Reduced connectivity in the self-processing network of schizophrenia patients with poor insight

Global neural self-disturbance in schizophrenia: A systematic fMRI review

There is a general consensus that schizophrenia (SZ) is characterized by major changes in the sense of self. Phenomenological studies suggest that these changes in the sense of self stem from a basic disturbance, hence the term 'basic self-disturbance'. While imaging studies demonstrate changes in various regions during self-focused tasks, the exact neural correlates of such basic self-disturbances remain unclear. If the self-disturbance is indeed basic and thereby underlies all other symptoms, one would expect it to be related to more global rather than local changes in the brain. Testing this hypothesis, we conducted a systematic review of fMRI studies on self in SZ. Our main findings are 1. Abnormal activity related to the self can be observed in a variety of different regions ranging from higher-order transmodal to lower-order unimodal regions, 2. These findings hold true across different tasks including self-reflection, self-referentiality, and self-agency, and 3. The global neural abnormalities related to the self in SZ correspond to all layers of the self, predominantly the mental and exteroceptive self. Such global neural disturbance of self converges well with the basic self-disturbance as described in phenomenology.

Structure/function interrelationships and illness insight in patients with schizophrenia: a multimodal MRI data fusion study

Illness insight in schizophrenia (SZ) has an important impact on treatment outcome, integration into society and can vary over the course of the disorder. To deal with and treat reduced or absent illness insight, we need to better understand its functional and structural correlates. Previous studies showed regionally abnormal brain volume in brain areas related to cognitive control and self-reference. However, little is known about associations between illness insight and structural and functional network strength in patients with SZ. This study employed a cross-sectional design to examine structural and functional differences between patients with SZ (n = 74) and healthy controls (n = 47) using structural and resting-state functional magnetic resonance imaging (MRI). Voxel-based morphometry was performed on structural data, and the amplitude of low frequency fluctuations (ALFF) was calculated for functional data. To investigate abnormal structure/function interrelationships and their association with illness insight, we used parallel independent component analysis (pICA). Significant group (SZ vs. HC) differences were detected in distinct structural and functional networks, predominantly comprising frontoparietal, temporal and cerebellar regions. Significant associations were found between illness insight and two distinct structural networks comprising frontoparietal (pre- and postcentral gyrus, inferior parietal lobule, thalamus, and precuneus) and posterior cortical regions (cuneus, precuneus, lingual, posterior cingulate, and middle occipital gyrus). Finally, we found a significant relationship between illness insight and functional network comprising temporal regions (superior temporal gyrus). This study suggests that aberrant structural and functional integrity of neural systems subserving cognitive control, memory and self-reference are tightly coupled to illness insight in SZ.

Decreased cortical gyrification and surface area in the left medial parietal cortex in patients with treatment-resistant and ultratreatment-resistant schizophrenia

AIM

Validating the vulnerabilities and pathologies underlying treatment-resistant schizophrenia (TRS) is an important challenge in optimizing treatment. Gyrification and surface area (SA), reflecting neurodevelopmental features, have been linked to genetic vulnerability to schizophrenia. The aim of this study was to identify gyrification and SA abnormalities specific to TRS.

METHODS

We analyzed 3T magnetic resonance imaging findings of 24 healthy controls (HCs), 20 responders to first-line antipsychotics (FL-Resp), and 41 patients with TRS, including 19 clozapine responders (CLZ-Resp) and 22 FL- and clozapine-resistant patients (patients with ultratreatment-resistant schizophrenia [URS]). The local gyrification index (LGI) and associated SA were analyzed across groups. Diagnostic accuracy was verified by receiver operating characteristic curve analysis.

RESULTS

Both CLZ-Resp and URS had lower LGI values than HCs (P = 0.041, Hedges g [g_H ] = 0.75; P = 0.013, g_H  = 0.96) and FL-Resp (P = 0.007, g_H  = 1.00; P = 0.002, g_H  = 1.31) in the left medial parietal cortex (Lt-MPC). In addition, both CLZ-Resp and URS had lower SA in the Lt-MPC than FL-Resp (P < 0.001, g_H  = 1.22; P < 0.001, g_H  = 1.75). LGI and SA were positively correlated in non-TRS (FL-Resp) (ρ = 0.64, P = 0.008) and TRS (CLZ-Resp + URS) (ρ = 0.60, P < 0.001). The areas under the receiver operating characteristic curve for non-TRS versus TRS with LGI and SA in the Lt-MPC were 0.79 and 0.85, respectively. SA in the Lt-MPC was inversely correlated with negative symptoms (ρ = -0.40, P = 0.018) and clozapine plasma levels (ρ = -0.35, P = 0.042) in TRS.

CONCLUSION

LGI and SA in the Lt-MPC, a functional hub in the default-mode network, were abnormally reduced in TRS compared with non-TRS. Thus, altered LGI and SA in the Lt-MPC might be structural features associated with genetic vulnerability to TRS.

Delineating insight-processing-related functional activations in the precuneus in first-episode psychosis patients

Poor insight is a central characteristic of psychotic disorders, and it has been suggested to result from a general dysfunction in self-reflection. However, brain processing of clinical insight and more general self-reflection has not been directly compared. We compared tasks on (1) self-reflection on psychosis-related mental functioning (clinical insight, in patients only), (2) self-reflection on mental functioning unrelated to psychosis (general metacognition), and (3) semantic control during blood-oxygenation-level-dependent (BOLD) functional magnetic resonance imaging with 19 first-episode psychosis patients and 24 control participants. Arterial-spin-labeling (ASL) images were collected at rest. Clinical insight was evaluated with the Schedule for the Assessment of Insight. In patients, posterosuperior precuneus showed stronger activation during the insight task than during the semantic control task, while anteroinferior precuneus and posterior cingulate cortex (PCC) showed stronger activation during the insight task than during the general metacognition task. No significant group differences in brain activation emerged during the general metacognition task. Although the BOLD measures did not correlate with clinical insight measures, ASL-measured cerebral blood flow (CBF) values did correlate when extracted from the task-selective precuneus/PCC areas: higher CBF correlated with higher clinical insight scores. These results suggest that regions in the posteromedial cortex are selective for clinical insight.

Effects of Anosognosia on Static and Dynamic Amplitudes of Low-Frequency Fluctuation in Mild Cognitive Impairment

Background: Anosognosia is a significant symptom in patients with mild cognitive impairment (MCI) while the underlying neurological mechanism behind it is still unclear. Methods: A total of 121 subjects were included and classified into three groups, including 39 normal controls (NCs), 42 individuals with MCI without anosognosia (MCI-NA), and 40 individuals with MCI with anosognosia (MCI-A), based on their everyday cognition (ECog) questionnaire (discrepancy score). Resting-state functional MRIs were acquired from all the subjects, and the static amplitudes of low-frequency fluctuation (sALFF) and dynamic ALFF (dALFF) variance were investigated to evaluate the intrinsic functional network strength and stability, respectively, and both were corrected by age, sex, education, and gray matter volume. Eventually, correlation analyses were conducted to explore the relationship between brain activity changes and cognitive status in all the subjects. Results: No significant difference was found between MCI-A and MCI-NA (P > 0.05) in cognitive ability. Regarding intrinsic brain activity, MCI-A had increased sALFF and dALFF variance in the anterior cingulate cortex (ACC) relative to MCI-NA, as well as decreased sALFF and dALFF variance in the precuneus relative to MCI-NA and controls. Moreover, MCI-A had decreased sALFF in the inferior temporal gyrus (ITG) and paracentral lobule (PCL) compared to MCI-NA. Among all the subjects, correlation analyses showed that the sALFF and dALFF variance in the precuneus was related to the Ecog discrepancy score (r = 0.232 and 0.235, respectively), immediate story recall (r = 0.200 and 0.277, respectively), and delayed story recall (r = 0.255 and 0.298, respectively). Conclusion: Alterations of intrinsic brain activation in the ACC and precuneus seem to be associated with the anosognosia symptom in patients with MCI.

Aberrant Dynamic Functional Connectivity of Default Mode Network in Schizophrenia and Links to Symptom Severity

Background: Schizophrenia affects around 1% of the global population. Functional connectivity extracted from resting-state functional magnetic resonance imaging (rs-fMRI) has previously been used to study schizophrenia and has great potential to provide novel insights into the disorder. Some studies have shown abnormal functional connectivity in the default mode network (DMN) of individuals with schizophrenia, and more recent studies have shown abnormal dynamic functional connectivity (dFC) in individuals with schizophrenia. However, DMN dFC and the link between abnormal DMN dFC and symptom severity have not been well-characterized.

Method: Resting-state fMRI data from subjects with schizophrenia (SZ) and healthy controls (HC) across two datasets were analyzed independently. We captured seven maximally independent subnodes in the DMN by applying group independent component analysis and estimated dFC between subnode time courses using a sliding window approach. A clustering method separated the dFCs into five reoccurring brain states. A feature selection method modeled the difference between SZs and HCs using the state-specific FC features. Finally, we used the transition probability of a hidden Markov model to characterize the link between symptom severity and dFC in SZ subjects.

Results: We found decreases in the connectivity of the anterior cingulate cortex (ACC) and increases in the connectivity between the precuneus (PCu) and the posterior cingulate cortex (PCC) (i.e., PCu/PCC) of SZ subjects. In SZ, the transition probability from a state with weaker PCu/PCC and stronger ACC connectivity to a state with stronger PCu/PCC and weaker ACC connectivity increased with symptom severity.

Conclusions: To our knowledge, this was the first study to investigate DMN dFC and its link to schizophrenia symptom severity. We identified reproducible neural states in a data-driven manner and demonstrated that the strength of connectivity within those states differed between SZs and HCs. Additionally, we identified a relationship between SZ symptom severity and the dynamics of DMN functional connectivity. We validated our results across two datasets. These results support the potential of dFC for use as a biomarker of schizophrenia and shed new light upon the relationship between schizophrenia and DMN dynamics.

Gray Matter Volume and Functional Connectivity in Hypochondriasis: A Magnetic Resonance Imaging and Support Vector Machine Analysis

Objective: Patients with hypochondriasis hold unexplainable beliefs and a fear of having a lethal disease, with poor compliances and treatment response to psychotropic drugs. Although several studies have demonstrated that patients with hypochondriasis demonstrate abnormalities in brain structure and function, gray matter volume (GMV) and functional connectivity (FC) in hypochondriasis still remain unclear. Methods: The present study collected T1-weighted and resting-state functional magnetic resonance images from 21 hypochondriasis patients and 22 well-matched healthy controls (HCs). We first analyzed the difference in the GMV between the two groups. We then used the regions showing a difference in GMV between two groups as seeds to perform functional connectivity (FC) analysis. Finally, a support vector machine (SVM) was applied to the imaging data to distinguish hypochondriasis patients from HCs. Results: Compared with the HCs, the hypochondriasis group showed decreased GMV in the left precuneus, and increased GMV in the left medial frontal gyrus. FC analyses revealed decreased FC between the left medial frontal gyrus and cuneus, and between the left precuneus and cuneus. A combination of both GMV and FC in the left precuneus, medial frontal gyrus, and cuneus was able to discriminate the hypochondriasis patients from HCs with a sensitivity of 0.98, specificity of 0.93, and accuracy of 0.95. Conclusion: Our study suggests that smaller left precuneus volumes and decreased FC between the left precuneus and cuneus seem to play an important role of hypochondriasis. Future studies are needed to confirm whether this finding is generalizable to patients with hypochondriasis.

Predicting individual improvement in schizophrenia symptom severity at 1-year follow-up: Comparison of connectomic, structural, and clinical predictors

In a machine learning setting, this study aims to compare the prognostic utility of connectomic, brain structural, and clinical/demographic predictors of individual change in symptom severity in individuals with schizophrenia. Symptom severity at baseline and 1-year follow-up was assessed in 30 individuals with a schizophrenia-spectrum disorder using the Brief Psychiatric Rating Scale. Structural and functional neuroimaging was acquired in all individuals at baseline. Machine learning classifiers were trained to predict whether individuals improved or worsened with respect to positive, negative, and overall symptom severity. Classifiers were trained using various combinations of predictors, including regional cortical thickness and gray matter volume, static and dynamic resting-state connectivity, and/or baseline clinical and demographic variables. Relative change in overall symptom severity between baseline and 1-year follow-up varied markedly among individuals (interquartile range: 55%). Dynamic resting-state connectivity measured within the default-mode network was the most accurate single predictor of change in positive (accuracy: 87%), negative (83%), and overall symptom severity (77%) at follow-up. Incorporating predictors based on regional cortical thickness, gray matter volume, and baseline clinical variables did not markedly improve prediction accuracy and the prognostic utility of these predictors in isolation was moderate (<70%). Worsening negative symptoms at 1-year follow-up were predicted by hyper-connectivity and hypo-dynamism within the default-mode network at baseline assessment, while hypo-connectivity and hyper-dynamism predicted worsening positive symptoms. Given the modest sample size investigated, we recommend giving precedence to the relative ranking of the predictors investigated in this study, rather than the prediction accuracy estimates.

The 'Narcissus Effect': Top-down alpha-beta band modulation of face-related brain areas during self-face processing

Self-related information, such as one's own face, is prioritized by our cognitive system. Whilst recent theoretical developments suggest that this is achieved by an interplay between bottom-up and top-down attentional mechanisms, their underlying neural dynamics are still poorly understood. Furthermore, it is still matter of discussion as to whether these attentional mechanisms are truly self-specific or instead driven by face familiarity. To address these questions, we used EEG to record the brain activity of twenty-five healthy participants whilst identifying their own face, a friend's face and a stranger's face. Time-frequency analysis revealed a greater sustained power decrease in the alpha and beta frequency bands for the self-face, which emerged at late latencies and was maintained even when the face was no longer present. Critically, source analysis showed that this activity was generated in key brain regions for self-face recognition, such as the fusiform gyrus. As in the Myth of Narcissus, our results indicate that one's own face might have the potential to hijack attention. We suggest that this effect is specific to the self and driven by a top-down attentional control mechanism, which might facilitate further processing of personally relevant events.

Trait self-reflectiveness relates to time-varying dynamics of resting state functional connectivity and underlying structural connectomes: Role of the default mode network

BACKGROUND

Cognitive insight is defined as the ability to reflect upon oneself (i.e. self-reflectiveness), and to not be overly confident of one's own (incorrect) beliefs (i.e. self-certainty). These abilities are impaired in several disorders, while they are essential for the evaluation and regulation of one's behavior. We hypothesized that cognitive insight is a dynamic process, and therefore examined how it relates to temporal dynamics of resting state functional connectivity (FC) and underlying structural network characteristics in 58 healthy individuals.

METHODS

Cognitive insight was measured with the Beck Cognitive Insight Scale. FC characteristics were calculated after obtaining four FC states with leading eigenvector dynamics analysis. Gray matter (GM) and DTI connectomes were based on GM similarity and probabilistic tractography. Structural graph characteristics, such as path length, clustering coefficient, and small-world coefficient, were calculated with the Brain Connectivity Toolbox. FC and structural graph characteristics were correlated with cognitive insight.

RESULTS

Individuals with lower cognitive insight switched more and spent less time in a globally synchronized state. Additionally, individuals with lower self-reflectiveness spent more time in, had a higher probability of, and had a higher chance of switching to a state entailing default mode network (DMN) areas. With lower self-reflectiveness, DTI-connectomes were segregated less (i.e. lower global clustering coefficient) with lower embeddedness of the left angular gyrus specifically (i.e. lower local clustering coefficient).

CONCLUSIONS

Our results suggest less stable functional and structural networks in individuals with poorer cognitive insight, specifically self-reflectiveness. An overly present DMN appears to play a key role in poorer self-reflectiveness.

Intrinsic mesocorticolimbic connectivity is negatively associated with social amotivation in people with schizophrenia

BACKGROUND

Social amotivation is a core element of the negative symptoms of schizophrenia. However, it is still largely unknown which neural substrates underpin social amotivation in people with schizophrenia, though deficiencies in the mesocorticolimbic dopamine system have been proposed.

METHODS

We examined the association between social amotivation and substantia nigra/ventral tegmental area-seeded intrinsic connectivity in 84 people with schizophrenia using resting state functional magnetic resonance imaging.

RESULTS

Spontaneous fluctuations of midbrain dopaminergic regions were positively associated with striatal and prefrontal fluctuations in people with schizophrenia. Most importantly, social amotivation was negatively associated with functional connectivity between the midbrain's substantia nigra/ventral tegmental area and medial- and lateral prefrontal cortex, the temporoparietal junction, and dorsal and ventral striatum. These associations were observed independently of depressive and positive symptoms.

CONCLUSIONS

Our findings suggest that social amotivation in people with schizophrenia is associated with altered intrinsic connectivity of mesocorticolimbic pathways linked to cognitive control and reward processing. Dysconnectivity of dopaminergic neuronal ensembles that are fundamental to approach behavior and motivation may help explain the lack of initiative social behavior in people with social amotivation.

Distinct and opposite profiles of connectivity during self-reference task and rest in youth at clinical high risk for psychosis

Self-reference is impaired in psychotic disorders such as schizophrenia, associated with disability, and closely related to characteristic patterns of aberrant brain connectivity. However, at present, it is unclear whether self-reference is impacted in pathogenesis of the disorder. Alterations in connectivity during a self-reference task or resting-state in the psychosis risk (i.e., prodromal) period may yield important clues for biomarker development, as well as for novel treatment targets. This study examined a task-based and resting-state functional magnetic resonance imaging in individuals at clinical high risk (CHR) for psychosis (n = 22) and healthy control unaffected peers (n = 20). The self-reference task comprised three task conditions where subjects were asked if an adjective was relevant to themselves (self), a designated other individual (other), or to evaluate the word's spelling (letter). Connectivity analyses examined medial prefrontal cortex (mPFC) and posterior cingulate cortex (PCC), regions commonly found in conjunction analyses of self-reference, during both the self-reference task and rest. In task connectivity analyses, CHR individuals exhibited decreased mPFC-PCC connectivity when compared to controls. In resting-state analyses, CHR participants showed greater mPFC-PCC connectivity. Taken together, results suggest that psychosis-like alterations in mPFC-PCC connectivity is present prior to psychosis onset across both task and rest.

The right occipital lobe and poor insight in first-episode psychosis

Lack of insight is a core feature of non-affective psychosis and has been associated with poorer outcomes. Brain abnormalities underlying lack of insight have been suggested, mostly in the frontal lobe, although previous research showed mixed results. We used a voxel-based morphometry (VBM) analysis in 108 first-episode non-affective psychosis patients to investigate the pattern of brain structural abnormalities related to lack of insight. In addition, 77 healthy volunteers were compared with the patients classified as having poor and good insight. The shortened version of the Scale to Assess Unawareness of Mental Disorder was used to evaluate insight. Patients with poor insight (n = 68) compared with patients with good insight (n = 40) showed a single significant cluster (kc = 5834; PcFWE = 0.001) of reduced grey matter volume (GMV) in the right occipital lobe extending to its lateral and medial surfaces, the cuneus, and the middle temporal gyrus. In addition, GMV at this cluster showed a negative correlation with the score of the SUMD (r = -0.305; p = 0.001). When comparing patients with poor insight with healthy subjects overall reductions of GMV were found, mainly in frontal and occipital lobes. Hence, poor insight in non-affective psychosis seems to be associated with specific brain abnormalities in the right occipital and temporal cortical regions. Dysfunction in any combination of these areas may contribute to lack of insight in non-affective psychosis. Specifically, the 'right' hemisphere dysfunction underlying impaired insight in our sample is consistent with previously reported similarities between lack of insight in psychosis and anosognosia in neurological disorders.

Stronger default mode network connectivity is associated with poorer clinical insight in youth at ultra high-risk for psychotic disorders

Impaired clinical insight (CI) is a common symptom of psychotic disorders and a promising treatment target. However, to date, our understanding of how variability in CI is tied to underlying brain dysfunction in the clinical high-risk period is limited. Developing a stronger conception of this link will be a vital first step for efforts to determine if CI can serve as a useful prognostic indicator. The current study investigated whether variability in CI is related to major brain networks in adolescents and young adults at ultra high-risk (UHR) of developing psychosis. Thirty-five UHR youth were administered structured clinical interviews as well as an assessment for CI and underwent resting-state magnetic resonance imaging scans. Functional connectivity was calculated in the default mode network (DMN) and fronto-parietal network (FPN), two major networks that are dysfunctional in psychosis and are hypothesized to affect insight. Greater DMN connectivity between the posterior cingulate/precuneus and ventromedial prefrontal cortex (DMN) was related to poorer CI (R²=0.399). There were no significant relationships between insight and the FPN. This is the first study to relate a major brain network to clinical insight before the onset of psychosis. Findings are consistent with evidence if a hyperconnected DMN in schizophrenia and UHR, and similar to a previous study of insight and connectivity in schizophrenia. Results suggest that a strongly connected DMN may be related to poor self-awareness of subthreshold psychotic symptoms in UHR adolescents and young adults.

Neurobiological Basis of Insight in Schizophrenia: A Systematic Review

BACKGROUND

Insight in schizophrenia is defined as awareness into illness, symptoms, and need for treatment and has long been associated with cognition, other psychopathological symptoms, and several adverse clinical and functional outcomes. However, the biological basis of insight is not clearly understood.

OBJECTIVE

The aim of this systematic review was to critically evaluate and summarize advances in the study of the biological basis of insight in schizophrenia and to identify gaps in this knowledge.

METHODS

A literature search of PubMed, CINAHL, PsycINFO, and EMBASE databases was conducted using search terms to identify articles relevant to the biology of insight in schizophrenia published in the last 6 years. Articles that focused on etiology of insight in schizophrenia and those that examined the neurobiology of insight in schizophrenia or psychoses were chosen for analysis. Articles on insight in conditions other than schizophrenia or psychoses and which did not investigate the neurobiological underpinnings of insight were excluded from the review.

RESULTS

Twenty-six articles met the inclusion criteria for this review. Of the 26 articles, 3 focused on cellular abnormalities and 23 were neuroimaging studies. Preliminary data identify the prefrontal cortex, cingulate cortex, and regions of the temporal and parietal lobe (precuneus, inferior parietal lobule) and hippocampus as the neural correlates of insight.

DISCUSSION

A growing body of literature attests to the neurobiological basis of insight in schizophrenia. Current evidence supports the neurobiological basis of insight in schizophrenia and identifies specific neural correlates for insight types and its dimensions. Further studies that examine the precise biological mechanisms of insight are needed to apply this knowledge to effective clinical intervention development.

Association of medial prefrontal resting state functional connectivity and metacognitive capacity in early phase psychosis

Metacognition refers to a range of cognitive processes that allow one to form complex ideas of self and others and to use this information to navigate psychosocial challenges. Several studies in both early-phase and prolonged schizophrenia have demonstrated not only that significant deficits in metacognitive ability are present, but importantly that they are associated with significant functional impairment and decreased quality of life. In spite of the importance of metacognitive impairment in schizophrenia, relatively little is known about the biological substrates that may contribute to this dysfunction. In this study, we examined the relationship between resting state functional connectivity of the medial prefrontal cortex (mPFC), a structure shown in prior voxel-based morphometry studies to be associated with metacognition, with metacognitive function in an early-phase psychosis cohort (n=18). Analyses revealed a positive association of resting state functional connectivity between the mPFC and precuneus and posterior cingulate structures and metacognitive ability. These results provide evidence of disrupted resting state connectivity in structures relevant to metacognitive dysfunction in early-phase psychosis, which may have implications for pathophysiological models of complex cognitive deficits in this illness.

Default mode functional connectivity is associated with social functioning in schizophrenia

Individuals with schizophrenia display notable deficits in social functioning. Research indicates that neural connectivity within the default mode network (DMN) is related to social cognition and social functioning in healthy and clinical populations. However, the association between DMN connectivity, social cognition, and social functioning has not been studied in schizophrenia. For the present study, the authors used resting-state neuroimaging data to evaluate connectivity between the main DMN hubs (i.e., the medial prefrontal cortex [mPFC] and the posterior cingulate cortex-anterior precuneus [PPC]) in individuals with schizophrenia (n = 28) and controls (n = 32). The authors also examined whether DMN connectivity was associated with social functioning via social attainment (measured by the Specific Levels of Functioning Scale) and social competence (measured by the Social Skills Performance Assessment), and if social cognition mediates the association between DMN connectivity and these measures of social functioning. Results revealed that DMN connectivity did not differ between individuals with schizophrenia and controls. However, connectivity between the mPFC and PCC hubs was significantly associated with social competence and social attainment in individuals with schizophrenia but not in controls as reflected by a significant group-by-connectivity interaction. Social cognition did not mediate the association between DMN connectivity and social functioning in individuals with schizophrenia. The findings suggest that fronto-parietal DMN connectivity in particular may be differentially associated with social functioning in schizophrenia and controls. As a result, DMN connectivity may be used as a neuroimaging marker to monitor treatment response or as a potential target for interventions that aim to enhance social functioning in schizophrenia. (PsycINFO Database Record

Association between prefrontal N-acetylaspartate and insight in psychotic disorders

Insight is impaired in most patients with psychosis and has been associated with poorer prognosis. The exact neural basis of impaired insight is still unknown, but it may involve disrupted prefrontal neural connectivity. Numerous studies have indeed found white matter (WM) abnormalities in psychosis. The association between prefrontal WM abnormalities and insight has not been studied yet by means of proton magnetic resonance spectroscopy (¹H-MRS). ¹H-MRS can be used to measure N-acetylaspartate (NAA), which is considered to be a marker of neuronal integrity. We measured insight with the Birchwood Insight Scale (BIS) as well as item G12 of the Positive and Negative Syndrome Scale (PANSS) in 88 patients with psychosis. Prefrontal WM concentrations of NAA and ratios of NAA to creatine (Cr) were assessed with ¹H-MRS. Nonparametric partial correlational analyses were conducted between NAA concentrations and insight controlling for illness duration, standardized antipsychotic dose, symptom scores, voxel grey matter content and voxel cerebrospinal fluid content. We found a significant correlation between reduced NAA/Cr ratios and poorer insight as measured with the BIS, which remained significant after additional correction for full width at half maximum, signal/noise and age. This is the first study reporting a relationship between lower prefrontal concentrations of a marker of neuronal integrity and impaired insight, providing further evidence that prefrontal pathology may play an important role in impaired insight in psychosis. This may be explained by the involvement of the prefrontal cortex in several executive and metacognitive functions, such as cognitive flexibility and perspective taking.

Resting-state functional connectivity changes within the default mode network and the salience network after antipsychotic treatment in early-phase schizophrenia

OBJECTIVE

Abnormal resting-state functional connectivity (FC), particularly in the default mode network (DMN) and the salience network (SN), has been reported in schizophrenia, but little is known about the effects of antipsychotics on these networks. The purpose of this study was to examine the effects of atypical antipsychotics on DMN and SN and the relationship between these effects and symptom improvement in patients with schizophrenia.

METHODS

This was a prospective study of 33 patients diagnosed with schizophrenia and treated with antipsychotics at Shanghai Mental Health Center. Thirty-three healthy controls matched for age and gender were recruited. All subjects underwent functional magnetic resonance imaging (fMRI). Healthy controls were scanned only once; patients were scanned before and after 6-8 weeks of treatment.

RESULTS

In the DMN, the patients exhibited increased FC after treatment in the right superior temporal gyrus, right medial frontal gyrus, and left superior frontal gyrus and decreased FC in the right posterior cingulate/precuneus (P<0.005). In the SN, the patients exhibited decreased FC in the right cerebellum anterior lobe and left insula (P<0.005). The FC in the right posterior cingulate/precuneus in the DMN negatively correlated with the difference between the Clinical Global Impression (CGI) score pre/post-treatment (r=-0.564, P=0.023) and negative trends with the difference in the Positive and Negative Syndrome Scale (PANSS) total score pre/post-treatment (r=-0.475, P=0.063) and the difference in PANSS-positive symptom scores (r=-0.481, P=0.060).

CONCLUSION

These findings suggest that atypical antipsychotics could regulate the FC of certain key brain regions within the DMN in early-phase schizophrenia, which might be related to symptom improvement. However, the effects of atypical antipsychotics on SN are less clear.

A Review of the Functional and Anatomical Default Mode Network in Schizophrenia

Schizophrenia is a severe mental disorder characterized by impaired perception, delusions, thought disorder, abnormal emotion regulation, altered motor function, and impaired drive. The default mode network (DMN), since it was first proposed in 2001, has become a central research theme in neuropsychiatric disorders, including schizophrenia. In this review, first we define the DMN and describe its functional activity, functional and anatomical connectivity, heritability, and inverse correlation with the task positive network. Second, we review empirical studies of the anatomical and functional DMN, and anti-correlation between DMN and the task positive network in schizophrenia. Finally, we review preliminary evidence about the relationship between antipsychotic medications and regulation of the DMN, review the role of DMN as a treatment biomarker for this disease, and consider the DMN effects of individualized therapies for schizophrenia.

The fragmented self: imbalance between intrinsic and extrinsic self-networks in psychotic disorders

Self-disturbances are among the core features of schizophrenia and related psychotic disorders. The basic structure of the self could depend on the balance between intrinsic and extrinsic self-processing. We discuss studies on self-related processing in psychotic disorders that provide converging evidence for disrupted communication between neural networks subserving the so-called intrinsic self and extrinsic self. This disruption might be mainly caused by impaired integrity of key brain hubs. The intrinsic self has been associated with cortical midline structures involved in self-referential processing, autobiographical memory, and emotional evaluation. Additionally, we highlight central aspects of the extrinsic self in its interaction with the environment using sensorimotor networks, including self-experience in sensation and actions. A deficient relationship between these self-aspects because of disrupted between-network interactions offers a framework to explain core clinical features of psychotic disorders. In particular, we show how relative isolation and reduced modularity of networks subserving intrinsic and extrinsic self-processing might trigger the emergence of hallucinations and delusions, and why patients with psychosis typically have difficulties with self-other relationships and do not recognise mental problems.

Altered Neural Correlate of the Self-Agency Experience in First-Episode Schizophrenia-Spectrum Patients: An fMRI Study

BACKGROUND

The phenomenology of the clinical symptoms indicates that disturbance of the sense of self be a core marker of schizophrenia.

AIMS

To compare neural activity related to the self/other-agency judgment in patients with first-episode schizophrenia-spectrum disorders (FES, n = 35) and healthy controls (HC, n = 35).

METHOD

A functional magnetic resonance imaging (fMRI) using motor task with temporal distortion of the visual feedback was employed. A task-related functional connectivity was analyzed with the use of independent component analysis (ICA).

RESULTS

(1) During self-agency experience, FES showed a deficit in cortical activation in medial frontal gyrus (BA 10) and posterior cingulate gyrus, (BA 31; P < .05, Family-Wise Error [FWE] corrected). (2) Pooled-sample task-related ICA revealed that the self/other-agency judgment was dependent upon anti-correlated default mode and central-executive networks (DMN/CEN) dynamic switching. This antagonistic mechanism was substantially impaired in FES during the task.

DISCUSSION

During self-agency experience, FES demonstrate deficit in engagement of cortical midline structures along with substantial attenuation of anti-correlated DMN/CEN activity underlying normal self/other-agency discriminative processes.

An integrative model of the impairments in insight in schizophrenia: emerging research on causal factors and treatments

INTRODUCTION

Poor insight, or unawareness of some major aspect of mental illness, is a major barrier to wellness when it interferes with persons seeking out treatment or forming their own understanding of the challenges they face. One barrier to addressing impaired insight is the absence of a comprehensive model of how poor insight develops.

AREAS COVERED

To explore this issue we review how poor insight is the result of multiple phenomena which interfere with the construction of narrative accounts of psychiatric challenges, rather than a single social or biological cause. Expert commentary: We propose an integrative model of poor insight in schizophrenia which involves the interaction of symptoms, deficits in neurocognition, social cognition, metacognition, and stigma. Emerging treatments for poor insight including therapies which focus on the development of metacognition are discussed.

Insight and psychosis: Functional and anatomical brain connectivity and self-reflection in Schizophrenia

Impaired insight into illness, associated with worse treatment outcome, is common in schizophrenia. Insight has been related to the self-reflective processing, centred on the medial frontal cortex. We hypothesized that anatomical and functional routes to and from the ventromedial prefrontal cortex (vmPFC) would differ in patients according to their degree of impaired insight. Forty-five schizophrenia patients and 19 healthy subjects performed a self-reflection task during fMRI, and underwent diffusion tensor imaging. Using dynamic causal modelling we observed increased effective connectivity from the posterior cingulate cortex (PCC), inferior parietal lobule (IPL), and dorsal mPFC (dmPFC) towards the vmPFC with poorer insight and decrease from vmPFC to the IPL. Stronger connectivity from the PCC to vmPFC during judgment of traits related to self was associated with poorer insight. We found small-scale significant changes in white matter integrity associated with clinical insight. Self-reflection may be influenced by synaptic changes that lead to the observed alterations in functional connectivity accompanied by the small-scale but measurable alterations in anatomical connections. Our findings may point to a neural compensatory response to an impairment of connectivity between self-processing regions. Similarly, the observed hyper-connectivity might be a primary deficit linked to inefficiency in the component cognitive processes that lead to impaired insight. We suggest that the stronger cognitive demands placed on patients with poor insight is reflected in increased effective connectivity during the task in this study.

Distinct neural correlates for attention lapses in patients with schizophrenia and healthy participants

Momentary lapses in attention are common in healthy populations. This phenomenon has recently received increased investigation, particularly in relationship to the default mode network (DMN). Previous research has suggested that these lapses may be due to intrusive task-irrelevant thoughts. The study of this phenomenon in schizophrenia, which is characterized by a wide variety of cognitive deficits including deficits in attention, has not previously been explored. We used the AX Continuous Performance Task to investigate attention lapses in healthy participants as well as patients with schizophrenia. We found distinct patterns of network activation between these two groups. Lapses in healthy participants were associated with DMN activation, while in patients, the same behavioral phenomenon was associated with deactivations in frontal-parietal control network (FPCN) regions. When considered in contrast to the results observed in healthy participants, these results suggest an additional origin of attention lapses in patients derived from a loss of task-related context, rather than intrusive task-irrelevant thoughts.

Insight of patients and their parents into schizophrenia: Exploring agreement and the influence of parental factors

Poor insight is found in up to 80% of schizophrenia patients and has been associated with multiple factors of which cognitive functioning, social and environmental factors. Few studies have explored associations between patient insight and that of their biological parents', and the influence of parental factors. Insight was assessed in 41 patients and their biological parents with Amador's Scale for the assessment of Unawareness of Mental Disorder (SUMD). Parents' knowledge about schizophrenia and critical attitudes were assessed with validated self-report questionnaires. Both groups underwent cognitive assessments for working memory and executive functioning. Insight in patients and their parents was not associated for any of the SUMD dimensions but a significant correlation was found between patient and parent awareness of treatment effect for patient-parent dyads with frequent daily contact. Low parental critical attitude was associated with higher patient awareness of symptoms and a high parental memory task score with high patient insight. Our study is the first to suggest a possible influence of parental factors such as critical attitudes and cognitive performance on patient insight.

Neurobiology of insight deficits in schizophrenia: An fMRI study

Prior research has shown insight deficits in schizophrenia to be associated with specific neuroimaging changes (primarily structural) especially in the prefrontal sub-regions. However, little is known about the functional correlates of impaired insight. Seventeen patients with schizophrenia (mean age 40.0±10.3; M/F=14/3) underwent fMRI on a Philips 3.0 T Achieva system while performing on a self-awareness task containing self- vs. other-directed sentence stimuli. SPM5 was used to process the imaging data. Preprocessing consisted of realignment, coregistration, and normalization, and smoothing. A regression analysis was used to examine the relationship between brain activation in response to self-directed versus other-directed sentence stimuli and average scores on behavioral measures of awareness of symptoms and attribution of symptoms to the illness from Scale to Assess Unawareness of Mental Disorders. Family Wise Error correction was employed in the fMRI analysis. Average scores on awareness of symptoms (1=aware; 5=unaware) were associated with activation of multiple brain regions, including prefrontal, parietal and limbic areas as well as basal ganglia. However, average scores on correct attribution of symptoms (1=attribute; 5=misattribute) were associated with relatively more localized activation of prefrontal cortex and basal ganglia. These findings suggest that unawareness and misattribution of symptoms may have different neurobiological basis in schizophrenia. While symptom unawareness may be a function of a more complex brain network, symptom misattribution may be mediated by specific brain regions.

ZNF804A rs1344706 is associated with cortical thickness, surface area, and cortical volume of the unmedicated first episode schizophrenia and healthy controls

The effects of ZNF804A rs1344706, a prominent susceptibility gene for schizophrenia, on gray matter (GM) structure in unmedicated schizophrenia (SZ) patients are still unknown, although several previous studies investigated the effects in medicated SZ patients and healthy controls (HC). Analyzing cortical thickness, surface area, and GM volume simultaneously may provide a more precise and complete picture of the effects. We genotyped 59 unmedicated first episode SZ patients and 60 healthy controls for the ZNF804A single nucleotide polymorphism (SNP) rs1344706, and examined between-group differences in cortical thickness, surface area, and cortical volume using a full-factorial 2 × 2 analysis of variance (ANOVA). We found the risk allele (T) in ZNF804A rs1344706, compared to the non-risk allele (G), was associated with thinner cortex in the bilateral precuneus, left precentral gyrus, and several other regions, associated with a smaller cortical surface area in the left superior parietal, precuneus cortex and left superior frontal, and associated with a lower cortical volume in the left superior frontal, left precentral, and right precuneus in SZ patients. In contrast, in the controls, the T allele was associated with the increased cortical measurements compared to the G allele in the same regions as those mentioned above. ZNF804A rs1344706 has significant, but different, effects on cortical thickness, surface area, and cortical volume in multiple regions of the brain cortex. Our findings suggest that ZNF804A rs1344706 may aggravate the risk for schizophrenia by exerting its effects on cortical thickness, surface area, and cortical volume in these brain regions.

Denial in methamphetamine users: Associations with cognition and functional connectivity in brain

BACKGROUND

Despite harmful consequences of drug addiction, it is common for individuals with substance use disorders to deny having problems with drugs. Emerging evidence suggests that some drug users lack insight into their behavior due to neurocognitive dysfunction, but little research has examined potential neurocognitive contributions to denial.

METHODS

This study explored the relationship between denial, cognitive performance and functional connectivity in brain. The participants were 58 non-treatment-seeking, methamphetamine-dependent participants who completed the URICA precontemplation scale, a self-report measure of denial of drug problems warranting change, as well as a cognitive test battery. A subset of participants (N = 21) had functional MRI scans assessing resting-state functional connectivity. Given literature indicating roles of the rostral anterior cingulate (rACC), anterior insula and precuneus in self-awareness, relationships between denial and resting-state connectivity were tested using seeds placed in these regions.

RESULTS

The results revealed a negative relationship between denial and an overall cognitive battery score (p = 0.001), the effect being driven particularly by performance on tests of memory and executive function. Denial was negatively associated with strength of connectivity between the rACC and regions of the frontal lobe (precentral gyri, left ventromedial prefrontal cortex, left orbitofrontal cortex), limbic system (left amygdala, left hippocampus and left parahippocampal gyrus), occipital lobes and cerebellum; and between the precuneus and the midbrain and cerebellum. Anterior insula connectivity was unrelated to denial.

CONCLUSIONS

These findings suggest that denial by methamphetamine users is linked with a cognitive and neural phenotype that may impede the development of insight into their behavior.

Impaired insight into illness and cognitive insight in schizophrenia spectrum disorders: resting state functional connectivity

BACKGROUND

Impaired insight into illness (clinical insight) in schizophrenia has negative effects on treatment adherence and clinical outcomes. Schizophrenia is described as a disorder of disrupted brain connectivity. In line with this concept, resting state networks (RSNs) appear differentially affected in persons with schizophrenia. Therefore, impaired clinical, or the related construct of cognitive insight (which posits that impaired clinical insight is a function of metacognitive deficits), may reflect alterations in RSN functional connectivity (fc). Based on our previous research, which showed that impaired insight into illness was associated with increased left hemisphere volume relative to right, we hypothesized that impaired clinical insight would be associated with increased connectivity in the DMN with specific left hemisphere brain regions.

METHODS

Resting state MRI scans were acquired for participants with schizophrenia or schizoaffective disorder (n=20). Seed-to-voxel and ROI-to-ROI fc analyses were performed using the CONN-fMRI fc toolbox v13 for established RSNs. Clinical and cognitive insight were measured with the Schedule for the Assessment of Insight-Expanded Version and Beck Cognitive Insight Scale, respectively, and included as the regressors in fc analyses.

RESULTS

As hypothesized, impaired clinical insight was associated with increased connectivity in the default mode network (DMN) with the left angular gyrus, and also in the self-referential network (SRN) with the left insula. Cognitive insight was associated with increased connectivity in the dorsal attention network (DAN) with the right inferior frontal cortex (IFC) and left anterior cingulate cortex (ACC).

CONCLUSION

Increased connectivity in DMN and SRN with the left angular gyrus and insula, respectively, may represent neural correlates of impaired clinical insight in schizophrenia spectrum disorders, and is consistent with the literature attributing impaired insight to left hemisphere dominance. Increased connectivity in the DAN with the IFC and ACC in relation to cognitive insight may facilitate enhanced mental flexibility in this sample.

The neuropsychology of self-reflection in psychiatric illness

The development of robust neuropsychological measures of social and affective function-which link critical dimensions of mental health to their underlying neural circuitry-could be a key step in achieving a more pathophysiologically-based approach to psychiatric medicine. In this article, we summarize research indicating that self-reflection (the inward attention to personal thoughts, memories, feelings, and actions) may be a useful model for developing such a paradigm, as there is evidence that self-reflection is (1) measurable with self-report scales and performance-based tests, (2) linked to the activity of a specific neural circuit, and (3) dimensionally related to mental health and various forms of psychopathology.

Neural correlates of insight in dreaming and psychosis

The idea that dreaming can serve as a model for psychosis has a long and honourable tradition, however it is notoriously speculative. Here we demonstrate that recent research on the phenomenon of lucid dreaming sheds new light on the debate. Lucid dreaming is a rare state of sleep in which the dreamer gains insight into his state of mind during dreaming. Recent electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) data for the first time allow very specific hypotheses about the dream-psychosis relationship: if dreaming is a reasonable model for psychosis, then insight into the dreaming state and insight into the psychotic state should share similar neural correlates. This indeed seems to be the case: cortical areas activated during lucid dreaming show striking overlap with brain regions that are impaired in psychotic patients who lack insight into their pathological state. This parallel allows for new therapeutic approaches and ways to test antipsychotic medication.

The relationship between default mode network connectivity and social functioning in individuals at familial high-risk for schizophrenia

Unaffected first-degree relatives of individuals with schizophrenia (i.e., those at familial high-risk [FHR]), demonstrate social dysfunction qualitatively similar though less severe than that of their affected relatives. These social difficulties may be the consequence of genetically conferred disruption to aspects of the default mode network (DMN), such as the dMPFC subsystem, which overlaps with the network of brain regions recruited during social cognitive processes. In the present study, we investigate this possibility, testing DMN connectivity and its relationship to social functioning in FHR using resting-state fMRI. Twenty FHR individuals and 17 controls underwent fMRI during a resting-state scan. Hypothesis-driven functional connectivity analyses examined ROI-to-ROI correlations between the DMN's hubs, and regions of the dMPFC subsystem and MTL subsystem. Connectivity values were examined in relationship to a measure of social functioning and empathy/perspective-taking. Results demonstrate that FHR exhibit reduced connectivity specifically within the dMPFC subsystem of the DMN. Certain ROI-to-ROI correlations predicted aspects of social functioning and empathy/perspective-taking across all participants. Together, the data indicate that disruption to the dMPFC subsystem of the DMN may be associated with familial risk for schizophrenia, and that these intrinsic connections may carry measurable consequences for social functioning.

[Brain activitivation of euthymic patients with Type I bipolar disorder in resting state Default Mode Network]

INTRODUCTION

As there are still doubts about brain connectivity in type I bipolar disorder (BID), resting-state functional magnetic resonance imaging (RS-fMRI) studies are necessary during euthymia for a better control of confounding factors.

OBJECTIVE

To evaluate the differences in brain activation between euthymic BID patients and control subjects using resting state- functional-magnetic resonance imaging (RS-fMRI), and to identify the lithium effect in these activations.

METHODS

A cross-sectional study was conducted on 21 BID patients (10 receiving lithium only, and 11 non-medicated) and 12 healthy control subjects, using RS fMRI and independent component analysis (ICA).

RESULTS

Increased activation was found in the right hippocampus (P=.049) and posterior cingulate (P=.040) within the Default Mode Network (DMN) when BID and control group were compared. No statistically significant differences were identified between BID on lithium only therapy and non-medicated BID patients.

CONCLUSIONS

The results suggest that there are changes in brain activation and connectivity in BID even during euthymic phase and mainly within the DMN network, which could be relevant in affect regulation.

Anosognosia in schizophrenia: hidden in plain sight

OBJECTIVE

Poor insight is a cardinal symptom of schizophrenia that, while not universally and uniformly expressed in all patients, is among the most common of its manifestations. Available neurobiological and neurocognitive evidence linking the phenomenon to core pathophysiology of schizophrenia justifies extension of the anosognosia construct to schizophrenia-related insight deficits. Poor insight is a core attribute of schizophrenia, occurring in 57 to 98 percent of patients. Insight is an important outcome predictor, associated with treatment adherence, relapse frequency, symptom remission, psychosocial functioning, vocational attainment, and risk of violence toward self or others. Combined findings lend urgency to the importance of reducing psychotic relapse. This can only be achieved in the majority of patients with consistent medication adherence- something that is often exceedingly difficult in patients lacking belief in the fact of their illness. This article examines whether anosognosia, the unawareness of deficit or illness, should apply to our understanding of insight deficits in patients with schizophrenia. Although research in the field is limited at this time, there is hope that anosognosia as a symptom of schizophrenia will become a focus of further research and a critically important therapeutic target amenable to treatment.

DESIGN

This article is a literature review and conceptualization.

CONCLUSION

Limited research in the field gives cause for hope that anosognosia as a symptom of schizophrenia will become a critically important therapeutic target that is amendable to treatment.

The structural neuroanatomy of metacognitive insight in schizophrenia and its psychopathological and neuropsychological correlates

Lack of insight into illness is a multidimensional phenomenon that has relevant implications on clinical course and therapy compliance. Here, we focused on metacognitive insight in schizophrenia, that is, the ability to monitor one's changes in state of mind and sensations, with the aim of investigating its neuroanatomical, psychopathological, and neuropsychological correlates. Fifty-seven consecutive patients with Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition, Text Revision) diagnosis of schizophrenia were administered the Insight Scale, and comprehensive psychopathological and neuropsychological batteries. They underwent a high-resolution T1-weighted magnetic resonance imaging investigation. Gray matter (GM) and white matter (WM) volumes were analyzed on a voxel-by-voxel basis using Statistical Parametric Mapping 8. Reduced metacognitive insight was related to reduced GM volumes in the left ventrolateral prefrontal cortex, right dorsolateral prefrontal cortex and insula, and bilateral premotor area and putamen. Further, it was related to reduced WM volumes of the right superior longitudinal fasciculum, left corona radiata, left forceps minor, and bilateral cingulum. Increased metacognitive insight was related to increased depression severity and attentional control impairment, while the latter was related to increased GM volumes in brain areas linked to metacognitive insight. Results of this study suggest that prefrontal GM and WM bundles, all implied in cognitive control and self-reflection, may be the neuroanatomical correlates of metacognitive insight in schizophrenia. Further, higher metacognitive insight is hypothesized to be a risk factor for depression which may subsequently impair attention. This line of research may provide the basis for the development of cognitive interventions aimed at improving self-monitoring and compliance to treatment.

Poor insight into schizophrenia: contributing factors, consequences and emerging treatment approaches

Poor insight or unawareness of illness has been commonly observed in schizophrenia and has been long recognized as a potent barrier to treatment adherence and a risk factor for a range of poorer outcomes. Paradoxically, the achievement of insight often poses a different set of problems including depression and low self-esteem. One barrier to the treatment of poor insight has been a lack of understanding of the phenomenon, which causes poor insight to develop and persist over time. Without knowing what promotes poor insight, treatment to date has had little to offer beyond the supportive provision of information. To explore these issues, this article reviews emerging literature on the correlates of poor insight in schizophrenia, and newly developing ways of conceptualizing insight. It then details a number of innovative integrative group and individual treatment approaches in the early stages of development, which take into account some of the potential causal forces behind poor insight, including deficits in neurocognition, social cognition, metacognition and heightened self-stigma. A plan for further research is presented to develop a model of the factors whose interaction influences insight, and to refine and test integrative treatments.

Normal brain activation in schizophrenia patients during associative emotional learning

Emotional deficits are among the core features of schizophrenia and both associative emotional learning and the related ability to verbalize emotions can be reduced. We investigated whether schizophrenia patients demonstrated impaired function of limbic and prefrontal areas during associative emotional learning. Patients and controls filled out an alexithymia questionnaire and performed an associative emotional learning task with positive, negative and neutral picture-word pairs during fMRI scanning. After scanning, they indicated for each pair whether they remembered it. We conducted standard GLM analysis and Independent Component Analysis (ICA). Both the GLM results and task-related ICA components were compared between groups. The alexithymia questionnaire indicated more cognitive-emotional processing difficulties in patients than controls, but equal experienced intensity of affective states. Patients remembered less picture-word pairs, irrespective of valence. GLM analysis showed significant visual, temporal, amygdalar/hippocampal, and prefrontal activation in all subjects. ICA identified a network of brain areas similar to GLM, mainly in response to negative stimuli. Neither analysis showed differences between patients and controls during learning. Although in previous studies schizophrenia patients showed abnormalities in both memory and emotion processing, neural circuits involved in cross-modal associative emotional learning may remain intact to a certain degree, which may have potential consequences for treatment.

Aberrant default mode functional connectivity in early onset schizophrenia

Background

The default mode network (DMN) has been linked to a number of mental disorders including schizophrenia. However, the abnormal connectivity of DMN in early onset schizophrenia (EOS) has been rarely reported.

Methods

Independent component analysis (ICA) was used to investigate functional connectivity (FC) of the DMN in 32 first-episode adolescents with EOS and 32 age and gender-matched healthy controls.

Results

Compared to healthy controls, patients with EOS showed increased FC between the medial frontal gyrus and other areas of the DMN. Partial correlation analyses showed that the FC of medial frontal gyrus significantly correlated with PANSS-positive symptoms (partial correlation coefficient  = 0.538, Bonferoni corrected P = 0.018).

Limitations

Although the sample size of participants was comparable with most fMRI studies to date, it was still relatively small. Pediatric brains were registered to the MNI adult brain template. However, possible age-specific differences in spatial normalization that arise from registering pediatric brains to the MNI adult brain template may have little effect on fMRI results.

Conclusion

This study provides evidence for functional abnormalities of DMN in first-episode EOS. These abnormalities could be a source of abnormal introspectively-oriented mental actives.

Functional connectivity-based parcellation of amygdala using self-organized mapping: a data driven approach

The overall goal of this work is to demonstrate how resting state functional magnetic resonance imaging (fMRI) signals may be used to objectively parcellate functionally heterogeneous subregions of the human amygdala into structures characterized by similar patterns of functional connectivity. We hypothesize that similarity of functional connectivity of subregions with other parts of the brain can be a potential basis to segment and cluster voxels using data driven approaches. In this work, self-organizing map (SOM) was implemented to cluster the connectivity maps associated with each voxel of the human amygdala, thereby defining distinct subregions. The functional separation was optimized by evaluating the overall differences in functional connectivity between the subregions at group level. Analysis of 25 resting state fMRI data sets suggests that SOM can successfully identify functionally independent nuclei based on differences in their inter subregional functional connectivity, evaluated statistically at various confidence levels. Although amygdala contains several nuclei whose distinct roles are implicated in various functions, our objective approach discerns at least two functionally distinct volumes comparable to previous parcellation results obtained using probabilistic tractography and cytoarchitectonic analysis. Association of these nuclei with various known functions and a quantitative evaluation of their differences in overall functional connectivity with lateral orbital frontal cortex and temporal pole confirms the functional diversity of amygdala. The data driven approach adopted here may be used as a powerful indicator of structure-function relationships in the amygdala and other functionally heterogeneous structures as well.

Genetic strategies to investigate neuronal circuit properties using stem cell-derived neurons

The mammalian brain is anatomically and functionally complex, and prone to diverse forms of injury and neuropathology. Scientists have long strived to develop cell replacement therapies to repair damaged and diseased nervous tissue. However, this goal has remained unrealized for various reasons, including nascent knowledge of neuronal development, the inability to track and manipulate transplanted cells within complex neuronal networks, and host graft rejection. Recent advances in embryonic stem cell (ESC) and induced pluripotent stem cell (iPSC) technology, alongside novel genetic strategies to mark and manipulate stem cell-derived neurons, now provide unprecedented opportunities to investigate complex neuronal circuits in both healthy and diseased brains. Here, we review current technologies aimed at generating and manipulating neurons derived from ESCs and iPSCs toward investigation and manipulation of complex neuronal circuits, ultimately leading to the design and development of novel cell-based therapeutic approaches.