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Precision psychiatry is an emerging field that aims to provide individualized approaches to mental health care. An important strategy to achieve this precision is to reduce uncertainty about prognosis and treatment response. Multivariate analysis and machine learning are used to create outcome prediction models based on clinical data such as demographics, symptom assessments, genetic information, and brain imaging. While much emphasis has been placed on technical innovation, the complex and varied nature of mental health presents significant challenges to the successful implementation of these models. From this perspective, I review ten challenges in the field of precision psychiatry, including the need for studies on real-world populations and realistic clinical outcome definitions, and consideration of treatment-related factors such as placebo effects and non-adherence to prescriptions. Fairness, prospective validation in comparison to current practice and implementation studies of prediction models are other key issues that are currently understudied. A shift is proposed from retrospective studies based on linear and static concepts of disease towards prospective research that considers the importance of contextual factors and the dynamic and complex nature of mental health.

Abstract Background Language and speech disturbances, or formal thought disorder (FTD), are a core symptom of schizophrenia. Historically this symptom group was introduced as disturbances in thought, however, contemporary research redefined these symptoms as severe language and speech disturbances, since these disturbances can only be observed as the expression of thought through language. A previous meta-analysis on the neural correlates of FTD in schizophrenia revealed that FTD in schizophrenia may be associated with both structural and functional aberrations in the language network. However, there is no research investigating the direct relationship between distortions in language and speech disturbances and aberrations in the language pathways in patients with schizophrenia and healthy controls. This study addresses this question by specifically looking at neural correlates of language and speech disturbances, rather than at FTD. Based on previous literature on this relation in FTD a negative relationship is expected between fractional anisotropy (FA) values of the language tracts and the language and speech measures in patients. A reverse, positive relationship is expected for mean diffusivity (MD) values and language and speech measures. Methods A total of 25 patients with a schizophrenia spectrum disorder and 25 healthy controls were included at the UMC Utrecht hospital. Participants were included if they were age eighteen or above and a native speaker of Dutch. Spontaneous speech was collected by means of a semi-structured interview. Interviews were recorded, transcribed and analyzed for measures of both the form and the meaning of the language that was produced. Diffuse Tensor Imaging (DTI) scans were obtained for all participants. Tract-based spatial statistics (TBSS) was used to extract FA and MD values of the main tracts (ROIs) important for language processing white matter tracts. Results Overall, the schizophrenia spectrum patients spoke slower and produced fewer words than the healthy controls. TBSS analyses showed significant differences between patients and healthy controls, revealing lower FA and higher MD in the patient group as compared to healthy controls. The integrity of the language tracts bilaterally was predictive of language and speech measures in patients, but less so in healthy controls. Discussion Our results indicate that white matter integrity of language tracts is predictive of language and speech disturbances in patients with a schizophrenia spectrum disorder, but not in healthy controls. This study adds to the understanding of FTD as a disturbance of language and speech, by proving a direct relationship between language and speech disturbances in schizophrenia and structural aberrations in the language network.

Hallucinations may arise from an imbalance between sensory and higher cognitive brain regions, reflected by alterations in functional connectivity. It is unknown whether hallucinations across the psychosis continuum exhibit similar alterations in functional connectivity, suggesting a common neural mechanism, or whether different mechanisms link to hallucinations across phenotypes. We acquired resting-state functional MRI scans of 483 participants, including 40 non-clinical individuals with hallucinations, 99 schizophrenia patients with hallucinations, 74 bipolar-I disorder patients with hallucinations, 42 bipolar-I disorder patients without hallucinations, and 228 healthy controls. The weighted connectivity matrices were compared using network-based statistics. Non-clinical individuals with hallucinations and schizophrenia patients with hallucinations exhibited increased connectivity, mainly among fronto-temporal and fronto-insula/cingulate areas compared to controls ( P  < 0.001 adjusted). Differential effects were observed for bipolar-I disorder patients with hallucinations versus controls, mainly characterized by decreased connectivity between fronto-temporal and fronto-striatal areas ( P  = 0.012 adjusted). No connectivity alterations were found between bipolar-I disorder patients without hallucinations and controls. Our results support the notion that hallucinations in non-clinical individuals and schizophrenia patients are related to altered interactions between sensory and higher-order cognitive brain regions. However, a different dysconnectivity pattern was observed for bipolar-I disorder patients with hallucinations, which implies a different neural mechanism across the psychosis continuum.

Background Both epilepsy patients and brain tumor patients show altered functional connectivity and less optimal brain network topology when compared to healthy controls, particularly in the theta band. Furthermore, the duration and characteristics of epilepsy may also influence functional interactions in brain networks. However, the specific features of connectivity and networks in tumor-related epilepsy have not been investigated yet. We hypothesize that epilepsy characteristics are related to (theta band) connectivity and network architecture in operated glioma patients suffering from epileptic seizures. Included patients participated in a clinical study investigating the effect of levetiracetam monotherapy on seizure frequency in glioma patients, and were assessed at two time points: directly after neurosurgery (t1), and six months later (t2). At these time points, magnetoencephalography (MEG) was recorded and information regarding clinical status and epilepsy history was collected. Functional connectivity was calculated in six frequency bands, as were a number of network measures such as normalized clustering coefficient and path length. Results At the two time points, MEG registrations were performed in respectively 17 and 12 patients. No changes in connectivity or network topology occurred over time. Increased theta band connectivity at t1 and t2 was related to a higher total number of seizures. Furthermore, higher number of seizures was related to a less optimal, more random brain network topology. Other factors were not significantly related to functional connectivity or network topology. Conclusions These results indicate that (pathologically) increased theta band connectivity is related to a higher number of epileptic seizures in brain tumor patients, suggesting that theta band connectivity changes are a hallmark of tumor-related epilepsy. Furthermore, a more random brain network topology is related to greater vulnerability to seizures. Thus, functional connectivity and brain network architecture may prove to be important parameters of tumor-related epilepsy.

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SignificanceA description of the structural and functional connections in the human brain is necessary for the understanding of both normal and abnormal brain functioning. Although it has become clear in recent years that stable patterns of functional connectivity can be observed during the resting state, to date, it remains unclear what the dominant patterns of information flow are in this functional connectome and how these relate to the integration of brain function. Our results are the first to describe the large-scale frequency-specific patterns of information flow in the human brain, showing that different subsystems form a loop through which information “reverberates” or “circulates.” These results could be extended to give insights into how such flow optimizes integrative cognitive processing. Normal brain function requires interactions between spatially separated, and functionally specialized, macroscopic regions, yet the directionality of these interactions in large-scale functional networks is unknown. Magnetoencephalography was used to determine the directionality of these interactions, where directionality was inferred from time series of beamformer-reconstructed estimates of neuronal activation, using a recently proposed measure of phase transfer entropy. We observed well-organized posterior-to-anterior patterns of information flow in the higher-frequency bands (alpha1, alpha2, and beta band), dominated by regions in the visual cortex and posterior default mode network. Opposite patterns of anterior-to-posterior flow were found in the theta band, involving mainly regions in the frontal lobe that were sending information to a more distributed network. Many strong information senders in the theta band were also frequent receivers in the alpha2 band, and vice versa. Our results provide evidence that large-scale resting-state patterns of information flow in the human brain form frequency-dependent reentry loops that are dominated by flow from parieto-occipital cortex to integrative frontal areas in the higher-frequency bands, which is mirrored by a theta band anterior-to-posterior flow.

This study aims to identify novel quantitative EEG measures associated with mindfulness meditation. As there is some evidence that meditation is associated with higher integration of brain networks, we focused on EEG measures of network integration. Sixteen novice meditators and sixteen experienced meditators participated in the study. Novice meditators performed a basic meditation practice that supported effortless awareness, which is an important quality of experience related to mindfulness practices, while their EEG was recorded. Experienced meditators performed a self-selected meditation practice that supported effortless awareness. Network integration was analyzed with maximum betweenness centrality and leaf fraction (which both correlate positively with network integration) as well as with diameter and average eccentricity (which both correlate negatively with network integration), based on a phase-lag index (PLI) and minimum spanning tree (MST) approach. Differences between groups were assessed using repeated-measures ANOVA for the theta (4–8 Hz), alpha (8–13 Hz) and lower beta (13–20 Hz) frequency bands. Maximum betweenness centrality was significantly higher in experienced meditators than in novices (P = 0.012) in the alpha band. In the same frequency band, leaf fraction showed a trend toward being significantly higher in experienced meditators than in novices (P = 0.056), while diameter and average eccentricity were significantly lower in experienced meditators than in novices (P = 0.016 and P = 0.028 respectively). No significant differences between groups were observed for the theta and beta frequency bands. These results show that alpha band functional network topology is better integrated in experienced meditators than in novice meditators during meditation. This novel finding provides the rationale to investigate the temporal relation between measures of functional connectivity network integration and meditation quality, for example using neurophenomenology experiments.

Childhood trauma increases risk for psychopathology and cognitive impairment. Prior research mainly focused on the hippocampus and amygdala in single diagnostic categories. However, other brain regions may be impacted by trauma as well, and effects may be independent of diagnosis. This cross-sectional study investigated cortical and subcortical gray matter volume in relation to childhood trauma severity. We included 554 participants: 250 bipolar-I patients, 84 schizophrenia-spectrum patients and 220 healthy individuals without a psychiatric history. Participants filled in the Childhood Trauma Questionnaire. Anatomical T1 MRI scans were acquired at 3T, regional brain morphology was assessed using Freesurfer. In the total sample, trauma-related gray matter reductions were found in the frontal lobe ( = -0.049, = 0.008; = 0.048), this effect was driven by the right medial orbitofrontal, paracentral, superior frontal regions and the left precentral region. No trauma-related volume reductions were observed in any other (sub)cortical lobes nor the hippocampus or amygdala, trauma-by-group (i.e. both patient groups and healthy subjects) interaction effects were absent. A categorical approach confirmed a pattern of more pronounced frontal gray matter reductions in individuals reporting multiple forms of trauma and across quartiles of cumulative trauma scores. Similar dose-response patterns were revealed within the bipolar and healthy subgroups, but did not reach significance in schizophrenia-spectrum patients. Findings show that childhood trauma is linked to frontal gray matter reductions, independent of psychiatric morbidity. Our results indicate that childhood trauma importantly contributes to the neurobiological changes commonly observed across psychiatric disorders. Frontal volume alterations may underpin affective and cognitive disturbances observed in trauma-exposed individuals.

Abstract Psychotic experiences are prevalent across a wide variety of psychiatric, neurological, and medical conditions. Yet current assessments are often designed for one disorder, or are limited in their examination of phenomenological features; this has hindered transdiagnostic research. This article describes an examination of the validity and reliability of the English version of a new assessment, the Questionnaire for Psychotic Experiences (QPE). This study aimed to use the QPE to examine hallucinations and delusions across a number of different conditions, and to ensure that the QPE had acceptable psychometric properties. An International Consortium on Hallucination Research working group, along with consumer groups, developed the 50-item QPE to assess the presence, severity, and phenomenology of hallucinations and delusions. Participants in the study who reported psychotic experiences included those with schizophrenia, schizoaffective disorder, bipolar affective disorder, and major depressive disorder, and those without a need for care (ie, nonclinical participants). There were 173 participants in total. Convergent and discriminant validity were assessed. Reliability was examined in terms of stability, equivalence, and internal consistency. The data confirmed that the QPE had good psychometric properties and could be put forward as an accepted measure of the transdiagnostic evaluation of psychotic experiences. Further validation is recommended with neurological and medical populations. Given its validity and reliability, comprehensive evaluation of psychotic phenomena, and relatively quick administration time, we propose that the QPE is a valuable instrument for both clinical and research settings.

Individuals with psychotic disorders often lead sedentary lives, heightening the risk of developing forward head posture. Forward head posture affects upper cervical vertebrae, raising the likelihood of daily discomforts like skeletal misalignment, neck pain, and reduced cardiorespiratory fitness. Improving cardiorespiratory fitness in psychotic disorders is relevant, given its proven benefits in enhancing physical and mental health. This study investigates forward head posture by measuring craniovertebral angles in psychotic disorders and the relationship with reduced cardiorespiratory fitness. To determine whether forward head posture is specific to psychotic disorders, we also included individuals with autism spectrum disorder and healthy controls. Among 85 participants (32 psychotic disorders, 26 autism spectrum disorder, 27 healthy controls), photogrammetric quantification revealed a significantly lower mean craniocervical angle in psychotic disorders compared to autism spectrum disorder ( p  =  < 0.02) and the healthy control group ( p  =  < 0.01). Reduced craniovertebral angle is related to diminished cardiorespiratory fitness in psychosis (R 2  = 0.45, p  =  < 0.01) but not in other control groups. This study found reduced craniovertebral angles, indicating forward head posture in psychotic disorders. Moreover, this relates to diminished cardiorespiratory fitness. Further research is needed to examine the underlying causes and to investigate whether this can be reversed through physical therapy.