Dysregulation of working memory and default-mode networks in schizophrenia using independent component analysis, an fBIRN and MCIC study

Investigating the association between symptoms and functional activity in brain regions in schizophrenia: A cross-sectional fmri-based neuroimaging study

Schizophrenia is a persistent neurological disorder profoundly affecting cognitive, emotional, and behavioral functions, prominently characterized by delusions, hallucinations, disordered speech, and abnormal motor activity. These symptoms often present diagnostic challenges due to their overlap with other forms of psychosis. Therefore, the implementation of automated diagnostic methodologies is imperative. This research leverages Functional Magnetic Resonance Imaging (fMRI), a neuroimaging modality capable of delineating functional activations across diverse brain regions. Furthermore, the utilization of evolving machine learning techniques for fMRI data analysis has significantly progressive. Here, our study stands as a novel attempt, focusing on the comprehensive assessment of both classical and atypical symptoms of schizophrenia. We aim to uncover associated changes in brain functional activity. Our study encompasses two distinct fMRI datasets (1.5T and 3T), each comprising 34 schizophrenia patients for the 1.5T dataset and 25 schizophrenia patients for the 3T dataset, along with an equal number of healthy controls. Machine learning algorithms are applied to assess data subsets, enabling an in-depth evaluation of the current functional condition concerning symptom impact. The identified voxels contribute to determining the brain regions most influenced by each symptom, as quantified by symptom intensity. This rigorous approach has yielded various new findings while maintaining an impressive classification accuracy rate of 97 %. By elucidating variations in activation patterns across multiple brain regions in individuals with schizophrenia, this study contributes to the understanding of functional brain changes associated with the disorder. The insights gained may inform differential clinical interventions and provide a means of assessing symptom severity accurately, offering new avenues for the management of schizophrenia.

Disrupted cognitive network revealed by task-induced brain entropy in schizophrenia

Brain entropy (BEN), which measures the amount of information in brain activity, provides a novel perspective for evaluating brain function. Recent studies using resting-state functional magnetic resonance imaging (fMRI) have shown that BEN during rest can help characterize brain function alterations in schizophrenia (SCZ). However, there is a lack of research on BEN using task-evoked fMRI to explore task-dependent cognitive deficits in SCZ. In this study, we evaluate whether the reduced working memory (WM) capacity in SCZ is possibly associated with dynamic changes in task BEN during tasks with high cognitive demands. We analyzed data from 15 patients with SCZ and 15 healthy controls (HC), calculating task BEN from their N-back task fMRI scans. We then examined correlations between task BEN values, clinical symptoms, 2-back task performance, and neuropsychological test scores. Patients with SCZ exhibited significantly reduced task BEN in the cerebellum, hippocampus, parahippocampal gyrus, thalamus, and the middle and superior frontal gyrus (MFG and SFG) compared to HC. In HC, significant positive correlations were observed between task BEN and 2-back accuracy in several brain regions, including the MFG and SFG; such correlations were absent in patients with SCZ. Additionally, task BEN was negatively associated with scores for both positive and negative symptoms in areas including the parahippocampal gyrus among patients with SCZ. In conclusion, our findings indicate that a reduction in BEN within prefrontal and hippocampal regions during cognitively demanding tasks may serve as a neuroimaging marker for SCZ.

Medial Prefrontal Cortex Dysfunction Mediates Working Memory Deficits in Patients With Schizophrenia

Background

Schizophrenia (SCZ) is marked by working memory (WM) deficits, which predict poor functional outcome. While most functional magnetic resonance imaging studies of WM in SCZ have focused on the dorsolateral prefrontal cortex (PFC), some recent work suggests that the medial PFC (mPFC) may play a role. We investigated whether task-evoked mPFC deactivation is associated with WM performance and whether it mediates deficits in SCZ. In addition, we investigated associations between mPFC deactivation and cortical dopamine release.

Methods

Patients with SCZ (n = 41) and healthy control participants (HCs) (n = 40) performed a visual object n-back task during functional magnetic resonance imaging. Dopamine release capacity in mPFC was quantified with [11C]FLB457 in a subset of participants (9 SCZ, 14 HCs) using an amphetamine challenge. Correlations between task-evoked deactivation and performance were assessed in mPFC and dorsolateral PFC masks and were further examined for relationships with diagnosis and dopamine release.

Results

mPFC deactivation was associated with WM task performance, but dorsolateral PFC activation was not. Deactivation in the mPFC was reduced in patients with SCZ relative to HCs and mediated the relationship between diagnosis and WM performance. In addition, mPFC deactivation was significantly and inversely associated with dopamine release capacity across groups and in HCs alone, but not in patients.

Conclusions

Reduced WM task-evoked mPFC deactivation is a mediator of, and potential substrate for, WM impairment in SCZ, although our study design does not rule out the possibility that these findings could relate to cognition in general rather than WM specifically. We further present preliminary evidence of an inverse association between deactivation during WM tasks and dopamine release capacity in the mPFC.

Dysconnection and cognition in schizophrenia: A spectral dynamic causal modeling study

Schizophrenia (SZ) is a severe mental disorder characterized by failure of functional integration (aka dysconnection) across the brain. Recent functional connectivity (FC) studies have adopted functional parcellations to define subnetworks of large-scale networks, and to characterize the (dys)connection between them, in normal and clinical populations. While FC examines statistical dependencies between observations, model-based effective connectivity (EC) can disclose the causal influences that underwrite the observed dependencies. In this study, we investigated resting state EC within seven large-scale networks, in 66 SZ and 74 healthy subjects from a public dataset. The results showed that a remarkable 33% of the effective connections (among subnetworks) of the cognitive control network had been pathologically modulated in SZ. Further dysconnection was identified within the visual, default mode and sensorimotor networks of SZ subjects, with 24%, 20%, and 11% aberrant couplings. Overall, the proportion of discriminative connections was remarkably larger in EC (24%) than FC (1%) analysis. Subsequently, to study the neural correlates of impaired cognition in SZ, we conducted a canonical correlation analysis between the EC parameters and the cognitive scores of the patients. As such, the self-inhibitions of supplementary motor area and paracentral lobule (in the sensorimotor network) and the excitatory connection from parahippocampal gyrus to inferior temporal gyrus (in the cognitive control network) were significantly correlated with the social cognition, reasoning/problem solving and working memory capabilities of the patients. Future research can investigate the potential of whole-brain EC as a biomarker for diagnosis of brain disorders and for neuroimaging-based cognitive assessment.

Opposite effects of positive and negative symptoms on resting-state brain networks in schizophrenia

Schizophrenia is a severe psychotic disorder characterized by positive and negative symptoms, but their neural bases remain poorly understood. Here, we utilized a nested-spectral partition (NSP) approach to detect hierarchical modules in resting-state brain functional networks in schizophrenia patients and healthy controls, and we studied dynamic transitions of segregation and integration as well as their relationships with clinical symptoms. Schizophrenia brains showed a more stable integrating process and a more variable segregating process, thus maintaining higher segregation, especially in the limbic system. Hallucinations were associated with higher integration in attention systems, and avolition was related to a more variable segregating process in default-mode network (DMN) and control systems. In a machine-learning model, NSP-based features outperformed graph measures at predicting positive and negative symptoms. Multivariate analysis confirmed that positive and negative symptoms had opposite effects on dynamic segregation and integration of brain networks. Gene ontology analysis revealed that the effect of negative symptoms was related to autistic, aggressive and violent behavior; the effect of positive symptoms was associated with hyperammonemia and acidosis; and the interaction effect was correlated with abnormal motor function. Our findings could contribute to the development of more accurate diagnostic criteria for positive and negative symptoms in schizophrenia.

Recurrence quantification analysis of periodic dynamics in the default mode network in first-episode drug-naïve schizophrenia

Abnormal functional connectivity (FC) within the default model network (DMN) in schizophrenia has been frequently reported in previous studies. However, traditional FC analysis was mostly linear correlations based, with the information on nonlinear or temporally lagged brain signals largely overlooked. Fifty-five first-episode drug-naïve schizophrenia (FES) patients and 53 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging scanning. The DMN was extracted using independent component analysis. Recurrence quantification analysis was used to measure the duration, predictability, and complexity of the periodic processes of the nonlinear DMN time series. The Mann‒Whitney U test was conducted to compare these features between FES patients and HCs. The support vector machine was applied to discriminate FES from HCs based on these features. Determinism, which means predictability of periodic process activity, between the ventromedial prefrontal cortex (vMPFC) and posterior cingulate and between the vMPFC and precuneus, was significantly decreased in FES compared with HCs. Determinism between the vMPFC and precuneus was positively correlated with category fluency scores in FES. The classifier achieved 77% accuracy. Our results suggest that synchronized periodicity among DMN brain regions is dysregulated in FES, and the periodicity in BOLD signals may be a promising indicator of brain functional connectivity.

Distinct but cooperating brain networks supporting semantic cognition

Semantic cognition is a complex multifaceted brain function involving multiple processes including sensory, semantic, and domain-general cognitive systems. However, it remains unclear how these systems cooperate with each other to achieve effective semantic cognition. Here, we used independent component analysis (ICA) to investigate the functional brain networks that support semantic cognition. We used a semantic judgment task and a pattern-matching control task, each with 2 levels of difficulty, to disentangle task-specific networks from domain-general networks. ICA revealed 2 task-specific networks (the left-lateralized semantic network [SN] and a bilateral, extended semantic network [ESN]) and domain-general networks including the frontoparietal network (FPN) and default mode network (DMN). SN was coupled with the ESN and FPN but decoupled from the DMN, whereas the ESN was synchronized with the FPN alone and did not show a decoupling with the DMN. The degree of decoupling between the SN and DMN was associated with semantic task performance, with the strongest decoupling for the poorest performing participants. Our findings suggest that human higher cognition is achieved by the multiple brain networks, serving distinct and shared cognitive functions depending on task demands, and that the neural dynamics between these networks may be crucial for efficient semantic cognition.

Network hub centrality and working memory performance in schizophrenia

Cognitive impairment, and working memory deficits in particular, are debilitating, treatment-resistant aspects of schizophrenia. Dysfunction of brain network hubs, putatively related to altered neurodevelopment, is thought to underlie the cognitive symptoms associated with this illness. Here, we used weighted degree, a robust graph theory metric representing the number of weighted connections to a node, to quantify centrality in cortical hubs in 29 patients with schizophrenia and 29 age- and gender-matched healthy controls and identify the critical nodes that underlie working memory performance. In both patients and controls, elevated weighted degree in the default mode network (DMN) was generally associated with poorer performance (accuracy and reaction time). Higher degree in the ventral attention network (VAN) nodes in the right superior temporal cortex was associated with better performance (accuracy) in patients. Degree in several prefrontal and parietal areas was associated with cognitive performance only in patients. In regions that are critical for sustained attention, these correlations were primarily driven by between-network connectivity in patients. Moreover, a cross-validated prediction analysis showed that a linear model using a summary degree score can be used to predict an individual’s working memory accuracy (r = 0.35). Our results suggest that schizophrenia is associated with dysfunctional hubs in the cortical systems supporting internal and external cognition and highlight the importance of topological network analysis in the search of biomarkers for cognitive deficits in schizophrenia.

New insights of the role of the KCNH2 gene in schizophrenia: An fMRI case-control study

The KCNH2 gene, encoding for a subunit of a voltage-gated potassium channel, has been identified as a key element of neuronal excitability and a promising novel therapeutic target for schizophrenia (SZ). Nonetheless, evidence highlighting the role of KCNH2 on cognitive and brain activity phenotypes comes mainly from studies based on healthy controls (HC). Therefore, we aimed to study the role of KCNH2 on the brain functional differences between patients with SZ and HC. The fMRI sample comprised 78 HC and 79 patients with SZ (matched for age, sex and premorbid IQ). We studied the effect of the polymorphism KCNH2-rs3800779 on attention and working memory-related brain activity, evaluated through the N-back task, in regions with detected diagnostic differences (regression model, controlled for age, sex and premorbid IQ, FEAT-FSL). We report a significant diagnosis x KCNH2 interaction on brain activity (1-back vs baseline contrast) at the medial superior prefrontal cortex (Zmax=3.55, p = 0.00861). In this region, patients with SZ carrying the risk genotype (AA) show a deactivation failure, while HC depict the opposite pattern towards deactivation. The brain region with significant diagnosis x KCNH2 interaction has been previously associated with SZ. The results of this study, in which the role of KCNH2 on fMRI response is analysed for the first time in patients, suggest that KCNH2 variability contributes to inefficient brain activity modulation during the N-back task in affected subjects. These data may pave the way to further understand how KCNH2 genetic variability is related to the pathophysiological mechanisms underlying schizophrenia.

The passive recipient: Neural correlates of negative self-view in depression

INTRODCTION

Previous studies have argued that people tend to isolate themselves from negative information. This tendency is modulated by the individual's role in social interaction, that is, as an initiative actor (e.g., "I hit Tom") or a passive recipient (e.g., "Paul hits me"). Depressed patients tend to focus on negative aspects of themselves and cope with situations passively. It is still an open question how the actor/recipient role affects the behavioral and neural responses to self in depression.

METHODS

The present study adopted functional magnetic resonance imaging (fMRI) technology to investigate behavioral and neural responses to self (as an actor/recipient) in depressed patients and the matched healthy controls when attributing negative events.

RESULTS

Compared with healthy controls, depressed patients showed more self-attribution for negative events. Depressed patients showed increased brain activity in the dorsal medial prefrontal cortex (dmPFC) subsystem of the default mode network (DMN) when they played recipient role in self-related negative events. Activity of the dmPFC subsystem was negatively correlated with depressed patients' self-attribution for negative events in recipient condition. While decreased brain activity in the medial temporal lobe (MTL) subsystem was observed in depressed patients when they played the actor or recipient role in self-related negative events. Activity of the MTL subsystem was negatively correlated with depressed patients' reaction time when they played recipient role in selfrelated negative events.

CONCLUSION

These results implicated that depressed patients manifested the negative self-view. Actor/recipient role affected their activation patterns in the DMN which were different from the healthy controls. The correlation between the abnormal brain activations of the DMN and the behavioral performances might manifest more easily when depressed patients played recipient role in negative events.

Confirmation Bias in the Course of Instructed Reinforcement Learning in Schizophrenia-Spectrum Disorders

A large body of research attributes learning deficits in schizophrenia (SZ) to the systems involved in value representation (prefrontal cortex, PFC) and reinforcement learning (basal ganglia, BG) as well as to the compromised connectivity of these regions. In this study, we employed learning tasks hypothesized to probe the function and interaction of the PFC and BG in patients with SZ-spectrum disorders in comparison to healthy control (HC) subjects. In the Instructed Probabilistic Selection task (IPST), participants received false instruction about one of the stimuli used in the course of probabilistic learning which creates confirmation bias, whereby the instructed stimulus is overvalued in comparison to its real experienced value. The IPST was administered to 102 patients with SZ and 120 HC subjects. We have shown that SZ patients and HC subjects were equally influenced by false instruction in reinforcement learning (RL) probabilistic task (IPST) (p-value = 0.441); however, HC subjects had significantly higher learning rates associated with the process of overcoming cognitive bias in comparison to SZ patients (p-value = 0.018). The behavioral results of our study could be hypothesized to provide further evidence for impairments in the SZ-BG circuitry; however, this should be verified by neurofunctional imaging studies.

How recent learning shapes the brain: Memory-dependent functional reconfiguration of brain circuits

The process of storing recently encoded episodic mnestic traces so that they are available for subsequent retrieval is accompanied by specific brain functional connectivity (FC) changes. In this fMRI study, we examined the early processing of memories in twenty-eight healthy participants performing an episodic memory task interposed between two resting state sessions. Memory performance was assessed through a forced-choice recognition test after the scanning sessions. We investigated resting state system configuration changes via Independent Component Analysis by cross-modeling baseline resting state spatial maps onto the post-encoding resting state, and post-encoding resting state spatial maps onto baseline. We identified both persistent and plastic components of the overall brain functional configuration between baseline and post-encoding. While FC patterns within executive, default mode, and cerebellar circuits persisted from baseline to post-encoding, FC within the visual circuit changed. A significant session × performance interaction characterized medial temporal lobe and prefrontal cortex FC with the visual circuit, as well as thalamic FC within the executive control system. Findings reveal early-stage FC changes at the system-level subsequent to a learning experience and associated with inter-individual variation in memory performance.

Shared and distinct brain fMRI response during performance of working memory tasks in adult patients with schizophrenia and major depressive disorder

Working memory (WM) impairments are common features of psychiatric disorders. A systematic meta-analysis was performed to determine common and disorder-specific brain fMRI response during performance of WM tasks in patients with SZ and patients with MDD relative to healthy controls (HC). Thirty-four published fMRI studies of WM in patients with SZ and 18 published fMRI studies of WM in patients with MDD, including relevant HC, were included in the meta-analysis. In both SZ and MDD there was common stronger fMRI response in right medial prefrontal cortex (MPFC) and bilateral anterior cingulate cortex (ACC), which are part of the default mode network (DMN). The effects were of greater magnitude in SZ than MDD, especially in prefrontal-temporal-cingulate-striatal-cerebellar regions. In addition, a disorder-specific weaker fMRI response was observed in right middle frontal gyrus (MFG) in MDD, relative to HC. For both SZ and MDD a significant correlation was observed between the severity of clinical symptoms and lateralized fMRI response relative to HC. These findings indicate that there may be common and distinct anomalies in brain function underlying deficits in WM in SZ and MDD, which may serve as a potential functional neuroimaging-based diagnostic biomarker with value in supporting clinical diagnosis, measuring illness severity and assessing the efficacy of treatments for SZ and MDD at the brain level.

Functional Delineation of Prefrontal Networks Underlying Working Memory in Schizophrenia: A Cross-data-set Examination

BACKGROUND

Working memory (WM) impairment in schizophrenia substantially impacts functional outcome. Although the dorsolateral pFC has been implicated in such impairment, a more comprehensive examination of brain networks comprising pFC is warranted. The present research used a whole-brain, multi-experiment analysis to delineate task-related networks comprising pFC. Activity was examined in schizophrenia patients across a variety of cognitive demands.

METHODS

One hundred schizophrenia patients and 102 healthy controls completed one of four fMRI tasks: a Sternberg verbal WM task, a visuospatial WM task, a Stroop set-switching task, and a thought generation task (TGT). Task-related networks were identified using multi-experiment constrained PCA for fMRI. Effects of task conditions and group differences were examined using mixed-model ANOVA on the task-related time series. Correlations between task performance and network engagement were also performed.

RESULTS

Four spatially and temporally distinct networks with pFC activation emerged and were postulated to subserve (1) internal attention, (2) auditory-motor attention, (3) motor responses, and (4) task energizing. The "energizing" network-engaged during WM encoding and diminished in patients-exhibited consistent trend relationships with WM capacity across different data sets. The dorsolateral-prefrontal-cortex-dominated "internal attention" network exhibited some evidence of hypoactivity in patients, but was not correlated with WM performance.

CONCLUSIONS

Multi-experiment analysis allowed delineation of task-related, pFC-anchored networks across different cognitive constructs. Given the results with respect to the early-responding "energizing" network, WM deficits in schizophrenia may arise from disruption in the "energization" process described by Donald Stuss' model of pFC functions.

Electrophysiological Correlates of Rodent Default-Mode Network Suppression Revealed by Large-Scale Local Field Potential Recordings

The default-mode network (DMN) in humans consists of a set of brain regions that, as measured with functional magnetic resonance imaging (fMRI), show both intrinsic correlations with each other and suppression during externally oriented tasks. Resting-state fMRI studies have previously identified similar patterns of intrinsic correlations in overlapping brain regions in rodents (A29C/posterior cingulate cortex, parietal cortex, and medial temporal lobe structures). However, due to challenges with performing rodent behavior in an MRI machine, it is still unclear whether activity in rodent DMN regions are suppressed during externally oriented visual tasks. Using distributed local field potential measurements in rats, we have discovered that activity in DMN brain regions noted above show task-related suppression during an externally oriented visual task at alpha and low beta-frequencies. Interestingly, this suppression (particularly in posterior cingulate cortex) was linked with improved performance on the task. Using electroencephalography recordings from a similar task in humans, we identified a similar suppression of activity in posterior cingulate cortex at alpha/low beta-frequencies. Thus, we have identified a common electrophysiological marker of DMN suppression in both rodents and humans. This observation paves the way for future studies using rodents to probe circuit-level functioning of DMN function.

SIGNIFICANCE

Here we show that alpha/beta frequency oscillations in rats show key features of DMN activity, including intrinsic correlations between DMN brain regions, task-related suppression, and interference with attention/decision-making. We found similar task-related suppression at alpha/low beta-frequencies of DMN activity in humans.

Working memory in schizophrenia: The role of the locus coeruleus and its relation to functional brain networks

Evidence suggests functional brain networks, especially the executive control network (ECN) and default mode network (DMN), to be abnormal in schizophrenia. Dysfunctions within the locus coeruleus (LC)-noradrenaline (NE) system, which is supposed to be pivotal to modulate neuronal network activation during executive control (e.g., working memory function), are also considered to play a vital role in the occurrence of positive (e.g., hallucinatory) or negative (e.g., inattentive) symptoms in these patients. In the present study, we sought to shed further light on the role of the LC-NE system in patients with schizophrenia. More specifically, we wanted to improve our understanding of the relationship and possible disturbances of the ECN and DMN during a working memory task in patients. A total of 58 healthy control subjects and 40 medicated patients with schizophrenia were investigated using a working memory 3-back task during functional magnetic resonance imaging. Main findings of our present study were differential dynamics of ECN and DMN blood oxygenation level-dependent (BOLD) activations with increasing task demands in both patients and controls. Moreover, we found increased BOLD activation in the LC in patients compared to controls in the interaction contrast between groups and conditions. LC BOLD activation significantly correlated with both, the main hub of the ECN, that is, the dorsolateral prefrontal cortex, and of the DMN, that is, the posterior cingulate cortex. Thus, the LC-NE system seems to be crucial in modulating neuronal network activity in a 3-back working memory task and might significantly contribute to cognitive impairments in schizophrenia.

Abnormal dynamics of functional connectivity in first-episode and treatment-naive patients with obsessive-compulsive disorder

AIM

The aim of this study was to assess the whole-brain dynamic functional connectivity of first-episode and treatment-naive patients with obsessive-compulsive disorder (OCD) and to investigate the clinical correlations of abnormal changes in dynamic functional connectivity.

METHODS

Twenty-nine patients in our hospital diagnosed with first-episode OCD and 29 healthy controls matched for age, sex, and education were included in our study. Resting-state functional magnetic resonance imaging scans were performed on a 3.0-Tesla magnetic resonance scanner in our hospital. Three temporal metrics of connectivity state expression were calculated: (i) fraction of time; (ii) mean dwell time; and (iii) number of transitions. The Yale-Brown Obsessive-Compulsive Scale was used to assess the severity of OCD symptoms.

RESULTS

In the comparison of dynamic functional connectivity indicators, we found that there were significant differences in the number of transitions among the four functional connectivity states but no significant differences in the fraction of time or the mean dwell time. The total Yale-Brown Obsessive-Compulsive Scale score was positively correlated with the number of transitions. In the validation analysis, when the size of the sliding window changed, there was still a significant difference in the number of transitions between OCD patients and healthy controls.

CONCLUSION

The functional networks of OCD patients have lost the correct dynamic rhythm, which may be considered as a potential marker for OCD and for new directions for its intervention.

Cognitive functions relating to aberrant interactions between task-positive and task-negative networks: Resting fMRI study of patients with schizophrenia

Brain functional connectivity in the resting-state represents intrinsic functional states and correlates with cognitive performance. In patients with schizophrenia, reports on the relationships between forms of functional disconnectivity in local areas and cognitive disability have used resting-state functional magnetic resonance imaging data. Meanwhile, cognitive deficits in relation to inter-network forms of functional connectivity on a large scale are not well understood. This study examines cognitive functions in relation to the number of resting-state inter-network forms of functional connectivity focusing on task-positive networks (fronto-parietal network [FPN] and cingulo-opercular network [CON]) and task-negative network (default mode network [DMN]). We compare patients with schizophrenia (SCH group) and healthy controls (HC group). We conducted a functional network analysis by applying graph theory and evaluated cognitive functions using the Brief Assessment of Cognition in Schizophrenia. The number of forms of functional connectivity between FPN and DMN and between CON and DMN were significantly higher in SCH group than in HC group, and those in SCH group were also weakly correlated with their attention scores. It is suggested that fewer than typical functional segregations between task-positive and task-negative networks in SCH group relate to inefficient distribution of cognitive resources and low attentional abilities.

Regional GABA Concentrations Modulate Inter-network Resting-state Functional Connectivity

Coordinated activity within and differential activity between large-scale neuronal networks such as the default mode network (DMN) and the control network (CN) is a critical feature of brain organization. The CN usually exhibits activations in response to cognitive tasks while the DMN shows deactivations; in addition, activity between the two networks is anti-correlated at rest. To address this issue, we used functional MRI to measure whole-brain BOLD signal during resting-state and task-evoked conditions, and MR spectroscopy (MRS) to quantify GABA and glutamate concentrations, in nodes within the DMN and CN (MPFC and DLPFC, respectively) in 19 healthy individuals at 3 Tesla. We found that GABA concentrations in the MPFC were significantly associated with DMN deactivation during a working memory task and with anti-correlation between DMN and CN at rest and during task performance, while GABA concentrations in the DLPFC weakly modulated DMN-CN anti-correlation in the opposite direction. Highlighting specificity, glutamate played a less significant role related to brain activity. These findings indicate that GABA in the MPFC is potentially involved in orchestrating between-network brain activity at rest and during task performance.

Resting-State Functional Network Organization Is Stable Across Adolescent Development for Typical and Psychosis Spectrum Youth

BACKGROUND

Resting-state functional neuroimaging captures large-scale network organization; whether this organization is intact or disrupted during adolescent development across the psychosis spectrum is unresolved. We investigated the integrity of network organization in psychosis spectrum youth and those with first episode psychosis (FEP) from late childhood through adulthood.

METHODS

We analyzed data from Philadelphia Neurodevelopmental Cohort (PNC; typically developing = 450, psychosis spectrum = 273, 8-22 years), a longitudinal cohort of typically developing youth (LUNA; N = 208, 1-3 visits, 10-25 years), and a sample of FEP (N = 39) and matched controls (N = 34). We extracted individual time series and calculated correlations from brain regions and averaged them for 4 age groups: late childhood, early adolescence, late adolescence, adulthood. Using multiple analytic approaches, we assessed network stability across 4 age groups, compared stability between controls and psychosis spectrum youth, and compared group-level network organization of FEP to controls. We explored whether variability in cognition or clinical symptomatology was related to network organization.

RESULTS

Network organization was stable across the 4 age groups in the PNC and LUNA typically developing youth and PNC psychosis spectrum youth. Psychosis spectrum and typically developing youth had similar functional network organization during all age ranges. Network organization was intact in PNC youth who met full criteria for psychosis and in FEP. Variability in cognitive functioning or clinical symptomatology was not related to network organization in psychosis spectrum youth or FEP.

DISCUSSION

These findings provide rigorous evidence supporting intact functional network organization in psychosis risk and psychosis from late childhood through adulthood.

Altered brain functional networks in Internet gaming disorder: independent component and graph theoretical analysis under a probability discounting task

OBJECTIVES

Internet gaming disorder (IGD) is becoming a matter of concern around the world. However, the neural mechanism underlying IGD remains unclear. The purpose of this paper is to explore the differences between the neuronal network of IGD participants and that of recreational Internet game users (RGU).

METHODS

Imaging and behavioral data were collected from 18 IGD participants and 20 RGU under a probability discounting task. The independent component analysis (ICA) and graph theoretical analysis (GTA) were used to analyze the data.

RESULTS

Behavioral results showed the IGD participants, compared to RGU, prefer risky options to the fixed ones and spent less time in making risky decisions. In imaging results, the ICA analysis revealed that the IGD participants showed stronger functional connectivity (FC) in reward circuits and executive control network, as well as lower FC in anterior salience network (ASN) than RGU; for the GTA results, the IGD participants showed impaired FC in reward circuits and ASN when compared with RGU.

CONCLUSIONS

These results suggest that IGD participants were more sensitive to rewards, and they were more impulsive in decision-making as they could not control their impulsivity effectively. This might explain why IGD participants cannot stop their gaming behaviors even when facing severe negative consequences.

Frontal lobe functioning during a simple response conflict task in first-episode psychosis and its relationship to treatment response

Prior functional magnetic resonance imaging (fMRI) studies have investigated the neural mechanisms underlying cognitive control in patients with psychosis with findings of both hypo- and hyperfrontality. One factor that may contribute to inconsistent findings is the use of complex and polyfactorial tasks to investigate frontal lobe functioning. In the current study we employed a simple response conflict task during fMRI to examine differences in brain activation between patients experiencing their first-episode of psychosis (n = 33) and age- and sex-matched healthy volunteers (n = 33). We further investigated whether baseline brain activation among patients predicted changes in symptom severity and treatment response following 12 weeks of controlled antipsychotic treatment. During the task subjects were instructed to press a response button on the same side or opposite side of a circle that appeared on either side of a central fixation point. Imaging data revealed that for the contrast of opposite-side vs. same-side, patients showed significantly greater activation compared with healthy volunteers in the anterior cingulate cortex and intraparietal sulcus. Among patients, greater baseline anterior cingulate cortex, temporal-parietal junction, and superior temporal cortex activation predicted greater symptom reduction and therapeutic response following treatment. All findings remained significant after covarying for task performance. Intact performance on this relatively parsimonious task was associated with frontal hyperactivity suggesting the need for patients to utilize greater neural resources to achieve task performance comparable to healthy individuals. Moreover, frontal hyperactivity observed using a simple fMRI task may provide a biomarker for predicting treatment response in first-episode psychosis.

Functional fractionation of default mode network in first episode schizophrenia

A disruption in the connectivity between brain regions may underlie the core pathology in schizophrenia. One of the most consistent observations in human functional imaging is a network of brain regions referred to as the default network (DMN) that contains core subsystem, the dorsomedial prefrontal cortex (dMPFC) subsystem and the medial temporal lobe (MTL) subsystem, with differential contributions. The goal of this study was to examine abnormalities of different DMN subsystems in first episode schizophrenia and associations between these abnormalities and individual psychopathology. We recruited 203 patients and 131 healthy controls. A seed-based resting-state functional connectivity (RSFC) analysis on the 2D surface was conducted. Individual DMN functional connectivity matrices were then obtained by calculating spatial correlations between pairs of RSFC maps, characterizing the functional fractionation of the DMN. Patients showed patterns similar to controls but markedly reduced strength of DMN fractionation, with the degree centrality of the MTL subsystem significantly reduced, including the posterior inferior parietal lobule (pIPL), parahippocampal cortex (PHC) and lateral temporal cortex (LTC). Patients also exhibited hypo-connectivity within the MTL subsystem and between the MTL and dMPFC subsystems. Clinical symptoms were negatively correlated with degree centrality of LTC, pIPL and PHC in patients. Hyper-fractionation of different DMN components implied that communication and coordination throughout the dissociated components of the DMN are functionally over-segregated in schizophrenia. The associations between the hyper-fractionation with clinical symptoms suggest a role of the high fractionation in the DMN in the abnormal neuropathology observed in schizophrenia.

Effects of Amisulpride Adjunctive Therapy on Working Memory and Brain Metabolism in the Frontal Cortex of Patients with Schizophrenia: A Preliminary Positron Emission Tomography/Computerized Tomography Investigation

Objective

Dopamine plays a significant role in working memory by acting as a key neuromodulator between brain networks. Additionally, treatment of patients with schizophrenia using amisulpride, a pure dopamine class 2/3 receptor antagonist, improves their clinical symptoms with fewer side effects. We hypothesized that patients with schizophrenia treated with amisulpride and aripiprazole show increased working memory and glucose metabolism compared with those treated with cognitive behavioral therapy (CBT) and aripiprazole instead.

Methods

Sixteen patients with schizophrenia (eight in the amisulpride group [aripiprazole+amisulpride] and eight in the CBT group [aripiprazole+CBT]) and 15 age- and sex-matched healthy control subjects were recruited for a 12-week-long prospective trial. An [18F]-fluorodeoxyglucose-positron emission tomography/computerized tomography scanner was used to acquire the images.

Results

After 12 weeks of treatment, the amisulpride group showed greater improvement in the Letter-Number Span scores than the CBT group. Additionally, although brain metabolism in the left middle frontal gyrus, left occipital lingual gyrus, and right inferior parietal lobe was increased in all patients with schizophrenia, the amisulpride group exhibited a greater increase in metabolism in both the right superior frontal gyrus and right frontal precentral gyrus than the CBT group.

Conclusion

This study suggests that a small dose of amisulpride improves the general psychopathology, working memory performance, and brain glucose metabolism of patients with schizophrenia treated with aripiprazole.

Impaired prefrontal functional connectivity associated with working memory task performance and disorganization despite intact activations in schizophrenia

Working memory (WM) deficits are key features of schizophrenia and are associated with significant functional impairment. The precise mechanisms of WM and their relationship between WM deficits with other clinical symptoms of schizophrenia remain unclear. Contemporary models propose that WM requires synchronous activity across brain regions within a distributed network, including lateral prefrontal cortex (PFC) and task-relevant posterior sensory cortical regions. This suggests that WM deficits in patients may be due to PFC functional connectivity (FC) impairments rather than activation impairments per se. We tested this hypothesis by measuring the magnitude of FC between lateral PFC and visual cortex and univariate activations within these regions during visual WM. We found decreased FC in patients compared to healthy subjects in the context of similar levels of univariate activity. Furthermore, this decreased FC was associated with task performance and clinical symptomatology in patients. The magnitude of FC, particularly during the delay period, was positively correlated with WM task accuracy, while FC during cue was inversely correlated with severity of disorganization. Taken together, these results suggest that impairment in lateral PFC FC is a key aspect of information processing impairment in patients with schizophrenia, and may be a sensitive index of altered neurophysiology.

Brain networks of happiness: dynamic functional connectivity among the default, cognitive and salience networks relates to subjective well-being

Subjective well-being (SWB) reflects the cognitive and emotional evaluations of an individual's life and plays an important role in individual's success in health, work and social relationships. Although previous studies have revealed the spontaneous brain activity underlying SWB, little is known about the relationship between brain network interactions and SWB. The present study investigated the static and dynamic functional connectivity among large-scale brain networks during resting state functional magnetic resonance imaging (fMRI) in relation to SWB in two large independent datasets. The results showed that SWB is negatively correlated with static functional connectivity between the salience network (SN) and the anterior default mode network (DMN). Dynamic functional network connectivity (dFNC) analysis found that SWB is negatively correlated with the fraction of time that participants spent in a brain state characterized by weak cross-network connectivity (between the DMN, SN and frontal-parietal network [FPN]) and strong within-network connectivity (within the DMN and within the FPN). This connectivity profile may account for the good mental adaptability and flexible information communication of people with high levels of SWB. The dFNC results were well replicated with different analysis parameters and further validated in an independent sample. Taken together, these findings reveal that the dynamic interaction between networks involved in self-reflection, emotional regulation and cognitive control underlies SWB.

Identification of brain regions associated with working memory deficit in schizophrenia

Background: Schizophrenia, a severe psychological disorder, shows symptoms such as hallucinations and delusions. In addition, patients with schizophrenia often exhibit a deficit in working memory which adversely impacts the attentiveness and the behavioral characteristics of a person. Although several clinical efforts have already been made to study working memory deficit in schizophrenia, in this paper, we investigate the applicability of a machine learning approach for identification of the brain regions that get affected by schizophrenia leading to the dysfunction of the working memory.

Methods: We propose a novel scheme for identification of the affected brain regions from functional magnetic resonance imaging data by deploying group independent component analysis in conjunction with feature extraction based on statistical measures, followed by sequential forward feature selection. The features that show highest accuracy during the classification between healthy and schizophrenia subjects are selected.

Results: This study reveals several brain regions like cerebellum, inferior temporal gyrus, superior temporal gyrus, superior frontal gyrus, insula, and amygdala that have been reported in the existing literature, thus validating the proposed approach. We are also able to identify some functional changes in the brain regions, such as Heschl gyrus and the vermian area, which have not been reported in the literature involving working memory studies amongst schizophrenia patients.

Conclusions: As our study confirms the results obtained in earlier studies, in addition to pointing out some brain regions not reported in earlier studies, the findings are likely to serve as a cue for clinical investigation, leading to better medical intervention.

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

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

Effectiveness of the prefrontal repetitive transcranial magnetic stimulation on cognitive profiles in depression, schizophrenia, and Alzheimer's disease: A systematic review

Repetitive transcranial magnetic stimulation (rTMS) is an effective clinical intervention for various neuropsychiatric diseases. However, it is still unclear whether rTMS has an effect on cognitive functioning. In this review, we aimed to systematically evaluate the cognitive effects of rTMS in depression, schizophrenia, and Alzheimer's disease. We searched PubMed (1996-2018) under the set terms to review randomized controlled trials (RCT) to examine the effectiveness of rTMS administered to the dorsolateral prefrontal cortex (DLPFC) and evaluated cognitive functions in patients with depression, schizophrenia, and Alzheimer's disease. Two authors reviewed each article and came to consensus on the inclusion and exclusion criteria. All eligible studies were reviewed, duplicates were removed, and data were extracted individually. The search identified 579 articles, 31 of which met inclusion and exclusion criteria. Among them, 15 were conducted in patients with depression, 11 in patients with schizophrenia, and 5 in patients with Alzheimer's disease. Specifically, 6 studies demonstrated a significant improvement of executive function across these diseases. Further, no evidence for cognitive adverse effects was found in these included rTMS studies. Although the heterogeneity between studies in terms of cognitive measures applied, stimulation parameters, and participants limits the ability to generalize conclusions, this review demonstrated that prefrontal rTMS could exert pro-cognitive effects on executive function and attention in some patients with depression but inconsistent cognitive impacts in any of the examined domains especially in patients with schizophrenia and Alzheimer's disease. The results warrant further rTMS studies that include systematic assessment of cognition across various neuropsychiatric diseases.

PET neuroimaging reveals histone deacetylase dysregulation in schizophrenia

BACKGROUND

Patients with schizophrenia (SCZ) experience chronic cognitive deficits. Histone deacetylases (HDACs) are enzymes that regulate cognitive circuitry; however, the role of HDACs in cognitive disorders, including SCZ, remains unknown in humans. We previously determined that HDAC2 mRNA levels were lower in dorsolateral prefrontal cortex (DLPFC) tissue from donors with SCZ compared with controls. Here we investigated the relationship between in vivo HDAC expression and cognitive impairment in patients with SCZ and matched healthy controls using [11C]Martinostat positron emission tomography (PET).

METHODS

In a case-control study, relative [11C]Martinostat uptake was compared between 14 patients with SCZ or schizoaffective disorder (SCZ/SAD) and 17 controls using hypothesis-driven region-of-interest analysis and unbiased whole brain voxel-wise approaches. Clinical measures, including the MATRICS consensus cognitive battery, were administered.

RESULTS

Relative HDAC expression was lower in the DLPFC of patients with SCZ/SAD compared with controls, and HDAC expression positively correlated with cognitive performance scores across groups. Patients with SCZ/SAD also showed lower relative HDAC expression in the dorsomedial prefrontal cortex and orbitofrontal gyrus, and higher relative HDAC expression in the cerebral white matter, pons, and cerebellum compared with controls.

CONCLUSIONS

These findings provide in vivo evidence of HDAC dysregulation in patients with SCZ and suggest that altered HDAC expression may impact cognitive function in humans.

FUNDING

National Institute of Mental Health (NIMH), Brain and Behavior Foundation, Massachusetts General Hospital (MGH), Athinoula A. Martinos Center for Biomedical Imaging, National Institute of Biomedical Imaging and Bioengineering (NIBIB), NIH Shared Instrumentation Grant Program.

Group independent component analysis reveals alternation of right executive control network in Internet gaming disorder

OBJECTIVE

Previous studies have demonstrated that individuals with Internet gaming disorder (IGD) showed attentional bias toward gaming-related cues and exhibited impaired executive functions. The purpose of this study was to explore the alternations in related functional brain networks underlying attentional bias in IGD subjects.

METHODS

Eighteen IGD subjects and 19 healthy controls (HC) were scanned with functional magnetic resonance imaging while they were performing an addiction Stroop task. Networks of functional connectivity were identified using group independent component analysis (ICA).

RESULTS

ICA identified 4 functional networks that showed differences between the 2 groups, which were related to the right executive control network and visual related networks in our study. Within the right executive control network, in contrast to controls, IGD subjects showed increased functional connectivity in the temporal gyrus and frontal gyrus, and reduced functional connectivity in the posterior cingulate cortex, temporal gyrus, and frontal gyrus.

CONCLUSION

These findings suggest that IGD is related to abnormal functional connectivity of the right executive control network, and may be described as addiction-related abnormally increased cognitive control processing and diminished response inhibition during an addiction Stroop task. The results suggest that IGD subjects show increased susceptibility towards gaming-related cues but weakened strength of inhibitory control.

Intrinsic network connectivity and own body perception in gender dysphoria

Gender dysphoria (GD) is characterized by incongruence between one's identity and gender assigned at birth. The biological mechanisms of GD are unclear. We investigated brain network connectivity patterns involved in own body perception in the context of self in GD. Twenty-seven female-to-male (FtM) individuals with GD, 27 male controls, and 27 female controls underwent resting state fMRI. We compared functional connections within intrinsic connectivity networks involved in self-referential processes and own body perception -default mode network (DMN) and salience network - and visual networks, using independent components analyses. Behavioral correlates of network connectivity were also tested using self-perception ratings while viewing own body images morphed to their sex assigned at birth, and to the sex of their gender identity. FtM exhibited decreased connectivity of anterior and posterior cingulate and precuneus within the DMN compared with controls. In FtM, higher "self" ratings for bodies morphed towards the sex of their gender identity were associated with greater connectivity of the anterior cingulate within the DMN, during long viewing times. In controls, higher ratings for bodies morphed towards their gender assigned at birth were associated with right insula connectivity within the salience network, during short viewing times. Within visual networks FtM showed weaker connectivity in occipital and temporal regions. Results suggest disconnectivity within networks involved in own body perception in the context of self in GD. Moreover, perception of bodies in relation to self may be reflective rather than reflexive, as a function of mesial prefrontal processes. These may represent neurobiological correlates to the subjective disconnection between perception of body and self-identification.

The Motivation-Based Promotion of Proactive Control: The Role of Salience Network

It has been shown that reward motivation can facilitate proactive control, a cognitive control mode that is characterized of prior preparation and sustained holding of the goal-relevant information in working memory. However, it remains to be established the neural networks that may be involved in this promotion effect. In this study, participants underwent the AX-Continuous Performance Task (AX-CPT) that measures relative proactive control during functional magnetic resonance imaging (fMRI) scanning. We employed independent component analysis to decompose multiple brain networks and identified the task related network. Results showed that the salience network (SN) was engaged in the AX-CPT protocol. Importantly, our data demonstrated that reward modulated the association between task engagement of SN and proactive control, whereby the positive correlation was particularly observed in the reward condition. Moreover, reward modulated task engagement of the SN in a proactive manner, which may contribute to the behavioral proactive performance. Overall, our data suggest the involvement of SN in the reward facilitation effect of proactive control.

Differentiating between clinical and behavioral phenotypes in first-episode psychosis during maintenance of visuospatial working memory

INTRODUCTION

We probed the neural basis of working memory in individuals with first episode of psychosis (FEP) and assessed how these neural abnormalities are associated with behavioral performance and/or core to psychosis pathophysiology.

METHODS

FEP (N=35) and matched controls (N=25) performed a visuospatial working memory task during fMRI acquisition. We isolated neural activity during the maintenance period and examined neural activity within regions typically engaged during a working memory task. Functional connectivity estimates were derived using psychophysiological interaction analysis. We examined correlations between brain function and behavioral performance and clinical symptomatology.

RESULTS

FEP had reduced accuracy and slower reaction times compared to controls (p<0.05, q<0.05). During the maintenance period, FEP exhibited reduced right dorsolateral prefrontal cortex (DLPFC) activation compared to controls (p=0.007, q=0.01), even when behavioral performance was matched between groups (p=0.01, q=0.03). Unlike controls, FEP failed to show increased dorsal anterior cingulate (dACC) activity with increased load level (p=0.02, q=0.06). Compared to controls, FEP showed increased negative DLPFC-dACC coupling during the maintenance period (p=0.05). Increased DLPFC activation was significantly associated with greater negative symptoms (p<0.005, q=0.02), while greater dACC activation was significantly associated with better performance in FEP (p<0.05, q<0.17).

CONCLUSION

WM impairment in psychosis may be specific to abnormalities in the ability of frontal systems processing executive commands (DLPFC) and monitoring performance (dACC) during the maintenance of information. Our results add to accumulating evidence indicating that DLPFC abnormalities may be core to psychosis psychopathology. We also provide new insights regarding how DLPFC abnormalities may undermine dACC processing during the maintenance of information.

Incentives facilitate developmental improvement in inhibitory control by modulating control-related networks

Adolescence is a period of heightened sensitivity to incentives and relatively weak cognitive control, which may contribute to risky behaviors. Studies of brain activity have generally identified greater activation of the ventral striatum to rewards and less activation of prefrontal regions during control tasks in adolescents compared to adults. Little is known, however, about age-related changes in the functional brain networks underlying incentive processing and cognitive control. This cross-sectional study characterized the effects of incentives on inhibitory control during an oculomotor task using whole-brain functional connectivity analyses. During an fMRI scan, one hundred forty typically developing individuals completed an incentivized antisaccade task consisting of incentive cue, preparation, and response phases. We found that task modulation of control networks increased gradually from childhood to adulthood, whereas a network including ventral striatum and ventromedial prefrontal cortex displayed an adolescent-specific peak in response to the receipt of outcomes, consistent with dual-systems models. Notably, however, greater modulation of salience and motor networks during the preparation phase mediated age-related improvements in antisaccade accuracy, whereas adolescent enhancement of value-related circuitry did not. Relative to neutral cues, both reward and loss cues enhanced task-related connectivity of the salience network when preparing to inhibit a saccade. Altogether, our findings suggest that incentives facilitate inhibitory control by enhancing the salience of one's responses and that over development, the recruitment of functional networks involved in saliency and motor preparation supports better performance.

Classification of multi-site MR images in the presence of heterogeneity using multi-task learning

With the advent of Big Data Imaging Analytics applied to neuroimaging, datasets from multiple sites need to be pooled into larger samples. However, heterogeneity across different scanners, protocols and populations, renders the task of finding underlying disease signatures challenging. The current work investigates the value of multi-task learning in finding disease signatures that generalize across studies and populations. Herein, we present a multi-task learning type of formulation, in which different tasks are from different studies and populations being pooled together. We test this approach in an MRI study of the neuroanatomy of schizophrenia (SCZ) by pooling data from 3 different sites and populations: Philadelphia, Sao Paulo and Tianjin (50 controls and 50 patients from each site), which posed integration challenges due to variability in disease chronicity, treatment exposure, and data collection. Some existing methods are also tested for comparison purposes. Experiments show that classification accuracy of multi-site data outperformed that of single-site data and pooled data using multi-task feature learning, and also outperformed other comparison methods. Several anatomical regions were identified to be common discriminant features across sites. These included prefrontal, superior temporal, insular, anterior cingulate cortex, temporo-limbic and striatal regions consistently implicated in the pathophysiology of schizophrenia, as well as the cerebellum, precuneus, and fusiform, middle temporal, inferior parietal, postcentral, angular, lingual and middle occipital gyri. These results indicate that the proposed multi-task learning method is robust in finding consistent and reliable structural brain abnormalities associated with SCZ across different sites, in the presence of multiple sources of heterogeneity.

Polymorphism in schizophrenia risk gene MIR137 is associated with the posterior cingulate Cortex's activation and functional and structural connectivity in healthy controls

MIR137 gene has been repeatedly reported as a schizophrenia risk gene in genome-wide association studies (GWAS). A polymorphism (rs1625579) at the MIR137 gene has been associated with both neural activation and behavioral performance during a working memory task. This study examined MIR137's associations with task-related (N-back working memory) fMRI, resting state fMRI, and diffusion tensor images (DTI) data in 177 healthy adults. We found less deactivation of the PCC in risk allele homozygotes (TT) as compared to the GT heterozygotes (cluster size = 630 voxels, cluster level P_FWE < 0.001) during the N-back task, which replicated previous findings. Using the identified cluster within the PCC as the seed, we further found decreased functional connectivity between the PCC and the anterior cingulate cortex and its adjacent medial prefrontal cortex (ACC/MPFC) in risk allele homozygotes during both resting state (cluster size = 427 voxels, cluster level P_FWE = 0.001) and the N-back task (cluster size = 73 voxels, cluster level P_FWE = 0.05). Finally, an analysis of our DTI data showed decreased white matter integrity of the posterior cingulum in risk allele homozygotes (cluster size = 214 voxels, cluster level P_FWE = 0.03). Taken together, rs1625579 seems to play an important role in both functional and structural connectivity between the PCC and the ACC/MPFC, which may serve as the brain mechanisms for the link between rs1625579 and schizophrenia.

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This study replicated the association between the risk allele of rs1625579 and altered activations at the PCC.

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This study found decreased functional connectivity between the PCC and the ACC/MPFC in the risk allele homozygotes.

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This study found decreased FA value in the posterior cingulum in the risk allele homozygotes.

A novel fuzzy rough selection of non-linearly extracted features for schizophrenia diagnosis using fMRI

BACKGROUND AND OBJECTIVES

Schizophrenia is a severe brain disorder primarily diagnosed through externally observed behavioural symptoms due to the dearth of established clinical tests. Functional magnetic resonance imaging (fMRI) can capture the distortions caused by schizophrenia in the brain activation. Hence, it can be useful for developing a decision model that performs computer-aided diagnosis of schizophrenia. But, fMRI data is huge in dimension. Therefore dimension reduction is indispensable. It is additionally required to identify the discriminative brain regions. Hence, we aim to build an effective decision model that incorporates suitable dimension reduction and also identifies discriminative brain regions.

METHODS

We propose a three-phase dimension reduction. First phase involves spatially-constrained fuzzy clustering of 3-dimensional spatial maps (obtained from general linear model and independent component analysis). In the second phase, non-linear features are extracted from each cluster using a generalized discriminant analysis. In the third phase, a novel fuzzy rough feature selection is proposed. The features obtained after the third phase are used for learning a decision model by the help of support vector machine classifier. This complete method is implemented within leave-one-out cross-validation on two balanced datasets (respectively acquired on 1.5Tesla and 3Tesla scanners). Both these datasets are created using Function Biomedical Informatics Research Network multisite data and contain fMRI data acquired during auditory oddball task performed by age-matched schizophrenia patients and healthy subjects. A permutation test is also carried out to ensure that no bias is involved in the learning.

RESULTS

The results indicate that the proposed method achieves maximum classification accuracy of 97.1% and 98.0% for the two datasets respectively. The proposed method outperforms the state-of-the-art methods. The results of the permutation test show that p-values are lesser than the significance level i.e. 0.05. Therefore, the classifier has found a significant class structure and does not involve any bias. Further, discriminative brain regions are identified and are in agreement with the findings in related literature.

CONCLUSION

The proposed method is able to derive suitable non-linear features and the related brain regions for effective computer-aided diagnosis. The fuzzy and rough set based approaches help in handling uncertainty and ambiguity in real data.

Biochemical, physiological and clinical effects of l-methylfolate in schizophrenia: a randomized controlled trial

Folic acid supplementation confers modest benefit in schizophrenia, but its effectiveness is influenced by common genetic variants in the folate pathway that hinder conversion to its active form. We examined physiological and clinical effects of l-methylfolate, the fully reduced and bioactive form of folate, in schizophrenia. In this randomized, double-blind trial, outpatients with schizophrenia (n=55) received l-methylfolate 15 mg or placebo for 12 weeks. Patients were maintained on stable doses of antipsychotic medications. The pre-defined primary outcome was change in plasma methylfolate at 12 weeks. Secondary outcomes included change in symptoms (Positive and Negative Syndrome Scale (PANSS), Scale for Assessment of Negative Symptoms, Calgary Depression Scale for Schizophrenia), cognition (Measurement and Treatment Research to Improve Cognition in Schizophrenia composite) and three complementary magnetic resonance imaging measures (working memory-related activation, resting connectivity, cortical thickness). Primary, mixed model, intent-to-treat analyses covaried for six genetic variants in the folate pathway previously associated with symptom severity and/or response to folate supplementation. Analyses were repeated without covariates to evaluate dependence on genotype. Compared with placebo, l-methylfolate increased plasma methylfolate levels (d=1.00, P=0.0009) and improved PANSS Total (d=0.61, P=0.03) as well as PANSS Negative and General Psychopathology subscales. Although PANSS Total and General Psychopathology changes were influenced by genotype, significant PANSS Negative changes occurred regardless of genotype. No treatment differences were seen in other symptom rating scales or cognitive composite scores. Patients receiving l-methylfolate exhibited convergent changes in ventromedial prefrontal physiology, including increased task-induced deactivation, altered limbic connectivity and increased cortical thickness. In conclusion, l-methylfolate supplementation was associated with salutary physiological changes and selective symptomatic improvement in this study of schizophrenia patients, warranting larger clinical trials. ClinicalTrials.gov, NCT01091506.

Not single brain areas but a network is involved in language: Applications in presurgical planning

OBJECTIVES

Language is an important human function, and is a determinant of the quality of life. In conditions such as brain lesions, disruption of the language function may occur, and lesion resection is a solution for that. Presurgical planning to determine the language-related brain areas would enhance the chances of language preservation after the operation; however, availability of a normative language template is essential.

PATIENTS AND METHODS

In this study, using data from 60 young individuals who were meticulously checked for mental and physical health, and using fMRI and robust imaging and data analysis methods, functional brain maps for the language production, perception and semantic were produced.

RESULTS

The obtained templates showed that the language function should be considered as the product of the collaboration of a network of brain regions, instead of considering only few brain areas to be involved in that.

CONCLUSION

This study has important clinical applications, and extends our knowledge on the neuroanatomy of the language function.

Dynamic Functional Connectivity States Reflecting Psychotic-like Experiences

BACKGROUND

Psychotic-like experiences (PLEs) are associated with lower social and occupational functioning, and lower executive function. Emerging evidence also suggests that PLEs reflect neural dysfunction resembling that of psychotic disorders.

METHODS

The present study examined dynamic connectivity related to a measure of PLEs derived from the Achenbach Adult Self-Report, in an otherwise-healthy sample of adults from the Human Connectome Project. A total of 76 PLE-endorsing and 153 control participants were included in the final sample. To characterize network dysfunction, dynamic connectivity states were examined across large-scale resting-state networks using dynamic conditional correlation and k-means clustering.

RESULTS

Three dynamic states were identified. The PLE-endorsing group spent more time than the control group in state 1, a state reflecting hyperconnectivity within visual regions and hypoconnectivity within the default mode network, and less time in state 2, a state characterized by robust within-network connectivity for all networks and strong default mode network anticorrelations. Within the PLE-endorsing group, worse executive function was associated with more time spent in and more transitions into state 1 and less time spent in and fewer transitions into state 3.

CONCLUSIONS

PLEs are associated with altered large-scale brain dynamics, which tip the system away from spending more time in states reflecting more "typical" connectivity patterns toward more time in states reflecting visual hyperconnectivity and default mode hypoconnectivity.

Load-dependent hyperdeactivation of the default mode network in people with schizophrenia

Schizophrenia is associated with impairment in a range of cognitive functions. Neuroimaging studies have reported lower, but also higher, task-induced activation accompanying impaired performance. Differences in task-load and the ability of people with schizophrenia (PSZ) to stay engaged in the cognitive operations probed appear to underlie such discrepancies. Similarly, task-induced deactivation of the default mode network (DMN) was weaker in PSZ relative to healthy control subjects (HCS) in most studies, but some reported greater deactivation. An inability to stay engaged in the cognitive operations could account for these discrepancies, too, as it would lead to more time off-task and consequently less deactivation of DMN functions. The present study employed a change detection paradigm with small to moderate set sizes (SSs) of 1, 2, and 4 items. Task training prior to fMRI scanning abolished the group difference in no-response trials. Task-positive regions of interest (ROIs) displayed greater activation with increasing SS in both groups. PSZ showed greater activation relative to HCS at SSs 1 and 2. DMN ROIs displayed greater deactivation with increasing SS in PSZ, but not in HCS, and PSZ tended to hyperdeactivate DMN regions at SS 4. No hypodeactivation was observed in PSZ. In conclusion, when minimizing differences in task-engagement, PSZ tend to over-recruit task-positive regions during low-load operations, and hyperdeactivate DMN functions at higher load, perhaps reflecting heightened non-specific vigilance or effort when dealing with cognitive challenges. This speaks against an inability to down-regulate task-independent thought processes as a primary mechanism underlying cognitive impairment in schizophrenia.