Reduced anterior cingulate cognitive activation is associated with prefrontal-temporal cortical thinning in schizophrenia

Localized alterations in cortical thickness and sulcal depth of the cingulo-opercular network in relation to lower reading fluency skills in children with dyslexia

The traditional models of reading development describe how language processing and word decoding contribute to reading comprehension and how impairments in word decoding, a defining feature of dyslexia, affect reading comprehension outcomes. However, these models do not include word and sentence reading (contextual reading) fluency, both of which engage executive functions, with notably decreased performance in children with dyslexia. In the current study, we compared cortical thickness and sulcal depth (CT/SD) in the cingulo-opercular (CO) executive functions brain network in children with dyslexia and typical readers and examined associations with word vs. contextual reading fluency. Overall, CT was lower in insular regions and higher in parietal and caudal anterior cingulate cortex regions in children with dyslexia. Children with dyslexia showed positive correlations between word reading fluency and CT/SD in insular regions, whereas no significant correlations were observed in typical readers. For sentence reading fluency, negative correlations with CT/SD were found in insular regions in children with dyslexia, while positive correlations with SD were found in insular regions in typical readers. These results demonstrate the differential relations between word and sentence reading fluency and anatomical circuitry supporting executive functions in children with dyslexia vs. typical readers. It also suggests that word and sentence reading fluency, relate to morphology of executive function-related regions in children with dyslexia, whereas in typical readers, only sentence reading fluency relates to morphology of executive function regions. The results also highlight the role of the insula within the CO network in reading fluency. Here we suggest that word and sentence reading fluency are distinct components of reading that should each be included in the Simple View of Reading traditional model.

Anatomically compliant modes of variations: New tools for brain connectivity

Anatomical complexity and data dimensionality present major issues when analysing brain connectivity data. The functional and anatomical aspects of the connections taking place in the brain are in fact equally relevant and strongly intertwined. However, due to theoretical challenges and computational issues, their relationship is often overlooked in neuroscience and clinical research. In this work, we propose to tackle this problem through Smooth Functional Principal Component Analysis, which enables to perform dimensional reduction and exploration of the variability in functional connectivity maps, complying with the formidably complicated anatomy of the grey matter volume. In particular, we analyse a population that includes controls and subjects affected by schizophrenia, starting from fMRI data acquired at rest and during a task-switching paradigm. For both sessions, we first identify the common modes of variation in the entire population. We hence explore whether the subjects' expressions along these common modes of variation differ between controls and pathological subjects. In each session, we find principal components that are significantly differently expressed in the healthy vs pathological subjects (with p-values < 0.001), highlighting clearly interpretable differences in the connectivity in the two subpopulations. For instance, the second and third principal components for the rest session capture the imbalance between the Default Mode and Executive Networks characterizing schizophrenia patients.

An attention-based hybrid deep learning framework integrating brain connectivity and activity of resting-state functional MRI data

Functional magnetic resonance imaging (fMRI) as a promising tool to investigate psychotic disorders can be decomposed into useful imaging features such as time courses (TCs) of independent components (ICs) and functional network connectivity (FNC) calculated by TC cross-correlation. TCs reflect the temporal dynamics of brain activity and the FNC characterizes temporal coherence across intrinsic brain networks. Both features have been used as input to deep learning approaches with decent results. However, few studies have tried to leverage their complementary information to learn optimal representations at multiple facets. Motivated by this, we proposed a Hybrid Deep Learning Framework integrating brain Connectivity and Activity (HDLFCA) together by combining convolutional recurrent neural network (C-RNN) and deep neural network (DNN), aiming to improve classification accuracy and interpretability simultaneously. Specifically, C-RNNAM was proposed to extract temporal dynamic dependencies with an attention module (AM) to automatically learn discriminative knowledge from TC nodes, while DNN was applied to identify the most group-discriminative FNC patterns with layer-wise relevance propagation (LRP). Then, both prediction outputs were concatenated to build a new feature matrix, generating the final decision by logistic regression. The effectiveness of HDLFCA was validated on both multi-site schizophrenia (SZ, n ∼ 1100) and public autism datasets (ABIDE, n ∼ 1522) by outperforming 12 alternative models at 2.8-8.9% accuracy, including 8 models using either static FNC or TCs and 4 models using dynamic FNC. Appreciable classification accuracy was achieved for HC vs. SZ (85.3%) and HC vs. Autism (72.4%) respectively. More importantly, the most group-discriminative brain regions can be easily attributed and visualized, providing meaningful biological interpretability and highlighting the great potential of the proposed HDLFCA model in the identification of valid neuroimaging biomarkers.

A scoping review of near infrared spectroscopy studies employing a verbal fluency task in bipolar disorder

BACKGROUND

Deficits in cognitive functioning, including attention, memory, and executive functions, along with impairments in language production, are present in patients with bipolar disorder (BD) patients during mood phases, but also during euthymia.Verbal fluency tasks (VFTs), being able to evaluate integrity of a wide range of cognitive domains and represent, can be used to screen for these disturbances. Neuroimaging studies, including Near-InfraRed Spectroscopy (NIRS), have repeatedly showed widespread alterations in the prefrontal and temporal cortex during the performance of VFTs in BD patients. This review aims to summarize the results of NIRS studies that evaluated hemodynamic responses associated with the VFTs in prefrontal and temporal regions in BD patients.

METHODS

We performed a scoping review of studies evaluating VFT-induced activation in prefrontal and temporal regions in BD patients, and the relationship between NIRS data and various clinical variables.

RESULTS

15 studies met the inclusion criteria. In BD patients, compared to healthy controls, NIRS studies showed hypoactivation of the dorsolateral prefrontal cortex, ventrolateral prefrontal cortex and anterior temporal regions. Moreover, clinical variables, such as depressive and social adaptation scores, were negatively correlated with hemodynamic responses in prefrontal and temporal regions, while a positive correlation were reported for measures of manic symptoms and impulsivity.

LIMITATIONS

The heterogeneity of the studies in terms of methodology, study design and clinical characteristics of the samples limited the comparability of the findings.

CONCLUSIONS

Given its non-invasiveness, good time-resolution and no need of posturalconstraint, NIRS technique could represent a useful tool for the evaluation of prefrontal and temporal haemodynamic correlates of cognitive performances in BD patients.

Relationship between Dynamic Blood-Oxygen-Level-Dependent Activity and Functional Network Connectivity: Characterization of Schizophrenia Subgroups

Aim: In this work, we propose the novel use of adaptively constrained independent vector analysis (acIVA) to effectively capture the temporal and spatial properties of dynamic blood-oxygen-level-dependent (BOLD) activity (dBA), and we efficiently quantify the spatial property of dBA (sdBA). We also propose to incorporate dBA into the study of brain dynamics to gain insight into activity-connectivity co-evolution patterns. Introduction: Studies of the dynamics of the human brain using functional magnetic resonance imaging (fMRI) have enabled the identification of unique functional network connectivity (FNC) states and provided new insights into mental disorders. There is evidence showing that both BOLD activity, which is captured by fMRI, and FNC are related to mental and cognitive processes. However, a few studies have evaluated the inter-relationships of these two domains of function. Moreover, the identification of subgroups of schizophrenia has gained significant clinical importance due to a need to study the heterogeneity of schizophrenia. Methods: We design a simulation study to verify the effectiveness of acIVA and apply acIVA to the dynamic study of resting-state fMRI data collected from individuals with schizophrenia and healthy controls (HCs) to investigate the relationship between dBA and dynamic FNC (dFNC). Results: The simulation study demonstrates that acIVA accurately captures the spatial variability and provides an efficient quantification of sdBA. The fMRI analysis yields synchronized sdBA-temporal property of dBA (tdBA) patterns and shows that the dBA and dFNC are significantly correlated in the spatial domain. Using these dynamic features, we identify schizophrenia subgroups with significant differences in terms of their clinical symptoms. Conclusion: We find that brain function is abnormally organized in schizophrenia compared with HCs since there are less synchronized sdBA-tdBA patterns in schizophrenia and schizophrenia prefers a component that merges multiple brain regions. Identification of schizophrenia subgroups using dynamic features inspires the use of neuroimaging in studying the heterogeneity of disorders. Impact statement This work introduces the use of joint blind source separation for the study of brain dynamics to enable efficient quantification of the spatial property of dynamic blood-oxygen-level-dependent (BOLD) activity to provide insight into the relationship of dynamic BOLD activity and dynamic functional network connectivity. The identification of subgroups of schizophrenia using dynamic features allows the study of heterogeneity of schizophrenia, emphasizing the importance of functional magnetic resonance imaging analysis in the study of brain activity and functional connectivity to gain a better understanding of the human brain, especially the brain with a mental disorder.

Hallucination-Specific structure-function associations in schizophrenia

Combining structural (sMRI) and functional magnetic resonance imaging (fMRI) data in schizophrenia patients with and without auditory hallucinations (9 SZ_AVH, 12 SZ_nAVH), 18 patients with bipolar disorder, and 22 healthy controls, we examined whether cortical thinning was associated with abnormal activity in functional brain networks associated with auditory hallucinations. Language-task fMRI data were combined with mean cortical thickness values from 148 brain regions in a constrained principal component analysis (CPCA) to identify brain structure-function associations predictable from group differences. Two components emerged from the multimodal analysis. The "AVH component" highlighted an association of frontotemporal and cingulate thinning with altered brain activity characteristic of hallucinations among patients with AVH. In contrast, the "Bipolar component" distinguished bipolar patients from healthy controls and linked increased activity in the language network with cortical thinning in the left occipital-temporal lobe. Our findings add to a body of evidence of the biological underpinnings of hallucinations and illustrate a method for multimodal data analysis of structure-function associations in psychiatric illness.

Analysis of local gyrification index using a novel shape-adaptive kernel and the standard FreeSurfer spherical kernel - evidence from chronic schizophrenia outpatients

Schizophrenia can be considered a brain disconnectivity condition related to aberrant neurodevelopment that causes alterations in the brain structure, including gyrification of the cortex. Literature findings on cortical folding are incoherent: they report hypogyria in the frontal, superior-parietal and temporal cortices, but also frontal hypergyria. This discrepancy in local gyrification index (LGI) results could be due to the commonly used spherical kernel (Freesurfer), which is a method of analysis that is still not spatially precise enough. In this study we would like to test the spatial accuracy of a novel method based on a shape-adaptive kernel (Cmorph). The analysis of differences in gyrification between chronic schizophrenia outpatients (n = 30) and healthy controls (n = 30) was conducted with two methods: Freesurfer LGI and Cmorph LGI. Widespread differences in the LGI between schizophrenia outpatients and healthy controls were found using both methods. Freesurfer showed hypogyria in the superior temporal gyrus and the right temporal pole; it also showed hypergyria in the rostral-middle-frontal cortex in schizophrenia outpatients. In comparison, Cmorph revealed that hypergyria is equally represented as hypogyria in orbitofrontal and central brain regions. The clusters from Cmorph were smaller and distributed more broadly, covering all lobes of the brain. The presented evidence from disrupted cortical folding in schizophrenia indicates that the shape-adaptive kernel approach has a potential to improve the knowledge on the disrupted cortical folding in schizophrenia; therefore, it could be a valuable tool for further investigation on big sample size.

Linked 4-Way Multimodal Brain Differences in Schizophrenia in a Large Chinese Han Population

Multimodal fusion has been regarded as a promising tool to discover covarying patterns of multiple imaging types impaired in brain diseases, such as schizophrenia (SZ). In this article, we aim to investigate the covarying abnormalities underlying SZ in a large Chinese Han population (307 SZs, 298 healthy controls [HCs]). Four types of magnetic resonance imaging (MRI) features, including regional homogeneity (ReHo) from resting-state functional MRI, gray matter volume (GM) from structural MRI, fractional anisotropy (FA) from diffusion MRI, and functional network connectivity (FNC) resulted from group independent component analysis, were jointly analyzed by a data-driven multivariate fusion method. Results suggest that a widely distributed network disruption appears in SZ patients, with synchronous changes in both functional and structural regions, especially the basal ganglia network, salience network (SAN), and the frontoparietal network. Such a multimodal coalteration was also replicated in another independent Chinese sample (40 SZs, 66 HCs). Our results on auditory verbal hallucination (AVH) also provide evidence for the hypothesis that prefrontal hypoactivation and temporal hyperactivation in SZ may lead to failure of executive control and inhibition, which is relevant to AVH. In addition, impaired working memory performance was found associated with GM reduction and FA decrease in SZ in prefrontal and superior temporal area, in both discovery and replication datasets. In summary, by leveraging multiple imaging and clinical information into one framework to observe brain in multiple views, we can integrate multiple inferences about SZ from large-scale population and offer unique perspectives regarding the missing links between the brain function and structure that may not be achieved by separate unimodal analyses.

ANK3 gene polymorphisms and bipolar disorder: a meta-analysis

OBJECTIVE

Converging evidence has suggested ankyrin 3 (ANK3) as a risk gene for bipolar disorder (BD). However, association studies investigating its genetic variants and BD susceptibility have reported inconsistent results. In the present meta-analysis, we aimed to establish whether ANK3 single nucleotide polymorphisms (SNPs) confer increased risk for BD.

METHODS

PubMed, Medline, PsycINFO, Embase, and Scopus were searched for literature published up to January 2017. Fourteen case-control studies met our eligibility criteria. We targeted ANK3 SNPs that have been reported by three or more studies to be included in the current meta-analysis, resulting in a final list of four SNPs: rs10994336, rs9804190, rs10994397, and rs1938526. Odds ratios (ORs) for the allele model were calculated using a random effect model as a measure of association. Additional experimental characteristics and between-study heterogeneity were explored using sensitivity test, subgroup analysis, and meta-regression techniques. Publication bias was also assessed using Egger's test and rank correlation test.

RESULTS

Overall, a significant association was found between BD and rs10994336 (OR=1.18; 95% confidence interval: 1.06-1.31; P=0.0027) as well as rs1938526 (OR=1.16; 95% confidence interval: 1.06-1.28; P=0.0016). Subsequent sensitivity analysis and publication bias test reaffirmed the stability and consistency of these results.

CONCLUSION

The current meta-analysis provides corroborating evidence suggesting two ANK3 SNPs are associated with an increased susceptibility for developing BD. However, broader coverage is needed on less explored SNPs to further elucidate the genetic effect of other ANK3 variants that may harbor potential BD risk.

Free Energy and Virtual Reality in Neuroscience and Psychoanalysis: A Complexity Theory of Dreaming and Mental Disorder

The main concepts of the free energy (FE) neuroscience developed by Karl Friston and colleagues parallel those of Freud's Project for a Scientific Psychology. In Hobson et al. (2014) these include an innate virtual reality generator that produces the fictive prior beliefs that Freud described as the primary process. This enables Friston's account to encompass a unified treatment-a complexity theory-of the role of virtual reality in both dreaming and mental disorder. In both accounts the brain operates to minimize FE aroused by sensory impingements-including interoceptive impingements that report compliance with biological imperatives-and constructs a representation/model of the causes of impingement that enables this minimization. In Friston's account (variational) FE equals complexity minus accuracy, and is minimized by increasing accuracy and decreasing complexity. Roughly the brain (or model) increases accuracy together with complexity in waking. This is mediated by consciousness-creating active inference-by which it explains sensory impingements in terms of perceptual experiences of their causes. In sleep it reduces complexity by processes that include both synaptic pruning and consciousness/virtual reality/dreaming in REM. The consciousness-creating active inference that effects complexity-reduction in REM dreaming must operate on FE-arousing data distinct from sensory impingement. The most relevant source is remembered arousals of emotion, both recent and remote, as processed in SWS and REM on "active systems" accounts of memory consolidation/reconsolidation. Freud describes these remembered arousals as condensed in the dreamwork for use in the conscious contents of dreams, and similar condensation can be seen in symptoms. Complexity partly reflects emotional conflict and trauma. This indicates that dreams and symptoms are both produced to reduce complexity in the form of potentially adverse (traumatic or conflicting) arousals of amygdala-related emotions. Mental disorder is thus caused by computational complexity together with mechanisms like synaptic pruning that have evolved for complexity-reduction; and important features of disorder can be understood in these terms. Details of the consilience among Freudian, systems consolidation, and complexity-reduction accounts appear clearly in the analysis of a single fragment of a dream, indicating also how complexity reduction proceeds by a process resembling Bayesian model selection.

Cortical thickness in regions of frontal and temporal lobes is associated with responsiveness to cognitive remediation therapy in schizophrenia

BACKGROUND

Despite the evidence for the efficacy of cognitive remediation therapy (CRT) in patients with schizophrenia, comparatively little is known about the potential predictors of good treatment response. We tried to determine whether improvement in cognition following CRT is positively associated with baseline cortical thickness (CTh) or baseline clinical symptoms level or baseline cognitive performance.

METHODS

The current work uses data collected in a previous study (Penadés et al., 2013) in which a CRT program was investigated through a controlled randomized trial (NCT 01318850) with three groups: patients receiving cognitive treatment, patients receiving a different psychological intervention as an active and a healthy control groups (HC). CTh was estimated from the T1-weighted MRIs using the FreeSurfer software.

RESULTS

We found that CRT responsiveness was associated with baseline measures of cortical thickness in the frontal and temporal lobes. Positive changes in non-verbal memory were associated with greater initial thickness in cortical regions involving left superior frontal, left caudal middle frontal, left precuneus and paracentral; superior frontal, right caudal middle frontal gyrus and pars opercularis. Additionally, uncorrected data also suggested that verbal memory improvement could be associated with CTh in some areas of the frontal and temporal lobes.

DISCUSSION

Our findings are consistent with the hypothesis that greater CTh in specific brain areas could be associated with better response to CRT. Furthermore, brain areas associated with CRT responsiveness were located mainly in regions of frontal and temporal lobes.

Abnormalities of cingulate cortex in antipsychotic-naïve chronic schizophrenia

While several morphometric studies have postulated a critical contribution of the cingulate cortex (CC) to the pathophysiology of schizophrenia based on abnormalities in CC volume, other studies have been inconclusive. Most such studies have focused only on changes in cortical volume, whereas other morphometric parameters such as surface area and cortical thickness could be more relevant and possibly account for these discrepancies. Furthermore, factors such as antipsychotic drug use and treatment duration may also influence cortical morphology. To clarify the association between schizophrenia and CC deficits, we investigated morphometric abnormalities of the CC in antipsychotic drug (AD)-naïve chronic schizophrenia patients by comparing T1-weighted magnetic resonance images (T1WI-MRI) from patients (n=17) to healthy controls (n=17) using the surface-based morphometry program FreeSurfer. Partial correlations were examined between abnormal morphometric measures and both clinical variables and cognitive performance scores. Compared to healthy controls, drug-naïve schizophrenia patients exhibited significantly lower volumes in both left rostral anterior CC (rACC) and left posterior CC (PCC). These reductions in CC volume resulted from reduced surface area rather than reduced cortical thickness. There was also a significant relationship between left PCC volume and working memory in patients. No significant correlations were observed between CC volume and clinical variables. The results suggest that abnormalities in the CC as manifested by reduced surface area may contribute to cognitive dysfunction in schizophrenia. This article is part of a Special Issue entitled SI: PSC and the brain.

Assessing brain structural associations with working-memory related brain patterns in schizophrenia and healthy controls using linked independent component analysis

Schizophrenia (SZ) is a psychotic disorder with significant cognitive dysfunction. Abnormal brain activation during cognitive processing has been reported, both in task-positive and task-negative networks. Further, structural cortical and subcortical brain abnormalities have been documented, but little is known about how task-related brain activation is associated with brain anatomy in SZ compared to healthy controls (HC). Utilizing linked independent component analysis (LICA), a data-driven multimodal analysis approach, we investigated structure-function associations in a large sample of SZ (n = 96) and HC (n = 142). We tested for associations between task-positive (fronto-parietal) and task-negative (default-mode) brain networks derived from fMRI activation during an n-back working memory task, and brain structural measures of surface area, cortical thickness, and gray matter volume, and to what extent these associations differed in SZ compared to HC. A significant association (p < .05, corrected for multiple comparisons) was found between a component reflecting the task-positive fronto-parietal network and another component reflecting cortical thickness in fronto-temporal brain regions in SZ, indicating increased activation with increased thickness. Other structure-function associations across, between and within groups were generally moderate and significant at a nominal p-level only, with more numerous and stronger associations in SZ compared to HC. These results indicate a complex pattern of moderate associations between brain activation during cognitive processing and brain morphometry, and extend previous findings of fronto-temporal brain abnormalities in SZ by suggesting a coupling between cortical thickness of these brain regions and working memory-related brain activation.

Does neuroanatomy account for superior temporal dysfunction in early psychosis? A multimodal MRI investigation

BACKGROUND

Neuroimaging studies of ultra-high risk (UHR) and first-episode psychosis (FEP) have revealed widespread alterations in brain structure and function. Recent evidence suggests there is an intrinsic relationship between these 2 types of alterations; however, there is very little research linking these 2 modalities in the early stages of psychosis.

METHODS

To test the hypothesis that functional alteration in UHR and FEP articipants would be associated with corresponding structural alteration, we examined brain function and structure in these participants as well as in a group of healthy controls using multimodal MRI. The data were analyzed using statistical parametric mapping.

RESULTS

We included 24 participants in the FEP group, 18 in the UHR group and 21 in the control group. Patients in the FEP group showed a reduction in functional activation in the left superior temporal gyrus relative to controls, and the UHR group showed intermediate values. The same region showed a corresponding reduction in grey matter volume in the FEP group relative to controls. However, while the difference in grey matter volume remained significant after including functional activation as a covariate of no interest, the reduction in functional activation was no longer evident after including grey matter volume as a covariate of no interest.

LIMITATIONS

Our sample size was relatively small. All participants in the FEP group and 2 in the UHR group had received antipsychotic medication, which may have impacted neurofunction and/or neuroanatomy.

CONCLUSION

Our results suggest that superior temporal dysfunction in early psychosis is accounted for by a corresponding alteration in grey matter volume. This finding has important implications for the interpretation of functional alteration in early psychosis.

Cortical thinning in temporo-parietal junction (TPJ) in non-affective first-episode of psychosis patients with persistent negative symptoms

BACKGROUND

Negative symptoms represent an unmet therapeutic need in many patients with schizophrenia. In an extension to our previous voxel-based morphometry findings, we employed a more specific, vertex-based approach to explore cortical thinning in relation to persistent negative symptoms (PNS) in non-affective first-episode of psychosis (FEP) patients to advance our understanding of the pathophysiology of primary negative symptoms.

METHODS

This study included 62 non-affective FEP patients and 60 non-clinical controls; 16 patients were identified with PNS (i.e., at least 1 primary negative symptom at moderate or greater severity sustained for at least 6 consecutive months). Using cortical thickness analyses, we explored for differences between PNS and non-PNS patients as well as between each patient group and healthy controls; cut-off threshold was set at p<0.01, corrected for multiple comparisons.

RESULTS

A thinner cortex prominently in the right superior temporal gyrus extending into the temporo-parietal junction (TPJ), right parahippocampal gyrus, and left orbital frontal gyrus was identified in PNS patients vs. non-PNS patients. Compared with healthy controls, PNS patients showed a thinner cortex prominently in the right superior temporal gyrus, right parahippocampal gyrus, and right cingulate; non-PNS patients showed a thinner cortex prominently in the parahippocampal gyrus bi-laterally.

CONCLUSION

Cortical thinning in the early stages of non-affective psychosis is present in the frontal and temporo-parietal regions in patients with PNS. With these brain regions strongly related to social cognitive functioning, our finding suggests a potential link between primary negative symptoms and social cognitive deficits through common brain etiologies.

Cortical thinning in temporo-parietal junction (TPJ) in non-affective first-episode of psychosis patients with persistent negative symptoms

BACKGROUND

Negative symptoms represent an unmet therapeutic need in many patients with schizophrenia. In an extension to our previous voxel-based morphometry findings, we employed a more specific, vertex-based approach to explore cortical thinning in relation to persistent negative symptoms (PNS) in non-affective first-episode of psychosis (FEP) patients to advance our understanding of the pathophysiology of primary negative symptoms.

METHODS

This study included 62 non-affective FEP patients and 60 non-clinical controls; 16 patients were identified with PNS (i.e., at least 1 primary negative symptom at moderate or greater severity sustained for at least 6 consecutive months). Using cortical thickness analyses, we explored for differences between PNS and non-PNS patients as well as between each patient group and healthy controls; cut-off threshold was set at p<0.01, corrected for multiple comparisons.

RESULTS

A thinner cortex prominently in the right superior temporal gyrus extending into the temporo-parietal junction (TPJ), right parahippocampal gyrus, and left orbital frontal gyrus was identified in PNS patients vs. non-PNS patients. Compared with healthy controls, PNS patients showed a thinner cortex prominently in the right superior temporal gyrus, right parahippocampal gyrus, and right cingulate; non-PNS patients showed a thinner cortex prominently in the parahippocampal gyrus bi-laterally.

CONCLUSION

Cortical thinning in the early stages of non-affective psychosis is present in the frontal and temporo-parietal regions in patients with PNS. With these brain regions strongly related to social cognitive functioning, our finding suggests a potential link between primary negative symptoms and social cognitive deficits through common brain etiologies.

ZNF804A and cortical structure in schizophrenia: in vivo and postmortem studies

Recent evidence indicated that the ZNF804A (rs1344706) risk allele A is associated with better cognitive performance in patients with schizophrenia. Moreover, it has been demonstrated that ZNF804A may also be related to relatively intact gray matter volume in patients. To further explore these putatively protective effects, the impact of ZNF804A on cortical thickness and folding was examined in this study. To elucidate potential molecular mechanisms, an allelic-specific gene expression study was also carried out. Magnetic resonance imaging cortical thickness and folding were computed in 55 genotyped patients with schizophrenia and 40 healthy controls. Homozygous risk allele carriers (AA) were compared with AC/CC carriers. ZNF804A gene expression was analyzed in a prefrontal region using postmortem tissue from another cohort of 35 patients. In patients, AA carriers exhibited significantly thicker cortex in prefrontal and temporal regions and less disturbed superior temporal cortical folding, whereas the opposite effect was observed in controls, ie, AA carrier status was associated with thinner cortex and more severe altered cortical folding. Along with this, our expression analysis revealed that the risk allele is associated with lower prefrontal ZNF804A expression in patients, whereas the opposite effect in controls has been observed by prior analyses. In conclusion, our analyses provide convergent support for the hypothesis that the schizophrenia-associated ZNF804A variant mediates protective effects on cortex structure in patients. In particular, the allele-specific expression profile in patients might constitute a molecular mechanism for the observed protective influence of ZNF804A on cortical thickness and folding and potentially other intermediate phenotypes.

Association of a risk allele of ANK3 with cognitive performance and cortical thickness in patients with first-episode psychosis

BACKGROUND

The gene ANK3 is implicated in bipolar disorder and schizophrenia. The present study investigated the influence of this gene on cognitive performance and brain structure among individuals with first-episode psychosis (FEP). The brief illness duration of an FEP sample makes it well suited for studying the effects of genetic variation.

METHODS

We genotyped 2 single nucleotide polymorphisms (SNPs; rs1938526 and rs10994336) in ANK3 in patients with FEP. Multivariate analysis of variance compared risk allele carriers and noncarriers on 6 domains of cognition consistent with MATRICS consensus. A subsample of 82 patients was assessed using magnetic resonance imaging. We compared brain structure between carriers and noncarriers using cortical thickness analysis and voxel-based morphometry on white matter.

RESULTS

In the 173 patients with FEP included in our study, rs1938526 and rs10994336 were in very high linkage disequilibrium (d' = 0.95), and analyses were therefore only carried out on the SNP (rs1938526) with the highest minor allele frequency (G). Allele G of rs1938526, was associated with lower cognitive performance across domains (F6,164 = 2.38, p = 0.030) and significantly lower scores on the domains of verbal memory (p = 0.015), working memory (p = 0.006) and attention (p = 0.019). The significant effects of this SNP on cognition were not maintained when controlling for IQ. Cortical thinning was observed in risk allele carriers at diverse sites across cortical lobes bilaterally at a threshold of p < 0.01, false discovery rate-corrected. Risk-allele carriers did not show any regions of reduced white matter volume.

LIMITATIONS

The sample size is modest given that a low-frequency variant was being examined.

CONCLUSION

The ANK3 risk allele rs1938526 appears to be associated with general cognitive impairment and widespread cortical thinning in patients with FEP.

Inferior frontal and insular cortical thinning is related to dysfunctional brain activation/deactivation during working memory task in schizophrenic patients

Although working memory is known to be impaired in schizophrenia the anatomical and functional relationships underlying this deficit remain to be elucidated. A combined imaging approach involving functional and structural magnetic resonance techniques was used, applying independent component analysis and surface-based morphometry to 14 patients with schizophrenia and 14 healthy controls. Neurocognitive functioning was assessed by a neuropsychological test battery that measured executive function. It was hypothesized that working memory dysfunctional connectivity in schizophrenia is related to underlying anatomical abnormalities. Patients with schizophrenia showed cortical thinning in the left inferior frontal gyrus and insula, which explained 57% of blood oxygenation level-dependent signal magnitude in functional magnetic resonance imaging in the central executive network (lateral prefrontal and parietal cortex) over-activation and default mode network (anterior and posterior cingulate) deactivation. No structure-function relationship emerged in the healthy control group. The study provides evidence to suggest that dysfunctional activation/deactivation patterns in schizophrenia may be explained in terms of underlying gray matter deficits.

Links among resting-state default-mode network, salience network, and symptomatology in schizophrenia

Neuroimaging data support the idea that schizophrenia is a brain disorder with altered brain structure and function. New resting-state functional connectivity techniques allow us to highlight synchronization of large-scale networks, such as the default-mode network (DMN) and salience network (SN). A large body of work suggests that disruption of these networks could give rise to specific schizophrenia symptoms. We examined the intra-network connectivity strength and gray matter content (GMC) of DMN and SN in 26 schizophrenia patients using resting-state functional magnetic resonance imaging and voxel-based morphometry. Resting-state data were analyzed with independent component analysis and dual-regression techniques. We reported reduced functional connectivity within both DMN and SN in patients with schizophrenia. Concerning the DMN, patients showed weaker connectivity in a cluster located in the right paracingulate cortex. Moreover, patients showed decreased GMC in this cluster. With regard to the SN, patients showed reduced connectivity in the left and right striatum. Decreased connectivity in the paracingulate cortex was correlated with difficulties in abstract thinking. The connectivity decrease in the left striatum was correlated with delusion and depression scores. Correlation between the connectivity of DMN frontal regions and difficulties in abstract thinking emphasizes the link between negative symptoms and the likely alteration of the frontal medial cortex in schizophrenia. Correlation between the connectivity of SN striatal regions and delusions supports the aberrant salience hypothesis. This work provides new insights into dysfunctional brain organization in schizophrenia and its contribution to specific schizophrenia symptoms.

Altered auditory processing in frontal and left temporal cortex in 22q11.2 deletion syndrome: a group at high genetic risk for schizophrenia

In order to investigate electroencephalographic (EEG) biomarkers of auditory processing for schizophrenia, we studied a group with a well known high-risk profile: patients with 22q11.2 deletion syndrome (22q11 DS) have a 30% risk of developing schizophrenia during adulthood. We performed high-density EEG source imaging to measure auditory gating of the P50 component of the evoked potential and middle to late latency auditory processing in 21 participants with the 22q11.2 deletion and 17 age-matched healthy controls. While we found no indication of altered P50 suppression in 22q11 DS, we observed marked differences for the first N1 component with increased amplitudes on central electrodes, corresponding to increased activations in dorsal anterior cingulate and medial frontal cortex. We also found a left lateralized reduction of activation of primary and secondary auditory cortex during the second N1 (120ms) and the P2 component in 22q11 DS. Our results show that sensory gating and activations until 50ms were preserved in 22q11 DS, while impairments appear at latencies that correspond to higher order auditory processing. While the increased activation of cingulate and medial frontal cortex could reflect developmental changes in 22q11 DS, the reduced activity seen in left auditory cortex might serve as a biomarker for the development of schizophrenia, if confirmed by longitudinal research protocols.

Redox dysregulation in the pathophysiology of schizophrenia and bipolar disorder: insights from animal models

SIGNIFICANCE

Schizophrenia (SZ) and bipolar disorder (BD) are classified as two distinct diseases. However, accumulating evidence shows that both disorders share genetic, pathological, and epidemiological characteristics. Based on genetic and functional findings, redox dysregulation due to an imbalance between pro-oxidants and antioxidant defense mechanisms has been proposed as a risk factor contributing to their pathophysiology.

RECENT ADVANCES

Altered antioxidant systems and signs of increased oxidative stress are observed in peripheral tissues and brains of SZ and BD patients, including abnormal prefrontal levels of glutathione (GSH), the major cellular redox regulator and antioxidant. Here we review experimental data from rodent models demonstrating that permanent as well as transient GSH deficit results in behavioral, morphological, electrophysiological, and neurochemical alterations analogous to pathologies observed in patients. Mice with GSH deficit display increased stress reactivity, altered social behavior, impaired prepulse inhibition, and exaggerated locomotor responses to psychostimulant injection. These behavioral changes are accompanied by N-methyl-D-aspartate receptor hypofunction, elevated glutamate levels, impairment of parvalbumin GABA interneurons, abnormal neuronal synchronization, altered dopamine neurotransmission, and deficient myelination.

CRITICAL ISSUES

Treatment with the GSH precursor and antioxidant N-acetylcysteine normalizes some of those deficits in mice, but also improves SZ and BD symptoms when given as adjunct to antipsychotic medication.

FUTURE DIRECTIONS

These data demonstrate the usefulness of GSH-deficient rodent models to identify the mechanisms by which a redox imbalance could contribute to the development of SZ and BD pathophysiologies, and to develop novel therapeutic approaches based on antioxidant and redox regulator compounds.

Multimodal functional and structural imaging investigations in psychosis research

Substantial pathophysiological questions about the relationship of brain pathologies in psychosis can only be answered by multimodal neuroimaging approaches combining different imaging modalities such as structural MRI (sMRI), functional MRI (fMRI), diffusion tensor imaging (DTI), positron emission tomography (PET) and magnetic-resonance spectroscopy. In particular, the multimodal imaging approach has the potential to shed light on the neuronal mechanisms underlying the major brain structural and functional pathophysiological features of schizophrenia and high-risk states such as prefronto-temporal gray matter reduction, altered higher-order cognitive processing, or disturbed dopaminergic and glutamatergic neurotransmission. In recent years, valuable new findings have been revealed in these fields by multimodal imaging studies mostly reflecting a direct and aligned correlation of brain pathologies in psychosis. However, the amount of multimodal studies is still limited, and further efforts have to be made to consolidate previous findings and to extend the scope to other pathophysiological parameters contributing to the pathogenesis of psychosis. Here, investigating the genetic foundations of brain pathology relationships is a major challenge for future multimodal imaging applications in psychosis research.