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The chapter opens by exploring different perspectives on defining mental disorders, contrasting Freudian psychoanalytic views with the diagnostic criteria of the DSM and newer alternative frameworks for understanding mental health. It then critiques early modular models of emotion, such as Papez’s circuit and the limbic system, which attempt to localize emotions to specific brain regions but fail to comprehensively explain diverse emotions and their complex manifestations in behavior. The chapter concludes by evaluating the value and limitations of brain stimulation for treating depression, with a focus on modern experiments involving deep-brain stimulation.
Low heart rate variability (HRV) levels may be a susceptibility factor for major depressive disorder (MDD). Sleep-state HRV may be more likely to reveal the pathological features of MDD compared with resting state HRV (RS-HRV). This study aimed to elucidate HRV alterations in the sleep states of patients with MDD.
Methods:
Physiological signal data from the resting state before sleep, first non-rapid eye movement (NREM) and rapid eye movement (REM) stages, and last NREM and REM stages were acquired using polysomnography.
Results:
The RS-HRV indices (the standard deviation [SD] of all normal-to-normal [NN] intervals [SDNN], the square root of the mean of the sum of the squares of the differences between adjacent NN intervals [RMSSD], the percentage difference between adjacent NN intervals >50 ms [pNN50], high-frequency [HF], low-frequency [LF], very low frequency [VLF], SD1, and sample entropy [SampEn]) were lower in patients with MDD than in healthy controls (HCs). Patients with MDD had lower SDNN, RMSSD, pNN50, HF, LF, VLF, SD1, SD2, and SampEn and higher SD2/SD1, α1, and α2 than HCs in the NREM stage. They also had lower SDNN, RMSSD, pNN50, HF, LF, VLF, SD1, SD2, and SampEn and higher LF/HF than HCs in the REM stage. Fewer indices changed significantly during different sleep stages in patients with MDD than in HCs.
Conclusions:
Patients with MDD had a generalized reduction in HRV in both RS and sleep state and decreased dynamic changes during sleep. Altered autonomic nervous system activity has been implicated in MDD pathology.
Major depressive disorder (MDD) is the leading cause of disability worldwide, affecting roughly 322 million people. Recently, doses of psilocybin have shown promise in treating mood disorders, sparking interest in other dosing practices. According to anecdotal reports and observational studies, microdosing psilocybin yields benefits to mental health; however, rigorously controlled trials have failed to produce compelling evidence for this.
Aims
To conduct a phase II, double-blind, placebo-controlled, randomised partial crossover trial to compare microdosing psilocybin to placebo for MDD, evaluating its safety, tolerability and preliminary antidepressant effects.
Method
Forty adults with MDD will be randomised to four doses of psilocybin (2 mg) or placebo (maltodextrin) once weekly over 4 weeks, then four doses of psilocybin (2 mg) once weekly for an additional 4 weeks. The primary efficacy end-point will be change in depression symptoms, as measured at baseline (0 weeks), after the experimental phase (4 weeks), and after the open-label phase (8 weeks). A battery of mood, well-being, attention, creativity, mindfulness and pro-sociality measures will be administered at each time point. Follow-ups will occur every 6 months for up to 2 years after the trial start date, as part of a long-term extension study.
Results
The results of the primary outcome of this trial will be published as a manuscript in a peer-reviewed science or medical journal regardless of the magnitude or direction of effect.
Conclusions
Findings will inform future research on microdosing psilocybin for MDD, regarding dose regimens, effect sizes and expectancy bias. Findings will also facilitate discussions on the comparable benefits of sub- versus threshold doses of psilocybin and the therapeutic value of radically altered perception.
Cognitive and behavioral symptoms of major depressive disorder (MDD) are linked to aberrant changes in the controllability of brain networks. However, previous studies examined network controllability using white matter tractography, neglecting the contributions of gray matter. We aimed to examine differences in the controllability of morphometric networks between patients with MDD and demographic-matched healthy controls and identify the associated neurobiological signatures.
Methods
Based on the structural and diffusion MRI data from two independent cohorts, we calculated the controllability of morphometric similarity networks for each participant. A generalized additive model was used to investigate the case–control differences in regional controllability and their cognitive and behavioral associations. We investigated the associations between imaging-derived controllability and neurotransmitters, brain metabolism, and gene transcription profiles using multivariate linear regression and partial least squares regression analyses.
Results
In both cohorts, depression-related abnormalities of morphometric network controllability were primarily located in the prefrontal, cingulate, and visual cortices, contributing to memory, sensation, and perception processes. These abnormalities in network controllability were spatially aligned with the distributions of serotonergic transmission pathways as well as with altered oxygen and glucose metabolism. In addition, these abnormalities spatially overlapped with differentially expressed genes enriched in annotations related to protein catabolism and mitochondria in neuronal cells and were disproportionately located on chromosome 22.
Conclusions
Collectively, neuroimaging evidence revealed aberrant morphometric network controllability underlying MDD-related cognitive and behavioral deficits, and the associated genetic and molecular signatures may help identify the neurobiological mechanisms underlying MDD and provide feasible therapeutic targets.
Growing studies have reported an elevated risk of violence in patients with depression, yet the neurobiological underpinnings remain poorly understood. The present study explored the resting-state electroencephalogram (EEG) features in major depressive disorder (MDD) patients with violent offenses to identify potential neurological markers for violence prediction and intervention.
Methods
Twenty-nine MDD patients who committed violent offenses (violent depression [VD] group), 27 MDD patients without violent behaviors (nonviolent depression [NVD] group), and 25 healthy controls (HCs) were included. Resting-state EEGs were recorded for at least 5 min. EEG microstates, functional connectivity (FC), and graph theory metrics were analyzed and compared between groups.
Results
First, the VD group had increased microstate A, more microstates A-B transition, but lower microstates B-D and C-D transition. Second, the VD group exhibited two enhanced functional brain networks compared to NVD and HCs, and three weakened functional brain networks compared to HCs, which were primarily distributed in the frontal and frontoparietal networks. Third, the VD group specifically exhibited reduced nodal efficiency (aNe) in the superior parietal lobe and increased aNe in the middle occipital gyrus.
Conclusions
MDD patients with violent offenses exhibited alterations in EEG microstates, FCs in the frontal lobe and frontoparietal network, and disrupted aNe in specific parietal and occipital lobes. These alternations are closely associated with deficits in emotional regulation, executive function, and inhibitory control, which may subserve as potential neurobiomarkers for violence risk assessment in patients with depression.
Anhedonia is a multidimensional concept, and it is not known which aspects of it are linked to the heterogeneity of treatment responses in major depressive disorder (MDD). We examine the role of anhedonia dimensions in predicting response to antidepressant medication and adjunctive pharmacotherapy.
Methods
In CAN-BIND-1, 187 adults with MDD completed the Dimensional Anhedonia Rating Scale (DARS) and the Snaith–Hamilton Pleasure Scale (SHAPS) before undergoing 8 weeks of treatment with escitalopram. At week 8, 90 nonresponders received adjunctive treatment with aripiprazole for an additional 8 weeks. Mixed-effects models tested the hobbies, food, social, and sensory subscales and items of DARS and SHAPS as predictors of change in the Montgomery-Åsberg Depression Rating Scale (MADRS).
Results
Of the four DARS subscales, sensory anhedonia predicted a worse treatment outcome with escitalopram (b = 1.14, 95%CI 0.08 to 2.20, p = 0.034) as did a three-item SHAPS sensory anhedonia subscale (b = 1.50, 95%CI 0.43 to 2.57, p = 0.006). A combined DARS–SHAPS sensory anhedonia subscale complemented the previously reported interest–activity symptom dimension to improve treatment outcome prediction. In contrast, food and social anhedonia dimensions predicted worse outcomes with adjunctive aripiprazole (b = 2.52, 95%CI 1.25 to 3.80, p < 0.001; b = 2.56, 95%CI 1.16 to 3.96, p < 0.001). Corresponding SHAPS items showed similar results.
Conclusions
The inability to enjoy sensory experiences and the lack of interest in food and social activities distinctly predict outcomes with serotonergic versus dopaminergic pharmacotherapy. These findings require replication and extension to other treatments.
Antidepressants are the primary treatment for major depressive disorder (MDD), yet their precise neurobiological mechanisms remain incompletely understood. This study aimed to elucidate neural differences between medicated and unmedicated MDD patients by analyzing resting-state functional magnetic resonance imaging data.
Methods
We conducted a coordinate-based meta-analysis, complemented by behavioral, genetic, and neurotransmitter-level evaluations to identify potential therapeutic targets and diagnostic biomarkers. Using seed-based d-mapping with permutation of subject images (SDM-PSI), we assessed brain activation changes associated with antidepressant treatment. The identified regions were further characterized using large-scale molecular and functional brain databases.
Results
A total of 59 studies on unmedicated MDD (2,618 patients, 2,486 controls) and 15 studies on medicated MDD (541 patients, 483 controls) were included. The meta-analysis revealed significantly increased activation in the left striatum among medicated patients, a region linked to cognitive functions such as memory and perception. Gene expression analysis highlighted SLC5A7 and prolactin (PRL) as key genes in this region, while neurotransmitter mapping showed associations with serotonin (5-HT1a, 5-HT2a) and dopamine (D1, D2) receptors. Additionally, reduced activation in the left middle occipital gyrus (MOG) was observed across both medicated and unmedicated groups. This region, implicated in recognition and face processing, showed high expression of TFAP2B and PRL and was associated with serotonin and norepinephrine transporter distributions.
Conclusions
These findings suggest that the left striatum may represent a core neurofunctional target of antidepressant treatment, while the left MOG may serve as a stable neurobiological marker for MDD diagnosis, independent of pharmacological status.
Cognitive impairment in major depressive disorder (MDD) may be driven by neuro-inflammatory processes involving pro-inflammatory cytokines.
Aims
This study aimed to examine the relationship between serum tumour necrosis factor-alpha (TNF-α) levels and cognitive performance across different domains in individuals with MDD.
Method
Sixty patients with MDD and 60 healthy controls were recruited. Cognitive function was assessed using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), and serum TNF-α levels were measured via flow cytometry.
Results
After adjusting for covariates, RBANS total and subscale scores were significantly lower in MDD patients compared with controls (P < 0.001), while log10-transformed TNF-α levels were significantly higher in the MDD group (P = 0.006). In MDD patients, log10TNF-α levels were inversely correlated with immediate memory scores after adjusting for confounding factors (r = −0.35, P = 0.009); however, this relationship was not observed in healthy controls (r = −0.02, P = 0.90). Stepwise multivariate regression analysis further confirmed the negative association of log10TNF-α with immediate memory scores in MDD patients (β = −14.58, t = −4.14, P < 0.001), but not in healthy controls (β = −0.02, t = −0.14, P = 0.89).
Conclusions
These findings suggest that elevated serum TNF-α may contribute to the pathophysiology of MDD and is specifically associated with deficits in immediate memory.
Mitochondrial dysfunction has been implicated in the pathogenesis of major depressive disorder (MDD); however, the causal contributions of specific mitochondrial genes across regulatory layers remain unclear.
Methods
We integrated genome-wide association study summary statistics from the Psychiatric Genomics Consortium and FinnGen with quantitative-trait-locus (QTL) datasets for DNA methylation, gene expression (eQTL), and protein abundance. Mitochondrial genes were annotated using the MitoCarta3.0 database. Summary-based Mendelian randomization and Bayesian colocalization were applied to assess causal relationships, with colocalization determined by the posterior probability of a shared causal variant (PPH4), and the false discovery rate used for multiple-testing correction. Brain-specific effects were evaluated using Genotype-Tissue Expression eQTL data. Prioritized genes were ranked based on cross-omics consistency and replication evidence.
Results
Five mitochondrial genes were prioritized. TDRKH showed consistent associations across methylation, transcription, and protein levels, with hypermethylation at cg24503712 linked to reduced expression and a lower risk of MDD (Tier 1). METAP1D (Tier 2) demonstrated protective effects at both the transcript and protein levels. LONP1, FIS1, and SCP2 (Tier 3) exhibited consistent but complex regulatory patterns. Several signals were replicated in brain tissues, including TDRKH in the caudate and METAP1D in the cortex.
Conclusions
This study provides multi-omics evidence for the causal involvement of mitochondrial genes in MDD. TDRKH and METAP1D emerged as key candidates, offering promising targets for future mechanistic research and therapeutic development.
Major depressive disorder (MDD) is a heterogeneous with underlying mechanisms that are insufficiently studied. We aimed to identify functional connectivity (FC)-based subtypes of MDD and investigate their biological mechanisms.
Methods
Consensus clustering of FC patterns was applied to a population of 829 MDD patients from the REST-Meta-MDD database, with validity assessed across multiple dimensions, including atlas replication, cross-validated classification, and drug-naïve subgroup analysis. Regression models were used to quantify FC alterations in each MDD subgroup compared with 770 healthy controls, and to analyze spatial associations between FC alterations and publicly available gene transcriptomic and neurotransmitter receptor/transporter density databases.
Results
Two stable MDD subtypes emerged: hypoconnectivity (n = 527) and hyperconnectivity (n = 299), which had both shared and distinct regions with remarkable FC alterations (i.e. epicenters) in the default mode network.
There were several common enriched genes (e.g. axon/brain development, synaptic transmission/organization, etc.) related to FC alterations in both subtypes. However, glial cell and neuronal differentiation genes were specifically enriched in the hypoconnectivity and hyperconnectivity subtypes, respectively.
Both subtypes showed spatial associations between FC alterations and serotonin receptor/transporter density. In the hypoconnectivity subtype, FC alterations correlated with GABA and acetylcholine receptor densities, while norepinephrine transporter and glutamate receptor densities were linked to the hyperconnectivity subtype.
Conclusions
Our findings suggested the presence of two neuroimaging subtypes of MDD characterized by hypoconnectivity or hyperconnectivity, demonstrating robust reproducibility. The two subtypes had both shared and distinct genetic mechanisms and neurotransmitter receptor/transporter profiles, suggesting potential clinical implications for this heterogeneous disorder.
Nutraceuticals are increasingly of interest in nutritional psychiatry, where creatine has been investigated in several randomised trials for its effects on depressive symptoms. However, these findings have not yet been systematically synthesised. We conducted a systematic review to assess the effects of creatine supplementation on symptoms of depression. Four databases were searched up to February 2025 for trials comparing creatine with placebo in individuals with or without depression. Study selection, data extraction and risk of bias assessment (RoB 2) were conducted independently, and certainty of evidence was evaluated using Grading of Recommendations, Assessment, Development and Evaluation (GRADE). Random-effects meta-analyses with Hartung–Knapp–Sidik–Jonkman adjustment including eleven trials (1093 participants) found a standardised mean difference of −0·34 (95 % CI −0·68, −0·00; GRADE: very low quality of evidence), equivalent to 2·2 points on the seventeen-item Hamilton Depression Rating Scale, below the minimal important difference of 3·0 points. CI include non-clinically important effects, and heterogeneity was substantial (I2 = 71·3 %). While effects appeared larger in clinically depressed populations, subgroup analyses and trim-and-fill adjustments indicated substantial bias favouring creatine. Results for secondary endpoints were significant for remission (three trials, OR 3·60; 95 % CI 1·76, 7·56), but not for treatment response (two trials, OR 0·72; 95 % CI 0·28, 1·88). Our findings suggest that creatine may offer a small-to-moderate benefit for individuals with depression, but average effects were not clinically important and the true effect may be trivial or null. The evidence on which these results are based is very uncertain. Larger, more rigorous randomised trials are required to draw definitive conclusions.
Major depressive disorder (MDD) patients exhibit a mood-congruent emotional processing bias within the amygdala toward negative facial stimuli at both unconscious and conscious levels. Therefore, our study aimed to investigate the temporal and spatial dynamics of amygdala along with its interactions with the whole brain during implicit and explicit conditions in MDD.
Methods
Thirty MDD patients and 26 healthy controls (HCs) underwent magnetoencephalography (MEG) recordings and performed implicit and explicit emotional face recognition tasks with happy, sad, and neutral facial expressions. Using the amygdala as a seed region, time frequency representations (TFR) and functional connectivity (FC) were calculated. Pearson correlation analyses measured the relationship between TFR and FC values with clinical symptoms.
Results
During implicit processing, MDD patients exhibited left amygdala activation in the gamma power (60–70 Hz) before 250 ms in response to sad facial stimuli compared to HCs. In the implicit mode, there were increased FC between the right amygdala and several brain regions in the occipitoparietal lobes, as well as higher FC between the left amygdala and putamen in MDD patients. Additionally, the right amygdala was positively correlated with the severity of depression and anxiety during implicit processing.
Conclusions
MDD patients had lateralized amygdala activation in response to sad facial expressions during unconscious emotional recognition of facial stimuli. Our study provided valuable insights into the spatiotemporal dynamics of facial emotional recognition associated with depressive and anxiety-related cognitive bias during implicit and explicit processing.
Heightened reactivity in the amygdala measured by functional magnetic resonance imaging during emotional processing is considered a potential biomarker for clinical depression. Still, it is unknown whether this is also true for depressive symptoms in the general population, and – when in remission after recurrent depressive episodes – it is associated with future episodes.
Methods
Using the UK Biobank population study (n = 11,334), we investigated the association of amygdala reactivity during negative facial stimuli, focusing on lifetime depression (trait), depressive symptoms (state), and the modulating effect of antidepressant (AD) treatment thereof. We employed normative modeling (NM) to better incorporate population heterogeneity of the amygdala activity.
Results
In line with a previous study, depressive symptoms (state) over the last 2 weeks were not associated with the amygdala reactivity signal. Rather, our results indicate a significant positive association (p = 0.03, ω2 = 0.001) between amygdala response and the recurrence of depressive episodes (trait). Longitudinal analysis revealed that the group that had experienced a single depressive episode before showed a significantly increased amygdala response after additional episodes (p = 0.03, ω2 = 0.017). ADs were not associated with amygdala response directly, but decreased associations within episode recurrence severity.
Conclusions
The amygdala response to negative stimuli was associated with an individual’s risk of recurrence of depressive episodes, and AD treatment reduced these associations. This study highlights the relevance of amygdala reactivity as a trait, but not a state biomarker for (recurrent) depression. Moreover, it demonstrates the benefit of applying NM in the context of population data.
Reward can influence cognitive control; however, dysfunctional interactions between reward and cognitive control in adolescents with major depressive disorder (MDD) remain unclear.
Methods
We recruited 35 adolescents with MDD and 29 healthy controls (HC) who completed the AX version of the Continuous Performance Test (AX-CPT) under reward and non-reward conditions, while undergoing functional Near-Infrared Spectroscopy (fNIRS).
Results
Adolescents with MDD exhibited slower response times and higher error rates compared to healthy controls. Under reward conditions, they responded more quickly but made more errors. Hierarchical Drift Diffusion Modeling (HDDM) revealed that adolescents with MDD showed a reduced starting bias toward more rewarding responses and a broader decision threshold in reward contexts. Neuroimaging results indicated that the MDD group showed diminished activation differences in the left dorsolateral prefrontal cortex (DLPFC), left ventrolateral prefrontal cortex (VLPFC), and right VLPFC in response to cues requiring high versus low cognitive control. Additionally, they exhibited weaker functional connectivity between these regions during reward-related cognitive control. Correlation analyses further showed that greater anhedonia severity was associated with poorer behavioral performance and less flexible activation in the prefrontal cortex.
Conclusions
Cognitive control impairments in depressed adolescents may be related to dysfunction in the motivational system. Our findings provide behavioral, computational, and neural evidence for the Expected Value of Control (EVC) theory. Diminished reward sensitivity and inflexible cognitive control may jointly contribute to these deficits, highlighting the importance of considering motivational factors in the diagnosis and intervention of cognitive control impairments in adolescents with depression.
Psychomotor disturbance (PmD) is prevalent in major depressive disorder (MDD), with neural substrates implicated in disrupted motor circuits and the interaction to non-motor cortex. Our objective is to explore the functional connectivity pattern underlying PmD using functional magnetic resonance imaging (fMRI).
Methods
A total of 150 patients with MDD and 91 healthy controls (HCs) were included in this study. The patients were categorized into psychomotor (pMDD, n = 107) and non-psychomotor (npMDD, n = 43) groups based on the Hamilton Depression Rating Scale. Seed-based connectivity (SBC) analysis was conducted using predefined somatomotor and cerebellar network (SMN and CN) coordinates as seeds, to assess group differences and symptom correlations. Subsequently, we correlated the group-contrast SBC map with existing neurotransmitter maps to explore the neurochemical basis.
Results
In pMDD patients compared to HC, we observed decreased connectivity, especially between the SMN and frontal cortex, within the bilateral SMN, and between the CN and right precentral cortex. Meanwhile, connectivity increased between the SMN and the middle cingulate cortex and between the CN and left precentral cortex in pMDD relative to npMDD and HC. Connectivity between the SMN and angular gyrus was positively correlated with the severity of PmD. Additionally, the aberrant SBC patterns in pMDD were linked to the distribution of dopamine D1 and D2 receptors.
Conclusions
This study provides insights into the aberrant connectivity within the motor circuits and its interactions with non-motor regions in PmD. It also suggests a potential role for dopaminergic dysregulation in the connectivity abnormalities associated with PmD.
Howard CH Khoe, National Psychiatry Residency Programme, Singapore,Cheryl WL Chang, National University Hospital, Singapore,Cyrus SH Ho, National University Hospital, Singapore
Chapter 5 covers the topic of grief and prolonged grief disorder. Through a case vignette with topical MCQs for consolidation of learning, readers are brought through the diagnosis and treatment of a patient with normal grief and prolonged grief disorder. We also explore how to differentiate it from major depressive disorder. Topics covered include the symptoms, psychopathology, treatment including psychological therapies.
Howard CH Khoe, National Psychiatry Residency Programme, Singapore,Cheryl WL Chang, National University Hospital, Singapore,Cyrus SH Ho, National University Hospital, Singapore
Chapter 3 covers the topic of major depressive disorder. Through a case vignette with topical MCQs for consolidation of learning, readers are brought through the management of a patient with major depressive disorder from first presentation to subsequent complications of the conditions and its treatment. Things covered include the symptoms, psychopathology, co–morbid conditions, psychological therapies, the evidence-based use of pharmacological treatment including antidepressants and adjuncts, adverse effects of commonly used medications, management of treatment-resistant depression.