Differentiation Across Bipolar Disorder and Major Depressive Disorder by Whole-Night Polysomnographic Findings.

Abstract.Background: There is growing evidence that understanding the role of sleep disturbance in bipolar disorder (BD) and major depressive disorder (MDD) is helpful when studying the high heterogeneity of patients across psychiatric disorders.Objective: The present study was designed to investigate the transdiagnostic role of sleep disturbance measured by polysomnography (PSG) in differentiating from MDD with BD.Methods: A total of 256 patients with MDD and 107 first-episode and never medicated patients with BD using the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, criteria were recruited. All patients completed 1 night of PSG recording, and the changes in objective sleep structure parameters were determined by PSG analysis.Results: We showed that patients with MDD had statistically longer rapid eye movement (REM) latency, a higher percentage of stage N2 sleep, and lower percentages of stage N3 sleep and REM sleep than those with BD after controlling for confounding factors (all P < .05). Moreover, using the logistic regression analysis, we identified that REM latency was associated with BD diagnosis among the PSG sleep features. The cutoff value for PSG characteristics to differentiate BD from MDD was 261 in REM latency (sensitivity: 41.4% and specificity: 84.1%).Conclusions: Our findings suggest that PSG-measured sleep abnormalities, such as reduced REM latency, may be a diagnostic differentiating factor between MDD and BD, indicating their roles in identifying homogeneous transdiagnostic subtypes across psychiatric disorders.

Dynamicity of brain network organization & their community architecture as characterizing features for classification of common mental disorders from whole-brain connectome.

The urgency of addressing common mental disorders (bipolar disorder, attention-deficit hyperactivity disorder (ADHD), and schizophrenia) arises from their significant societal impact. Developing strategies to support psychiatrists is crucial. Previous studies focused on the relationship between these disorders and changes in the resting-state functional connectome's modularity, often using static functional connectivity (sFC) estimation. However, understanding the dynamic reconfiguration of resting-state brain networks with rich temporal structure is essential for comprehending neural activity and addressing mental health disorders. This study proposes an unsupervised approach combining spatial and temporal characterization of brain networks to classify common mental disorders using fMRI timeseries data from two cohorts (N = 408 participants). We employ the weighted stochastic block model to uncover mesoscale community architecture differences, providing insights into network organization. Our approach overcomes sFC limitations and biases in community detection algorithms by modelling the functional connectome's temporal dynamics as a landscape, quantifying temporal stability at whole-brain and network levels. Findings reveal individuals with schizophrenia exhibit less assortative community structure and participate in multiple motif classes, indicating less specialized network organization. Patients with schizophrenia and ADHD demonstrate significantly reduced temporal stability compared to healthy controls. This study offers insights into functional connectivity (FC) patterns' spatiotemporal organization and their alterations in common mental disorders, highlighting the potential of temporal stability as a biomarker.

Investigating the role of obesity, circadian disturbances and lifestyle factors in people with schizophrenia and bipolar disorder: Study protocol for the SOMBER trial.

The aim of this study is to investigate circadian rhythms in independently living adults with obesity and mental disease, exploring the interplay between biological markers and lifestyle factors. Eighty participants divided equally into four groups; (i) people with obesity and schizophrenia; (ii) people with obesity and bipolar disorder; (iii) people with obesity without mental disease or sleep disorders, and (iv) people without obesity, mental disease or sleep disorders. Over two consecutive days, participants engage in repeated self-sampling of hair follicle and saliva; concurrently, data is collected on diet, body temperature, light exposure, sleep parameters, and physical activity by accelerometry. Hair follicles are analyzed for circadian gene expression, saliva samples for cortisol and melatonin concentrations. Circadian rhythms are investigated by cosinor analysis. The study employs a participant-tailored sampling schedule to minimize disruptions to daily routine and enhance ecological validity. The methodology aims to provide a comprehensive insight into the factors contributing to circadian disruptions in people with obesity, bipolar disorder and schizophrenia, potentially informing strategies for future management and mitigation. Trial registration: (ClinicalTrials.gov Identifier: NCT05413486).

Different structural connectivity patterns in the subregions of the thalamus, hippocampus, and cingulate cortex between schizophrenia and psychotic bipolar disorder.

OBJECTIVE: Schizophrenia (SCZ) and psychotic bipolar disorder (PBD) are two major psychotic disorders with similar symptoms and tight associations on the psychopathological level, posing a clinical challenge for their differentiation. This study aimed to investigate and compare the structural connectivity patterns of the limbic system between SCZ and PBD, and to identify specific regional disruptions associated with psychiatric symptoms. METHODS: Using sMRI data from 146 SCZ, 160 PBD, and 145 healthy control (HC) participants, we employed a data-driven approach to segment the hippocampus, thalamus, hypothalamus, amygdala, and cingulate cortex into subregions. We then investigated the structural connectivity patterns between these subregions at the global and nodal levels. Additionally, we assessed psychotic symptoms by utilizing the subscales of the Brief Psychiatric Rating Scale (BPRS) to examine correlations between symptom severity and network metrics between groups. RESULTS: Patients with SCZ and PBD had decreased global efficiency (Eglob) (SCZ: adjusted P<0.001; PBD: adjusted P = 0.003), local efficiency (Eloc) (SCZ and PBD: adjusted P<0.001), and clustering coefficient (Cp) (SCZ and PBD: adjusted P<0.001), and increased path length (Lp) (SCZ: adjusted P<0.001; PBD: adjusted P = 0.004) compared to HC. Patients with SCZ showed more pronounced decreases in Eglob (adjusted P<0.001), Eloc (adjusted P<0.001), and Cp (adjusted P = 0.029), and increased Lp (adjusted P = 0.024) compared to patients with PBD. The most notable structural disruptions were observed in the hippocampus and thalamus, which correlated with different psychotic symptoms, respectively. CONCLUSION: This study provides evidence of distinct structural connectivity disruptions in the limbic system of patients with SCZ and PBD. These findings might contribute to our understanding of the neuropathological basis for distinguishing SCZ and PBD.

The Role of Selected Speech Signal Characteristics in Discriminating Unipolar and Bipolar Disorders.

OBJECTIVE: The objective of this study is to explore and enhance the diagnostic process of unipolar and bipolar disorders. The primary focus is on leveraging automated processes to improve the accuracy and accessibility of diagnosis. The study aims to introduce an audio corpus collected from patients diagnosed with these disorders, annotated using the Clinical Global Impressions Scale (CGI) by psychiatrists. METHODS AND PROCEDURES: Traditional diagnostic methods rely on the clinician's expertise and consideration of co-existing mental disorders. However, this study proposes the implementation of automated processes in the diagnosis, providing quantitative measures and enabling prolonged observation of patients. The paper introduces a speech signal pipeline for CGI state classification, with a specific focus on selecting the most discriminative features. Acoustic features such as prosodies, MFCC, and LPC coefficients are examined in the study. The classification process utilizes common machine learning methods. RESULTS: The results of the study indicate promising outcomes for the automated diagnosis of bipolar and unipolar disorders using the proposed speech signal pipeline. The audio corpus annotated with CGI by psychiatrists achieved a classification accuracy of 95% for the two-class classification. For the four- and seven-class classifications, the results were 77.3% and 73%, respectively, demonstrating the potential of the developed method in distinguishing different states of the disorders.

Cognitive reserve and cognition in mood disorders: A systematic review and meta-analysis.

Cognitive functioning heterogeneity is a well-recognized phenomenon in individuals diagnosed with mood disorders. Cognitive Reserve (CR) has been linked to multiple positive outcomes, including cognitive performance in these patients. This systematic review and meta-analysis aim to provide a comprehensive analysis of the relationship between CR and cognitive functioning in individuals with mood disorders, including bipolar disorder and depressive disorders. Following PRISMA guidelines, a systematic review and meta-analysis was conducted of original research exploring the relationship between CR and cognitive performance in adult individuals with mood disorders. The literature search was conducted on PubMed, Scopus, and Web of Science, from 2002 to September 2023, and the Newcastle-Ottawa Scale (NOS) was used to evaluate the quality of studies. Overall, 17 studies met the inclusion criteria for the systematic review and 11 for the meta-analysis. Both qualitative and quantitative findings suggested a positive relationship between CR measures and cognitive domains. CR emerges as a possible protective factor for cognitive functioning in adult individuals with mood disorders, potentially helping to mitigate the cognitive impairments associated with the disorder. These findings underscore the importance of the fact that promoting and enhancing CR could help in the cognitive prognosis of this population.

Toward a neurocircuit-based sequential transcranial magnetic stimulation treatment of pediatric bipolar II disorder.

BACKGROUND: Abnormalities in large-scale neuronal networks-the frontoparietal central executive network (CEN)-are consistent findings in bipolar disorder and potential therapeutic targets for transcranial magnetic stimulation (TMS). OBJECTIVE: The present study aimed to assess the effects of CEN neurocircuit-based sequential TMS on the clinical symptoms and cognitive functions of adolescents with bipolar II disorder. METHODS: The study was a single-blinded, randomized, placebo-control trial. Participants with DSM-5-defined bipolar disorder II were recruited and randomized to receive either a sham treatment (n = 20) or an active TMS treatment (n = 22). The active group patients were taking medication, with intermittent theta burst stimulation (iTBS) treatment provided as adjunctive treatment targeting the left DLPFC, the left ITG, and the left PPC nodes consecutively. Patients completed the measurements of HAMD and the Das-Naglieri Cognition Assessment System at baseline and 3 weeks after the intervention. RESULTS: A significant group-by-time interaction was observed in the HAMD, total cognition, and planning. Post-hoc analysis revealed that patients in the active group significantly improved HAMD scores following neurostimulation. Moreover, within-subject analysis indicated that the active group significantly improved in scores of total cognition and planning, while the sham group did not. No significant differences were seen in the other cognitive measures. CONCLUSION: The neurocircuit-based sequential TMS protocol targeting three CEN nodes, in conjunction with medication, safely and effectively improved depressive symptoms and cognitive function in adolescents with bipolar II disorder.

Altered oxidative neurometabolic response to methylene blue in bipolar disorder revealed by quantitative neuroimaging.

BACKGROUND: Cerebral mitochondrial and hemodynamic abnormalities have been implicated in Bipolar Disorder pathophysiology, likely contributing to neurometabolic vulnerability-leading to worsen clinical outcomes and mood instability. To investigate neurometabolic vulnerability in patients with BD, we combined multi-modal quantitative MRI assessment of cerebral oxygenation with acute administration of Methylene Blue, a neurometabolic/hemodynamic modulator acting on cerebral mitochondria. METHODS: Fifteen euthymic patients with chronic BD-type 1, and fifteen age/gender-matched healthy controls underwent two separate MRI sessions in a single-blinded randomized cross-over design, each after intravenous infusion of either MB (0.5 mg/kg) or placebo. MRI-based measures of Cerebral Blood Flow and Oxygen Extraction Fraction were integrated to compute Cerebral Metabolic Rate of Oxygen in Frontal Lobe, Anterior Cingulate, and Hippocampus-implicated in BD neurometabolic pathophysiology. Inter-daily variation in mood rating was used to assess mood instability. RESULTS: A decrease in global CBF and CMRO2 was observed after acutely administrating MB to all participants. Greater regional CMRO2 reductions were observed after MB, in patients compared to controls in FL (mean = -14.2 ± 19.5 % versus 2.3 ± 14.8 %), ACC (mean = -14.8 ± 23.7 % versus 2.4 ± 15.7 %). The effects on CMRO2 in those regions were primarily driven by patients with longer disease duration and higher mood instability. LIMITATIONS: Sample size; medications potentially impacting on response to MB. CONCLUSIONS: An altered neurometabolic response to MB, a mitochondrial/hemodynamic modulator, was observed in patients, supporting the hypothesis of vulnerability to neurometabolic stress in BD. Integrating quantitative imaging of cerebral oxygen metabolism with a mitochondrial-targeting pharmacological challenge could provide a novel biomarker of neurometabolic and cerebrovascular pathophysiology in BD.

Disrupted default mode network connectivity in bipolar disorder: a resting-state fMRI study.

BACKGROUND: Theoretical and empirical evidence indicates the critical role of the default mode network (DMN) in the pathophysiology of the bipolar disorder (BD). This study aims to identify the specific brain regions of the DMN that is impaired in patients with BD. METHODS: A total of 56 patients with BD and 71 healthy controls (HC) underwent resting-state functional magnetic resonance imaging. Three commonly used functional indices, i.e., fractional amplitude of low-frequency fluctuation (fALFF), regional homogeneity (ReHo), and degree centrality (DC), were utilized to identify the brain region showing abnormal spontaneous brain activity in patients with BD. Then, this region served as the seed region for resting-state functional connectivity (rsFC) analysis. RESULTS: Compared to the HC group, the BD group showed reduced fALFF, ReHo, and DC values in the left precuneus. Moreover, patients exhibited decreased rsFCs within the left precuneus and between the left precuneus and the medial prefrontal cortex. Additionally, there was diminished negative connectivity between the left precuneus and the left putamen, extending to the left insula (putamen/insula). The abnormalities in DMN functional connectivity were confirmed through various analysis strategies. CONCLUSIONS: Our findings provide convergent evidence for the abnormalities in the DMN, particularly located in the left precuneus. Decreased functional connectivity within the DMN and the reduced anticorrelation between the DMN and the salience network are found in patients with BD. These findings suggest that the DMN is a key aspect for understanding the neural basis of BD, and the altered functional patterns of DMN may be a potential candidate biomarker for diagnosis of BD.

A machine learning approach for differentiating bipolar disorder type II and borderline personality disorder using electroencephalography and cognitive abnormalities.

This study addresses the challenge of differentiating between bipolar disorder II (BD II) and borderline personality disorder (BPD), which is complicated by overlapping symptoms. To overcome this, a multimodal machine learning approach was employed, incorporating both electroencephalography (EEG) patterns and cognitive abnormalities for enhanced classification. Data were collected from 45 participants, including 20 with BD II and 25 with BPD. Analysis involved utilizing EEG signals and cognitive tests, specifically the Wisconsin Card Sorting Test and Integrated Cognitive Assessment. The k-nearest neighbors (KNN) algorithm achieved a balanced accuracy of 93%, with EEG features proving to be crucial, while cognitive features had a lesser impact. Despite the strengths, such as diverse model usage, it's important to note limitations, including a small sample size and reliance on DSM diagnoses. The study suggests that future research should explore multimodal data integration and employ advanced techniques to improve classification accuracy and gain a better understanding of the neurobiological distinctions between BD II and BPD.

Female sex and age-based advantage of simulated electric field in TMS to the prefrontal cortex in schizophrenia and mood disorders.

This study investigates computational models of electric field strength for transcranial magnetic stimulation (TMS) of the left dorsolateral prefrontal cortex (DLPFC) based on individual MRI data of patients with schizophrenia (SZ), major depressive disorder (MDD), bipolar disorder (BP), and healthy controls (HC). In addition, it explores the association of electric field intensities with age, gender and intracranial volume. The subjects were 23 SZ (12 male, mean age = 45.30), 24 MDD (16 male, mean age = 43.57), 23 BP (16 male, mean age = 39.29), 23 HC (13 male, mean age = 40.91). Based on individual MRI sequences, electric fields were computationally modeled by two independent investigators using SimNIBS ver. 2.1.1. There was no significant difference in electric field strength between the groups (HC vs SZ, HC vs MDD, HC vs BP, SZ vs MDD, SZ vs BP, MDD vs BP). Female subjects showed higher electric field intensities in widespread areas than males, and age was positively significantly associated with electric field strength in the left parahippocampal area as observed. Our results suggest differences in electric field strength of left DLPFC TMS for gender and age. It may open future avenues for individually modeling TMS based on structural MRI data.

Deficits in prefrontal metabotropic glutamate receptor 5 are associated with functional alterations during emotional processing in bipolar disorder.

BACKGROUND: Elucidating biological mechanisms contributing to bipolar disorder (BD) is key to improved diagnosis and treatment development. With converging evidence implicating the metabotropic glutamate receptor 5 (mGlu5) in the pathology of BD, here, we therefore test the hypothesis that recently identified deficits in mGlu5 are associated with functional brain differences during emotion processing in BD. METHODS: Positron emission tomography (PET) with [18F]FPEB was used to measure mGlu5 receptor availability and functional imaging (fMRI) was performed while participants completed an emotion processing task. Data were analyzed from 62 individuals (33 ± 12 years, 45 % female) who completed both PET and fMRI, including individuals with BD (n = 18), major depressive disorder (MDD: n = 20), and psychiatrically healthy comparisons (HC: n = 25). RESULTS: Consistent with some prior reports, the BD group displayed greater activation during fear processing relative to MDD and HC, notably in right lateralized frontal and parietal brain regions. In BD, (but not MDD or HC) lower prefrontal mGlu5 availability was associated with greater activation in bilateral pre/postcentral gyri and cuneus during fear processing. Furthermore, greater prefrontal mGlu5-related brain activity in BD was associated with difficulties in psychomotor function (r≥0.904, p≤0.005) and attention (r≥0.809, p≤0.028). LIMITATIONS: The modest sample size is the primary limitation. CONCLUSIONS: Deficits in prefrontal mGlu5 in BD were linked to increased cortical activation during fear processing, which in turn was associated with impulsivity and attentional difficulties. These data further implicate an mGlu5-related mechanism unique to BD. More generally these data suggest integrating PET and fMRI can provide novel mechanistic insights.

Inflammatory and oxidative stress biomarkers in children and adolescents with bipolar disorder - A systematic review and meta-analysis.

Evidence suggests a role for low-grade inflammation and oxidative stress in the pathophysiology of bipolar disorder. We conducted a systematic review and meta-analysis of peripheral markers of inflammation and oxidative stress in children and adolescents under 20 years of age with bipolar disorder. We searched PubMed, Embase and psycINFO and performed random effects meta-analysis calculating standardized mean differences (SMD) of marker levels between patients with bipolar disorder and healthy control individuals. Ten studies comprising a total of 418 patients with bipolar disorder and 3017 healthy control individuals were included. The levels of C-Reactive Protein were higher in patients with bipolar disorder compared with healthy individuals (SMD 0.53; 95 %CI: 0.33-0.74; I2 = 0 %). For other biomarkers there were no statistically significant differences between groups. Findings were limited by a low number of studies and participants and methodological issues in the included studies. More and larger studies using rigorous methodology are needed to establish the role of inflammation and oxidative stress in children and adolescents with bipolar disorder.

Optical coherence tomography angiography in patients with bipolar disorder and major depressive disorder.

BACKGROUND: Cerebral microvascular dysfunction is a promising area for research into the pathogenesis of major depressive disorder (MDD) and bipolar disorder (BD). Despite the scientific and clinical potential of studying microvascular dysfunction, progress in this area has long been hampered by the lack of methods to study microvessels intravitally. AIMS: The aim of the present study was to search for potential optical coherence tomography (OCT) and OCT-angiography (OCTA) biomarkers of BD and MDD. METHODS: One hundred and five consecutive patients with a current depressive episode were enrolled in the study (39 - BD and 66 - MDD). In addition, forty-one generally healthy subjects were enrolled as a control group. Only the right eye was examined in all subjects. Structural OCT and OCTA scans with signal strength ≥7 were included. RESULTS: Structural OCT measurements showed no significant differences between the groups. OCTA measurements of foveal avascular zone (FAZ), area and skeleton density showed a decrease in the retinal capillary bed in BD patients, whereas OCTA values in MDD patients did not differ from the control group. Several significant differences were found between the BD and control groups. In the BD group, the FAZ of the deep capillary plexus was increased, reflecting a reduction in capillary perfusion in the central subfield of this plexus. CONCLUSIONS: OCTA measurements of FAZ, area and skeleton density showed a decrease in the retinal capillary bed in BD patients, whereas OCTA values in MDD patients did not differ from the control group.

Evidence from comprehensive independent validation studies for smooth pursuit dysfunction as a sensorimotor biomarker for psychosis.

Smooth pursuit eye movements are considered a well-established and quantifiable biomarker of sensorimotor function in psychosis research. Identifying psychotic syndromes on an individual level based on neurobiological markers is limited by heterogeneity and requires comprehensive external validation to avoid overestimation of prediction models. Here, we studied quantifiable sensorimotor measures derived from smooth pursuit eye movements in a large sample of psychosis probands (N = 674) and healthy controls (N = 305) using multivariate pattern analysis. Balanced accuracies of 64% for the prediction of psychosis status are in line with recent results from other large heterogenous psychiatric samples. They are confirmed by external validation in independent large samples including probands with (1) psychosis (N = 727) versus healthy controls (N = 292), (2) psychotic (N = 49) and non-psychotic bipolar disorder (N = 36), and (3) non-psychotic affective disorders (N = 119) and psychosis (N = 51) yielding accuracies of 65%, 66% and 58%, respectively, albeit slightly different psychosis syndromes. Our findings make a significant contribution to the identification of biologically defined profiles of heterogeneous psychosis syndromes on an individual level underlining the impact of sensorimotor dysfunction in psychosis.

Targeting inflammasome complexes as a novel therapeutic strategy for mood disorders.

INTRODUCTION: Inflammasome complexes, especially NLRP3, have gained great attention as a potential therapeutic target in mood disorders. NLRP3 triggers a caspase 1-dependent release of the inflammatory cytokines IL-1ß and IL-18, and seems to interact with purinergic and kynurenine pathways, all of which are implicated in mood disorders development and progression. AREAS COVERED: Emerging evidence supports NLRP3 inflammasome as a promising pharmacological target for mood disorders. We discussed the available evidence from animal models and human studies and provided a reflection on drawbacks and perspectives for this novel target. EXPERT OPINION: Several studies have supported the involvement of NLRP3 inflammasome in MDD. However, most of the evidence comes from animal models. The role of NLRP3 inflammasome in BD as well as its anti-manic properties is not very clear and requires further exploration. There is evidence of anti-manic effects of P2×R7 antagonists associated with reduction in the brain levels of IL-1ß and TNF-α in a murine model of mania. The involvement of other NLRP3 inflammasome expressing cells besides microglia, like astrocytes, and of other inflammasome complexes in mood disorders also deserves further investigation. Preclinical and clinical characterization of NLRP3 and other inflammasomes in mood disorders is needed before considering translational approaches, including clinical trials.

Comparative analysis of resting-state EEG-based multiscale entropy between schizophrenia and bipolar disorder.

BACKGROUND: Studies that use nonlinear methods to identify abnormal brain dynamics in patients with psychiatric disorders are limited. This study investigated brain dynamics based on EEG using multiscale entropy (MSE) analysis in patients with schizophrenia (SZ) and bipolar disorder (BD). METHODS: The eyes-closed resting-state EEG data were collected from 51 patients with SZ, 51 patients with BD, and 51 healthy controls (HCs). Patients with BD were further categorized into type I (n = 23) and type II (n = 16), and then compared with patients with SZ. A sample entropy-based MSE was evaluated from the bilateral frontal, central, and parieto-occipital regions using 30-s artifact-free EEG data for each individual. Correlation analyses of MSE values and psychiatric symptoms were performed. RESULTS: For patients with SZ, higher MSE values were observed at higher-scale factors (i.e., 41-70) across all regions compared with both HCs and patients with BD. Furthermore, there were positive correlations between the MSE values in the left frontal and parieto-occipital regions and PANSS scores. For patients with BD, higher MSE values were observed at middle-scale factors (i.e., 13-40) in the bilateral frontal and central regions compared with HCs. Patients with BD type I exhibited higher MSE values at higher-scale factors across all regions compared with those with BD type II. In BD type I, positive correlations were found between MSE values in all left regions and YMRS scores. CONCLUSIONS: Patients with psychiatric disorders exhibited group-dependent MSE characteristics. These results suggest that MSE features may be useful biomarkers that reflect pathophysiological characteristics.

Active suicidal ideation associated with dysfunction in default mode network using resting-state EEG and functional MRI - Findings from the T-RAD Study.

Suicide in youth and young adults is a serious public health problem. However, the biological mechanisms of suicidal ideation (SI) remain poorly understood. The primary goal of these analyses was to identify the connectome profile of suicidal ideation using resting state electroencephalography (EEG). We evaluated the neurocircuitry of SI in a sample of youths and young adults (aged 10-26 years, n = 111) with current or past diagnoses of either a depressive disorder or bipolar disorder who were enrolled in the Texas Resilience Against Depression Study (T-RAD). Neurocircuitry was analyzed using orthogonalized power envelope connectivity computed from resting state EEG. Suicidal ideation was assessed with the 3-item Suicidal Thoughts factor of the Concise Health Risk Tracking self-report scale. The statistical pipeline involved dimension reduction using principal component analysis, and the association of neuroimaging data with SI using regularized canonical correlation analysis. From the original 111 participants and the correlation matrix of 4950 EEG connectivity pairs in each band (alpha, beta, theta), dimension reduction generated 1305 EEG connectivity pairs in the theta band, 2337 EEG pairs in the alpha band, and 914 EEG connectivity pairs in the beta band. Overall, SI was consistently involved with dysfunction of the default mode network (DMN). This report provides preliminary evidence of DMN dysfunction associated with active suicidal ideation in adolescents. Using EEG using power envelopes to compute connectivity moves us closer to using neurocircuit dysfunction in the clinical setting to identify suicidal ideation.

Analyzing fractal dimension in electroconvulsive therapy: Unraveling complexity in structural and functional neuroimaging.

BACKGROUND: Numerous studies show that electroconvulsive therapy (ECT) induces hippocampal neuroplasticity, but findings are inconsistent regarding its clinical relevance. This study aims to investigate ECT-induced plasticity of anterior and posterior hippocampi using mathematical complexity measures in neuroimaging, namely Higuchi's fractal dimension (HFD) for fMRI time series and the fractal dimension of cortical morphology (FD-CM). Furthermore, we explore the potential of these complexity measures to predict ECT treatment response. METHODS: Twenty patients with a current depressive episode (16 with major depressive disorder and 4 with bipolar disorder) underwent MRI-scans before and after an ECT-series. Twenty healthy controls matched for age and sex were also scanned twice for comparison purposes. Resting-state fMRI data were processed, and HFD was computed for anterior and posterior hippocampi. Group-by-time effects for HFD in anterior and posterior hippocampi were calculated and correlations between HFD changes and improvement in depression severity were examined. For FD-CM analyses, we preprocessed structural MRI with CAT12's surface-based methods. We explored group-by-time effects for FD-CM and the predictive value of baseline HFD and FD-CM for treatment outcome. RESULTS: Patients exhibited a significant increase in bilateral hippocampal HFD from baseline to follow-up scans. Right anterior hippocampal HFD increase was associated with reductions in depression severity. We found no group differences and group-by-time effects in FD-CM. After applying a whole-brain regression analysis, we found that baseline FD-CM in the left temporal pole predicted reduction of overall depression severity after ECT. Baseline hippocampal HFD did not predict treatment outcome. CONCLUSION: This study suggests that HFD and FD-CM are promising imaging markers to investigate ECT-induced neuroplasticity associated with treatment response.

Theory of mind abilities during the course of bipolar disorder: A longitudinal study using mixed models.

Theory of mind (ToM) deficits, difficulties in recognizing the intentions, propensities, and beliefs of others have been shown in individuals with bipolar disorder in several studies; however, it is not yet elucidated how ToM abilities changes over the course of bipolar disorder and is related to illness symptoms. This is one of the first longitudinal studies to compare the ToM abilities of euthymic bipolar individuals and healthy controls over a four and a half years period. ToM abilities were measured using the Reading the Mind in the Eyes Test (RMET). A total of 91 euthymic bipolar individuals and 91 healthy controls were included in the analyses. Linear mixed models were used to compare ToM abilities of bipolar individuals and healthy controls. It was found that bipolar individuals scored lower on average on the RMET than healthy controls and that these RMET scores were stable over four and a half years. The results of this study suggest that ToM deficits are a stable (possibly endophenotypic) trait of bipolar disorder. This understanding can contribute to better identification, assessment, and treatment strategies for individuals with bipolar disorder, ultimately improving their overall care and outcome.