Failure to deactivate in the prefrontal cortex in schizophrenia: dysfunction of the default mode network?

Longitudinal Analysis of Brain Function-Structure Dependencies in 22q11.2DS and Psychotic Symptoms

BACKGROUND

Understanding how brain function and structure relate to one another, compared to conventional unimodal analysis, opens a new biologically-relevant assessment of neural mechanisms. However, how function-structure dependencies evolve throughout typical and abnormal neurodevelopment remains elusive. The 22q11.2 deletion syndrome (22q11.2DS) offers an important opportunity to study the development of function-structure dependencies and their specific association to the pathophysiology of psychosis.

METHODS

Previously, we used graph signal processing to combine brain activity and structural connectivity measures in adults, quantifying functional-structural dependency (FSD). Here, we combined FSD with longitudinal multivariate partial least squares correlation (PLS-C) to evaluate FSD alterations across groups and among patients with and without mild to moderate positive psychotic symptoms (PPS). We assessed 391 longitudinally repeated resting-state functional and diffusion-weighted magnetic resonance imaging from 194 healthy controls and 197 deletion carriers (age span 7-34, data collected over a span of 12 years) RESULTS: Relative to controls, patients with 22q11.2DS showed a persistent developmental offset from childhood, with regions of hyper- and hypo-coupling across the brain. Additionally, a second deviating developmental pattern showed an exacerbation during adolescence, presenting hypo-coupling in frontal and cingulate cortex and hyper-coupling in temporal regions for patients with 22q11.2DS. Interestingly, the observed aggravation during adolescence was strongly driven by the PPS+ group.

CONCLUSIONS

These results confirm a central role of altered FSD-maturation in the emergence of psychotic symptoms in 22q11.2DS during adolescence. The FSD deviations precede the onset of psychotic episodes and thus offer a potential early indication for behavioral interventions in individuals at risk.

Neuroimaging features of cognitive impairments in schizophrenia and major depressive disorder

Cognitive dysfunctions are one of the key symptoms of schizophrenia (SZ) and major depressive disorder (MDD), which exist not only during the onset of diseases but also before the onset, even after the remission of psychiatric symptoms. With the development of neuroimaging techniques, these non-invasive approaches provide valuable insights into the underlying pathogenesis of psychiatric disorders and information of cognitive remediation interventions. This review synthesizes existing neuroimaging studies to examine domains of cognitive impairment, particularly processing speed, memory, attention, and executive function in SZ and MDD patients. First, white matter (WM) abnormalities are observed in processing speed deficits in both SZ and MDD, with distinct neuroimaging findings highlighting WM connectivity abnormalities in SZ and WM hyperintensity caused by small vessel disease in MDD. Additionally, the abnormal functions of prefrontal cortex and medial temporal lobe are found in both SZ and MDD patients during various memory tasks, while aberrant amygdala activity potentially contributes to a preference to negative memories in MDD. Furthermore, impaired large-scale networks including frontoparietal network, dorsal attention network, and ventral attention network are related to attention deficits, both in SZ and MDD patients. Finally, abnormal activity and volume of the dorsolateral prefrontal cortex (DLPFC) and abnormal functional connections between the DLPFC and the cerebellum are associated with executive dysfunction in both SZ and MDD. Despite these insights, longitudinal neuroimaging studies are lacking, impeding a comprehensive understanding of cognitive changes and the development of early intervention strategies for SZ and MDD. Addressing this gap is critical for advancing our knowledge and improving patient prognosis.

Functional neuroimaging in patients with catatonia: A systematic review

BACKGROUND

Catatonia is a challenging and heterogeneous neuropsychiatric syndrome of motor, affective and behavioral dysregulation which has been associated with multiple disorders such as structural brain lesions, systemic diseases, and psychiatric disorders. This systematic review summarized and compared functional neuroimaging abnormalities in catatonia associated with psychiatric and medical conditions.

METHODS

Using PRISMA methods, we completed a systematic review of 6 databases from inception to February 7th, 2024 of patients with catatonia that had functional neuroimaging performed.

RESULTS

A total of 309 studies were identified through the systematic search and 62 met the criteria for full-text review. A total of 15 studies reported patients with catatonia associated with a psychiatric disorder (n = 241) and one study reported catatonia associated with another medical condition, involving patients with N-methyl-d-aspartate receptor antibody encephalitis (n = 23). Findings varied across disorders, with hyperactivity observed in areas like the prefrontal cortex (PFC), the supplementary motor area (SMA) and the ventral pre-motor cortex in acute catatonia associated to a psychiatric disorder, hypoactivity in PFC, the parietal cortex, and the SMA in catatonia associated to a medical condition, and mixed metabolic activity in the study on catatonia linked to a medical condition.

CONCLUSION

Findings support the theory of dysfunction in cortico-striatal-thalamic, cortico-cerebellar, anterior cingulate-medial orbitofrontal, and lateral orbitofrontal networks in catatonia. However, the majority of the literature focuses on schizophrenia spectrum disorders, leaving the pathophysiologic characteristics of catatonia in other disorders less understood. This review highlights the need for further research to elucidate the pathophysiology of catatonia across various disorders.

Multi feature fusion network for schizophrenia classification and abnormal brain network recognition

Schizophrenia classification and abnormal brain network recognition have an important research significance. Researchers have proposed many classification methods based on machine learning and deep learning. However, fewer studies utilized the advantages of complementary information from multi feature to learn the best representation of schizophrenia. In this study, we proposed a multi-feature fusion network (MFFN) using functional network connectivity (FNC) and time courses (TC) to distinguish schizophrenia patients from healthy controls. DNN backbone was adopted to learn the feature map of functional network connectivity, C-RNNAM backbone was designed to learn the feature map of time courses, and Deep SHAP was applied to obtain the most discriminative brain networks. We proved the effectiveness of this proposed model using the combining two public datasets and evaluated this model quantitatively using the evaluation indexes. The results showed that the functional network connectivity generated by independent component analysis has advantage in schizophrenia classification by comparing static and dynamic functional connections. This method obtained the best classification accuracy (ACC=87.30%, SPE=89.28%, SEN=85.71%, F1 =88.23%, and AUC=0.9081), and it demonstrated the superiority of this proposed model by comparing state-of-the-art methods. Ablation experiment also demonstrated that multi feature fusion and attention module can improve classification accuracy. The most discriminative brain networks showed that default mode network and visual network of schizophrenia patients have aberrant connections in brain networks. In conclusion, this method can identify schizophrenia effectively and visualize the abnormal brain network, and it has important clinical application value.

Working memory performance in glioma patients is associated with functional connectivity between the right dorsolateral prefrontal cortex and default mode network

In healthy subjects, activity in the default mode network (DMN) and the frontoparietal network (FPN) has consistently been associated with working memory (WM). In particular, the dorsolateral prefrontal cortex (DLPFC) is important for WM. The functional-anatomical basis of WM impairment in glioma patients is, however, still poorly understood. We investigated whether WM performance of glioma patients is reflected in resting-state functional connectivity (FC) between the DMN and FPN, additionally focusing on the DLPFC. Resting-state functional MRI data were acquired from 45 glioma patients prior to surgery. WM performance was derived from a pre-operative N-back task. Scans were parcellated into ROIs using both the Gordon and Yeo atlas. FC was calculated as the average Pearson correlation between functional time series. The FC between right DLPFC and DMN was inversely related to WM performance for both the Gordon and Yeo atlas (p = .010). No association was found for FC between left DLPFC and DMN, nor between the whole FPN and DMN. The results are robust and not dependent on atlas choice or tumor location, as they hold for both the Gordon and Yeo atlases, and independently of location variables. Our findings show that WM performance of glioma patients can be quantified in terms of interactions between regions and large-scale networks that can be measured with resting-state fMRI. These group-based results are a necessary step toward development of biomarkers for clinical management of glioma patients, and provide additional evidence that global disruption of the DMN relates to cognitive impairment in glioma patients.

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.

Regional cerebral blood flow at rest in schizophrenia and major depressive disorder: A functional neuroimaging meta-analysis

Severe mental disorders (SMDs) such as schizophrenia (SCZ), major depressive disorder (MDD) and bipolar disorder (BD) are associated with altered brain function. Neuroimaging studies have illustrated spontaneous activity alterations across SMDs, but no meta-analysis has directly compared resting-state regional cerebral blood flow (rCBF) with one another. We conducted a meta-analysis of PET, SPECT and ASL neuroimaging studies to identify specific alterations of rCBF at rest in SMDs. Included are 20 studies in MDD, and 18 studies in SCZ. Due to the insufficient number of studies in BD, this disorder was left out of the analyses. Compared to controls, the SCZ group displayed reduced rCBF in the triangular part of the left inferior frontal gyrus and in the medial orbital part of the bilateral superior frontal gyrus. After correction, only a small cluster in the right inferior frontal gyrus exhibited reduced rCBF in MDD, compared to controls. Differences were found in these brain regions between SCZ and MDD. SCZ displayed reduced rCBF at rest in regions associated with default-mode, reward processing and language processing. MDD was associated with reduced rCBF in a cluster involved in response inhibition. Our meta-analysis highlights differences in the resting-state rCBF alterations between SCZ and MDD.

An fNIRS investigation of novel expressed emotion stimulations in schizophrenia

Living in high expressed emotion (EE) environments tends to increase the relapse rate in schizophrenia (SZ). At present, the neural substrates responsible for high EE in SZ remain poorly understood. Functional near-infrared spectroscopy (fNIRS) may be of great use to quantitatively assess cortical hemodynamics and elucidate the pathophysiology of psychiatric disorders. In this study, we designed novel low- (positivity and warmth) and high-EE (criticism, negative emotion, and hostility) stimulations, in the form of audio, to investigate cortical hemodynamics. We used fNIRS to measure hemodynamic signals while participants listened to the recorded audio. Healthy controls (HCs, [Formula: see text]) showed increased hemodynamic activation in the major language centers across EE stimulations, with stronger activation in Wernicke's area during the processing of negative emotional language. Compared to HCs, people with SZ ([Formula: see text]) exhibited smaller hemodynamic activation in the major language centers across EE stimulations. In addition, people with SZ showed weaker or insignificant hemodynamic deactivation in the medial prefrontal cortex. Notably, hemodynamic activation in SZ was found to be negatively correlated with the negative syndrome scale score at high EE. Our findings suggest that the neural mechanisms in SZ are altered and disrupted, especially during negative emotional language processing. This supports the feasibility of using the designed EE stimulations to assess people who are vulnerable to high-EE environments, such as SZ. Furthermore, our findings provide preliminary evidence for future research on functional neuroimaging biomarkers for people with psychiatric disorders.

Failure of deactivation in bipolar disorder during performance of an fMRI adapted version of the Stroop task

INTRODUCTION

Few studies have examined the functional brain correlates of the performance of the Stroop task in bipolar disorder (BD). It is also not known whether it is associated with failure of de-activation in the default mode network, as has been found in studies using other tasks.

METHODS

Twenty-four BD patients and 48 age, sex and educationally estimated intellectual quotient (IQ) matched healthy subjects (HS) underwent a functional MRI during performance of the counting Stroop task. Task-related activations (incongruent versus congruent condition) and de-activations (incongruent versus fixation) were examined using whole-brain, voxel-based methodology.

RESULTS

Both the BD patients and the HS showed activation in a cluster encompassing the left dorsolateral and ventrolateral prefrontal cortex and the rostral anterior cingulate cortex and supplementary motor area, with no differences between them. The BD patients, however, showed significant failure of de-activation in the medial frontal cortex and the posterior cingulate cortex/precuneus.

CONCLUSIONS

The failure to find activation differences between BD patients and controls suggests that the 'regulative' component of cognitive control remains intact in the disorder, at least outside episodes of illness. The failure of de-activation found adds to evidence documenting trait-like default mode network dysfunction in the disorder.

Brain functional abnormality in drug treated and drug naïve adolescents with borderline personality disorder: Evidence for default mode network dysfunction

BACKGROUND

Patients with borderline personality disorder (BPD) have been found to show functional brain abnormality, including in the medial frontal cortex and other areas of the default mode network (DMN). The current study aimed to examine activations and de-activations in drug treated and medication-free female adolescents with the disorder.

METHODS

39 DSM-5 adolescent female patients with BPD without psychiatric comorbidity and 31 matched healthy female adolescents underwent fMRI during the performance of 1-back and 2-back versions of the n-back working memory task. Linear models were used to obtain maps of within-group activations and de-activations and areas of differences between the groups.

RESULTS

On corrected whole-brain analysis, the BPD patients showed failure to de-activate a region of the medial frontal cortex in the 2-back > 1-back comparison. The 30 never-medicated patients additionally showed a failure to de-activate the right hippocampus in the 2-back versus baseline contrast.

CONCLUSIONS

Evidence of DMN dysfunction was observed in adolescent patients with BPD. Because the relevant medial frontal and hippocampal changes were seen in unmedicated young patients without comorbidity, they might be considered intrinsic to the disorder.

Beyond the Beta Rebound: Post-Task Responses in Oscillatory Activity follow Cessation of Working Memory Processes

Post-task responses (PTRs) are transitionary responses occurring for several seconds between the end of a stimulus/task and a period of rest. The most well-studied of these are beta band (13 - 30 Hz) PTRs in motor networks following movement, often called post-movement beta rebounds, which have been shown to differ in patients with schizophrenia and autism. Previous studies have proposed that beta PTRs reflect inhibition of task-positive networks to enable a return to resting brain activity, scaling with cognitive demand and reflecting cortical self-regulation. It is unknown whether PTRs are a phenomenon of the motor system, or whether they are a more general self-modulatory property of cortex that occur following cessation of higher cognitive processes as well as movement. To test this, we recorded magnetoencephalography (MEG) responses in 20 healthy participants to a working-memory task, known to recruit cortical networks associated with higher cognition. Our results revealed PTRs in the theta, alpha and beta bands across many regions of the brain, including the dorsal attention network (DAN) and lateral visual regions. These PTRs increased significantly (p < 0.05) in magnitude with working-memory load, an effect which is independent of oscillatory modulations occurring over the task period as well as those following individual stimuli. Furthermore, we showed that PTRs are functionally related to reaction times in left lateral visual (p < 0.05) and left parietal (p < 0.1) regions, while the oscillatory responses measured during the task period are not. Importantly, motor PTRs following button presses did not modulate with task condition, suggesting that PTRs in different networks are driven by different aspects of cognition. Our findings show that PTRs are not limited to motor networks but are widespread in regions which are recruited during the task. We provide evidence that PTRs have unique properties, scaling with cognitive load and correlating significantly with behaviour. Based on the evidence, we suggest that PTRs inhibit task-positive network activity to enable a transition to rest, however, further investigation is required to uncover their role in neuroscience and pathology.

Decreased integration of default-mode network during a working memory task in schizophrenia with severe attention deficits

Background

Working memory (WM) and attention deficits are both important features of schizophrenia. WM is closely related to attention, for it acted as an important characteristic in activating and manipulating WM. However, the knowledge of neural mechanisms underlying the relationship between WM and attention deficits in schizophrenia is poorly investigated.

Methods

Graph theory was used to examine the network topology at the whole-brain and large-scale network levels among 125 schizophrenia patients with different severity of attention deficits (65 mild attention deficits; 46 moderate attention deficits; and 14 severe attention deficits) and 53 healthy controls (HCs) during an N-back WM task. These analyses were repeated in the same participants during the resting state.

Results

In the WM task, there were omnibus differences in small-worldness and normalized clustering coefficient at a whole-brain level and normalized characterized path length of the default-mode network (DMN) among all groups. Post hoc analysis further indicated that all patient groups showed increased small-worldness and normalized clustering coefficient of the whole brain compared with HCs, and schizophrenia with severe attention deficits showed increased normalized characterized path length of the DMN compared with schizophrenia with mild attention deficits and HCs. However, these observations were not persisted under the resting state. Further correlation analyses indicated that the increased normalized characterized path length of the DMN was correlated with more severe attentional deficits and poorer accuracy of the WM task.

Conclusion

Our research demonstrated that, compared with the schizophrenia patients with less attention deficits, disrupted integration of the DMN may more particularly underlie the WM deficits in schizophrenia patients with severe attention deficits.

Integrative Brain Network and Salience Models of Psychopathology and Cognitive Dysfunction in Schizophrenia

Brain network models of cognitive control are central to advancing our understanding of psychopathology and cognitive dysfunction in schizophrenia. This review examines the role of large-scale brain organization in schizophrenia, with a particular focus on a triple-network model of cognitive control and its role in aberrant salience processing. First, we provide an overview of the triple network involving the salience, frontoparietal, and default mode networks and highlight the central role of the insula-anchored salience network in the aberrant mapping of salient external and internal events in schizophrenia. We summarize the extensive evidence that has emerged from structural, neurochemical, and functional brain imaging studies for aberrancies in these networks and their dynamic temporal interactions in schizophrenia. Next, we consider the hypothesis that atypical striatal dopamine release results in misattribution of salience to irrelevant external stimuli and self-referential mental events. We propose an integrated triple-network salience-based model incorporating striatal dysfunction and sensitivity to perceptual and cognitive prediction errors in the insula node of the salience network and postulate that dysregulated dopamine modulation of salience network-centered processes contributes to the core clinical phenotype of schizophrenia. Thus, a powerful paradigm to characterize the neurobiology of schizophrenia emerges when we combine conceptual models of salience with large-scale cognitive control networks in a unified manner. We conclude by discussing potential therapeutic leads on restoring brain network dysfunction in schizophrenia.

Spectral perturbations of cortical dipoles during a dynamic visuo-spatial working memory task in schizophrenia

Altered neural oscillations during prestimulus-task conditions have been reported to be associated with aberrant information processing in schizophrenia. Spectral perturbations induced by visuo-spatial working memory (VSWM) task were investigated in patients and their first-degree relatives in order to study the biomarkers in schizophrenia. EEG was recorded using 128-channel during VSWM task in 28 patients, 27 first-degree relatives and 25 controls. After pre-processing and ICA, current dipole was estimated for each IC. Total of 1609 independent and localizable EEG components across all groups were used to compute ERSP during different events of task. Patients deactivated DMN, RSN, auditory cortex more compared to controls during search period to perform VSWM task. Relatives showed altered activation of right medial and inferior frontal gyri during different events and loads of task in lower frequencies compared to controls. Relatives also showed hyperactivity in right cingulate and parahippocampal gyri compared to controls. This is suggestive of genetic predisposition in schizophrenia and could act as vulnerability markers, further strengthened by no significant differences between patients and relatives. Altered processing of simultaneous ongoing events in patients and relatives can serve as state and trait-specific features of schizophrenia.

Functional disconnection between subsystems of the default mode network in schizophrenia

BACKGROUND

A dysfunctional default mode network (DMN) has been reported in patients with schizophrenia. However, the stability of the deficits has not been determined across different stages of the disorder.

METHODS

We examined the functional connectivity of the DMN subsystems of 125 patients with first-episode schizophrenia (FES) or recurrent schizophrenia (RES), compared to that of 82 healthy controls. We tested the robustness of the findings in an independent cohort of 158 patients and 39 healthy controls. We performed resting-state functional connectivity analysis, and examined the strength of the connections within and between the three subsystems of the DMN (core, dorsal medial prefrontal cortex [dMPFC], and medial temporal lobe [MTL]). We also analyzed the connectivity correlations to symptoms and illness duration.

RESULTS

We found reduced connectivity strength between the core and MTL subsystems in schizophrenia patients compared to controls, with no differences between the FES and RES patient groups; these findings were validated in the second sample. Schizophrenia patients also showed a significant reduction in connectivity within the MTL and between the dMPFC-MTL subsystems, similarly between FES and RES groups. The connectivity strength within the core subsystem was negatively correlated with clinical symptoms in schizophrenia. There was no significant correlation between the DMN subsystem connectivity and illness duration.

CONCLUSIONS

DMN subsystem connectivity deficits are present in schizophrenia, and the homochronicity of their appearance indicates the trait-like nature of these alterations. The DMN deficit may be useful for early diagnosis, and MTL dysfunction may be a crucial mechanism underlying 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.

Abnormal functional connectivities patterns of multidomain cognitive impairments in pontine stroke patients

Cognitive dysfunction in patients with infratentorial stroke has been paid little attention. Brainstem stroke may disrupt network connectivity across the whole brain and affect multidomain cognition, but the details of this process remain unclear. The study aimed to investigate the effects of stroke‐induced pontine injury on whole‐brain network connectivity and cognitive function. We included 47 patients with pontine stroke and 56 healthy comparisons (HC), who underwent cognitive tests and functional magnetic resonance imaging (fMRI). Seven meaningful brain networks were identified using independent component analysis (ICA). Patients with pontine stroke had decreased intra‐network functional connectivities (FCs) in the primary perceptual and higher cognitive control networks, including sensorimotor network (SMN), visual network (VIS), default mode network (DMN), and salience network (SAN), as well as decreased inter‐network FCs in the primary perceptual (VIS‐SMN) and higher cognitive control networks (bilateral frontoparietal networks, rFPN‐lFPN). While the FCs between the primary perceptual and higher cognitive control networks (VIS‐DMN, VIS‐rFPN, VIS‐lFPN) were increased. Furthermore, the alterations in these FCs correlated with patients' cognitive measurements. These findings suggested that the infratentorial stroke can induce dysfunctional connectivity in both primary perceptual and higher cognitive control networks at the whole‐brain level, which may be attributable to the neural substrates of multidomain cognitive deficits in these patients.

Combining fMRI and DISC1 gene haplotypes to understand working memory-related brain activity in schizophrenia

The DISC1 gene is one of the most relevant susceptibility genes for psychosis. However, the complex genetic landscape of this locus, which includes protective and risk variants in interaction, may have hindered consistent conclusions on how DISC1 contributes to schizophrenia (SZ) liability. Analysis from haplotype approaches and brain-based phenotypes can contribute to understanding DISC1 role in the neurobiology of this disorder. We assessed the brain correlates of DISC1 haplotypes associated with SZ through a functional neuroimaging genetics approach. First, we tested the association of two DISC1 haplotypes, the HEP1 (rs6675281-1000731-rs999710) and the HEP3 (rs151229-rs3738401), with the risk for SZ in a sample of 138 healthy subjects (HS) and 238 patients. This approach allowed the identification of three haplotypes associated with SZ (HEP1-CTG, HEP3-GA and HEP3-AA). Second, we explored whether these haplotypes exerted differential effects on n-back associated brain activity in a subsample of 70 HS compared to 70 patients (diagnosis × haplotype interaction effect). These analyses evidenced that HEP3-GA and HEP3-AA modulated working memory functional response conditional to the health/disease status in the cuneus, precuneus, middle cingulate cortex and the ventrolateral and dorsolateral prefrontal cortices. Our results are the first to show a diagnosis-based effect of DISC1 haplotypes on working memory-related brain activity, emphasising its role in SZ.

Minding my brain: Fourteen neuroscience-based principles to enhance psychotherapy responsiveness

Intersections between psychotherapy and neurosciences are at its dawn. The quest to understand the neural underpinnings of psychological processes has led several generations of scientists to explore neural correlates between mind, brain, and behavior. Neuroscience methods and research has given psychology new perspectives and insights about the structure and function of complex neural pathways, that underly human functioning (cognition, emotion, motivation, and interpersonal behavior). By translating neuroscientific findings into psychotherapeutic principles of change, it is possible to promote responsiveness towards brain dysfunction that underlies patients' psychological malfunctioning. In psychotherapy, responsiveness is a core aspect of the therapeutic change process, especially to adapt psychological interventions to patients' motivational stages and preferences, coping styles, neurobehavioral modes, and emotional needs. Within a transtheoretical and translational approach, contemporary neuroscientific findings are revised, discussed, and used to attempt to build-on fourteen theoretical brain-based principles that may be applied to psychotherapy. Translating these empirical findings into practical principles, clinical strategies and tasks is expected to enhance psychotherapy responsiveness grounded on a science-based knowledge of brain functioning.

Schizophrenia

Schizophrenia, characterised by psychotic symptoms and in many cases social and occupational decline, remains an aetiological and therapeutic challenge. Contrary to popular belief, the disorder is modestly more common in men than in women. Nor is the outcome uniformly poor. A division of symptoms into positive, negative, and disorganisation syndromes is supported by factor analysis. Catatonic symptoms are not specific to schizophrenia and so-called first rank symptoms are no longer considered diagnostically important. Cognitive impairment is now recognised as a further clinical feature of the disorder. Lateral ventricular enlargement and brain volume reductions of around 2% are established findings. Brain functional changes occur in different subregions of the frontal cortex and might ultimately be understandable in terms of disturbed interaction among large-scale brain networks. Neurochemical disturbance, involving dopamine function and glutamatergic N-methyl-D-aspartate receptor function, is supported by indirect and direct evidence. The genetic contribution to schizophrenia is now recognised to be largely polygenic. Birth and early life factors also have an important aetiological role. The mainstay of treatment remains dopamine receptor-blocking drugs; a psychological intervention, cognitive behavioural therapy, has relatively small effects on symptoms. The idea that schizophrenia is better regarded as the extreme end of a continuum of psychotic symptoms is currently influential. Other areas of debate include cannabis and childhood adversity as causative factors, whether there is progressive brain change after onset, and the long-term success of early intervention initiatives.

Target selection for deep brain stimulation in treatment resistant schizophrenia

The use of deep brain stimulation (DBS) in treatment resistant patients with schizophrenia is of considerable current interest, but where to site the electrodes is challenging. This article reviews rationales for electrode placement in schizophrenia based on evidence for localized brain abnormality in the disorder and the targets that have been proposed and employed to date. The nucleus accumbens and the subgenual anterior cingulate cortex are of interest on the grounds that they are sites of potential pathologically increased brain activity in schizophrenia and so susceptible to the local inhibitory effects of DBS; both sites have been employed in trials of DBS in schizophrenia. Based on other lines of reasoning, the ventral tegmental area, the substantia nigra pars reticulata and the habenula have also been proposed and in some cases employed. The dorsolateral prefrontal cortex has not been suggested, probably reflecting evidence that it is underactive rather than overactive in schizophrenia. The hippocampus is also of theoretical interest but there is no clear functional imaging evidence that it shows overactivity in schizophrenia. On current evidence, the nucleus accumbens may represent the strongest candidate for DBS electrode placement in schizophrenia, with the substantia nigra pars reticulata also showing promise in a single case report; the ventral tegmental area is also of potential interest, though it remains untried.

Activation and deactivation patterns in schizophrenia during performance of an fMRI adapted version of the stroop task

The Stroop task, which examines an aspect of executive function/cognitive control, the ability to inhibit prepotent responses, has been relatively little examined in schizophrenia, and the findings have been inconsistent. Whether performance of this task is associated with failure of de-activation in the disorder is also uncertain. We examined 42 schizophrenic patients and 61 healthy controls during performance of an fMRI-adapted version of the Stroop task, the counting Stroop task. Task-related activations (incongruent > congruent condition) and de-activations (baseline > incongruent) were examined using whole-brain, voxel-based methods. In the healthy controls, task performance was found to be associated with activations in the left dorsolateral prefrontal cortex and the dorsal anterior cingulate cortex, among other regions. De-activations were seen in the medial frontal cortex, the middle and posterior cingulate gyrus and cuneus, the parahippocampal gyrus and the hippocampus. The schizophrenic patients did not show reduced activation compared to the healthy controls. They did, however, show failure of de-activation in the medial frontal cortex. Our negative finding with respect to hypoactivation during performance of a task requiring inhibition of prepotent responses suggests that brain functional abnormality in schizophrenia may not affect all aspects of executive function/cognitive control. The finding of medial frontal cortex failure of de-activation adds to existing findings of default mode network dysfunction in the disorder.

Dissecting the neurobiology of linguistic disorganisation and impoverishment in schizophrenia

Schizophrenia provides a quintessential disease model of how disturbances in the molecular mechanisms of neurodevelopment lead to disruptions in the emergence of cognition. The central and often persistent feature of this illness is the disorganisation and impoverishment of language and related expressive behaviours. Though clinically more prominent, the periodic perceptual distortions characterised as psychosis are non-specific and often episodic. While several insights into psychosis have been gained based on study of the dopaminergic system, the mechanistic basis of linguistic disorganisation and impoverishment is still elusive. Key findings from cellular to systems-level studies highlight the role of ubiquitous, inhibitory processes in language production. Dysregulation of these processes at critical time periods, in key brain areas, provides a surprisingly parsimonious account of linguistic disorganisation and impoverishment in schizophrenia. This review links the notion of excitatory/inhibitory (E/I) imbalance at cortical microcircuits to the expression of language behaviour characteristic of schizophrenia, through the building blocks of neurochemistry, neurophysiology, and neurocognition.

Toward a transdiagnostic neurocircuitry-based biomarker model for pro-cognitive effects: challenges, opportunities, and next steps

Cognitive impairment has emerged as a key treatment priority in neuropsychiatric disorders. However, there is a lack of treatments with solid and lasting efficacy on cognition. A neurocircuitry-based biomarker model of pro-cognitive effects is critically needed to select among new candidate treatments. In a recent review of functional magnetic resonance imaging (fMRI) studies in mood disorders, we found that cognitive impairments are consistently accompanied by aberrant (hypo- and hyper-) activity in the dorsal prefrontal cortex (PFC) and the default mode network (DMN), and that activity change in these regions commonly occurs with cognitive improvements. Here, we (i) review the putative model from our recent review article, which explains the discrepant findings regarding the direction of aberrant dorsal PFC activity and treatment-related activity change in mood disorders. Inspired by the Research Domain Criteria project, we do this in order to (ii) examine whether a similar pattern of activity change occurs across distinct neuropsychiatric disorders and thereby provides a common biomarker for pro-cognitive effects. Lastly, we (iii) discuss whether dorsal PFC and DMN target engagement is a putative transdiagnostic neurocircuitry-based biomarker model for pro-cognitive effects, and (iv) outline the necessary next steps to address this question.

Brain preparedness: The proactive role of the cortisol awakening response in hippocampal-prefrontal functional interactions

Upon awakening from nighttime sleep, the stress hormone cortisol in humans exhibits a robust rise within thirty to forty-five minutes. This cortisol awakening response (CAR), a crucial point of reference within the healthy cortisol circadian rhythm, has been linked to various psychological, psychiatric and health-related conditions. The CAR is thought to prepare the brain for anticipated challenges of the upcoming day to maintain one's homeostasis and promote adaptive responses. Using brain imaging with a prospective design and pharmacological manipulation, we investigate the neurobiological mechanisms underlying this preparation function of the CAR across two studies. In Study 1, a robust CAR is predictive of less hippocampal and prefrontal activity, though enhanced functional coupling between those regions during a demanding task hours later in the afternoon. Reduced prefrontal activity is in turn linked to better working memory performance, implicating that the CAR proactively promotes brain preparedness based on improved neurocognitive efficiency. In Study 2, pharmacologically suppressed CAR using Dexamethasone mirrors this proactive effect, which further causes a selective reduction of prefrontal top-down functional modulation over hippocampal activity. These findings establish a causal link between the CAR and its proactive role in optimizing functional brain networks involved in neuroendocrine control, executive function and memory.

Aberrant modulation of brain activity underlies impaired working memory following traumatic brain injury

Impaired working memory is a common and disabling consequence of traumatic brain injury (TBI) that is caused by aberrant brain processing. However, little is known about the extent to which deficits are perpetuated by specific working memory subprocesses. Using a combined functional magnetic resonance imaging (fMRI) and working memory paradigm, we tested the hypothesis that the pattern of brain activation subserving working memory following TBI would interact with both task demands and specific working memory subcomponents: encoding, maintenance, and retrieval. Forty-three patients with moderate-severe TBI, of whom 25 were in the acute phase of recovery (M = 2.16 months, SD = 1.48 months, range = 0.69 - 6.64 months) and 18 in the chronic phase of recovery (M = 23.44 months, SD = 6.76 months, range = 13.35 - 34.82 months), were compared with 38 demographically similar healthy controls. Behaviourally, we found that working memory deficits were confined to the high cognitive load trials in both acute (P = 0.006) and chronic (P = 0.024) cohorts. Furthermore, results for a subset of the sample (18 chronic TBI and 17 healthy controls) who underwent fMRI revealed that the TBI group showed reduced brain activation when simply averaged across all task trials (regardless of cognitive load or subcomponent). However, interrogation of the subcomponents of working memory revealed a more nuanced pattern of activation. When examined more closely, patterns of brain activity following TBI were found to interact with both task demands and the working memory subcomponent: increased activation was observed during encoding in the left inferior occipital gyrus whereas decreased activation was apparent during maintenance in the bilateral cerebellum and left calcarine sulcus. Taken together, findings indicate an inability to appropriately modulate brain activity according to task demand that is specific to working memory encoding and maintenance.

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.

Emotional imagination of negative situations: Functional neuroimaging in anorexia and bulimia

Aim

The present study aims to extend the knowledge of the neural correlates of emotion processing in first episode subjects affected by anorexia nervosa (AN) or bulimia nervosa (BN). We applied an emotional distress paradigm targeting negative emotions thought to be relevant for interpersonal difficulties and therapeutic resistance mechanisms.

Methods

The current study applied to 44 female participants with newly diagnosed AN or BN and 20 matched controls a neuroimaging paradigm eliciting affective responses. The measurements also included an extensive assessment comprising clinical scales, neuropsychological tests, measures of emotion processing and empathy.

Results

AN and BN did not differ from controls in terms of emotional response, emotion matching, self-reported empathy and cognitive performance. However, eating disorder and psychopathological clinical scores, as well as alexithymia levels, were increased in AN and BN. On a neural level, no significant group differences emerged, even when focusing on a region of interest selected a priori: the amygdala. Some interesting findings put in relation the hippocampal activity with the level of Body Dissatisfaction of the participants, the relative importance of the key nodes for the common network in the decoding of different emotions (BN = right amygdala, AN = anterior cingulate area), and the qualitative profile of the deactivations.

Conclusions

Our data do not support the hypothesis that participants with AN or BN display reduced emotional responsiveness. However, peculiar characteristics in emotion processing could be associated to the three different groups. Therefore, relational difficulties in eating disorders, as well as therapeutic resistance, could be not secondary to a simple difficulty in feeling and identifying basic negative emotions in AN and BN participants.

A functional MRI study of presurgical cognitive deficits in glioma patients

Background

The main goal of this functional MRI (fMRI) study was to examine whether cognitive deficits in glioma patients prior to treatment are associated with abnormal brain activity in either the central executive network (CEN) or default mode network (DMN).

Methods

Forty-six glioma patients, and 23 group-matched healthy controls (HCs) participated in this fMRI experiment, performing an N-back task. Additionally, cognitive profiles of patients were evaluated outside the scanner. A region of interest–based analysis was used to compare brain activity in CEN and DMN between groups. Post hoc analyses were performed to evaluate differences between low-grade glioma (LGG) and high-grade glioma (HGG) patients.

Results

In-scanner performance was lower in glioma patients compared to HCs. Neuropsychological testing indicated cognitive impairment in LGG as well as HGG patients. fMRI results revealed normal CEN activation in glioma patients, whereas patients showed reduced DMN deactivation compared to HCs. Brain activity levels did not differ between LGG and HGG patients.

Conclusions

Our study suggests that cognitive deficits in glioma patients prior to treatment are associated with reduced responsiveness of the DMN, but not with abnormal CEN activation. These results suggest that cognitive deficits in glioma patients reflect a reduced capacity to achieve a brain state necessary for normal cognitive performance, rather than abnormal functioning of executive brain regions. Solely focusing on increases in brain activity may well be insufficient if we want to understand the underlying brain mechanism of cognitive impairments in patients, as our results indicate the importance of assessing deactivation.

A new era for executive function research: On the transition from centralized to distributed executive functioning

"Executive functions" (EFs) is an umbrella term for higher cognitive control functions such as working memory, inhibition, and cognitive flexibility. One of the most challenging problems in this field of research has been to explain how the wide range of cognitive processes subsumed as EFs are controlled without an all-powerful but ill-defined central executive in the brain. Efforts to localize control mechanisms in circumscribed brain regions have not led to a breakthrough in understanding how the brain controls and regulates itself. We propose to re-conceptualize EFs as emergent consequences of highly distributed brain processes that communicate with a pool of highly connected hub regions, thus precluding the need for a central executive. We further discuss how graph-theory driven analysis of brain networks offers a unique lens on this problem by providing a reference frame to study brain connectivity in EFs in a holistic way and helps to refine our understanding of the mechanisms underlying EFs by providing new, testable hypotheses and resolves empirical and theoretical inconsistencies in the EF literature.

Neural Signatures of Memory Encoding in Schizophrenia Are Modulated by Antipsychotic Treatment

There is no pharmacological treatment to remediate cognitive impairment in schizophrenia (SZ). It is imperative to characterize underlying pathologies of memory processing in order to effectively develop new treatments. In this longitudinal study, we combined functional magnetic resonance imaging during a memory encoding task with proton MR spectroscopy to measure hippocampal glutamate + glutamine (Glx). Seventeen SZ were scanned while unmedicated and after 6 weeks of treatment with risperidone and compared to a group of matched healthy controls (HC) scanned 6 weeks apart. Unmedicated patients showed reduced blood oxygen level dependent (BOLD) response in several regions, including the hippocampus, and greater BOLD response in regions of the default mode network (DMN) during correct memory encoding. Post hoc contrasts from significant group by time interactions indicated reduced hippocampal BOLD response at baseline with subsequent increase following treatment. Hippocampal Glx was not different between groups at baseline, but at week 6, hippocampal Glx was significantly lower in SZ compared to HC. Finally, in unmedicated SZ, higher hippocampal Glx predicted less deactivation of the BOLD response in regions of the DMN. Using 2 brain imaging modalities allowed us to concurrently investigate different mechanisms involved in memory encoding dysfunction in SZ. Hippocampal pathology during memory encoding stems from decreased hippocampal recruitment and faulty deactivation of the DMN, and hippocampal recruitment during encoding can be modulated by antipsychotic treatment. High Glx in unmedicated patients predicted less deactivation of the DMN; these results suggest a mechanism by which faulty DMN deactivation, a hallmark of pathological findings in SZ, is achieved.

Autobiographical memory and default mode network function in schizophrenia: an fMRI study

BACKGROUND

The brain functional correlates of autobiographical recall are well established, but have been little studied in schizophrenia. Additionally, autobiographical memory is one of a small number of cognitive tasks that activates rather than de-activates the default mode network, which has been found to be dysfunctional in this disorder.

METHODS

Twenty-seven schizophrenic patients and 30 healthy controls underwent functional magnetic resonance imaging while viewing cue words that evoked autobiographical memories. Control conditions included both non-memory-evoking cues and a low level baseline (cross fixation).

RESULTS

Compared to both non-memory evoking cues and low level baseline, autobiographical recall was associated with activation in default mode network regions in the controls including the medial frontal cortex, the posterior cingulate cortex and the hippocampus, as well as other areas. Clusters of de-activation were seen outside the default mode network. There were no activation differences between the schizophrenic patients and the controls, but the patients showed clusters of failure of de-activation in non-default mode network regions.

CONCLUSIONS

According to this study, patients with schizophrenia show intact activation of the default mode network and other regions associated with recall of autobiographical memories. The finding of failure of de-activation outside the network suggests that schizophrenia may be associated with a general difficulty in de-activation rather than dysfunction of the default mode network per se.

Application of Near-Infrared Spectroscopy for Understanding Spontaneous Brain Activity During Resting State in Schizophrenia: A Mini Review

Spontaneous brain activity occurs at rest, as represented by the default mode network. A resting paradigm is suitable for investigating brain function of patients with psychiatric diseases who may have difficulties adhering to goal-oriented tasks. Evidence accumulated in neuroimaging studies using functional magnetic resonance imaging has shown that the resting cerebral blood flow is impaired in psychiatric diseases. Near-infrared spectroscopy (NIRS), a simple neuroimaging modality, is an optimal tool for the resting paradigm, because it can offer a comfortable environment for measurement. Recent NIRS studies have demonstrated some promising data of altered resting activity in the prefrontal cortex of patients with schizophrenia, which may be exploited to develop further applications of NIRS in clinical psychiatry. Based on these findings, we emphasize the benefits of NIRS for assessing the prefrontal pathophysiology during the resting state and some methodological issues to be noted while analyzing cerebral blood flow using NIRS; moreover, we focus on interpreting these changes based on the complex nature of the spontaneous brain activity during resting state.

Progressive reconfiguration of resting-state brain networks as psychosis develops: Preliminary results from the North American Prodrome Longitudinal Study (NAPLS) consortium

Mounting evidence has shown disrupted brain network architecture across the psychosis spectrum. However, whether these changes relate to the development of psychosis is unclear. Here, we used graph theoretical analysis to investigate longitudinal changes in resting-state brain networks in samples of 72 subjects at clinical high risk (including 8 cases who converted to full psychosis) and 48 healthy controls drawn from the North American Prodrome Longitudinal Study (NAPLS) consortium. We observed progressive reduction in global efficiency (P = 0.006) and increase in network diversity (P = 0.001) in converters compared with non-converters and controls. More refined analysis separating nodes into nine key brain networks demonstrated that these alterations were primarily driven by progressively diminished local efficiency in the default-mode network (P = 0.004) and progressively enhanced node diversity across all networks (P < 0.05). The change rates of network efficiency and network diversity were significantly correlated (P = 0.003), suggesting these changes may reflect shared neural mechanisms. In addition, change rates of global efficiency and node diversity were significantly correlated with change rate of cortical thinning in the prefrontal cortex in converters (P < 0.03) and could be predicted by visuospatial memory scores at baseline (P < 0.04). These results provide preliminary evidence for longitudinal reconfiguration of resting-state brain networks during psychosis development and suggest that decreased network efficiency, reflecting an increase in path length between nodes, and increased network diversity, reflecting a decrease in the consistency of functional network organization, may be implicated in the progression to full psychosis.

Identifying neural signatures mediating behavioral symptoms and psychosis onset: High-dimensional whole brain functional mediation analysis

Along the pathway from behavioral symptoms to the development of psychotic disorders sits the multivariate mediating brain. The functional organization and structural topography of large-scale multivariate neural mediators among patients with brain disorders, however, are not well understood. Here, we design a high-dimensional brain-wide functional mediation framework to investigate brain regions that intermediate between baseline behavioral symptoms and future conversion to full psychosis among individuals at clinical high risk (CHR). Using resting-state functional magnetic resonance imaging (fMRI) data from 263 CHR subjects, we extract an α brain atlas and a β brain atlas: the former underlines brain areas associated with prodromal symptoms and the latter highlights brain areas associated with disease onset. In parallel, we identify and separate mediators that potentially positively and negatively mediate symptoms and psychosis, respectively, and quantify the effect of each neural mediator on disease development. Taken together, these results paint a brain-wide picture of neural markers that are potentially mediating behavioral symptoms and the development of psychotic disorders; additionally, they underscore a statistical framework that is useful to uncover large-scale intermediating variables in a regulatory biological system.

More stringent criteria are needed for diagnosing internet gaming disorder: Evidence from regional brain features and whole-brain functional connectivity multivariate pattern analyses

BACKGROUND

Internet gaming disorder (IGD) is included in the DSM-5 as a provisional diagnosis. Whether IGD should be regarded as a disorder and, if so, how it should be defined and thresholded have generated considerable debate.

METHODS

In the current study, machine learning was used, based on regional and interregional brain features. Resting-state data from 374 subjects (including 148 IGD subjects with DSM-5 scores ≥5 and 93 IGD subjects with DSM-5 scores ≥6) were collected, and multivariate pattern analysis (MVPA) was employed to classify IGD from recreational game use (RGU) subjects based on regional brain features (ReHo) and communication between brain regions (functional connectivity; FC). Permutation tests were used to assess classifier performance.

RESULTS

The results demonstrated that when using DSM-5 scores ≥5 as the inclusion criteria for IGD subjects, MVPA could not differentiate IGD subjects from RGU, whether based on ReHo or FC features or by using different templates. MVPA could differentiate IGD subjects from RGU better than expected by chance when using DSM-5 scores ≥6 with both ReHo and FC features. The brain regions involved in the default mode network and executive control network and the cerebellum exhibited high discriminative power during classification.

DISCUSSION

The current findings challenge the current IGD diagnostic criteria thresholding proposed in the DSM-5, suggesting that more stringent criteria may be needed for diagnosing IGD. The findings suggest that brain regions involved in the default mode network and executive control network relate importantly to the core criteria for IGD.

Deficits of entropy modulation of the EEG: A biomarker for altered function in schizophrenia and bipolar disorder?

BACKGROUND

The synchronized activity of distributed neural assemblies — reflected in the electroencephalogram (EEG) — underpins mental function. In schizophrenia, modulation deficits of EEG spectral content during a P300 task have been replicated. The effects of treatment, chronicity and specificity in these deficits and their possible relationship with anatomic connectivity remain to be explored.

METHODS

We assessed spectral entropy modulation of the EEG during a P300 task in 79 patients with schizophrenia (of those, 31 werein their first episode), 29 patients with bipolar disorder and 48 healthy controls. Spectral entropy values summarize EEG characteristics by quantifying the irregularity of spectral content. In a subsample, we calculated the network architecture of structural connectivity using diffusion tensor imaging and graph-theory parameters.

RESULTS

We found significant spectral entropy modulation deficits with task performance in patients with chronic or first-episode schizophrenia and in patients with bipolar disorder, without significant pre-stimulus spectral entropy differences. The deficits were unrelated to treatment doses, and spectral entropy modulation did not differ between patients taking or not taking antipsychotics, lithium, benzodiazepines or antidepressants. Structural connectivity values were unrelated to spectral entropy modulation. In patients with schizophrenia, spectral entropy modulation was inversely related to negative symptoms and directly related to verbal memory.

LIMITATIONS

All patients were taking medication. Patients with bipolar disorder were euthymic and chronic. The cross-sectional nature of this study prevented a more thorough analysis of state versus trait criteria for spectral entropy changes.

CONCLUSION

Spectral entropy modulation with task performance is decreased in patients with schizophrenia and bipolar disorder. This deficit was not an effect of psychopharmacological treatment or structural connectivity and might reflect a deficit in the synchronization of the neural assemblies that underlie cognitive activity.

Discriminative Analysis of Symptom Severity and Ultra-High Risk of Schizophrenia Using Intrinsic Functional Connectivity

Past studies have consistently shown functional dysconnectivity of large-scale brain networks in schizophrenia. In this study, we aimed to further assess whether multivariate pattern analysis (MVPA) could yield a sensitive predictor of patient symptoms, as well as identify ultra-high risk (UHR) stage of schizophrenia from intrinsic functional connectivity of whole-brain networks. We first combined rank-based feature selection and support vector machine methods to distinguish between 43 schizophrenia patients and 52 healthy controls. The constructed classifier was then applied to examine functional connectivity profiles of 18 UHR individuals. The classifier indicated reliable relationship between MVPA measures and symptom severity, with higher classification accuracy in more severely affected schizophrenia patients. The UHR subjects had classification scores falling between those of healthy controls and patients, suggesting an intermediate level of functional brain abnormalities. Moreover, UHR individuals with schizophrenia-like connectivity profiles at baseline presented higher rate of conversion to full-blown illness in the follow-up visits. Spatial maps of discriminative brain regions implicated increases of functional connectivity in the default mode network, whereas decreases of functional connectivity in the cerebellum, thalamus and visual areas in schizophrenia. The findings may have potential utility in the early diagnosis and intervention of schizophrenia.

Connectomic Underpinnings of Working Memory Deficits in Schizophrenia: Evidence From a replication fMRI study

BACKGROUND

Working memory (WM) deficit is a key feature of schizophrenia that relates to a generalized neural inefficiency of extensive brain areas. To date, it remains unknown how these distributed regions are systemically organized at the connectome level and how the disruption of such organization brings about the WM impairment seen in schizophrenia.

METHODS

We used graph theory to examine the neural efficiency of the functional connectome in different granularity in 155 patients with schizophrenia and 96 healthy controls during a WM task. These analyses were repeated in another independent dataset (81 patients and 54 controls). Linear regression analysis was used to test associations of altered graph properties, clinical symptoms, and WM accuracy in patients. A machine-learning approach was adopted to study the ability of multivariate connectome features from one dataset to discriminate patients from controls in the second dataset.

RESULTS

Small-worldness of the whole-brain connectome was significantly increased in schizophrenia during the WM task; this increase is related to better (though subpar) WM accuracy in patients with more severe negative symptom burden. There was a shift in the degree distribution to a more homogeneous form in patients. The machine-learning approach classified a new set of patients from controls with 84.3% true-positivity rate for schizophrenia and 71.6% overall accuracy.

CONCLUSIONS

We demonstrate a putative mechanistic link between connectome topology, hub redistribution, and impaired n-back performance in schizophrenia. The task-dependent modulation of the connectome relates to, but remains inefficient in, improving the performance above par in the presence of severe negative symptoms.

Evidence for default mode network dysfunction in borderline personality disorder

BACKGROUND

Although executive and other cognitive deficits have been found in patients with borderline personality disorder (BPD), whether these have brain functional correlates has been little studied. This study aimed to examine patterns of task-related activation and de-activation during the performance of a working memory task in patients with the disorder.

METHODS

Sixty-seven DSM-IV BPD patients and 67 healthy controls underwent fMRI during the performance of the n-back task. Linear models were used to obtain maps of within-group activations and areas of differential activation between the groups.

RESULTS

On corrected whole-brain analysis, there were no activation differences between the BPD patients and the healthy controls during the main 2-back v. baseline contrast, but reduced activation was seen in the precentral cortex bilaterally and the left inferior parietal cortex in the 2-back v. 1-back contrast. The patients showed failure of de-activation affecting the medial frontal cortex and the precuneus, plus in other areas. The changes did not appear to be attributable to previous history of depression, which was present in nearly half the sample.

CONCLUSIONS

In this study, there was some, though limited, evidence for lateral frontal hypoactivation in BPD during the performance of an executive task. BPD also appears to be associated with failure of de-activation in key regions of the default mode network.

Abnormal Development and Dysconnectivity of Distinct Thalamic Nuclei in Patients With 22q11.2 Deletion Syndrome Experiencing Auditory Hallucinations

BACKGROUND

Several studies in patients with schizophrenia have demonstrated an abnormal thalamic volume and thalamocortical connectivity. Specifically, hyperconnectivity with somatosensory areas has been related to the presence of auditory hallucinations (AHs). The 22q11.2 deletion syndrome is a neurogenetic disorder conferring proneness to develop schizophrenia, and deletion carriers (22qdel carriers) experience hallucinations to a greater extent than the general population.

METHODS

We acquired 442 consecutive magnetic resonance imaging scans from 120 22qdel carriers and 110 control subjects every 3 years (age range: 8-35 years). The volume of thalamic nuclei was obtained with FreeSurfer and was compared between 22qdel carriers and control subjects and between 22qdel carriers with and without AHs. In a subgroup of 76 22qdel carriers, we evaluated the functional connectivity between thalamic nuclei affected in patients experiencing AHs and cortical regions.

RESULTS

As compared with control subjects, 22qdel carriers had lower and higher volumes of nuclei involved in sensory processing and cognitive functions, respectively. 22qdel carriers with AHs had a smaller volume of the medial geniculate nucleus, with deviant trajectories showing a steeper volume decrease from childhood with respect to those without AHs. Moreover, we showed an aberrant development of nuclei intercalated between the prefrontal cortex and hippocampus (the anteroventral and medioventral reuniens nuclei) and hyperconnectivity of the medial geniculate nucleus and anteroventral nucleus with the auditory cortex and Wernicke's area.

CONCLUSIONS

The increased connectivity of the medial geniculate nucleus and anteroventral nucleus to the auditory cortex might be interpreted as a lack of maturation of thalamocortical connectivity. Overall, our findings point toward an aberrant development of thalamic nuclei and an immature pattern of connectivity with temporal regions in relation to AHs.

Dysfunctional default mode network and executive control network in people with Internet gaming disorder: Independent component analysis under a probability discounting task

Background

The present study identified the neural mechanism of risky decision-making in Internet gaming disorder (IGD) under a probability discounting task.

Methods

Independent component analysis was used on the functional magnetic resonance imaging data from 19 IGD subjects (22.2 ± 3.08 years) and 21 healthy controls (HC, 22.8 ± 3.5 years).

Results

For the behavioral results, IGD subjects prefer the risky to the fixed options and showed shorter reaction time compared to HC. For the imaging results, the IGD subjects showed higher task-related activity in default mode network (DMN) and less engagement in the executive control network (ECN) than HC when making the risky decisions. Also, we found the activities of DMN correlate negatively with the reaction time and the ECN correlate positively with the probability discounting rates.

Conclusions

The results suggest that people with IGD show altered modulation in DMN and deficit in executive control function, which might be the reason for why the IGD subjects continue to play online games despite the potential negative consequences.

Connectivity strength of the EEG functional network in schizophrenia and bipolar disorder

The application of graph theory measures in the study of functional brain networks allows for the description of their general properties and their alterations in mental illness. Among these measures, connectivity strength (CS) estimates the degree of functional connectivity of the whole network. Previous studies in schizophrenia patients have reported higher baseline CS values and modulation deficits in EEG spectral properties during cognitive activity. The specificity of these alterations and their relationships with pharmacological treatments remain unknown. Therefore, in the present study, we assessed functional CS on EEG-based brain networks in 79 schizophrenia and 29 bipolar patients in addition to 63 healthy controls. The subjects performed a P300 task during the EEG recordings from which the pre-stimulus and the task-related modulation CS values were computed in the global and theta bands. These values were compared between the groups and between the patients who had and had not received different treatments. The global band pre-stimulus CS was significantly higher in the schizophrenia group compared with the bipolar and control groups. Theta band CS modulation was decreased in schizophrenia and bipolar patients. Treatment with antipsychotics, lithium, benzodiazepines, and anticonvulsants did not significantly alter these CS values. The first-episode and chronic schizophrenia patients did not show significant differences in CS values. Higher global band pre-stimulus CS values were associated with worse general cognition in schizophrenia patients. These data support increased connectivity in the whole-brain network that is specific to schizophrenia and suggest a general hyper-synchronized basal state that might hamper cognition in this syndrome.

Deep brain stimulation in treatment resistant schizophrenia: A pilot randomized cross-over clinical trial

Background

Up to 30% of patients with schizophrenia are resistant to antipsychotic drug treatment, with 60% of such cases also failing to respond to clozapine. Deep brain stimulation (DBS) has been used in treatment resistant patients with other psychiatric disorders, but there is a lack of trials in schizophrenia, partly due to uncertainties over where to site the electrodes. This trial aimed to examine the effectiveness of nucleus accumbens (NAcc) and subgenual anterior cingulate cortex (subgenual ACC) targeted DBS; the primary outcome measure was PANSS total score, as assessed fortnightly.

Methods

Eight patients with schizophrenia, who met criteria for treatment resistance and were also resistant to/intolerant of clozapine, were randomly assigned using central allocation to receive DBS in the NAcc or subgenual ACC. An open stabilization phase lasting at least six months was followed by a randomized double-blind crossover phase lasting 24 weeks in those who met symptomatic improvement criteria. The primary end-point was a 25% improvement in PANSS total score. (ClinicalTrials.gov Identifier: NCT02377505; trial completed).

Findings

One implanted patient did not receive DBS due to complications of surgery. Of the remaining 7 patients, 2/3 with NAcc and 2/4 with subgenual ACC electrode placements met the symptomatic improvement criteria (58% and 86%, and 37% and 68% improvement in PANSS total score, respectively). Three of these patients entered the crossover phase and all showed worsening when the stimulation was discontinued. The fourth patient worsened after the current was switched off accidentally without her or the investigators’ knowledge. Physical adverse events were uncommon, but two patients developed persistent psychiatric adverse effects (negative symptoms/apathy and mood instability, respectively).

Interpretation

These preliminary findings point to the possibility of DBS having therapeutic effects in patients with schizophrenia who do not respond to any other treatment. Larger trials with careful attention to blinding will be necessary to establish the extent of the benefits and whether these can be achieved without psychiatric side-effects.

Generalizability of machine learning for classification of schizophrenia based on resting-state functional MRI data

Machine learning has increasingly been applied to classification of schizophrenia in neuroimaging research. However, direct replication studies and studies seeking to investigate generalizability are scarce. To address these issues, we assessed within-site and between-site generalizability of a machine learning classification framework which achieved excellent performance in a previous study using two independent resting-state functional magnetic resonance imaging data sets collected from different sites and scanners. We established within-site generalizability of the classification framework in the main data set using cross-validation. Then, we trained a model in the main data set and investigated between-site generalization in the validated data set using external validation. Finally, recognizing the poor between-site generalization performance, we updated the unsupervised algorithm to investigate if transfer learning using additional unlabeled data were able to improve between-site classification performance. Cross-validation showed that the published classification procedure achieved an accuracy of 0.73 using majority voting across all selected components. External validation found a classification accuracy of 0.55 (not significant) and 0.70 (significant) using the direct and transfer learning procedures, respectively. The failure of direct generalization from one site to another demonstrates the limitation of within-site cross-validation and points toward the need to incorporate efforts to facilitate application of machine learning across multiple data sets. The improvement in performance with transfer learning highlights the importance of taking into account the properties of data when constructing predictive models across samples and sites. Our findings suggest that machine learning classification result based on a single study should be interpreted cautiously.

Brain imaging correlates of self- and other-reflection in schizophrenia

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Self- and other-reflection in schizophrenia were studied with fMRI.

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Patients failed to activate the right temporo-parietal junction in other-reflection.

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They also hyperactivated lateral prefrontal cortex for self and other-reflection.

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These findings might be linked to altered self/other processing in schizophrenia.

Background

An alteration in self/other differentiation has been proposed as a basis for several symptoms in schizophrenia, including delusions of reference and social functioning deficits. Dysfunction of the right temporo-parietal junction (TPJ), a region linked with social cognition, has been proposed as the basis of this alteration. However, imaging studies of self- and other-processing in schizophrenia have shown, so far, inconsistent results.

Methods

Patients with schizophrenia and healthy controls underwent fMRI scanning while performing a task with three conditions: self-reflection, other-reflection and semantic processing.

Results

Both groups activated similar brain regions for self- and other-reflection compared to semantic processing, including the medial prefrontal cortex, the precuneus and the TPJ. Compared to healthy subjects, patients hyperactivated the left lateral frontal cortex during self- and other-reflection. In other-reflection, compared to self-reflection, patients failed to increase right TPJ activity.

Conclusions

Altered activity in the right TPJ supports a disturbance in self/other differentiation in schizophrenia, which could be linked with psychotic symptoms and affect social functioning in patients. Hyperactivity of the lateral frontal cortex for self- and other-reflection suggests the presence of greater cognitive demand to perform the task in the patient group.

From State-to-Trait Meditation: Reconfiguration of Central Executive and Default Mode Networks

While brain default mode network (DMN) activation in human subjects has been associated with mind wandering, meditation practice has been found to suppress it and to increase psychological well-being. In addition to DMN activity reduction, experienced meditators (EMs) during meditation practice show an increased connectivity between the DMN and the central executive network (CEN).

While brain default mode network (DMN) activation in human subjects has been associated with mind wandering, meditation practice has been found to suppress it and to increase psychological well-being. In addition to DMN activity reduction, experienced meditators (EMs) during meditation practice show an increased connectivity between the DMN and the central executive network (CEN). However, the gradual change between DMN and CEN configuration from pre-meditation, during meditation, and post-meditation is unknown. Here, we investigated the change in DMN and CEN configuration by means of brain activity and functional connectivity (FC) analyses in EMs across three back-to-back functional magnetic resonance imaging (fMRI) scans: pre-meditation baseline (trait), meditation (state), and post-meditation (state-to-trait). Pre-meditation baseline group comparison was also performed between EMs and healthy controls (HCs). Meditation trait was characterized by a significant reduction in activity and FC within DMN and increased anticorrelations between DMN and CEN. Conversely, meditation state and meditation state-to-trait periods showed increased activity and FC within the DMN and between DMN and CEN. However, the latter anticorrelations were only present in EMs with limited practice. The interactions between networks during these states by means of positive diametric activity (PDA) of the fractional amplitude of low-frequency fluctuations (fALFFs) defined as CEN fALFF¯ − DMN fALFF¯ revealed no trait differences but significant increases during meditation state that persisted in meditation state-to-trait. The gradual reconfiguration in DMN and CEN suggest a neural mechanism by which the CEN negatively regulates the DMN and is probably responsible for the long-term trait changes seen in meditators and reported psychological well-being.

Paradoxical regulation of iron in hippocampus and prefrontal cortex induces schizophrenic-like symptoms in male rats

Introduction: Social isolation induces schizophrenic-like symptoms. Iron is an essential element for brain functions. The aim of this study is to investigate if the emergence of schizophrenia after social isolation is the result of impaired iron metabolism in the hippocampus and in the prefrontal cortex.Methods and materials: In this study, 42 male Sprague-Dawley rats were randomly divided into six groups: 1) grouped housed (GH), 2) socially isolated (SI), 3) grouped housed + vehicle, 4) grouped housed + morphine, 5) socially isolated + vehicle and 6) socially isolated + morphine. After 14 days of social isolation and group housing, behavioral experiments were performed. Then, the iron in the hippocampus, prefrontal cortex, and serum was assessed.Results: SI rats were more anxious in compared to GH rats. Memory was better in GH rats compared to SI rats. SI rats had more locomotor activity compared to GH rats. Iron was higher in the hippocampus in GH rats compared to SI rats. Paradoxically iron was higher in the prefrontal cortex in SI rats compared to GH rats. In serum, iron was higher in GH rats compared to SI rats.Conclusion: Emergence of schizophrenic-like symptoms is associated with the paradoxical concentration of iron in hippocampus and prefrontal cortex in the isolation period. Further studies are recommended to investigate the possible specific changes in ion transporters and the metabolism of the neurotransmitter that occurs as the result of this paradoxical regulation.

Frontostriatal functional connectivity and striatal dopamine synthesis capacity in schizophrenia in terms of antipsychotic responsiveness: an [18F]DOPA PET and fMRI study

BACKGROUND

Given that only a subgroup of patients with schizophrenia responds to first-line antipsychotic drugs, a key clinical question is what underlies treatment response. Observations that prefrontal activity correlates with striatal dopaminergic function, have led to the hypothesis that disrupted frontostriatal functional connectivity (FC) could be associated with altered dopaminergic function. Thus, the aim of this study was to investigate the relationship between frontostriatal FC and striatal dopamine synthesis capacity in patients with schizophrenia who had responded to first-line antipsychotic drug compared with those who had failed but responded to clozapine.

METHODS

Twenty-four symptomatically stable patients with schizophrenia were recruited from Seoul National University Hospital, 12 of which responded to first-line antipsychotic drugs (first-line AP group) and 12 under clozapine (clozapine group), along with 12 matched healthy controls. All participants underwent resting-state functional magnetic resonance imaging and [18F]DOPA PET scans.

RESULTS

No significant difference was found in the total PANSS score between the patient groups. Voxel-based analysis showed a significant correlation between frontal FC to the associative striatum and the influx rate constant of [18F]DOPA in the corresponding region in the first-line AP group. Region-of-interest analysis confirmed the result (control group: R2 = 0.019, p = 0.665; first-line AP group: R2 = 0.675, p < 0.001; clozapine group: R2 = 0.324, p = 0.054) and the correlation coefficients were significantly different between the groups.

CONCLUSIONS

The relationship between striatal dopamine synthesis capacity and frontostriatal FC is different between responders to first-line treatment and clozapine treatment in schizophrenia, indicating that a different pathophysiology could underlie schizophrenia in patients who respond to first-line treatments relative to those who do not.