Amplitude of low-frequency oscillations in schizophrenia: a resting state fMRI study

Transdiagnostic Neurobiology of Social Cognition and Individual Variability as Measured by Fractional Amplitude of Low-Frequency Fluctuation in Schizophrenia and Autism Spectrum Disorders

Fractional amplitude of low-frequency fluctuation (fALFF) is a validated measure of resting-state spontaneous brain activity. Previous fALFF findings in autism and schizophrenia spectrum disorders (ASDs and SSDs) have been highly heterogeneous. We aimed to use fALFF in a large sample of typically developing control (TDC), ASD and SSD participants to explore group differences and relationships with inter-individual variability of fALFF maps and social cognition. fALFF from 495 participants (185 TDC, 68 ASD, and 242 SSD) was computed using functional magnetic resonance imaging as signal power within two frequency bands (i.e., slow-4 and slow-5), normalized by the power in the remaining frequency spectrum. Permutation analysis of linear models was employed to investigate the relationship of fALFF with diagnostic groups, higher-level social cognition, and lower-level social cognition. Each participant's average distance of fALFF map to all others was defined as a variability score, with higher scores indicating less typical maps. Lower fALFF in the visual and higher fALFF in the frontal regions were found in both SSD and ASD participants compared with TDCs. Limited differences were observed between ASD and SSD participants in the cuneus regions only. Associations between slow-4 fALFF and higher-level social cognitive scores across the whole sample were observed in the lateral occipitotemporal and temporoparietal junction. Individual variability within the ASD and SSD groups was also significantly higher compared with TDC. Similar patterns of fALFF and individual variability in ASD and SSD suggest some common neurobiological deficits across these related heterogeneous conditions.

Shared atypical spontaneous brain activity pattern in early onset schizophrenia and autism spectrum disorders: evidence from cortical surface-based analysis

Schizophrenia and autism spectrum disorders (ASD) were considered as two neurodevelopmental disorders and had shared clinical features. we hypothesized that they have some common atypical brain functions and the purpose of this study was to explored the shared brain spontaneous activity strength alterations in early onset schizophrenia (EOS) and ASD in the children and adolescents with a multi-center large-sample study. A total of 171 EOS patients (aged 14.25 ± 1.87), 188 ASD patients (aged 9.52 ± 5.13), and 107 healthy controls (aged 11.52 ± 2.82) had scanned with Resting-fMRI and analyzed surface-based amplitude of low-frequency fluctuations (ALFF). Results showed that both EOS and ASD had hypoactivity in the primary sensorimotor regions (bilateral primary and early visual cortex, left ventral visual stream, left primary auditory cortex) and hyperactivity in the high-order transmodal regions (bilateral SFL, bilateral DLPFC, right frontal eye fields), and bilateral thalamus. EOS had more severe abnormality than ASD. This study revealed shared functional abnormalities in the primary sensorimotor regions and the high-order transmodal regions in EOS and ASD, which provided neuroimaging evidence of common changes in EOS and ASD, and may help with better early recognition and precise treatment for EOS and ASD.

Mapping Individual Differences in Intermodal Coupling in Neurodevelopment

Within-individual coupling between measures of brain structure and function evolves in development and may underlie differential risk for neuropsychiatric disorders. Despite increasing interest in the development of structure-function relationships, rigorous methods to quantify and test individual differences in coupling remain nascent. In this article, we explore and address gaps in approaches for testing and spatially localizing individual differences in intermodal coupling. We propose a new method, called CIDeR, which is designed to simultaneously perform hypothesis testing in a way that limits false positive results and improve detection of true positive results. Through a comparison across different approaches to testing individual differences in intermodal coupling, we delineate subtle differences in the hypotheses they test, which may ultimately lead researchers to arrive at different results. Finally, we illustrate the utility of CIDeR in two applications to brain development using data from the Philadelphia Neurodevelopmental Cohort.

Extracting interpretable signatures of whole-brain dynamics through systematic comparison

The brain's complex distributed dynamics are typically quantified using a limited set of manually selected statistical properties, leaving the possibility that alternative dynamical properties may outperform those reported for a given application. Here, we address this limitation by systematically comparing diverse, interpretable features of both intra-regional activity and inter-regional functional coupling from resting-state functional magnetic resonance imaging (rs-fMRI) data, demonstrating our method using case-control comparisons of four neuropsychiatric disorders. Our findings generally support the use of linear time-series analysis techniques for rs-fMRI case-control analyses, while also identifying new ways to quantify informative dynamical fMRI structures. While simple statistical representations of fMRI dynamics performed surprisingly well (e.g., properties within a single brain region), combining intra-regional properties with inter-regional coupling generally improved performance, underscoring the distributed, multifaceted changes to fMRI dynamics in neuropsychiatric disorders. The comprehensive, data-driven method introduced here enables systematic identification and interpretation of quantitative dynamical signatures of multivariate time-series data, with applicability beyond neuroimaging to diverse scientific problems involving complex time-varying systems.

Differences in fractional amplitude of low-frequency fluctuations (fALFF) and cognitive function between untreated major depressive disorder and schizophrenia with depressive mood patients

BACKGROUND

Distinguishing untreated major depressive disorder without medication (MDD) from schizophrenia with depressed mood (SZDM) poses a clinical challenge. This study aims to investigate differences in fractional amplitude of low-frequency fluctuations (fALFF) and cognition in untreated MDD and SZDM patients.

METHODS

The study included 42 untreated MDD cases, 30 SZDM patients, and 46 healthy controls (HC). Cognitive assessment utilized the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). Resting-state functional magnetic resonance imaging (rs-fMRI) scans were conducted, and data were processed using fALFF in slow-4 and slow-5 bands.

RESULTS

Significant fALFF changes were observed in four brain regions across MDD, SZDM, and HC groups for both slow-4 and slow-5 fALFF. Compared to SZDM, the MDD group showed increased slow-5 fALFF in the right gyrus rectus (RGR). Relative to HC, SZDM exhibited decreased slow-5 fALFF in the left gyrus rectus (LGR) and increased slow-5 fALFF in the right putamen. Changes in slow-5 fALFF in both RGR and LGR were negatively correlated with RBANS scores. No significant correlations were found between remaining fALFF (slow-4 and slow-5 bands) and RBANS scores in MDD or SZDM groups.

CONCLUSIONS

Alterations in slow-5 fALFF in RGR may serve as potential biomarkers for distinguishing MDD from SZDM, providing preliminary insights into the neural mechanisms of cognitive function in schizophrenia.

Abnormal regional activity in the prefrontal-limbic circuit at rest: Potential imaging markers and treatment predictors in drug-naive anxiety disorders

BACKGROUND

Previous research has identified functional impairments within the prefrontal-limbic circuit in individuals with anxiety disorders. However, the link between these deficiencies, clinical symptoms, and responses to antipsychotic treatment is still not fully understood. This study aimed to investigate abnormal regional activity within the prefrontal-limbic circuit among drug-naive individuals diagnosed with generalized anxiety disorder (GAD) and panic disorder (PD) and to analyze changes following treatment.

METHODS

Resting-state magnetic resonance imaging was performed on a cohort of 118 anxiety disorder patients (64 GAD, 54 PD) and 61 healthy controls (HCs) at baseline. Among them, 52 patients with GAD and 44 patients with PD underwent a 4-week treatment regimen of paroxetine. Fractional amplitude of low-frequency fluctuation (fALFF) measurements and pattern classification techniques were employed to analyze the data in accordance with the human Brainnetome atlas.

RESULTS

Both patients with GAD and PD demonstrated decreased fALFF in the right cHipp subregion of the hippocampus and increased fALFF in specified subregions of the cingulate and orbitofrontal lobe. Notably, patients with PD exhibited significantly higher fALFF in the left A24cd subregion compared to patients with GAD, while other ROI subregions showed no significant variations between the two patient groups. Whole-brain analysis revealed abnormal fALFF in both patient groups, primarily in specific areas of the cingulate and parasingulate gyrus, as well as the inferior and medial orbitofrontal gyrus (OFG). Following a 4-week treatment period, specific subregions in the GAD and PD groups showed a significant decrease in fALFF. Further analysis using support vector regression indicated that fALFF measurements in the right A13 and right A24cd subregions may be predictive of treatment response among anxiety disorder patients.

CONCLUSIONS

Aberrant functional activity in certain subregions of the prefrontal-limbic circuit appears to be linked to the manifestation of anxiety disorders. These findings suggest potential imaging indicators for individual responses to antipsychotic treatment.

Beta-informativeness-diffusion multilayer graph embedding for brain network analysis

Brain network analysis provides essential insights into the diagnosis of brain disease. Integrating multiple neuroimaging modalities has been demonstrated to be more effective than using a single modality for brain network analysis. However, a majority of existing brain network analysis methods based on multiple modalities often overlook both complementary information and unique characteristics from various modalities. To tackle this issue, we propose the Beta-Informativeness-Diffusion Multilayer Graph Embedding (BID-MGE) method. The proposed method seamlessly integrates structural connectivity (SC) and functional connectivity (FC) to learn more comprehensive information for diagnosing neuropsychiatric disorders. Specifically, a novel beta distribution mapping function (beta mapping) is utilized to increase vital information and weaken insignificant connections. The refined information helps the diffusion process concentrate on crucial brain regions to capture more discriminative features. To maximize the preservation of the unique characteristics of each modality, we design an optimal scale multilayer brain network, the inter-layer connections of which depend on node informativeness. Then, a multilayer informativeness diffusion is proposed to capture complementary information and unique characteristics from various modalities and generate node representations by incorporating the features of each node with those of their connected nodes. Finally, the node representations are reconfigured using principal component analysis (PCA), and cosine distances are calculated with reference to multiple templates for statistical analysis and classification. We implement the proposed method for brain network analysis of neuropsychiatric disorders. The results indicate that our method effectively identifies crucial brain regions associated with diseases, providing valuable insights into the pathology of the disease, and surpasses other advanced methods in classification performance.

Modulation of hippocampal activity in schizophrenia with levetiracetam: a randomized, double-blind, cross-over, placebo-controlled trial

Hippocampal hyperactivity is a novel pharmacological target in the treatment of schizophrenia. We hypothesized that levetiracetam (LEV), a drug binding to the synaptic vesicle glycoprotein 2 A, normalizes hippocampal activity in persons with schizophrenia and can be measured using neuroimaging methods. Thirty healthy control participants and 30 patients with schizophrenia (28 treated with antipsychotic drugs), were randomly assigned to a double-blind, cross-over trial to receive a single administration of 500 mg oral LEV or placebo during two study visits. At each visit, we assessed hippocampal function using resting state fractional amplitude of low frequency fluctuations (fALFF), cerebral blood flow (CBF) with arterial spin labeling, and hippocampal blood-oxygen-level-dependent (BOLD) signal during a scene processing task. After placebo treatment, we found significant elevations in hippocampal fALFF in patients with schizophrenia, consistent with hippocampal hyperactivity. Additionally, hippocampal fALFF in patients with schizophrenia after LEV treatment did not significantly differ from healthy control participants receiving placebo, suggesting that LEV may normalize hippocampal hyperactivity. In contrast to our fALFF findings, we did not detect significant group differences or an effect of LEV treatment on hippocampal CBF. In the context of no significant group difference in BOLD signal, we found that hippocampal recruitment during scene processing is enhanced by LEV more significantly in schizophrenia. We conclude that pharmacological modulation of hippocampal hyperactivity in schizophrenia can be studied with some neuroimaging methods, but not others. Additional studies in different cohorts, employing alternate neuroimaging methods and study designs, are needed to establish levetiracetam as a treatment for schizophrenia.

Identification of genetic features that are associated with amplitude of low-frequency fluctuation changes in schizophrenia using omics analysis

Genetic risk for schizophrenia is thought to trigger variation in clinical features of schizophrenia, but biological processes associated with neuronal activity in brain regions remain elusive. In this study, gene expression features were mapped to various sub-regions of the brain by integrating low-frequency amplitude features and gene expression data from the schizophrenia brain and using gene co-expression network analysis of the Allen Transcriptome Atlas of the human brain from six donors to identify genetic features of brain regions and important associations with neuronal features. The results indicate that changes in the dynamic amplitude of low-frequency fluctuation (dALFF) are mainly associated with transcriptome signature factors such as cortical layer synthesis, immune response, and expanded membrane transport. Further modular disease enrichment analysis revealed that the same set of signature genes associated with dALFF levels was enriched for multiple neurological biological processes. Finally, genetic profiling of individual modules identified multiple core genes closely related to schizophrenia, also potentially associated with neuronal activity. Thus, this paper explores genetic features of brain regions in the schizophrenia closely related to low-frequency amplitude ratio levels based on imaging genetics, which suggests structural endophenotypes associated with schizophrenia.

Correlation between low frequency fluctuation and cognitive performance in bipolar disorder patients with suicidal ideation

BACKGROUND

Patients with bipolar disorder (BD) are at high risk of suicidal ideation (SI), and BD patients with suicidal ideation (BDSI) have shown marked abnormalities in spontaneous brain function. Cognitive impairment, on the other hand, is considered to be one of the core symptoms of BD. However, few studies have addressed the association between cognitive performance and abnormal spontaneous brain function in BDSI.

METHODS

In the current study, the MATRICS Consensus Cognitive Battery (MCCB) was used to assess cognitive performance in BDSI (n = 20), BD subjects without suicidal ideation (BDNSI) (n = 24) and healthy controls (HC) (n = 30). Their cognitive performance was then correlated with amplitude of low frequency fluctuation (ALFF) values obtained by resting-state functional magnetic resonance imaging (rs-fMRI).

RESULTS

We found that ALFF was significantly higher in the left precuneus and right posterior cingulate cortex in the BDSI group and significantly lower in the right precuneus in the BDNSI group than in the HC group. In addition, in the BDSI group, visual learning performance was positively correlated with ALFF values in the left precuneus.

CONCLUSIONS

Our findings support the notion that BD patients present with ALFF abnormalities, which are associated with cognitive performance in BDSI.

Neural correlates of social interaction anxiety and their relation to emotional intelligence: A resting-state fMRI study

Social interaction anxiety refers to a state of anxiety resulting from the prospect or presence of interpersonal evaluation in real or imagined social settings. Previous neuroimaging studies have revealed neural basis of social anxiety disorder. However, little is known about the neural correlates of individual differences in social interaction anxiety in nonclinical population. In the present study, we used resting-state functional magnetic resonance imaging to explore the relationship between individual's spontaneous neural activity and social interaction anxiety, and the role that emotional intelligence played in the relationship. To this end, the correlation between the regional fractional amplitude of low-frequency fluctuations (fALFF) of the brain and individuals' social interaction anxiety scores was examined. We found that social interaction anxiety was correlated with the fALFF in the insula, parahippocampal gyrus, bilateral superior temporal gyrus, and superior parietal lobule. Furthermore, we also found that emotional intelligence partially mediated the association between the fALFF in these regions and social interaction anxiety. Taken together, our study provided the first evidence for the spontaneous neural basis of social interaction anxiety in normal population, and highlighted the neural substrates through which emotional intelligence might play an important role in social interaction anxiety.

Pre-COVID resting-state brain activity in the fusiform gyrus prospectively predicts social anxiety alterations during the pandemic

BACKGROUND

Social anxiety (SA) has been linked to the coronavirus disease 2019 (COVID-19) pandemic, but the neurobiopsychological mechanisms underlying this relationship remain unclear. This study aimed to elucidate the neurofunctional markers for COVID-induced SA development and the potential role of COVID-related posttraumatic stress symptoms (PTSS) in the brain-SA alterations link.

METHODS

Before the COVID-19 pandemic (T1), 100 general college students underwent resting-state magnetic resonance imaging and behavioral tests. During the period of community-level outbreaks (T2), these students were re-contacted to undergo follow-up behavioral assessments.

RESULTS

Whole-brain correlation and prediction analyses found that pre-pandemic spontaneous neural activity (measured by fractional amplitude of low-frequency fluctuations) in the right fusiform gyrus (FG) was positively correlated to SA alterations (T2 - T1). Mediation analyses revealed that COVID-specific PTSS mediated the effects of right FG on SA alterations.

LIMITATIONS

The results should be interpreted carefully because only one-session neuroimaging data in a sample of normal adults were included.

CONCLUSIONS

The results provide evidence for neurofunctional markers of COVID-induced SA and may help develop targeted brain-based interventions that reduce SA.

Regional brain activity of resting-state fMRI and auditory oddball ERP with multimodal approach in individuals with internet gaming disorder

Background and aims

Resting-state brain activity may be associated with the ability to perform tasks; however, a multimodal approach involving resting-state functional magnetic resonance imaging (fMRI) and event-related potentials (ERPs) has not been widely used to investigate addictive disorders.

Methods

We explored resting-state fMRI and auditory oddball ERP values from 26 with internet gaming disorder (IGD) patients and 27 age- and intelligence quotient-matched healthy controls (HCs). To assess the characteristics of resting-state fMRI, we calculated regional homogeneity (ReHo), amplitude of low-frequency fluctuation (ALFF), and fractional amplitude of low-frequency fluctuation (fALFF); we also calculated the P3 component of the ERPs.

Results

Compared with HCs, the individuals with IGD exhibited significant decreases in ReHo and fALFF values in the left inferior occipital gyrus, increased ReHo and ALFF values in the right precuneus, increased ALFF in the left superior frontal gyrus, and lower P3 amplitudes in the midline centro-parietal area during the auditory ERP task. Furthermore, the regional activity of resting-state fMRI in the right inferior temporal gyrus and the occipital regions were positively correlated with the P3 amplitudes in IGD patients, whereas ReHo values of the left hippocampus and the right amygdala were negatively correlated with P3.

Discussion and conclusions

Our results suggest that IGD patients have difficulty interacting effectively with cognitive function and sensory processing, although its interpretations need some cautions. The findings in this study will broaden the overall understanding of the neurobiological mechanisms that underlie IGD pathophysiology.

Structural and Functional Brain Patterns Predict Formal Thought Disorder's Severity and Its Persistence in Recent-Onset Psychosis: Results From the PRONIA Study

BACKGROUND

Formal thought disorder (FThD) is a core feature of psychosis, and its severity and long-term persistence relates to poor clinical outcomes. However, advances in developing early recognition and management tools for FThD are hindered by a lack of insight into the brain-level predictors of FThD states and progression at the individual level.

METHODS

Two hundred thirty-three individuals with recent-onset psychosis were drawn from the multisite European Prognostic Tools for Early Psychosis Management study. Support vector machine classifiers were trained within a cross-validation framework to separate two FThD symptom-based subgroups (high vs. low FThD severity), using cross-sectional whole-brain multiband fractional amplitude of low frequency fluctuations, gray matter volume and white matter volume data. Moreover, we trained machine learning models on these neuroimaging readouts to predict the persistence of high FThD subgroup membership from baseline to 1-year follow-up.

RESULTS

Cross-sectionally, multivariate patterns of gray matter volume within the salience, dorsal attention, visual, and ventral attention networks separated the FThD severity subgroups (balanced accuracy [BAC] = 60.8%). Longitudinally, distributed activations/deactivations within all fractional amplitude of low frequency fluctuation sub-bands (BACslow-5 = 73.2%, BACslow-4 = 72.9%, BACslow-3 = 68.0%), gray matter volume patterns overlapping with the cross-sectional ones (BAC = 62.7%), and smaller frontal white matter volume (BAC = 73.1%) predicted the persistence of high FThD severity from baseline to follow-up, with a combined multimodal balanced accuracy of BAC = 77%.

CONCLUSIONS

We report the first evidence of brain structural and functional patterns predictive of FThD severity and persistence in early psychosis. These findings open up avenues for the development of neuroimaging-based diagnostic, prognostic, and treatment options for the early recognition and management of FThD and associated poor outcomes.

ROI-based analysis of diffusion indices in healthy subjects and subjects with deficit or non-deficit syndrome schizophrenia

We analyzed DTI data involving 22 healthy subjects (HC), 15 patients with deficit syndrome schizophrenia (DSZ), and 25 patients with non-deficit syndrome schizophrenia (NDSZ). We used a 1.5-T MRI scanner to collect diffusion-weighted images and T1 images, which were employed to correct distortions and deformations within the diffusion-weighted images. For 156 regions of interest (ROI), we calculated the average fractional anisotropy (FA), mean diffusion (MD), and radial diffusion (RD). Each ROI underwent a group-wise comparison using permutation F-test, followed by post hoc pairwise comparisons with Bonferroni correction. In general, we observed lower FA in both schizophrenia groups compared to HC (i.e., HC>(DSZ=NDSZ)), while MD and RD showed the opposite pattern. Notably, specific ROIs with reduced FA in schizophrenia patients included bilateral nucleus accumbens, left fusiform area, brain stem, anterior corpus callosum, left rostral and caudal anterior cingulate, right posterior cingulate, left thalamus, left hippocampus, left inferior temporal cortex, right superior temporal cortex, left pars triangularis and right lingual gyrus. Significantly, the right cuneus exhibited lower FA in the DSZ group compared to other groups ((HC=NDSZ)>DSZ), without affecting MD and RD. These results indicate that compromised neural integrity in the cuneus may contribute to the pathophysiological distinctions between DSZ and NDSZ.

Association of dopamine-based genetic risk score with dynamic low-frequency fluctuations in first-episode drug-naïve schizophrenia

Alterations in dynamic intrinsic brain activity and signaling of neurotransmitters, such as dopamine, have been independently detected in schizophrenia patients. Yet, it remains unclear whether the dopamine genetic risk variants have association with brain intrinsic activity. We aimed to investigate the schizophrenia-specific dynamic amplitude of low frequency fluctuation (dALFF) altered pattern, and its association with dopamine genetic risk score in first-episode drug-naïve schizophrenia (FES). Fifty-two FES and 51 healthy controls were included. A sliding-window method based on the dALFF was adopted to estimate the dynamic alterations in intrinsic brain activity. Subjects were genotyped, and a genetic risk score (GRS), which combined the additive effects of ten risk genotypes from five dopamine-related genes, was calculated. We used the voxel-wise correlation analysis to explore the association of dopamine-GRS with dALFF. FES showed significantly increased dALFF left medial prefrontal cortex and significantly decreased dALFF in the right posterior cingulate cortex compared with healthy controls. Greater dopamine GRS in FES was associated with higher dALFF in the left middle frontal gyrus and left inferior parietal gyrus. Our findings indicate that cumulative dopamine genetic risk is associated with a known imaging phenotype for schizophrenia.

Association between thyroid functions, cognition, and functional connectivity of the brain in early-course schizophrenia: A preliminary study

Background

The functional outcome of the debilitating mental illness schizophrenia (SZ) has an integral role in cognition. The thyroid hormone has a vital role in the developmental stages and functioning of the human brain.

Aim

This study aimed to evaluate the relationship between thyroid functions, cognition, and functional imaging of the brain in persons with SZ.

Materials and Methods

Sixty SZ (Diagnostic and Statistical Manual (DSM-5)) persons, aged 18-50 years of both genders, were recruited in this cross-sectional observational study. Positive and Negative Syndrome Scale (PANSS) and Trail Making Tests (TMTs) A and B were administered to all patients. To assess the level of thyroid hormone, a test was conducted. Functional connectivity of the brain was assessed using resting-state functional magnetic resonance imaging (rs-fMRI). Data analysis was performed by descriptive and analytical statistical methods. FSL version 5.9 (FMRIB's) software was used for analyses of fMRI neuroimages.

Results

There were no significant differences between the two populations on sociodemographic factors. The average value for thyroid-stimulating hormone (TSH) in the hypothyroid group (n = 12) and the euthyroid group (n = 47) was 8.38 mIU/l and 2.44 mIU/l, respectively. The average time in seconds for TMT-A and TMT-B was 87.27 and 218.27 in the hypothyroid group and 97.07 and 293.27 in the euthyroid group, respectively. Similarly, in the sample matched on age, gender, and age at onset of illness, there were no significant differences in demographic and clinical factors and resting-state network (RSN) between the hypothyroid (N = 10) and euthyroid (N = 10) groups.

Conclusion

No differences were found in the functional brain network between the hypothyroid and euthyroid groups as the study sample did not include clinically hypothyroid persons with SZ.

Abnormalities of Regional Brain Activity in Patients With Schizophrenia: A Longitudinal Resting-State fMRI Study

BACKGROUND

Evidence from functional and structural research suggests that abnormal brain activity plays an important role in the pathophysiology of schizophrenia (SZ). However, limited studies have focused on post-treatment changes, and current conclusions are inconsistent.

STUDY DESIGN

We recruited 104 SZ patients to have resting-state functional magnetic resonance imaging scans at baseline and 8 weeks of treatment with second-generation antipsychotics, along with baseline scanning of 86 healthy controls (HCs) for comparison purposes. Individual regional homogeneity (ReHo), amplitude of low-frequency fluctuations (ALFF), and degree centrality values were calculated to evaluate the functional activity. The Positive and Negative Syndrome Scale (PANSS) and MATRICS Consensus Cognitive Battery were applied to measure psychiatric symptoms and cognitive impairment in SZ patients.

RESULTS

Compared with HCs at baseline, SZ patients had higher ALFF and ReHo values in the bilateral inferior temporal gyrus, inferior frontal gyrus, and lower ALFF and ReHo values in fusiform gyrus and precuneus. Following 8 weeks of treatment, ReHo was increased in right medial region of the superior frontal gyrus (SFGmed) and decreased in the left middle occipital gyrus and the left postcentral gyrus. Meanwhile, ReHo of the right SFGmed was increased after treatment in the response group (the reduction rate of PANSS ≥50%). Enhanced ALFF in the dorsolateral of SFG correlated with improvement in depressive factor score.

CONCLUSIONS

These findings provide novel evidence for the abnormal functional activity hypothesis of SZ, suggesting that abnormality of right SFGmed can be used as a biomarker of treatment response in SZ.

Structural brain networks in schizophrenia based on nonnegative matrix factorization

Schizophrenia is a severe mental disease with significant morphometric reductions in gray matter volume and cortical thickness in a variety of brain regions. However, most studies only focused on the voxel level alterations in specific cerebral regions and ignored the spatial relationship between voxels. In the present study, we used a novel, data-driven technique-nonnegative matrix factorization (NMF) to group voxels with similar information into a network, and studied the structural covariance at the network level in schizophrenia. Our sample included 36 patients with schizophrenia and 21 healthy controls. Compared with healthy controls, patients with schizophrenia showed significant gray matter volume reductions in six structural covariance networks (dorsal striatum, thalamus, hippocampus-parahippocampus, supplementary motor area-fusiform, middle/inferior temporal network, frontal-parietal-occipital network). Our findings confirmed the assumption of a disturbance in the cortical-subcortical circuit in schizophrenia and suggested that NMF is a useful multivariate method to identify brain networks, which provides a new perspective to study the neural mechanism in schizophrenia.

Individual Differences in Emotion Attenuation Brought by Indirect Replies Is Related to Resting-State Brain Activity

During daily conversations, people prefer indirect replies in face-threatening situations. Existent studies have indicated that recipients tend to perceive the information conveyed by indirect replies as negative and emotion regions are engaged in indirect replies processing in face-threatening situations. In this study, we examined whether indirect replies can reduce recipients' experience of negative emotion and what are the underlying cerebral structures that may give rise to individual differences in the effectiveness of such replies in attenuating negative emotion. Behavior ratings and resting-stating functional magnetic resonance imaging (rs-fMRI) techniques were combined to explore these questions. We created dialogues expressing refusal or negative opinion with direct/indirect replies. Participants were asked to rate their emotional valence and arousal when they received such replies. The rating scores were used to correlate with spontaneous brain activity. Results showed that indirect replies indeed attenuated recipients' negative emotion experience. Moreover, the left caudate, the right anterior cingulate cortex (rACC), and the connectivity of rACC and left medial prefrontal cortex (lmPFC) were found to be positively correlated to individual differences in such emotion attenuation. Our findings provide direct empirical evidence for the face-saving function of indirect replies and reveal that the intrinsic brain activities of emotion network and theory of mind (ToM) network are related to individual differences in such emotion attenuation.

A schizophrenia study based on multi-frequency dynamic functional connectivity analysis of fMRI

At present, fMRI studies mainly focus on the entire low-frequency band (0. 01-0.08 Hz). However, the neuronal activity is dynamic, and different frequency bands may contain different information. Therefore, a novel multi-frequency-based dynamic functional connectivity (dFC) analysis method was proposed in this study, which was then applied to a schizophrenia study. First, three frequency bands (Conventional: 0.01-0.08 Hz, Slow-5: 0.0111-0.0302 Hz, and Slow-4: 0.0302-0.0820 Hz) were obtained using Fast Fourier Transform. Next, the fractional amplitude of low-frequency fluctuations was used to identify abnormal regions of interest (ROIs) of schizophrenia, and dFC among these abnormal ROIs was implemented by the sliding time window method at four window-widths. Finally, recursive feature elimination was employed to select features, and the support vector machine was applied for the classification of patients with schizophrenia and healthy controls. The experimental results showed that the proposed multi-frequency method (Combined: Slow-5 and Slow-4) had a better classification performance compared with the conventional method at shorter sliding window-widths. In conclusion, our results revealed that the dFCs among the abnormal ROIs varied at different frequency bands and the efficiency of combining multiple features from different frequency bands can improve classification performance. Therefore, it would be a promising approach for identifying brain alterations in schizophrenia.

Dynamic alterations of spontaneous neural activity in post-stroke aphasia: a resting-state functional magnetic resonance imaging study

Background and purpose

The dynamic alterations in spontaneous neural activity of the brain during the acute phase of post-stroke aphasia (PSA) remain unclear. Therefore, in this study, dynamic amplitude of low-frequency fluctuation (dALFF) was applied to explore abnormal temporal variability in local functional activity of the brain during acute PSA.

Materials and methods

Resting-state functional magnetic resonance imaging (rs-fMRI) data from 26 patients with PSA and 25 healthy controls (HCs) were acquired. The sliding window method was used to assess dALFF, with the k-means clustering method used to identify dALFF states. The two-sample t-test was applied to compare differences in dALFF variability and state metrics between the PSA and HC groups.

Results

(1) In the PSA group, greater variance of dALFF in the cerebellar network (CBN) and left fronto-temporo-parietal network (FTPN) was observed. (2) Three dALFF states were identified among all subjects. States 1 and 2 were identified in the PSA patients, and the two dALFF states shared a similar proportion. Moreover, the number of transitions between the two dALFF states was higher in the patients compared with that in HCs.

Conclusion

The results of this study provide valuable insights into brain dysfunction that occurs during the acute phase (6.00 ± 3.52 days) of PSA. The observed increase in variability of local functional activities in CBN and left FTPN may be related to the spontaneous functional recovery of language during acute PSA, and it also suggests that cerebellum plays an important role in language.

From local properties to brain-wide organization: A review of intraregional temporal features in functional magnetic resonance imaging data

Based on the fluctuations ensembled over neighbouring neurons, blood oxygen level-dependent (BOLD) signal is a mesoscale measurement of brain signals. Intraregional temporal features (IRTFs) of BOLD signal, extracted from regional neural activities, are utilized to investigate how the brain functions in local brain areas. This literature highlights four types of IRTFs and their representative calculations including variability in the temporal domain, variability in the frequency domain, entropy, and intrinsic neural timescales, which are tightly related to cognitions. In the brain-wide spatial organization, these brain features generally organized into two spatial hierarchies, reflecting structural constraints of regional dynamics and hierarchical functional processing workflow in brain. Meanwhile, the spatial organization gives rise to the link between neuronal properties and cognitive performance. Disrupted or unbalanced spatial conditions of IRTFs emerge with suboptimal cognitive states, which improved our understanding of the aging process and/or neuropathology of brain disease. This review concludes that IRTFs are important properties of the brain functional system and IRTFs should be considered in a brain-wide manner.

Neuronal dysfunction in individuals at early stage of schizophrenia, A resting-state fMRI study

Schizophrenia has been associated with abnormal intrinsic brain activity, involving various cognitive impairments. Qualitatively similar abnormalities are seen in individuals at ultra-high risk (UHR) for psychosis. In this study, resting-state fMRI (rs-fMRI) data were collected from 44 drug-naïve first-episode schizophrenia (Dn-FES) patients, 48 UHR individuals, and 40 healthy controls (HCs). The fractional amplitude of low-frequency fluctuations (fALFF), regional homogeneity (ReHo), and functional connectivity (FC), were performed to evaluate resting brain function. A support vector machine (SVM) was applied for classification analysis. Compared to HCs, both clinical groups showed increased fALFF in the central executive network (CEN), decreased ReHo in the ventral visual pathway (VVP) and decreased FC in temporal-sensorimotor regions. Excellent performance was achieved by using fALFF value in distinguishing both FES (sensitivity=83.21%, specificity=80.58%, accuracy=81.37%, p=0.009) and UHR (sensitivity=75.88%, specificity=85.72%, accuracy=80.72%, p<0.001) from HC group. Moreover, the study highlighted the importance of frontal and temporal alteration in the pathogenesis of schizophrenia. However, no fMRI features were observed that could well distinguish Dn-FES from UHR group. To conclude, fALFF in the CEN may provide potential power for identifying individuals at the early stage of schizophrenia and the alteration in the frontal and temporal lobe may be important to these individuals.

Research on brain functions related to visual information processing and body coordination function of pilots based on the low-frequency amplitude method

Objective

Research on the differences in physiological and psychological mechanisms of practitioners in different occupations is a current hot spot, such as pilots. This study explores the frequency-dependent changes of pilots’ low-frequency amplitudes in the classical frequency band and sub-frequency band between pilots and general occupations. The goal of the current work is to provide objective brain images for the selection and evaluation of outstanding pilots.

Methods

Twenty-six pilots and 23 age-, sex-, and education-matched healthy controls were included in this study. Then the mean low-frequency amplitude (mALFF) of the classical frequency band and sub-frequency band was calculated. The two-sample t-test was performed on SPM12 to analyze the differences between the flight group and control group in the classic frequency band. To explore the main effects and the inter-band effects of the mean low-frequency amplitude (mALFF), the mixed design analysis of variance was applied in the sub-frequency bands.

Results

Compared with the control group, left cuneiform lobe and the right cerebellum six area of pilots show significant difference in the classic frequency band. And the main effect results in the sub-frequency bands show that the area with higher mALFF in the flight group is located on the left middle occipital gyrus, the left cuneiform lobe, the right superior occipital gyrus, the right superior gyrus, and the left lateral central lobule. However, the area where the value of mALFF decreased is mainly located on the left rectangular cleft with surrounding cortex and the right dorsolateral superior frontal gyrus. Besides, compared with the slow-4 frequency band, the mALFF of the left middle orbital middle frontal gyrus of the slow-5 frequency band was increased, while the mALFF value of the left putamen, left fusiform gyrus, and right thalamus was decreased. The sensitivity of the slow-5 frequency band and the slow-4 frequency band to the pilots’ different brain areas was also different. Also, the different brain areas in the classic frequency band and the sub-frequency band were significantly correlated with pilots’ flight hours.

Conclusion

Our findings showed that the left cuneiform brain area and the right cerebellum of pilots changed significantly during resting state. And there was a positive correlation between the mALFF value of those brain area and flight hours. The comparative analysis of sub-frequency bands found that the slow-5 band could elucidate a wider range of different brain regions, providing new ideas for exploring the brain mechanisms of pilots.

Neurodevelopmental trajectories, polygenic risk, and lipometabolism in vulnerability and resilience to schizophrenia

BACKGROUND

Schizophrenia (SZ) arises from a complex interplay involving genetic and molecular factors. Early intervention of SZ hinges upon understanding its vulnerability and resiliency factors in study of SZ and genetic high risk for SZ (GHR).

METHODS

Herein, using integrative and multimodal strategies, we first performed a longitudinal study of neural function as measured by amplitude of low frequency function (ALFF) in 21 SZ, 26 GHR, and 39 healthy controls to characterize neurodevelopmental trajectories of SZ and GHR. Then, we examined the relationship between polygenic risk score for SZ (SZ-PRS), lipid metabolism, and ALFF in 78 SZ, and 75 GHR in cross-sectional design to understand its genetic and molecular substrates.

RESULTS

Across time, SZ and GHR diverge in ALFF alterations of the left medial orbital frontal cortex (MOF). At baseline, both SZ and GHR had increased left MOF ALFF compared to HC (P < 0.05). At follow-up, increased ALFF persisted in SZ, yet normalized in GHR. Further, membrane genes and lipid species for cell membranes predicted left MOF ALFF in SZ; whereas in GHR, fatty acids best predicted and were negatively correlated (r = -0.302, P < 0.05) with left MOF.

CONCLUSIONS

Our findings implicate divergence in ALFF alteration in left MOF between SZ and GHR with disease progression, reflecting vulnerability and resiliency to SZ. They also indicate different influences of membrane genes and lipid metabolism on left MOF ALFF in SZ and GHR, which have important implications for understanding mechanisms underlying vulnerability and resiliency in SZ and contribute to translational efforts for early intervention.

Sparse non-convex regularization based explainable DBN in the analysis of brain abnormalities in schizophrenia

Deep belief networks have been widely used in medical image analysis. However, the high-dimensional but small-sample-size characteristic of medical image data makes the model prone to dimensional disaster and overfitting. Meanwhile, the traditional DBN is driven by performance and ignores the explainability which is important for medical image analysis. In this paper, a sparse non-convex based explainable deep belief network is proposed by combining DBN with non-convex sparsity learning. For sparsity, the non-convex regularization and Kullback-Leibler divergence penalty are embedded into DBN to obtain the sparse connection and sparse response representation of the network. It effectively reduces the complexity of the model and improves the generalization ability of the model. Considering explainability, the crucial features for decision-making are selected through the feature back-selection based on the row norm of each layer's weight after network training. We apply the model to schizophrenia data and demonstrate it achieves the best performance among several typical feature selection models. It reveals 28 functional connections highly correlated with schizophrenia, which provides an effective foundation for the treatment and prevention of schizophrenia and methodological assurance for similar brain disorders.

Frequency-Dependent Alterations in the Amplitude of Low-Frequency Fluctuations in Patients with Acute Pericoronitis: A Resting-State fMRI Study

Background

Acute pericoronitis (AP) is a common cause of odontogenic toothache. Pain significantly affects the structure and function of the brain, but alterations in spontaneous brain activity in patients with AP are unclear.

Purpose

To apply the amplitude of low-frequency fluctuations (ALFF) method in resting-state functional magnetic resonance imaging to investigate altered spontaneous brain activity characteristics in patients with AP in different frequency bands (typical, slow-4, and slow-5 bands) and assess their correlation with clinical scores.

Patients and Methods

Thirty-four right-handed patients with AP and 31 healthy controls (HC), matched for age, sex, education, and right-handedness, were enrolled. All subjects underwent resting-state functional magnetic resonance imaging. DPABI software was used for data preprocessing and extracting the ALFF values in different frequency bands. Subsequently, differences in ALFF values in the three bands were compared between the two groups. Correlation between ALFF values in the differential brain regions and clinical scores was assessed.

Results

In the typical band, ALFF values were higher in the left insula, left superior occipital gyrus, left inferior parietal lobule, left posterior cerebellar lobule, and right postcentral gyrus in the AP than in the HC group. In the slow-4 band, ALFF values in the left superior occipital gyrus, right superior occipital gyrus, and right middle occipital gyrus were higher, and those in the right cingulate gyrus and right superior temporal gyrus were lower in the AP than in the HC group. In the slow-5 band, the ALFF values in the left insula and left superior occipital gyrus were higher in the AP than in the HC group. The ALFF values of the typical bands in the left insula, left inferior parietal lobule, and right postcentral gyrus correlated negatively, those of the slow-4 band in the right middle occipital gyrus correlated positively, and those of the slow-5 band in the left insula correlated negatively with the visual analogue scale score in the AP group.

Conclusion

Our results suggested that the intrinsic brain activity of AP patients was abnormal and frequency-dependent. This provides new insights to explore the neurophysiological mechanisms of AP.

A resting-state functional MRI study in patients with vestibular migraine during interictal period

To evaluate the spontaneous neuronal activities and the changes of brain functional network in patients with vestibular migraine (VM). Three groups including18 patients with VM, 21 patients with migraine without aura (MWoA) and 21 healthy controls (HCs) underwent the scanning of the resting-state fMRI. Covariance analysis and bonferroni multiple comparisons were used to obtain brain regions with significant differences in amplitude of low-frequency fluctuation (ALFF) values. Furthermore, the brain regions with the most significant differences of ALFF values were recognized as a region of interest (ROI) and functional connectivity (FC) analysis was performed in these regions. (1) ALFF: Compared with HCs, patients with VM showed significantly lower ALFF in the right putamen (P < 0.05), and significantly higher ALFF in the right lingual gyrus (P < 0.05). In addition, compared with MWoA patients, patients with VM showed significantly higher ALFF in the right lingual gyrus (P < 0.05). (2) Compared with HCs, VM patients showed significantly higher FC among the cerebellum, the left dorsolateral superior frontal gyrus and the right putamen (P < 0.05) but significantly lower FC among the left median cingulate, paracingulate gyri and the right putamen (P < 0.05). Compared with MWoA patients, VM patients showed significantly higher FC between the cerebellum and the right putamen (P < 0.05) but significantly lower FC among the left median cingulate, paracingulate gyri and the right putamen (P < 0.05). There are functional abnormalities in nociceptive, vestibular and visual cortex regions in patients with VM during the interictal period.

People with high schizotypy experience more illusions in the Pattern Glare Test: Consistent with the hyperexcitability hypothesis

Individuals diagnosed with schizophrenia spectrum disorders (SSD) exhibit a constellation of sensory and perceptual impairments, including hyporeactivity to external input. However, individuals with SSD also report subjective experiences of sensory flooding, suggesting sensory hyperexcitability. To identify the extent to which behavioural indices of hyperexcitability are related to non-psychotic symptoms of schizophrenia, we tested a non-clinical population measured for schizophrenia-like traits (schizotypy), and a behavioural measure of sensory hyperexcitability, specifically the number of illusions seen in the Pattern Glare Test. Two samples totaling 913 individuals completed an online version of the Schizotypal Personality Questionnaire - Brief Revised (SPQ-BR) and the Pattern Glare Test. Individuals with higher schizotypy traits reported more illusions in the Pattern Glare Test. Additionally, one of the three SPQ-BR factors, the disorganized factor, significantly predicted the number of illusions reported. These data illustrate the potential for research in non-clinical samples to inform clinically relevant research.

Default mode network alterations underlie auditory verbal hallucinations in schizophrenia

Although alterations of the default mode network (DMN) in schizophrenia (SZ) have been largely investigated, less research has been carried out on DMN alterations in different sub-phenotypes of this disorder. The aim of this pilot study was to compare DMN features among SZ patients with and without auditory verbal hallucinations (AVH). Three groups of 17 participants each were considered: patients with hallucinations (AVH-SZ), patients without hallucinations (nAVH-SZ) and age-matched healthy controls (HC). The DMN spatial pattern was similar between the nAVH-SZ and HC, but the comparison between these two groups and the AVH-SZ group revealed alterations in the left Angular Gyrus (lAG) node of the DMN. Using a novel approach based on normalized fractional Amplitude of Low-Frequency Fluctuations (fALFF), the AVH-SZ subgroup showed altered spectral activity in the DMN compared with the other two groups, especially in the lower-frequency bands (0.017-0.04 Hz). Significant positive correlations were found for both SZ groups collapsed, and for the nAVH-SZ group alone between delusional scores (PANSS-P1) and slow fALFF bands of the DMN. Narrowing the analysis to the ROI centered on the lAG, significant correlations were found in the AVH-SZ group for hallucination scores (PANSS-P3) and Slow-5 and Slow-4 (both positive), and Slow-3 (negative) fALFF bands. Our results reveal the central role of the lAG in relation to hallucinations, an important cortical area connecting auditory cortex with several hubs (including frontal linguistic centers) and involved in auditory process monitoring.

Comparisons of resting-state brain activity between insomnia and schizophrenia: a coordinate-based meta-analysis

Growing evidence shows that insomnia is closely associated with schizophrenia (SCZ), but the neural mechanism under the association remains unclear. A direct comparison of the patterns of resting-state brain activities would help understand the above question. Using meta-analytic approach, 11 studies of insomnia vs. healthy controls (HC) and 39 studies of SCZ vs. HC were included to illuminate the common and distinct patterns between insomnia and SCZ. Results showed that SCZ and insomnia shared increased resting-state brain activities in frontolimbic structures including the right medial prefrontal gyrus (mPFC) and left parahippocampal gyrus. SCZ additionally revealed greater increased activities in subcortical areas including bilateral putamen, caudate and right insula and greater decreased activities in precentral gyrus and orbitofrontal gyrus. Our study reveals both shared and distinct activation patterns in SCZ and insomnia, which may provide novel insights for understanding the neural basis of the two disorders and enlighten the possibility of the development of treatment strategies for insomnia in SCZ in the future.

Alterations of Power Spectral Density in Salience Network during Thought-action Fusion Induction Paradigm in Obsessive-compulsive Disorder

Objective

Methods

Results

Conclusion

Intrinsic brain activity patterns across large-scale networks predict reciprocity propensity

Reciprocity is prevalent across human societies, but individuals are heterogeneous regarding their reciprocity propensity. Although a large body of task-based brain imaging measures has shed light on the neural underpinnings of reciprocity at group level, the neural basis underlying the individual differences in reciprocity propensity remains largely unclear. Here, we combined brain imaging and machine learning techniques to individually predict reciprocity propensity from resting-state brain activity measured by fractional amplitude of low-frequency fluctuation. The brain regions contributing to the prediction were then analyzed for functional connectivity and decoding analyses, allowing for a data-driven quantitative inference on psychophysiological functions. Our results indicated that patterns of resting-state brain activity across multiple brain systems were capable of predicting individual reciprocity propensity, with the contributing regions distributed across the salience (e.g., ventrolateral prefrontal cortex), fronto-parietal (e.g., dorsolateral prefrontal cortex), default mode (e.g., ventromedial prefrontal cortex), and sensorimotor (e.g., supplementary motor area) networks. Those contributing brain networks are implicated in emotion and cognitive control, mentalizing, and motor-based processes, respectively. Collectively, these findings provide novel evidence on the neural signatures underlying the individual differences in reciprocity, and lend support the assertion that reciprocity emerges from interactions among regions embodied in multiple large-scale brain networks.

Aberrant amplitude of low-frequency fluctuations in different frequency bands and changes after one-night positive airway pressure treatment in severe obstructive sleep apnea

Objective

This study was aimed to investigate the characteristics of the amplitude of low-frequency fluctuation (ALFF) at specific frequencies in severe obstructive sleep apnea (OSA) patients. A comparison was made between pre-CPAP treatment and one night after continuous positive airway pressure (CPAP) treatment.

Methods

30 severe OSA patients and 19 healthy controls (HC) were recruited. The ALFF method was used to assess the local features of spontaneous brain activity and calculated at different bands (slow-5 and slow-4). A correlation analysis was performed to evaluate the relationship between the changes of the ALFF and polysomnography data.

Results

Compared with HC, in slow-5 frequency band, OSA patients showed significantly decreased ALFF in the left inferior temporal gyrus, and significantly increased ALFF in the left middle frontal gyrus, left inferior frontal gyrus, triangular part, right superior frontal gyrus, dorsolateral and right middle temporal gyrus. In slow-4 frequency, there was significantly decreased ALFF in the right inferior temporal gyrus, and significantly increased ALFF in the left precuneus, right posterior cingulate gyrus and right median cingulate besides the slow-5 difference band showed. Compared with pre-CPAP, we found that after CPAP treatment, ALFF signals in the left insula in slow-5 and left caudate in slow-4 increased, but the calcarine in slow-4 significantly reduced. Correlation analysis showed that the left angular slow-4 band change was positively correlated with the slow wave sleep change (r = 0.4933, p = 0.0056). The left cerebellum 6 slow-5 band change was positively correlated with the duration of the REM sleep change (r = 0.4563, p = 0.0113), and the left cerebellum 6 slow-4 band change was also positively correlated with the mean blood oxygen change in the REM (r = 0.4591, p = 0.0107) and NREM sleep (r = 0.4492, p = 0.0128).

Conclusion

We found that the use of slow-4 was more specific in OSA studies. These results suggested that the severe OSA patients have frequency-related abnormal spontaneous neural activity, which may contribute to a better understanding of the pathological basis of OSA-related diseases and provide a potential therapeutic target for OSA patients.

Amplitude of low-frequency fluctuations in multiple-frequency bands in patients with intracranial tuberculosis: a prospective cross-sectional study

Background

Resting-state functional magnetic resonance imaging (rs-fMRI) is widely used to study brain functional alteration, but there have been no reports of research regarding the application of rs-fMRI in intracranial tuberculosis. The purpose of this prospective, cross-sectional study was to investigate spontaneous neural activity at different frequency bands in patients with intracranial tuberculosis using rs-fMRI with amplitude of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF) methods.

Methods

The rs-fMRI data of 31 patients with intracranial tuberculosis and 30 gender-, age-, and education-matched healthy controls (HCs) were included. The ALFF and fALFF values in the conventional frequency band (0.01−0.08 Hz) and 2 sub-frequency bands (slow-4: 0.027–0.073 Hz; slow-5: 0.01–0.027 Hz) were calculated and compared between the groups. The resultant T-maps were corrected using the Gaussian random field (GRF) theory (voxel P<0.01, cluster P<0.05). Correlations between the ALFF and fALFF values and neurocognitive scores were assessed.

Results

Compared with the HCs, patients with intracranial tuberculosis showed decreased ALFF in the right paracentral lobule (T=−4.69) in the conventional frequency band, in the right supplementary motor area (T=−4.85) in the slow-4 band, and in the left supplementary motor area (T=−3.76) in the slow-5 band. Compared to the slow-5 band, the voxels with decreased ALFF were spatially more extensive in the slow-4 band. Compared with HCs, patients with intracranial tuberculosis showed decreased fALFF in the opercular parts of the right inferior frontal gyrus (T=−4.50) and the left inferior parietal lobe (T=−4.86) and increased fALFF in the left inferior cerebellum (T=5.84) in the conventional frequency band. In the slow-4 band, fALFF decreased in the opercular parts of the right inferior frontal gyrus (T=−5.29) and right precuneus (T=−4.34). In the slow-5 band, fALFF decreased in the left middle occipital gyrus (T=−4.65) and right middle frontal gyrus (T=−5.05).

Conclusions

Patients with intracranial tuberculosis showed abnormal intrinsic brain activity at different frequency bands, and ALFF abnormalities in different brain regions could be better detected in the slow-4 band. This preliminary study might provide new insights into understanding the pathophysiological mechanism in intracranial tuberculosis.

Alterations in Spontaneous Brain Activity in Drug-Naïve First-Episode Schizophrenia: An Anatomical/Activation Likelihood Estimation Meta-Analysis

OBJECTIVE

The etiology of schizophrenia is unknown and is associated with abnormal spontaneous brain activity. There are no consistent results regarding the change in spontaneous brain activity of people with schizophrenia. In this study, we determined the specific changes in the amplitude of low-frequency fluctuation/fractional amplitude of low-frequency fluctuation (ALFF/fALFF) and regional homogeneity (ReHo) in patients with drug-naïve first-episode schizophrenia (Dn-FES).

METHODS

A comprehensive search of databases such as PubMed, Web of Science, and Embase was conducted to find articles on resting-state functional magnetic resonance imaging using ALFF/fALFF and ReHo in schizophrenia patients compared to healthy controls (HCs) and then, anatomical/activation likelihood estimation was performed.

RESULTS

Eighteen eligible studies were included in this meta-analysis. Compared to the spontaneous brain activity of HCs, we found changes in spontaneous brain activity in Dn-FES based on these two methods, mainly including the frontal lobe, putamen, lateral globus pallidus, insula, cerebellum, and posterior cingulate cortex.

CONCLUSION

We found that widespread abnormalities of spontaneous brain activity occur in the early stages of the onset of schizophrenia and may provide a reference for the early intervention of schizophrenia.

Typical resting state activity of the brain requires visual input during an early sensitive period

Sensory deprivation, following a total loss of one sensory modality e.g. vision, has been demonstrated to result in compensatory plasticity. It is yet not known to which extent neural changes, e.g. higher resting-state activity in visual areas (cross-modal plasticity) as a consequence of blindness, reverse, when sight is restored. Here, we used functional MRI to acquire blood oxygen level-dependent resting-state activity during an eyes open and an eyes closed state in congenital cataract-reversal individuals, developmental cataract-reversal individuals, congenitally permanently blind individuals and sighted controls. The amplitude of low frequency fluctuation of the blood oxygen level-dependent signal—a neural marker of spontaneous brain activity during rest—was analyzed. In accordance with previous reports, in normally sighted controls we observed an increase in amplitude of low-frequency fluctuation during rest with the eyes open compared with rest with eyes closed in visual association areas and in parietal cortex but a decrease in auditory and sensorimotor regions. In congenital cataract-reversal individuals, we found an increase of the amplitude of slow blood oxygen level-dependent fluctuations in visual cortex during rest with eyes open compared with rest with eyes closed too but this increase was larger in amplitude than in normally sighted controls. In contrast, congenital cataract-reversal individuals lagged a similar increase in parietal regions and did not show the typical decrease of amplitude of low-frequency fluctuation in auditory cortex. Congenitally blind individuals displayed an overall higher amplitude in slow blood oxygen level-dependent fluctuations in visual cortex compared with sighted individuals and compared with congenital cataract-reversal individuals in the eyes closed condition. Higher amplitude of low-frequency fluctuation in visual cortex of congenital cataract-reversal individuals than in normally sighted controls during eyes open might indicate an altered excitatory–inhibitory balance of visual neural circuits. By contrast, the lower parietal increase and the missing downregulation in auditory regions suggest a reduced influence of the visual system on multisensory and the other sensory systems after restoring sight in congenitally blind individuals. These results demonstrate a crucial dependence of visual and multisensory neural system functioning on visual experience during a sensitive phase in human brain development.

Feature and decision-level fusion for schizophrenia detection based on resting-state fMRI data

Mental disorders, especially schizophrenia, still pose a great challenge for diagnosis in early stages. Recently, computer-aided diagnosis techniques based on resting-state functional magnetic resonance imaging (Rs-fMRI) have been developed to tackle this challenge. In this work, we investigate different decision-level and feature-level fusion schemes for discriminating between schizophrenic and normal subjects. Four types of fMRI features are investigated, namely the regional homogeneity, voxel-mirrored homotopic connectivity, fractional amplitude of low-frequency fluctuations and amplitude of low-frequency fluctuations. Data denoising and preprocessing were first applied, followed by the feature extraction module. Four different feature selection algorithms were applied, and the best discriminative features were selected using the algorithm of feature selection via concave minimization (FSV). Support vector machine classifiers were trained and tested on the COBRE dataset formed of 70 schizophrenic subjects and 70 healthy subjects. The decision-level fusion method outperformed the single-feature-type approaches and achieved a 97.85% accuracy, a 98.33% sensitivity, a 96.83% specificity. Moreover, feature-fusion scheme resulted in a 98.57% accuracy, a 99.71% sensitivity, a 97.66% specificity, and an area under the ROC curve of 0.9984. In general, decision-level and feature-level fusion schemes boosted the performance of schizophrenia detectors based on fMRI features.

Intermittent theta burst stimulation improved visual-spatial working memory in treatment-resistant schizophrenia: A pilot study

BACKGROUND

Visual-spatial working memory (vsWM) impairment in treatment-resistant schizophrenia (TRS) currently has no satisfactory treatment. Our study aimed to improve vsWM function in TRS through intermittent theta burst stimulation (iTBS) using neuronavigation equipment to target the left dorsolateral prefrontal cortex.

METHOD

TRS patients (n = 59) were randomly allocated to receive iTBS (n = 33) or a sham treatment (n = 26) over 2 weeks. The participants including TRS patients and healthy controls (HCs) performed the vsWM n-back task, and TRS patients' neuroimaging data were acquired before and after treatment. All patients also underwent a battery of symptom measures to assess the severity of illness. The main outcome measure was the accuracy (ACC) of n-back target responses, particularly 3-back ACC.

RESULTS

The iTBS group showed considerable improvement in n-back ACC compared to the sham group, especially 3-back ACC. After iTBS, performance on the n-back task was comparable to that of HCs. The interaction (group × time) results showed increased fractional amplitude of low frequency fluctuations (fALFF) in the right occipital areas and decreased fALFF in the right precuneus. However, there was a negative correlation between the 3-back ACC and improved clinical symptoms scores. Improvements in 3-back ACC were positively correlated with activity in the right visual cortex.

CONCLUSIONS

Our study suggested that 2 weeks of iTBS intervention may be a novel, efficacious treatment for vsWM deficits in TRS, which can modulate the activity of local brain regions. iTBS can provide a solution for clinical treatment of TRS and may help patients approach normalcy.

Machine Learning Evidence for Sex Differences Consistently Influences Resting-State Functional Magnetic Resonance Imaging Fluctuations Across Multiple Independently Acquired Data Sets

Background/Introduction: Sex classification using functional connectivity from resting-state functional magnetic resonance imaging (rs-fMRI) has shown promising results. This suggested that sex difference might also be embedded in the blood-oxygen-level-dependent properties such as the amplitude of low-frequency fluctuation (ALFF) and the fraction of ALFF (fALFF). This study comprehensively investigates sex differences using a reliable and explainable machine learning (ML) pipeline. Five independent cohorts of rs-fMRI with over than 5500 samples were used to assess sex classification performance and map the spatial distribution of the important brain regions. Methods: Five rs-fMRI samples were used to extract ALFF and fALFF features from predefined brain parcellations and then were fed into an unbiased and explainable ML pipeline with a wide range of methods. The pipeline comprehensively assessed unbiased performance for within-sample and across-sample validation. In addition, the parcellation effect, classifier selection, scanning length, spatial distribution, reproducibility, and feature importance were analyzed and evaluated thoroughly in the study. Results: The results demonstrated high sex classification accuracies from healthy adults (area under the curve >0.89), while degrading for nonhealthy subjects. Sex classification showed moderate to good intraclass correlation coefficient based on parcellation. Linear classifiers outperform nonlinear classifiers. Sex differences could be detected even with a short rs-fMRI scan (e.g., 2 min). The spatial distribution of important features overlaps with previous results from studies. Discussion: Sex differences are consistent in rs-fMRI and should be considered seriously in any study design, analysis, or interpretation. Features that discriminate males and females were found to be distributed across several different brain regions, suggesting a complex mosaic for sex differences in rs-fMRI. Impact statement The presented study unraveled that sex differences are embedded in the blood-oxygen-level dependent (BOLD) and can be predicted using unbiased and explainable machine learning pipeline. The study revealed that psychiatric disorders and demographics might influence the BOLD signal and interact with the classification of sex. The spatial distribution of the important features presented here supports the notion that the brain is a mosaic of male and female features. The findings emphasize the importance of controlling for sex when conducting brain imaging analysis. In addition, the presented framework can be adapted to classify other variables from resting-state BOLD signals.

Increased cingulo-orbital connectivity is associated with violent behaviours in schizophrenia

OBJECTIVE

Although schizophrenia patients are at a heightened risk of exhibiting violent behaviours compared to the general population, few functional neuroimaging studies have explored the aberrant neurocircuitry underpinning such behaviours. This study aimed to identify disrupted resting-state activity and functional connectivity in schizophrenia patients with a history of violence.

METHODS

Resting state functional magnetic resonance imaging data was collected from 62 schizophrenia patients and 25 healthy controls. Voxel-wise analyses of fractional amplitude of low frequency fluctuations (fALFF) were implemented to investigate disrupted regional patterns of spontaneous brain activity. Brain regions which yielded significant differences between groups were subsequently used as data-driven seeds for functional connectivity analyses. Finally, significant alterations (activity and connectivity) were correlated with lifetime violent behaviours.

RESULTS

When compared to healthy controls, schizophrenia patients exhibited reduced fALFF in multiple brain regions including the (subgenual) anterior cingulate cortex (ACC), posterior cingulate cortex, precuneus cortex and left lateral orbitofrontal cortex (OFC). Seed-to-voxel analyses yielded significantly enhanced connectivity between the ACC and left OFC. The heightened functional connectivity between the latter two regions predicted the number of violent behaviours reported by schizophrenia patients.

CONCLUSION

The current study demonstrated that the functional connectivity of brain regions associated with emotion regulation is impaired in schizophrenia and associated with violent antecedents among patients. This result is consistent with predominant theoretical models proposing that the OFC plays a critical role in the neurobiology of violence.

Frequency-specific age-related changes in the amplitude of spontaneous fluctuations in autism

BACKGROUND

Autism spectrum disorder is characterized by atypical developmental changes during brain maturation, but regional brain functional changes that occur with age and across different frequency bands are unknown. Therefore, the current study aimed to explore potential age and frequency band-related changes in the regional brain activities in autism.

METHODS

A total of 65 participants who met the DSM-IV criteria for autistic disorder and 55 typically developed (TD) participants (both age 6-30 years) were recruited in the current study. The two groups were matched in age (t=-1.314, P=0.191) and gender (χ²=2.760, P=0.097). The amplitude of low-frequency fluctuations (ALFF) was employed to explore the effect of development on spontaneous brain activity in individuals with autism and in TD participants across slow-5 (0.01-0.027 Hz), slow-4 (0.027-0.073 Hz), and slow-3 (0.073-0.1 Hz) frequency bands. The diagnosis-by-age interaction effect in the whole brain voxels in autism and TD groups was investigated.

RESULTS

Autism individuals showed significantly higher ALFF in the dorsal striatum in childhood (Caudate cluster: t=3.626, P=0.001; Putamen cluster: t=2.839, P=0.007) and remarkably lower ALFF in the dorsal striatum in adulthood (Caudate cluster: t=-2.198, P=0.038; Putamen cluster: t=-2.314, P=0.030) relative to TD, while no significant differences were observed in adolescence (all P>0.05). In addition, abnormal ALFF amplitudes were specific to the slow-4 (0.027-0.073 Hz) frequency band in the clusters above.

CONCLUSIONS

The current study indicated abnormal development patterns in the spontaneous activity of the dorsal striatum in autism and highlighted the potential role of the slow-4 frequency band in the pathology of autism. Also, the potential brain mechanism of autism was revealed, suggesting that autism-related variations should be investigated in a specific frequency.

A Real-World Observation of Antipsychotic Effects on Brain Volumes and Intrinsic Brain Activity in Schizophrenia

Background

The confounding effects of antipsychotics that led to the inconsistencies of neuroimaging findings have long been the barriers to understanding the pathophysiology of schizophrenia (SZ). Although it is widely accepted that antipsychotics can alleviate psychotic symptoms during the early most acute phase, the longer-term effects of antipsychotics on the brain have been unclear. This study aims to look at the susceptibility of different imaging measures to longer-term medicated status through real-world observation.

Methods

We compared gray matter volume (GMV) with amplitude of low-frequency fluctuations (ALFFs) in 89 medicated-schizophrenia (med-SZ), 81 unmedicated-schizophrenia (unmed-SZ), and 235 healthy controls (HC), and the differences were explored for relationships between imaging modalities and clinical variables. We also analyzed age-related effects on GMV and ALFF values in the two patient groups (med-SZ and unmed-SZ).

Results

Med-SZ demonstrated less GMV in the prefrontal cortex, temporal lobe, cingulate gyri, and left insula than unmed-SZ and HC (p &lt; 0.05, family-wise error corrected). Additionally, GMV loss correlated with psychiatric symptom relief in all SZ. However, medicated status did not influence ALFF values: all SZ showed increased ALFF in the anterior cerebrum and decreased ALFF in posterior visual cortices compared with HC (p &lt; 0.05, family-wise error corrected). Age-related GMV effects were seen in all regions, which showed group-level differences except fusiform gyrus. No significant correlation was found between ALFF values and psychiatric symptoms.

Conclusion

GMV loss appeared to be pronounced to longer-term antipsychotics, whereby imbalanced alterations in regional low-frequency fluctuations persisted unaffected by antipsychotic treatment. Our findings may help to understand the disease course of SZ and potentially identify a reliable neuroimaging feature for diagnosis.

Detection of functional and structural brain alterations in female schizophrenia using elastic net logistic regression

Neuroimaging technique is a powerful tool to characterize the abnormality of brain networks in schizophrenia. However, the neurophysiological substrate of schizophrenia is still unclear. Here we investigated the patterns of brain functional and structural changes in female patients with schizophrenia using elastic net logistic regression analysis of resting-state functional magnetic resonance imaging data. Data from 52 participants (25 female schizophrenia patients and 27 healthy controls) were obtained. Using an elastic net penalty, the brain regions most relevant to schizophrenia pathology were defined in the models using the amplitude of low-frequency fluctuations (ALFF) and gray matter, respectively. The receiver operating characteristic analysis showed reliable classification accuracy with 85.7% in ALFF analysis, and 77.1% in gray matter analysis. Notably, our results showed eight common regions between the ALFF and gray matter analyses, including the Frontal-Inf-Orb-R, Rolandic-Oper-R, Olfactory-R, Angular-L, Precuneus-L, Precuenus-R, Heschl-L, and Temporal-Pole-Mid-R. In addition, the severity of symptoms was found positively associated with the ALFF within the Rolandic-Oper-R and Frontal-Inf-Orb-R. Our findings indicated that elastic net logistic regression could be a useful tool to identify the characteristics of schizophrenia -related brain deterioration, which provides novel insights into schizophrenia diagnosis and prediction.

Frequency-Specific Changes of Amplitude of Low-Frequency Fluctuations in Patients with Acute Basal Ganglia Ischemic Stroke

Objective. The purpose of this study was to investigate the characteristics of different frequency bands in the spontaneous brain activity among patients with acute basal ganglia ischemic stroke (BGIS). Methods. In the present study, thirty-four patients with acute BGIS and forty-four healthy controls were examined by resting-state functional magnetic resonance imaging (rs-fMRI) from May 2019 to December 2020. Two amplitude methods including amplitude of low-frequency fluctuations (ALFF) and fractional ALFF (fALFF) calculated in three frequency bands (conventional frequency band: 0.01-0.08 Hz; slow-5 frequency band: 0.01-0.027 Hz; and slow-4 frequency band: 0.027-0.073 Hz) were conducted to evaluate the spontaneous brain activity in patients with acute BGIS and healthy controls (HCs). Gaussian Random Field Theory (GRF, voxel $p<0.01$ and cluster $p<0.05$ ) correction was applied. The correlation analyses were performed between clinical scores and altered metrics values. Results. Compared to HCs, patients with acute BGIS showed decreased ALFF in the right supramarginal gyrus (SMG) in the conventional and slow-4 bands, increased fALFF in the right middle frontal gyrus (MFG) in the conventional and slow-4 bands, and increased fALFF in the bilateral caudate in the slow-5 frequency band. The fALFF value of the right caudate in the slow-5 frequency band was negatively correlated with the clinical scores. Conclusion. In conclusion, this study showed the alterations in ALFF and fALFF in three frequency bands between patients with acute BGIS and HCs. The results reflected that the abnormal LFO amplitude might be related with different frequency bands and promoted our understanding of pathophysiological mechanism in acute BGIS.

Test-retest stability of spontaneous brain activity and functional connectivity in the core resting-state networks assessed with ultrahigh field 7-Tesla resting-state functional magnetic resonance imaging

The growing demand for precise and reliable biomarkers in psychiatry is fueling research interest in the hope that identifying quantifiable indicators will improve diagnoses and treatment planning across a range of mental health conditions. The individual properties of brain networks at rest have been highlighted as a possible source for such biomarkers, with the added advantage that they are relatively straightforward to obtain. However, an important prerequisite for their consideration is their reproducibility. While the reliability of resting‐state (RS) measurements has often been studied at standard field strengths, they have rarely been investigated using ultrahigh‐field (UHF) magnetic resonance imaging (MRI) systems. We investigated the intersession stability of four functional MRI RS parameters—amplitude of low‐frequency fluctuations (ALFF) and fractional ALFF (fALFF; representing the spontaneous brain activity), regional homogeneity (ReHo; measure of local connectivity), and degree centrality (DC; measure of long‐range connectivity)—in three RS networks, previously shown to play an important role in several psychiatric diseases—the default mode network (DMN), the central executive network (CEN), and the salience network (SN). Our investigation at individual subject space revealed a strong stability for ALFF, ReHo, and DC in all three networks, and a moderate level of stability in fALFF. Furthermore, the internetwork connectivity between each network pair was strongly stable between CEN/SN and moderately stable between DMN/SN and DMN/SN. The high degree of reliability and reproducibility in capturing the properties of the three major RS networks by means of UHF‐MRI points to its applicability as a potentially useful tool in the search for disease‐relevant biomarkers.

Aberrant Functional Connectivity of the Orbitofrontal Cortex Is Associated With Excited Symptoms in First-Episode Drug-Naïve Patients With Schizophrenia

BACKGROUND

Schizophrenia (SZ) is associated with the highest disability rate among serious mental disorders. Excited symptoms are the core symptoms of SZ, which appear in the early stage, followed by other stages of the disease subsequently. These symptoms are destructive and more prone to violent attacks, posing a serious economic burden to the society. Abnormal spontaneous activity in the orbitofrontal cortex had been reported to be associated with excited symptoms in patients with SZ. However, whether the abnormality appears in first-episode drug-naïve patients with SZ has still remained elusive.

METHODS

A total of 56 first-episode drug-naïve patients with SZ and 27 healthy controls underwent resting-state functional magnetic resonance imaging (rs-fMRI) and positive and negative syndrome scale (PANSS). First, differences in fractional amplitude of low-frequency fluctuations (fALFF) between first-episode drug-naïve patients with SZ and healthy controls were examined to identify cerebral regions exhibiting abnormal local spontaneous activity. Based on the fALFF results, the resting-state functional connectivity analysis was performed to determine changes in cerebral regions exhibiting abnormal local spontaneous activity. Finally, the correlation between abnormal functional connectivity and exciting symptoms was analyzed.

RESULTS

Compared with the healthy controls, first-episode drug-naïve patients with SZ showed a significant decrease in intrinsic activity in the bilateral precentral gyrus, bilateral postcentral gyrus, and the left orbitofrontal cortex. In addition, first-episode drug-naïve patients with SZ had significantly reduced functional connectivity values between the left orbitofrontal cortex and several cerebral regions, which were mainly distributed in the bilateral postcentral gyrus, the right middle frontal gyrus, bilateral paracentral lobules, the left precentral gyrus, and the right median cingulate. Further analyses showed that the functional connectivity between the left orbitofrontal cortex and the left postcentral gyrus, as well as bilateral paracentral lobules, was negatively correlated with excited symptoms in first-episode drug-naïve patients with SZ.

CONCLUSION

Our results indicated the important role of the left orbitofrontal cortex in first-episode drug-naïve patients with SZ and suggested that the abnormal spontaneous activity of the orbitofrontal cortex may be valuable to predict the occurrence of excited symptoms. These results may provide a new direction to explore the excited symptoms of SZ.

Gender differences in major depressive disorders: A resting state fMRI study

BACKGROUND

Major depressive disorder (MDD) has a high disability rate and brings a large disease burden to patients and the country. Significant sex differences exist in both the epidemiological and clinical features in MDD. The effect of sex on brain function in MDD is not clear now. Regional homogeneity (ReHo) and ALFF are widely used research method in the study of brain function. This research aimed to use ReHo and ALFF to explore gender differences in brain function images in MDD.

METHODS

Eighty first-episode drug-naive patients (47 women and 30 men) with MDD and 85 age, education matched healthy volunteers (47 women and 31 men) were recruited in our study and participated in resting-state functional magnetic resonance imaging scans. ReHo and ALFF were used to assess brain activity, two-way ANOVA and post hoc analysis was conducted to explore the sex difference in MDD. Correlation analysis was used to explore the relationship between abnormal brain functioning and clinical symptoms.

RESULTS

We observed sex-specific patterns and diagnostic differences in MDD Patients, further post hoc comparisons indicated that women with MDD showed decreased ALFF value in the right superior occipital gyrus and decreased ReHo value in the left calcarine and left dorsolateral superior frontal gyrus compared with HC females and men with MDD. Men with MDD showed decreased ReHo value in the right median cingulate gyrus compared with HC males and increased ReHo value in the left dorsolateral superior frontal gyrus compared with HC males, we also found that HC males showed higher ReHo value in the right median cingulate gyrus than HC females.

CONCLUSIONS

Men and women do have sex differences in brain function, the occipital lobe, calcarine, DLPFC, and DCG were the main different brain regions found between male and female in MDD, which may be the biomarker brain regions that can help diagnose and treat MDD in men and women.