The neural signature of psychomotor disturbance in depression

Transdiagnostic network alterations and associated neurotransmitter signatures across major psychiatric disorders in adolescents: Evidence from edge-centric analysis of time-varying functional brain networks

BACKGROUND

Adolescence is a pivotal phase marked by heightened vulnerability to the onset of psychiatric disorders. However, there are few transdiagnostic studies of dynamic brain networks across major psychiatric disorders during this phase.

METHODS

We collected resting-state functional MRI data from 189 adolescent patients (61 with bipolar disorder, 73 with major depressive disorder, and 55 with schizophrenia) and 181 healthy adolescents. Functional networks were constructed using a state-of-art edge-centric dynamic functional connectivity (DFC) approach.

RESULTS

Four DFC states were identified for the healthy adolescents that were related to different behavioral and cognitive terms. Disorder-related alterations were observed in two states involving motor and somatosensory processing and one state involving various cognitive functions. Regardless of the state, the three patient groups exhibited lower FC that were mainly involved in edges between different functional subsystems and were predominantly linked to regions in the somatomotor network. The patients with major depressive disorder additionally showed increased FC that were primarily linked to default mode regions. Graph-based network analysis revealed different patterns of disrupted small-world organization and altered nodal degree in the disorders in a state-dependent manner. The nodal degree alterations were correlated with the concentration of various neurotransmitters. Intriguingly, the noradrenaline concentration was engaged in the nodal degree alterations in each patient group. Finally, decreased FC involving regions in the somatomotor network showed significant correlations with clinical variables in the major depressive disorder patients.

CONCLUSION

These findings may help understand the developmental pathways associated with the heightened vulnerability to major psychiatric disorders during adolescence.

Depression is marked by differences in structural covariance between deep-brain nuclei and sensorimotor cortex

BACKGROUND

Depression impacts nearly 3% of the global adult population. Symptomatology is likely related to regions encompassing frontoparietal, somatosensory, and salience networks. Questions regarding deep brain nuclei (DBN), including the substantia nigra (STN), subthalamic nucleus (STN), and red nucleus (RN) remain unanswered.

METHODS

Using an existing structural neuroimaging dataset including 86 individuals (Baranger et al., 2021; nDEP = 39), frequentist and Bayesian logistic regressions assessed whether DBN volumes predict diagnosis, then structural covariance analyses in FreeSurfer tested diagnostic differences in deep brain volume and cortical morphometry covariance. Exploratory correlations tested relationships between implicated cortical regions and Hamilton Depression Rating Scale (HAM-D) scores.

RESULTS

Group differences emerged in deep brain/cortical covariance. Right RN volume covaried with left parietal operculum volume and central sulcus thickness, while left RN and right STN volumes covaried with right occipital pole volume. Positive relationships were observed within the unaffected group and negative relationships among those with depression. These cortical areas did not correlate with HAM-D scores. Simple DBN volumes did not predict diagnostic group.

CONCLUSION

Structural codependence between DBN and cortical regions may be important in depression, potentially for sensorimotor features. Future work should focus on causal mechanisms of DBN involvement with sensory integration.

The neurobiology of motivational anhedonia in patients with depression

Anhedonia is a core feature of depression. It contains a consummatory and a motivational aspect. Whilst much neuroimaging research in patients with depression focused on the consummatory aspect of anhedonia, less is known about its motivational aspect. This study aimed to explore the neurobiology of networks related to motivational anhedonia. Thirty-eight patients with major depressive disorder (MDD) and 19 healthy controls underwent diffusion-weighted and resting state functional magnetic resonance imaging (rs-fMRI). For assessment of motivational anhedonia, we summed the values of the CORE non-interactiveness score, and the items 1 (hopelessness) and 7 (work and activities) of the Hamilton Depression Rating Scale. Whole-brain voxel-wise statistical analysis of fractional anisotropy (FA) data was performed using Tract-Based Spatial Statistics (TBSS). Additionally, we performed a whole-brain comparison of integrated local correlation of rs-fMRI signal (LCOR), to investigate regional functional differences between patients and healthy controls. Whole brain correlations between motivational anhedonia and measures of structural and functional connectivity (FA, and LCOR) were calculated. TBSS-analyses revealed reduced FA in the left superior longitudinal fasciculus (SLF) in patients with MDD. LCOR was reduced in patients with depression in an adjacent cluster localized in bilateral precunei. Within patients, there was a positive correlation between motivational anhedonia and LCOR in the precunei and a negative correlation in bilateral sensorimotor areas. FA-values did not show significant correlations. These findings suggest that motivational anhedonia in depression is linked to alterations of functional connectivity within bilateral precunei. Observed white matter microstructural alterations in the SLF do not show such an association.

Association Between Depressive Symptoms in Spousal Caregivers and Falls in Care Recipients With Disability: A Nationwide Population-Based Cohort Study

OBJECTIVE

To investigate the association between depressive symptoms in spousal caregivers and both fall risk and the frequency of falls requiring medical treatment in care recipients with disabilities.

DESIGN

A retrospective cohort study.

SETTING

Data from the China Health and Retirement Longitudinal Study.

PARTICIPANTS

1357 patient-caregiver dyads.

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURES

The incidence of falls and the frequency of falls requiring medical treatment among care recipients.

RESULTS

The mean (standard deviation) age of care recipients was 61.6 (9.1) years, and 62.1% of them were women. After adjusting for covariates, it was found that caregiver depressive symptoms were associated with a 32% higher risk of falls (relative risk [RR], 1.32; 95% confidence interval [CI], 1.08-1.61). Moreover, caregivers who exhibited depressive symptoms only at follow-up had a RR of falls requiring medical treatment of 2.74 (95% CI, 1.28-5.88), whereas those who had depressive symptoms at both the baseline and follow-up had a RR of 2.13 (95% CI, 1.19-3.80). The likelihood ratio test showed that grouping depressive symptoms significantly improved the model fit for both fall risk (likelihood ratio [LR] χ²(3)=8.89, P=.031) and falls requiring medical treatment (LR χ²(3)=14.50, P=.002).

CONCLUSION

Caregiver depressive symptoms are significantly associated with an increased risk of falls and a higher frequency of falls requiring medical treatment among care recipients with disabilities. Addressing the mental health of caregivers may help reduce fall-related risks in this population.

Higher amplitudes of visual networks are associated with trait- but not state-depression

Despite depression being a leading cause of global disability, neuroimaging studies have struggled to identify replicable neural correlates of depression or explain limited variance. This challenge may, in part, stem from the intertwined state (current symptoms; variable) and trait (general propensity; stable) experiences of depression.Here, we sought to disentangle state from trait experiences of depression by leveraging a longitudinal cohort and stratifying individuals into four groups: those in remission ('trait depression group'), those with large longitudinal severity changes in depression symptomatology ('state depression group'), and their respective matched control groups (total analytic n = 1030). We hypothesized that spatial network organization would be linked to trait depression due to its temporal stability, whereas functional connectivity between networks would be more sensitive to state-dependent depression symptoms due to its capacity to fluctuate.We identified 15 large-scale probabilistic functional networks from resting-state fMRI data and performed group comparisons on the amplitude, connectivity, and spatial overlap between these networks, using matched control participants as reference. Our findings revealed higher amplitude in visual networks for the trait depression group at the time of remission, in contrast to controls. This observation may suggest altered visual processing in individuals predisposed to developing depression over time. No significant group differences were observed in any other network measures for the trait-control comparison, nor in any measures for the state-control comparison. These results underscore the overlooked contribution of visual networks to the psychopathology of depression and provide evidence for distinct neural correlates between state and trait experiences of depression.

Functional connectivity gradients and neurotransmitter maps among patients with mild cognitive impairment and depression symptoms

BACKGROUND

Both depressive symptoms and neurotransmitter changes affect the characteristics of functional brain networks in clinical patients. We sought to explore how brain functional grading is organized among patients with mild cognitive impairment and depressive symptoms (D-MCI) and whether changes in brain organization are related to neurotransmitter distribution.

METHODS

Using 3 T magnetic resonance imaging (MRI) we acquired functional MRI (fMRI) data from patients with D-MCI, patients with mild cognitive impairment without depression (nD-MCI), and healthy controls. We used resting-state fMRI and diffusion embedding to examine the pattern of functional connectivity gradients. We used analysis of covariance and post hoc t tests to compare the difference in functional connectivity gradients among the 3 groups. We examined the correlation between variations in functional connectivity gradients and neurotransmitter maps using the JuSpace toolbox.

RESULTS

We included 105 participants, including 31 patients with D-MCI, 40 patients with nD-MCI, and 34 healthy controls. Compared with healthy controls, both the nD-MCI and D-MCI groups showed abnormalities in the principal unimodal-transmodal gradient pattern. Compared with controls, the D-MCI group showed an increased secondary gradient in the default mode network. Differences in the functional connectivity gradients between the D-MCI and nD-MCI groups were significantly correlated with the distribution of 5-hydroxytryptamine receptor subtype 1A.

LIMITATIONS

The small sample size affects the generalizability of the results, and the neurotransmitter template is based on healthy participants, not patients.

CONCLUSION

Our results suggest that depressive symptoms cause abnormalities in the hierarchical segregation of functional brain organization among patients with MCI. Such abnormal changes may be related to the distribution of neurotransmitters.

3D-optical motion capturing examination of sensori- and psychomotor abnormalities in mental disorders: Progress and perspectives

Sensori-/psychomotor abnormalities refer to a wide range of disturbances in individual motor, affective and behavioral functions that are often observed in mental disorders. However, many of these studies have mainly used clinical rating scales, which can be potentially confounded by observer bias and are not able to detect subtle sensori-/psychomotor abnormalities. Yet, an innovative three-dimensional (3D) optical motion capturing technology (MoCap) can provide more objective and quantifiable data about movements and posture in psychiatric patients. To draw attention to recent rapid progress in the field, we performed a systematic review using PubMed, Medline, Embase, and Web of Science until May 01st 2024. We included 55 studies in the qualitative analysis and gait was the most examined movement. The identified studies suggested that sensori-/psychomotor abnormalities in neurodevelopmental, mood, schizophrenia spectrum and neurocognitive disorders are associated with alterations in spatiotemporal parameters (speed, step width, length and height; stance time, swing time, double limb support time, phases duration, adjusting sway, acceleration, etc.) during various movements such as walking, running, upper body, hand and head movements. Some studies highlighted the advantages of 3D optical MoCap systems over traditional rating scales and measurements such as actigraphy and ultrasound gait analyses. 3D optical MoCap systems are susceptible to detecting differences not only between patients with mental disorders and healthy persons but also among at-risk individuals exhibiting subtle sensori-/psychomotor abnormalities. Overall, 3D optical MoCap systems hold promise for objectively examining sensori-/psychomotor abnormalities, making them valuable tools for use in future clinical trials.

Temporal dysregulation of the somatomotor network in agitated depression

Agitated depression (A-MDD) is a severe subtype of major depressive disorder, with an increased risk of suicidality and the potential to evolve into bipolar disorder. Despite its clinical significance, the neural basis remains unclear. We hypothesize that psychomotor agitation, marked by pressured speech and racing thoughts, is linked to disruptions in brain dynamics. To test this hypothesis, we examined brain dynamics using time delay estimation and edge-centre time series, as well as dynamic connections between the somatomotor network (SMN) and the default mode network in 44 patients with A-MDD, 75 with non-agitated MDD (NA-MDD), and 94 healthy controls. Our results revealed that the neural co-activity duration was shorter in the A-MDD group compared with both the NA-MDD and controls (A-MDD versus NA-MDD: t = 2.295; A-MDD versus controls: t = 2.192, all P < 0.05). In addition, the dynamic of neural fluctuation in SMN altered in the A-MDD group than in the NA-MDD group (t = -2.616, P = 0.011) and was correlated with agitation severity (β = -0.228, P = 0.011). The inter-network connection was reduced in the A-MDD group compared with the control group (t = 2.102, P = 0.037), especially at low-amplitude time points (t = 2.139, P = 0.034). These findings indicate rapid neural fluctuations and disrupted dynamic coupling between the SMN and default mode network in A-MDD, potentially underlying the psychomotor agitation characteristic of this subtype. These insights contribute to a more nuanced understanding of the heterogeneity of depression and have implications for differential diagnosis and treatment strategies.

The Algorithmic Agent Perspective and Computational Neuropsychiatry: From Etiology to Advanced Therapy in Major Depressive Disorder

Major Depressive Disorder (MDD) is a complex, heterogeneous condition affecting millions worldwide. Computational neuropsychiatry offers potential breakthroughs through the mechanistic modeling of this disorder. Using the Kolmogorov theory (KT) of consciousness, we developed a foundational model where algorithmic agents interact with the world to maximize an Objective Function evaluating affective valence. Depression, defined in this context by a state of persistently low valence, may arise from various factors-including inaccurate world models (cognitive biases), a dysfunctional Objective Function (anhedonia, anxiety), deficient planning (executive deficits), or unfavorable environments. Integrating algorithmic, dynamical systems, and neurobiological concepts, we map the agent model to brain circuits and functional networks, framing potential etiological routes and linking with depression biotypes. Finally, we explore how brain stimulation, psychotherapy, and plasticity-enhancing compounds such as psychedelics can synergistically repair neural circuits and optimize therapies using personalized computational models.

Thalamic Volumes and Functional Networks Linked With Self-Regulation Dysfunction in Major Depressive Disorder

AIMS

Self-regulation (SR) dysfunction is a crucial risk factor for major depressive disorder (MDD). However, neural substrates of SR linking MDD remain unclear.

METHODS

Sixty-eight healthy controls and 75 MDD patients were recruited to complete regulatory orientation assessments with the Regulatory Focus Questionnaire (RFQ) and Regulatory Mode Questionnaire (RMQ). Nodal intra and inter-network functional connectivity (FC) was defined as FC sum within networks of 46 thalamic subnuclei (TS) or 88 AAL brain regions, and between the two networks separately. Group-level volumetric and functional difference were compared by two sample t-tests. Pearson's correlation analysis and mediation analysis were utilized to investigate the relationship among imaging parameters and the two behaviors. Canonical correlation analysis (CCA) was conducted to explore the inter-network FC mode of TS related to behavioral subscales. Network-based Statistics with machine learning combining powerful brain imaging features was applied to predict individual behavioral subscales.

RESULTS

MDD patients showed no group-level volumetric difference in 46 TS but represented significant correlation of TS volume and nodal FC with behavioral subscales. Specially, inter-network FC of the orbital part of the right superior frontal gyrus and the left supplementary motor area mediated the correlation between RFQ/RMQ subscales and depressive severity. Furthermore, CCA identified how the two behaviors are linked via the inter-network FC mode of TS. More crucially, thalamic functional subnetworks could predict RFQ/RMQ subscales and psychomotor retardation for MDD individuals.

CONCLUSION

These findings provided neurological evidence for SR affecting depressive severity in the MDD patients and proposed potential biomarkers to identify the SR-based risk phenotype of MDD individuals.

Motor versus Psychomotor? Deciphering the Neural Source of Psychomotor Retardation in Depression

Major depressive disorder (MDD) is characterized by psychomotor retardation whose underlying neural source remains unclear. Psychomotor retardation may either be related to a motor source like the motor cortex or, alternatively, to a psychomotor source with neural changes outside motor regions, like input regions such as visual cortex. These two alternative hypotheses in main (n = 41) and replication (n = 18) MDD samples using 7 Tesla MRI are investigated. Analyzing both global and local connectivity in primary motor cortex (BA4), motor network and middle temporal visual cortex complex (MT+), the main findings in MDD are: 1) Reduced local and global synchronization and increased local-to-global output in motor regions, which do not correlate with psychomotor retardation, though. 2) Reduced local-to-local BA4 - MT+ functional connectivity (FC) which correlates with psychomotor retardation. 3) Reduced global synchronization and increased local-to-global output in MT+ which relate to psychomotor retardation. 4) Reduced variability in the psychophysical measures of MT+ based motion perception which relates to psychomotor retardation. Together, it is shown that visual cortex MT+ and its relation to motor cortex play a key role in mediating psychomotor retardation. This supports psychomotor over motor hypothesis about the neural source of psychomotor retardation in MDD.

Alterations of perfusion and functional connectivity of the cingulate motor area are associated with psychomotor retardation in major depressive disorder

Psychomotor retardation, characterized by slowing of speech, thoughts, and a decrease of movements, is frequent in patients with major depressive disorder (MDD). However, its neurobiological correlates are still poorly understood. This study aimed to explore if cerebral blood flow (CBF) and resting state functional connectivity (rs-FC) of the motor network are altered in patients with MDD and if these changes are associated with psychomotor retardation. Thirty-six right-handed patients with depression and 19 right-handed healthy controls (HC) that did not differ regarding age and sex underwent arterial spin labelling (ASL) and resting-state functional MRI (rs-fMRI) scans. Psychomotor retardation was assessed with the motoric items of the core assessment of psychomotor change (CORE) questionnaire. Patients with MDD had more pronounced psychomotor retardation scores than HC. Patients with MDD had reduced CBF in bilateral cingulate motor area (CMA) and increased resting-state functional connectivity (rs-FC) between the cluster in the CMA and a cluster localized in bilateral supplementary motor areas (SMA). Furthermore, increased rs-FC between the CMA and the left SMA was associated with more pronounced psychomotor retardation. Our results suggest that reduced perfusion of the CMA and increased rs-FC between the CMA and the SMA are associated with psychomotor retardation in patients with depression.

Is depression a global brain disorder with topographic dynamic reorganization?

Major depressive disorder (MDD) is characterized by a multitude of psychopathological symptoms including affective, cognitive, perceptual, sensorimotor, and social. The neuronal mechanisms underlying such co-occurrence of psychopathological symptoms remain yet unclear. Rather than linking and localizing single psychopathological symptoms to specific regions or networks, this perspective proposes a more global and dynamic topographic approach. We first review recent findings on global brain activity changes during both rest and task states in MDD showing topographic reorganization with a shift from unimodal to transmodal regions. Next, we single out two candidate mechanisms that may underlie and mediate such abnormal uni-/transmodal topography, namely dynamic shifts from shorter to longer timescales and abnormalities in the excitation-inhibition balance. Finally, we show how such topographic shift from unimodal to transmodal regions relates to the various psychopathological symptoms in MDD including their co-occurrence. This amounts to what we describe as 'Topographic dynamic reorganization' which extends our earlier 'Resting state hypothesis of depression' and complements other models of MDD.

Substance use disorders are characterised by increased voxel-wise intrinsic measures in sensorimotor cortices: An ALE meta-analysis

Substance use disorders (SUDs) are severe psychiatric illnesses. Seed region and independent component analyses are currently the dominant connectivity measures but carry the risk of false negatives due to selection. They can be complemented by a data-driven and whole-brain usage of voxel-wise intrinsic measures (VIMs). We meta-analytically integrated VIMs, namely regional homogeneity (ReHo), amplitude of low-frequency fluctuations (ALFF), voxel-mirrored homotopy connectivity (VMHC) and degree centrality (DC) across different SUDs using the Activation Likelihood Estimation (ALE) algorithm, functionally decoded emerging clusters, and analysed their connectivity profiles. Our systematic search identified 51 studies including 1439 SUD participants. Although no overall convergent pattern of alterations across VIMs in SUDs was found, sensitivity analyses demonstrated two ALE-derived clusters of increased ReHo and ALFF in SUDs, which peaked in the left pre- and postcentral cortices. Subsequent analyses showed their involvement in action execution, somesthesis, finger tapping and vibrotactile monitoring/discrimination. Their numerous clinical correlates across included studies highlight the under-discussed role of sensorimotor cortices in SUD, urging a more attentive exploration of their clinical significance.

Psychomotor Slowing in Psychosis and Inhibitory Repetitive Transcranial Magnetic Stimulation: A Randomized Clinical Trial

Importance

Psychomotor slowing is a frequent symptom of psychosis, impairing gross and fine motor behavior. It is associated with poor outcomes and functioning, and no treatment is available.

Objective

To investigate whether 15 sessions of inhibitory repetitive transcranial magnetic stimulation (rTMS) may reduce psychomotor slowing.

Design, Setting, and Participants

This was a 4-arm, double-blind, randomized, sham-controlled trial at a university hospital in Switzerland. Enrollment took place from March 2019 to August 2022. Adults aged 18 to 60 years with schizophrenia spectrum disorders and severe psychomotor slowing were eligible. All patients continued existing medications, including antipsychotics and benzodiazepines. Those with substance misuse (other than nicotine), conditions associated with impaired or aberrant movement, convulsions, history of hearing problems, other conditions typically excluded from magnetic resonance imaging or TMS, any TMS treatment in the past 3 months, or those who were pregnant or breastfeeding were excluded. Of 615 patients screened for eligibility, 103 were randomized and 88 received at least 1 session of rTMS: 22 were assigned to 1-Hz rTMS, 22 to iTBS, 22 to sham, and 22 to the waiting group. Follow-up was conducted at 6 weeks and 24 weeks following the week 3 assessments including clinical, functional, and motor measures.

Interventions

Fifteen sessions of rTMS in 3 weeks over the supplementary motor area: 1-Hz rTMS, iTBS, sham, or no treatment (waiting). After 3 weeks, the waiting group received 15 sessions of 1-Hz rTMS over the supplementary motor area.

Main Outcomes and Measures

The main outcome was the proportion of responders at week 3 in the Salpêtrière Retardation Rating Scale (SRRS) defined as a 30% or greater reduction from baseline (last-observation-carried-forward). The SRRS has 15 items and a maximum total score of 60.

Results

Of the 88 participants analyzed, 45 were men and 43 were women. The mean (SD) age was 36.3 (12.4) years and the mean (SD) SRRS score was 24.0 (5.9). A total of 69 participants completed the study. At week 3, response rates differed between groups: 15 of 22 (68%) in the 1-Hz rTMS group, 8 of 22 (36%) in the iTBS group, 7 of 22 (32%) in the sham group, and 4 of 22 (18%) in the waiting group (χ23 = 12.1; P = .007). The 1-Hz rTMS group had more responders than sham (odds ratio [OR], 0.13; 95% CI, 0.02-0.65; P = .03), iTBS (OR, 0.12; 95% CI, 0.02-0.61; P = .02), and waiting (OR, 0.04; 95% CI, 0.01-0.22; P = .003). In the waiting group, 10 of 16 participants (63%) responded after receiving 15 sessions of 1-Hz rTMS. No serious adverse events occurred.

Conclusions and Relevance

In this study, inhibitory add-on rTMS safely alleviated psychomotor slowing in psychosis compared with iTBS, sham, and no treatment. The treatment was also effective with delayed onset. Future studies need to explore the neural changes associated with supplementary motor area rTMS in psychosis.

Trial Registration

ClinicalTrials.gov Identifier: NCT03921450.