Precuneus functioning differentiates first-episode psychosis patients during the fantasy movie Alice in Wonderland

Real-world goal-directed behavior reveals aberrant functional brain connectivity in children with ADHD

Functional connectomics is a popular approach to investigate the neural underpinnings of developmental disorders of which attention deficit hyperactivity disorder (ADHD) is one of the most prevalent. Nonetheless, neuronal mechanisms driving the aberrant functional connectivity resulting in ADHD symptoms remain largely unclear. Whereas resting state activity reflecting intrinsic tonic background activity is only vaguely connected to behavioral effects, naturalistic neuroscience has provided means to measure phasic brain dynamics associated with overt manifestation of the symptoms. Here we collected functional magnetic resonance imaging (fMRI) data in three experimental conditions, an active virtual reality (VR) task where the participants execute goal-directed behaviors, a passive naturalistic Video Viewing task, and a standard Resting State condition. Thirty-nine children with ADHD and thirty-seven typically developing (TD) children participated in this preregistered study. Functional connectivity was examined with network-based statistics (NBS) and graph theoretical metrics. During the naturalistic VR task, the ADHD group showed weaker task performance and stronger functional connectivity than the TD group. Group differences in functional connectivity were observed in widespread brain networks: particularly subcortical areas showed hyperconnectivity in ADHD. More restricted group differences in functional connectivity were observed during the Video Viewing, and there were no group differences in functional connectivity in the Resting State condition. These observations were consistent across NBS and graph theoretical analyses, although NBS revealed more pronounced group differences. Furthermore, during the VR task and Video Viewing, functional connectivity in TD controls was associated with task performance during the measurement, while Resting State activity in TD controls was correlated with ADHD symptoms rated over six months. We conclude that overt expression of the symptoms is correlated with aberrant brain connectivity in ADHD. Furthermore, naturalistic paradigms where clinical markers can be coupled with simultaneously occurring brain activity may further increase the interpretability of psychiatric neuroimaging findings.

Suicidal Behaviour Prior to First Episode Psychosis: Wider and More Widespread Grey-Matter Alterations

INTRODUCTION

The prodromal phase preceding the onset of First Episode Psychosis (FEP) is associated with an increased risk of Suicidal Behaviors (SBs). The aim of this study was to identify specific structural brain abnormalities linked to SBs that occur prior to the onset of FEP.

METHODS

Voxel-based morphometry analyses were used to investigate differences in brain Grey Matter (GM) volume using the CAT12 toolbox within SPM12. Covariates, including gender, age, handedness, intracranial volume, depression severity, and global cognitive functioning, were controlled for as confounding factors.

RESULTS

Significant reductions in GM were observed in the left superior temporal gyrus, dorsal posterior cingulate cortex, precuneus, cuneus, anterior cerebellum (p-FWE corrected < 0.05, k > 50) as well as in the right amygdala (0.96 ± 0.06 vs. 1.01 ± 0.05; F = 4.78; p < 0.05) and left amygdala (0.97 ± 0.06 vs. 1.02 ± 0.05; F = 8.97; p = 0.01).

CONCLUSIONS

History of SB prior to the onset of the psychotic disorder was related to wider and more widespread brain GM alterations. The regions identified are involved in cognitive and emotional processes such as emotional regulation, social cognition, perseverative thinking, and pain tolerance. These findings suggest that structural brain abnormalities related to SB occurring before FEP onset may serve as early biomarkers for identifying individuals at increased risk of suicide.

Establishing group-level brain structural connectivity incorporating anatomical knowledge under latent space modeling

Brain structural connectivity, capturing the white matter fiber tracts among brain regions inferred by diffusion MRI (dMRI), provides a unique characterization of brain anatomical organization. One fundamental question to address with structural connectivity is how to properly summarize and perform statistical inference for a group-level connectivity architecture, for instance, under different sex groups, or disease cohorts. Existing analyses commonly summarize group-level brain connectivity by a simple entry-wise sample mean or median across individual brain connectivity matrices. However, such a heuristic approach fully ignores the associations among structural connections and the topological properties of brain networks. In this project, we propose a latent space-based generative network model to estimate group-level brain connectivity. Within our modeling framework, we incorporate the anatomical information of brain regions as the attributes of nodes to enhance the plausibility of our estimation and improve biological interpretation. We name our method the attributes-informed brain connectivity (ABC) model, which compared with existing group-level connectivity estimations, (1) offers an interpretable latent space representation of the group-level connectivity, (2) incorporates the anatomical knowledge of nodes and tests its co-varying relationship with connectivity and (3) quantifies the uncertainty and evaluates the likelihood of the estimated group-level effects against chance. We devise a novel Bayesian MCMC algorithm to estimate the model. We evaluate the performance of our model through extensive simulations. By applying the ABC model to study brain structural connectivity stratified by sex among Alzheimer's Disease (AD) subjects and healthy controls incorporating the anatomical attributes (volume, thickness and area) on nodes, our method shows superior predictive power on out-of-sample structural connectivity and identifies meaningful sex-specific network neuromarkers for AD.

Multimodal prediction of the need of clozapine in treatment resistant schizophrenia; a pilot study in first-episode psychosis

As many as one third of the patients diagnosed with schizophrenia do not respond to first-line antipsychotic medication. This group may benefit from the atypical antipsychotic medication clozapine, but initiation of treatment is often delayed, which may worsen prognosis. Predicting which patients do not respond to traditional antipsychotic medication at the onset of symptoms would provide fast-tracked treatment for this group of patients. We collected data from patient records of 38 first-episode psychosis patients, of whom seven did not respond to traditional antipsychotic medications. We used clinical data including medical records, voxel-based morphometry MRI data and inter-subject correlation fMRI data, obtained during movie viewing, to predict future treatment resistance. Using a neural network model, we correctly predicted future treatment resistance in six of the seven treatment resistance patients and 25 of 31 patients who did not require clozapine treatment. Prediction improved significantly when using imaging data in tandem with clinical data. The accuracy of the neural network model was significantly higher than the accuracy of a support vector machine algorithm. These results support the notion that treatment resistant schizophrenia could represent a separate entity of psychotic disorders, characterized by morphological and functional changes in the brain which could represent biomarkers detectable at early onset of symptoms.

Explainable fuzzy clustering framework reveals divergent default mode network connectivity dynamics in schizophrenia

Introduction

Dynamic functional network connectivity (dFNC) analysis of resting state functional magnetic resonance imaging data has yielded insights into many neurological and neuropsychiatric disorders. A common dFNC analysis approach uses hard clustering methods like k-means clustering to assign samples to states that summarize network dynamics. However, hard clustering methods obscure network dynamics by assuming (1) that all samples within a cluster are equally like their assigned centroids and (2) that samples closer to one another in the data space than to their centroids are well-represented by their centroids. In addition, it can be hard to compare subjects, as in some cases an individual may not manifest a state strongly enough to enter a hard cluster. Approaches that allow a dimensional approach to connectivity patterns (e.g., fuzzy clustering) can mitigate these issues. In this study, we present an explainable fuzzy clustering framework by combining fuzzy c-means clustering with several explainability metrics and novel summary features.

Methods

We apply our framework for schizophrenia (SZ) default mode network analysis. Namely, we extract dFNC from individuals with SZ and controls, identify 5 dFNC states, and characterize the dFNC features most crucial to those states with a new perturbation-based clustering explainability approach. We then extract several features typically used in hard clustering and further present a variety of unique features specially designed for use with fuzzy clustering to quantify state dynamics. We examine differences in those features between individuals with SZ and controls and further search for relationships between those features and SZ symptom severity.

Results

Importantly, we find that individuals with SZ spend more time in states of moderate anticorrelation between the anterior and posterior cingulate cortices and strong anticorrelation between the precuneus and anterior cingulate cortex. We further find that individuals with SZ tend to transition more rapidly than controls between low-magnitude and high-magnitude dFNC states.

Conclusion

We present a novel dFNC analysis framework and use it to identify effects of SZ upon network dynamics. Given the ease of implementing our framework and its enhanced insight into network dynamics, it has great potential for use in future dFNC studies.

Hippocampus-Centered Network Is Associated With Positive Symptom Alleviation in Patients With First-Episode Psychosis

BACKGROUND

Previous functional magnetic resonance imaging studies have reported widespread brain functional connectivity alterations in patients with psychosis. These studies have mostly used either resting-state or simple-task paradigms, thereby compromising experimental control or ecological validity, respectively. Additionally, in a conventional functional magnetic resonance imaging intrasubject functional connectivity analysis, it is difficult to identify which connections relate to extrinsic (stimulus-induced) and which connections relate to intrinsic (non-stimulus-related) neural processes.

METHODS

To mitigate these limitations, we used intersubject functional connectivity (ISFC) to analyze longitudinal functional magnetic resonance imaging data collected while 36 individuals with first-episode psychosis (FEP) and 29 age- and sex-matched population control participants watched scenes from the fantasy movie Alice in Wonderland at baseline and again at 1-year follow-up. Furthermore, to allow unconfounded comparison and to overcome possible circularity of ISFC, we introduced a novel approach wherein ISFC in both the FEP and population control groups was calculated with respect to an independent group of participants (not included in the analyses).

RESULTS

Using this independent-reference ISFC approach, we found an interaction effect wherein the independent-reference ISFC in individuals with FEP, but not in the control group participants, was significantly stronger at baseline than at follow-up in a network centered in the hippocampus and involving thalamic, striatal, and cortical regions, such as the orbitofrontal cortex. Alleviation of positive symptoms, particularly delusions, from baseline to follow-up was correlated with decreased network connectivity in patients with FEP.

CONCLUSIONS

These findings link deviation of naturalistic information processing in the hippocampus-centered network to positive symptoms.

Functional neuroimaging as a catalyst for integrated neuroscience

Functional magnetic resonance imaging (fMRI) enables non-invasive access to the awake, behaving human brain. By tracking whole-brain signals across a diverse range of cognitive and behavioural states or mapping differences associated with specific traits or clinical conditions, fMRI has advanced our understanding of brain function and its links to both normal and atypical behaviour. Despite this headway, progress in human cognitive neuroscience that uses fMRI has been relatively isolated from rapid advances in other subdomains of neuroscience, which themselves are also somewhat siloed from one another. In this Perspective, we argue that fMRI is well-placed to integrate the diverse subfields of systems, cognitive, computational and clinical neuroscience. We first summarize the strengths and weaknesses of fMRI as an imaging tool, then highlight examples of studies that have successfully used fMRI in each subdomain of neuroscience. We then provide a roadmap for the future advances that will be needed to realize this integrative vision. In this way, we hope to demonstrate how fMRI can help usher in a new era of interdisciplinary coherence in neuroscience.

Narrative simulation of social experiences in naturalistic context - A neurocinematic approach

Narratives may be regarded as simulations of everyday social situations. They are key to studying the human mind in socio-culturally determined contexts as they allow anchoring to the common ground of embodied and environmentally-engaged cognition. Here we review recent findings from naturalistic neuroscience on neural functions in conditions that mimic lifelike situations. We will focus particularly on neurocinematics, a research field that applies mediated narratives as stimuli for neuroimaging experiments. During the last two decades, this paradigm has contributed to an accumulation of insights about the neural underpinnings of behavior and sense-making in various narratively contextualized situations particularly pertaining to socio-emotional encounters. One of the key questions in neurocinematics is, how do intersubjectively synchronized brain activations relate to subjective experiences? Another question we address is how to bring natural contexts into experimental studies. Seeking to respond to both questions, we suggest neurocinematic studies to examine three manifestations of the same phenomenon side-by-side: subjective experiences of narrative situations, unfolding of narrative stimulus structure, and neural processes that co-constitute the experience. This approach facilitates identifying experientially meaningful activity patterns in the brain and points out what they may mean in relation to shared and communicable contents. Via rich-featured and temporally contextualized narrative stimuli, neurocinematics attempts to contribute to emerging holistic theories of neural dynamics and connectomics explaining typical and atypical interindividual variability.

The default network dominates neural responses to evolving movie stories

Neuroscientific studies exploring real-world dynamic perception often overlook the influence of continuous changes in narrative content. In our research, we utilize machine learning tools for natural language processing to examine the relationship between movie narratives and neural responses. By analyzing over 50,000 brain images of participants watching Forrest Gump from the studyforrest dataset, we find distinct brain states that capture unique semantic aspects of the unfolding story. The default network, associated with semantic information integration, is the most engaged during movie watching. Furthermore, we identify two mechanisms that underlie how the default network liaises with the amygdala and hippocampus. Our findings demonstrate effective approaches to understanding neural processes in everyday situations and their relation to conscious awareness.

Naturalistic viewing increases individual identifiability based on connectivity within functional brain networks

Naturalistic viewing (NV) is currently considered a promising paradigm for studying individual differences in functional brain organization. While whole brain functional connectivity (FC) under NV has been relatively well characterized, so far little work has been done on a network level. Here, we extend current knowledge by characterizing the influence of NV on FC in fourteen meta-analytically derived brain networks considering three different movie stimuli in comparison to resting-state (RS). We show that NV increases identifiability of individuals over RS based on functional connectivity in certain, but not all networks. Furthermore, movie stimuli including a narrative appear more distinct from RS. In addition, we assess individual variability in network FC by comparing within- and between-subject similarity during NV and RS. We show that NV can evoke individually distinct NFC patterns by increasing inter-subject variability while retaining within-subject similarity. Crucially, our results highlight that this effect is not observable across all networks, but rather dependent on the network-stimulus combination. Our results confirm that NV can improve the detection of individual differences over RS and underline the importance of selecting the appropriate combination of movie and cognitive network for the research question at hand.

Aberrant functional connectivity of the bed nucleus of the stria terminalis and its age dependence in children and adolescents with social anxiety disorder

BACKGROUND

Social anxiety disorder (SAD) is a prevalent and impairing mental disorder among children and adolescents. The bed nucleus of the stria terminalis (BNST) plays a critical role in anxiety disorders, including valence surveillance and hypervigilance for potential threats. However, the role of BNST and its related functional network in children and adolescents with SAD has not been fully investigated. This study examined the aberration of BNST's functional connectivity and its age dependence in adolescents with SAD.

METHODS

Using a sample of 75 SAD patients and 75 healthy controls (HCs) children aged 9-18 years old, we delineated the group-by-age interaction of BNST-seeded functional connectivity (FC) during resting state and movie-watching. The relationships between BNST-seeded FC and clinical scores were also examined.

RESULTS

During movie viewing, the FC between the right BNST and the left amygdala, bilateral posterior cingulate cortex (PCC), bilateral superior temporal cortex, and right pericalcarine cortex showed a diagnostic group-by-age interaction. Compared to HCs, SAD patients showed a significant enhancement of the above FC at younger ages. Meanwhile, they showed an age-dependent decrease in FC between the right BNST and left amygdala. Furthermore, for SAD patients, FC between the right BNST and left amygdala during movie viewing was positively correlated with separation anxiety scores.

CONCLUSIONS

The right BNST plays an essential role in the aberrant brain functioning in children and adolescents with SAD. The atypicality of BNST's FC has remarkable age dependence in SAD, suggesting an association of SAD with neurodevelopmental traits.

Connectivity alterations of mesostriatal pathways in first episode psychosis

BACKGROUND AND HYPOTHESIS

Pathogenic understanding of the psychotic disorders converges on regulation of dopaminergic signaling in mesostriatocortical pathways. Functional connectivity of the mesostriatal pathways may inform us of the neuronal networks involved.

STUDY DESIGN

This longitudinal study of first episode psychosis (FEP) (49 patients, 43 controls) employed seed-based functional connectivity analyses of fMRI data collected during a naturalistic movie stimulus.

STUDY RESULTS

We identified hypoconnectivity of the dorsal striatum with the midbrain, associated with antipsychotic medication dose in FEP, in comparison with the healthy control group. The midbrain regions that showed hypoconnectivity with the dorsal striatum also showed hypoconnectivity with cerebellar regions suggested to be involved in regulation of the mesostriatocortical dopaminergic pathways. None of the baseline hypoconnectivity detected was seen at follow-up.

CONCLUSIONS

These findings extend earlier resting state findings on mesostriatal connectivity in psychotic disorders and highlight the potential for cerebellar regulation of the mesostriatocortical pathways as a target of treatment trials.

Associations between acceptance of the implausible bias, theory of mind and delusions in first-episode psychosis patients; A longitudinal study

Multiple different cognitive biases, among them the liberal acceptance (LA) bias, have been suggested to contribute to reality distortion in psychotic disorders. Earlier studies have been cross-sectional and considered a limited set of cognitive correlates of psychosis, thus the relationship between LA bias and psychosis remains poorly known. We studied a similar bias (acceptance of the implausible (AOI)) in 62 first-episode psychosis (FEP) patients and 62 control subjects, who watched movie scenes with varying degrees of realism and were asked to evaluate the probability of these events occurring in real life. We assessed theory of mind (ToM) performance using the Hinting task and delusion severity using Brief Psychiatric Rating Scale item 11. We correlated the magnitude of AOI with the severity of delusions and performance in the ToM task. Furthermore, we used 1-year follow-up data from 40 FEP patients and 40 control subjects to disentangle state vs trait-like characteristics of AOI. At baseline FEP patients expressed more AOI than control subjects, and the magnitude of AOI correlated positively with the severity of delusions and negatively with ToM performance. At the one-year follow-up, when most patients were in remission, patients still displayed increased AOI, which no longer correlated with delusions. These findings support the notion that the AOI bias could represent a trait rather than a state feature and support further studies to test the hypothesis that it could be one of the causal factors of psychotic disorders, possibly associated with ToM.

Temporal and electroencephalography dynamics of surreal marketing

Event-related spectral perturbation analysis was employed in this study to explore whether surreal image designs containing metaphors could influence product marketing effects, including consumers' product curiosity, product comprehension, product preference, and purchase intention. A total of 30 healthy participants aged 21-30 years were recruited. Neurophysiological findings revealed that lower gamma, beta, and theta spectral powers were evoked in the right insula (Brodmann Area 13) by surreal marketing images. This was associated, behaviorally, with the manifestation of higher product curiosity and purchase intention. Based on previous research, the brain functions of this area include novelty, puzzle-solving, and cravings for reward caused by cognitive overload.

State-like changes in the salience network correlate with delusion severity in first-episode psychosis patients

BACKGROUND AND HYPOTHESIS

Delusions are characteristic of psychotic disorders; however, the brain correlates of delusions remain poorly known. Imaging studies on delusions typically compare images across individuals. Related confounding of inter-individual differences beyond delusions may be avoided by comparing delusional and non-delusional states within individuals.

STUDY DESIGN

We studied correlations of delusions using intra-subject correlation (intra-SC) and inter-subject correlation of functional magnetic resonance imaging (fMRI) signal time series, obtained during a movie stimulus at baseline and follow-up. We included 27 control subjects and 24 first-episode psychosis patients, who were free of delusions at follow-up, to calculate intra-SC between fMRI signals obtained during the two time points. In addition, we studied changes in functional connectivity at baseline and during the one-year follow-up using regions where delusion severity correlated with intra-SC as seeds.

RESULTS

The intra-SC correlated negatively with the baseline delusion severity in the bilateral anterior insula. In addition, we observed a subthreshold cluster in the anterior cingulate. These three regions constitute the cortical salience network (SN). Functional connectivity between the bilateral insula and the precuneus was weaker in the patients at baseline than in patients at follow-up or in control subjects at any time point.

CONCLUSIONS

The results suggest that intra-SC is a powerful tool to study brain correlates of symptoms and highlight the role of the SN and internetwork dysconnectivity between the SN and the default mode network in delusions.

Real-time neurofeedback to alter interpretations of a naturalistic narrative

We explored the potential of using real-time fMRI (rt-fMRI) neurofeedback training to bias interpretations of naturalistic narrative stimuli. Participants were randomly assigned to one of two possible conditions, each corresponding to a different interpretation of an ambiguous spoken story. While participants listened to the story in the scanner, neurofeedback was used to reward neural activity corresponding to the assigned interpretation. After scanning, final interpretations were assessed. While neurofeedback did not change story interpretations on average, participants with higher levels of decoding accuracy during the neurofeedback procedure were more likely to adopt the assigned interpretation; additional control conditions are needed to establish the role of individualized feedback in driving this result. While naturalistic stimuli introduce a unique set of challenges in providing effective and individualized neurofeedback, we believe that this technique holds promise for individualized cognitive therapy.

Functional network connectivity and topology during naturalistic stimulus is altered in first-episode psychosis

BACKGROUND

Psychotic disorders have been suggested to derive from dysfunctional integration of signaling between brain regions. Earlier studies have found several changes in functional network synchronization as well as altered network topology in patients with psychotic disorders. However, studies have used mainly resting-state that makes it more difficult to link functional alterations to any specific stimulus or experience. We set out to examine functional connectivity as well as graph (topological) measures and their association to symptoms in first-episode psychosis patients during movie viewing. Our goal was to understand whole-brain functional dynamics of complex naturalistic information processing in psychosis and changes in brain functional organization related to symptoms.

METHODS

71 first-episode psychosis patients and 57 control subjects watched scenes from the movie Alice in Wonderland during 3 T fMRI. We compared functional connectivity and graph measures indicating integration, segregation and centrality between groups, and examined the association between topology and symptom scores in the patient group.

RESULTS

We identified a subnetwork with predominantly decreased links of functional connectivity in first-episode psychosis patients. The subnetwork was mainly comprised of nodes of and links between the cingulo-opercular, sensorimotor and default-mode networks. In topological measures, we observed between-group differences in properties of centrality.

CONCLUSIONS

Functional brain networks are affected during naturalistic information processing already in the early stages of psychosis, concentrated in salience- and cognitive control-related hubs and subnetworks. Understanding these aberrant dynamics could add to better targeted cognitive and behavioral interventions in the early stages of psychotic disorders.

Brain structural correlates of schizotypal signs and subclinical schizophrenia nuclear symptoms in healthy individuals

BACKGROUND

Subclinical psychotic-like experiences (PLE), resembling key symptoms of psychotic disorders, are common throughout the general population and possibly associated with psychosis risk. There is evidence that such symptoms are also associated with structural brain changes.

METHODS

In 672 healthy individuals, we assessed PLE and associated distress with the symptom-checklist-90R (SCL-90R) scales 'schizotypal signs' (STS) and 'schizophrenia nuclear symptoms' (SNS) and analysed associations with voxel- and surfaced-based brain structural parameters derived from structural magnetic resonance imaging at 3 T with CAT12.

RESULTS

For SNS, we found a positive correlation with the volume in the left superior parietal lobule and the precuneus, and a negative correlation with the volume in the right inferior temporal gyrus [p < 0.05 cluster-level Family Wise Error (FWE-corrected]. For STS, we found a negative correlation with the volume of the left and right precentral gyrus (p < 0.05 cluster-level FWE-corrected). Surface-based analyses did not detect any significant clusters with the chosen statistical threshold of p < 0.05. However, in exploratory analyses (p < 0.001, uncorrected), we found a positive correlation of SNS with gyrification in the left insula and rostral middle frontal gyrus and of STS with the left precuneus and insula, as well as a negative correlation of STS with gyrification in the left temporal pole.

CONCLUSIONS

Our results show that brain structures in areas implicated in schizophrenia are also related to PLE and its associated distress in healthy individuals. This pattern supports a dimensional model of the neural correlates of symptoms of the psychotic spectrum.

Towards clinical applications of movie fMRI

As evidenced by the present special issue, movie fMRI is emerging as a powerful tool for exploring brain function and characterizing its variation across individuals. Here, we provide a brief perspective on the potential of movie fMRI for advancing the discovery of brain imaging-based markers of psychiatric illness. We discuss relevant gaps and opportunities in movie fMRI, and propose community-level models that might accelerate the pace of discovery of fMRI-based biomarkers in psychiatry.

Segregated precuneus network and default mode network in naturalistic imaging

A resting-state network centered at the precuneus has been recently proposed as a precuneus network (PCUN) or "parietal memory network". Due to its spatial adjacency and overlapping with the default mode network (DMN), it is still not consensus to consider PCUN and DMN separately. Whether considering PCUN and DMN as different networks is a critical question that influences our understanding of brain functions and impairments. Previous resting-state studies using multiple methodologies have demonstrated a robust separation of the two networks. However, since there is no gold standard in justifying the functional difference between the networks in resting-state, we still lack of biological evidence to directly support the separation of the two networks. This study compared the responses and functional couplings of PCUN and DMN when participants were watching a movie and examined how the continuity of the movie context modulated the response of the networks. We identified PCUN and DMN in resting-state fMRI of 48 healthy subjects. The networks' response to a context-rich video and its context-shuffled version was characterized using the variance of temporal fluctuations and functional connectivity metrics. The results showed that (1) scrambling the contextual information altered the fluctuation level of DMN and PCUN in reversed ways; (2) compared to DMN, the FC within PCUN showed significantly higher sensitivity to the contextual continuity; (3) PCUN exhibited a significantly stronger functional network connectivity with the primary visual regions than DMN. These findings provide evidence for the distinct functional roles of PCUN and DMN in processing context-rich information and call for separately considering the functions and impairments of these networks in resting-state studies.

Machine learning in mental health: a scoping review of methods and applications

BACKGROUND

This paper aims to synthesise the literature on machine learning (ML) and big data applications for mental health, highlighting current research and applications in practice.

METHODS

We employed a scoping review methodology to rapidly map the field of ML in mental health. Eight health and information technology research databases were searched for papers covering this domain. Articles were assessed by two reviewers, and data were extracted on the article's mental health application, ML technique, data type, and study results. Articles were then synthesised via narrative review.

RESULTS

Three hundred papers focusing on the application of ML to mental health were identified. Four main application domains emerged in the literature, including: (i) detection and diagnosis; (ii) prognosis, treatment and support; (iii) public health, and; (iv) research and clinical administration. The most common mental health conditions addressed included depression, schizophrenia, and Alzheimer's disease. ML techniques used included support vector machines, decision trees, neural networks, latent Dirichlet allocation, and clustering.

CONCLUSIONS

Overall, the application of ML to mental health has demonstrated a range of benefits across the areas of diagnosis, treatment and support, research, and clinical administration. With the majority of studies identified focusing on the detection and diagnosis of mental health conditions, it is evident that there is significant room for the application of ML to other areas of psychology and mental health. The challenges of using ML techniques are discussed, as well as opportunities to improve and advance the field.

Naturalistic Stimuli in Neuroscience: Critically Acclaimed

Cognitive neuroscience has traditionally focused on simple tasks, presented sparsely and using abstract stimuli. While this approach has yielded fundamental insights into functional specialisation in the brain, its ecological validity remains uncertain. Do these tasks capture how brains function 'in the wild', where stimuli are dynamic, multimodal, and crowded? Ecologically valid paradigms that approximate real life scenarios, using stimuli such as films, spoken narratives, music, and multiperson games emerged in response to these concerns over a decade ago. We critically appraise whether this approach has delivered on its promise to deliver new insights into brain function. We highlight the challenges, technological innovations, and clinical opportunities that are required should this field meet its full potential.

Aberrant Cortical Integration in First-Episode Psychosis During Natural Audiovisual Processing

BACKGROUND

Functional magnetic resonance imaging studies of psychotic disorders have reported both hypoactivity and hyperactivity in numerous brain regions. In line with the dysconnection hypothesis, these regions include cortical integrative hub regions. However, most earlier studies focused on a single cognitive function at a time, assessed by delivering artificial stimuli to patients with chronic psychosis. Thus, it remains unresolved whether these findings are present already in early psychosis and whether they translate to real-life-like conditions that require multisensory processing and integration.

METHODS

Scenes from the movie Alice in Wonderland (2010) were shown to 51 patients with first-episode psychosis (16 women) and 32 community-based control subjects (17 women) during 3T functional magnetic resonance imaging. We compared intersubject correlation, a measure of similarity of brain signal time courses in each voxel, between the groups. We also quantified the hubness as the number of connections each region has.

RESULTS

Intersubject correlation was significantly lower in patients with first-episode psychosis than in control subjects in the medial and lateral prefrontal, cingulate, precuneal, and parietotemporal regions, including the default mode network. Regional magnitude of between-group difference in intersubject correlation was associated with the hubness.

CONCLUSIONS

Our findings provide novel evidence for the dysconnection hypothesis by showing that during complex real-life-like stimulation, the most prominent functional alterations in psychotic disorders relate to integrative brain functions. Presence of such abnormalities in first-episode psychosis rules out long-term effects of illness or medication. These methods can be used in further studies to map widespread hub alterations in a single functional magnetic resonance imaging session and link them to potential downstream and upstream pathways.

Connectivity of the precuneus-posterior cingulate cortex with the anterior cingulate cortex-medial prefrontal cortex differs consistently between control subjects and first-episode psychosis patients during a movie stimulus

BACKGROUND

Functional connectivity is altered in psychotic disorders. Multiple findings concentrate on the default mode network, anchored on the precuneus-posterior cingulate cortex (PC-PCC). However, the nature of the alterations varies between studies and connectivity alterations have not been studied during an ecologically valid natural stimulus. In the present study, we investigated the functional and structural connectivity of a PC-PCC region, where functioning differentiated first-episode psychosis patients from control subjects during free viewing of a movie in our earlier study.

METHODS

14 first-episode psychosis patients and 12 control subjects were imaged with GE 3T, and 29 patients and 19 control subjects were imaged with a Siemens Skyra 3T scanner while watching scenes from the movie Alice in Wonderland. Group differences in functional connectivity were analysed for both scanners separately and results were compared to identify any overlap. Diffusion tensor measures of 26 patients and 19 control subjects were compared for the related white matter tracts, identified by deterministic tractography.

RESULTS

Functional connectivity was increased in patients across scanners between the midline regions of the PC-PCC and the anterior cingulate cortex-medial prefrontal cortex (ACC-mPFC). We found no group differences in any of the diffusion tensor imaging measures.

CONCLUSIONS

Already in the early stages of psychosis functional connectivity between the midline structures of the PC-PCC and the ACC-mPFC is consistently increased during naturalistic stimulus.

Is It Possible to Predict the Future in First-Episode Psychosis?

The outcome of first-episode psychosis (FEP) is highly variable, ranging from early sustained recovery to antipsychotic treatment resistance from the onset of illness. For clinicians, a possibility to predict patient outcomes would be highly valuable for the selection of antipsychotic treatment and in tailoring psychosocial treatments and psychoeducation. This selective review summarizes current knowledge of prognostic markers in FEP. We sought potential outcome predictors from clinical and sociodemographic factors, cognition, brain imaging, genetics, and blood-based biomarkers, and we considered different outcomes, like remission, recovery, physical comorbidities, and suicide risk. Based on the review, it is currently possible to predict the future for FEP patients to some extent. Some clinical features-like the longer duration of untreated psychosis (DUP), poor premorbid adjustment, the insidious mode of onset, the greater severity of negative symptoms, comorbid substance use disorders (SUDs), a history of suicide attempts and suicidal ideation and having non-affective psychosis-are associated with a worse outcome. Of the social and demographic factors, male gender, social disadvantage, neighborhood deprivation, dysfunctional family environment, and ethnicity may be relevant. Treatment non-adherence is a substantial risk factor for relapse, but a small minority of patients with acute onset of FEP and early remission may benefit from antipsychotic discontinuation. Cognitive functioning is associated with functional outcomes. Brain imaging currently has limited utility as an outcome predictor, but this may change with methodological advancements. Polygenic risk scores (PRSs) might be useful as one component of a predictive tool, and pharmacogenetic testing is already available and valuable for patients who have problems in treatment response or with side effects. Most blood-based biomarkers need further validation. None of the currently available predictive markers has adequate sensitivity or specificity used alone. However, personalized treatment of FEP will need predictive tools. We discuss some methodologies, such as machine learning (ML), and tools that could lead to the improved prediction and clinical utility of different prognostic markers in FEP. Combination of different markers in ML models with a user friendly interface, or novel findings from e.g., molecular genetics or neuroimaging, may result in computer-assisted clinical applications in the near future.

Abnormal neural hierarchy in processing of verbal information in patients with schizophrenia

Previous research indicates abnormal comprehension of verbal information in patients with schizophrenia. Yet the neural mechanism underlying the breakdown of verbal information processing in schizophrenia is poorly understood. Imaging studies in healthy populations have shown a network of brain areas involved in hierarchical processing of verbal information over time. Here, we identified critical aspects of this hierarchy, examining patients with schizophrenia. Using functional magnetic resonance imaging, we examined various levels of information comprehension elicited by naturally presented verbal stimuli; from a set of randomly shuffled words to an intact story. Specifically, patients with first episode schizophrenia (N = 15), their non-manifesting siblings (N = 14) and healthy controls (N = 15) listened to a narrated story and randomly scrambled versions of it. To quantify the degree of dissimilarity between the groups, we adopted an inter-subject correlation (inter-SC) approach, which estimates differences in synchronization of neural responses within and between groups. The temporal topography found in healthy and siblings groups were consistent with our previous findings - high synchronization in responses from early sensory toward high order perceptual and cognitive areas. In patients with schizophrenia, stimuli with short and intermediate temporal scales evoked a typical pattern of reliable responses, whereas story condition (long temporal scale) revealed robust and widespread disruption of the inter-SCs. In addition, the more similar the neural activity of patients with schizophrenia was to the average response in the healthy group, the less severe the positive symptoms of the patients. Our findings suggest that system-level neural indication of abnormal verbal information processing in schizophrenia reflects disease manifestations.

Childhood adversities and clinical symptomatology in first-episode psychosis

In addition to severe traumatic experiences, milder, more common childhood adversities reflecting psychosocial burden may also be common in people with psychotic disorders and have an effect on symptomatology and functioning. We explored eleven negative childhood experiences and their influence on clinical symptoms among young adults with first-episode psychosis (FEP, n = 75) and matched population controls (n = 51). Individuals with FEP reported more adversities than controls. Specifically serious conflicts within the family, bullying at school, maternal mental health problems, and one's own and parents' serious illness during childhood were experienced by the patients more often than by controls. In the FEP group, the severity of adversity was associated with increased anxiety, manic, and obsessive-compulsive symptoms, but not with the severity of positive psychotic symptoms. Adversity produced a more pronounced effect on symptoms in male patients than in female patients. To conclude, in line with earlier studies of more chronic psychosis, a majority of the participants with FEP reported exposure to childhood adversities, with the FEP group reporting more adversities than controls. High levels of mood and anxiety symptoms in patients with FEP may be related to cumulative exposure to childhood adversities. This should be taken into account in the treatment for FEP.