Right and left amygdalae activation in patients with major depression receiving antidepressant treatment, as revealed by fMRI

Amygdala biomarkers of treatment response in major depressive disorder: An fMRI systematic review of SSRI antidepressants

Functional neuroimaging studies have demonstrated abnormal activity and functional connectivity (FC) of the amygdala among individuals with major depressive disorder (MDD), which may be rectified with selective serotonin reuptake inhibitor (SSRI) treatment. This systematic review aimed to identify changes in the amygdala on functional magnetic resonance imaging (fMRI) scans among individuals with MDD who received SSRIs. A search for fMRI studies examining amygdala correlates of SSRI response via fMRI was conducted through OVID (MEDLINE, PsycINFO, and Embase). The end date was April 4th, 2023. In total, 623 records were screened, and 16 studies were included in this review. While the search pertained to SSRIs broadly, the included studies were escitalopram-, citalopram-, fluoxetine-, sertraline-, and paroxetine-specific. Decreases in event-related amygdala activity were found following 6-to-12-week SSRI treatment, particularly in response to negative stimuli. Eight-week courses of SSRI pharmacotherapy were associated with increased event-related amygdala FC (i.e., with the prefrontal [PFC] and anterior cingulate cortices, insula, thalamus, caudate nucleus, and putamen) and decreased resting-state effective connectivity (i.e., amygdala-PFC). Preliminary evidence suggests that SSRIs may alter amygdala activity and FC in MDD. Additional studies are needed to corroborate findings. Future research should employ long-term follow-ups to determine whether effects persist after treatment termination.

Review: The use of functional magnetic resonance imaging (fMRI) in clinical trials and experimental research studies for depression

Functional magnetic resonance imaging (fMRI) is a non-invasive technique that can be used to examine neural responses with and without the use of a functional task. Indeed, fMRI has been used in clinical trials and pharmacological research studies. In mental health, it has been used to identify brain areas linked to specific symptoms but also has the potential to help identify possible treatment targets. Despite fMRI's many advantages, such findings are rarely the primary outcome measure in clinical trials or research studies. This article reviews fMRI studies in depression that sought to assess the efficacy and mechanism of action of compounds with antidepressant effects. Our search results focused on selective serotonin reuptake inhibitors (SSRIs), the most commonly prescribed treatments for depression and ketamine, a fast-acting antidepressant treatment. Normalization of amygdala hyperactivity in response to negative emotional stimuli was found to underlie successful treatment response to SSRIs as well as ketamine, indicating a potential common pathway for both conventional and fast-acting antidepressants. Ketamine's rapid antidepressant effects make it a particularly useful compound for studying depression with fMRI; its effects on brain activity and connectivity trended toward normalizing the increases and decreases in brain activity and connectivity associated with depression. These findings highlight the considerable promise of fMRI as a tool for identifying treatment targets in depression. However, additional studies with improved methodology and study design are needed before fMRI findings can be translated into meaningful clinical trial outcomes.

Structural covariance network of the hippocampus-amygdala complex in medication-naïve patients with first-episode major depressive disorder

Background

The hippocampus and amygdala are densely interconnected structures that work together in multiple affective and cognitive processes that are important to the etiology of major depressive disorder (MDD). Each of these structures consists of several heterogeneous subfields. We aim to explore the topologic properties of the volume-based intrinsic network within the hippocampus-amygdala complex in medication-naïve patients with first-episode MDD.

Methods

High-resolution T1-weighted magnetic resonance imaging scans were acquired from 123 first-episode, medication-naïve, and noncomorbid MDD patients and 81 age-, sex-, and education level-matched healthy control participants (HCs). The structural covariance network (SCN) was constructed for each group using the volumes of the hippocampal subfields and amygdala subregions; the weights of the edges were defined by the partial correlation coefficients between each pair of subfields/subregions, controlled for age, sex, education level, and intracranial volume. The global and nodal graph metrics were calculated and compared between groups.

Results

Compared with HCs, the SCN within the hippocampus-amygdala complex in patients with MDD showed a shortened mean characteristic path length, reduced modularity, and reduced small-worldness index. At the nodal level, the left hippocampal tail showed increased measures of centrality, segregation, and integration, while nodes in the left amygdala showed decreased measures of centrality, segregation, and integration in patients with MDD compared with HCs.

Conclusion

Our results provide the first evidence of atypical topologic characteristics within the hippocampus-amygdala complex in patients with MDD using structure network analysis. It provides more delineate mechanism of those two structures that underlying neuropathologic process in MDD.

Utilization of passive visual perception task indetecting patients with major depressive disorder for active health

Depression is a common emotional and mental disease. At present, doctors' diagnosis mainly depends on the existing evaluation scales and their accumulated experience, lack of objective electrophysiological quantitative evaluation indicators. This study explores the difference in event-related potential (ERP) between patients with depression and healthy controls under the stimulation of multi-dimensional tasks, extracts the characteristic data, and uses a t-test for statistical analysis to provide an objective evaluation index for the clinical diagnosis of depression. Ninety-nine patients in the major depression group (MDD) and thirty patients in the healthy control group (HC) were used to compare the responses to positive, negative, and neutral stimulation, the results showed that there were significant differences between the left and right occipital lobes and one frontal lobe, and the frontal lobe showed lateralization; There were significant differences between the depression group and the healthy control group under multi-dimensional stimulation (P < 0.01), and the depression patients were significantly lower than the healthy patients. The results showed that emotional information was processed differently in patients with depression in the early stages of visual face processing. Therefore, EEG indices could be used as an objective index for the early detection of depression. Moreover, according to the instructions before the test, the subject is only asked to recognize visual pictures instead report emotional feelings. Stigma about psychiatric disorders could thus be reduced in this way. The explorations above facilitate designing more accurate and implicit active mental health techniques.

Increased occurrence of PTSD symptoms in adolescents with major depressive disorder soon after the start of the COVID-19 outbreak in China: a cross-sectional survey

BACKGROUND

The Coronavirus Disease 2019 (COVID-19) pandemic continues to threaten the physical and mental health of people across the world. This study aimed to understand the psychological impact of this disease on adolescents with major depressive disorder (MDD) at 1 month after the start of the outbreak in China.

METHODS

Using the Children's Impact of Event Scale (CRIES-13) questionnaire, we investigated the occurrence of posttraumatic stress disorder (PTSD) in two groups of adolescents: MDD patients who were in continuous antidepressant therapy and healthy controls. Total scores and factor subscores were compared between the two groups and subgroups stratified by sex and school grade. Logistic regression was used to identify variables associated with high total CRIES-13 scores.

RESULTS

Compared to controls (n = 107), the MDD group (n = 90) had higher total CRIES-13 scores and a higher proportion with a total score ≥ 30. They also had a lower intrusion subscore and a higher arousal subscore. In the MDD group, males and females did not differ significantly in total CRIES-13 scores or factor subscores, but junior high school students had higher avoidance subscores than senior high school students. Logistic regression showed high total CRIES-13 scores to be associated with MDD and the experience of "flashbacks" or avoidance of traumatic memories associated with COVID-19.

CONCLUSIONS

It is crucial to understand the psychological impact of COVID-19 on adolescents with MDD in China, especially females and junior high school students. Long-term monitoring of adolescents with a history of mental illness is required to further understand these impacts.

TRIAL REGISTRATION

ChiCTR, ChiCTR2000033402 , Registered 31 May 2020.

Effects of negativity bias on amygdala and anterior cingulate cortex activity in short and long emotional stimulation paradigms

Recent functional studies have reported that amygdala and anterior cingulate cortex (ACC) dysfunction is a reproducible and good biomarker of major depressive disorder. When we use the activation of these regions as biomarkers of major depressive disorder, a short and simple stimulation paradigm could be preferable to reduce the burden on patients. However, negativity bias, which is the phenomenon by which negative stimuli are processed noticeably faster than positive stimuli, might affect the activation of these regions in the short and simple stimulation paradigm. Few studies have reported the relationship between the length of the stimulation paradigm and activation in the amygdala and ACC from the viewpoint of negativity bias. The purpose of this study was to assess the effects of negativity bias on the amygdala and ACC as a result of manipulating the stimulation paradigm (short-simple vs. long-complex conditions) on presenting pleasant and unpleasant pictures. Image analyses showed that the amygdala was activated during unpleasant picture presentation, regardless of the task length, but no activation was observed during pleasant picture presentation under the short-simple condition. The ACC was deactivated in both the short-simple and long-complex conditions. Region of interest analyses showed that the effect of negativity bias was prominent for the amygdala in the short-simple condition and for the ACC in the long-complex condition. In conclusion, the effects of negativity bias depend on neural regions, including the amygdala and ACC, and therefore, we should consider these effects while designing stimulation paradigms.

Differences in cytokines between patients with generalised anxiety disorder and panic disorder

OBJECTIVE

The purpose of this study was to evaluate the differences among panic disorder (PD), generalised anxiety disorder (GAD) and controls in inflammatory cytokines. We also analysed the correlation between inflammatory cytokines and response to escitalopram in PD and GAD patients.

METHODS

Eighty-six patients with PD, 86 patients with GAD and 86 healthy controls were recruited for this study. All participants were, respectively, assessed for severity of anxiety and panic symptoms using the Hamilton Anxiety Rating Scale (HAMA) and the Panic Disorder Severity Scale (PDSS); all patients in the study were also assessed after 4 weeks of treatment. The serum levels of cytokines were measured using a flow fluorescence microsphere assay.

RESULTS

Both PD and GAD patients had higher serum levels of interleukin 6 (IL-6) than controls, and patients with PD showed significantly higher IL-6 than GAD patients. Significant positive correlations were found between the IFN-γ levels and the severity of anxiety in GAD patients. Higher level of IL-6 was associated with better response to escitalopram treatment in PD patients. However, the baseline levels of cytokines were not associated with treatment responses in GAD patients.

CONCLUSION

The present findings suggest that patients with PD may have higher levels of IL-6 than GAD, and higher baseline levels of IL-6 may be a better response to escitalopram in the treatment of PD.

A systematic review of the impact of social cognitive deficits on psychosocial functioning in major depressive disorder and opportunities for therapeutic intervention

Social cognition is the ability to identify, perceive and interpret socially relevant information from the external world. It is an important adaptive trait, but is frequently affected in major depressive disorder by a mood-congruent interpretive bias. The present review examined the existing body of literature to determine (i) the impact social cognitive deficits in depression have on psychosocial functioning; and (ii) the utility of psychotropic, psychological and procedural interventions employed to target these deficits. A total of 107 studies met inclusion criteria for review. Social cognitive performance was found to adversely impact depressed patients' psychosocial functioning across the key domains of general cognitive functioning and quality of life. Secondly, many current therapies were found to have a normalising effect on the social cognitive abilities of subjects with major depressive disorder, both at a neural and functional level. In particular, certain anti-depressant medications corrected facial affect recognition deficits, while several psychotherapeutic approaches improved impairments in theory of mind and negative interpretive bias.

Interactive effect of 5-HTTLPR and BDNF polymorphisms on amygdala intrinsic functional connectivity and anxiety

The serotonin transporter (5-HTTLPR) and brain-derived neurotrophic factor (BDNF) gene polymorphisms have been associated with risk for affective disorders and functional variability of the amygdala. We examined whether the two genotypes interactively influence intrinsic functional connectivity (FC) of the amygdala and whether FC mediates the genetic association with anxiety. Eighty genotyped healthy adults underwent resting state fMRI and completed the self-reported State-Trait Anxiety Inventory. Interactive genetic association with anxiety was observed such that effects of 5-HTTLPR depended on the BDNF Val66Met polymorphism (rs6265 variant), with higher anxiety scores in short and Met carriers compared to the other allelic groups. Voxel-wise FC with left and right amygdala seeds identified regions that were sensitive to variability in anxiety scores. A significant moderated mediation model demonstrated that the effect of 5-HTTLPR genotype on anxiety, moderated by BDNF Val66Met genotype, was fully mediated by FC between the left amygdala and the right dorsolateral prefrontal cortex, a cognitive control-related region, during a task-free state. FC was highest in carriers of the 5-HTTLPR short allele and BDNF Met allele. These findings establish intrinsic amygdala-prefrontal functional connectivity as a potential intermediate phenotype for anxiety, an important step toward identification of causal pathways for vulnerability to affective disorders.

Cortical thickness in major depressive disorder: A systematic review and meta-analysis

Neuroimaging studies assessing neurobiological differences between patients with major depressive disorder (MDD) and healthy controls (HC) are often hindered by small sample sizes and heterogeneity of the patient sample. We performed a comprehensive literature search for studies assessing cortical thickness between patient and control groups, including studies investigating treatment effects on cortical thickness. We identified 34 studies meeting criteria for the systematic review and used Seed-based d Mapping to meta-analyze 24 of those that met additional criteria. Analysis of the full sample of subjects (MDD = 1073; HC = 936) revealed significant thinning in the MDD group in the bilateral orbitofrontal gyrus (BA 11), left pars opercularis (BA 45) and left calcarine fissure/lingual gyrus (BA 17), as well as an area of significant thickening in the left supramarginal gyrus (BA 40). These results support other imaging modalities that report disruptions in various frontal and temporal areas in MDD and identify additional areas in all major cerebral lobes likely to be significant when parsing for biomarkers of treatment or relapse.

Significant Decrease in Hippocampus and Amygdala Mean Diffusivity in Treatment-Resistant Depression Patients Who Respond to Electroconvulsive Therapy

Introduction: The hippocampus plays a key role in depressive disorder, and the amygdala is involved in depressive disorder through the key role that it plays in emotional regulation. Electroconvulsive therapy (ECT) may alter the microstructure of these two regions. Since mean diffusivity (MD), is known to be an indirect marker of microstructural integrity and can be derived from diffusion tensor imaging (DTI) scans, we aim to test the hypothesis that treatment-resistant depression (TRD) patients undergoing bilateral (BL) ECT exhibit a decrease of MD in their hippocampus and amygdala. Methods: Patients, between 50 and 70 years of age, diagnosed with TRD were recruited from the University Hospital of Toulouse and assessed clinically (Hamilton Depression Rating Scale, HAM-D) and by DTI scans at three time points: baseline, V2 (during treatment), and V3 within 1 week of completing ECT. Results: We included 15 patients, who were all responders. The left and right hippocampi and the left amygdala showed a significant decrease in MD at V3, compared to baseline [respectively: β = -2.78, t = -1.97, p = 0.04; β = -2.56, t = -2, p = 0.04; β = -2.5, t = -2.3, p = 0.04, false discovery rate (FDR) corrected]. MD did not decrease in the right amygdala. Only the left amygdala was significantly associated with a reduction in HAM-D (ρ = 0.55, p = 0.049, FDR corrected). Conclusion: MD is an indirect microstructural integrity marker, which decreases in the hippocampus and the left amygdala, during BL ECT in TRD populations. This could be interpreted as a normalization of microstructural integrity in these structures.

Neurotrophic factors and neuroplasticity pathways in the pathophysiology and treatment of depression

Depression is a major health problem with a high prevalence and a heavy socioeconomic burden in western societies. It is associated with atrophy and impaired functioning of cortico-limbic regions involved in mood and emotion regulation. It has been suggested that alterations in neurotrophins underlie impaired neuroplasticity, which may be causally related to the development and course of depression. Accordingly, mounting evidence suggests that antidepressant treatment may exert its beneficial effects by enhancing trophic signaling on neuronal and synaptic plasticity. However, current antidepressants still show a delayed onset of action, as well as lack of efficacy. Hence, a deeper understanding of the molecular and cellular mechanisms involved in the pathophysiology of depression, as well as in the action of antidepressants, might provide further insight to drive the development of novel fast-acting and more effective therapies. Here, we summarize the current literature on the involvement of neurotrophic factors in the pathophysiology and treatment of depression. Further, we advocate that future development of antidepressants should be based on the neurotrophin theory.

Machine-Learning Classifier for Patients with Major Depressive Disorder: Multifeature Approach Based on a High-Order Minimum Spanning Tree Functional Brain Network

High-order functional connectivity networks are rich in time information that can reflect dynamic changes in functional connectivity between brain regions. Accordingly, such networks are widely used to classify brain diseases. However, traditional methods for processing high-order functional connectivity networks generally include the clustering method, which reduces data dimensionality. As a result, such networks cannot be effectively interpreted in the context of neurology. Additionally, due to the large scale of high-order functional connectivity networks, it can be computationally very expensive to use complex network or graph theory to calculate certain topological properties. Here, we propose a novel method of generating a high-order minimum spanning tree functional connectivity network. This method increases the neurological significance of the high-order functional connectivity network, reduces network computing consumption, and produces a network scale that is conducive to subsequent network analysis. To ensure the quality of the topological information in the network structure, we used frequent subgraph mining technology to capture the discriminative subnetworks as features and combined this with quantifiable local network features. Then we applied a multikernel learning technique to the corresponding selected features to obtain the final classification results. We evaluated our proposed method using a data set containing 38 patients with major depressive disorder and 28 healthy controls. The experimental results showed a classification accuracy of up to 97.54%.

The facial expression of schizophrenic patients applied with infrared thermal facial image sequence

BACKGROUND

Schizophrenia is a neurological disease characterized by alterations to patients' cognitive functions and emotional expressions. Relevant studies often use magnetic resonance imaging (MRI) of the brain to explore structural differences and responsiveness within brain regions. However, as this technique is expensive and commonly induces claustrophobia, it is frequently refused by patients. Thus, this study used non-contact infrared thermal facial images (ITFIs) to analyze facial temperature changes evoked by different emotions in moderately and markedly ill schizophrenia patients.

METHODS

Schizophrenia is an emotion-related disorder, and images eliciting different types of emotions were selected from the international affective picture system (IAPS) and presented to subjects during ITFI collection. ITFIs were aligned using affine registration, and the changes induced by small irregular head movements were corrected. The average temperatures from the forehead, nose, mouth, left cheek, and right cheek were calculated, and continuous temperature changes were used as features. After performing dimensionality reduction and noise removal using the component analysis method, multivariate analysis of variance and the Support Vector Machine (SVM) classification algorithm were used to identify moderately and markedly ill schizophrenia patients.

RESULTS

Analysis of five facial areas indicated significant temperature changes in the forehead and nose upon exposure to various emotional stimuli and in the right cheek upon evocation of high valence low arousal (HVLA) stimuli. The most significant P-value (lower than 0.001) was obtained in the forehead area upon evocation of disgust. Finally, when the features of forehead temperature changes in response to low valence high arousal (LVHA) were reduced to 9 using dimensionality reduction and noise removal, the identification rate was as high as 94.3%.

CONCLUSIONS

Our results show that features obtained in the forehead, nose, and right cheek significantly differed between moderately and markedly ill schizophrenia patients. We then chose the features that most effectively distinguish between moderately and markedly ill schizophrenia patients using the SVM. These results demonstrate that the ITFI analysis protocol proposed in this study can effectively provide reference information regarding the phase of the disease in patients with schizophrenia.

A Correlative Classification Study of Schizophrenic Patients with Results of Clinical Evaluation and Structural Magnetic Resonance Images

Patients with schizophrenia suffer from symptoms such as hallucination and delusion. There are currently a number of publications that discuss the treatment, diagnosis, prognosis, and damage in schizophrenia. This study utilized joint independent component analysis to process the images of GMV and WMV and incorporated the Wisconsin card sorting test (WCST) and the positive and negative syndrome scale (PANSS) to examine the correlation of obtained brain characteristics. We also used PANSS score to classify schizophrenic patients into acute and subacute cases, to analyze the brain structure differences. Finally, we used brain structure images and the error rate of the WCST as eigenvalues in support vector machine learning and classification. The results of this study showed that the frontal and temporal lobes of a normal brain are more apparent than those of a schizophrenia brain. The highest level of classification recognition reached 91.575%, indicating that the WCST error rate and characteristic changes in brain structure volume can be used to effectively distinguish schizophrenia and normal brains. Similarly, this result confirmed that the WCST and brain structure volume are correlated with the differences between schizophrenia and normal participants.

Clinical neuroimaging markers of response to treatment in mood disorders

Mood disorders (MD) are important and frequent psychiatric illness. The management of patients affected by these conditions represents an important factor of disability as well as a significant social and economic burden. The "in-vivo" studies can help researchers to understand the first developmental events of the pathology and to identify the molecular and non-molecular targets of therapies. However, they have strong limitations due to the fact that human brain circuitry can not be reproduced in animal models. In addition, these neural pathways are difficult to be selectively studied with the modern imaging (such as Magnetic Resonance and Positron Emitted Tomography/Computed Tomography) and non-imaging (such as electroencephalography, magnetoencephalography, transcranial magnetic stimulation and evoked potentials) methods. In comparison with other methods, the "in-vivo" imaging investigations have higher temporal and spatial resolution compared to the "in-vivo" non-imaging techniques. All these factors make difficult to fully understand the aetiology and pathophysiology of these disorders, and consequently hinder the analysis of the effects of pharmacological and non-pharmacological therapies, which have been demonstrated effective in clinical settings. In this review, we will focus our attention on the current state of the art of imaging in the assessment of treatment efficacy in MD. We will analyse briefly the actual classification of MD; then we will focus on the "in vivo" imaging methods used in research and clinical activity, the current knowledge about the neural models at the base of MD. Finally the last part of the review will focus on the analysis of the main markers of response to treatment.