Aberrant connectivity during self-other source monitoring in schizophrenia

Unraveling the brain mechanisms of source monitoring with non-invasive brain stimulation: A systematic review

Background/Objective

Source monitoring refers to the ability to determine the source of memories and encompasses three subprocesses: internal source monitoring, reality monitoring, and external source monitoring. Neuroimaging studies provide valuable insights about neural correlates of source monitoring, but the causal relationship between brain and behavior is lacking. This study aimed to identify brain circuits involved in source monitoring by synthesizing the effects of brain stimulation on source monitoring as a function of the targeted brain regions or circuits.

Method

We conducted a systematic review of interventional studies that have examined the effects of brain stimulation on source monitoring across six databases. The principal outcome was the difference of source monitoring performance between active and control stimulation conditions.

Results

23 studies (920 healthy participants and 54 patients with schizophrenia) were included. Our findings revealed the involvement of i) the lateral prefrontal and temporoparietal cortices in internal source monitoring, ii) the medial prefrontal and temporoparietal cortices in reality monitoring, and iii) the precuneus and the left angular gyrus in external source monitoring.

Conclusions

These findings deepen our understanding of the brain mechanisms of source monitoring and highlight specific stimulation targets to alleviate source monitoring deficits.

A systematic review of performance-based assessment studies on cognitive biases in schizophrenia spectrum psychoses and clinical high-risk states: A summary of 40 years of research

Cognitive models of psychosis have stimulated empirical studies on cognitive biases involved in schizophrenia spectrum psychoses and their symptoms. This systematic review aimed to summarize the studies on the role of cognitive biases as assessed in different performance-based tasks in schizophrenia spectrum psychoses and clinical high-risk states. We focused on five cognitive biases linked to psychosis, i.e., aberrant salience, attentional biases, source monitoring biases, jumping to conclusions, and bias against disconfirmatory evidence. We identified N = 324 studies published in N = 308 articles fulfilling inclusion criteria. Most studies have been cross-sectional and confirmed that the schizophrenia spectrum psychoses are related to exaggerated cognitive biases compared to healthy controls. On the contrary, less evidence suggests a higher tendency for cognitive biases in the UHR sample. The only exceptions were source monitoring and jumping to conclusions, which were confirmed to be exaggerated in both clinical groups. Hallucinations and delusions were the most frequent symptoms studied in the context of cognitive biases. Based on the findings, we presented a hypothetical model on the role of interactions between cognitive biases or additive effects of biases in shaping the risk of psychosis. Future research is warranted for further development of cognitive models for psychosis.

The noise in our brain: A systematic review and meta-analysis of neuroimaging and signal-detection studies on source monitoring in psychosis

OBJECTIVES

Noisy thoughts or perceptions are characteristics of psychosis (PSY) and, they are deeply related to source monitoring (SM) - the ability to discriminate the origin of internal/external experiences.

METHODS

This MOOSE, PRISMA-compliant meta-analysis compared SM performances in PSY compared to healthy controls (HC) focusing on signal-to-noise discrimination in order to: i) test whether neuroimaging procedures (fMRI/EEG) might be a group-specific source of noise for SM; ii) compare error- and accuracy-based indexes; iii) to meta-analyze signal-detection measures (i.e., discrimination index and response bias); iv) to determine the best index capturing SM deficits in psychosis. We conducted a 3-level meta-analysis for each aim to estimate pooled effect-sizes (Cohen's d). SM type, source discrimination and stimulus modality were used as meta-regressors. Heterogeneity (I2), publication bias (Egger's test) and multiple comparisons (Bonferroni correction) were considered.

RESULTS

Sixteen neuroimaging, 44 error/accuracy-based behavioral and 7 signal-detection trials were included (2297 PSY, age range = 18.78-52.6; 1745 HC, age range = 21.1-53.3). The noise generated by neuroimaging procedures slightly influenced error, but not accuracy. Accuracy-based (d = -0.83), but not error-based, indexes showed significant and large SM impairments in PSY compared to HC. Overall SM performance differences between PSY and HC were larger in discrimination index (d = -0.65) and accuracy (d = -0.61), followed by response bias (d = -0.59, ns) and error-based (d = 0.35) indexes.

CONCLUSION

Although both accuracy and discrimination indexes differentiate patients with PSY from HC, discrimination index is more reliable and may better capture the bi-directional nature of the internal/external source confusion.

Analysis of functional connectivity using machine learning and deep learning in different data modalities from individuals with schizophrenia

Objective. Schizophrenia(SCZ) is a severe mental disorder associated with persistent or recurrent psychosis, hallucinations, delusions, and thought disorders that affect approximately 26 million people worldwide, according to the World Health Organization. Several studies encompass machine learning (ML) and deep learning algorithms to automate the diagnosis of this mental disorder. Others study SCZ brain networks to get new insights into the dynamics of information processing in individuals suffering from the condition. In this paper, we offer a rigorous approach with ML and deep learning techniques for evaluating connectivity matrices and measures of complex networks to establish an automated diagnosis and comprehend the topology and dynamics of brain networks in SCZ individuals.Approach.For this purpose, we employed an functional magnetic resonance imaging (fMRI) and electroencephalogram (EEG) dataset. In addition, we combined EEG measures, i.e. Hjorth mobility and complexity, with complex network measurements to be analyzed in our model for the first time in the literature.Main results.When comparing the SCZ group to the control group, we found a high positive correlation between the left superior parietal lobe and the left motor cortex and a positive correlation between the left dorsal posterior cingulate cortex and the left primary motor. Regarding complex network measures, the diameter, which corresponds to the longest shortest path length in a network, may be regarded as a biomarker because it is the most crucial measure in different data modalities. Furthermore, the SCZ brain networks exhibit less segregation and a lower distribution of information. As a result, EEG measures outperformed complex networks in capturing the brain alterations associated with SCZ.Significance. Our model achieved an area under receiver operating characteristic curve (AUC) of 100% and an accuracy of 98.5% for the fMRI, an AUC of 95%, and an accuracy of 95.4% for the EEG data set. These are excellent classification results. Furthermore, we investigated the impact of specific brain connections and network measures on these results, which helped us better describe changes in the diseased brain.

A functional neuroimaging study of self-other processing alterations in atypical developmental trajectories of psychotic-like experiences

Self-disturbances constitute a hallmark of psychosis, but it remains unclear whether these alterations are present in at-risk populations, and therefore their role in the development of psychosis has yet to be confirmed. The present study addressed this question by measuring neural correlates of self-other processing in youth belonging to three developmental trajectories of psychotic experiences. Eighty-six youths were recruited from a longitudinal cohort of over 3800 adolescents based on their trajectories of Psychotic-Like Experiences from 12 to 16 years of age. Participants underwent neuroimaging at 17 years of age (mean). A functional neuroimaging task evaluating self- and other-related trait judgments was used to measure whole-brain activation and connectivity. Youth who showed an increasing trajectory displayed hypoactivation of the dorsomedial prefrontal cortex and hypoconnectivity with the cerebellum. By contrast, youth who showed a decreasing trajectory displayed decreased activation of the superior temporal gyrus, the inferior frontal gyrus, and the middle occipital gyrus. These findings suggest that the increasing trajectory is associated with alterations that might erode distinctions between self and other, influencing the emergence of symptoms such as hallucinations. The decreasing trajectory, in comparison, was associated with hypoactivations in areas influencing attention and basic information processing more generally. These alterations might affect the trajectories’ susceptibilities to positive vs. negative symptoms, respectively.

Perceptual reality monitoring: Neural mechanisms dissociating imagination from reality

There is increasing evidence that imagination relies on similar neural mechanisms as externally triggered perception. This overlap presents a challenge for perceptual reality monitoring: deciding what is real and what is imagined. Here, we explore how perceptual reality monitoring might be implemented in the brain. We first describe sensory and cognitive factors that could dissociate imagery and perception and conclude that no single factor unambiguously signals whether an experience is internally or externally generated. We suggest that reality monitoring is implemented by higher-level cortical circuits that evaluate first-order sensory and cognitive factors to determine the source of sensory signals. According to this interpretation, perceptual reality monitoring shares core computations with metacognition. This multi-level architecture might explain several types of source confusion as well as dissociations between simply knowing whether something is real and actually experiencing it as real. We discuss avenues for future research to further our understanding of perceptual reality monitoring, an endeavour that has important implications for our understanding of clinical symptoms as well as general cognitive function.

Diagnosis of Schizophrenia Based on the Data of Various Modalities: Biomarkers and Machine Learning Techniques (Review)

Schizophrenia is a socially significant mental disorder resulting frequently in severe forms of disability. Diagnosis, choice of treatment tactics, and rehabilitation in clinical psychiatry are mainly based on the assessment of behavioral patterns, socio-demographic data, and other investigations such as clinical observations and neuropsychological testing including examination of patients by the psychiatrist, self-reports, and questionnaires. In many respects, these data are subjective and therefore a large number of works have appeared in recent years devoted to the search for objective characteristics (indices, biomarkers) of the processes going on in the human body and reflected in the behavioral and psychoneurological patterns of patients. Such biomarkers are based on the results of instrumental and laboratory studies (neuroimaging, electro-physiological, biochemical, immunological, genetic, and others) and are successfully being used in neurosciences for understanding the mechanisms of the emergence and development of nervous system pathologies. Presently, with the advent of new effective neuroimaging, laboratory, and other methods of investigation and also with the development of modern methods of data analysis, machine learning, and artificial intelligence, a great number of scientific and clinical studies is being conducted devoted to the search for the markers which have diagnostic and prognostic value and may be used in clinical practice to objectivize the processes of establishing and clarifying the diagnosis, choosing and optimizing treatment and rehabilitation tactics, predicting the course and outcome of the disease. This review presents the analysis of the works which describe the correlates between the diagnosis of schizophrenia, established by health professionals, various manifestations of the psychiatric disorder (its subtype, variant of the course, severity degree, observed symptoms, etc.), and objectively measured characteristics/quantitative indicators (anatomical, functional, immunological, genetic, and others) obtained during instrumental and laboratory examinations of patients. A considerable part of these works has been devoted to correlates/biomarkers of schizophrenia based on the data of structural and functional (at rest and under cognitive load) MRI, EEG, tractography, and immunological data. The found correlates/biomarkers reflect anatomic disorders in the specific brain regions, impairment of functional activity of brain regions and their interconnections, specific microstructure of the brain white matter and the levels of connectivity between the tracts of various structures, alterations of electrical activity in various parts of the brain in different EEG spectral ranges, as well as changes in the innate and adaptive links of immunity. Current methods of data analysis and machine learning to search for schizophrenia biomarkers using the data of diverse modalities and their application during building and interpretation of predictive diagnostic models of schizophrenia have been considered in the present review.

Neural Correlates of Aberrant Salience and Source Monitoring in Schizophrenia and At-Risk Mental States-A Systematic Review of fMRI Studies

Cognitive biases are an important factor contributing to the development and symptom severity of psychosis. Despite the fact that various cognitive biases are contributing to psychosis, they are rarely investigated together. In the current systematic review, we aimed at investigating specific and shared functional neural correlates of two important cognitive biases: aberrant salience and source monitoring. We conducted a systematic search of fMRI studies of said cognitive biases. Eight studies on aberrant salience and eleven studies on source monitoring were included in the review. We critically discussed behavioural and neuroimaging findings concerning cognitive biases. Various brain regions are associated with aberrant salience and source monitoring in individuals with schizophrenia and the risk of psychosis. The ventral striatum and insula contribute to aberrant salience. The medial prefrontal cortex, superior and middle temporal gyrus contribute to source monitoring. The anterior cingulate cortex and hippocampus contribute to both cognitive biases, constituting a neural overlap. Our review indicates that aberrant salience and source monitoring may share neural mechanisms, suggesting their joint role in producing disrupted external attributions of perceptual and cognitive experiences, thus elucidating their role in positive symptoms of psychosis. Account bridging mechanisms of these two biases is discussed. Further studies are warranted.

LSD alters dynamic integration and segregation in the human brain

Investigating changes in brain function induced by mind-altering substances such as LSD is a powerful method for interrogating and understanding how mind interfaces with brain, by connecting novel psychological phenomena with their neurobiological correlates. LSD is known to increase measures of brain complexity, potentially reflecting a neurobiological correlate of the especially rich phenomenological content of psychedelic-induced experiences. Yet although the subjective stream of consciousness is a constant ebb and flow, no studies to date have investigated how LSD influences the dynamics of functional connectivity in the human brain. Focusing on the two fundamental network properties of integration and segregation, here we combined graph theory and dynamic functional connectivity from resting-state functional MRI to examine time-resolved effects of LSD on brain networks properties and subjective experiences. Our main finding is that the effects of LSD on brain function and subjective experience are non-uniform in time: LSD makes globally segregated sub-states of dynamic functional connectivity more complex, and weakens the relationship between functional and anatomical connectivity. On a regional level, LSD reduces functional connectivity of the anterior medial prefrontal cortex, specifically during states of high segregation. Time-specific effects were correlated with different aspects of subjective experiences; in particular, ego dissolution was predicted by increased small-world organisation during a state of high global integration. These results reveal a more nuanced, temporally-specific picture of altered brain connectivity and complexity under psychedelics than has previously been reported.

Differences in the amplitude of low-frequency fluctuation between methamphetamine and heroin use disorder individuals: A resting-state fMRI study

INTRODUCTION

Methamphetamine has surpassed heroin as the most popular abused drug in China. Although the use of both heroin and methamphetamine leads to use disorders through dysfunction of the dopamine pathway, the incidence of psychiatric disorder caused by methamphetamine abuse is higher than the incidence of psychiatric disorder caused by heroin abuse. The difference in resting-state function between heroin use disorder (HUD) and methamphetamine use disorder (MAUD) and the relationship between resting-state function and psychiatric disorder related to MAUD are unknown.

METHODS

In the present study, 21 male individuals with MAUD, 21 demographically matched individuals with HUD, and 21 normal controls (NC) were recruited. The amplitude of low-frequency fluctuation (ALFF) during resting-state brain function was measured by magnetic resonance imaging. Psychiatric status was evaluated by the Symptom Checklist-90 (SCL90).

RESULTS

Individuals with MAUD had increased SCL90 scores compared to those of the NC for anxiety, paranoia, and additional items, and the hostility score was significantly increased compared to that of individuals with HUD. There is no significant difference between HUD and NC individuals. Individuals with MAUD had increased ALFF compared to those of the NC for thalamus, right postcentral, and right inferior temporal gyri, but a decreased ALFF in the cerebellum. Individuals with HUD had significantly increased ALFF compared to those of the NC for left middle frontal gyrus but a decreased ALFF in the left postcentral gyrus. Individuals with MAUD had significantly increased ALFF compared to those of the HUD for thalamus, the right inferior temporal, and bilateral postcentral gyri, and the ALFF of cerebellum and left middle frontal was significantly increased.

CONCLUSIONS

Methamphetamine can induce more serious psychiatric disorders than heroin. The resting-state function involved in mood adjustment, the auditory, and memory-related brain regions may affect psychotic symptoms related to MAUD.

Real-time fMRI neurofeedback reduces auditory hallucinations and modulates resting state connectivity of involved brain regions: Part 2: Default mode network -preliminary evidence

Auditory hallucinations (AHs) are one of the most distressing symptoms of schizophrenia (SZ) and are often resistant to medication. Imaging studies of individuals with SZ show hyperactivation of the default mode network (DMN) and the superior temporal gyrus (STG). Studies in SZ show DMN hyperconnectivity and reduced anticorrelation between DMN and the central executive network (CEN). DMN hyperconnectivity has been associated with positive symptoms such as AHs while reduced DMN anticorrelations with cognitive impairment. Using real-time fMRI neurofeedback (rt-fMRI-NFB) we trained SZ patients to modulate DMN and CEN networks. Meditation is effective in reducing AHs in SZ and to modulate brain network integration and increase DMN anticorrelations. Consequently, patients were provided with meditation strategies to enhance their abilities to modulate DMN/CEN. Results show a reduction of DMN hyperconnectivity and increase in DMNCEN anticorrelation. Furthermore, the change in individual DMN connectivity significantly correlated with reductions in AHs. This is the first time that meditation enhanced through rt-fMRI-NFB is used to reduce AHs in SZ. Moreover, it provides the first empirical evidence for a direct causal relation between meditation enhanced rt-fMRI-NFB modulation of DMNCEN activity and post-intervention modulation of resting state networks ensuing in reductions in frequency and severity of AHs.

Impaired action self-monitoring and cognitive confidence among ultra-high risk for psychosis and first-episode psychosis patients

Background

Self-monitoring biases and overconfidence in incorrect judgments have been suggested as playing a role in schizophrenia spectrum disorders. Little is known about whether self-monitoring biases may contribute to early risk factors for psychosis. In this study, action self-monitoring (i.e., discrimination between imagined and performed actions) was investigated, along with confidence in judgments among ultra-high risk (UHR) for psychosis individuals and first-episode psychosis (FEP) patients.

Methods

Thirty-six UHR for psychosis individuals, 25 FEP patients and 33 healthy controls (CON) participated in the study. Participants were assessed with the Action memory task. Simple actions were presented to participants verbally or non-verbally. Some actions were required to be physically performed and others were imagined. Participants were asked whether the action was presented verbally or non-verbally (action presentation type discrimination), and whether the action was performed or imagined (self-monitoring). Confidence self-ratings related to self-monitoring responses were obtained.

Results

The analysis of self-monitoring revealed that both UHR and FEP groups misattributed imagined actions as being performed (i.e., self-monitoring errors) significantly more often than the CON group. There were no differences regarding performed actions as being imagined. UHR and FEP groups made their false responses with higher confidence in their judgments than the CON group. There were no group differences regarding discrimination between the types of actions presented (verbal vs non-verbal).

Conclusions

A specific type of self-monitoring bias (i.e., misattributing imagined actions with performed actions), accompanied by high confidence in this judgment, may be a risk factor for the subsequent development of a psychotic disorder.

Altered neural basis of self-reflective processing in schizophrenia: An fMRI study

BACKGROUND

Impaired self-awareness has often been described in schizophrenia. Recent neuroimaging studies examining the self-reflection processes in schizophrenia have produced inconsistent results.

METHOD

We examined the self-reflective neural network using self- and other-evaluation tasks in schizophrenia. Fifteen schizophrenia patients and fifteen age- and sex-matched healthy subjects underwent functional magnetic resonance imaging. Subjects were required to decide whether the sentence described their own personal trait (self-evaluation) and that of their close friends (other-evaluation).

RESULTS

Unlike normal control subjects, the schizophrenia patients did not have greater activation of the left posterior cingulate gyrus and hippocampus during self-evaluation than during other-evaluation. On the other hand, the schizophrenia patients had higher activation of the right superior frontal and right supramarginal gyri during self-evaluation than control subjects. Only the patient group exhibited hyperactivation in the left hippocampus and right external capsule associated with the other-evaluation task.

CONCLUSIONS

These findings provide evidence for an altered neural basis of self-reflective processing, which may underlie the self-awareness deficits in schizophrenia.

Are basic auditory processes involved in source-monitoring deficits in patients with schizophrenia?

Patients with schizophrenia (SZ) display deficits in both basic non-verbal auditory processing and source-monitoring of speech. To date, the contributions of basic auditory deficits to higher-order cognitive impairments, such as source-monitoring, and to clinical symptoms have yet to be elucidated. The aim of this study was to investigate the deficits and relationships between basic auditory functions, source-monitoring performances, and clinical symptom severity in SZ. Auditory processing of 4 psychoacoustic features (pitch, intensity, amplitude, length) and 2 types of source-monitoring (internal and reality monitoring) performances were assessed in 29 SZ and 29 healthy controls. Clinical symptoms were evaluated in patients with the Positive And Negative Syndrome Scale. Compared to the controls, SZ individuals in showed significant reductions in both global basic auditory processing (p < .0005, d = 1.16) and source-monitoring (p < .0005, d = 1.24) abilities. Both deficits correlated significantly in patients and across groups (all p < .05). Pitch processing skills were negatively correlated with positive symptom severity (r = -0.4, p < .05). A step-wise regression analysis showed that pitch discrimination was a significant predictor of source-monitoring performance. These results suggest that cognitive mechanisms associated with the discrimination of basic auditory features are most compromised in patients with source-monitoring disability. Basic auditory processing may index pathophysiological processes that are critical for optimal source-monitoring in schizophrenia and that are involved in positive symptoms.

Linking resting-state networks and social cognition in schizophrenia and bipolar disorder

Individuals with schizophrenia and bipolar disorder show alterations in functional neural connectivity during rest. However, resting-state network (RSN) disruptions have not been systematically compared between the two disorders. Further, the impact of RSN disruptions on social cognition, a key determinant of functional outcome, has not been studied. Forty-eight individuals with schizophrenia, 46 with bipolar disorder, and 48 healthy controls completed resting-state functional magnetic resonance imaging. An atlas-based approach was used to examine functional connectivity within nine RSNs across the cortex. RSN connectivity was assessed via nonparametric permutation testing, and associations with performance on emotion perception, mentalizing, and emotion management tasks were examined. Group differences were observed in the medial and lateral visual networks and the sensorimotor network. Individuals with schizophrenia demonstrated reduced connectivity relative to healthy controls in all three networks. Individuals with bipolar disorder demonstrated reduced connectivity relative to controls in the medial visual network and connectivity within this network was significantly positively correlated with emotion management. In healthy controls, connectivity within the medial and lateral visual networks positively correlated with mentalizing. No significant correlations were found for either visual network in schizophrenia. Results highlight the role of altered early visual processing in social cognitive deficits in both schizophrenia and bipolar disorder. However, individuals with bipolar disorder appear to compensate for disrupted visual network connectivity on social cognitive tasks, whereas those with schizophrenia do not. The current study adds clarity on the neurophysiology underlying social cognitive deficits that result in impaired functioning in serious mental illness.

Effects and potential mechanisms of transcranial direct current stimulation (tDCS) on auditory hallucinations: A meta-analysis

Auditory hallucinations are the most common psychiatric symptoms of schizophrenia with high recurrence and refractoriness. Transcranial direct current stimulation (tDCS), a novel, non-invasion and affordable brain stimulation technique, has been recently applying on the schizophrenia patients to treat the auditory hallucinations. To analyze the efficacy of tDCS treatment on such symptoms and to reveal its potential working mechanisms, we carried out a structured literature search in PubMed, Embase and Cochrane Library database up to May 12, 2018. Five studies that met inclusion criteria with a total of 137 patients were included in this meta-analysis. After pooling all the data, we found that there was no significant effect between active group and sham group of tDCS (p = 0.18). When we removed one study that did not collaboratively stimulate the frontal-temporal sites, the active tDCS group marks a significant improvement of therapeutic effect compared with sham group (p = 0.007). Our findings suggested that tDCS could be a promising tool to alleviate auditory hallucinations, provided that the simulation sites and protocols are targeting at the sensorimotor frontal-parietal network.

Brain network dynamics in schizophrenia: Reduced dynamism of the default mode network

Complex human behavior emerges from dynamic patterns of neural activity that transiently synchronize between distributed brain networks. This study aims to model the dynamics of neural activity in individuals with schizophrenia and to investigate whether the attributes of these dynamics associate with the disorder's behavioral and cognitive deficits. A hidden Markov model (HMM) was inferred from resting-state functional magnetic resonance imaging (fMRI) data that was temporally concatenated across individuals with schizophrenia (n = 41) and healthy comparison individuals (n = 41). Under the HMM, fluctuations in fMRI activity within 14 canonical resting-state networks were described using a repertoire of 12 brain states. The proportion of time spent in each state and the mean length of visits to each state were compared between groups, and canonical correlation analysis was used to test for associations between these state descriptors and symptom severity. Individuals with schizophrenia activated default mode and executive networks for a significantly shorter proportion of the 8-min acquisition than healthy comparison individuals. While the default mode was activated less frequently in schizophrenia, the duration of each activation was on average 4-5 s longer than the comparison group. Severity of positive symptoms was associated with a longer proportion of time spent in states characterized by inactive default mode and executive networks, together with heightened activity in sensory networks. Furthermore, classifiers trained on the state descriptors predicted individual diagnostic status with an accuracy of 76-85%.

Lower P300 amplitudes for internally-generated events in patients with schizophrenia

BACKGROUND

Patients with schizophrenia demonstrate difficulty differentiating internally-generated from externally-generated events. An excessive deployment of attention to external events as well as poor processing of self-generated events has been proposed to explain this misattribution. This study was done to understand the neurophysiological basis of source monitoring bias in schizophrenia.

METHODS

Seventeen patients and fourteen healthy controls completed a two-stage source monitoring task involving solving a three-letter jumbled word either by the participant or a computer following which they had to identify the correct source of the word - solved by self (internal source monitoring, ISM) or by computer (external source monitoring, ESM) - while EEG was recorded. P300 amplitude and latency were computed separately for ISM and ESM conditions.

RESULTS

P300 amplitude for ISM condition was lower in patients with schizophrenia compared to controls over right and left parietal regions. Additionally, P300 amplitude for ISM condition was lower compared to ESM condition in patients over right and left parietal regions. However, P300 amplitude for ESM condition did not differ significantly between the groups. In contrast to P300 amplitude, there was no significant difference in P300 latency in ISM or ESM condition within or between the groups.

CONCLUSION

P300 amplitude was lower for internally-generated but not externally-generated events in patients with schizophrenia. These findings suggest that patients allocate less attentional resources to internally generated events resulting in poorer processing and consequent misattribution of their source of origin. This study provides the first specific electrophysiological evidence of impaired source monitoring in schizophrenia.

Efficacy of fronto-temporal transcranial direct current stimulation for refractory auditory verbal hallucinations in schizophrenia: A randomized, double-blind, sham-controlled study

Persistent auditory verbal hallucinations (AVH) that are refractory to antipsychotic medications are reported in about 20-30% of schizophrenia patients. Transcranial Direct Current Stimulation (tDCS), a non-invasive and safe neuromodulatory technique, has attracted significant interest as an add-on treatment for refractory AVH in schizophrenia. Studies examining the efficacy of tDCS for refractory AVH in schizophrenia have reported inconsistent findings. In this study, using a randomized, double-blind, sham-controlled design (RCT), we sought to examine the effect of add-on tDCS [anode corresponding to left dorsolateral prefrontal cortex and cathode to left temporo-parietal junction; 2-mA, twice-daily sessions for 5-days] to treat refractory AVH in schizophrenia patients (N=25); following this RCT phase, patients that had <30% reduction in AVH severity were offered an open-label extension (OLE) active stimulation to evaluate the effect of cross-over to verum tDCS. In the RCT phase, repeated measures ANOVA with tDCS type [verum (N=12) vs. sham (N=13)] as between subjects factor demonstrated a significant tDCS-type X time-point interaction [F=21.5, p<0.001, partial-η2=0.48] with significantly greater reduction of AVH score in verum tDCS group as compared to sham group. In the OLE phase, sham-to-verum crossed over patients (N=13) showed significantly greater reduction in AVH severity than their corresponding change during RCT phase (t=2.9; p=0.01). Together, these observations add further support to the beneficial effects of add-on tDCS to treat refractory AVH schizophrenia.

The neural correlates of self-referential memory encoding and retrieval in schizophrenia

BACKGROUND

Enhanced memory for self-oriented information is known as the self-referential memory (SRM) effect. fMRI studies of the SRM effect have focused almost exclusively on encoding, revealing selective engagement of the medial prefrontal cortex (mPFC) during "self" relative to other processing conditions. Other critical areas for self-processing include ventrolateral prefrontal cortex (vlPFC), temporo-parietal junction (TPJ) and posterior cingulate/precuneus (PCC/PC). Previous behavioral studies show that individuals with schizophrenia fail to benefit from this memory boost. However, the neural correlates of this deficit, at either encoding or retrieval, are unknown.

METHODS

Twenty individuals with schizophrenia and 16 healthy controls completed an event-related fMRI SRM paradigm. During encoding, trait adjectives were judged in terms of structural features ("case" condition), social desirability ("other" condition), or as self-referential ("self" condition). Participants then completed an unexpected recognition test (retrieval phase). We examined BOLD activation during both encoding and retrieval within mPFC, vlPFC, TPJ, and PCC/PC regions-of-interest (ROIs).

RESULTS

During encoding, fMRI data indicated both groups had greater activation during the "self" relative to the "other" condition across ROIs. Controls showed this primarily in mPFC whereas patients showed this in PCC/PC. During retrieval, fMRI data indicated controls showed differentiation across ROIs between "self" and "other" conditions, but patients did not.

CONCLUSIONS

Results suggest regional differences in the neural processing of self-referential information in individuals with schizophrenia, perhaps because representation of the self is not as well established in patients relative to controls. The current study presents novel findings that add to the literature implicating impaired self-oriented processing in schizophrenia.

Brain Mechanisms of Reality Monitoring

Reality monitoring processes are necessary for discriminating between internally generated information and information that originated in the outside world. They help us to identify our thoughts, feelings, and imaginations, and to distinguish them from events we may have experienced or have been told about by someone else. Reality monitoring errors range from confusions between real and imagined experiences, that are byproducts of normal cognition, to symptoms of mental illness such as hallucinations. Recent advances support an emerging neurocognitive characterization of reality monitoring that provides insights into its underlying operating principles and neural mechanisms, the differing ways in which impairment may occur in health and disease, and the potential for rehabilitation strategies to be devised that might help those who experience clinically significant reality monitoring disruption.

Abnormal Degree Centrality of Bilateral Putamen and Left Superior Frontal Gyrus in Schizophrenia with Auditory Hallucinations: A Resting-state Functional Magnetic Resonance Imaging Study

BACKGROUND

Dysconnectivity hypothesis of schizophrenia has been increasingly emphasized. Recent researches showed that this dysconnectivity might be related to occurrence of auditory hallucination (AH). However, there is still no consistent conclusion. This study aimed to explore intrinsic dysconnectivity pattern of whole-brain functional networks at voxel level in schizophrenic with AH.

METHODS

Auditory hallucinated patients group (n = 42 APG), no hallucinated patients group (n = 42 NPG) and normal controls (n = 84 NCs) were analyzed by resting-state functional magnetic resonance imaging. The functional connectivity metrics index (degree centrality [DC]) across the entire brain networks was calculated and evaluated among three groups.

RESULTS

DC decreased in the bilateral putamen and increased in the left superior frontal gyrus in all the patients. However, in APG, the changes of DC were more obvious compared with NPG. Symptomology scores were negatively correlated with the DC of bilateral putamen in all patients. AH score of APG positively correlated with the DC in left superior frontal gyrus but negatively correlated with the DC in bilateral putamen.

CONCLUSION

Our findings corroborated that schizophrenia was characterized by functional dysconnectivity, and the abnormal DC in bilateral putamen and left superior frontal gyrus might be crucial in the occurrence of AH.

Interaction of language, auditory and memory brain networks in auditory verbal hallucinations

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The language, auditory and memory/limbic networks are of particular relevance for auditory verbal hallucinations.

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An increased interaction among the auditory-language and striatal brain regions occurs while patients hallucinate.

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Fronto-temporal connections are often altered in AVH individuals, but there is no consensus regarding increase or decrease.

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Connections of the interhemispheric auditory pathway are stronger for first episode patients, but they are weaker in chronic patients.

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The majority of studies support hybrid AVH hypotheses in which all three networks and the striatal network are involved.

Auditory verbal hallucinations (AVH) occur in psychotic disorders, but also as a symptom of other conditions and even in healthy people. Several current theories on the origin of AVH converge, with neuroimaging studies suggesting that the language, auditory and memory/limbic networks are of particular relevance. However, reconciliation of these theories with experimental evidence is missing. We review 50 studies investigating functional (EEG and fMRI) and anatomic (diffusion tensor imaging) connectivity in these networks, and explore the evidence supporting abnormal connectivity in these networks associated with AVH. We distinguish between functional connectivity during an actual hallucination experience (symptom capture) and functional connectivity during either the resting state or a task comparing individuals who hallucinate with those who do not (symptom association studies). Symptom capture studies clearly reveal a pattern of increased coupling among the auditory, language and striatal regions. Anatomical and symptom association functional studies suggest that the interhemispheric connectivity between posterior auditory regions may depend on the phase of illness, with increases in non-psychotic individuals and first episode patients and decreases in chronic patients. Leading hypotheses involving concepts as unstable memories, source monitoring, top-down attention, and hybrid models of hallucinations are supported in part by the published connectivity data, although several caveats and inconsistencies remain. Specifically, possible changes in fronto-temporal connectivity are still under debate. Precise hypotheses concerning the directionality of connections deduced from current theoretical approaches should be tested using experimental approaches that allow for discrimination of competing hypotheses.

Development of Embodied Sense of Self Scale (ESSS): Exploring Everyday Experiences Induced by Anomalous Self-Representation

The scientific exploration of the self has progressed, with much attention focused on the Embodied Sense of Self (ESS). Empirical studies have suggested the mechanisms for self-representation. On the other hand, less attention has been paid to the subjectivity itself of the self. With reference to previous studies, the current study collected items that reflect the ESS and statistically extracted three factors for it: Ownership, Agency, and Narrative. The developed questionnaire [Embodied Sense of Self Scale (ESSS)] showed good enough validity and reliability for practical use. Furthermore, ESSS discriminated schizophrenia, a disorder of the ESS, from controls. We discuss the factorial structure of ESS and the relationship among factors on the basis of the current results.

Misattributing the Source of Self-Generated Representations Related to Dissociative and Psychotic Symptoms

Objective: An intertwined relationship has been found between dissociative and psychotic symptoms, as the two symptom clusters frequently co-occur, suggesting some shared risk factors. Using a source monitoring paradigm, previous studies have shown that patients with schizophrenia made more errors in source monitoring, suggesting that a weakened sense of individuality may be associated with psychotic symptoms. However, no studies have verified a relationship between sense of individuality and dissociation, and it is unclear whether an altered sense of individuality is a shared sociocognitive deficit underlying both dissociation and psychosis.

Method: Data from 80 acute psychiatric patients with unspecified mental disorders were analyzed to test the hypothesis that an altered sense of individuality underlies dissociation and psychosis. Behavioral tasks, including tests of intelligence and source monitoring, as well as interview schedules and self-report measures of dissociative and psychotic symptoms, general psychopathology, and trauma history, were administered.

Results: Significant correlations of medium effect sizes indicated an association between errors attributing the source of self-generated items and positive psychotic symptoms and the absorption and amnesia measures of dissociation. The associations with dissociative measures remained significant after the effects of intelligence, general psychopathology, and trauma history were excluded. Moreover, the relationships between source misattribution and dissociative measures remained marginally significant and significant after controlling for positive and negative psychotic symptoms, respectively.

Limitations: Self-reported measures were collected from a small sample, and most of the participants were receiving medications when tested, which may have influenced their cognitive performance.

Conclusions: A tendency to misidentify the source of self-generated items characterized both dissociation and psychosis. An altered sense of individuality embedded in self-referential representations appears to be a common sociocognitive deficit of dissociation and psychosis.

Non-invasive Brain Stimulation and Auditory Verbal Hallucinations: New Techniques and Future Directions

Auditory verbal hallucinations (AVHs) are the experience of hearing a voice in the absence of any speaker. Results from recent attempts to treat AVHs with neurostimulation (rTMS or tDCS) to the left temporoparietal junction have not been conclusive, but suggest that it may be a promising treatment option for some individuals. Some evidence suggests that the therapeutic effect of neurostimulation on AVHs may result from modulation of cortical areas involved in the ability to monitor the source of self-generated information. Here, we provide a brief overview of cognitive models and neurostimulation paradigms associated with treatment of AVHs, and discuss techniques that could be explored in the future to improve the efficacy of treatment, including alternating current and random noise stimulation. Technical issues surrounding the use of neurostimulation as a treatment option are discussed (including methods to localize the targeted cortical area, and the state-dependent effects of brain stimulation), as are issues surrounding the acceptability of neurostimulation for adolescent populations and individuals who experience qualitatively different types of AVH.

Targeting Treatment-Resistant Auditory Verbal Hallucinations in Schizophrenia with fMRI-Based Neurofeedback - Exploring Different Cases of Schizophrenia

Auditory verbal hallucinations (AVHs) are a hallmark of schizophrenia and can significantly impair patients' emotional, social, and occupational functioning. Despite progress in psychopharmacology, over 25% of schizophrenia patients suffer from treatment-resistant hallucinations. In the search for alternative treatment methods, neurofeedback (NF) emerges as a promising therapy tool. NF based on real-time functional magnetic resonance imaging (rt-fMRI) allows voluntarily change of the activity in a selected brain region - even in patients with schizophrenia. This study explored effects of NF on ongoing AVHs. The selected participants were trained in the self-regulation of activity in the anterior cingulate cortex (ACC), a key monitoring region involved in generation and intensity modulation of AVHs. Using rt-fMRI, three right-handed patients, suffering from schizophrenia and ongoing, treatment-resistant AVHs, learned control over ACC activity on three separate days. The effect of NF training on hallucinations' severity was assessed with the Auditory Vocal Hallucination Rating Scale (AVHRS) and on the affective state - with the Positive and Negative Affect Schedule (PANAS). All patients yielded significant upregulation of the ACC and reported subjective improvement in some aspects of AVHs (AVHRS) such as disturbance and suffering from the voices. In general, mood (PANAS) improved during NF training, though two patients reported worse mood after NF on the third day. ACC and reward system activity during NF learning and specific effects on mood and symptoms varied across the participants. None of them profited from the last training set in the prolonged three-session training. Moreover, individual differences emerged in brain networks activated with NF and in symptom changes, which were related to the patients' symptomatology and disease history. NF based on rt-fMRI seems a promising tool in therapy of AVHs. The patients, who suffered from continuous hallucinations for years, experienced symptom changes that may be attributed to the NF training. In order to assess the effectiveness of NF as a therapeutic method, this effect has to be studied systematically in larger groups; further, long-term effects need to be assessed. Particularly in schizophrenia, future NF studies should take into account the individual differences in reward processing, fatigue, and motivation to develop individualized training protocols.

Translating Neurocognitive Models of Auditory-Verbal Hallucinations into Therapy: Using Real-time fMRI-Neurofeedback to Treat Voices

Auditory-verbal hallucinations (AVHs) are frequent and disabling symptoms, which can be refractory to conventional psychopharmacological treatment in more than 25% of the cases. Recent advances in brain imaging allow for a better understanding of the neural underpinnings of AVHs. These findings strengthened transdiagnostic neurocognitive models that characterize these frequent and disabling experiences. At the same time, technical improvements in real-time functional magnetic resonance imaging (fMRI) enabled the development of innovative and non-invasive methods with the potential to relieve psychiatric symptoms, such as fMRI-based neurofeedback (fMRI-NF). During fMRI-NF, brain activity is measured and fed back in real time to the participant in order to help subjects to progressively achieve voluntary control over their own neural activity. Precisely defining the target brain area/network(s) appears critical in fMRI-NF protocols. After reviewing the available neurocognitive models for AVHs, we elaborate on how recent findings in the field may help to develop strong a priori strategies for fMRI-NF target localization. The first approach relies on imaging-based "trait markers" (i.e., persistent traits or vulnerability markers that can also be detected in the presymptomatic and remitted phases of AVHs). The goal of such strategies is to target areas that show aberrant activations during AVHs or are known to be involved in compensatory activation (or resilience processes). Brain regions, from which the NF signal is derived, can be based on structural MRI and neurocognitive knowledge, or functional MRI information collected during specific cognitive tasks. Because hallucinations are acute and intrusive symptoms, a second strategy focuses more on "state markers." In this case, the signal of interest relies on fMRI capture of the neural networks exhibiting increased activity during AVHs occurrences, by means of multivariate pattern recognition methods. The fine-grained activity patterns concomitant to hallucinations can then be fed back to the patients for therapeutic purpose. Considering the potential cost necessary to implement fMRI-NF, proof-of-concept studies are urgently required to define the optimal strategy for application in patients with AVHs. This technique has the potential to establish a new brain imaging-guided psychotherapy for patients that do not respond to conventional treatments and take functional neuroimaging to therapeutic applications.

Aberrant Salience Is Related to Dysfunctional Self-Referential Processing in Psychosis

BACKGROUND

A dysfunctional differentiation between self-relevant and irrelevant information may affect the perception of environmental stimuli as abnormally salient. The aberrant salience hypothesis assumes that positive symptoms arise from an attribution of salience to irrelevant stimuli accompanied by the feeling of self-relevance. Self-referential processing relies on the activation of cortical midline structures which was demonstrated to be impaired in psychosis. We investigated the neural correlates of self-referential processing, aberrant salience attribution, and the relationship between these 2 measures across the psychosis continuum.

METHODS

Twenty-nine schizophrenia patients, 24 healthy individuals with subclinical delusional ideation, and 50 healthy individuals participated in this study. Aberrant salience was assessed behaviorally in terms of reaction times to task irrelevant cues. Participants performed a self-reference task during fMRI in which they had to apply neutral trait words to them or to a public figure. The correlation between self-referential processing and aberrant salience attribution was tested.

RESULTS

Schizophrenia patients displayed increased aberrant salience attribution compared with healthy controls and individuals with subclinical delusional ideation, while the latter exhibited intermediate aberrant salience scores. In the self-reference task, schizophrenia patients showed reduced activation in the ventromedial prefrontal cortex (vmPFC), but individuals with subclinical delusional ideation did not differ from healthy controls. In schizophrenia patients, vmPFC activation correlated negatively with implicit aberrant salience attribution.

CONCLUSIONS

Higher aberrant salience attribution in schizophrenia patients is related to reduced vmPFC activation during self-referential judgments suggesting that aberrant relevance coding is reflected in decreased neural self-referential processing as well as in aberrant salience attribution.

An integrated network model of psychotic symptoms

The full body of research on the nature of psychosis and its determinants indicates that a considerable number of factors are relevant to the development of hallucinations, delusions, and other positive symptoms, ranging from neurodevelopmental parameters and altered connectivity of brain regions to impaired cognitive functioning and social factors. We aimed to integrate these factors in a single mathematical model based on network theory. At the microscopic level this model explains positive symptoms of psychosis in terms of experiential equivalents of robust, high-frequency attractor states of neural networks. At the mesoscopic level it explains them in relation to global brain states, and at the macroscopic level in relation to social-network structures and dynamics. Due to the scale-free nature of biological networks, all three levels are governed by the same general laws, thereby allowing for an integrated model of biological, psychological, and social phenomena involved in the mediation of positive symptoms of psychosis. This integrated network model of psychotic symptoms (INMOPS) is described together with various possibilities for application in clinical practice.

A Window into the Brain: Advances in Psychiatric fMRI

Functional magnetic resonance imaging (fMRI) plays a key role in modern psychiatric research. It provides a means to assay differences in brain systems that underlie psychiatric illness, treatment response, and properties of brain structure and function that convey risk factor for mental diseases. Here we review recent advances in fMRI methods in general use and progress made in understanding the neural basis of mental illness. Drawing on concepts and findings from psychiatric fMRI, we propose that mental illness may not be associated with abnormalities in specific local regions but rather corresponds to variation in the overall organization of functional communication throughout the brain network. Future research may need to integrate neuroimaging information drawn from different analysis methods and delineate spatial and temporal patterns of brain responses that are specific to certain types of psychiatric disorders.

Hearing voices in the resting brain: A review of intrinsic functional connectivity research on auditory verbal hallucinations

Resting state networks (RSNs) are thought to reflect the intrinsic functional connectivity of brain regions. Alterations to RSNs have been proposed to underpin various kinds of psychopathology, including the occurrence of auditory verbal hallucinations (AVH). This review outlines the main hypotheses linking AVH and the resting state, and assesses the evidence for alterations to intrinsic connectivity provided by studies of resting fMRI in AVH. The influence of hallucinations during data acquisition, medication confounds, and movement are also considered. Despite a large variety of analytic methods and designs being deployed, it is possible to conclude that resting connectivity in the left temporal lobe in general and left superior temporal gyrus in particular are disrupted in AVH. There is also preliminary evidence of atypical connectivity in the default mode network and its interaction with other RSNs. Recommendations for future research include the adoption of a common analysis protocol to allow for more overlapping datasets and replication of intrinsic functional connectivity alterations.

Prefrontal cortex and the dysconnectivity hypothesis of schizophrenia

Schizophrenia is hypothesized to arise from disrupted brain connectivity. This "dysconnectivity hypothesis" has generated interest in discovering whether there is anatomical and functional dysconnectivity between the prefrontal cortex (PFC) and other brain regions, and how this dysconnectivity is linked to the impaired cognitive functions and aberrant behaviors of schizophrenia. Critical advances in neuroimaging technologies, including diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI), make it possible to explore these issues. DTI affords the possibility to explore anatomical connectivity in the human brain in vivo and fMRI can be used to make inferences about functional connections between brain regions. In this review, we present major advances in the understanding of PFC anatomical and functional dysconnectivity and their implications in schizophrenia. We then briefly discuss future prospects that need to be explored in order to move beyond simple mapping of connectivity changes to elucidate the neuronal mechanisms underlying schizophrenia.

Resting-state functional connectivity alterations in the default network of schizophrenia patients with persistent auditory verbal hallucinations

To understand the neural mechanism that underlies treatment resistant auditory verbal hallucinations (AVH), is still an important issue in psychiatric research. Alterations in functional connectivity during rest have been frequently reported in patients with schizophrenia. Though the default mode network (DN) appears to be abnormal in schizophrenia patients, little is known about its role in resistant AVH. We collected resting-state functional magnetic resonance imaging (R-fMRI) data with a 3T scanner from 19 schizophrenia patients with chronic AVH resistant to pharmacological treatment, 14 schizophrenia patients without AVH and 20 healthy controls. Using seed-based correlation analysis, we created spherical seed regions of interest (ROI) to examine functional connectivity of the two DN hub regions (posterior cingulate cortex and anteromedial prefrontal cortex) and the two DN subsystems: dorsomedial prefrontal cortex subsystem and medial temporal lobe subsystem (p<0.0045 corrected). Patients with hallucinations exhibited higher FC between dMPFC ROI and bilateral central opercular cortex, bilateral insular cortex and bilateral precentral gyrus compared to non hallucinating patients and healthy controls. Additionally, patients with hallucinations also exhibited lower FC between vMPFC ROI and bilateral paracingulate and dorsal anterior cingulate cortex. As the anterior cingulate cortex and the insula are two hubs of the salience network, our results suggest cross-network abnormalities between DN and salience system in patients with persistent hallucinations.

Discrimination of schizophrenia auditory hallucinators by machine learning of resting-state functional MRI

Auditory hallucinations (AH) are a symptom that is most often associated with schizophrenia, but patients with other neuropsychiatric conditions, and even a small percentage of healthy individuals, may also experience AH. Elucidating the neural mechanisms underlying AH in schizophrenia may offer insight into the pathophysiology associated with AH more broadly across multiple neuropsychiatric disease conditions. In this paper, we address the problem of classifying schizophrenia patients with and without a history of AH, and healthy control (HC) subjects. To this end, we performed feature extraction from resting state functional magnetic resonance imaging (rsfMRI) data and applied machine learning classifiers, testing two kinds of neuroimaging features: (a) functional connectivity (FC) measures computed by lattice auto-associative memories (LAAM), and (b) local activity (LA) measures, including regional homogeneity (ReHo) and fractional amplitude of low frequency fluctuations (fALFF). We show that it is possible to perform classification within each pair of subject groups with high accuracy. Discrimination between patients with and without lifetime AH was highest, while discrimination between schizophrenia patients and HC participants was worst, suggesting that classification according to the symptom dimension of AH may be more valid than discrimination on the basis of traditional diagnostic categories. FC measures seeded in right Heschl's gyrus (RHG) consistently showed stronger discriminative power than those seeded in left Heschl's gyrus (LHG), a finding that appears to support AH models focusing on right hemisphere abnormalities. The cortical brain localizations derived from the features with strong classification performance are consistent with proposed AH models, and include left inferior frontal gyrus (IFG), parahippocampal gyri, the cingulate cortex, as well as several temporal and prefrontal cortical brain regions. Overall, the observed findings suggest that computational intelligence approaches can provide robust tools for uncovering subtleties in complex neuroimaging data, and have the potential to advance the search for more neuroscience-based criteria for classifying mental illness in psychiatry research.

Dynamic connectivity states estimated from resting fMRI Identify differences among Schizophrenia, bipolar disorder, and healthy control subjects

Schizophrenia (SZ) and bipolar disorder (BP) share significant overlap in clinical symptoms, brain characteristics, and risk genes, and both are associated with dysconnectivity among large-scale brain networks. Resting state functional magnetic resonance imaging (rsfMRI) data facilitates studying macroscopic connectivity among distant brain regions. Standard approaches to identifying such connectivity include seed-based correlation and data-driven clustering methods such as independent component analysis (ICA) but typically focus on average connectivity. In this study, we utilize ICA on rsfMRI data to obtain intrinsic connectivity networks (ICNs) in cohorts of healthy controls (HCs) and age matched SZ and BP patients. Subsequently, we investigated difference in functional network connectivity, defined as pairwise correlations among the timecourses of ICNs, between HCs and patients. We quantified differences in both static (average) and dynamic (windowed) connectivity during the entire scan duration. Disease-specific differences were identified in connectivity within different dynamic states. Notably, results suggest that patients make fewer transitions to some states (states 1, 2, and 4) compared to HCs, with most such differences confined to a single state. SZ patients showed more differences from healthy subjects than did bipolars, including both hyper and hypo connectivity in one common connectivity state (dynamic state 3). Also group differences between SZ and bipolar patients were identified in patterns (states) of connectivity involving the frontal (dynamic state 1) and frontal-parietal regions (dynamic state 3). Our results provide new information about these illnesses and strongly suggest that state-based analyses are critical to avoid averaging together important factors that can help distinguish these clinical groups.

Towards a cognitive model of hallucinations in the course of alcohol dependence? A source monitoring-based pilot study

BACKGROUND

We investigated whether source-monitoring deficits (here a discrimination between imagined and performed actions) underlie hallucinations among patients with a history of hallucinations in the course of their alcohol dependence.

METHOD

We assessed 29 patients with alcohol dependence who had no history of hallucinations during their course of alcoholism and 29 patients with a history of at least one episode of hallucinations of any modality during their course of alcohol dependency. The control group consisted of 24 healthy participants. Participants were assessed with an action memory task. Simple actions were presented to the participants verbally or non-verbally. Some actions were performed physically and others were imagined. In the recognition phase, participants were asked whether the action was presented verbally or non-verbally (action presentation type discrimination) and whether the action was performed or imagined (self-monitoring). A confidence score related to self-monitoring responses was also obtained.

RESULTS

Alcoholics with a history of hallucinations misremembered imagined actions as perceived ones more frequently than patients without hallucinations, but not the reverse. Only patients with a history of hallucinations committed more errors of this type than healthy subjects. There were no group differences regarding discrimination between an action presentation type. Both clinical groups committed errors with a higher degree of confidence than healthy subjects.

CONCLUSIONS

Our results tentatively suggest that a specific type of source-monitoring deficit (i.e., confusing imagery with reality) may be involved in the hallucinations in patients with alcohol dependence. The findings are discussed in the light of a transdiagnostic approach to hallucinations.

Source retrieval is not properly differentiated from object retrieval in early schizophrenia: an fMRI study using virtual reality

Source memory, the ability to identify the context in which a memory occurred, is impaired in schizophrenia and has been related to clinical symptoms such as hallucinations. The neurobiological underpinnings of this deficit are not well understood. Twenty-five patients with recent onset schizophrenia (within the first 4.5 years of treatment) and twenty-four healthy controls completed a source memory task. Participants navigated through a 3D virtual city, and had 20 encounters of an object with a person at a place. Functional magnetic resonance imaging was performed during a subsequent forced-choice recognition test. Two objects were presented and participants were asked to either identify which object was seen (new vs. old object recognition), or identify which of the two old objects was associated with either the person or the place being presented (source memory recognition). Source memory was examined by contrasting person or place with object. Both patients and controls demonstrated significant neural activity to source memory relative to object memory, though activity in controls was much more widespread. Group differences were observed in several regions, including the medial parietal and cingulate cortex, lateral frontal lobes and right superior temporal gyrus. Patients with schizophrenia did not differentiate between source and object memory in these regions. Positive correlations with hallucination proneness were observed in the left frontal and right middle temporal cortices and cerebellum. Patients with schizophrenia have a deficit in the neural circuits which facilitate source memory, which may underlie both the deficits in this domain and be related to auditory hallucinations.

Do thoughts have sound? Differences between thoughts and auditory hallucinations in schizophrenia

Cognitive theories about auditory hallucinations maintain that inner speech is erroneously interpreted as coming from an external source. Few first-hand accounts of patients' experiences have been made, so there is limited knowledge of the process through which patients distinguish their auditory verbal hallucinations (AVHs) from ordinary thoughts. 89 individuals diagnosed with schizophrenia, some experiencing acute hallucinatory symptomatology (Sz-AVHs) and some who were not (Sz-noAVHs), were assessed along with 48 individuals from the general population using the Auditory Hallucinations Assessment Questionnaire (AHAQ; Cuevas-Yust, Rodríguez Martín, Ductor Recuerda, Salas Azcona, & León Gómez, 2006). The Schz-AVHs group reported hearing ordinary thoughts at the same volume as their auditory hallucinations (p = .53) and spoken words (p = .89). In contrast, the Sz-noAVHs and general population samples reported hearing spoken words louder than their own thoughts (p = .002; p = .04). In comparison to these last two groups, the Sz-AVHs group described the sound of their thoughts as louder. These findings are consistent with the cognitive hypothesis of auditory verbal hallucinations. Confusion identifying the source of auditory hallucinations could be due, in part, to "hearing" one's thoughts at the same volume as auditory hallucinations and spoken words.

Subclinical delusional thinking predicts lateral temporal cortex responses during social reflection

Neuroimaging studies have demonstrated associations between delusions in psychotic disorders and abnormalities of brain areas involved in social cognition, including medial prefrontal cortex (MPFC), posterior cingulate cortex, and lateral temporal cortex (LTC). General population studies have linked subclinical delusional thinking to impaired social cognition, raising the question of whether a specific pattern of brain activity during social perception is associated with delusional beliefs. Here, we tested the hypothesis that subclinical delusional thinking is associated with changes in neural function, while subjects made judgments about themselves or others ['social reflection' (SR)]. Neural responses during SR and non-social tasks, as well as resting-state activity, were measured using functional magnetic resonance imaging in 22 healthy subjects. Delusional thinking was measured using the Peters et al. Delusions Inventory. Delusional thinking was negatively correlated with responses of the left LTC during SR (r = -0.61, P = 0.02, Bonferroni corrected), and connectivity between the left LTC and left ventral MPFC, and was positively correlated with connectivity between the left LTC and the right middle frontal and inferior temporal cortices. Thus, delusional thinking in the general population may be associated with reduced activity and aberrant functional connectivity of cortical areas involved in SR.

Self-disturbances as a possible premorbid indicator of schizophrenia risk: a neurodevelopmental perspective

Self-disturbances (SDs) are increasingly identified in schizophrenia and are theorized to confer vulnerability to psychosis. Neuroimaging research has shed some light on the neural correlates of SDs in schizophrenia. But, the onset and trajectory of the neural alterations underlying SDs in schizophrenia remain incompletely understood. We hypothesize that the aberrant structure and function of brain areas (e.g., prefrontal, lateral temporal, and parietal cortical structures) comprising the "neural circuitry of self" may represent an early, premorbid (i.e., pre-prodromal) indicator of schizophrenia risk. Consistent with neurodevelopmental models, we argue that "early" (i.e., perinatal) dysmaturational processes (e.g., abnormal cortical neural cell migration and mini-columnar formation) affecting key prefrontal (e.g., medial prefrontal cortex), lateral temporal cortical (e.g., superior temporal sulcus), and parietal (e.g., inferior parietal lobule) structures involved in self-processing may lead to subtle disruptions of "self" during childhood in persons at risk for schizophrenia. During adolescence, progressive neurodevelopmental alterations (e.g., aberrant synaptic pruning) affecting the neural circuitry of self may contribute to worsening of SDs. This could result in the emergence of prodromal symptoms and, eventually, full-blown psychosis. To highlight why adolescence may be a period of heightened risk for SDs, we first summarize the literature regarding the neural correlates of self in typically developing children. Next, we present evidence from neuroimaging studies in genetic high-risk youth suggesting that fronto-temporal-parietal structures mediating self-reflection may be abnormal in the premorbid period. Our goal is that the ideas presented here might provide future directions for research into the neurobiology of SDs during the pre-psychosis development of youth at risk for schizophrenia.

The development of delusion revisited: a transdiagnostic framework

This study proposes a transdiagnostic framework for delusion development, analysing psychiatric (schizophrenia, bipolar disorder, major depressive disorder) and neurological disorders (stroke, and neurodegenerative diseases) in which delusions are predominant. Our aim is to identify a transdiagnostic core of neural and cognitive alterations associated with delusions across distinct clinical disorders. Reviewed empirical evidence suggests delusions are associated: on the neural level with changes in the ventromedial prefrontal cortex (vmPFC) networks, and on the neuropsychological level with dysfunction in the processes (generation of affective value, the construction of internal models of the world, and the reflection about Self and/or Other's mental states) that these network mediate. The concurrent aberration of all these processes could be critical for the clinical transition to a psychotic delusional state. In particular, delusions could become clinically manifest when (1) stimuli are attributed an aberrant affective salience, that (2) is explained by the patient within distorted explanatory internal models that (3) are poorly inhibited by cognitive control systems. This framework extends the two-factor account of delusion model and suggests that common neural mechanisms for the delusions in psychiatric and in neurological disorders.