Examining the relationships between cognition and auditory hallucinations: A systematic review.

OBJECTIVE: Auditory hallucinations (hearing voices) have been associated with a range of altered cognitive functions, pertaining to signal detection, source-monitoring, memory, inhibition and language processes. Yet, empirical results are inconsistent. Despite this, several theoretical models of auditory hallucinations persist, alongside increasing emphasis on the utility of a multidimensional framework. Thus, clarification of current evidence across the broad scope of proposed mechanisms is warranted. METHOD: A systematic search of the Web of Science, PubMed and Scopus databases was conducted. Records were screened to confirm the use of an objective behavioural cognitive task, and valid measurement of hallucinations specific to the auditory modality. RESULTS: Auditory hallucinations were primarily associated with difficulties in perceptual decision-making (i.e. reduced sensitivity/accuracy for signal-noise discrimination; liberal responding to ambiguity), source-monitoring (i.e. self-other and temporal context confusion), working memory and language function (i.e. reduced verbal fluency). Mixed or limited support was observed for perceptual feature discrimination, imagery vividness/illusion susceptibility, source-monitoring for stimulus form and spatial context, recognition and recall memory, executive functions (e.g. attention, inhibition), emotion processing and language comprehension/hemispheric organisation. CONCLUSIONS: Findings were considered within predictive coding and self-monitoring frameworks. Of concern was the portion of studies which - despite offering auditory-hallucination-specific aims and inferences - employed modality-general measures, and/or diagnostic-based contrasts with psychologically healthy individuals. This review highlights disparities within the literature between theoretical conceptualisations of auditory hallucinations and the body of rigorous empirical evidence supporting such inferences. Future cognitive investigations, beyond the schizophrenia-spectrum, which explicitly define and measure the timeframe and sensory modality of hallucinations, are recommended.

Functional connectivity and glutamate levels of the medial prefrontal cortex in schizotypy are related to sensory amplification in a probabilistic reasoning task.

The circular inference (CI) computational model assumes a corruption of sensory data by prior information and vice versa, leading at the extremes to 'see what we expect' (through prior amplification) and/or to 'expect what we see' (through sensory amplification). Although a CI mechanism has been reported in a schizophrenia population, it has not been investigated in individuals experiencing psychosis-like experiences, such as people with high schizotypy traits. Furthermore, the neurobiological basis of CI, such as the link between hierarchical amplifications, excitatory neurotransmission, and resting state functional connectivity (RSFC), remains untested. The participants included in the present study consisted of a subsample of those recruited in a study previously published by our group, Kozhuharova et al. (2021b). We included 36 participants with High (n=18) and Low (n=18) levels of schizotypy who completed a probabilistic reasoning task (the Fisher task) for which individual confidence levels were obtained and fitted to the CI model. Participants also underwent a 1H-Magnetic Resonance Spectroscopy (MRS) scan to measure medial prefrontal cortex (mPFC) glutamate metabolite levels, and a functional Magnetic Resonance Imaging (fMRI) scan to measure RSFC of the medial prefrontal cortex (mPFC). People with high levels of schizotypy exhibited changes in CI parameters, altered cortical excitatory neurotransmission and RSFC that were all associated with sensory amplification. Our findings capture a multimodal signature of CI that is observable in people early in the psychosis spectrum.

The neural signature of reality-monitoring: A meta-analysis of functional neuroimaging studies.

Distinguishing imagination and thoughts from information we perceived from the environment, a process called reality-monitoring, is important in everyday situations. Although reality monitoring seems to overlap with the concept of self-monitoring, which allows one to distinguish self-generated actions or thoughts from those generated by others, the two concepts remain largely separate cognitive domains and their common brain substrates have received little attention. We investigated the brain regions involved in these two cognitive processes and explored the common brain regions they share. To do this, we conducted two separate coordinate-based meta-analyses of functional magnetic resonance imaging studies assessing the brain regions involved in reality- and self-monitoring. Few brain regions survived threshold-free cluster enhancement family-wise multiple comparison correction (p < .05), likely owing to the small number of studies identified. Using uncorrected statistical thresholds recommended by Signed Differential Mapping with Permutation of Subject Images, the meta-analysis of reality-monitoring studies (k = 9 studies including 172 healthy subjects) revealed clusters in the lobule VI of the cerebellum, the right anterior medial prefrontal cortex and anterior thalamic projections. The meta-analysis of self-monitoring studies (k = 12 studies including 192 healthy subjects) highlighted the involvement of a set of brain regions including the lobule VI of the left cerebellum and fronto-temporo-parietal regions. We showed with a conjunction analysis that the lobule VI of the cerebellum was consistently engaged in both reality- and self-monitoring. The current findings offer new insights into the common brain regions underlying reality-monitoring and self-monitoring, and suggest that the neural signature of the self that may occur during self-production should persist in memories.

Admission to jail and psychotic symptoms: a study of the psychotic continuum in a sample of recently incarcerated men.

PURPOSE: We sought to measure the prevalence of psychotic symptoms (PSs) and psychotic disorders (PDs) in a sample of men entering jail and to compare these prevalences with those observed in the general population. We also aimed to explore the sociodemographic and clinical factors associated with PSs and PDs. METHODS: The Mental Health in the Prison Population (MHPP) survey interviewed 630 incarcerated men upon admission to jail, using the Mini International Neuropsychiatric Interview. We looked for associations between sociodemographic and clinical characteristics and the presence of lifetime PSs and PDs in the MHPP and Mental Health in the General Population (MHGP) surveys, which used the same methodology to collect data from the jail and general populations of the same geographical area. RESULTS: A higher proportion of PSs without PDs was found in the MHGP group (25.3% vs. 17.8%, p < 0.001), whereas a higher prevalence of PDs was found in the MHPP group (7.0% vs. 2.6%, p < 0.001). The multivariable model indicated that subjects who were single or separated/divorced/widowed and had a history of trauma exposure were at joint risk of PSs and PDs, whereas entering jail was not associated with either PSs or PDs after adjustment for all covariates. CONCLUSION: The present study shows that PDs, but not PSs, are more prevalent in men entering jail than in the general population. This overrepresentation could be further explained by the exposure to vulnerability factors found in this population rather than by any specificity related to entering jail.

No increased circular inference in adults with high levels of autistic traits or autism.

Autism spectrum disorders have been proposed to arise from impairments in the probabilistic integration of prior knowledge with sensory inputs. Circular inference is one such possible impairment, in which excitation-to-inhibition imbalances in the cerebral cortex cause the reverberation and amplification of prior beliefs and sensory information. Recent empirical work has associated circular inference with the clinical dimensions of schizophrenia. Inhibition impairments have also been observed in autism, suggesting that signal reverberation might be present in that condition as well. In this study, we collected data from 21 participants with self-reported diagnoses of autism spectrum disorders and 155 participants with a broad range of autistic traits in an online probabilistic decision-making task (the fisher task). We used previously established Bayesian models to investigate possible associations between autistic traits or autism and circular inference. There was no correlation between prior or likelihood reverberation and autistic traits across the whole sample. Similarly, no differences in any of the circular inference model parameters were found between autistic participants and those with no diagnosis. Furthermore, participants incorporated information from both priors and likelihoods in their decisions, with no relationship between their weights and psychiatric traits, contrary to what common theories for both autism and schizophrenia would suggest. These findings suggest that there is no increased signal reverberation in autism, despite the known presence of excitation-to-inhibition imbalances. They can be used to further contrast and refine the Bayesian theories of schizophrenia and autism, revealing a divergence in the computational mechanisms underlying the two conditions.

Place of the partial dopamine receptor agonist aripiprazole in the management of schizophrenia in adults: a Delphi consensus study.

BACKGROUND: Aripiprazole is a second-generation antipsychotic, efficacious in patients with schizophrenia during acute episodes. Due to its pharmacological profile, aripiprazole may be of interest in patients with specific clinical profiles who have not been studied extensively in randomised clinical trials. OBJECTIVES: To capture experience with aripiprazole in everyday psychiatric practice using the Delphi method in order to inform decision-making on the use of aripiprazole for the treatment of patients with schizophrenia in clinical situations where robust evidence from clinical trials is lacking. METHODS: The scope of the survey was defined as the management of schizophrenia in adults. A systematic literature review was performed to identify the different clinical situations in which aripiprazole has been studied, and to describe the level of clinical evidence. Clinical profiles to include in the Delphi survey were selected if there was a clear interest in terms of medical need but uncertainty over the efficacy of aripiprazole. For each clinical profile retained, five to seven specific statements were generated and included in a questionnaire. The final 41-item questionnaire was proposed to a panel of 406 French psychiatrists with experience in the treatment of schizophrenia. Panellists rated their level of agreement using a Likert scale. A second round of voting on eleven items was organised to clarify points for which a consensus was not obtained in the first round. RESULTS: Five clinical profiles were identified in the literature review (persistent negative symptoms, pregnancy, cognitive dysfunction, addictive comorbidity and clozapine resistance). Sixty-two psychiatrists participated in the first round of the Delphi survey and 33 in the second round. A consensus was obtained for 11 out of 41 items in the first round and for 9/11 items in the second round. According to the panellists' clinical experience, aripiprazole can be used as maintenance treatment for pregnant women, is relevant to preserve cognitive function and can be considered an option in patients with a comorbid addictive disorder or with persistent negative symptoms. CONCLUSION: These findings may help physicians in choosing relevant ways to use aripiprazole and highlight areas where more research is needed to widen the evidence base.

Functional parcellation of human and macaque striatum reveals human-specific connectivity in the dorsal caudate.

A wide homology between human and macaque striatum is often assumed as in both the striatum is involved in cognition, emotion and executive functions. However, differences in functional and structural organization between human and macaque striatum may reveal evolutionary divergence and shed light on human vulnerability to neuropsychiatric diseases. For instance, dopaminergic dysfunction of the human striatum is considered to be a pathophysiological underpinning of different disorders, such as Parkinson's disease (PD) and schizophrenia (SCZ). Previous investigations have found a wide similarity in structural connectivity of the striatum between human and macaque, leaving the cross-species comparison of its functional organization unknown. In this study, resting-state functional connectivity (RSFC) derived striatal parcels were compared based on their homologous cortico-striatal connectivity. The goal here was to identify striatal parcels whose connectivity is human-specific compared to macaque parcels. Functional parcellation revealed that the human striatum was split into dorsal, dorsomedial, and rostral caudate and ventral, central, and caudal putamen, while the macaque striatum was divided into dorsal, and rostral caudate and rostral, and caudal putamen. Cross-species comparison indicated dissimilar cortico-striatal RSFC of the topographically similar dorsal caudate. We probed clinical relevance of the striatal clusters by examining differences in their cortico-striatal RSFC and gray matter (GM) volume between patients (with PD and SCZ) and healthy controls. We found abnormal RSFC not only between dorsal caudate, but also between rostral caudate, ventral, central and caudal putamen and widespread cortical regions for both PD and SCZ patients. Also, we observed significant structural atrophy in rostral caudate, ventral and central putamen for both PD and SCZ while atrophy in the dorsal caudate was specific to PD. Taken together, our cross-species comparative results revealed shared and human-specific RSFC of different striatal clusters reinforcing the complex organization and function of the striatum. In addition, we provided a testable hypothesis that abnormalities in a region with human-specific connectivity, i.e., dorsal caudate, might be associated with neuropsychiatric disorders.

A functional theory of bistable perception based on dynamical circular inference.

When we face ambiguous images, the brain cannot commit to a single percept; instead, it switches between mutually exclusive interpretations every few seconds, a phenomenon known as bistable perception. While neuromechanistic models, e.g., adapting neural populations with lateral inhibition, may account for the dynamics of bistability, a larger question remains unresolved: how this phenomenon informs us on generic perceptual processes in less artificial contexts. Here, we propose that bistable perception is due to our prior beliefs being reverberated in the cortical hierarchy and corrupting the sensory evidence, a phenomenon known as "circular inference". Such circularity could occur in a hierarchical brain where sensory responses trigger activity in higher-level areas but are also modulated by feedback projections from these same areas. We show that in the face of ambiguous sensory stimuli, circular inference can change the dynamics of the perceptual system and turn what should be an integrator of inputs into a bistable attractor switching between two highly trusted interpretations. The model captures various aspects of bistability, including Levelt's laws and the stabilizing effects of intermittent presentation of the stimulus. Since it is related to the generic perceptual inference and belief updating mechanisms, this approach can be used to predict the tendency of individuals to form aberrant beliefs from their bistable perception behavior. Overall, we suggest that feedforward/feedback information loops in hierarchical neural networks, a phenomenon that could lead to psychotic symptoms when overly strong, could also underlie perception in nonclinical populations.

Association between childhood trauma and multimodal early-onset hallucinations.

Previous reports suggest that adverse events during childhood could be related to an array of psychiatric problems. Here, we question the relationship between childhood traumatic experiences and the sensory complexity of hallucinations in a cohort of 75 children and adolescents. We evidence a positive link between the number of sensory modalities involved in hallucinations and history of childhood trauma, even after controlling for the co-occurrence of suicidal ideation or the number of ICD-10 diagnoses. These findings support initiatives in which a routine exploration of traumatic events in childhood is performed when multimodal hallucinations are present.

Circular inference in bistable perception.

When facing ambiguous images, the brain switches between mutually exclusive interpretations, a phenomenon known as bistable perception. Despite years of research, a consensus on whether bistability is driven primarily by bottom-up or top-down mechanisms has not been achieved. Here, we adopted a Bayesian approach to reconcile these two theories. Fifty-five healthy participants were exposed to an adaptation of the Necker cube paradigm, in which we manipulated sensory evidence and prior knowledge. Manipulations of both sensory evidence and priors significantly affected the way participants perceived the Necker cube. However, we observed an interaction between the effect of the cue and the effect of the instructions, a finding that is incompatible with Bayes-optimal integration. In contrast, the data were well predicted by a circular inference model. In this model, ambiguous sensory evidence is systematically biased in the direction of current expectations, ultimately resulting in a bistable percept.

Brain-based ranking of cognitive domains to predict schizophrenia.

Schizophrenia is a devastating brain disorder that disturbs sensory perception, motor action, and abstract thought. Its clinical phenotype implies dysfunction of various mental domains, which has motivated a series of theories regarding the underlying pathophysiology. Aiming at a predictive benchmark of a catalog of cognitive functions, we developed a data-driven machine-learning strategy and provide a proof of principle in a multisite clinical dataset (n = 324). Existing neuroscientific knowledge on diverse cognitive domains was first condensed into neurotopographical maps. We then examined how the ensuing meta-analytic cognitive priors can distinguish patients and controls using brain morphology and intrinsic functional connectivity. Some affected cognitive domains supported well-studied directions of research on auditory evaluation and social cognition. However, rarely suspected cognitive domains also emerged as disease relevant, including self-oriented processing of bodily sensations in gustation and pain. Such algorithmic charting of the cognitive landscape can be used to make targeted recommendations for future mental health research.

Excess Significance Bias in Repetitive Transcranial Magnetic Stimulation Literature for Neuropsychiatric Disorders.

INTRODUCTION: Repetitive transcranial magnetic stimulation (rTMS) has been widely tested and promoted for use in multiple neuropsychiatric conditions, but as for many other medical devices, some gaps may exist in the literature and the evidence base for the clinical efficacy of rTMS remains under debate. OBJECTIVE: We aimed to test for an excess number of statistically significant results in the literature on the therapeutic efficacy of rTMS across a wide range of meta-analyses and to characterize the power of studies included in these meta-analyses. METHODS: Based on power calculations, we computed the expected number of "positive" datasets for a medium effect size (standardized mean difference, SMD = 0.30) and compared it with the number of observed "positive" datasets. Sensitivity analyses considered small (SMD = 0.20), modest (SMD = 0.50), and large (SMD = 0.80) effect sizes. RESULTS: A total of 14 meta-analyses with 228 datasets (110 for neurological disorders and 118 for psychiatric disorders) were assessed. For SMD = 0.3, the number of observed "positive" studies (n = 94) was larger than expected (n = 35). We found evidence for an excess of significant findings overall (p < 0.0001) and in 8/14 meta-analyses. Evidence for an excess of significant findings was also observed for SMD = 0.5 for neurological disorders. Of the 228 datasets, 0 (0%), 0 (0%), 3 (1%), and 53 (23%) had a power >0.80, respectively, for SMDs of 0.30, 0.20, 0.50, and 0.80. CONCLUSION: Most studies in the rTMS literature are underpowered. This results in fragmentation and waste of research efforts. The somewhat high frequency of "positive" results seems spurious and may reflect bias. Caution is warranted in accepting rTMS as an established treatment for neuropsychiatric conditions.

A look into hallucinations: the relationship between visual imagery and hallucinations in Alzheimer's disease.

Introduction: We investigated the relationship between visual hallucinations and vividness of visual imagery in patients with Alzheimer's disease (AD). Method: We recruited 28 patients with AD and 30 healthy control participants, matched for age and education. We evaluated proneness towards hallucinations with the Launay-Slade Hallucinations Scale, which includes items assessing visual and auditory hallucinations. We also evaluated vividness of visual imagery with the Vividness of Visual Imagery Questionnaire on which participants had to imagine four images (i.e., imagining the face of a friend, the rising sun, a familiar shop-front, and a country scene) and report the vividness of the images they generated. Results: Analysis demonstrated significant positive correlations between visual hallucinations and vividness of visual imagery in AD patients, however, no significant correlations were observed between auditory hallucinations and vividness of visual imagery in these participants. No significant correlations were observed between hallucinations and vividness of visual imagery in healthy control participants, probably due to the lack of hallucinations in these participants. Discussion: These results demonstrate a selective relationship between the occurrence of visual (but not auditory) hallucinations and the ability to generate vivid visual images in AD.

Prediction of activation patterns preceding hallucinations in patients with schizophrenia using machine learning with structured sparsity.

Despite significant progress in the field, the detection of fMRI signal changes during hallucinatory events remains difficult and time-consuming. This article first proposes a machine-learning algorithm to automatically identify resting-state fMRI periods that precede hallucinations versus periods that do not. When applied to whole-brain fMRI data, state-of-the-art classification methods, such as support vector machines (SVM), yield dense solutions that are difficult to interpret. We proposed to extend the existing sparse classification methods by taking the spatial structure of brain images into account with structured sparsity using the total variation penalty. Based on this approach, we obtained reliable classifying performances associated with interpretable predictive patterns, composed of two clearly identifiable clusters in speech-related brain regions. The variation in transition-to-hallucination functional patterns not only from one patient to another but also from one occurrence to the next (e.g., also depending on the sensory modalities involved) appeared to be the major difficulty when developing effective classifiers. Consequently, second, this article aimed to characterize the variability within the prehallucination patterns using an extension of principal component analysis with spatial constraints. The principal components (PCs) and the associated basis patterns shed light on the intrinsic structures of the variability present in the dataset. Such results are promising in the scope of innovative fMRI-guided therapy for drug-resistant hallucinations, such as fMRI-based neurofeedback.

Different shades of default mode disturbance in schizophrenia: Subnodal covariance estimation in structure and function.

Schizophrenia is a devastating mental disease with an apparent disruption in the highly associative default mode network (DMN). Interplay between this canonical network and others probably contributes to goal-directed behavior so its disturbance is a candidate neural fingerprint underlying schizophrenia psychopathology. Previous research has reported both hyperconnectivity and hypoconnectivity within the DMN, and both increased and decreased DMN coupling with the multimodal saliency network (SN) and dorsal attention network (DAN). This study systematically revisited network disruption in patients with schizophrenia using data-derived network atlases and multivariate pattern-learning algorithms in a multisite dataset (n = 325). Resting-state fluctuations in unconstrained brain states were used to estimate functional connectivity, and local volume differences between individuals were used to estimate structural co-occurrence within and between the DMN, SN, and DAN. In brain structure and function, sparse inverse covariance estimates of network coupling were used to characterize healthy participants and patients with schizophrenia, and to identify statistically significant group differences. Evidence did not confirm that the backbone of the DMN was the primary driver of brain dysfunction in schizophrenia. Instead, functional and structural aberrations were frequently located outside of the DMN core, such as in the anterior temporoparietal junction and precuneus. Additionally, functional covariation analyses highlighted dysfunctional DMN-DAN coupling, while structural covariation results highlighted aberrant DMN-SN coupling. Our findings reframe the role of the DMN core and its relation to canonical networks in schizophrenia. We thus underline the importance of large-scale neural interactions as effective biomarkers and indicators of how to tailor psychiatric care to single patients.

Very early hallucinatory experiences: a school-based study.

BACKGROUND: The prevalence and clinical significance of hallucinatory experiences among children below 7 years of age remain unknown. We aimed to determine the independent influences of sensory deficits, the presence of an imaginary companion and metacognition on hallucinatory experiences. We assumed that hallucinatory experiences were associated with (a) sensory deficits, (b) the presence of an imaginary companion (IC) and (c) metacognition defaults (i.e. first- and second-order theory of mind default). METHODS: All children in the third year of preschool from a region of Northern France underwent medical screening. We compared the prevalence rates of visual, auditory and audio-visual hallucinatory experiences based on (a) the presence of visual or auditory deficits, (b) the actual presence of an IC and (c) metacognition. The analyses were adjusted for age. RESULTS: A total of 1,087 children aged between 5 and 7 years were included. The prevalence rates of auditory, visual and audio-visual hallucinatory experiences were 15.8%, 12.5% and 5.8%, respectively. The prevalences of different types of hallucinatory experiences were not significantly different according to sensory deficit. The prevalences of all types of hallucinatory experiences were significantly higher among children with an IC and among children with metacognition defaults. CONCLUSIONS: The association between hallucinatory experiences and sensory deficits might concern only long-lasting deficits. The association with the presence of an IC confirms experimental findings of the likelihood of perceiving words among meaningless auditory stimuli. Relations between hallucinatory experiences and theory of mind need to be addressed in longitudinal studies.

A latent class analysis of psychotic symptoms in the general population.

OBJECTIVE: Individuals with psychotic symptoms may actually correspond to various subgroups, characterized by different patterns of psychotic symptoms as well as specific sociodemographic and clinical correlates. We aimed to identify groups of individuals from the general population with specific patterns of psychotic symptoms. METHODS: In a 38,694-subject survey, a latent class analysis was performed to identify subgroups based on the distribution of seven psychotic symptoms taken from the Mini International Neuropsychiatric Interview. The different classes were subsequently compared according to sociodemographic and clinical correlates. RESULTS: The best fit was obtained with a four-class solution, including the following: (1) a class with a low prevalence of all psychotic symptoms ('LOW', 85.9%); (2) a class with a high prevalence of all psychotic symptoms ('HAL + DEL', 1.7%); and classes with a high prevalence of (3) hallucinations ('HAL', 4.5%) or (4) delusions ('DEL', 7.9%). The HAL + DEL class displayed higher rates of history of trauma, social deprivation and migrant status, while the HAL and DEL classes displayed intermediate rates between HAL + DEL and LOW. HAL + DEL displayed the highest rates of psychotic and non-psychotic disorders and the use of mental health treatment, while HAL and DEL displayed intermediate rates of these disorders between HAL + DEL and LOW. In comparison to the HAL class, psychotic and substance use disorders were more frequent in the DEL class, while anxiety and mood disorders were less frequent. CONCLUSION: These findings support the hypothesis of a continuum model relating the level of psychotic symptoms to the level of global psychopathology.

fMRI capture of auditory hallucinations: Validation of the two-steps method.

Our purpose was to validate a reliable method to capture brain activity concomitant with hallucinatory events, which constitute frequent and disabling experiences in schizophrenia. Capturing hallucinations using functional magnetic resonance imaging (fMRI) remains very challenging. We previously developed a method based on a two-steps strategy including (1) multivariate data-driven analysis of per-hallucinatory fMRI recording and (2) selection of the components of interest based on a post-fMRI interview. However, two tests still need to be conducted to rule out critical pitfalls of conventional fMRI capture methods before this two-steps strategy can be adopted in hallucination research: replication of these findings on an independent sample and assessment of the reliability of the hallucination-related patterns at the subject level. To do so, we recruited a sample of 45 schizophrenia patients suffering from frequent hallucinations, 20 schizophrenia patients without hallucinations and 20 matched healthy volunteers; all participants underwent four different experiments. The main findings are (1) high accuracy in reporting unexpected sensory stimuli in an MRI setting; (2) good detection concordance between hypothesis-driven and data-driven analysis methods (as used in the two-steps strategy) when controlled unexpected sensory stimuli are presented; (3) good agreement of the two-steps method with the online button-press approach to capture hallucinatory events; (4) high spatial consistency of hallucinatory-related networks detected using the two-steps method on two independent samples. By validating the two-steps method, we advance toward the possible transfer of such technology to new image-based therapies for hallucinations. Hum Brain Mapp 38:4966-4979, 2017. © 2017 Wiley Periodicals, Inc.