Deep phenotyping of attention impairments and the 'Inattention Biotype' in Major Depressive Disorder

Characterizing Major Depressive Disorder (MDD) using alpha-band activity in resting-state electroencephalogram (EEG) combined with MATRICS Consensus Cognitive Battery (MCCB)

BACKGROUND

The diagnosis of major depressive disorder (MDD) is commonly based on the subjective evaluation by experienced psychiatrists using clinical scales. Hence, it is particularly important to find more objective biomarkers to aid in diagnosis and further treatment. Alpha-band activity (7-13 Hz) is the most prominent component in resting electroencephalogram (EEG), which is also thought to be a potential biomarker. Recent studies have shown the existence of multiple sub-oscillations within the alpha band, with distinct neural underpinnings. However, the specific contribution of these alpha sub-oscillations to the diagnosis and treatment of MDD remains unclear.

METHODS

In this study, we recorded the resting-state EEG from MDD and HC populations in both open and closed-eye state conditions. We also assessed cognitive processing using the MATRICS Consensus Cognitive Battery (MCCB).

RESULTS

We found that the MDD group showed significantly higher power in the high alpha range (10.5-11.5 Hz) and lower power in the low alpha range (7-8.5 Hz) compared to the HC group. Notably, high alpha power in the MDD group is negatively correlated with working memory performance in MCCB, whereas no such correlation was found in the HC group. Furthermore, using five established classification algorithms, we discovered that combining alpha oscillations with MCCB scores as features yielded the highest classification accuracy compared to using EEG or MCCB scores alone.

CONCLUSIONS

Our results demonstrate the potential of sub-oscillations within the alpha frequency band as a potential distinct biomarker. When combined with psychological scales, they may provide guidance relevant for the diagnosis and treatment of MDD.

Analysis of functional connectivity changes in attention networks and default mode networks in patients with depression and insomnia

PURPOSE

Major Depressive Disorder (MDD) and Insomnia Disorder (ID) are prevalent psychiatric conditions often occurring concurrently, leading to substantial impairment in daily functioning. Understanding the neurobiological underpinnings of these disorders and their comorbidity is crucial for developing effective interventions. This study aims to analyze changes in functional connectivity within attention networks and default mode networks in patients with depression and insomnia.

METHODS

The functional connectivity alterations in individuals with MDD, ID, comorbid MDD and insomnia (iMDD), and healthy controls (HC) were assessed from a cohort of 174 participants. They underwent rs-fMRI scans, demographic assessments, and scale evaluations for depression and sleep quality. Functional connectivity analysis was conducted using region-of-interest (ROI) and whole-brain methods.

RESULTS

The MDD and iMDD groups exhibited higher Hamilton Depression Scale (HAMD) scores compared to HC and ID groups (P < 0.001). Both ID and MDD groups displayed enhanced connectivity between the left and right orbital frontal cortex compared to HC (P < 0.05), while the iMDD group showed reduced connectivity compared to HC and ID groups (P < 0.05). In the left insula, reduced connectivity with the right medial superior frontal gyrus was observed across patient groups compared to HC (P < 0.05), with the iMDD group showing increased connectivity compared to MDD (P < 0.05). Moreover, alterations in functional connectivity between the left thalamus and left temporal pole were found in iMDD compared to HC and MDD (P < 0.05). Correlation analyses revealed associations between abnormal connectivity and symptom severity in MDD and ID groups.

CONCLUSIONS

Our findings demonstrate distinct patterns of altered functional connectivity in individuals with MDD, ID, and iMDD compared to healthy controls. These findings contribute to a better understanding of the pathophysiology of depression and insomnia, which could be used as a reference for the diagnosis and treatments of these patients.

Neuroimaging features of cognitive impairments in schizophrenia and major depressive disorder

Cognitive dysfunctions are one of the key symptoms of schizophrenia (SZ) and major depressive disorder (MDD), which exist not only during the onset of diseases but also before the onset, even after the remission of psychiatric symptoms. With the development of neuroimaging techniques, these non-invasive approaches provide valuable insights into the underlying pathogenesis of psychiatric disorders and information of cognitive remediation interventions. This review synthesizes existing neuroimaging studies to examine domains of cognitive impairment, particularly processing speed, memory, attention, and executive function in SZ and MDD patients. First, white matter (WM) abnormalities are observed in processing speed deficits in both SZ and MDD, with distinct neuroimaging findings highlighting WM connectivity abnormalities in SZ and WM hyperintensity caused by small vessel disease in MDD. Additionally, the abnormal functions of prefrontal cortex and medial temporal lobe are found in both SZ and MDD patients during various memory tasks, while aberrant amygdala activity potentially contributes to a preference to negative memories in MDD. Furthermore, impaired large-scale networks including frontoparietal network, dorsal attention network, and ventral attention network are related to attention deficits, both in SZ and MDD patients. Finally, abnormal activity and volume of the dorsolateral prefrontal cortex (DLPFC) and abnormal functional connections between the DLPFC and the cerebellum are associated with executive dysfunction in both SZ and MDD. Despite these insights, longitudinal neuroimaging studies are lacking, impeding a comprehensive understanding of cognitive changes and the development of early intervention strategies for SZ and MDD. Addressing this gap is critical for advancing our knowledge and improving patient prognosis.

Brain Circuit-Derived Biotypes for Treatment Selection in Mood Disorders: A Critical Review and Illustration of a Functional Neuroimaging Tool for Clinical Translation

Although the lifetime burden due to major depressive disorder is increasing, we lack tools for selecting the most effective treatments for each patient. One-third to one-half of patients with major depressive disorder do not respond to treatment, and we lack strategies for selecting among available treatments or expediting access to new treatment options. This critical review concentrates on functional neuroimaging as a modality of measurement for precision psychiatry. We begin by summarizing the current landscape of how functional neuroimaging-derived circuit predictors can forecast treatment outcomes in depression. Then, we outline the opportunities and challenges in integrating circuit predictors into clinical practice. We highlight one standardized and reproducible approach for quantifying brain circuit function at an individual level, which could serve as a model for clinical translation. We conclude by evaluating the prospects and practicality of employing neuroimaging tools, such as the one that we propose, in routine clinical practice.

Personalized functional brain network topography is associated with individual differences in youth cognition

Individual differences in cognition during childhood are associated with important social, physical, and mental health outcomes in adolescence and adulthood. Given that cortical surface arealization during development reflects the brain's functional prioritization, quantifying variation in the topography of functional brain networks across the developing cortex may provide insight regarding individual differences in cognition. We test this idea by defining personalized functional networks (PFNs) that account for interindividual heterogeneity in functional brain network topography in 9-10 year olds from the Adolescent Brain Cognitive Development℠ Study. Across matched discovery (n = 3525) and replication (n = 3447) samples, the total cortical representation of fronto-parietal PFNs positively correlates with general cognition. Cross-validated ridge regressions trained on PFN topography predict cognition in unseen data across domains, with prediction accuracy increasing along the cortex's sensorimotor-association organizational axis. These results establish that functional network topography heterogeneity is associated with individual differences in cognition before the critical transition into adolescence.

Major Depression and the Perception of Affective Instrumental and Expressive Gestures: An fMRI Investigation

Major depressive disorder (MDD) is associated with biased perception of human movement. Gesture is important for communication and in this study we investigated neural correlates of gesture perception in MDD. We hypothesised different neural activity between individuals with MDD and typical individuals when viewing instrumental and expressive gestures that were negatively or positively valenced. Differences were expected in brain areas associated with gesture perception, including superior temporal, frontal, and emotion processing regions. We recruited 12 individuals with MDD and 12 typical controls matched on age, gender, and handedness. They viewed gestures displayed by stick figures while functional magnetic resonance imaging (fMRI) was performed. Results of a random effects three-way mixed ANOVA indicated that individuals with MDD had greater activity in the right claustrum compared to controls, regardless of gesture type or valence. Additionally, we observed main effects of gesture type and valence, regardless of group. Perceiving instrumental compared to expressive gestures was associated with greater activity in the left cuneus and left superior temporal gyrus, while perceiving negative compared to positive gestures was associated with greater activity in the right precuneus and right lingual gyrus. We also observed a two-way interaction between gesture type and valence in various brain regions.

Depressive states in healthy subjects lead to biased processing in frontal-parietal ERPs during emotional stimuli

Subthreshold depressive (sD) states and major depression are considered to occur on a continuum, and there are only quantitative and not qualitative differences between depressive states in healthy individuals and patients with depression. sD is showing a progressively increasing prevalence and has a lifelong impact, and the social and clinical impacts of sD are no less than those of major depressive disorder (MDD). Because depression leads to biased cognition, patients with depression and healthy individuals show different visual processing properties. However, it remains unclear whether there are significant differences in visual information recognition among healthy individuals with various depressive states. In this study, we investigated the event-related potentials (ERPs) and event-related spectrum perturbation (ERSP) of healthy individuals with various depressive states during the perception of emotional visual stimulation. We show that different neural activities can be detected even among healthy individuals. We divided healthy participants into high, middle, and low depressive state groups and found that participants in a high depressive state had a lower P300 amplitude and significant differences in fast and slow neural responses in the frontal and parietal lobes. We anticipate our study to provide useful parameters for assessing the evaluation of depressive states in healthy individuals.

Issues and opportunities of digital phenotyping: ecological momentary assessment and behavioral sensing in protecting the young from suicide

Digital phenotyping refers to the collection of real-time biometric and personal data on digital tools, mainly smartphones, and wearables, to measure behaviors and variables that can be used as a proxy for complex psychophysiological conditions. Digital phenotyping might be used for diagnosis, clinical assessment, predicting changes and trajectories in psychological clinical conditions, and delivering tailored interventions according to individual real-time data. Recent works pointed out the possibility of using such an approach in the field of suicide risk in high-suicide-risk patients. Among the possible targets of such interventions, adolescence might be a population of interest, since they display higher odds of committing suicide and impulsive behaviors. The present work systematizes the available evidence of the data that might be used for digital phenotyping in the field of adolescent suicide and provides insight into possible personalized approaches for monitoring and treating suicidal risk or predicting risk trajectories. Specifically, the authors first define the field of digital phenotyping and its features, secondly, they organize the available literature to gather all the digital indexes (active and passive data) that can provide reliable information on the increase in the suicidal odds, lastly, they discuss the challenges and future directions of such an approach, together with its ethical implications.

Mapping the relationship of white matter lesions to depression in multiple sclerosis

Importance

Multiple sclerosis (MS) is an immune-mediated neurological disorder that affects nearly one million people in the United States. Up to 50% of patients with MS experience depression.

Objective

To investigate how white matter network disruption is related to depression in MS.

Design

Retrospective case-control study of participants who received research-quality 3-tesla neuroimaging as part of MS clinical care from 2010-2018. Analyses were performed from May 1 to September 30, 2022.

Setting

Single-center academic medical specialty MS clinic.

Participants

Participants with MS were identified via the electronic health record (EHR). All participants were diagnosed by an MS specialist and completed research-quality MRI at 3T. After excluding participants with poor image quality, 783 were included. Inclusion in the depression group (MS+Depression) required either: 1) ICD-10 depression diagnosis (F32-F34.*); 2) prescription of antidepressant medication; or 3) screening positive via Patient Health Questionnaire-2 (PHQ-2) or -9 (PHQ-9). Age- and sex-matched nondepressed comparators (MS-Depression) included persons with no depression diagnosis, no psychiatric medications, and were asymptomatic on PHQ-2/9.

Exposure

Depression diagnosis.

Main Outcomes and Measures

We first evaluated if lesions were preferentially located within the depression network compared to other brain regions. Next, we examined if MS+Depression patients had greater lesion burden, and if this was driven by lesions specifically in the depression network. Outcome measures were the burden of lesions (e.g., impacted fascicles) within a network and across the brain. Secondary measures included between-diagnosis lesion burden, stratified by brain network. Linear mixed-effects models were employed.

Results

Three hundred-eighty participants met inclusion criteria, (232 MS+Depression: age[SD]=49[12], %females=86; 148 MS-Depression: age[SD]=47[13], %females=79). MS lesions preferentially affected fascicles within versus outside the depression network (β=0.09, 95% CI=0.08-0.10, P<0.001). MS+Depression had more white matter lesion burden (β=0.06, 95% CI=0.01-0.10, P=0.015); this was driven by lesions within the depression network (β=0.02, 95% CI 0.003-0.040, P=0.020).

Conclusions and Relevance

We provide new evidence supporting a relationship between white matter lesions and depression in MS. MS lesions disproportionately impacted fascicles in the depression network. MS+Depression had more disease than MS-Depression, which was driven by disease within the depression network. Future studies relating lesion location to personalized depression interventions are warranted.

Behavioral and biologic characteristics of cancer-related cognitive impairment biotypes

Psychiatric diagnosis is moving away from symptom-based classification and towards multi-dimensional, biologically-based characterization, or biotyping. We previously identified three biotypes of chemotherapy-related cognitive impairment based on functional brain connectivity. In this follow-up study of 80 chemotherapy-treated breast cancer survivors and 80 non-cancer controls, we evaluated additional factors to help explain biotype expression: neurofunctional stability, brain age, apolipoprotein (APOE) genotype, and psychoneurologic symptoms. We also compared the discriminative ability of a traditional, symptom-based cognitive impairment definition with that of biotypes. We found significant differences in cortical brain age (F = 10.50, p < 0.001), neurofunctional stability (F = 2.83, p = 0.041), APOE e4 genotype (X2 = 7.68, p = 0.050), and psychoneurological symptoms (Pillai = 0.378, p < 0.001) across the three biotypes. The more resilient Biotype 2 demonstrated significantly higher neurofunctional stability compared to the other biotypes. Symptom-based classification of cognitive impairment did not differentiate biologic or other behavioral variables, suggesting that traditional categorization of cancer-related cognitive effects may miss important characteristics which could inform targeted treatment strategies. Additionally, biotyping, but not symptom-typing, was able to distinguish survivors with cognitive versus psychological effects. Our results suggest that Biotype 1 survivors might benefit from first addressing symptoms of anxiety and fatigue, Biotype 3 might benefit from a treatment plan which includes sleep hygiene, and Biotype 2 might benefit most from cognitive skills training or rehabilitation. Future research should include additional demographic and clinical information to further investigate biotype expression related to risk and resilience and examine integration of more clinically feasible imaging approaches.

Negative association between anterior insula activation and resilience during sustained attention: an fMRI twin study

BACKGROUND

While previous studies have suggested that higher levels of cognitive performance may be related to greater wellbeing and resilience, little is known about the associations between neural circuits engaged by cognitive tasks and wellbeing and resilience, and whether genetics or environment contribute to these associations.

METHODS

The current study consisted of 253 monozygotic and dizygotic adult twins, including a subsample of 187 early-life trauma-exposed twins, with functional Magnetic Resonance Imaging data from the TWIN-E study. Wellbeing was measured using the COMPAS-W Wellbeing Scale while resilience was defined as a higher level of positive adaptation (higher levels of wellbeing) in the presence of trauma exposure. We probed both sustained attention and working memory processes using a Continuous Performance Task in the scanner.

RESULTS

We found significant negative associations between resilience and activation in the bilateral anterior insula engaged during sustained attention. Multivariate twin modelling showed that the association between resilience and the left and right insula activation was mostly driven by common genetic factors, accounting for 71% and 87% of the total phenotypic correlation between these variables, respectively. There were no significant associations between wellbeing/resilience and neural activity engaged during working memory updating.

CONCLUSIONS

The findings suggest that greater resilience to trauma is associated with less activation of the anterior insula during a condition requiring sustained attention but not working memory updating. This possibly suggests a pattern of 'neural efficiency' (i.e. more efficient and/or attenuated activity) in people who may be more resilient to trauma.

Hierarchical functional system development supports executive function

In this perspective, we describe how developmental improvements in youth executive function (EF) are supported by hierarchically organized maturational changes in functional brain systems. We first highlight evidence that functional brain systems are embedded within a hierarchical sensorimotor-association axis of cortical organization. We then review data showing that functional system developmental profiles vary along this axis: systems near the associative end become more functionally segregated, while those in the middle become more integrative. Developmental changes that strengthen the hierarchical organization of the cortex may support EF by facilitating top-down information flow and balancing within- and between-system communication. We propose a central role for attention and frontoparietal control systems in the maturation of healthy EF and suggest that reduced functional system differentiation across the sensorimotor-association axis contributes to transdiagnostic EF deficits.

Decomposing Working Memory in Recurrent Major Depression: Impaired Encoding and Limited Maintenance Immune-to-Encoding Constraint

It is generally believed that working memory (WM) is dysfunctional in depression. However, whether this impaired performance originates from impaired encoding, maintenance or both stages is still unclear. Here, we aimed to decompose the abnormal characteristics of encoding and maintenance in patients with recurrent major depressive disorder (MDD). Thirty patients and thirty-nine healthy controls completed a spatial working memory task where the encoding time and the retention time could vary under different load levels. Encoding performance was assessed by comparing accuracies between short and long encoding times, and maintenance performance was assessed by comparing accuracies between short and long retention times. The results show a lower performance in depression than the controls. However, while the decreased accuracy by long retention (vs. short retention) was increased by a short encoding time in the control group, the retention performance of the depression group did not further suffer from the short encoding time. The generally impaired encoding, together with limited maintenance of immunity against the constrained encoding time, suggests a common bias for fixed internal processing over external processing in recurrent MDD. The paradigm provided in this study can be a convenient and efficient clinical test for assessing the WM encoding and maintenance function.

The Role of Alpha Oscillations among the Main Neuropsychiatric Disorders in the Adult and Developing Human Brain: Evidence from the Last 10 Years of Research

Alpha oscillations (7-13 Hz) are the dominant rhythm in both the resting and active brain. Accordingly, translational research has provided evidence for the involvement of aberrant alpha activity in the onset of symptomatological features underlying syndromes such as autism, schizophrenia, major depression, and Attention Deficit and Hyperactivity Disorder (ADHD). However, findings on the matter are difficult to reconcile due to the variety of paradigms, analyses, and clinical phenotypes at play, not to mention recent technical and methodological advances in this domain. Herein, we seek to address this issue by reviewing the literature gathered on this topic over the last ten years. For each neuropsychiatric disorder, a dedicated section will be provided, containing a concise account of the current models proposing characteristic alterations of alpha rhythms as a core mechanism to trigger the associated symptomatology, as well as a summary of the most relevant studies and scientific contributions issued throughout the last decade. We conclude with some advice and recommendations that might improve future inquiries within this field.

Reduced neural responses to reward reflect anhedonia and inattention: an ERP study

An inhibited neural response to reward is typical of clinical depression and can predict an individual's overall depressive symptoms. However, the mechanism underlying this are unclear. Previous studies have found that anhedonia and inattention may mediate the relationship between reward sensitivity and depressive symptoms. Therefore, this study aimed to verify the relationship between reward sensitivity and overall depressive symptoms in a depressive tendency sample as well as to explore the mechanism underlying the ability of neural responses to reward to predict overall depressive symptoms via a mediation model. Sixty-four participants (33 with depressive tendencies and 31 without; dichotomized by BDI-II) finished simple gambling tasks while their event-related potential components (ERPs) were recorded and compared. Linear regression was conducted to verify the predictive effect of ERPs on overall depressive symptoms. A multiple mediator model was used, with anhedonia and distractibility as mediators reward sensitivity and overall depressive symptoms. The amplitude of reward positivity (ΔRewP) was greater in healthy controls compared to those with depressive tendencies (p = 0.006). Both the gain-locked ERP component (b = - 1.183, p = 0.007) and the ΔRewP (b = - 0.991, p = 0.024) could significantly negatively predict overall depressive symptoms even after controlling for all anxiety symptoms. The indirect effects of anhedonia and distractibility were significant (both confidence intervals did not contain 0) while the direct effect of reward sensitivity on depressive symptom was not significant (lower confidence interval = - 0.320, upper confidence interval = 0.065). Individuals with depressive tendencies display impaired neural responses to reward compared to healthy controls and reduced individual neural responses to reward may reflect the different biotypes of depression such as anhedonia and inattention.

Aberrant brain connectivity is associated with childhood maltreatment in individuals with major depressive disorder

Although childhood maltreatment confers a high risk for the development of major depressive disorder, the neurobiological mechanisms underlying this connection remain unknown. The present study sought to identify the specific resting-state networks associated with childhood maltreatment. We recruited major depressive disorder patients with and without a history of childhood maltreatment (n = 31 and n = 30, respectively) and healthy subjects (n = 80). We used independent component analysis to compute inter- and intra- network connectivity. We found that individuals with major depressive disorder and childhood maltreatment could be characterized by the following network disconnectivity model relative to healthy subjects: (i) decreased intra-network connectivity in the left frontoparietal network and increased intra-network connectivity in the right frontoparietal network, (ii) decreased inter-network connectivity in the posterior default mode network-auditory network, posterior default mode network-limbic system, posterior default mode network-anterior default mode network, auditory network-medial visual network, lateral visual network - medial visual network, medial visual network-sensorimotor network, medial visual network - anterior default mode network, occipital pole visual network-dorsal attention network, and posterior default mode network-anterior default mode network, and (iii) increased inter-network connectivity in the sensorimotor network-ventral attention network, and dorsal attention network-ventral attention network. Moreover, we found significant correlations between the severity of childhood maltreatment and the intra-network connectivity of the frontoparietal network. Our study demonstrated that childhood maltreatment is integrally associated with aberrant network architecture in patients with major depressive disorder.

The Effects of Self-Perceived Parenting Attitudes on Visuo-Spatial Attention and Mental Rotation Abilities among Adolescents

Highlights

Abstract

The present study aimed to investigate the effect of adolescents’ perceived negative evaluation of parenting on their visuo-spatial attention and mental rotation abilities. The useful field of view (UFOV) and mental rotation tasks were used to measure visuo-spatial attention and mental rotation abilities among adolescents. The experimental groups were divided into the negatively evaluating group (M_Age = 18.44, SD = 0.87, 20.7% girls) and positively evaluating group (M_Age = 18.40, SD = 0.81, 23.3% girls) based on their scores on the self-perceived parenting attitude scales. The UFOV task showed lesser accuracy of the negatively evaluating group when compared to the positively evaluating one in target perception presented in 20° visual angle, indicating a deteriorated visuo-spatial attention ability in the negatively evaluating group. In the mental rotation task, the negatively evaluating group exhibited a small trade-off effect between response times and rotation angles, which implied an impatient strategy was employed to perform the task, whereas such a trade-off was not observed in the positively evaluating group. Thus, both experimental groups differed in terms of their visual attention and mental spatial abilities. This study suggests that the reduced visuo-spatial attention and mental rotation abilities may act as precursors for serious psychological symptoms caused by the negative self-evaluation of their parents’ parenting attitudes.

Spatial attention impairments are characterized by specific electro-encephalographic correlates and partially mediate the association between early life stress and anxiety

Although impaired attention is a diagnostic feature of anxiety disorders, we lack an understanding of which aspects of attention are impaired, the neurobiological basis of these impairments, and the contribution of stressors. To address these gaps in knowledge, we developed and tested behavioral tasks designed to parse the subdomains of attention impairments associated with anxiety symptoms and used electro-encephalographic (EEG) recordings to probe the neural basis of attentional performance. Participants were n = 55 individuals aged 18-35 with mild-to-moderate mood and anxiety symptoms. We also assessed stressful life events that may impact mental health and attention abilities, including stressors that occurred in early life before age 18 years. Severity of anxiety was found to be specifically associated with impairments in spatial attention but not feature-based attention. These impairments in spatial attention also partially mediated the association between early-life stressors and anxiety symptoms. Impairments in spatial selective attention were associated with decreased posterior alpha oscillations in EEG recordings in a subsample of participants, whereas spatial divided attention impairments were associated with decreased frontocentral theta oscillations. Our results provide a thorough characterization of attention impairments associated with anxiety, their EEG correlates, and the impact of stressors both in early life and adulthood.

Ethical Development of Digital Phenotyping Tools for Mental Health Applications: Delphi Study

BACKGROUND

Digital phenotyping (also known as personal sensing, intelligent sensing, or body computing) involves the collection of biometric and personal data in situ from digital devices, such as smartphones, wearables, or social media, to measure behavior or other health indicators. The collected data are analyzed to generate moment-by-moment quantification of a person's mental state and potentially predict future mental states. Digital phenotyping projects incorporate data from multiple sources, such as electronic health records, biometric scans, or genetic testing. As digital phenotyping tools can be used to study and predict behavior, they are of increasing interest for a range of consumer, government, and health care applications. In clinical care, digital phenotyping is expected to improve mental health diagnoses and treatment. At the same time, mental health applications of digital phenotyping present significant areas of ethical concern, particularly in terms of privacy and data protection, consent, bias, and accountability.

OBJECTIVE

This study aims to develop consensus statements regarding key areas of ethical guidance for mental health applications of digital phenotyping in the United States.

METHODS

We used a modified Delphi technique to identify the emerging ethical challenges posed by digital phenotyping for mental health applications and to formulate guidance for addressing these challenges. Experts in digital phenotyping, data science, mental health, law, and ethics participated as panelists in the study. The panel arrived at consensus recommendations through an iterative process involving interviews and surveys. The panelists focused primarily on clinical applications for digital phenotyping for mental health but also included recommendations regarding transparency and data protection to address potential areas of misuse of digital phenotyping data outside of the health care domain.

RESULTS

The findings of this study showed strong agreement related to these ethical issues in the development of mental health applications of digital phenotyping: privacy, transparency, consent, accountability, and fairness. Consensus regarding the recommendation statements was strongest when the guidance was stated broadly enough to accommodate a range of potential applications. The privacy and data protection issues that the Delphi participants found particularly critical to address related to the perceived inadequacies of current regulations and frameworks for protecting sensitive personal information and the potential for sale and analysis of personal data outside of health systems.

CONCLUSIONS

The Delphi study found agreement on a number of ethical issues to prioritize in the development of digital phenotyping for mental health applications. The Delphi consensus statements identified general recommendations and principles regarding the ethical application of digital phenotyping to mental health. As digital phenotyping for mental health is implemented in clinical care, there remains a need for empirical research and consultation with relevant stakeholders to further understand and address relevant ethical issues.

Impaired executive function exacerbates neural markers of posttraumatic stress disorder

BACKGROUND

A major obstacle in understanding and treating posttraumatic stress disorder (PTSD) is its clinical and neurobiological heterogeneity. To address this barrier, the field has become increasingly interested in identifying subtypes of PTSD based on dysfunction in neural networks alongside cognitive impairments that may underlie the development and maintenance of symptoms. The current study aimed to determine if subtypes of PTSD, based on normative-based cognitive dysfunction across multiple domains, have unique neural network signatures.

METHODS

In a sample of 271 veterans (90% male) that completed both neuropsychological testing and resting-state fMRI, two complementary, whole-brain functional connectivity analyses explored the link between brain functioning, PTSD symptoms, and cognition.

RESULTS

At the network level, PTSD symptom severity was associated with reduced negative coupling between the limbic network (LN) and frontal-parietal control network (FPCN), driven specifically by the dorsolateral prefrontal cortex and amygdala Hubs of Dysfunction. Further, this relationship was uniquely moderated by executive function (EF). Specifically, those with PTSD and impaired EF had the strongest marker of LN-FPCN dysregulation, while those with above-average EF did not exhibit PTSD-related dysregulation of these networks.

CONCLUSION

These results suggest that poor executive functioning, alongside LN-FPCN dysregulation, may represent a neurocognitive subtype of PTSD.

Disrupted hemispheric connectivity specialization in patients with major depressive disorder: Evidence from the REST-meta-MDD Project

BACKGROUND

Functional specialization is a feature of human brain for understanding the pathophysiology of major depressive disorder (MDD). The degree of human specialization refers to within and cross hemispheric interactions. However, most previous studies only focused on interhemispheric connectivity in MDD, and the results varied across studies. Hence, brain functional connectivity asymmetry in MDD should be further studied.

METHODS

Resting-state fMRI data of 753 patients with MDD and 451 healthy controls were provided by REST-meta-MDD Project. Twenty-five project contributors preprocessed their data locally with the Data Processing Assistant State fMRI software and shared final indices. The parameter of asymmetry (PAS), a novel voxel-based whole-brain quantitative measure that reflects inter- and intrahemispheric asymmetry, was reported. We also examined the effects of age, sex and clinical variables (including symptom severity, illness duration and three depressive phenotypes).

RESULTS

Compared with healthy controls, patients with MDD showed increased PAS scores (decreased hemispheric specialization) in most of the areas of default mode network, control network, attention network and some regions in the cerebellum and visual cortex. Demographic characteristics and clinical variables have significant effects on these abnormalities.

LIMITATIONS

Although a large sample size could improve statistical power, future independent efforts are needed to confirm our results.

CONCLUSIONS

Our results highlight the idea that many brain networks contribute to broad clinical pathophysiology of MDD, and indicate that a lateralized, efficient and economical brain information processing system is disrupted in MDD. These findings may help comprehensively clarify the pathophysiology of MDD in a new hemispheric specialization perspective.

EEG as a Functional Marker of Nicotine Activity: Evidence From a Pilot Study of Adults With Late-Life Depression

Late-life depression (LLD) is a debilitating condition that is associated with poor response to antidepressant medications and deficits in cognitive performance. Nicotinic cholinergic stimulation has emerged as a potentially effective candidate to improve cognitive performance in patients with cognitive impairment. Previous studies of nicotinic stimulation in animal models and human populations with cognitive impairment led to examining potential cognitive and mood effects of nicotinic stimulation in older adults with LLD. We report results from a pilot study of transdermal nicotine in LLD testing whether nicotine treatment would enhance cognitive performance and mood. The study used electroencephalography (EEG) recordings as a tool to test for potential mechanisms underlying the effect of nicotine. Eight non-smoking participants with LLD completed EEG recordings at baseline and after 12 weeks of transdermal nicotine treatment (NCT02816138). Nicotine augmentation treatment was associated with improved performance on an auditory oddball task. Analysis of event-related oscillations showed that nicotine treatment was associated with reduced beta desynchronization at week 12 for both standard and target trials. The change in beta power on standard trials was also correlated with improvement in mood symptoms. This pilot study provides preliminary evidence for the impact of nicotine in modulating cortical activity and improving mood in depressed older adults and shows the utility of using EEG as a marker of functional engagement in nicotinic interventions in clinical geriatric patients.

fMRI Neurofeedback-Enhanced Cognitive Reappraisal Training in Depression: A Double-Blind Comparison of Left and Right vlPFC Regulation

Affective disorders are associated with maladaptive emotion regulation strategies. In particular, the left more than the right ventrolateral prefrontal cortex (vlPFC) may insufficiently regulate emotion processing, e.g., in the amygdala. A double-blind cross-over study investigated NF-supported cognitive reappraisal training in major depression (n = 42) and age- and gender-matched controls (n = 39). In a randomized order, participants trained to upregulate either the left or the right vlPFC during cognitive reappraisal of negative images on two separate days. We wanted to confirm regional specific NF effects with improved learning for left compared to right vlPFC (ClinicalTrials.gov NCT03183947). Brain responses and connectivity were studied with respect to training progress, gender, and clinical outcomes in a 4-week follow-up. Increase of vlPFC activity was stronger after NF training from the left- than the right-hemispheric ROI. This regional-specific NF effect during cognitive reappraisal was present across patients with depression and controls and supports a central role of the left vlPFC for cognitive reappraisal. Further, the activity in the left target region was associated with increased use of cognitive reappraisal strategies (r = 0.48). In the 4-week follow-up, 75% of patients with depression reported a successful application of learned strategies in everyday life and 55% a clinically meaningful symptom improvement suggesting clinical usability.

Stress Markers for Mental States and Biotypes of Depression and Anxiety: A Scoping Review and Preliminary Illustrative Analysis

Depression and anxiety disrupt daily function and their effects can be long-lasting and devastating, yet there are no established physiological indicators that can be used to predict onset, diagnose, or target treatments. In this review, we conceptualize depression and anxiety as maladaptive responses to repetitive stress. We provide an overview of the role of chronic stress in depression and anxiety and a review of current knowledge on objective stress indicators of depression and anxiety. We focused on cortisol, heart rate variability and skin conductance that have been well studied in depression and anxiety and implicated in clinical emotional states. A targeted PubMed search was undertaken prioritizing meta-analyses that have linked depression and anxiety to cortisol, heart rate variability and skin conductance. Consistent findings include reduced heart rate variability across depression and anxiety, reduced tonic and phasic skin conductance in depression, and elevated cortisol at different times of day and across the day in depression. We then provide a brief overview of neural circuit disruptions that characterize particular types of depression and anxiety. We also include an illustrative analysis using predictive models to determine how stress markers contribute to specific subgroups of symptoms and how neural circuits add meaningfully to this prediction. For this, we implemented a tree-based multi-class classification model with physiological markers of heart rate variability as predictors and four symptom subtypes, including normative mood, as target variables. We achieved 40% accuracy on the validation set. We then added the neural circuit measures into our predictor set to identify the combination of neural circuit dysfunctions and physiological markers that accurately predict each symptom subtype. Achieving 54% accuracy suggested a strong relationship between those neural-physiological predictors and the mental states that characterize each subtype. Further work to elucidate the complex relationships between physiological markers, neural circuit dysfunction and resulting symptoms would advance our understanding of the pathophysiological pathways underlying depression and anxiety.

Cognitive dysfunction in mice lacking proper glucocorticoid receptor dimerization

Stress is a major risk factor for depression and anxiety. One of the effects of stress is the (over-) activation of the hypothalamic-pituitary-adrenal (HPA) axis and the release of stress hormones such as glucocorticoids (GCs). Chronically increased stress hormone levels have been shown to have detrimental effects on neuronal networks by inhibiting neurotrophic processes particularly in the hippocampus proper. Centrally, GCs modulate metabolic as well as behavioural processes by activating two classes of corticoid receptors, high-affinity mineralocorticoid receptors (MR) and low-affinity glucocorticoid receptors (GR). Upon activation, GR can modulate gene transcription either as a monomeric protein, or as a dimer interacting directly with DNA. GR can also modulate cellular processes via non-genomic mechanisms, for example via a GPCR-protein interaction. We evaluated the behavioral phenotype in mice with a targeted mutation in the GR in a FVB/NJ background. In GRdim/dim mice, GR proteins form poor homodimers, while the GR monomer remains intact. We evaluated the effect of poor GR dimerization on hippocampus-dependent cognition as well as on exploration and emotional behavior under baseline and chronically increased stress hormone levels. We found that GRdim/dim mice did not behave differently from GRwt/wt littermates under baseline conditions. However, after chronic elevation of stress hormone levels, GRdim/dim mice displayed a significant impairment in hippocampus-dependent memory compared to GRwt/wt mice, which correlated with differential expression of hippocampal Bdnf/TrkB and Fkbp5.

Paying attention to attention in depression

Attention is the gate through which sensory information enters our conscious experiences. Oftentimes, patients with major depressive disorder (MDD) complain of concentration difficulties that negatively impact their day-to-day function, and these attention problems are not alleviated by current first-line treatments. In spite of attention's influence on many aspects of cognitive and emotional functioning, and the inclusion of concentration difficulties in the diagnostic criteria for MDD, the focus of depression as a disease is typically on mood features, with attentional features considered less of an imperative for investigation. Here, we summarize the breadth and depth of findings from the cognitive neurosciences regarding the neural mechanisms supporting goal-directed attention in order to better understand how these might go awry in depression. First, we characterize behavioral impairments in selective, sustained, and divided attention in depressed individuals. We then discuss interactions between goal-directed attention and other aspects of cognition (cognitive control, perception, and decision-making) and emotional functioning (negative biases, internally-focused attention, and interactions of mood and attention). We then review evidence for neurobiological mechanisms supporting attention, including the organization of large-scale neural networks and electrophysiological synchrony. Finally, we discuss the failure of current first-line treatments to alleviate attention impairments in MDD and review evidence for more targeted pharmacological, brain stimulation, and behavioral interventions. By synthesizing findings across disciplines and delineating avenues for future research, we aim to provide a clearer outline of how attention impairments may arise in the context of MDD and how, mechanistically, they may negatively impact daily functioning across various domains.