Oscillatory and non-oscillatory features of the magnetoencephalic sensorimotor rhythm in Parkinson's disease.

Parkinson's disease (PD) is associated with changes in neural activity in the sensorimotor alpha and beta bands. Using magnetoencephalography (MEG), we investigated the role of spontaneous neuronal activity within the somatosensory cortex in a large cohort of early- to mid-stage PD patients (N = 78) on Parkinsonian medication and age- and sex-matched healthy controls (N = 60) using source reconstructed resting-state MEG. We quantified features of the time series data in terms of oscillatory alpha power and central alpha frequency, beta power and central beta frequency, and 1/f broadband characteristics using power spectral density. Furthermore, we characterised transient oscillatory burst events in the mu-beta band time-domain signals. We examined the relationship between these signal features and the patients' disease state, symptom severity, age, sex, and cortical thickness. PD patients and healthy controls differed on PSD broadband characteristics, with PD patients showing a steeper 1/f exponential slope and higher 1/f offset. PD patients further showed a steeper age-related decrease in the burst rate. Out of all the signal features of the sensorimotor activity, the burst rate was associated with increased severity of bradykinesia, whereas the burst duration was associated with axial symptoms. Our study shows that general non-oscillatory features (broadband 1/f exponent and offset) of the sensorimotor signals are related to disease state and oscillatory burst rate scales with symptom severity in PD.

The Swedish National Facility for Magnetoencephalography Parkinson's disease dataset.

Parkinson's disease (PD) is characterised by a loss of dopamine and dopaminergic cells. The consequences hereof are widespread network disturbances in brain function. It is an ongoing topic of investigation how the disease-related changes in brain function manifest in PD relate to clinical symptoms. We present The Swedish National Facility for Magnetoencephalography Parkinson's Disease Dataset (NatMEG-PD) as an Open Science contribution to identify the functional neural signatures of Parkinson's disease and contribute to diagnosis and treatment. The dataset contains whole-head magnetoencephalographic (MEG) recordings from 66 well-characterised PD patients on their regular dose of dopamine replacement therapy and 68 age- and sex-matched healthy controls. NatMEG-PD contains three-minute eyes-closed resting-state MEG, MEG during an active movement task, and MEG during passive movements. The data includes anonymised MRI for source analysis and clinical scores. MEG data is rich in nature and can be used to explore numerous functional features. By sharing these data, we hope other researchers will contribute to advancing our understanding of the relationship between brain activity and disease state or symptoms.

Alternative beliefs in psychedelic drug users.

Previous research has suggested that classical psychedelics can foster significant and enduring changes in personality traits and subjective wellbeing. Despite the lack of evidence for adverse effects on mental health stemming from psychedelic use, concerns persist regarding the capacity of these substances to modulate information processing and attitudes towards factual data. The aim of the present study was to investigate the propensity for accepting alternative facts and the general treatment of knowledge within a sample of 392 participants, 233 of whom reported at least a single incidence of psychedelic use in their lifetime. To do this, we leveraged step-wise methods of linear modelling investigating effects of demographics, psychiatric conditions and concomitant drug use. Our findings revealed a moderate positive association between psychedelic use and beliefs in alternative facts, as well as the specific belief that facts are politically influenced. However, no links were found for favouring intuition over evidence when confirming facts. Among other investigated drugs, only alcohol was negatively associated with beliefs in alternative facts. Taken together, our results support the link between psychedelic use and non-conformist thinking styles, which can be attributed to the psychological effects of the drugs themselves, but may also mirror a common trait related to unconventional beliefs and illicit substance use.

Structural brain differences related to compulsive sexual behavior disorder.

Background and aims: Compulsive sexual behavior disorder (CSBD) has been included as an impulse control disorder in the International Classification of Diseases (ICD-11). However, the neurobiological mechanisms underlying CSBD remain largely unknown, and given previous indications of addiction-like mechanisms at play, the aim of the present study was to investigate if CSBD is associated with structural brain differences in regions involved in reward processing. Methods: We analyzed structural MRI data of 22 male CSBD patients (mean = 38.7 years, SD = 11.7) and 20 matched healthy controls (HC; mean = 37.6 years, SD = 8.5). Main outcome measures were regional cortical thickness and surface area. We also tested for case-control differences in subcortical structures and the effects of demographic and clinical variables, such as CSBD symptom severity, on neuroimaging outcomes. Moreover, we explored case-control differences in regions outside our hypothesis including white matter. Results: CSBD patients had significantly lower cortical surface area in right posterior cingulate cortex than HC. We found negative correlations between right posterior cingulate area and CSBD symptoms scores. There were no group differences in subcortical volume. Conclusions: Our findings suggest that CSBD is associated with structural brain differences, which contributes to a better understanding of CSBD and encourages further clarifications of the neurobiological mechanisms underlying the disorder.

Mega-analysis of association between obesity and cortical morphology in bipolar disorders: ENIGMA study in 2832 participants.

BACKGROUND: Obesity is highly prevalent and disabling, especially in individuals with severe mental illness including bipolar disorders (BD). The brain is a target organ for both obesity and BD. Yet, we do not understand how cortical brain alterations in BD and obesity interact. METHODS: We obtained body mass index (BMI) and MRI-derived regional cortical thickness, surface area from 1231 BD and 1601 control individuals from 13 countries within the ENIGMA-BD Working Group. We jointly modeled the statistical effects of BD and BMI on brain structure using mixed effects and tested for interaction and mediation. We also investigated the impact of medications on the BMI-related associations. RESULTS: BMI and BD additively impacted the structure of many of the same brain regions. Both BMI and BD were negatively associated with cortical thickness, but not surface area. In most regions the number of jointly used psychiatric medication classes remained associated with lower cortical thickness when controlling for BMI. In a single region, fusiform gyrus, about a third of the negative association between number of jointly used psychiatric medications and cortical thickness was mediated by association between the number of medications and higher BMI. CONCLUSIONS: We confirmed consistent associations between higher BMI and lower cortical thickness, but not surface area, across the cerebral mantle, in regions which were also associated with BD. Higher BMI in people with BD indicated more pronounced brain alterations. BMI is important for understanding the neuroanatomical changes in BD and the effects of psychiatric medications on the brain.

Development of the key performance indicators for digital health interventions: A scoping review.

Background: Digital health interventions offer new methods for delivering healthcare, with the potential to innovate healthcare services. Key performance indicators play a role in the evaluation, measurement, and improvement in healthcare quality and service performance. The aim of this scoping review was to identify current knowledge and evidence surrounding the development of key performance indicators for digital health interventions. Methods: A literature search was conducted across ten key databases: AMED - The Allied and Complementary Medicine Database, CINAHL - Complete, Health Source: Nursing/Academic Edition, MEDLINE, APA PsycINFO, EMBASE, EBM Reviews - Cochrane Database of Systematic Reviews, EBM Reviews - Database of Abstracts of Reviews of Effects, EBM Reviews - Health Technology Assessment, and IEEE Xplore. Results: Five references were eligible for the review. Two were articles on original research studies of a specific digital health intervention, and two were overviews of methods for developing digital health interventions (not specific to a single digital health intervention). All the included reports discussed the involvement of stakeholders in developing key performance indicators for digital health interventions. The step of identifying and defining the key performance indicators was completed using various methodologies, but all centred on a form of stakeholder involvement. Potential options for stakeholder involvement for key performance indicator identification include the use of an elicitation framework, a factorial survey approach, or a Delphi study. Conclusions: Few articles were identified, highlighting a significant gap in evidence-based knowledge in this domain. All the included articles discussed the involvement of stakeholders in developing key performance indicators for digital health interventions, which were performed using various methodologies. The articles acknowledged a lack of literature related to key performance indicator development for digital health interventions. To allow comparability between key performance indicator initiatives and facilitate work in the field, further research would be beneficial to develop a common methodology for key performance indicators development for digital health interventions.

CODE-EHR best practice framework for the use of structured electronic healthcare records in clinical research.

Big data is central to new developments in global clinical science aiming to improve the lives of patients. Technological advances have led to the routine use of structured electronic healthcare records with the potential to address key gaps in clinical evidence. The covid-19 pandemic has demonstrated the potential of big data and related analytics, but also important pitfalls. Verification, validation, and data privacy, as well as the social mandate to undertake research are key challenges. The European Society of Cardiology and the BigData@Heart consortium have brought together a range of international stakeholders, including patient representatives, clinicians, scientists, regulators, journal editors and industry. We propose the CODE-EHR Minimum Standards Framework as a means to improve the design of studies, enhance transparency and develop a roadmap towards more robust and effective utilisation of healthcare data for research purposes.

CODE-EHR best-practice framework for the use of structured electronic health-care records in clinical research.

Big data is important to new developments in global clinical science that aim to improve the lives of patients. Technological advances have led to the regular use of structured electronic health-care records with the potential to address key deficits in clinical evidence that could improve patient care. The COVID-19 pandemic has shown this potential in big data and related analytics but has also revealed important limitations. Data verification, data validation, data privacy, and a mandate from the public to conduct research are important challenges to effective use of routine health-care data. The European Society of Cardiology and the BigData@Heart consortium have brought together a range of international stakeholders, including representation from patients, clinicians, scientists, regulators, journal editors, and industry members. In this Review, we propose the CODE-EHR minimum standards framework to be used by researchers and clinicians to improve the design of studies and enhance transparency of study methods. The CODE-EHR framework aims to develop robust and effective utilisation of health-care data for research purposes.

Neural and behavioral correlates of sexual stimuli anticipation point to addiction-like mechanisms in compulsive sexual behavior disorder.

Background and aims: Compulsive sexual behavior disorder (CSBD) is characterized by persistent patterns of failure to control sexual impulses resulting in repetitive sexual behavior, pursued despite adverse consequences. Despite previous indications of addiction-like mechanisms and the recent impulse-control disorder classification in the International Classification of Diseases (ICD-11), the neurobiological processes underlying CSBD are unknown. Methods: We designed and applied a behavioral paradigm aimed at disentangling processes related to anticipation and viewing of erotic stimuli. In 22 male CSBD patients (age: M = 38.7, SD = 11.7) and 20 healthy male controls (HC, age: M = 37.6, SD = 8.5), we measured behavioral responses and neural activity during functional magnetic resonance imaging (fMRI). The main outcomes were response time differences between erotic and non-erotic trials and ventral striatum (VS) activity during anticipation of visual stimuli. We related these outcomes with each other, to CSBD diagnosis, and symptom severity. Results: We found robust case-control differences on behavioral level, where CSBD patients showed larger response time differences between erotic and non-erotic trials than HC. The task induced reliable main activations within each group. While we did not observe significant group differences in VS activity, VS activity during anticipation correlated with response time differences and self-ratings for anticipation of erotic stimuli. Discussion and Conclusions: Our results support the validity and applicability of the developed task and suggest that CSBD is associated with altered behavioral correlates of anticipation, which were associated with ventral striatum activity during anticipation of erotic stimuli. This supports the idea that addiction-like mechanisms play a role in CSBD.

Enhanced Instructed Fear Learning in Delusion-Proneness.

Psychosis is associated with distorted perceptions and deficient bottom-up learning such as classical fear conditioning. This has been interpreted as reflecting imprecise priors in low-level predictive coding systems. Paradoxically, overly strong beliefs, such as overvalued beliefs and delusions, are also present in psychosis-associated states. In line with this, research has suggested that patients with psychosis and associated phenotypes rely more on high-order priors to interpret perceptual input. In this behavioural and fMRI study we studied two types of fear learning, i.e., instructed fear learning mediated by verbal suggestions about fear contingencies and classical fear conditioning mediated by low level associative learning, in delusion proneness-a trait in healthy individuals linked to psychotic disorders. Subjects were shown four faces out of which two were coupled with an aversive stimulation (CS+) while two were not (CS-) in a fear conditioning procedure. Before the conditioning, subjects were informed about the contingencies for two of the faces of each type, while no information was given for the two other faces. We could thereby study the effect of both classical fear conditioning and instructed fear learning. Our main outcome variable was evaluative rating of the faces. Simultaneously, fMRI-measurements were performed to study underlying mechanisms. We postulated that instructed fear learning, measured with evaluative ratings, is stronger in psychosis-related phenotypes, in contrast to classical fear conditioning that has repeatedly been shown to be weaker in these groups. In line with our hypothesis, we observed significantly larger instructed fear learning on a behavioural level in delusion-prone individuals (n = 20) compared to non-delusion-prone subjects (n = 23; n = 20 in fMRI study). Instructed fear learning was associated with a bilateral activation of lateral orbitofrontal cortex that did not differ significantly between groups. However, delusion-prone subjects showed a stronger functional connectivity between right lateral orbitofrontal cortex and regions processing fear and pain. Our results suggest that psychosis-related states are associated with a strong instructed fear learning in addition to previously reported weak classical fear conditioning. Given the similarity between nocebo paradigms and instructed fear learning, our results also have an impact on understanding why nocebo effects differ between individuals.

Changes in emotion processing in early Parkinson's disease reflect disease progression.

OBJECTIVE: Parkinson's disease (PD) is a neurodegenerative disorder which can substantially affect nonmotor functions related to emotional processing. We aimed to examine the underlying differences in emotional processing in PD by comparing how early-stage PD patients recognize, rate, and react to facial, bodily, and vocal emotional stimuli to that of healthy controls (HC). METHOD: We compared emotion recognition, emotional rating bias, and emotional response range between a PD patient group (n = 33) and a HC group (n = 29). Pearson's correlations were conducted to evaluate the relationship between emotion processing measures and clinical outcome measures in each group. RESULTS: PD patients showed an enhanced emotion processing as compared to HC. They were overall more accurate than HC's at identifying correct emotions and furthermore showed an increase in emotional ratings and reactions to both positive and negative stimuli that scaled with increased symptom severity, thereby yielding significant correlations between clinical outcomes and emotional range in the PD patient group. CONCLUSION: Our results suggest that alterations in emotional processing reflect disease progression in early PD. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Large-scale societal dynamics are reflected in human mood and brain.

The stock market is a bellwether of socio-economic changes that may directly affect individual well-being. Using large-scale UK-biobank data generated over 14 years, we applied specification curve analysis to rigorously identify significant associations between the local stock market index (FTSE100) and 479,791 UK residents' mood, as well as their alcohol intake and blood pressure adjusting the results for a large number of potential confounders, including age, sex, linear and non-linear effects of time, research site, other stock market indexes. Furthermore, we found similar associations between FTSE100 and volumetric measures of affective brain regions in a subsample (n = 39,755; measurements performed over 5.5 years), which were particularly strong around phase transitions characterized by maximum volatility in the market. The main findings did not depend on applied effect-size estimation criteria (linear methods or mutual information criterion) and were replicated in two independent US-based studies (Parkinson's Progression Markers Initiative; n = 424; performed over 2.5 years and MyConnectome; n = 1; 81 measurements over 1.5 years). Our results suggest that phase transitions in the society, indexed by stock market, exhibit close relationships with human mood, health and the affective brain from an individual to population level.

The Hypothesis of Subliminal Cue Reactivity in Addiction Revisited: An fMRI Study.

INTRODUCTION: Exposure to conditioned cues is a common trigger of relapse in addiction. It has been suggested that such cues can activate motivationally relevant neurocircuitry in individuals with substance use disorders even without being consciously perceived. We aimed to see if this could be replicated in a sample with severe amphetamine use disorder and a control group of healthy subjects. METHODS: We used fMRI to test the hypothesis that individuals with amphetamine use disorder, but not healthy controls, exhibit a specific neural reactivity to subliminally presented pictures related to amphetamine use. Twenty-four amphetamine users and 25 healthy controls were recruited and left data of sufficient quality to be included in the final analysis. All subjects were exposed to drug-related and neutral pictures of short duration (13.3 ms), followed by a backward visual mask image. The contrast of interest was drug versus neutral subliminal pictures. RESULTS: There were no statistically significant differences in BOLD signal between the drug and neutral cues, neither in the limbic regions of primary interest nor in exploratory whole-brain analyses. The same results were found both in amphetamine users and controls. DISCUSSION/CONCLUSION: We found no evidence of neural reactivity to subliminally presented drug cues in this sample of subjects with severe amphetamine dependence. These results are discussed in relation to the earlier literature, and the evidence for subliminal drug cue reactivity in substance use disorders is questioned.

Intelligence, educational attainment, and brain structure in those at familial high-risk for schizophrenia or bipolar disorder.

First-degree relatives of patients diagnosed with schizophrenia (SZ-FDRs) show similar patterns of brain abnormalities and cognitive alterations to patients, albeit with smaller effect sizes. First-degree relatives of patients diagnosed with bipolar disorder (BD-FDRs) show divergent patterns; on average, intracranial volume is larger compared to controls, and findings on cognitive alterations in BD-FDRs are inconsistent. Here, we performed a meta-analysis of global and regional brain measures (cortical and subcortical), current IQ, and educational attainment in 5,795 individuals (1,103 SZ-FDRs, 867 BD-FDRs, 2,190 controls, 942 schizophrenia patients, 693 bipolar patients) from 36 schizophrenia and/or bipolar disorder family cohorts, with standardized methods. Compared to controls, SZ-FDRs showed a pattern of widespread thinner cortex, while BD-FDRs had widespread larger cortical surface area. IQ was lower in SZ-FDRs (d = -0.42, p = 3 × 10-5 ), with weak evidence of IQ reductions among BD-FDRs (d = -0.23, p = .045). Both relative groups had similar educational attainment compared to controls. When adjusting for IQ or educational attainment, the group-effects on brain measures changed, albeit modestly. Changes were in the expected direction, with less pronounced brain abnormalities in SZ-FDRs and more pronounced effects in BD-FDRs. To conclude, SZ-FDRs and BD-FDRs show a differential pattern of structural brain abnormalities. In contrast, both had lower IQ scores and similar school achievements compared to controls. Given that brain differences between SZ-FDRs and BD-FDRs remain after adjusting for IQ or educational attainment, we suggest that differential brain developmental processes underlying predisposition for schizophrenia or bipolar disorder are likely independent of general cognitive impairment.

Longitudinal Structural Brain Changes in Bipolar Disorder: A Multicenter Neuroimaging Study of 1232 Individuals by the ENIGMA Bipolar Disorder Working Group.

BACKGROUND: Bipolar disorder (BD) is associated with cortical and subcortical structural brain abnormalities. It is unclear whether such alterations progressively change over time, and how this is related to the number of mood episodes. To address this question, we analyzed a large and diverse international sample with longitudinal magnetic resonance imaging (MRI) and clinical data to examine structural brain changes over time in BD. METHODS: Longitudinal structural MRI and clinical data from the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) BD Working Group, including 307 patients with BD and 925 healthy control subjects, were collected from 14 sites worldwide. Male and female participants, aged 40 ± 17 years, underwent MRI at 2 time points. Cortical thickness, surface area, and subcortical volumes were estimated using FreeSurfer. Annualized change rates for each imaging phenotype were compared between patients with BD and healthy control subjects. Within patients, we related brain change rates to the number of mood episodes between time points and tested for effects of demographic and clinical variables. RESULTS: Compared with healthy control subjects, patients with BD showed faster enlargement of ventricular volumes and slower thinning of the fusiform and parahippocampal cortex (0.18

Diagnosis of bipolar disorders and body mass index predict clustering based on similarities in cortical thickness-ENIGMA study in 2436 individuals.

AIMS: Rates of obesity have reached epidemic proportions, especially among people with psychiatric disorders. While the effects of obesity on the brain are of major interest in medicine, they remain markedly under-researched in psychiatry. METHODS: We obtained body mass index (BMI) and magnetic resonance imaging-derived regional cortical thickness, surface area from 836 bipolar disorders (BD) and 1600 control individuals from 14 sites within the ENIGMA-BD Working Group. We identified regionally specific profiles of cortical thickness using K-means clustering and studied clinical characteristics associated with individual cortical profiles. RESULTS: We detected two clusters based on similarities among participants in cortical thickness. The lower thickness cluster (46.8% of the sample) showed thinner cortex, especially in the frontal and temporal lobes and was associated with diagnosis of BD, higher BMI, and older age. BD individuals in the low thickness cluster were more likely to have the diagnosis of bipolar disorder I and less likely to be treated with lithium. In contrast, clustering based on similarities in the cortical surface area was unrelated to BD or BMI and only tracked age and sex. CONCLUSIONS: We provide evidence that both BD and obesity are associated with similar alterations in cortical thickness, but not surface area. The fact that obesity increased the chance of having low cortical thickness could explain differences in cortical measures among people with BD. The thinner cortex in individuals with higher BMI, which was additive and similar to the BD-associated alterations, may suggest that treating obesity could lower the extent of cortical thinning in BD.

On the Annotation of Health Care Pathways to Allow the Application of Care-Plans That Generate Data for Multiple Purposes.

Objectives: Procedural interoperability in health care requires information support and monitoring of a common work practice. Our aim was to devise an information model for a complete annotation of actions in clinical pathways that allow use of multiple plans concomitantly as several partial processes underlie any composite clinical process. Materials and Methods: The development of the information model was based on the integration of a defined protocol for clinical interoperability in the care of patients with chronic obstructive pulmonary disease and an observational study protocol for cohort characterization at the group level. In the clinical process patient reported outcome measures were included. Results: The clinical protocol and the observation study protocol were developed on the clinical level and a single plan definition was developed by merging of the protocols. The information model and a common data model that had been developed for care pathways was successfully implemented and data for the medical records and the observational study could be extracted independently. The interprofessional process support improved the communication between the stakeholders (health care professionals, clinical scientists and providers). Discussion: We successfully merged the processes and had a functionally successful pilot demonstrating a seamless appearance for the health care professionals, while at the same time it was possible to generate data that could serve quality registries and clinical research. The adopted data model was initially tested and hereby published to the public domain. Conclusion: The use of a patient centered information model and data annotation focused on the care pathway simplifies the annotation of data for different purposes and supports sharing of knowledge along the patient care path.

Genetic risk for bipolar disorder and schizophrenia predicts structure and function of the ventromedial prefrontal cortex.

BACKGROUND: Bipolar disorder is highly heritable and polygenic. The polygenic risk for bipolar disorder overlaps with that of schizophrenia, and polygenic scores are normally distributed in the population. Bipolar disorder has been associated with structural brain abnormalities, but it is unknown how these are linked to genetic risk factors for psychotic disorders. METHODS: We tested whether polygenic risk scores for bipolar disorder and schizophrenia predict structural brain alterations in 98 patients with bipolar disorder and 81 healthy controls. We derived brain cortical thickness, surface area and volume from structural MRI scans. In post-hoc analyses, we correlated polygenic risk with functional hub strength, derived from resting-state functional MRI and brain connectomics. RESULTS: Higher polygenic risk scores for both bipolar disorder and schizophrenia were associated with a thinner ventromedial prefrontal cortex (vmPFC). We found these associations in the combined group, and separately in patients and drug-naive controls. Polygenic risk for bipolar disorder was correlated with the functional hub strength of the vmPFC within the default mode network. LIMITATIONS: Polygenic risk is a cumulative measure of genomic burden. Detailed genetic mechanisms underlying brain alterations and their cognitive consequences still need to be determined. CONCLUSION: Our multimodal neuroimaging study linked genomic burden and brain endophenotype by demonstrating an association between polygenic risk scores for bipolar disorder and schizophrenia and the structure and function of the vmPFC. Our findings suggest that genetic factors might confer risk for psychotic disorders by influencing the integrity of the vmPFC, a brain region involved in self-referential processes and emotional regulation. Our study may also provide an imaging-genetics vulnerability marker that can be used to help identify individuals at risk for developing bipolar disorder.