment failures. Low theta in frontal cortex and rACC are found in responders to antidepressant treatments with a small effect size. Future studies should investigate in more detail the role of previous treatment (failure) in the association between theta and treatment outcome.