Altered resting-state functional connectivity and anatomical connectivity of hippocampus in schizophrenia

Abnormal resting-state hyperconnectivity in schizophrenia: A whole-head near-infrared spectroscopy study

Near-infrared spectroscopy (NIRS) is a noninvasive functional neuroimaging modality that can detect changes in blood oxygenation levels by tracking cortical neural activity. We recorded the resting-state brain activity of 24 individuals with schizophrenia and 90 healthy controls for 8 min using a whole-head NIRS arrangement and then used partial correlation analysis to estimate the resting-state functional connectivity (RSFC) between 17 cortical regions. We found that the RSFC between the bilateral orbitofrontal cortices (OFCs) and between the right temporal and parietal lobes was significantly higher in patients with schizophrenia than in healthy controls. The RSFC between the bilateral OFCs was positively correlated with negative symptom severity, whereas the RSFC between the right temporal and parietal lobes was positively correlated with the chlorpromazine equivalent for antipsychotics prescribed to patients with schizophrenia. This finding was consistent with that for the RSFC calculated using the anterior 52-channel signals. Our results suggest that NIRS-based RSFC measurements have potential clinical applications.

A connectome-wide association study of altered functional connectivity in schizophrenia based on resting-state fMRI

BACKGROUND

Aberrant resting-state functional connectivity is a neuropathological feature of schizophrenia (SCZ). Prior investigations into functional connectivity abnormalities have primarily employed seed-based connectivity analysis, necessitating predefined seed locations. To address this limitation, a data-driven multivariate method known as connectome-wide association study (CWAS) has been proposed for exploring whole-brain functional connectivity.

METHODS

We conducted a CWAS analysis involving 46 patients with SCZ and 40 age- and sex-matched healthy controls. Multivariate distance matrix regression (MDMR) was utilized to identify key nodes in the brain. Subsequently, we conducted a follow-up seed-based connectivity analysis to elucidate specific connectivity patterns between regions of interest (ROIs). Additionally, we explored the spatial correlation between changes in functional connectivity and underlying molecular architectures by examining correlations between neurotransmitter/transporter distribution densities and functional connectivity.

RESULTS

MDMR revealed the right medial frontal gyrus and the left calcarine sulcus as two key nodes. Follow-up analysis unveiled hypoconnectivity between the right medial frontal superior gyrus and the right fusiform gyrus, as well as hypoconnectivity between the left calcarine sulcus and the right lingual gyrus in SCZ. Notably, a significant association between functional connectivity strength and positive symptom severity was identified. Furthermore, altered functional connectivity patterns suggested potential dysfunctions in the dopamine, serotonin, and gamma-aminobutyric acid systems.

CONCLUSIONS

This study elucidated reduced functional connectivity both within and between the medial frontal regions and the occipital cortex in patients with SCZ. Moreover, it indicated potential alterations in molecular architecture, thereby expanding current knowledge regarding neurobiological changes associated with SCZ.

Videogame training increases clinical well-being, attention and hippocampal-prefrontal functional connectivity in patients with schizophrenia

Recent research shows that videogame training enhances neuronal plasticity and cognitive improvements in healthy individuals. As patients with schizophrenia exhibit reduced neuronal plasticity linked to cognitive deficits and symptoms, we investigated whether videogame-related cognitive improvements and plasticity changes extend to this population. In a training study, patients with schizophrenia and healthy controls were randomly assigned to 3D or 2D platformer videogame training or E-book reading (active control) for 8 weeks, 30 min daily. After training, both videogame conditions showed significant increases in sustained attention compared to the control condition, correlated with increased functional connectivity in a hippocampal-prefrontal network. Notably, patients trained with videogames mostly improved in negative symptoms, general psychopathology, and perceived mental health recovery. Videogames, incorporating initiative, goal setting and gratification, offer a training approach closer to real life than current psychiatric treatments. Our results provide initial evidence that they may represent a possible adjunct therapeutic intervention for complex mental disorders.

The relationship between the resting state functional connectivity and social cognition in schizophrenia: Results from the Italian Network for Research on Psychoses

Deficits in social cognition (SC) interfere with recovery in schizophrenia (SZ) and may be related to resting state brain connectivity. This study aimed at assessing the alterations in the relationship between resting state functional connectivity and the social-cognitive abilities of patients with SZ compared to healthy subjects. We divided the brain into 246 regions of interest (ROI) following the Human Healthy Volunteers Brainnetome Atlas. For each participant, we calculated the resting-state functional connectivity (rsFC) in terms of degree centrality (DC), which evaluates the total strength of the most powerful coactivations of every ROI with all other ROIs during rest. The rs-DC of the ROIs was correlated with five measures of SC assessing emotion processing and mentalizing in 45 healthy volunteers (HVs) chosen as a normative sample. Then, controlling for symptoms severity, we verified whether these significant associations were altered, i.e., absent or of opposite sign, in 55 patients with SZ. We found five significant differences between SZ patients and HVs: in the patients' group, the correlations between emotion recognition tasks and rsFC of the right entorhinal cortex (R-EC), left superior parietal lobule (L-SPL), right caudal hippocampus (R-c-Hipp), and the right caudal (R-c) and left rostral (L-r) middle temporal gyri (MTG) were lost. An altered resting state functional connectivity of the L-SPL, R-EC, R-c-Hipp, and bilateral MTG in patients with SZ may be associated with impaired emotion recognition. If confirmed, these results may enhance the development of non-invasive brain stimulation interventions targeting those cerebral regions to reduce SC deficit in SZ.

Abnormal Spatial and Temporal Overlap of Time-Varying Brain Functional Networks in Patients with Schizophrenia

Schizophrenia (SZ) is a complex psychiatric disorder with unclear etiology and pathological features. Neuroscientists are increasingly proposing that schizophrenia is an abnormality in the dynamic organization of brain networks. Previous studies have found that the dynamic brain networks of people with SZ are abnormal in both space and time. However, little is known about the interactions and overlaps between hubs of the brain underlying spatiotemporal dynamics. In this study, we aimed to investigate different patterns of spatial and temporal overlap of hubs between SZ patients and healthy individuals. Specifically, we obtained resting-state functional magnetic resonance imaging data from the public dataset for 43 SZ patients and 49 healthy individuals. We derived a representation of time-varying functional connectivity using the Jackknife Correlation (JC) method. We employed the Betweenness Centrality (BC) method to identify the hubs of the brain's functional connectivity network. We then applied measures of temporal overlap, spatial overlap, and hierarchical clustering to investigate differences in the organization of brain hubs between SZ patients and healthy controls. Our findings suggest significant differences between SZ patients and healthy controls at the whole-brain and subnetwork levels. Furthermore, spatial overlap and hierarchical clustering analysis showed that quasi-periodic patterns were disrupted in SZ patients. Analyses of temporal overlap revealed abnormal pairwise engagement preferences in the hubs of SZ patients. These results provide new insights into the dynamic characteristics of the network organization of the SZ brain.

Hippocampal Network Dysfunction in Early Psychosis: A 2-Year Longitudinal Study

Background

Hippocampal abnormalities are among the most consistent findings in schizophrenia. Numerous studies have reported deficits in hippocampal volume, function, and connectivity in the chronic stage of illness. While hippocampal volume and function deficits are also present in the early stage of illness, there is mixed evidence of both higher and lower functional connectivity. Here, we use graph theory to test the hypothesis that hippocampal network connectivity is broadly lowered in early psychosis and progressively worsens over 2 years.

Methods

We examined longitudinal resting-state functional connectivity in 140 participants (68 individuals in the early stage of psychosis, 72 demographically similar healthy control individuals). We used an anatomically driven approach to quantify hippocampal network connectivity at 2 levels: 1) a core hippocampal-medial temporal lobe cortex (MTLC) network; and 2) an extended hippocampal-cortical network. Group and time effects were tested in a linear mixed effects model.

Results

Early psychosis patients showed elevated functional connectivity in the core hippocampal-MTLC network, but contrary to our hypothesis, did not show alterations within the broader hippocampal-cortical network. Hippocampal-MTLC network hyperconnectivity normalized longitudinally and predicted improvement in positive symptoms but was not associated with increasing illness duration.

Conclusions

These results show abnormally elevated functional connectivity in a core hippocampal-MTLC network in early psychosis, suggesting that selectively increased hippocampal signaling within a localized cortical circuit may be a marker of the early stage of psychosis. Hippocampal-MTLC hyperconnectivity could have prognostic and therapeutic implications.

Resting-State Functional Connectivity Explained Psychotic-like Experiences in the General Population and Partially Generalized to Patients and Relatives

Background

Psychotic-like experiences (PLEs) are considered the subclinical portion of the psychosis continuum. Research suggests that there are resting-state functional connectivity (rsFC) substrates of PLEs, yet it is unclear if the same substrates underlie more severe psychosis. Here, to our knowledge, we report the first study to build a cross-validated rsFC model of PLEs in a large community sample and directly test its ability to explain psychosis in an independent sample of patients with psychosis and their relatives.

Methods

Resting-state FC of 855 healthy young adults from the WU-Minn Human Connectome Project (HCP) was used to predict PLEs with elastic net. An rsFC composite score based on the resulting model was correlated with psychotic traits and symptoms in 118 patients with psychosis, 71 nonpsychotic first-degree relatives, and 45 healthy control subjects from the psychosis HCP.

Results

In the HCP, the cross-validated model explained 3.3% of variance in PLEs. Predictive connections spread primarily across the default, frontoparietal, cingulo-opercular, and dorsal attention networks. The model partially generalized to a younger, but not older, subsample in the psychosis HCP, explaining two measures of positive/disorganized psychotic traits (the Structured Interview for Schizotypy: β = 0.25, pone-tailed = .027; the Schizotypy Personality Questionnaire positive factor: β = 0.14, pone-tailed = .041). However, it did not differentiate patients from relatives and control subjects or explain psychotic symptoms in patients.

Conclusions

Some rsFC substrates of PLEs are shared across the psychosis continuum. However, explanatory power was modest, and generalization was partial. It is equally important to understand shared versus distinct rsFC variances across the psychosis continuum.

Functional and Structural Longitudinal Change Patterns in Adolescent Brain

Functional magnetic resonance imaging (fMRI) and structural magnetic resonance imaging (sMRI) are two widely used techniques to analyze longitudinal brain functional and structural change in adolescents. Although longitudinal changes in intrinsic functional and structural changes have been studied separately, most studies focus on univariate change rather than estimating multivariate patterns of functional network connectivity (FNC) and gray matter (GM) changes with increased age. To analyze whole-brain structural and functional changes with increased age, we suggest two complementary techniques (1: linking of functional change pattern (FCP) to voxel-wise ∆GM and 2: the connection between FCP and structural change pattern (SCP)). In this study, we apply our approaches to the functional and GM data from the large-scale Adolescent Brain and Cognitive Development (ABCD) data. We find a significant correlation between FCP and voxel-wise ∆GM for two components. We also investigate the links between FCP and SCP and hypothesize that functional connectivity and GM continue to exhibit linked changes during adolescence.Clinical Relevance- This work captures the whole-brain functional and structural change patterns link by introducing two complementary techniques.

Impaired large-scale cortico-hippocampal network connectivity, including the anterior temporal and posterior medial systems, and its associations with cognition in patients with first-episode schizophrenia

Background and objective

The cortico-hippocampal network is an emerging neural framework with striking evidence that it supports cognition in humans, especially memory; this network includes the anterior temporal (AT) system, the posterior medial (PM) system, the anterior hippocampus (aHIPPO), and the posterior hippocampus (pHIPPO). This study aimed to detect aberrant patterns of functional connectivity within and between large-scale cortico-hippocampal networks in first-episode schizophrenia patients compared with a healthy control group via resting-state functional magnetic resonance imaging (rs-fMRI) and to explore the correlations of these aberrant patterns with cognition.

Methods

A total of 86 first-episode, drug-naïve schizophrenia patients and 102 healthy controls (HC) were recruited to undergo rs-fMRI examinations and clinical evaluations. We conducted large-scale edge-based network analysis to characterize the functional architecture of the cortico-hippocampus network and investigate between-group differences in within/between-network functional connectivity. Additionally, we explored the associations of functional connectivity (FC) abnormalities with clinical characteristics, including scores on the Positive and Negative Syndrome Scale (PANSS) and cognitive scores.

Results

Compared with the HC group, schizophrenia patients exhibited widespread alterations to within-network FC of the cortico-hippocampal network, with decreases in FC involving the precuneus (PREC), amygdala (AMYG), parahippocampal cortex (PHC), orbitofrontal cortex (OFC), perirhinal cortex (PRC), retrosplenial cortex (RSC), posterior cingulate cortex (PCC), angular gyrus (ANG), aHIPPO, and pHIPPO. Schizophrenia patients also showed abnormalities in large-scale between-network FC of the cortico-hippocampal network, in the form of significantly decreased FC between the AT and the PM, the AT and the aHIPPO, the PM and the aHIPPO, and the aHIPPO and the pHIPPO. A number of these signatures of aberrant FC were correlated with PANSS score (positive, negative, and total score) and with scores on cognitive test battery items, including attention/vigilance (AV), working memory (WM), verbal learning and memory (Verb_Lrng), visual learning and memory (Vis_Lrng), reasoning and problem-solving (RPS), and social cognition (SC).

Conclusion

Schizophrenia patients show distinct patterns of functional integration and separation both within and between large-scale cortico-hippocampal networks, reflecting a network imbalance of the hippocampal long axis with the AT and PM systems, which regulate cognitive domains (mainly Vis_Lrng, Verb_Lrng, WM, and RPS), and particularly involving alterations to FC of the AT system and the aHIPPO. These findings provide new insights into the neurofunctional markers of schizophrenia.

Hippocampal Hyperconnectivity to the Visual Cortex Predicts Treatment Response

BACKGROUND

Converging lines of evidence point to hippocampal dysfunction in psychosis spectrum disorders, including altered functional connectivity. Evidence also suggests that antipsychotic medications can modulate hippocampal dysfunction. The goal of this project was to identify patterns of hippocampal connectivity predictive of response to antipsychotic treatment in 2 cohorts of patients with a psychosis spectrum disorder, one medication-naïve and the other one unmedicated.

HYPOTHESIS

We hypothesized that we would identify reliable patterns of hippocampal connectivity in the 2 cohorts that were predictive of treatment response and that medications would modulate abnormal hippocampal connectivity after 6 weeks of treatment.

STUDY DESIGN

We used a prospective design to collect resting-state fMRI scans prior to antipsychotic treatment and after 6 weeks of treatment with risperidone, a commonly used antipsychotic medication, in both cohorts. We enrolled 44 medication-naïve first-episode psychosis patients (FEP) and 39 unmedicated patients with schizophrenia (SZ).

STUDY RESULTS

In both patient cohorts, we observed a similar pattern where greater hippocampal connectivity to regions of the occipital cortex was predictive of treatment response. Lower hippocampal connectivity of the frontal pole, orbitofrontal cortex, subcallosal area, and medial prefrontal cortex was predictive of treatment response in unmedicated SZ, but not in the medication-naïve cohort. Furthermore, greater reduction in hippocampal connectivity to the visual cortex with treatment was associated with better clinical response.

CONCLUSIONS

Our results suggest that greater connectivity between the hippocampus and occipital cortex is not only predictive of better treatment response, but that antipsychotic medications have a modulatory effect by reducing hyperconnectivity.

Episodic Memory formation: A review of complex Hippocampus input pathways

Memories of everyday experiences involve the encoding of a rich and dynamic representation of present objects and their contextual features. Traditionally, the resulting mnemonic trace is referred to as Episodic Memory, i.e. the "what", "where" and "when" of a lived episode. The journey for such memory trace encoding begins with the perceptual data of an experienced episode handled in sensory brain regions. The information is then streamed to cortical areas located in the ventral Medio Temporal Lobe, which produces multi-modal representations concerning either the objects (in the Perirhinal cortex) or the spatial and contextual features (in the parahippocampal region) of the episode. Then, this high-level data is gated through the Entorhinal Cortex and forwarded to the Hippocampal Formation, where all the pieces get bound together. Eventually, the resulting encoded neural pattern is relayed back to the Neocortex for a stable consolidation. This review will detail these different stages and provide a systematic overview of the major cortical streams toward the Hippocampus relevant for Episodic Memory encoding.

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.

Functional re-organization of hippocampal-cortical gradients during naturalistic memory processes

The functional organization of the hippocampus mirrors that of the cortex, changing smoothly along connectivity gradients and abruptly at inter-areal boundaries. Hippocampal-dependent cognitive processes require flexible integration of these hippocampal gradients into functionally related cortical networks. To understand the cognitive relevance of this functional embedding, we acquired fMRI data while participants viewed brief news clips, either containing or lacking recently familiarized cues. Participants were 188 healthy mid-life adults and 31 adults with mild cognitive impairment (MCI) or Alzheimer's disease (AD). We employed a recently developed technique - connectivity gradientography - to study gradually changing patterns of voxel to whole brain functional connectivity and their sudden transitions. We observed that functional connectivity gradients of the anterior hippocampus map onto connectivity gradients across the default mode network during these naturalistic stimuli. The presence of familiar cues in the news clips accentuates a stepwise transition across the boundary from the anterior to the posterior hippocampus. This functional transition is shifted in the posterior direction in the left hippocampus of individuals with MCI or AD. These findings shed new light on the functional integration of hippocampal connectivity gradients into large-scale cortical networks, how these adapt with memory context and how these change in the presence of neurodegenerative disease.

Pentad: A reproducible cytoarchitectonic protocol and its application to parcellation of the human hippocampus

Introduction

The hippocampus is integral for learning and memory and is targeted by multiple diseases. Neuroimaging approaches frequently use hippocampal subfield volumes as a standard measure of neurodegeneration, thus making them an essential biomarker to study. Collectively, histologic parcellation studies contain various disagreements, discrepancies, and omissions. The present study aimed to advance the hippocampal subfield segmentation field by establishing the first histology based parcellation protocol, applied to n = 22 human hippocampal samples.

Methods

The protocol focuses on five cellular traits observed in the pyramidal layer of the human hippocampus. We coin this approach the pentad protocol. The traits were: chromophilia, neuron size, packing density, clustering, and collinearity. Subfields included were CA1, CA2, CA3, CA4, prosubiculum, subiculum, presubiculum, parasubiculum, as well as the medial (uncal) subfields Subu, CA1u, CA2u, CA3u, and CA4u. We also establish nine distinct anterior-posterior levels of the hippocampus in the coronal plane to document rostrocaudal differences.

Results

Applying the pentad protocol, we parcellated 13 subfields at nine levels in 22 samples. We found that CA1 had the smallest neurons, CA2 showed high neuronal clustering, and CA3 displayed the most collinear neurons of the CA fields. The border between presubiculum and subiculum was staircase shaped, and parasubiculum had larger neurons than presubiculum. We also demonstrate cytoarchitectural evidence that CA4 and prosubiculum exist as individual subfields.

Discussion

This protocol is comprehensive, regimented and supplies a high number of samples, hippocampal subfields, and anterior-posterior coronal levels. The pentad protocol utilizes the gold standard approach for the human hippocampus subfield parcellation.

The genetic influence of the DRD3 rs6280 polymorphism (Ser9Gly) on functional connectivity and gray matter volume of the hippocampus in patients with first-episode, drug-naïve schizophrenia

The D3 dopamine receptor (DRD3) plays a major role in cognitive function and is a candidate gene for schizophrenia. DRD3 is widely distributed in the hippocampus, but whether there are potential associations between the rs6280 genotype, the hippocampus, and cognitive function in first-episode, drug-naïve (FES) patients and healthy controls (HCs) is still poorly understood. First, using functional and structural magnetic resonance imaging data, we calculated the gray matter volume (GMV) and functional connectivity (FC) of the hippocampus. Then, we examined the possible interaction effect of the DRD3 genotype and the disease on the FC and GMV of the hippocampus in 52 FES patients and 51 HCs. Finally, the correlation between the FC and GMV in the hippocampus, influenced by rs6280, and the cognitive performance of subjects was analyzed. A significant interaction effect of diagnostic group by genotype of rs6280 on the GMV of the left hippocampus was found, with lower GMV in FES patients that were C carriers compared with TT homozygotes; the opposite pattern was found in the genetic subgroups of HCs. In the FES group, C carriers performed significantly worse on reasoning and problem-solving tests than TT homozygotes. The left hippocampal GMV positively correlated with reasoning and problem-solving performance in TT homozygotes, but this correlation disappeared in FES patients that were C carriers and in genetic subgroups of HCs. Together, these results suggest that FES patients that are C carriers of rs6280 have lower GMV in the hippocampus, resulting in greater cognitive impairment.

An evolutionary account of impairment of self in cognitive disorders

Recent research has proposed that certain aspects of psychosis, as experienced in, e.g., schizophrenia (SCZ), but also aspects of other cognitive conditions, such as autism spectrum disorders (ASD) and synesthesia, can be related to a shattered sense of the notion of self. In this paper, our goal is to show that altered processing of self can be attributed to an abnormal functioning of cortico-striatal brain networks supporting, among other, one key human distinctive cognitive ability, namely cross-modality, which plays multiple roles in human cognition and language. Specifically, our hypothesis is that this cognitive mechanism sheds light both on some basic aspects of the minimal self and on some aspects related to higher forms of self, such as the narrative self. We further link the atypical functioning in these conditions to some recent evolutionary changes in our species, specifically, an atypical presentation of human self-domestication (HSD) features. In doing so, we also lean on previous work concerning the link between cognitive disorders and language evolution under the effects of HSD. We further show that this approach can unify both linguistic and non-linguistic symptoms of these conditions through deficits in the notion of self. Our considerations provide further support for the hypothesis that SCZ and ASD are diametrically opposed cognitive conditions, as well for the hypothesis that their etiology is associated with recent human evolution, leading to a deeper understanding of the causes and symptoms of these disorders, and providing new cues, which can be used for an earlier and more accurate diagnostics.

Brain responses in aggression-prone individuals: A systematic review and meta-analysis of functional magnetic resonance imaging (fMRI) studies of anger- and aggression-eliciting tasks

Reactive aggression in response to perceived threat or provocation is part of humans' adaptive behavioral repertoire. However, high levels of aggression can lead to the violation of social and legal norms. Understanding brain function in individuals with high levels of aggression as they process anger- and aggression-eliciting stimuli is critical for refining explanatory models of aggression and thereby improving interventions. Three neurobiological models of reactive aggression - the limbic hyperactivity, prefrontal hypoactivity, and dysregulated limbic-prefrontal connectivity models - have been proposed. However, these models are based on neuroimaging studies involving mainly non-aggressive individuals, leaving it unclear which model best describes brain function in those with a history of aggression. We conducted a systematic literature search (PubMed and Psycinfo) and Multilevel Kernel Density meta-analysis (MKDA) of nine functional magnetic resonance imaging (fMRI) studies (eight included in the between-group analysis [i.e., aggression vs. control groups], five in the within-group analysis). Studies examined brain responses to tasks putatively eliciting anger and aggression in individuals with a history of aggression alone and relative to controls. Individuals with a history of aggression exhibited greater activity in the superior temporal gyrus and in regions comprising the cognitive control and default mode networks (right posterior cingulate cortex, precentral gyrus, precuneus, right inferior frontal gyrus) during reactive aggression relative to baseline conditions. Compared to controls, individuals with a history of aggression exhibited increased activity in limbic regions (left hippocampus, left amygdala, left parahippocampal gyrus) and temporal regions (superior, middle, inferior temporal gyrus), and reduced activity in occipital regions (left occipital cortex, left calcarine cortex). These findings lend support to the limbic hyperactivity model in individuals with a history of aggression, and further indicate altered temporal and occipital activity in anger- and aggression-eliciting conditions involving face and speech processing.

The Role of D-Serine and D-Aspartate in the Pathogenesis and Therapy of Treatment-Resistant Schizophrenia

Schizophrenia (Sch) is a severe and widespread mental disorder. Antipsychotics (APs) of the first and new generations as the first-line treatment of Sch are not effective in about a third of cases and are also unable to treat negative symptoms and cognitive deficits of schizophrenics. This explains the search for new therapeutic strategies for a disease-modifying therapy for treatment-resistant Sch (TRS). Biological compounds are of great interest to researchers and clinicians, among which D-Serine (D-Ser) and D-Aspartate (D-Asp) are among the promising ones. The Sch glutamate theory suggests that neurotransmission dysfunction caused by glutamate N-methyl-D-aspartate receptors (NMDARs) may represent a primary deficiency in this mental disorder and play an important role in the development of TRS. D-Ser and D-Asp are direct NMDAR agonists and may be involved in modulating the functional activity of dopaminergic neurons. This narrative review demonstrates both the biological role of D-Ser and D-Asp in the normal functioning of the central nervous system (CNS) and in the pathogenesis of Sch and TRS. Particular attention is paid to D-Ser and D-Asp as promising components of a nutritive disease-modifying therapy for TRS.

Dose-dependent effects of esketamine on brain activity in awake mice: A BOLD phMRI study

Pharmacological magnetic resonance imaging (phMRI) is a noninvasive method used to evaluate neural circuitry involved in the behavioral effects of drugs like ketamine, independent of their specific biochemical mechanism. The study was designed to evaluate the immediate effect of esketamine, the S-isomer of (±) ketamine on brain activity in awake mice using blood oxygenation level dependent (BOLD) imaging. It was hypothesized the prefrontal cortex, hippocampus, and brain areas associated with reward and motivation would show a dose-dependent increase in brain activity. Mice were given vehicle, 1.0, 3.3, or 10 mg/kg esketamine I.P. and imaged for 10 min post-treatment. Data for each treatment were registered to a 3D MRI mouse brain atlas providing site-specific information on 134 different brain areas. There was a global change in brain activity for both positive and negative BOLD signal affecting over 50 brain areas. Many areas showed a dose-dependent decrease in positive BOLD signal, for example, cortex, hippocampus, and thalamus. The most common profile when comparing the three doses was a U-shape with the 3.3 dose having the lowest change in signal. At 1.0 mg/kg there was a significant increase in positive BOLD in forebrain areas and hippocampus. The anticipated dose-dependent increase in BOLD was not realized; instead, the lowest dose of 1.0 mg/kg had the greatest effect on brain activity. The prefrontal cortex and hippocampus were significantly activated corroborating previous imaging studies in humans and animals. The unexpected sensitivity to the 1.0 mg/kg dose of esketamine could be explained by imaging in fully awake mice without the confound of anesthesia and/or its greater affinity for the N-methyl-d-aspartate receptor (NMDAR) receptor than (±) ketamine.

Disruptions in white matter microstructure associated with impaired visual associative memory in schizophrenia-spectrum illness

Episodic memory ability relies on hippocampal-prefrontal connectivity. However, few studies have examined relationships between memory performance and white matter (WM) microstructure in hippocampal-prefrontal pathways in schizophrenia-spectrum disorder (SSDs). Here, we investigated these relationships in individuals with first-episode psychosis (FEP) and chronic schizophrenia-spectrum disorders (SSDs) using tractography analysis designed to interrogate the microstructure of WM tracts in the hippocampal-prefrontal pathway. Measures of WM microstructure (fractional anisotropy [FA], radial diffusivity [RD], and axial diffusivity [AD]) were obtained for 47 individuals with chronic SSDs, 28 FEP individuals, 52 older healthy controls, and 27 younger healthy controls. Tractography analysis was performed between the hippocampus and three targets involved in hippocampal-prefrontal connectivity (thalamus, amygdala, nucleus accumbens). Measures of WM microstructure were then examined in relation to episodic memory performance separately across each group. Both those with FEP and chronic SSDs demonstrated impaired episodic memory performance. However, abnormal WM microstructure was only observed in individuals with chronic SSDs. Abnormal WM microstructure in the hippocampal-thalamic pathway in the right hemisphere was associated with poorer memory performance in individuals with chronic SSDs. These findings suggest that disruptions in WM microstructure in the hippocampal-prefrontal pathway may contribute to memory impairments in individuals with chronic SSDs but not FEP.

Abnormal resting-state functional connectivity of hippocampal subregions in children with primary nocturnal enuresis

Objective

Previous neuroimaging studies have shown abnormal brain-bladder control network in children with primary nocturnal enuresis (PNE). The hippocampus, which has long been considered to be an important nerve center for memory and emotion, has also been confirmed to be activating during micturition in several human imaging studies. However, few studies have explored hippocampus-related functional networks of PNE in children. In this study, the whole resting-state functional connectivity (RSFC) of hippocampus was investigated in children with PNE.

Methods

Functional magnetic resonance imaging data of 30 children with PNE and 29 matched healthy controls (HCs) were analyzed in our study. We used the seed-based RSFC method to evaluate the functional connectivity of hippocampal subregions defined according to the Human Brainnetome Atlas. Correlation analyses were also processed to investigate their relationship with disease duration time, bed-wetting frequency, and bladder volume.

Results

Compared with HCs, children with PNE showed abnormal RSFC of the left rostral hippocampus (rHipp) with right fusiform gyrus, right Rolandic operculum, left inferior parietal lobule, and right precentral gyrus, respectively. Moreover, decreased RSFC of the left caudal hippocampus (cHipp) with right fusiform gyrus and right supplementary motor area was discovered in the PNE group. There were no significant results in the right rHipp and cHipp seeds after multiple comparison corrections. In addition, disease duration time was negatively correlated with RSFC of the left rHipp with right Rolandic operculum (r = -0.386, p = 0.035, uncorrected) and the left cHipp with right fusiform gyrus (r = -0.483, p = 0.007, uncorrected) in the PNE group, respectively. In the Receiver Operating Characteristic (ROC) analysis, all the above results of RSFC achieved significant performance.

Conclusions

To our knowledge, this is the first attempt to examine the RSFC patterns of hippocampal subregions in children with PNE. These findings indicated that children with PNE have potential dysfunctions in the limbic network, sensorimotor network, default mode network, and frontoparietal network. These networks may become less efficient with disease duration time, inducing impairments in brain-bladder control, cognition, memory, and emotion. Further prospective research with dynamic observation of brain imaging, bladder function, cognition, memory, and emotion is warranted.

Structural and Functional Deviations of the Hippocampus in Schizophrenia and Schizophrenia Animal Models

Schizophrenia is a grave neuropsychiatric disease which frequently onsets between the end of adolescence and the beginning of adulthood. It is characterized by a variety of neuropsychiatric abnormalities which are categorized into positive, negative and cognitive symptoms. Most therapeutical strategies address the positive symptoms by antagonizing D2-dopamine-receptors (DR). However, negative and cognitive symptoms persist and highly impair the life quality of patients due to their disabling effects. Interestingly, hippocampal deviations are a hallmark of schizophrenia and can be observed in early as well as advanced phases of the disease progression. These alterations are commonly accompanied by a rise in neuronal activity. Therefore, hippocampal formation plays an important role in the manifestation of schizophrenia. Furthermore, studies with animal models revealed a link between environmental risk factors and morphological as well as electrophysiological abnormalities in the hippocampus. Here, we review recent findings on structural and functional hippocampal abnormalities in schizophrenic patients and in schizophrenia animal models, and we give an overview on current experimental approaches that especially target the hippocampus. A better understanding of hippocampal aberrations in schizophrenia might clarify their impact on the manifestation and on the outcome of this severe disease.

Statelets: Capturing recurrent transient variations in dynamic functional network connectivity

Dynamic functional network connectivity (dFNC) analysis is a widely used approach for capturing brain activation patterns, connectivity states, and network organization. However, a typical sliding window plus clustering (SWC) approach for analyzing dFNC models the system through a fixed sequence of connectivity states. SWC assumes connectivity patterns span throughout the brain, but they are relatively spatially constrained and temporally short‐lived in practice. Thus, SWC is neither designed to capture transient dynamic changes nor heterogeneity across subjects/time. We propose a state‐space time series summarization framework called “statelets” to address these shortcomings. It models functional connectivity dynamics at fine‐grained timescales, adapting time series motifs to changes in connectivity strength, and constructs a concise yet informative representation of the original data that conveys easily comprehensible information about the phenotypes. We leverage the earth mover distance in a nonstandard way to handle scale differences and utilize kernel density estimation to build a probability density profile for local motifs. We apply the framework to study dFNC of patients with schizophrenia (SZ) and healthy control (HC). Results demonstrate SZ subjects exhibit reduced modularity in their brain network organization relative to HC. Statelets in the HC group show an increased recurrence across the dFNC time‐course compared to the SZ. Analyzing the consistency of the connections across time reveals significant differences within visual, sensorimotor, and default mode regions where HC subjects show higher consistency than SZ. The introduced approach also enables handling dynamic information in cross‐modal and multimodal applications to study healthy and disordered brains.

Discriminative Analysis of Schizophrenia Patients Using Topological Properties of Structural and Functional Brain Networks: A Multimodal Magnetic Resonance Imaging Study

Interest in the application of machine learning (ML) techniques to multimodal magnetic resonance imaging (MRI) data for the diagnosis of schizophrenia (SZ) at the individual level is growing. However, a few studies have applied the features of structural and functional brain networks derived from multimodal MRI data to the discriminative analysis of SZ patients at different clinical stages. In this study, 205 normal controls (NCs), 61 first-episode drug-naive SZ (FESZ) patients, and 79 chronic SZ (CSZ) patients were recruited. We acquired their structural MRI, diffusion tensor imaging, and resting-state functional MRI data and constructed brain networks for each participant, including the gray matter network (GMN), white matter network (WMN), and functional brain network (FBN). We then calculated 3 nodal properties for each brain network, including degree centrality, nodal efficiency, and betweenness centrality. Two classifications (SZ vs. NC and FESZ vs. CSZ) were performed using five ML algorithms. We found that the SVM classifier with the input features of the combination of nodal properties of both the GMN and FBN achieved the best performance to discriminate SZ patients from NCs [accuracy, 81.2%; area under the receiver operating characteristic curve (AUC), 85.2%; p < 0.05]. Moreover, the SVM classifier with the input features of the combination of the nodal properties of both the GMN and WMN achieved the best performance to discriminate FESZ from CSZ patients (accuracy, 86.2%; AUC, 92.3%; p < 0.05). Furthermore, the brain areas in the subcortical/cerebellum network and the frontoparietal network showed significant importance in both classifications. Together, our findings provide new insights to understand the neuropathology of SZ and further highlight the potential advantages of multimodal network properties for identifying SZ patients at different clinical stages.

Hippocampal Dysconnectivity and Altered Glutamatergic Modulation of the Default Mode Network: A Combined Resting-State Connectivity and Magnetic Resonance Spectroscopy Study in Schizophrenia

BACKGROUND

Converging lines of evidence point to hippocampal dysfunction in schizophrenia. It is thought that hippocampal dysfunction spreads across hippocampal subfields and to cortical regions by way of long-range efferent projections. Importantly, abnormalities in the excitation/inhibition balance could impair the long-range modulation of neural networks. The goal of this project was twofold. First, we sought to identify replicable patterns of hippocampal dysconnectivity in patients with a psychosis spectrum disorder. Second, we aimed to investigate a putative link between glutamatergic metabolism and hippocampal connectivity alterations.

METHODS

We evaluated resting-state hippocampal functional connectivity alterations in two cohorts of patients with a psychosis spectrum disorder. The first cohort consisted of 55 medication-naïve patients with first-episode psychosis and 41 matched healthy control subjects, and the second cohort consisted of 42 unmedicated patients with schizophrenia and 41 matched control subjects. We also acquired measurements of glutamate + glutamine in the left hippocampus using magnetic resonance spectroscopy for 42 patients with first-episode psychosis and 37 healthy control subjects from our first cohort.

RESULTS

We observed a pattern of hippocampal functional hypoconnectivity to regions of the default mode network and hyperconnectivity to the lateral occipital cortex in both cohorts. We also show that in healthy control subjects, greater hippocampal glutamate + glutamine levels predicted greater hippocampal functional connectivity to the anterior default mode network. Furthermore, this relationship was reversed in medication-naïve subjects with first-episode psychosis.

CONCLUSIONS

These results suggest that an alteration in the relationship between glutamate and functional connectivity may disrupt the dynamic of major neural networks.

Hippocampal chloride transporter KCC2 contributes to excitatory GABA dysregulation in the developmental rat model of schizophrenia

Recent studies have revealed an altered expression of NKCC1 and KCC2 in prefrontal cortex (PFC) and hippocampus of schizophrenic patients. Despite extensive considerations, the alteration of NKCC1 and KCC2 co-transporters at different stages of development has not been fully studied. Therefore, we evaluated the expression of these transporters in PFC and hippocampus at time points of four, eight, and twelve weeks in post-weaning social isolation rearing rat model. For this purpose, 23-25 days-old rats were classified into social- or isolation-reared groups. The levels of NKCC1 and KCC2 mRNA expression were evaluated at hippocampus or PFC regions at the time-points of four, eight, and twelve weeks following housing. Post-weaning isolation rearing decreased the hippocampal KCC2 mRNA expression level, but does not affect the NKCC1 mRNA expression. However, no significant difference was observed in the PFC mRNA levels of NKCC1 and KCC2 in the isolation-reared group compared to the socially-reared group during the course of modeling. Further, we assessed the therapeutic effect of selective NKCC1 inhibitor bumetanide (10 mg/kg), on improvement of prepulse inhibition (PPI) test on twelve weeks isolation-reared rats. Intraperitoneal administration of bumetanide (10 mg/kg) did not exert beneficial effects on PPI deficit. Our findings show that isolation rearing reduces hippocampal KCC2 expression level and may underlie hippocampal GABA excitatory. In addition, 10 mg/kg bumetanide is not effective in improving the reduced PPI of twelve weeks isolation-reared rats. Collectively, our findings show that hippocampal chloride transporter KCC2 contributes to excitatory GABA dysregulation in the developmental rat model of schizophrenia.

Parallel hippocampal-parietal circuits for self- and goal-oriented processing

The hippocampus is critically important for a diverse range of cognitive processes, such as episodic memory, prospective memory, affective processing, and spatial navigation. Using individual-specific precision functional mapping of resting-state functional MRI data, we found the anterior hippocampus (head and body) to be preferentially functionally connected to the default mode network (DMN), as expected. The hippocampal tail, however, was strongly preferentially functionally connected to the parietal memory network (PMN), which supports goal-oriented cognition and stimulus recognition. This anterior-posterior dichotomy of resting-state functional connectivity was well-matched by differences in task deactivations and anatomical segmentations of the hippocampus. Task deactivations were localized to the hippocampal head and body (DMN), relatively sparing the tail (PMN). The functional dichotomization of the hippocampus into anterior DMN-connected and posterior PMN-connected parcels suggests parallel but distinct circuits between the hippocampus and medial parietal cortex for self- versus goal-oriented processing.

Diffusion MRI derived free-water imaging measures in patients with schizophrenia and their non-psychotic siblings

Free-water imaging is a diffusion MRI technique that separately models water diffusion hindered by fiber tissue and water that disperses freely in the extracellular space. Studies using this technique have shown that schizophrenia is characterized by a lower level of fractional anisotropy of the tissue compartment (FA_t) and higher free-water fractional volume (FW). It is unknown, however, whether such abnormalities are an expression of pre-existing (genetic) risk for schizophrenia or a manifestation of the illness. To investigate the contribution of familial risk factors to white matter abnormalities, we used the free-water imaging technique to assess FA_t and FW in a large cohort of 471 participants including 161 patients with schizophrenia, 182 non-psychotic siblings, and 128 healthy controls. In this sample, patients did not show significant differences in FA_t as compared to controls, but did exhibit a higher level of FW relative to both controls and siblings in the left uncinate fasciculus, superior corona radiata and fornix / stria terminalis. This increase in FW was found to be related to, though not solely explained by, ventricular enlargement. Siblings did not show significant FW abnormalities. However, siblings did show a higher level of FA_t as compared to controls and patients, in line with results of a previous study on the same data using conventional DTI. Taken together, our findings suggest that extracellular free-water accumulation in patients is likely a manifestation of established disease rather than an expression of familial risk for schizophrenia and that super-normal levels of FA_t in unaffected siblings may reflect a compensatory process.

Dysmaturation Observed as Altered Hippocampal Functional Connectivity at Rest Is Associated With the Emergence of Positive Psychotic Symptoms in Patients With 22q11 Deletion Syndrome

BACKGROUND

Hippocampal alterations are among the most replicated neuroimaging findings across the psychosis spectrum. Moreover, there is strong translational evidence that preserving the maturation of hippocampal networks in mice models prevents the progression of cognitive deficits. However, the developmental trajectory of hippocampal functional connectivity (HFC) and its contribution to psychosis is not well characterized in the human population. 22q11 deletion syndrome (22q11DS) offers a unique model for characterizing early neural correlates of schizophrenia.

METHODS

We acquired resting-state functional magnetic resonance imaging in 242 longitudinally repeated scans from 84 patients with 22q11DS (30 with moderate to severe positive psychotic symptoms) and 94 healthy control subjects in the age span of 6 to 32 years. We obtained bilateral hippocampus to whole-brain functional connectivity and employed a novel longitudinal multivariate approach by means of partial least squares correlation to evaluate the developmental trajectory of HFC across groups.

RESULTS

Relative to control subjects, patients with 22q11DS failed to increase HFC with frontal regions such as the dorsal part of the anterior cingulate cortex, prefrontal cortex, and supplementary motor area. Concurrently, carriers of the deletion had abnormally higher HFC with subcortical dopaminergic areas. Remarkably, this aberrant maturation of HFC was more prominent during midadolescence and was mainly driven by patients exhibiting subthreshold positive psychotic symptoms.

CONCLUSIONS

Our findings suggest a critical period of prefrontal cortex-hippocampal-striatal circuit dysmaturation, particularly during late adolescence, which in light of current translation evidence could be a target for short-term interventions to potentially achieve long-lasting rescue of circuit dysfunctions associated with psychosis.

Resting-state functional connectivity of the human hippocampus in periadolescent children: Associations with age and memory performance

The hippocampus is necessary for declarative (relational) memory, and the ability to form hippocampal‐dependent memories develops through late adolescence. This developmental trajectory of hippocampal‐dependent memory could reflect maturation of intrinsic functional brain networks, but resting‐state functional connectivity (rs‐FC) of the human hippocampus is not well‐characterized for periadolescent children. Measuring hippocampal rs‐FC in periadolescence would thus fill a gap, and testing covariance of hippocampal rs‐FC with age and memory could inform theories of cognitive development. Here, we studied hippocampal rs‐FC in a cross‐sectional sample of healthy children (N = 96; 59 F; age 9–15 years) using a seed‐based approach, and linked these data with NIH Toolbox measures, the Picture‐Sequence Memory Test (PSMT) and the List Sorting Working Memory Test (LSWMT). The PSMT was expected to rely more on hippocampal‐dependent memory than the LSWMT. We observed hippocampal rs‐FC with an extensive brain network including temporal, parietal, and frontal regions. This pattern was consistent with prior work measuring hippocampal rs‐FC in younger and older samples. We also observed novel, regionally specific variation in hippocampal rs‐FC with age and hippocampal‐dependent memory but not working memory. Evidence consistent with these findings was observed in a second, validation dataset of similar‐age healthy children drawn from the Philadelphia Neurodevelopment Cohort. Further, a cross‐dataset analysis suggested generalizable properties of hippocampal rs‐FC and covariance with age and memory. Our findings connect prior work by describing hippocampal rs‐FC and covariance with age and memory in typically developing periadolescent children, and our observations suggest a developmental trajectory for brain networks that support hippocampal‐dependent memory.

Brain functions and cognition on transient insulin deprivation in type 1 diabetes

BACKGROUND

Type 1 diabetes (T1D) is a risk factor for dementia and structural brain changes. It remains to be determined whether transient insulin deprivation that frequently occurs in insulin-treated individuals with T1D alters brain function.

METHODS

We therefore performed functional and structural magnetic resonance imaging, magnetic resonance spectroscopy, and neuropsychological testing at baseline and following 5.4 ± 0.6 hours of insulin deprivation in 14 individuals with T1D and compared results with those from 14 age-, sex-, and BMI-matched nondiabetic (ND) participants with no interventions.

RESULTS

Insulin deprivation in T1D increased blood glucose, and β-hydroxybutyrate, while reducing bicarbonate levels. Participants with T1D showed lower baseline brain N-acetyl aspartate and myo-inositol levels but higher cortical fractional anisotropy, suggesting unhealthy neurons and brain microstructure. Although cognitive functions did not differ between participants with T1D and ND participants at baseline, significant changes in fine motor speed as well as attention and short-term memory occurred following insulin deprivation in participants with T1D. Insulin deprivation also reduced brain adenosine triphosphate levels and altered the phosphocreatine/adenosine triphosphate ratio. Baseline differences in functional connectivity in brain regions between participants with T1D and ND participants were noted, and on insulin deprivation further alterations in functional connectivity between regions, especially cortical and hippocampus-caudate regions, were observed. These alterations in functional connectivity correlated to brain metabolites and to changes in cognition.

CONCLUSION

Transient insulin deprivation therefore caused alterations in executive aspects of cognitive function concurrent with functional connectivity between memory regions and the sensory cortex. These findings have important clinical implications, as many patients with T1D inadvertently have periods of transient insulin deprivation.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03392441.

FUNDING

Clinical and Translational Science Award (UL1 TR002377) from the National Center for Advancing Translational Science; NIH grants (R21 AG60139 and R01 AG62859); the Mayo Foundation.

Functional connectivity abnormalities of the long-axis hippocampal subregions in schizophrenia during episodic memory

Past evidence suggests that hippocampal subregions, namely the anterior and posterior parts, may be engaged in distinct networks underlying the memory functions which may be altered in patients with schizophrenia. However, of the very few studies that have investigated the hippocampal longitudinal axis subdivisions functional connectivity in patients with schizophrenia, the majority was based on resting-state data, and yet, none aimed to examine these during an episodic memory task. A total of 41 patients with schizophrenia and 45 healthy controls were recruited for a magnetic resonance imaging protocol in which they performed an explicit memory task. Seed-based functional connectivity analysis was employed to assess connectivity abnormalities between hippocampal subregions and voxel-wise connectivity targets in patients with schizophrenia. We observed a significantly reduced connectivity between the posterior hippocampus and regions from the default mode network, but increased connectivity with the primary visual cortex, in patients with schizophrenia compared to healthy subjects. Increased connectivity between the anterior hippocampus and anterior temporal regions also characterized patients with schizophrenia. In the current study, we provided evidence and support for studying hippocampal subdivisions along the longitudinal axis in schizophrenia. Our results suggest that the abnormalities in hippocampal subregions functional connectivity reflect deficits in episodic memory that may be implicated in the pathophysiology of schizophrenia.

Penalized model-based clustering of fMRI data

Functional magnetic resonance imaging (fMRI) data have become increasingly available and are useful for describing functional connectivity (FC), the relatedness of neuronal activity in regions of the brain. This FC of the brain provides insight into certain neurodegenerative diseases and psychiatric disorders, and thus is of clinical importance. To help inform physicians regarding patient diagnoses, unsupervised clustering of subjects based on FC is desired, allowing the data to inform us of groupings of patients based on shared features of connectivity. Since heterogeneity in FC is present even between patients within the same group, it is important to allow subject-level differences in connectivity, while still pooling information across patients within each group to describe group-level FC. To this end, we propose a random covariance clustering model (RCCM) to concurrently cluster subjects based on their FC networks, estimate the unique FC networks of each subject, and to infer shared network features. Although current methods exist for estimating FC or clustering subjects using fMRI data, our novel contribution is to cluster or group subjects based on similar FC of the brain while simultaneously providing group- and subject-level FC network estimates. The competitive performance of RCCM relative to other methods is demonstrated through simulations in various settings, achieving both improved clustering of subjects and estimation of FC networks. Utility of the proposed method is demonstrated with application to a resting-state fMRI data set collected on 43 healthy controls and 61 participants diagnosed with schizophrenia.

High schizotypy traits are associated with reduced hippocampal resting state functional connectivity

Altered hippocampal functioning is proposed to play a critical role in the development of schizophrenia-spectrum disorders. Previous resting state functional Magnetic Resonance Imaging (rs-fMRI) studies report disrupted hippocampal connectivity in patients with psychosis and in individuals with clinical high risk, yet hippocampal connectivity has not been investigated in people with high schizotypy traits. Here we used rs-fMRI to examine hippocampal connectivity in healthy people with low (LS, n = 23) and high levels (HS, n = 22) of schizotypal traits assessed using the Schizotypy Personality Questionnaire. Using a bilateral hippocampal seed region, we examined resting state functional connectivity (RSFC) between hippocampus and striatal, thalamic and prefrontal cortex regions of interest. Compared to LS, HS participants showed lower RSFC between hippocampus and striatum and between hippocampus and thalamus. Whilst the group effect of reduced hippocampal RSFC in striatal and thalamic regions was driven by total schizotypy scores, positive schizotypy subfactor scores were significantly positively correlated with hippocampus-caudate/thalamus RSFC. Group differences in RSFC were not observed between hippocampus and prefrontal cortex. These results demonstrate that subclinical schizotypal traits are associated with altered hippocampal connectivity in striatal and thalamic regions and provide further support that hippocampal dysconnectivity confers risk for schizophrenia spectrum disorders.

Neurodevelopmental insights into circuit dysconnectivity in schizophrenia

Schizophrenia is increasingly being recognized as a disorder of brain circuits of developmental origin. Animal models, however, have been technically limited in exploring the effects of early developmental circuit abnormalities on the maturation of the brain and associated behavioural outputs. This review discusses evidence of the developmental emergence of circuit abnormalities in schizophrenia, followed by a critical assessment on how animal models need to be adapted through optimized tools in order to spatially and temporally manipulate early developmental events, thereby providing insight into the causal contribution of developmental perturbations to schizophrenia.

Altered hippocampal-prefrontal functional network integrity in adult macaque monkeys with neonatal hippocampal lesions

The dorsolateral prefrontal cortex (DLPFC) and ventral lateral prefrontal cortex (VLPFC) play critical but different roles in working memory (WM) processes. Resting-state functional MRI (rs-fMRI) was employed to investigate the effects of neonatal hippocampal lesions on the functional connectivity (FC) between the hippocampus (H) and the DLPFC and VLPFC and its relation to WM performance in adult monkeys. Adult rhesus monkeys with neonatal H lesions (Neo-H, n = 5) and age- and gender-matched sham-operated monkeys (Neo-C, n = 5) were scanned around 10 years of age. The FC of H-DLPFC and H-VLPFC in Neo-H monkeys was significantly altered as compared to controls, but also switched from being positive in the Neo-C to negative in the Neo-H. In addition, the altered magnitude of FC between right H and bilateral DLPFC was significantly associated with the extent of the hippocampal lesions. In particular, the effects of neonatal hippocampal lesion on FC appeared to be selective to the left hemisphere of the brain (i.e. asymmetric in the two hemispheres). Finally, FC between H and DLPFC correlated with WM task performance on the SU-DNMS and the Obj-SO tasks for the control animals, but only with the H-VLPFC and SU-DNMS task for the Neo-H animals. In conclusion, the present rsfMRI study revealed that the neonatal hippocampal lesions significantly but differently altered the integrity in the functional connectivity of H-DLPFC and H-VLPFC. The similarities between the behavioral, cognitive and neural alterations in Neo-H monkeys and Schizophrenia (SZ) patients provide a strong translational model to develop new therapeutic tools for SZ.

Altered amygdala-based functional connectivity in individuals with attenuated psychosis syndrome and first-episode schizophrenia

Altered resting-state functional connectivity (FC) of the amygdala (AMY) has been demonstrated to be implicated in schizophrenia (SZ) and attenuated psychosis syndrome (APS). Specifically, no prior work has investigated FC in individuals with APS using subregions of the AMY as seed regions of interest. The present study examined AMY subregion-based FC in individuals with APS and first-episode schizophrenia (FES) and healthy controls (HCs). The resting state FC maps of the three AMY subregions were computed and compared across the three groups. Correlation analysis was also performed to examine the relationship between the Z-values of regions showing significant group differences and symptom rating scores. Individuals with APS showed hyperconnectivity between the right centromedial AMY (CMA) and left frontal pole cortex (FPC) and between the laterobasal AMY and brain stem and right inferior lateral occipital cortex compared to HCs. Patients with FES showed hyperconnectivity between the right superficial AMY and left occipital pole cortex and between the left CMA and left thalamus compared to the APS and HCs respectively. A negative relationship was observed between the connectivity strength of the CMA with the FPC and negative-others score of the Brief Core Schema Scales in the APS group. We observed different altered FC with subregions of the AMY in individuals with APS and FES compared to HCs. These results shed light on the pathogenetic mechanisms underpinning the development of APS and SZ.

A preliminary study to investigate resting state fMRI as a potential group differentiator for schizophrenia

Schizophrenia (SZ) is found to be associated with dysconnectivity between the various regions of the brain. These aberrant connections in brain networks responsible for various mental processes in schizophrenia. We examined differences in functional connectivity among persons with SZ (n = 30) and an equal number of their unaffected relatives using resting state functional Magnetic Resonance Imaging (rsfMRI). Subjects were interviewed using the Diagnostic Interview for Genetic Studies (DIGS) and Family Interview for Genetic Studies (FIGS). Cognition was assessed using the Computerized Neuropsychological Battery (CNB) and Trail Making Tests A and B. The resting state functional data were acquired using 3.0 T Magnetic Resonance Imaging system and analysed using Statistical Package for the Social Sciences (SPSS) version 21 and FSL version 5.01 (FMRIB's) Software. The persons with SZ performed significantly worse on tasks of cognition and executive functioning. On rsfMRI, a significantly reduced connectivity was noted in the case group in right and left precentral gyri, right post central gyrus, right and left middle temporal gyrus, left paracingulate gyrus, anterior and posterior cingulate, right planum temporale, right pallidum, left cerebellum-6,7b and 8 lobules. Increased connectivity was noted between areas of right temporal pole and left hippocampus, posterior cingulate and the precuneus, right planum polare and right amygdala, right Heschl's gyrus and left posterior supramarginal gyrus, right amygdala with right insular cortex and left cerebellum 6 with bilateral postcentral gyrus in the same group. These differences in connectivity could be utilised as potential group differentiator for schizophrenia.

Impaired theta phase coupling underlies frontotemporal dysconnectivity in schizophrenia

Frontotemporal dysconnectivity is a key pathology in schizophrenia. The specific nature of this dysconnectivity is unknown, but animal models imply dysfunctional theta phase coupling between hippocampus and medial prefrontal cortex (mPFC). We tested this hypothesis by examining neural dynamics in 18 participants with a schizophrenia diagnosis, both medicated and unmedicated; and 26 age, sex and IQ matched control subjects. All participants completed two tasks known to elicit hippocampal-prefrontal theta coupling: a spatial memory task (during magnetoencephalography) and a memory integration task. In addition, an overlapping group of 33 schizophrenia and 29 control subjects underwent PET to measure the availability of GABAARs expressing the α5 subunit (concentrated on hippocampal somatostatin interneurons). We demonstrate-in the spatial memory task, during memory recall-that theta power increases in left medial temporal lobe (mTL) are impaired in schizophrenia, as is theta phase coupling between mPFC and mTL. Importantly, the latter cannot be explained by theta power changes, head movement, antipsychotics, cannabis use, or IQ, and is not found in other frequency bands. Moreover, mPFC-mTL theta coupling correlated strongly with performance in controls, but not in subjects with schizophrenia, who were mildly impaired at the spatial memory task and no better than chance on the memory integration task. Finally, mTL regions showing reduced phase coupling in schizophrenia magnetoencephalography participants overlapped substantially with areas of diminished α5-GABAAR availability in the wider schizophrenia PET sample. These results indicate that mPFC-mTL dysconnectivity in schizophrenia is due to a loss of theta phase coupling, and imply α5-GABAARs (and the cells that express them) have a role in this process.

Identifying psychosis spectrum youth using support vector machines and cerebral blood perfusion as measured by arterial spin labeled fMRI

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Psychosis spectrum (PS) youth can be identified with support vector machines.

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Classification is improved when youth with psychiatric comorbidities are excluded.

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Cerebral blood flow (CBF) connectivity differences were noted between PS and non-PS.

Altered cerebral blood flow (CBF), as measured by arterial spin labelling (ASL), has been observed in several psychiatric conditions, but is a generally underutilized MRI technique, especially in the study of psychosis spectrum (PS) symptoms. We aimed to determine group differences in ASL resting state functional connectivity (rsFC) between PS and non-PS youth, and the reliability of a support vector machine (SVM) classifier trained on ASL rsFC features to differentiate PS and non-PS youth, especially compared to blood oxygen level dependent (BOLD) fMRI. 1146 youth aged 8–22 with ASL and BOLD data from the Philadelphia Neurodevelopmental Cohort were analyzed. Widespread ASL hyperconnectivity was found in the left cuneus, precuneus, and dorsolateral prefrontal cortex, and hypoconnectivity was found in the left cingulate cortex and orbitofrontal area (multiple linear regression, FDR corrected). An SVM trained on ASL and BOLD features outperformed either modality alone (AUC_BOTH = 0.72 versus AUC_ASL = 0.68 and AUC_BOLD = 0.67). Classification performance and precision improved when the non-PS group had no psychiatric comorbidities. The relative success of the classifier suggests ASL rsFC changes exist in PS individuals that differ from BOLD rsFC changes, and extends previous findings of CBF dysregulation in PS.

New insights on the influence of free d-aspartate metabolism in the mammalian brain during prenatal and postnatal life

Free d-aspartate is abundant in the mammalian embryonic brain. However, following the postnatal onset of the catabolic d-aspartate oxidase (DDO) activity, cerebral d-aspartate levels drastically decrease, remaining constantly low throughout life. d-Aspartate stimulates both glutamatergic NMDA receptors (NMDARs) and metabotropic Glu5 receptors. In rodents, short-term d-aspartate exposure increases spine density and synaptic plasticity, and improves cognition. Conversely, persistently high d-Asp levels produce NMDAR-dependent neurotoxic effects, leading to precocious neuroinflammation and cell death. These pieces of evidence highlight the dichotomous impact of d-aspartate signaling on NMDAR-dependent processes and, in turn, unveil a neuroprotective role for DDO in preventing the detrimental effects of excessive d-aspartate stimulation during aging. Here, we will focus on the in vivo influence of altered d-aspartate metabolism on the modulation of glutamatergic functions and its involvement in translational studies. Finally, preliminary data on the role of embryonic d-aspartate in the mouse brain will also be reviewed.

Aberrant posterior cingulate connectivity classify first-episode schizophrenia from controls: A machine learning study

BACKGROUND

Posterior cingulate cortex (PCC) is a key aspect of the default mode network (DMN). Aberrant PCC functional connectivity (FC) is implicated in schizophrenia, but the potential for PCC related changes as biological classifier of schizophrenia has not yet been evaluated.

METHODS

We conducted a data-driven approach using resting-state functional MRI data to explore differences in PCC-based region- and voxel-wise FC patterns, to distinguish between patients with first-episode schizophrenia (FES) and demographically matched healthy controls (HC). Discriminative PCC FCs were selected via false discovery rate estimation. A gradient boosting classifier was trained and validated based on 100 FES vs. 93 HC. Subsequently, classification models were tested in an independent dataset of 87 FES patients and 80 HC using resting-state data acquired on a different MRI scanner.

RESULTS

Patients with FES had reduced connectivity between PCC and frontal areas, left parahippocampal regions, left anterior cingulate cortex, and right inferior parietal lobule, but hyperconnectivity with left lateral temporal regions. Predictive voxel-wise clusters were similar to region-wise selected brain areas functionally connected with PCC in relation to discriminating FES from HC subject categories. Region-wise analysis of FCs yielded a relatively high predictive level for schizophrenia, with an average accuracy of 72.28% in the independent samples, while selected voxel-wise connectivity yielded an accuracy of 68.72%.

CONCLUSION

FES exhibited a pattern of both increased and decreased PCC-based connectivity, but was related to predominant hypoconnectivity between PCC and brain areas associated with DMN, that may be a useful differential feature revealing underpinnings of neuropathophysiology for schizophrenia.

Toward a Neural Model of the Openness-Psychoticism Dimension: Functional Connectivity in the Default and Frontoparietal Control Networks

Psychosis proneness has been linked to heightened Openness to Experience and to cognitive deficits. Openness and psychotic disorders are associated with the default and frontoparietal networks, and the latter network is also robustly associated with intelligence. We tested the hypothesis that functional connectivity of the default and frontoparietal networks is a neural correlate of the openness-psychoticism dimension. Participants in the Human Connectome Project (N = 1003) completed measures of psychoticism, openness, and intelligence. Resting state functional magnetic resonance imaging was used to identify intrinsic connectivity networks. Structural equation modeling revealed relations among personality, intelligence, and network coherence. Psychoticism, openness, and especially their shared variance were related positively to default network coherence and negatively to frontoparietal coherence. These associations remained after controlling for intelligence. Intelligence was positively related to frontoparietal coherence. Research suggests that psychoticism and openness are linked in part through their association with connectivity in networks involving experiential simulation and cognitive control. We propose a model of psychosis risk that highlights roles of the default and frontoparietal networks. Findings echo research on functional connectivity in psychosis patients, suggesting shared mechanisms across the personality-psychopathology continuum.

Anterior Hippocampal-Cortical Functional Connectivity Distinguishes Antipsychotic Naïve First-Episode Psychosis Patients From Controls and May Predict Response to Second-Generation Antipsychotic Treatment

BACKGROUND

Converging evidence implicates the anterior hippocampus in the proximal pathophysiology of schizophrenia. Although resting state functional connectivity (FC) holds promise for characterizing anterior hippocampal circuit abnormalities and their relationship to treatment response, this technique has not yet been used in first-episode psychosis (FEP) patients in a manner that distinguishes the anterior from posterior hippocampus.

METHODS

We used masked-hippocampal-group-independent component analysis with dual regression to contrast subregional hippocampal-whole brain FC between healthy controls (HCs) and antipsychotic naïve FEP patients (N = 61, 36 female). In a subsample of FEP patients (N = 27, 15 female), we repeated this analysis following 8 weeks of second-generation antipsychotic treatment and explored whether baseline FC predicted treatment response using random forest.

RESULTS

Relative to HC, untreated FEP subjects displayed reproducibly lower FC between the left anteromedial hippocampus and cortical regions including the anterior cingulate and insular cortex (P < .05, corrected). Anteromedial hippocampal FC increased in FEP patients following treatment (P < .005), and no longer differed from HC. Random forest analysis showed baseline anteromedial hippocampal FC with four brain regions, namely the insular-opercular cortex, superior frontal gyrus, precentral gyrus, and postcentral gyrus predicted treatment response (area under the curve = 0.95).

CONCLUSIONS

Antipsychotic naïve FEP is associated with lower FC between the anterior hippocampus and cortical regions previously implicated in schizophrenia. Preliminary analysis suggests that random forest models based on hippocampal FC may predict treatment response in FEP patients, and hence could be a useful biomarker for treatment development.

Machine learning technique reveals intrinsic characteristics of schizophrenia: an alternative method

Machine learning technique has long been utilized to assist disease diagnosis, increasing clinical physicians' confidence in their decision and expediting the process of diagnosis. In this case, machine learning technique serves as a tool for distinguishing patients from healthy people. Additionally, it can also serve as an exploratory method to reveal intrinsic characteristics of a disease based on discriminative features, which was demonstrated in this study. Resting-state functional magnetic resonance imaging (fMRI) data were obtained from 148 participants (including patients with schizophrenia and healthy controls). Connective strengths were estimated by Pearson correlation for each pair of brain regions partitioned according to automated anatomical labelling atlas. Subsequently, consensus connections with high discriminative power were extracted under the circumstance of the best classification accuracy. Investigating these consensus connections, we found that schizophrenia group predominately exhibited weaker strengths of inter-regional connectivity compared to healthy group. Aberrant connectivities in both intra- and inter-hemispherical connections were observed. Within intra-hemispherical connections, the number of aberrant connections in the right hemisphere was more than that of the left hemisphere. In the exploration of large regions, we revealed that the serious dysconnectivities mainly appeared on temporal and occipital regions for the within-large-region connections; while connectivity disruption was observed on the connections from temporal region to occipital, insula and limbic regions for the between-large-region connections. The findings of this study corroborate previous conclusion of dysconnectivity in schizophrenia and further shed light on distribution patterns of dysconnectivity, which deepens the understanding of pathological mechanism of schizophrenia.

Calcium Imaging in Drug Discovery for Psychiatric Disorders

The past 5 years have seen a sharp increase in the number of studies using calcium imaging in behaving rodents. These studies have helped identify important roles for individual cells, brain regions, and circuits in some of the core behavioral phenotypes of psychiatric disorders, such as schizophrenia and autism, and have characterized network dysfunction in well-established models of these disorders. Since rescuing clinically relevant behavioral deficits in disease model mice remains a foundation of preclinical CNS research, these studies have the potential to inform new therapeutic approaches targeting specific cell types or projections, or perhaps most importantly, the network-level context in which neurons function. In this mini-review, we will provide a brief overview of recent insights into psychiatric disease-associated mouse models and behavior paradigms, focusing on those achieved by cellular resolution imaging of calcium dynamics in neural populations. We will then discuss how these experiments can support efforts within the pharmaceutical industry, such as target identification, assay development, and candidate screening and validation. Calcium imaging is uniquely capable of bridging the gap between two of the key resources that currently enable CNS drug discovery: genomic and transcriptomic data from human patients, and translatable, population-resolution measures of brain activity (such as fMRI and EEG). Applying this knowledge could yield real value to patients in the near future.

High-order Feature Learning for Multi-atlas based Label Fusion: Application to Brain Segmentation with MRI

Multi-atlas based segmentation methods have shown their effectiveness in brain regions-of-interesting (ROIs) segmentation, by propagating labels from multiple atlases to a target image based on the similarity between patches in the target image and multiple atlas images. Most of the existing multiatlas based methods use image intensity features to calculate the similarity between a pair of image patches for label fusion. In particular, using only low-level image intensity features cannot adequately characterize the complex appearance patterns (e.g., the high-order relationship between voxels within a patch) of brain magnetic resonance (MR) images. To address this issue, this paper develops a high-order feature learning framework for multi-atlas based label fusion, where high-order features of image patches are extracted and fused for segmenting ROIs of structural brain MR images. Specifically, an unsupervised feature learning method (i.e., means-covariances restricted Boltzmann machine, mcRBM) is employed to learn high-order features (i.e., mean and covariance features) of patches in brain MR images. Then, a group-fused sparsity dictionary learning method is proposed to jointly calculate the voting weights for label fusion, based on the learned high-order and the original image intensity features. The proposed method is compared with several state-of-the-art label fusion methods on ADNI, NIREP and LONI-LPBA40 datasets. The Dice ratio achieved by our method is 88:30%, 88:83%, 79:54% and 81:02% on left and right hippocampus on the ADNI, NIREP and LONI-LPBA40 datasets, respectively, while the best Dice ratio yielded by the other methods are 86:51%, 87:39%, 78:48% and 79:65% on three datasets, respectively.