Psychomotor retardation in depression: biological underpinnings, measurement, and treatment

Dopaminergic dysfunction in the left putamen of patients with major depressive disorder

INTRODUCTION

Dopaminergic transmission impairment has been identified as one of the main neurobiological correlates of both depression and clinical symptoms commonly associated with its spectrum such as anhedonia and psychomotor retardation.

OBJECTIVES

We examined the relationship between dopaminergic deficit in the striatum, as measured by 123I-FP-CIT SPECT imaging, and specific psychopathological dimensions in patients with major depressive disorder.

METHODS

To our knowledge this is the first study with a sample of >120 subjects. After check for inclusion and exclusion criteria, 121 (67 females, 54 males) patients were chosen retrospectively from an extensive 1106 patients database of 123I-FP-CIT SPECT scans obtained at the Nuclear Medicine Unit of Fondazione Policlinico Universitario Agostino Gemelli IRCCS in Rome. These individuals had undergone striatal dopamine transporter (DAT) assessments based on the recommendation of their referring clinicians, who were either neurologists or psychiatrists. At the time of SPECT imaging, each participant underwent psychiatric and psychometric evaluations. We used the following psychometric scales: Hamilton Depression Rating Scale, Hamilton Anxiety Rating Scale, Snaith Hamilton Pleasure Scale, and Depression Retardation Rating Scale.

RESULTS

We found a negative correlation between levels of depression (p = 0.007), anxiety (p = 0.035), anhedonia (p = 0.028) and psychomotor retardation (p = 0.014) and DAT availability in the left putamen. We further stratified the sample and found that DAT availability in the left putamen was lower in seriously depressed patients (p = 0.027) and in patients with significant psychomotor retardation (p = 0.048).

CONCLUSION

To our knowledge this is the first study to have such a high number of sample. Our study reveals a pivotal role of dopaminergic dysfunction in patients with major depressive disorder. Elevated levels of depression, anxiety, anhedonia, and psychomotor retardation appear to be associated with reduced DAT availability specifically in the left putamen.

Chronic unpredictable stress (CUS) reduced phoenixin expression, induced abnormal sperm and testis morphology in male rats

Chronic stress caused by prolonged emotional pressure can lead to various physiological issues, including reproductive dysfunction. Although reproductive problems can also induce chronic stress, the impact of chronic stress-induced reproductive dysfunction remains contentious. This study investigates the effects of chronic unpredictable stress (CUS) on reproductive neuropeptides, sperm quality, and testicular morphology. Sixteen twelve-week-old Sprague Dawley rats were divided into two groups: a non-stress control group and a CUS-induced group. The CUS regimen involved various stressors over 28 days, with both groups undergoing behavioural assessments through sucrose-preference and forced-swim tests. Hypothalamic gene expression levels of CRH, PNX, GPR173, kisspeptin, GnRH, GnIH, and spexin neuropeptides were measured via qPCR, while plasma cortisol, luteinizing hormone (LH), and testosterone concentrations were quantified using ELISA. Seminal fluid and testis samples were collected for sperm analysis and histopathological evaluation, respectively. Results showed altered behaviours in CUS-induced rats, reflecting stress impacts. Hypothalamic corticotropin-releasing hormone (CRH) expression and plasma cortisol levels were significantly higher in CUS-induced rats compared to controls (p < 0.05). Conversely, phoenixin (PNX) expression decreased in the CUS group (p < 0.05), while kisspeptin, spexin, and gonadotropin-inhibitory hormone (GnIH) levels showed no significant differences between groups. Despite a significant increase in GnRH expression (p < 0.05), plasma LH and testosterone concentrations were significantly lower (p < 0.05) in CUS-induced rats. Histopathological analysis revealed abnormal testis morphology in CUS-induced rats, including disrupted architecture, visible interstitial spaces between seminiferous tubules, and absence of spermatogenesis. In conclusion, CUS affects reproductive function by modulating PNX and GnRH expression, influencing cortisol levels, and subsequently reducing plasma LH and testosterone concentrations. This study highlights the complex interplay between chronic stress and reproductive health, emphasizing the significant impact of stress on reproductive functions.

Structural Brain MR Imaging Alterations in Patients with Systemic Lupus Erythematosus with and without Neuropsychiatric Events

BACKGROUND AND PURPOSE

Systemic lupus erythematosus is a complex autoimmune disease known for its diverse clinical manifestations, including neuropsychiatric systemic lupus erythematosus, which impacts a patient's quality of life. Our aim was to explore the relationships among brain MR imaging morphometric findings, neuropsychiatric events, and laboratory values in patients with systemic lupus erythematosus, shedding light on potential volumetric biomarkers and diagnostic indicators for neuropsychiatric systemic lupus erythematosus.

MATERIALS AND METHODS

Twenty-seven patients with systemic lupus erythematosus (14 with neuropsychiatric systemic lupus erythematosus, 13 with systemic lupus erythematosus), 24 women and 3 men (average age, 43 years, ranging from 21 to 62 years) were included in this cross-sectional study, along with 10 neuropsychiatric patients as controls. An MR imaging morphometric analysis, with the VolBrain online platform, to quantitatively assess brain structural features and their differences between patients with neuropsychiatric systemic lupus erythematosus and systemic lupus erythematosus, was performed. Correlations and differences between MR imaging morphometric findings and laboratory values, including disease activity scores, such as the Systemic Lupus Erythematosus Disease Activity Index and the Systemic Lupus International Collaborating Clinics Damage Index, were explored. An ordinary least squares regression analysis further explored the Systemic Lupus Erythematosus Disease Activity Index and Systemic Lupus International Collaborating Clinics Damage Index relationship with MR imaging features.

RESULTS

For neuropsychiatric systemic lupus erythematosus and non-neuropsychiatric systemic lupus erythematosus, the brain regions with the largest difference in volumetric measurements were the insular central operculum volume (P value = .003) and the occipital cortex thickness (P = .003), which were lower in neuropsychiatric systemic lupus erythematosus. The partial correlation analysis showed that the most correlated morphometric features with neuropsychiatric systemic lupus erythematosus were subcallosal area thickness asymmetry (P < .001) and temporal pole thickness asymmetry (P = .011). The ordinary least squares regression analysis yielded an R 2 of 0.725 for the Systemic Lupus Erythematosus Disease Activity Index score, with calcarine cortex volume as a significant predictor, and an R 2 of 0.715 for the Systemic Lupus International Collaborating Clinics Damage Index score, with medial postcentral gyrus volume as a significant predictor.

CONCLUSIONS

The MR imaging volumetric analysis, along with the correlation study and the ordinary least squares regression analysis, revealed significant differences in brain regions and their characteristics between patients with neuropsychiatric systemic lupus erythematosus and those with systemic lupus erythematosus, as well as between patients with different Systemic Lupus Erythematosus Disease Activity Index and Systemic Lupus International Collaborating Clinics Damage Index scores.

Lycopene alleviates BCG-induced depressive phenotypes in mice by disrupting 5-HT3 receptor - IDO1 interplay in the brain

The 5-HT3 receptor and indoleamine 2,3-dioxygenase 1 (IDO1) enzyme play a crucial role in the pathogenesis of depression as their activation reduces serotonin contents in the brain. Since molecular docking analysis revealed lycopene as a potent 5-HT3 receptor antagonist and IDO1 inhibitor, we hypothesized that lycopene might disrupt the interplay between the 5-HT3 receptor and IDO1 to mitigate depression. In mice, the depression-like phenotypes were induced by inoculating Bacillus Calmette-Guerin (BCG). Lycopene (intraperitoneal; i.p.) was administered alone or in combination with 5-HT3 receptor antagonist ondansetron (i.p.) or IDO1 inhibitor minocycline (i.p.), and the behavioral screening was performed by the sucrose preference test, open field test, tail suspension test, and splash test which are based on the different principles. Further, the brains were subjected to the biochemical analysis of serotonin and its precursor tryptophan by the HPLC. The results showed depression-like behavior in BCG-inoculated mice, which was reversed by lycopene administration. Moreover, prior treatment with ondansetron or minocycline potentiated the antidepressant action of lycopene. Minocycline pretreatment also enhanced the antidepressant effect of ondansetron indicating the regulation of IDO1 activity by 5-HT3 receptor-triggered signaling. Biochemical analysis of brain samples revealed a drastic reduction in the levels of tryptophan and serotonin in depressed animals, which were restored following treatment with lycopene and its combination with ondansetron or minocycline. Taken together, the data from molecular docking, behavioral experiments, and biochemical estimation suggest that lycopene might block the 5-HT3 receptor and consequently inhibit the activity of IDO1 to ameliorate BCG-induced depression in mice.

Protocol for a randomised controlled trial of ketamine versus ketamine and behavioural activation therapy for adults with treatment-resistant depression in the community

INTRODUCTION

Although short-term benefits follow parenteral ketamine for treatment-resistant major depressive disorder (TR-MDD), there are challenges that prevent routine use of ketamine by clinicians. These include acute dissociative effects of parenteral ketamine, high relapse rates following ketamine dosing and the uncertain role of psychotherapy. This randomised controlled trial (RCT) seeks to establish the feasibility of evaluating repeated oral doses of ketamine and behavioural activation therapy (BAT), compared with ketamine treatment alone, for TR-MDD. We also aim to compare relapse rates between treatment arms to determine the effect size of adding BAT to oral ketamine.

METHODS AND ANALYSIS

This is a prospectively registered, two-centre, single-blind RCT. We aim to recruit 60 participants with TR-MDD aged between 18 and 65 years. Participants will be randomised to 8 weeks of oral ketamine and BAT, or 8 weeks of oral ketamine alone. Feasibility will be assessed by tracking attendance for ketamine and BAT, acceptability of treatment measures and retention to the study follow-up protocol. The primary efficacy outcome measure is the Montgomery-Asberg Depression Rating Scale (MADRS) measured weekly during treatment and fortnightly during 12 weeks of follow-up. Other outcome measures will assess the tolerability of ketamine and BAT, cognition and activity (using actigraphy). Participants will be categorised as non-responders, responders, remitters and relapsed during follow-up. MADRS scores will be analysed using a linear mixed model. For a definitive follow-up RCT study to be recommended, the recruitment expectations will be met and efficacy outcomes consistent with a >20% reduction in relapse rates favouring the BAT and ketamine arm will be achieved.

ETHICS AND DISSEMINATION

Ethics approval was granted by the New Zealand Central Health and Disability Ethics Committee (reference: 2023 FULL18176). Study findings will be reported to participants, stakeholder groups, conferences and peer-reviewed publications.

TRIAL REGISTRATION NUMBER

UTN: U1111-1294-9310, ACTRN12623000817640p.

Altered asymmetry of functional connectome gradients in major depressive disorder

Introduction

Major depressive disorder (MDD) is a debilitating disease involving sensory and higher-order cognitive dysfunction. Previous work has shown altered asymmetry in MDD, including abnormal lateralized activation and disrupted hemispheric connectivity. However, it remains unclear whether and how MDD affects functional asymmetries in the context of intrinsic hierarchical organization.

Methods

Here, we evaluate intra- and inter-hemispheric asymmetries of the first three functional gradients, characterizing unimodal-transmodal, visual-somatosensory, and somatomotor/default mode-multiple demand hierarchies, to study MDD-related alterations in overarching system-level architecture.

Results

We find that, relative to the healthy controls, MDD patients exhibit alterations in both primary sensory regions (e.g., visual areas) and transmodal association regions (e.g., default mode areas). We further find these abnormalities are woven in heterogeneous alterations along multiple functional gradients, associated with cognitive terms involving mind, memory, and visual processing. Moreover, through an elastic net model, we observe that both intra- and inter-asymmetric features are predictive of depressive traits measured by BDI-II scores.

Discussion

Altogether, these findings highlight a broad and mixed effect of MDD on functional gradient asymmetry, contributing to a richer understanding of the neurobiological underpinnings in MDD.

The clinical presentation of major depressive disorder in youth with co-occurring obsessive-compulsive disorder

BACKGROUND

Major depressive disorder (MDD) is common in youth and among the most frequent comorbid disorders in pediatric obsessive-compulsive disorder (OCD), but it is unclear whether the presence of OCD affects the symptom presentation of MDD in youth.

METHODS

A sample of youth with OCD and MDD (n = 124) and a sample of youth with MDD but no OCD (n = 673) completed the Patient Health Questionnaire for Adolescents (PHQ-A). The overall and symptom-level presentation of MDD were examined using group comparisons and network analysis.

RESULTS

Youth with MDD and OCD, compared to those with MDD and no OCD, had more severe MDD (Cohen's d = 0.39) and more reported moderate to severe depression (75 % vs 61 %). When accounting for demographic variables and the overall severity of MDD, those with comorbid OCD reported lower levels of anhedonia and more severe difficulties with psychomotor retardation/agitation. No significant differences in the interconnections among symptoms emerged.

LIMITATIONS

Data were cross-sectional and self-reported, gold standard diagnostic tools were not used to assess OCD, and the sample size for the group with MDD and OCD was relatively small yielding low statistical power for network analysis.

CONCLUSIONS

Youth with MDD and OCD have more severe MDD than those with MDD and no OCD and they experience more psychomotor issues and less anhedonia, which may relate to the behavioral activation characteristic of OCD.

Linking inter-subject variability of cerebellar functional connectome to clinical symptoms in major depressive disorder

Major depressive disorder (MDD) is a highly prevalent psychiatric disorder with remarkable inter-subject variability in clinical manifestations. Neuroimaging changes of the cerebellum have been recently proposed as a way to characterize MDD-related brain disruptions and might further explain various clinical symptoms. However, the cerebellar contributions to MDD clinical heterogeneity remain largely unknown. The analyzed data consisted of 251 MDD patients and 235 matching healthy controls (HC). The inter-subject variability of functional connectomes (IVFC) was estimated via Pearson's correlation analysis between each pair of the cerebellar and cerebral regions based on resting-state functional magnetic resonance imaging (rs-fMRI). A partial least squares (PLS) regression analysis was performed to determine the potential dimension linking the IVFC to clinical symptom measures. The results indicated that similar spatial distribution patterns of the cerebellar IVFC were observed between MDD and HC, but the MDD group exhibited abnormal IVFC alterations in the bilateral Cerebelum_4_5, bilateral Cerebelum_6, Vermis_1_2 and Vermis_8. The PLS model revealed that the IVFC pattern in the left Cerebelum_6 was significantly associated with three HAMD-17 items including the work and activities, psychomotor retardation, and depressed mood. These findings provided new evidence for the cerebellar changes in MDD. Specifically, we found that the altered inter-subject variability measurements correlated with clinical manifestations of this illness. Elucidating this variability could prove helpful for the evaluation of MDD heterogeneity as well as for understanding its pathophysiological mechanism.

Abnormal stability of spontaneous neuronal activity as a predictor of diagnosis conversion from major depressive disorder to bipolar disorder

OBJECTIVE

Bipolar disorder (BD) is often misdiagnosed as major depressive disorder (MDD) in the early stage, which may lead to inappropriate treatment. This study aimed to characterize the alterations of spontaneous neuronal activity in patients with depressive episodes whose diagnosis transferred from MDD to BD.

METHODS

532 patients with MDD and 132 healthy controls (HCs) were recruited over 10 years. During the follow-up period, 75 participants with MDD transferred to BD (tBD), and 157 participants remained with the diagnosis of unipolar depression (UD). After excluding participants with poor image quality and excessive head movement, 68 participants with the diagnosis of tBD, 150 participants with the diagnosis of UD, and 130 HCs were finally included in the analysis. The dynamic amplitude of low-frequency fluctuations (dALFF) of spontaneous neuronal activity was evaluated in tBD, UD and HC using functional magnetic resonance imaging at study inclusion. Receiver operating characteristic (ROC) analysis was performed to evaluate sensitivity and specificity of the conversion prediction from MDD to BD based on dALFF.

RESULTS

Compared to HC, tBD exhibited elevated dALFF at left premotor cortex (PMC_L), right lateral temporal cortex (LTC_R) and right early auditory cortex (EAC_R), and UD showed reduced dALFF at PMC_L, left paracentral lobule (PCL_L), bilateral medial prefrontal cortex (mPFC), right orbital frontal cortex (OFC_R), right dorsolateral prefrontal cortex (DLPFC_R), right posterior cingulate cortex (PCC_R) and elevated dALFF at LTC_R. Furthermore, tBD exhibited elevated dALFF at PMC_L, PCL_L, bilateral mPFC, bilateral OFC, DLPFC_R, PCC_R and LTC_R than UD. In addition, ROC analysis based on dALFF in differential areas obtained an area under the curve (AUC) of 72.7%.

CONCLUSIONS

The study demonstrated the temporal dynamic abnormalities of tBD and UD in the critical regions of the somatomotor network (SMN), default mode network (DMN), and central executive network (CEN). The differential abnormal patterns of temporal dynamics between the two diseases have the potential to predict the diagnosis transition from MDD to BD.

Multimodal Mental Health Digital Biomarker Analysis From Remote Interviews Using Facial, Vocal, Linguistic, and Cardiovascular Patterns

OBJECTIVE

Psychiatric evaluation suffers from subjectivity and bias, and is hard to scale due to intensive professional training requirements. In this work, we investigated whether behavioral and physiological signals, extracted from tele-video interviews, differ in individuals with psychiatric disorders.

METHODS

Temporal variations in facial expression, vocal expression, linguistic expression, and cardiovascular modulation were extracted from simultaneously recorded audio and video of remote interviews. Averages, standard deviations, and Markovian process-derived statistics of these features were computed from 73 subjects. Four binary classification tasks were defined: detecting 1) any clinically-diagnosed psychiatric disorder, 2) major depressive disorder, 3) self-rated depression, and 4) self-rated anxiety. Each modality was evaluated individually and in combination.

RESULTS

Statistically significant feature differences were found between psychiatric and control subjects. Correlations were found between features and self-rated depression and anxiety scores. Heart rate dynamics provided the best unimodal performance with areas under the receiver-operator curve (AUROCs) of 0.68-0.75 (depending on the classification task). Combining multiple modalities provided AUROCs of 0.72-0.82.

CONCLUSION

Multimodal features extracted from remote interviews revealed informative characteristics of clinically diagnosed and self-rated mental health status.

SIGNIFICANCE

The proposed multimodal approach has the potential to facilitate scalable, remote, and low-cost assessment for low-burden automated mental health services.

A three-dimensional model of neural activity and phenomenal-behavioral patterns

How phenomenal experience and behavior are related to neural activity in physiology and psychopathology represents a fundamental question in neuroscience and psychiatry. The phenomenal-behavior patterns may be deconstructed into basic dimensions, i.e., psychomotricity, affectivity, and thought, which might have distinct neural correlates. This work provides a data overview on the relationship of these phenomenal-behavioral dimensions with brain activity across physiological and pathological conditions (including major depressive disorder, bipolar disorder, schizophrenia, attention-deficit/hyperactivity disorder, anxiety disorders, addictive disorders, Parkinson's disease, Tourette syndrome, Alzheimer's disease, and frontotemporal dementia). Accordingly, we propose a three-dimensional model of neural activity and phenomenal-behavioral patterns. In this model, neural activity is organized into distinct units in accordance with connectivity patterns and related input/output processing, manifesting in the different phenomenal-behavioral dimensions. (1) An external neural unit, which involves the sensorimotor circuit/brain's sensorimotor network and is connected with the external environment, processes external inputs/outputs, manifesting in the psychomotor dimension (processing of exteroception/somatomotor activity). External unit hyperactivity manifests in psychomotor excitation (hyperactivity/hyperkinesia/catatonia), while external unit hypoactivity manifests in psychomotor inhibition (retardation/hypokinesia/catatonia). (2) An internal neural unit, which involves the interoceptive-autonomic circuit/brain's salience network and is connected with the internal/body environment, processes internal inputs/outputs, manifesting in the affective dimension (processing of interoception/autonomic activity). Internal unit hyperactivity manifests in affective excitation (anxiety/dysphoria-euphoria/panic), while internal unit hypoactivity manifests in affective inhibition (anhedonia/apathy/depersonalization). (3) An associative neural unit, which involves the brain's associative areas/default-mode network and is connected with the external/internal units (but not with the environment), processes associative inputs/outputs, manifesting in the thought dimension (processing of ideas). Associative unit hyperactivity manifests in thought excitation (mind-wandering/repetitive thinking/psychosis), while associative unit hypoactivity manifests in thought inhibition (inattention/cognitive deficit/consciousness loss). Finally, these neural units interplay and dynamically combine into various neural states, resulting in the complex phenomenal experience and behavior across physiology and neuropsychiatric disorders.

Directional associations among real-time activity, sleep, mood, and daytime symptoms in major depressive disorder using actigraphy and ecological momentary assessment

Previous research has suggested that individuals with major depressive disorder (MDD) experienced alterations in sleep and activity levels. However, the temporal associations among sleep, activity levels, mood, and daytime symptoms in MDD have not been fully investigated. The present study aimed to fill this gap by utilizing real-time data collected across time points and days. 75 individuals with MDD and 75 age- and gender-matched healthy controls were recruited. Ecological momentary assessments (EMA) were adopted to assess real-time mood status for 7 days, and actigraphy was employed to measure day-to-day sleep-activity patterns. Multilevel modeling analyses were performed. Results revealed a bidirectional association between mood/daytime symptoms and activity levels across EMA intervals. Increased activity levels were predictive of higher alert cognition and positive mood, while an increase in positive mood also predicted more increase in activity levels in depressed individuals. A bidirectional association between sleep and daytime symptoms was also found. Alert cognition was found to be predictive of better sleep in the subsequent night. Contrariwise, higher sleep efficiency predicted improved alert cognition and sleepiness/fatigue the next day. A unidirectional association between sleep and activity levels suggested that higher daytime activity levels predicted a larger increase in sleep efficiency among depressed individuals. This study indicated how mood, activity levels, and sleep were temporally and intricately linked to each other in depressed individuals using actigraphy and EMA. It could pave the way for novel and efficacious treatments for depression that target not just mood but sleep and activity levels.

The neural signature of psychomotor disturbance in depression

Up to 70% of patients with major depressive disorder present with psychomotor disturbance (PmD), but at the present time understanding of its pathophysiology is limited. In this study, we capitalized on a large sample of patients to examine the neural correlates of PmD in depression. This study included 820 healthy participants and 699 patients with remitted (n = 402) or current (n = 297) depression. Patients were further categorized as having psychomotor retardation, agitation, or no PmD. We compared resting-state functional connectivity (ROI-to-ROI) between nodes of the cerebral motor network between the groups, including primary motor cortex, supplementary motor area, sensory cortex, superior parietal lobe, caudate, putamen, pallidum, thalamus, and cerebellum. Additionally, we examined network topology of the motor network using graph theory. Among the currently depressed 55% had PmD (15% agitation, 29% retardation, and 11% concurrent agitation and retardation), while 16% of the remitted patients had PmD (8% retardation and 8% agitation). When compared with controls, currently depressed patients with PmD showed higher thalamo-cortical and pallido-cortical connectivity, but no network topology alterations. Currently depressed patients with retardation only had higher thalamo-cortical connectivity, while those with agitation had predominant higher pallido-cortical connectivity. Currently depressed patients without PmD showed higher thalamo-cortical, pallido-cortical, and cortico-cortical connectivity, as well as altered network topology compared to healthy controls. Remitted patients with PmD showed no differences in single connections but altered network topology, while remitted patients without PmD did not differ from healthy controls in any measure. We found evidence for compensatory increased cortico-cortical resting-state functional connectivity that may prevent psychomotor disturbance in current depression, but may perturb network topology. Agitation and retardation show specific connectivity signatures. Motor network topology is slightly altered in remitted patients arguing for persistent changes in depression. These alterations in functional connectivity may be addressed with non-invasive brain stimulation.

Evaluation of cognitive and psychomotor faculties in relation to mood-related symptoms under the conditions of sleep deprivation

Introduction

Deprivation of sleep (DS) has been associated with changes in mood and cognitive function, rapidly but transiently improving the severity of depression symptoms. However, it remains unclear whether there are differences in performance between DS responders and non-responders. The relationship between DS, mood, cognitive, and psychomotor function is also poorly understood.

Methods

Participants (n = 77) underwent a baseline assessment of sleep under the control of polysomnography (PSG). Later they were subjected to DS with actigraphy monitoring. Evaluation of mood as well as completing a battery of tests assessing cognitive functions and eye-hand coordination was conducted four times, pre/post PSG and DS. Participants were further divided into respondents (RE, n = 48) and non-respondents (NR, n = 29) depending on alleviation of depression symptoms severity following DS.

Results

All participants exhibited increased response speed to visual triggers after DS compared to baseline (p = 0.024). Psychomotor vigilance test (PVT) results remained intact in the RE, whereas it was increased in the NR (p = 0.008). Exposure time in the eye-hand coordination test improved in both groups, but total error duration was reduced only in RE individuals (p < 0.001, p = 0.009 for RE and NR, respectively). All subjects were more proficient at trail-making test (p ≤ 0.001 for Part 1 and 2 in all, NR, RE). Stroop test also improved regardless of mood changes after DS (p = 0.007, p = 0.008 for Part 1 and 2, respectively); cognitive interference remained at a similar level within groups (p = 0.059, p = 0.057 for NR and RE, respectively). A positive correlation was observed between the difference in PSG morning/DS morning depression severity and vigilance (R = 0.37, p = 0.001, R = 0.33, p = 0.005, for error duration eye-hand coordination test and PVT total average score, respectively).

Conclusion

RE tend to maintain or improve cognitive function after DS, oppositely to NR. Vigilance in particular might be tightly associated with changes in depression symptoms after DS. Future studies should examine the biological basis behind the response to sleep loss.

Reviewing the neurobiology of electroconvulsive therapy on a micro- meso- and macro-level

BACKGROUND

Electroconvulsive therapy (ECT) remains the one of the most effective of biological antidepressant interventions. However, the exact neurobiological mechanisms underlying the efficacy of ECT remain unclear. A gap in the literature is the lack of multimodal research that attempts to integrate findings at different biological levels of analysis METHODS: We searched the PubMed database for relevant studies. We review biological studies of ECT in depression on a micro- (molecular), meso- (structural) and macro- (network) level.

RESULTS

ECT impacts both peripheral and central inflammatory processes, triggers neuroplastic mechanisms and modulates large scale neural network connectivity.

CONCLUSIONS

Integrating this vast body of existing evidence, we are tempted to speculate that ECT may have neuroplastic effects resulting in the modulation of connectivity between and among specific large-scale networks that are altered in depression. These effects could be mediated by the immunomodulatory properties of the treatment. A better understanding of the complex interactions between the micro-, meso- and macro- level might further specify the mechanisms of action of ECT.

Chronic pain predicts a worse response to depression treatment, regardless of thyroid function or psychotropics prescribed

BACKGROUND

Chronic pain (CP) and thyroid hormones' (TH) abnormalities are associated with depression, but the impact of pain and TH fluctuation on the response to depression treatment is uncertain.

METHODS

Eighty-eight patients with major depression were evaluated before and after 6 months of specific treatment, through scales of symptoms' severity (HAM-D-17), psychomotor disturbance (CORE), and quality of life (WHOQOL-Bref). We reviewed psychiatric medications and measured TSH, T3 and T4. We used Generalized Estimating Equations to assess the interaction effect between CP and treatment time on depression severity and TH levels, and Bonferroni to compare means.

RESULTS

47.7 % of the patients had CP. Patients with and without CP did not differ at baseline. At follow-up, those with CP experienced a more modest decrease in symptoms' severity and no improvement in any domain of psychomotor disturbance, contrasting with a decrease of over 40 % from the baseline values of CORE in patients without CP (non-CP). Initial and final scores were respectively: HAM-D CP 24.06 and 19.3, Δ = -4.75; HAM-D non-CP 22.92 and 14.7, Δ = -8.21; CORE CP 5.36 and 5.24, Δ = -0.12; CORE non-CP 5.8 and 3.22, Δ = -2.57. There was no interaction with TH or life quality. Model adjustments for psychotropic drugs received and sensitivity analysis excluding somatic symptoms from severity scales did not impact the results.

LIMITATIONS

Findings may not replicate in mildly depressed patients from primary care. Pain scales were not applied.

CONCLUSIONS

Individuals with chronic pain showed a suboptimal response to depression treatment, regardless of the medications used or TH levels.

Compressed primary-to-transmodal gradient is accompanied with subcortical alterations and linked to neurotransmitters and cellular signatures in major depressive disorder

Major depressive disorder (MDD) has been shown to involve widespread changes in low-level sensorimotor and higher-level cognitive functions. Recent research found that a primary-to-transmodal gradient could capture a cortical hierarchical organization ranging from perception and action to cognition in healthy subjects, but a prominent gradient dysfunction in MDD patients. However, whether and how this cortical gradient is linked to subcortical impairments and whether it is reflected in the microscale neurotransmitter systems and cell type-specific transcriptional signatures remain largely unknown. Data were acquired from 323 MDD patients and 328 sex- and age-matched healthy controls derived from the REST-meta-MDD project, and the human brain neurotransmitter systems density maps and gene expression data were drawn from two publicly available datasets. We investigated alterations of the primary-to-transmodal gradient in MDD patients and their correlations with clinical symptoms of depression and anxiety, as well as  their paralleled subcortical impairments. The correlations between MDD-related gradient alterations and densities of the neurotransmitter systems and gene expression information were assessed, respectively. The results demonstrated that MDD patients had a compressed primary-to-transmodal gradient accompanied by paralleled alterations in subcortical regions including the caudate, amygdala, and thalamus. The case-control gradient differences were spatially correlated with the densities of the neurotransmitter systems including the serotonin and dopamine receptors, and meanwhile with gene expression enriched in astrocytes, excitatory and inhibitory neuronal cells. These findings mapped the paralleled subcortical impairments in cortical hierarchical organization and also helped us understand the possible molecular and cellular substrates of the co-occurrence of high-level cognitive impairments with low-level sensorimotor abnormalities in MDD.

Dynamics of Depressive and Psychomotor Symptoms During Electroconvulsive Therapy in Older Depressive Patients: A Case Series

OBJECTIVE

Electroconvulsive therapy (ECT) is an effective treatment for patients experiencing a major depressive episode, especially older ones. Identification of specific responses within early ECT sessions remains an issue of debate, however. Hence, this pilot study prospectively examined the outcome in terms of depressive signs, symptom by symptom, throughout a course of ECT, concentrating particularly on psychomotor retardation symptoms.

METHODS

Nine patients were clinically evaluated several times during the ECT course, before the first session and then weekly (over 3-6 weeks, according to their evolution), by completing the Montgomery-Åsberg Depression Rating Scale (MADRS), the Mini-Mental State Examination test, and the French Retardation Rating Scale for Depression for assessing the severity of psychomotor retardation.

RESULTS

Nonparametric Friedman tests showed significant positive changes in mood disorders during ECT in older depressive patients (mean, -27.3% of initial MADRS total score). Fast improvement in French Retardation Rating Scale for Depression score was observed at t1 (ie, after 3-4 ECT sessions), whereas a slightly delayed improvement in the MADRS scores was found at t2 (ie, after 5-6 ECT sessions). Moreover, the scores for items linked to the motor component of psychomotor retardation (eg, gait, postural control, fatigability) were the first to significantly decrease during the first 2 weeks of the ECT course compared with the cognitive component.

CONCLUSIONS

Interestingly, participants' concentration on daily functional activities, their interest and fatigability, and their reported state of sadness were the first to progress, representing possible precursor signs of positive patient outcomes after ECT.

Sex differences in depression, anxiety and health-promoting lifestyles among community residents: A network approach

BACKGROUND

Researchers have studied sex differences in typical depressive and anxiety symptoms and their cooccurrence. The World Health Organization (WHO) proposed a mental health promotion objective that suggests considering protective health-promoting factors when developing strategies for preventing mental disorders between sexes. From a network perspective, psychopathology is viewed as a result of interacting symptoms and influential factors. This study adopted network approach to investigate sex differences in health-promoting lifestyles (HPL) and the cooccurrence symptoms of communities in Shanghai. The aim is to provide health-promoting suggestions on better enhancing the life quality for community members.

METHODS

Depression, anxiety symptoms, and HPL were assessed with PHQ-9, GAD-7 and HPLP-II scales in 2420 adults (1411 females). Networks were constructed by Gaussian Graphical Models and the networks of two sexes using the Network Comparison Test.

RESULTS

Females scored significantly higher on PHQ-9 (p < 0.001) and GAD-7 (p < 0.001), and no differences were found between the two sexes in HPL scores. Restlessness and low energy yielded the highest strength centrality in the female network, while suicide ideation and restlessness were central in male network. Regarding protective HPL, physical activity and stress management were identified as the central mental health-promoting behaviours in female and male network, respectively. However, stress management was positively related to suicide ideation in the male network.

CONCLUSION

Communities should be aware of suicide ideation in males because of its high relationships with other symptoms and also provide stress management courses, especially for males. As for women, chronic energy deficiency deserves more attention for its high probability of cooccurrence with other symptoms in the network. Also, advocating physical activities may be particularly beneficial for the overall mental health among women. Future study should collect time-series data and analyze intraindividual networks to specify personalized health promoting strategies for each individual.

Oscillatory network markers of subcallosal cingulate deep brain stimulation for depression

Identifying functional biomarkers related to treatment success can aid in expediting therapy optimization, as well as contribute to a better understanding of the neural mechanisms of the treatment-resistant depression (TRD) and subcallosal cingulate deep brain stimulation (SCC-DBS). Magnetoencephalography data were obtained from 16 individuals with SCC-DBS for TRD and 25 healthy subjects. The first objective of the study was to identify region-specific oscillatory modulations that both (i) discriminate individuals with TRD (with SCC-DBS OFF) from healthy controls, and (ii) discriminate TRD treatment responders from non-responders (with SCC-DBS ON). The second objective of this work was to further explore the effects of stimulation intensity and frequency on oscillatory activity in the identified brain regions of interest. Oscillatory power analyses led to the identification of brain regions that differentiated responders from non-responders based on modulations of increased alpha (8-12 Hz) and decreased gamma (32-116 Hz) power within nodes of the default mode, central executive, and somatomotor networks, Broca's area, and lingual gyrus. Within these nodes, it was also found that low stimulation frequency had stronger effects on oscillatory modulation than increased stimulation intensity. The identified functional network biomarkers implicate modulation of TRD-related activity in brain regions involved in emotional control/processing, motor control, and the interaction between speech, vision, and memory, which have all been implicated in depression. These electrophysiological biomarkers have the potential to be used as functional proxies for therapy optimization. Additional stimulation parameter analyses revealed that oscillatory modulations can be strengthened by increasing stimulation intensity or reducing frequency, which may represent potential avenues of direction in non-responders.

[Movement as a Neuromodulator: How Physical Activity Influences the Physiology of Adolescent Depression]

Movement as a Neuromodulator: How Physical Activity Influences the Physiology of Adolescent Depression Abstract: In the context of adolescent depression, physical activity is becoming increasingly recognized for its positive effects on neuropathology. Current scientific findings indicate that physical training affects the biological effects of depression during adolescence. Yet the pathophysiology of adolescent depression is not yet fully understood. Besides psychosocial and genetic influences, various neurobiological factors are being discussed. One explanation model describes a dysfunction of the hypothalamus-pituitary-adrenal axis (HPA axis) with a sustained elevation in cortisol concentration. Recent studies highlight neuroimmunological processes and a reduced concentration of growth factors as causative factors. These changes appear to lead to a dysregulation of the excitation and inhibition balance of the cerebral cortex as well as to cerebral morphological alterations. Regular physical training can potentially counteract the dysregulation of the HPA axis and normalize cortisol levels. The release of proinflammatory cytokines is inhibited, and the expression of growth factors involved in adult neurogenesis is stimulated. One should ensure the synergistic interaction of biological and psychosocial factors when designing the exercise schedule (endurance or strength training, group or individual sports, frequency, duration, and intensity). Addressing these open questions is essential when integrating physical activity into the guidelines for treating depressive disorders in children and adolescents.

Unlocking the Emotional World of Visual Media: An Overview of the Science, Research, and Impact of Understanding Emotion: Drawing Insights From Psychology, Engineering, and the Arts, This Article Provides a Comprehensive Overview of the Field of Emotion Analysis in Visual Media and Discusses the Latest Research, Systems, Challenges, Ethical Implications, and Potential Impact of Artificial Emotional Intelligence on Society

The emergence of artificial emotional intelligence technology is revolutionizing the fields of computers and robotics, allowing for a new level of communication and understanding of human behavior that was once thought impossible. While recent advancements in deep learning have transformed the field of computer vision, automated understanding of evoked or expressed emotions in visual media remains in its infancy. This foundering stems from the absence of a universally accepted definition of "emotion," coupled with the inherently subjective nature of emotions and their intricate nuances. In this article, we provide a comprehensive, multidisciplinary overview of the field of emotion analysis in visual media, drawing on insights from psychology, engineering, and the arts. We begin by exploring the psychological foundations of emotion and the computational principles that underpin the understanding of emotions from images and videos. We then review the latest research and systems within the field, accentuating the most promising approaches. We also discuss the current technological challenges and limitations of emotion analysis, underscoring the necessity for continued investigation and innovation. We contend that this represents a "Holy Grail" research problem in computing and delineate pivotal directions for future inquiry. Finally, we examine the ethical ramifications of emotion-understanding technologies and contemplate their potential societal impacts. Overall, this article endeavors to equip readers with a deeper understanding of the domain of emotion analysis in visual media and to inspire further research and development in this captivating and rapidly evolving field.

Metaphor and the politics and poetics of youth distress in an evidence-based psychotherapy

This article explores the relationship between metaphors and emotion in the context of adolescent distress and psychotherapeutic treatment. Drawing on data from an ethnographic study of Mexican American adolescents receiving outpatient treatment for a variety of emotional and behavioral problems, the article examines what I call "prescribed" metaphors deployed in mainstream, manualized child and adolescent Cognitive Behavioral Therapies commonly used in mainstream clinical contexts. I explore the models of emotion communicated to youth by one such metaphor, youth responses to this metaphor, and the potential implications for young people as they take up the underlying models and affective practices embedded in the metaphor. Specifically, I examine how youth respond to messages about emotion metacognition and emotion regulation embedded in a metaphor that equates feelings with temperatures that can be monitored and objectively measured. I find that youth are at once convinced that abstract knowledge about internal states is inherently valuable because it is linked to desired forms of personhood, but also concerned about the limits of technical metaphors to capture aspects of lived experience and the flattening and homogenization of affect that might accompany the practices such metaphors help to enact. I analyze alternative interpretations of prescribed metaphors as well as the spontaneous metaphors used by youth to talk about their emotions and experiences of distress, in an effort to think through the politics and poetics of emotion metaphors in the context of an evidence-based psychotherapy for young people.

Relative importance of speech and voice features in the classification of schizophrenia and depression

Speech is a promising biomarker for schizophrenia spectrum disorder (SSD) and major depressive disorder (MDD). This proof of principle study investigates previously studied speech acoustics in combination with a novel application of voice pathology features as objective and reproducible classifiers for depression, schizophrenia, and healthy controls (HC). Speech and voice features for classification were calculated from recordings of picture descriptions from 240 speech samples (20 participants with SSD, 20 with MDD, and 20 HC each with 4 samples). Binary classification support vector machine (SVM) models classified the disorder groups and HC. For each feature, the permutation feature importance was calculated, and the top 25% most important features were used to compare differences between the disorder groups and HC including correlations between the important features and symptom severity scores. Multiple kernels for SVM were tested and the pairwise models with the best performing kernel (3-degree polynomial) were highly accurate for each classification: 0.947 for HC vs. SSD, 0.920 for HC vs. MDD, and 0.932 for SSD vs. MDD. The relatively most important features were measures of articulation coordination, number of pauses per minute, and speech variability. There were moderate correlations between important features and positive symptoms for SSD. The important features suggest that speech characteristics relating to psychomotor slowing, alogia, and flat affect differ between HC, SSD, and MDD.

Multimodal mental health assessment with remote interviews using facial, vocal, linguistic, and cardiovascular patterns

Objective

The current clinical practice of psychiatric evaluation suffers from subjectivity and bias, and requires highly skilled professionals that are often unavailable or unaffordable. Objective digital biomarkers have shown the potential to address these issues. In this work, we investigated whether behavioral and physiological signals, extracted from remote interviews, provided complimentary information for assessing psychiatric disorders.

Methods

Time series of multimodal features were derived from four conceptual modes: facial expression, vocal expression, linguistic expression, and cardiovascular modulation. The features were extracted from simultaneously recorded audio and video of remote interviews using task-specific and foundation models. Averages, standard deviations, and hidden Markov model-derived statistics of these features were computed from 73 subjects. Four binary classification tasks were defined: detecting 1) any clinically-diagnosed psychiatric disorder, 2) major depressive disorder, 3) self-rated depression, and 4) self-rated anxiety. Each modality was evaluated individually and in combination.

Results

Statistically significant feature differences were found between controls and subjects with mental health conditions. Correlations were found between features and self-rated depression and anxiety scores. Visual heart rate dynamics achieved the best unimodal performance with areas under the receiver-operator curve (AUROCs) of 0.68-0.75 (depending on the classification task). Combining multiple modalities achieved AUROCs of 0.72-0.82. Features from task-specific models outperformed features from foundation models.

Conclusion

Multimodal features extracted from remote interviews revealed informative characteristics of clinically diagnosed and self-rated mental health status.

Significance

The proposed multimodal approach has the potential to facilitate objective, remote, and low-cost assessment for low-burden automated mental health services.

Clinical specificity profile for novel rapid acting antidepressant drugs

Mood disorders are recurrent/chronic diseases with variable clinical remission rates. Available antidepressants are not effective in all patients and often show a relevant response latency, with a range of adverse events, including weight gain and sexual dysfunction. Novel rapid agents were developed with the aim of overcoming at least in part these issues. Novel drugs target glutamate, gamma-aminobutyric acid, orexin, and other receptors, providing a broader range of pharmacodynamic mechanisms, that is, expected to increase the possibility of personalizing treatments on the individual clinical profile. These new drugs were developed with the aim of combining a rapid action, a tolerable profile, and higher effectiveness on specific symptoms, which were relatively poorly targeted by standard antidepressants, such as anhedonia and response to reward, suicidal ideation/behaviours, insomnia, cognitive deficits, and irritability. This review discusses the clinical specificity profile of new antidepressants, namely 4-chlorokynurenine (AV-101), dextromethorphan-bupropion, pregn-4-en-20-yn-3-one (PH-10), pimavanserin, PRAX-114, psilocybin, esmethadone (REL-1017/dextromethadone), seltorexant (JNJ-42847922/MIN-202), and zuranolone (SAGE-217). The main aim is to provide an overview of the efficacy/tolerability of these compounds in patients with mood disorders having different symptom/comorbidity patterns, to help clinicians in the optimization of the risk/benefit ratio when prescribing these drugs.

Integrative bioinformatics and artificial intelligence analyses of transcriptomics data identified genes associated with major depressive disorders including NRG1

Major depressive disorder (MDD) is a common mental disorder and is amongst the most prevalent psychiatric disorders. MDD remains challenging to diagnose and predict its onset due to its heterogeneous phenotype and complex etiology. Hence, early detection using diagnostic biomarkers is critical for rapid intervention. In this study, a mixture of AI and bioinformatics were used to mine transcriptomic data from publicly available datasets including 170 MDD patients and 121 healthy controls. Bioinformatics analysis using gene set enrichment analysis (GSEA) and machine learning (ML) algorithms were applied. The GSEA revealed that differentially expressed genes in MDD patients are mainly enriched in pathways related to immune response, inflammatory response, neurodegeneration pathways and cerebellar atrophy pathways. Feature selection methods and ML provided predicted models based on MDD-altered genes with ≥75% of accuracy. The integrative analysis between the bioinformatics and ML approaches identified ten key MDD-related biomarkers including NRG1, CEACAM8, CLEC12B, DEFA4, HP, LCN2, OLFM4, SERPING1, TCN1 and THBS1. Among them, NRG1, active in synaptic plasticity and neurotransmission, was the most robust and reliable to distinguish between MDD patients and healthy controls amongst independent external datasets consisting of a mixture of populations. Further evaluation using saliva samples from an independent cohort of MDD and healthy individuals confirmed the upregulation of NRG1 in patients with MDD compared to healthy controls. Functional mapping to the human brain regions showed NRG1 to have high expression in the main subcortical limbic brain regions implicated in depression. In conclusion, integrative bioinformatics and ML approaches identified putative non-invasive diagnostic MDD-related biomarkers panel for the onset of depression.

Online speech assessment of the psychotic spectrum: Exploring the relationship between overlapping acoustic markers of schizotypy, depression and anxiety

BACKGROUND

Remote assessment of acoustic alterations in speech holds promise to increase scalability and validity in research across the psychosis spectrum. A feasible first step in establishing a procedure for online assessments is to assess acoustic alterations in psychometric schizotypy. However, to date, the complex relationship between alterations in speech related to schizotypy and those related to comorbid conditions such as symptoms of depression and anxiety has not been investigated. This study tested whether (1) depression, generalized anxiety and high psychometric schizotypy have similar voice characteristics, (2) which acoustic markers of online collected speech are the strongest predictors of psychometric schizotypy, (3) whether including generalized anxiety and depression symptoms in the model can improve the prediction of schizotypy.

METHODS

We collected cross-sectional, online-recorded speech data from 441 participants, assessing demographics, symptoms of depression, generalized anxiety and psychometric schizotypy.

RESULTS

Speech samples collected online could predict psychometric schizotypy, depression, and anxiety symptoms with weak to moderate predictive power, and with moderate and good predictive power when basic demographic variables were added to the models. Most influential features of these models largely overlapped. The predictive power of speech marker-based models of schizotypy significantly improved after including symptom scores of depression and generalized anxiety in the models (from R2 = 0.296 to R2 = 0. 436).

CONCLUSIONS

Acoustic features of online collected speech are predictive of psychometric schizotypy as well as generalized anxiety and depression symptoms. The acoustic characteristics of schizotypy, depression and anxiety symptoms significantly overlap. Speech models that are designed to predict schizotypy or symptoms of the schizophrenia spectrum might therefore benefit from controlling for symptoms of depression and anxiety.

Mental Gravity: Depression as Spacetime Curvature of the Self, Mind, and Brain

The principle of mental gravity contends that the mind uses physical gravity as a mental model or simulacrum to express the relation between the inner self and the outer world in terms of "UP"-ness and "DOWN"-ness. The simulation of increased gravity characterises a continuum of mental gravity which states includes depression as the paradigmatic example of being down, low, heavy, and slow. The physics of gravity can also be used to model spacetime curvature in depression, particularly gravitational time dilation as a property of MG analogous to subjective time dilation (i.e., the slowing of temporal flow in conscious experience). The principle has profound implications for the Temporo-spatial Theory of Consciousness (TTC) with regard to temporo-spatial alignment that establishes a "world-brain relation" that is centred on embodiment and the socialisation of conscious states. The principle of mental gravity provides the TTC with a way to incorporate the structure of the world into the structure of the brain, conscious experience, and thought. In concert with other theories of cognitive and neurobiological spacetime, the TTC can also work towards the "common currency" approach that also potentially connects the TTC to predictive processing frameworks such as free energy, neuronal gauge theories, and active inference accounts of depression. It gives the up/down dimension of space, as defined by the gravitational field, a unique status that is connected to both our embodied interaction with the physical world, and also the inverse, reflective, emotional but still embodied experience of ourselves.

On the Origins of MAOI Misconceptions: Reaffirming their Role in Melancholic Depression

The first monoamine oxidase inhibitors (MAOIs) used for the treatment of depression in the 1950-60s were credited with treating severe melancholic depression (MeD) successfully and greatly reducing the need for electroconvulsive therapy (ECT). Following the hiatus caused by the then ill-understood cheese reaction, MAOI use was relegated to atypical and treatment-resistant depressions only, based on data from insufficiently probing research studies suggesting their comparatively lesser effectiveness in MeD. The siren attraction of new 'better' drugs with different mechanisms amplified this trend. Following a re-evaluation of the data, we suggest that MAOIs are effective in MeD. Additionally, the broad unitary conceptualisation of major depressive disorder (MDD) in the DSM model diminished the chance of demonstrating distinctive responses to different antidepressant drugs (ADs) such as SSRIs, TCAs, and MAOIs, thereby further reducing the interest in MAOIs. More reliable categorical distinction of MeD, disentangling it from MDD, may be possible if more sensitive measuring instruments (CORE, SMPI) are used. We suggest these issues will benefit from re-appraisement via an inductive reasoning process within a binary (rather than a unitary) model for defining the different depressive disorders, allowing for the use of more reliable diagnostic criteria for MeD in particular. We conclude that MAOIs remain essential for, inter alia, TCA-resistant MeD, and should typically be used prior to ECT; additionally, they have a role in maintaining remission in cases treated with ECT (and ketamine/esketamine). We suggest that MAOIs should be utilized earlier in treatment algorithms and with greater regularity than is presently the case.

Motor Decision-Making as a Common Denominator in Motor Pathology and a Possible Rehabilitation Target

Despite the substantial progress in motor rehabilitation, patient involvement and motivation remain major challenges. They are typically addressed with communicational and environmental strategies, as well as with improved goal-setting procedures. Here we suggest a new research direction and framework involving Neuroeconomics principles to investigate the role of Motor Decision-Making (MDM) parameters in motivational component and motor performance in rehabilitation. We argue that investigating NE principles could bring new approaches aimed at increasing active patient engagement in the rehabilitation process by introducing more movement choice, and adapting existing goal-setting procedures. We discuss possible MDM implementation strategies and illustrate possible research directions using examples of stroke and psychiatric disorders.

Resolving heterogeneity in depression using individualized structural covariance network analysis

BACKGROUND

Elucidating individual aberrance is a critical first step toward precision medicine for heterogeneous disorders such as depression. The neuropathology of depression is related to abnormal inter-regional structural covariance indicating a brain maturational disruption. However, most studies focus on group-level structural covariance aberrance and ignore the interindividual heterogeneity. For that reason, we aimed to identify individualized structural covariance aberrance with the help of individualized differential structural covariance network (IDSCN) analysis.

METHODS

T1-weighted anatomical images of 195 first-episode untreated patients with depression and matched healthy controls (n = 78) were acquired. We obtained IDSCN for each patient and identified subtypes of depression based on shared differential edges.

RESULTS

As a result, patients with depression demonstrated tremendous heterogeneity in the distribution of differential structural covariance edges. Despite this heterogeneity, altered edges within subcortical-cerebellum network were often shared by most of the patients. Two robust neuroanatomical subtypes were identified. Specifically, patients in subtype 1 often shared decreased motor network-related edges. Patients in subtype 2 often shared decreased subcortical-cerebellum network-related edges. Functional annotation further revealed that differential edges in subtype 2 were mainly implicated in reward/motivation-related functional terms.

CONCLUSIONS

In conclusion, we investigated individualized differential structural covariance and identified that decreased edges within subcortical-cerebellum network are often shared by patients with depression. The identified two subtypes provide new insights into taxonomy and facilitate potential clues to precision diagnosis and treatment of depression.

Attenuated post-movement beta rebound reflects psychomotor alterations in major depressive disorder during a simple visuomotor task: a MEG study

BACKGROUND

Psychomotor alterations are a common symptom in patients with major depressive disorder (MDD). The primary motor cortex (M1) plays a vital role in the mechanism of psychomotor alterations. Post-movement beta rebound (PMBR) in the sensorimotor cortex is abnormal in patients with motor abnormalities. However, the changes in M1 beta rebound in patients with MDD remain unclear. This study aimed to primarily explore the relationship between psychomotor alterations and PMBR in MDD.

METHODS

One hundred thirty-two subjects were enrolled in the study, comprising 65 healthy controls (HCs) and 67 MDD patients. All participants performed a simple right-hand visuomotor task during MEG scanning. PMBR was measured in the left M1 at the source reconstruction level with the time-frequency analysis method. Retardation factor scores and neurocognitive test performance, including the Digit Symbol Substitution Test (DSST), the Making Test Part A (TMT-A), and the Verbal Fluency Test (VFT), were used to measure psychomotor functions. Pearson correlation analyses were used to assess relationships between PMBR and psychomotor alterations in MDD.

RESULTS

The MDD group showed worse neurocognitive performance than the HC group in all three neurocognitive tests. The PMBR was diminished in patients with MDD compared to HCs. In a group of MDD patients, the reduced PMBR was negatively correlated with retardation factor scores. Further, there was a positive correlation between the PMBR and DSST scores. PMBR is negatively associated with the TMT-A scores.

CONCLUSION

Our findings suggested that the attenuated PMBR in M1 could illustrate the psychomotor disturbance in MDD, possibly contributing to clinical psychomotor symptoms and deficits of cognitive functions.

Common and unique alterations of functional connectivity in major depressive disorder and bipolar disorder

OBJECTIVE

Major depressive disorder (MDD) and bipolar disorder (BD) are considered whole-brain disorders with some common clinical and neurobiological features. It is important to investigate neural mechanisms to distinguish between the two disorders. However, few studies have explored the functional dysconnectivity between the two disorders from the whole brain level.

METHODS

In this study, 117 patients with MDD, 65 patients with BD, and 116 healthy controls completed resting-state functional magnetic resonance imaging (R-fMRI) scans. Both edge-based network construction and large-scale network analyses were applied.

RESULTS

Results found that both the BD and MDD groups showed decreased FC in the whole brain network. The shared aberrant network across patients involves the visual network (VN), sensorimotor network (SMN), dorsal attention network (DAN), and ventral attention network (VAN), which is related to the processing of external stimuli. The default mode network (DMN) and the limbic network (LN) abnormalities were only found in patients with MDD. Furthermore, results showed the highest decrease in edges of patients with MDD in between-network FC in SMN-VN, whereas in VAN-VN of patients with BD.

CONCLUSIONS

Our findings indicated that both MDD and BD are extensive abnormal brain network diseases, mainly aberrant in those brain networks correlated to the processing of external stimuli, especially the attention network. Specific altered functional connectivity also was found in MDD and BD groups, respectively. These results may provide possible trait markers to distinguish the two disorders.

Manipulating facial musculature with functional electrical stimulation as an intervention for major depressive disorder: a focused search of literature for a proposal

BACKGROUND

Major Depressive Disorder (MDD) is associated with interoceptive deficits expressed throughout the body, particularly the facial musculature. According to the facial feedback hypothesis, afferent feedback from the facial muscles suffices to alter the emotional experience. Thus, manipulating the facial muscles could provide a new "mind-body" intervention for MDD. This article provides a conceptual overview of functional electrical stimulation (FES), a novel neuromodulation-based treatment modality that can be potentially used in the treatment of disorders of disrupted brain connectivity, such as MDD.

METHODS

A focused literature search was performed for clinical studies of FES as a modulatory treatment for mood symptoms. The literature is reviewed in a narrative format, integrating theories of emotion, facial expression, and MDD.

RESULTS

A rich body of literature on FES supports the notion that peripheral muscle manipulation in patients with stroke or spinal cord injury may enhance central neuroplasticity, restoring lost sensorimotor function. These neuroplastic effects suggest that FES may be a promising innovative intervention for psychiatric disorders of disrupted brain connectivity, such as MDD. Recent pilot data on repetitive FES applied to the facial muscles in healthy participants and patients with MDD show early promise, suggesting that FES may attenuate the negative interoceptive bias associated with MDD by enhancing positive facial feedback. Neurobiologically, the amygdala and nodes of the emotion-to-motor transformation loop may serve as potential neural targets for facial FES in MDD, as they integrate proprioceptive and interoceptive inputs from muscles of facial expression and fine-tune their motor output in line with socio-emotional context.

CONCLUSIONS

Manipulating facial muscles may represent a mechanistically novel treatment strategy for MDD and other disorders of disrupted brain connectivity that is worthy of investigation in phase II/III trials.

Spontaneous beta power, motor-related beta power and cortical thickness in major depressive disorder with psychomotor disturbance

INTRODUCTION

The psychomotor disturbance is a common symptom in patients with major depressive disorder (MDD). The neurological mechanisms of psychomotor disturbance are intricate, involving alterations in the structure and function of motor-related regions. However, the relationship among changes in the spontaneous activity, motor-related activity, local cortical thickness, and psychomotor function remains unclear.

METHOD

A total of 140 patients with MDD and 68 healthy controls performed a simple right-hand visuomotor task during magnetoencephalography (MEG) scanning. All patients were divided into two groups according to the presence of psychomotor slowing. Spontaneous beta power, movement-related beta desynchronization (MRBD), absolute beta power during movement and cortical characteristics in the bilateral primary motor cortex were compared using general linear models with the group as a fixed effect and age as a covariate. Finally, the moderated mediation model was tested to examine the relationship between brain metrics with group differences and psychomotor performance.

RESULTS

The patients with psychomotor slowing showed higher spontaneous beta power, movement-related beta desynchronization and absolute beta power during movement than patients without psychomotor slowing. Compared with the other two groups, significant decreases were found in cortical thickness of the left primary motor cortex in patients with psychomotor slowing. Our moderated mediation model showed that the increased spontaneous beta power indirectly affected impaired psychomotor performance by abnormal MRBD, and the indirect effects were moderated by cortical thickness.

CONCLUSION

These results suggest that patients with MDD have aberrant cortical beta activity at rest and during movement, combined with abnormal cortical thickness, contributing to the psychomotor disturbance observed in this patient population.

Eight-week antidepressant treatment changes intrinsic functional brain topology in first-episode drug-naïve patients with major depressive disorder

BACKGROUND

A recent study revealed disrupted topological organization of whole-brain networks in patients with major depressive disorder (MDD); however, these results were mostly driven by recurrent MDD patients, rather than first-episode drug-naïve (FEDN) patients. Furthermore, few longitudinal studies have explored the effects of antidepressant therapy on the topological organization of whole-brain networks.

METHODS

We collected clinical and neuroimaging data from 159 FEDN MDD patients and 152 normal controls (NCs). A total of 115 MDD patients completed an eight-week antidepressant treatment procedure. Topological features of brain networks were calculated using graph theory-based methods and compared between FEDN MDD patients and NCs, as well as before and after treatment.

RESULTS

Decreased global efficiency, local efficiency, small-worldness, and modularity were found in pretreatment FEDN MDD patients compared with NCs. Nodal degrees, betweenness, and efficiency decreased in several networks compared with NCs. After antidepressant treatment, the global efficiency increased, while the local efficiency, the clustering coefficient of the network, the path length, and the normalized characteristic path length decreased. Moreover, the reduction rate of the normalized characteristic path length was positively correlated with the reduction rate of retardation factor scores.

LIMITATIONS

The interaction effects of groups and time on the topological features were not explored because of absence of the eighth-week data of NC group.

CONCLUSIONS

The topological architecture of functional brain networks is disrupted in FEDN MDD patients. After antidepressant therapy, the global efficiency shifted toward recovery, but the local efficiency deteriorated, suggesting a correlation between recovery of retardation symptoms and global efficiency.

Using different types of visual reaction time measurements for assessing cognitive difficulties in depression

There is a need for objective, easy and relatively short methods to diagnose cognition in depression. We have constructed a set of simple visual tasks using three different ways of speed measuring: paper-pencil-based, computer-based, and eye-tracking based. We used a single case design with 22 participants. A clinical group counted 11 patients with major depression examined two times (first examination without medication and second after three months of medical treatment) together with a group of 11 matched healthy controls. Cognitive difficulties were observable in all the checked levels of performance. The weakest in all tasks were patients before medication, some improvement was observed after medical treatment, but not matching the level of healthy controls. Cognitive difficulties were not eliminated by medical treatment as quickly as emotional disturbances were. The observed difficulties could be interpreted in terms of psychomotor retardation, a typical symptom in depression, which proved to be mainly cognitive as the analysis of differences in reaction times and the first saccade latencies concluded. The analysis of simple visual reaction times on several stages turned out to be a promising method to measure the cognitive state in persons with mood disorders and cognitive convalescence during major depressive disorder treatment.

Circadian rhythm biomarker from wearable device data is related to concurrent antidepressant treatment response

Major depressive disorder (MDD) is associated with circadian rhythm disruption. Yet, no circadian rhythm biomarkers have been clinically validated for assessing antidepressant response. In this study, 40 participants with MDD provided actigraphy data using wearable devices for one week after initiating antidepressant treatment in a randomized, double-blind, placebo-controlled trial. Their depression severity was calculated pretreatment, after one week and eight weeks of treatment. This study assesses the relationship between parametric and nonparametric measures of circadian rhythm and change in depression. Results show significant association between a lower circadian quotient (reflecting less robust rhythmicity) and improvement in depression from baseline following first week of treatment (estimate = 0.11, F = 7.01, P = 0.01). There is insufficient evidence of an association between circadian rhythm measures acquired during the first week of treatment and outcomes after eight weeks of treatment. Despite this lack of association with future treatment outcome, this scalable, cost-effective biomarker may be useful for timely mental health care through remote monitoring of real-time changes in current depression.

Physical fitness is associated with neural activity during working memory performance in major depressive disorder

BACKGROUND

Deficits in cognition like working memory (WM) are highly prevalent symptoms related to major depressive disorder (MDD). Neuroimaging studies have described frontoparietal abnormalities in patients with MDD as a basis for these deficits. Based on research in healthy adults, it is hypothesized that increased physical fitness might be a protective factor for these deficits in MDD. However, the relationship between physical fitness and WM-related neural activity and performance has not been tested in MDD, to date. Understanding these associations could inform the development of physical exercise interventions in MDD.

METHODS

Within a larger project, 111 (53female) MDD outpatients and 56 (34female) healthy controls performed an n-back task (0-, 1-, 2-, 3-back) during functional Magnetic Resonance Imaging. Physical fitness from a graded exercise test on a cycle ergometer was performed by 106 MDD patients.

RESULTS

Patients showed reduced performance particularly at high loads of the n-back WM task and prolonged reaction times at all n-back loads. A whole-brain interaction analysis of group by WM load revealed reduced neural activity in six frontoparietal clusters at medium and high WM loads in MDD patients compared to healthy controls. Analysis of covariance within the MDD sample showed that physical fitness was associated with neural activity in right and left superior parietal lobules. Externally defined Regions of Interest confirmed this analysis.

CONCLUSIONS

Results indicate frontoparietal hypoactivity in MDD at high demands, arguing for decreased WM capacity. We demonstrate a parietal fitness correlate which could be used to guide future research on effects of exercise on cognitive functioning in MDD.

Suicide risk stratification among major depressed patients based on a machine learning approach and whole-brain functional connectivity

BACKGROUND

Suicide risk stratification and individual-level prediction among major depressive disorder (MDD) is important but unrecognized. Here, we construct models to detect suicidality in MDD using machine learning (ML) and whole-brain functional connectivity (FC).

METHODS

A cross-sectional assessment was conducted on 200 subjects, including 126 MDD with high suicide risk (HSR; 73 patients with suicidal ideation [SI], 53 patients with suicidal attempts [SA]), 36 patients with low suicide risk (LSR) and 38 healthy controls (HCs). Whole-brain FC features were calculated, the least absolute shrinkage and selection operator (LASSO) method was used for feature selection. A support vector machine (SVM) was performed to build models to distinguish MDD from HCs, and for suicide risk stratification among MDD. Leave-one-out cross-validation (LOOCV) was performed for validation.

RESULTS

The models constructed using SVM on whole-brain FC had powerful classification efficiency in screening MDD from HCs (accuracy = 88.50 %), and in suicide risk stratification among MDD patients (with accuracy = 84.56 % and 74.60 % in classifying patients with HSR or LSR, and SA or SI, respectively). Subsequent analysis demonstrated that intra-network dysconnectivity in the sensorimotor network and inter-network dysconnectivity between the default and dorsal attention network could characterize HSR and SA in MDD, separately.

LIMITATIONS

This study was a single center cohort study without external validation.

CONCLUSION

These findings indicate ML approaches are useful in suicide risk stratification among MDD based on whole-brain FC, which may help to identify individuals with different suicide risks in MDD and provide an individual-level prediction.

Using type-2 fuzzy ontology to improve semantic interoperability for healthcare and diagnosis of depression

Ontology enhances semantic interoperability through integrating health data from heterogeneous sources and sharing information in a meaningful way. In the field of smart health services, semantic interoperability means the exchange and interpretation of data without ambiguity and uncertainty. However, existing classical ontologies are not able to represent vague and uncertain knowledge, especially in contexts of mental health disorders which are associated with varying degrees of uncertainty and inaccuracy of diagnosis, and in this case, the treatment is a complex and common mental process necessitating to share information accurately and unambiguously. Type-2 fuzzy set theory can offer a fruitful solution in order to control uncertainty or express ambiguous concepts in a dynamic and complex environment such as healthcare systems. Herein, a semantic framework for healthcare, and also monitoring mental health disorders using type-2 fuzzy set theory based on the Internet of Thing (IoT) is suggested, in which all depression-related concepts are semantically annotated to share detailed information with the treatment staff. This framework not only paved the way to increasing the accuracy of medical diagnosis and decision-making but also provides the possibility of inference and semantic reasoning using the languages of SPARQL query and DL query.

Facebook addiction and its related factors among medical students; a cross- sectional study in Bangladesh

There is mounting evidence that Facebook Addiction is associated with poor mental health, physical symptoms, social dysfunction, and despair among the adolescent and youth population. The current study set out to identify the prevalence of Facebook Addiction among Bangladeshi medical students as well as its influencing factors. This cross-sectional survey was conducted on 720 randomly selected medical students from eight public medical colleges from January to June 2022. Data were obtained using a semi- structured, self-reported questionnaire and analyzed using the SPSS v.23 programs. The Bergen Facebook Addiction Scale BFAS was used to assess Facebook Addiction, while the Generalized Anxiety Disorder GAD-7, Patient Health Questionnaire PHQ-9, Perceived Stress Scale PSS10, Chen Internet Addiction Scale CIAS, and Pittsburg Sleep Quality Index PSQI was used to assess anxiety, depression, perceived stress, internet addiction, and sleep quality. Binary logistic regression was used to evaluate the influence of several demographic, psychological, and behavioral characteristics on the likelihood of respondents being addicted to Facebook. Facebook Addiction was observed in 29.4% of medical students. According to data, 63.7% of medical students reported mild to severe anxiety, 29.3% moderate to severe depression, and 84.9% moderate to high perceived stress. Lack of personal income [OR with (95% CI), 1.82 (1.13, 2.96)], poor academic performance [2.46 (1.45, 4.15)], moderate anxiety [2.45 (1.22, 4.92)], moderate perceived stress [5.87 (1.92, 17.95)], and moderately severe depression [2.62 (.97, 7.08)] were all found to play a significant role in the development of Facebook Addiction. However, living with parents [OR with (95% CI), .37 (.14, .95)] and positive family relationships [.40 (.18, .87)] reduces the likelihood of becoming addicted to Facebook. An integrated participative Behavioral and psychological intervention should be devised to reduce the risks of Facebook addiction in medical students while also improving their mental health-related quality of life.

Variability and concordance among indices of brain activity in major depressive disorder with suicidal ideation: A temporal dynamics resting-state fMRI analysis

OBJECTIVE

The resting-state functional magnetic resonance imaging (rs-fMRI) have been used to explore functional abnormality of the brain in MDD patients with suicidal ideation (SI). However, few studies reported the variability and concordance of alterations of rs-fMRI indices in MDD with SI. In this study, we aimed to explore the variability and concordance of alterations of rs-fMRI indices in MDD with SI.

METHODS

A sliding window analysis was performed among 36 MDD patients with SI, 66 MDD patients without SI (NSI), and 50 healthy controls (HCs). Furthermore, the correlation between voxel-wise concordance and cognitive function was examined in the SI group.

RESULTS

The SI group had a lower dynamics degree centrality (dDC) value than the NSI group in left inferior occipital gyrus, and a lower voxel mirrored homotopic connectivity (dVMHC) value than the NSI group in the right and left inferior occipital gyrus. The mean values of volume wise concordance of HCs group shown higher than SI group and NSI group. SI group revealed decreased voxel-wise concordance in right cerebellum, left fusiform gyrus, left lingual gyrus, right middle temporal gyrus, left postcentral gyrus, and right supplementary motor area compared to NSI group. Moreover, the voxel-wise concordance of left middle occipital gyrus was negatively correlated with verbal learning and memory and working memory in the SI group.

LIMITATION

This is a cross-sectional analysis, limiting causal inferences.

CONCLUSIONS

The abnormal voxel-wise concordance of left middle occipital gyrus could be useful in understanding the pathophysiology of MDD patients with SI.

Sleep Quality and Self-Reported Symptoms of Anxiety and Depression Are Associated with Physical Activity in Patients with Severe COPD

Sleep quantity, quality and symptoms of depression or anxiety potentially affect the level of daily physical activity (PAL) and plausibly counteracts benefits from pulmonary rehabilitation programs. Their collective impact on PAL is sparsely investigated, particularly in patients with severely progressed chronic obstructive pulmonary disease (COPD). Aim: To investigate if sleep quantity, quality and symptoms from self-reported hospital anxiety and depression scores (HADS) are associated with PAL. Methods: In this exploratory cross-sectional study data were analysed from 148 participants with COPD; GOLD grade II-IV; GOLD group B to D (52% female, mean 69.7 ± SD of 8.4 years, FEV1% predicted 33.6 ± 10.9, 6MWD 327 ± 122 m, CAT 20 ± 7 points), eligible for conventional outpatient hospital-based pulmonary rehabilitation. Participants had sleep and PAL measured 24 h per day for five consecutive days with an activPAL monitor. Adjusted negative binomial regression was applied to investigate the associations with PAL. Results: Participants walked median (25th, 75th percentile) of 2358 (1325.75; 3822.25) steps per day and 14% walked >5000 steps per day on average. Time in bed (TIB) were a median (25th, 75th percentile) of 8.3 (7.1; 9.7) hours and numbers of nocturnal sleeping bouts (NSB) were 1.5 (0.8; 3), Anxiety (HADS-A) and depression (HADS-D) scores were median (25th, 75th percentile) of 5 (3; 8) points and 3 (2; 6) points, respectively, whereof 29% (HADS-A) and 15% (HADS-D) reported scores ≥8 points indicating significant symptoms. The fully adjusted rate ratio (RR) for steps per day for TIB (hours) [RR 0.97 (95% CI: 0.92; 1.02)], NSB (numbers) [RR 1.02 (95% CI: 0.97; 1.07)] were not significantly associated with number of steps per day, while there was a significantly association with number of steps per day for HADS-A [RR 1.04 (95% CI: 1.01; 1.07)] and HADS-D [RR 0.95 (95% CI: 0.91; 0.99)]. Conclusion: This exploratory cross-sectional study found a statistically significant association between HADS-A and HADS-D with numbers of steps per day in patients with severe COPD.

Gradient boosting decision-tree-based algorithm with neuroimaging for personalized treatment in depression

Introduction

Pretreatment positron emission tomography (PET) with 2-deoxy-2-[18F]fluoro-D-glucose (FDG) and magnetic resonance spectroscopy (MRS) may identify biomarkers for predicting remission (absence of depression). Yet, no such image-based biomarkers have achieved clinical validity. The purpose of this study was to identify biomarkers of remission using machine learning (ML) with pretreatment FDG-PET/MRS neuroimaging, to reduce patient suffering and economic burden from ineffective trials.

Methods

This study used simultaneous PET/MRS neuroimaging from a double-blind, placebo-controlled, randomized antidepressant trial on 60 participants with major depressive disorder (MDD) before initiating treatment. After eight weeks of treatment, those with ≤ 7 on 17-item Hamilton Depression Rating Scale were designated a priori as remitters (free of depression, 37%). Metabolic rate of glucose uptake (metabolism) from 22 brain regions were acquired from PET. Concentrations (mM) of glutamine and glutamate and gamma-aminobutyric acid (GABA) in anterior cingulate cortex were quantified from MRS. The data were randomly split into 67% train and cross-validation (n = 40), and 33% test (n = 20) sets. The imaging features, along with age, sex, handedness, and treatment assignment (selective serotonin reuptake inhibitor or SSRI vs. placebo) were entered into the eXtreme Gradient Boosting (XGBoost) classifier for training.

Results

In test data, the model showed 62% sensitivity, 92% specificity, and 77% weighted accuracy. Pretreatment metabolism of left hippocampus from PET was the most predictive of remission.

Conclusions

The pretreatment neuroimaging takes around 60 minutes but has potential to prevent weeks of failed treatment trials. This study effectively addresses common issues for neuroimaging analysis, such as small sample size, high dimensionality, and class imbalance.

Characteristics of psychomotor retardation distinguishes patients with depression using multichannel near-infrared spectroscopy and finger tapping task

BACKGROUND

Psychomotor retardation (PMR) is frequently noted as a characteristic feature of major depressive disorder (MDD). In patients with depression, it is characterized by retardation of speech, emotion, thinking, and cognition. This study explored the activation pattern of the prefrontal cortex (PFC) during the finger-tapping task (FTT) in subjects with MDD, aiming to provide additional understanding on the connection between PMR and PFC activation pattern in depression through the use of near-Infrared Spectroscopy (NIRS). We hypothesized that, through use of NIRS during the FTT, motor retardation in depression would generate a distinct PFC activation pattern, allowing for differentiation between patients with MDD and healthy controls (HCs).

METHODS

Thirty-five patients with MDD and thirty-nine HCs underwent NIRS evaluation during performance of the FTT. The FTT included both left-finger tapping and right-finger tapping performed by a computer screen. Each participant was assessed using a 45-channel NIRS and various clinical scales.

FINDINGS

During the left-FTT, the left orbitofrontal cortex (OFC) showed higher oxy-hemoglobin (Oxy-Hb) activation in the MDD group when compared to the HCs. During the right-FTT, the right dorsolateral prefrontal cortex (DLPFC) demonstrated lower Oxy-Hb activation, and the dorsomedial prefrontal cortex (DMPFC) showed higher Oxy-Hb activation in the MDD group versus the HC group.

CONCLUSION

Our results demonstrated different activation patterns of the PFC between the MDD and HC groups, using FTT as a motor performance task. In particular, the OFC, the DLPFC and the DMPFC areas hold promise as new useful sites for such differentiation in future investigations.

Motor alterations in depression and anxiety disorders: A systematic review and meta-analysis

BACKGROUND

Psychomotor retardation has long been recognized as a major feature of depression, and anxiety disorders have been linked with freeze and flight motor responses. This systematic review and meta-analysis aimed a) to synthesize available evidence of motor alterations comparing individuals with depression and anxiety disorders to healthy individuals and b) to evaluate the effect of experimental manipulations of motor displays within these clinical groups.

METHOD

The databases PubMed and PsycINFO were searched for studies either assessing motor differences between clinical and healthy control groups or manipulating the motor system within a clinical group.

RESULTS

The literature search yielded 87 relevant papers, comprising 82 studies comparing a clinical group to a healthy group and 5 studies investigating motor manipulations within a clinical sample. The results of the meta-analysis (K = 71) indicated a statistically significant combined estimate of differences between healthy and clinical groups (g = 0.38 [0.31, 0.45], adjusted for publication bias g = 0.26 [0.19, 0.33]) of a small size. This effect did not vary according to type of disorder (anxiety vs. depression, p = .468). From a narrative review of experimental studies within clinical groups, four out of five studies reported statistically significant effects of manipulating the motor system on affective outcomes.

DISCUSSION

This synthesis adds to the accumulating empirical evidence of motor alterations in depression and anxiety disorders. Future research will need to investigate how individuals suffering from depression or anxiety disorders could benefit from psychological, behavioral, and physical interventions directly aimed at the motor system.

Waking inactivity as a welfare indicator in laboratory mice: investigating postures, facial expressions and depression-like states

Animal welfare assessment relies on valid and practical indicators of affect. In mice, the most widely used research vertebrates, lying still with eyes open, inactive-but-awake (IBA) in the home cage, has potential to be one such indicator. IBA is elevated in barren, conventional housing compared with well-resourced, enriched housing, and predicts immobility in Forced Swim Tests, a common measure of 'helplessness' in depression research. In Experiment 1, using females from three strains (C57BL/6, Balb/c and DBA/2), we first replicated past findings, confirming higher levels of IBA in conventional cages and a positive relationship between IBA and helplessness. We then extended this research to three other signs of depression: changes in weight and sleep, and reduced hippocampal volume. Here, IBA positively covaried with body mass index, with sleep in DBA/2s and conventionally housed BALB/cs, and negatively covaried with hippocampal volume in conventionally housed C57BL/6s. In Experiment 2, we sought to refine the phenotype of IBA to improve its accuracy as a welfare indicator. Here, scoring IBA performed in hunched postures appeared to improve its accuracy as an indicator in Balb/c mice. Additional research is now needed to further refine the phenotype of IBA and to confirm whether it reflects states consistent with depression, or instead other underlying poor welfare conditions.

An unsupervised machine learning approach using passive movement data to understand depression and schizophrenia

INTRODUCTION

Schizophrenia and Major Depressive Disorder (MDD) are highly burdensome mental disorders, with significant cost to both individuals and society. Despite these disorders representing distinct clinical categories, they are each heterogenous in their symptom profiles, with considerable transdiagnostic features. Although movement and sleep abnormalities exist in both disorders, little is known of the precise nature of these changes longitudinally. Passively-collected longitudinal data from wearable sensors is well suited to characterize naturalistic features which may cross traditional diagnostic categories (e.g., highlighting behavioral markers not captured by self-report information).

METHODS

The present analyses utilized raw minute-level actigraphy data from three diagnostic groups: individuals with schizophrenia (N = 23), individuals with depression (N = 22), and controls (N = 32), respectively, to interrogate naturalistic behavioral differences between groups. Subjects' week-long actigraphy data was processed without diagnostic labels via unsupervised machine learning clustering methods, in order to investigate the natural bounds of psychopathology. Further, actigraphic data was analyzed across time to determine timepoints influential in model outcomes.

RESULTS

We find distinct actigraphic phenotypes, which differ between diagnostic groups, suggesting that unsupervised clustering of naturalistic data aligns with existing diagnostic constructs. Further, we found statistically significant inter-group differences, with depressed persons showing the highest behavioral variability.

LIMITATIONS

However, diagnostic group differences only consider biobehavioral trends captured by raw actigraphy information.

CONCLUSIONS

Passively-collected movement information combined with unsupervised deep learning algorithms shows promise in identifying naturalistic phenotypes in individuals with mental health disorders, specifically in discriminating between MDD and schizophrenia.