Clinical utility of resting-state functional connectivity magnetic resonance imaging for mood and cognitive disorders

Gray matter volume and corresponding covariance connectivity are biomarkers for major depressive disorder

The major depressive disorder (MDD) is a common and severe mental disorder. To identify a reliable biomarker for MDD is important for early diagnosis and prevention. Given easy access and high reproducibility, the structural magnetic resonance imaging (sMRI) is an ideal method to identify the biomarker for depression. In this study, sMRI data of first episode, treatment-naïve 66 MDD patients and 54 sex-, age-, and education-matched healthy controls (HC) were used to identify the differences in gray matter volume (GMV), group-level, individual-level covariance connections. Finally, the abnormal GMV and individual covariance connections were applied to classify MDD from HC. MDD patients showed higher GMV in middle occipital gyrus (MOG) and precuneus (PCun), and higher structural covariance connections between MOG and PCun. In addition, the Allen Human Brain Atlas (AHBA) was applied and revealed the genetic basis for the changes of gray matter volume. Importantly, we reported that GMV in MOG, PCun and structural covariance connectivity between MOG and PCun are able to discriminate MDD from HC. Our results revealed structural underpinnings for MDD, which may contribute towards early discriminating for depression.

Unveiling altered connectivity between cognitive networks and cerebellum in schizophrenia

Cognitive functioning is a crucial aspect in schizophrenia (SZ), and when altered it has devastating effects on patients' quality of life and treatment outcomes. Several studies suggested that they could result from altered communication between the cortex and cerebellum. However, the neural correlates underlying these impairments have not been identified. In this study, we investigated resting state functional connectivity (rsFC) in SZ patients, by considering the interactions between cortical networks supporting cognition and cerebellum. In addition, we investigated the relationship between SZ patients' rsFC and their symptoms. We used fMRI data from 74 SZ patients and 74 matched healthy controls (HC) downloaded from the publicly available database SchizConnect. We implemented a seed-based connectivity approach to identify altered functional connections between specific cortical networks and cerebellum. We considered ten commonly studied resting state networks, whose functioning encompasses specific cognitive functions, and the cerebellum, whose involvement in supporting cognition has been recently identified. We then explored the relationship between altered rsFC values and Positive and Negative Syndrome Scale (PANSS) scores. The SZ group showed increased connectivity values compared with HC group for cortical networks involved in attentive processes, which were also linked to PANSS items describing attention and language-related processing. We also showed decreased connectivity between cerebellar regions, and increased connectivity between them and attentive networks, suggesting the contribution of cerebellum to attentive and affective deficits. In conclusion, our findings highlighted the link between negative symptoms in SZ and altered connectivity within the cerebellum and between the same and cortical networks supporting cognition.

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.

Changed brain entropy and functional connectivity patterns induced by electroconvulsive therapy in majoy depression disorder

OBJECTIVE

Our objective is to innovatively integrate both linear and nonlinear characteristics of brain signals in Electroconvulsive Therapy (ECT) research, with the goal of uncovering deeper insights into the pathogenesis of Major Depressive Disorder (MDD) and identifying novel targets for other physical intervention therapies.

METHODS

We measured brain entropy (BEN) in 42 MDD patients and 42 matched healthy controls (HC) using rs-fMRI data. Brain regions that differed significantly in patients with MDD before and after ECT were extracted. Then, we use these brain regions as seed points to investigate the differences in whole-brain resting-state functional connectivity (RSFC) patterns before and after ECT.

RESULTS

Compared to HCs, patients had higher BEN levels in the right precuneus (PCUN.R) and right angular gyrus (ANG.R). After ECT, patients had lower BEN levels in the PCUN.R and ANG.R. Compared with before ECT, patients showed significantly increased RSFC after ECT between the PCUN.R and right middle temporal gyrus and ANG.R. Significantly increased RSFC was observed between the ANG.R and right middle frontal gyrus and right supramarginal gyrus after ECT.

CONCLUSION

Combining the linear and nonlinear characteristics of brain signals can effectively explore the pathogenesis of depression and provide new targets for ECT.

Abnormal characteristic static and dynamic functional network connectivity in idiopathic normal pressure hydrocephalus

AIMS

Idiopathic Normal pressure hydrocephalus (iNPH) is a neurodegenerative disease characterized by gait disturbance, dementia, and urinary dysfunction. The neural network mechanisms underlying this phenomenon is currently unknown.

METHODS

To investigate the resting-state functional connectivity (rs-FC) abnormalities of iNPH-related brain connectivity from static and dynamic perspectives and the correlation of these abnormalities with clinical symptoms before and 3-month after shunt. We investigated both static and dynamic functional network connectivity (sFNC and dFNC, respectively) in 33 iNPH patients and 23 healthy controls (HCs).

RESULTS

The sFNC and dFNC of networks were generally decreased in iNPH patients. The reduction in sFNC within the default mode network (DMN) and between the somatomotor network (SMN) and visual network (VN) were related to symptoms. The temporal properties of dFNC and its temporal variability in state-4 were sensitive to the identification of iNPH and were correlated with symptoms. The temporal variability in the dorsal attention network (DAN) increased, and the average instantaneous FC was altered among networks in iNPH. These features were partially associated with clinical symptoms.

CONCLUSION

The dFNC may be a more sensitive biomarker for altered network function in iNPH, providing us with extra information on the mechanisms of iNPH.

Ketamine-induced 1-Hz oscillation of spontaneous neural activity is not directly visible in the hemodynamics

The extent to which resting-state hemodynamics reflects the underlying neural activity is still under debate. Especially in the delta frequency band (0.5-4 Hz), it is unclear whether the hemodynamics can directly track the dynamics of underlying neural activity. Based on a recent report showing that ketamine administration induced a 1-Hz neural activity oscillation in the retrosplenial cortex, we conducted simultaneous recordings of the calcium signal and hemodynamics in mice and examined whether the hemodynamics tracked the oscillatory neural activity. Although we observed that the oscillation induced by ketamine appeared in the calcium signal, no sign of oscillation was detected in the simultaneously recorded hemodynamics. Consistently, there was a notable decrease in the correlation between simultaneously recorded calcium signal and hemodynamics. However, on a much longer time scale (10-60 min), we unexpectedly observed an ultraslow increase of hemodynamic signals specifically in the same cortical region exhibiting the neural activity oscillation. These results indicated that hemodynamics cannot track the 1-Hz oscillation in neural activity, although the presence of neural activity oscillation was detectable on a longer timescale. Such ultraslow hemodynamics may be useful for detecting abnormal neural activity induced by psychotic drugs or mental disorders.

Interactions across emotional, cognitive and subcortical motor networks underlying freezing of gait

Freezing of gait (FOG) is a gait disorder affecting patients with Parkinson's disease (PD) and related disorders. The pathophysiology of FOG is unclear because of its phenomenological complexity involving motor, cognitive, and emotional aspects of behavior. Here we used resting-state functional MRI to retrieve functional connectivity (FC) correlated with the New FOG questionnaire (NFOGQ) reflecting severity of FOG in 67 patients with PD. NFOGQ scores were correlated with FCs in the extended basal ganglia network (BGN) involving the striatum and amygdala, and in the extra-cerebellum network (CBLN) involving the frontoparietal network (FPN). These FCs represented interactions across the emotional (amygdala), subcortical motor (BGN and CBLN), and cognitive networks (FPN). Using these FCs as features, we constructed statistical models that explained 40% of the inter-individual variances of FOG severity and that discriminated between PD patients with and without FOG. The amygdala, which connects to the subcortical motor (BGN and CBLN) and cognitive (FPN) networks, may have a pivotal role in interactions across the emotional, cognitive, and subcortical motor networks. Future refinement of the machine learning-based classifier using FCs may clarify the complex pathophysiology of FOG further and help diagnose and evaluate FOG in clinical settings.

Maternal psychological distress associates with alterations in resting-state low-frequency fluctuations and distal functional connectivity of the neonate medial prefrontal cortex

Prenatal stress exposure (PSE) has been observed to exert a programming effect on the developing infant brain, possibly with long-lasting consequences on temperament, cognitive functions and the risk for developing psychiatric disorders. Several prior studies have revealed that PSE associates with alterations in neonate functional connectivity in the prefrontal regions and amygdala. In this study, we explored whether maternal psychological symptoms measured during the 24th gestational week had associations with neonate resting-state network metrics. Twenty-one neonates (nine female) underwent resting-state fMRI scanning (mean gestation-corrected age at scan 26.95 days) to assess fractional amplitude of low-frequency fluctuation (fALFF) and regional homogeneity (ReHo). The ReHo/fALFF maps were used in multiple regression analysis to investigate whether maternal self-reported anxiety and/or depressive symptoms associate with neonate functional brain features. Maternal psychological distress (composite score of depressive and anxiety symptoms) was positively associated with fALFF in the neonate medial prefrontal cortex (mPFC). Anxiety and depressive symptoms, assessed separately, exhibited similar but weaker associations. Post hoc seed-based connectivity analyses further showed that distal connectivity of mPFC covaried with PSE. No associations were found between neonate ReHo and PSE. These results offer preliminary evidence that PSE may affect functional features of the developing brain during gestation.

Abnormal amplitude of low-frequency fluctuation values as a neuroimaging biomarker for major depressive disorder with suicidal attempts in adolescents: A resting-state fMRI and support vector machine analysis

Objective

Major depressive disorder (MDD) is associated with suicidal attempts (SAs) among adolescents, with suicide being the most common cause of mortality in this age group. This study explored the predictive utility of support vector machine (SVM)-based analyses of amplitude of low-frequency fluctuation (ALFF) results as a neuroimaging biomarker for aiding the diagnosis of MDD with SA in adolescents.

Methods

Resting-state functional magnetic resonance imaging (rs-fMRI) analyses of 71 first-episode, drug-naive adolescent MDD patients with SA and 54 healthy control individuals were conducted. ALFF and SVM methods were used to analyze the imaging data.

Results

Relative to healthy control individuals, adolescent MDD patients with a history of SAs showed reduced ALFF values in the bilateral medial superior frontal gyrus (mSFG) and bilateral precuneus. These lower ALFF values were also negatively correlated with child depression inventory (CDI) scores while reduced bilateral precuneus ALFF values were negatively correlated with Suicidal Ideation Questionnaire Junior (SIQ-JR) scores. SVM analyses showed that reduced ALFF values in the bilateral mSFG and bilateral precuneus had diagnostic accuracy levels of 76.8% (96/125) and 82.4% (103/125), respectively.

Conclusion

Adolescent MDD patients with a history of SA exhibited abnormal ALFF. The identified abnormalities in specific brain regions may be involved in the pathogenesis of this condition and may help identify at-risk adolescents. Specifically, reductions in the ALFF in the bilateral mSFG and bilateral precuneus may be indicative of MDD and SA in adolescent patients.

Altered functional connectivity in common resting-state networks in patients with major depressive disorder: A resting-state functional connectivity study

The neural correlates of major depressive disorder (MDD) remain disputed. In the absence of reliable biological markers, the dysfunction and interaction of neural networks have been proposed as pathophysiological neural mechanisms in depression. Here, we examined the functional connectivity (FC) of brain networks. 51 healthy volunteers (mean age 33.57 ± 7.80) and 55 individuals diagnosed with MDD (mean age 33.89 ± 11.00) participated by performing a resting-state (rs) fMRI scan. Seed to voxel FC analyses were performed. Compared to healthy control (HC), MDD patients showed higher connectivity between the hippocampus and the anterior cingulate cortex (ACC) and lower connectivity between the insula and the ACC. The MDD group displayed lower connectivity between the inferior parietal lobule (IPL) and the superior frontal gyrus (SFG). The current data replicate previous findings regarding the cortico-limbic network (hippocampus - ACC connection) and the salience network (insula - ACC connection) and provide novel insight into altered rsFC in MDD, in particular involving the hippocampus - ACC and the insula - ACC connection. Furthermore, altered connectivity between the IPL and SFG indicates that the processing in higher cognitive processes such as attention and working memory is affected in MDD. These data further support dysfunctional neuronal networks as an interesting pathophysiological marker in depression.

Regional amplitude abnormities in the major depressive disorder: A resting-state fMRI study and support vector machine analysis

PURPOSE

Major depressive disorder (MDD) is a common mood disorder. However, it still remains challenging to select sensitive biomarkers and establish reliable diagnosis methods currently. This study aimed to investigate the abnormalities of the spontaneous brain activity in the MDD and explore the clinical diagnostic value of three amplitude metrics in altered regions by applying the support vector machine (SVM) method.

METHODS

A total of fifty-two HCs and forty-eight MDD patients were recruited in the study. The amplitude of low-frequency fluctuation (ALFF), fractional amplitude of low-frequency fluctuation (fALFF) and percent amplitude of fluctuation (PerAF) metrics were calculated to assess local spontaneous brain activity. Then we performed correlation analysis to examine the association between cerebral abnormalities and clinical characteristics. Finally, SVM analysis was applied to conduct the classification model for evaluating the diagnostic value.

RESULTS

Two-sample t-test exhibited that MDD patients had increased ALFF value in the right caudate and corpus callosum, increased fALFF value in the same regions and increased PerAF value in the inferior parietal lobule and right caudate compared to HCs. Moreover, PerAF value in the inferior parietal lobule was negatively correlated with the slow factor scores. The SVM results showed that a combination of mean ALFF and fALFF in the right caudate and corpus callosum selected as features achieved a highest area under curve (AUC) value (0.89), accuracy (79.79%), sensitivity (65.12%) and specificity (92.16%).

CONCLUSION

Collectively, we found increased mean ALFF and fALFF may serve as a potential neuroimaging marker to discriminate MDD and HCs.

Multi-centre classification of functional neurological disorders based on resting-state functional connectivity

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Using machine learning on multi-centre data, FND patients were successfully classified with an accuracy of 72%.

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The angular- and supramarginal gyri, cingular- and insular cortex, and the hippocampus were the most discriminant regions.

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To provide diagnostic utility, future studies must include patients with similar symptoms but different diagnoses.

Background

Patients suffering from functional neurological disorder (FND) experience disabling neurological symptoms not caused by an underlying classical neurological disease (such as stroke or multiple sclerosis). The diagnosis is made based on reliable positive clinical signs, but clinicians often require additional time- and cost consuming medical tests and examinations. Resting-state functional connectivity (RS FC) showed its potential as an imaging-based adjunctive biomarker to help distinguish patients from healthy controls and could represent a “rule-in” procedure to assist in the diagnostic process. However, the use of RS FC depends on its applicability in a multi-centre setting, which is particularly susceptible to inter-scanner variability. The aim of this study was to test the robustness of a classification approach based on RS FC in a multi-centre setting.

Methods

This study aimed to distinguish 86 FND patients from 86 healthy controls acquired in four different centres using a multivariate machine learning approach based on whole-brain resting-state functional connectivity. First, previously published results were replicated in each centre individually (intra-centre cross-validation) and its robustness across inter-scanner variability was assessed by pooling all the data (pooled cross-validation). Second, we evaluated the generalizability of the method by using data from each centre once as a test set, and the data from the remaining centres as a training set (inter-centre cross-validation).

Results

FND patients were successfully distinguished from healthy controls in the replication step (accuracy of 74%) as well as in each individual additional centre (accuracies of 73%, 71% and 70%). The pooled cross validation confirmed that the classifier was robust with an accuracy of 72%. The results survived post-hoc adjustment for anxiety, depression, psychotropic medication intake, and symptom severity. The most discriminant features involved the angular- and supramarginal gyri, sensorimotor cortex, cingular- and insular cortex, and hippocampal regions. The inter-centre validation step did not exceed chance level (accuracy below 50%).

Conclusions

The results demonstrate the applicability of RS FC to correctly distinguish FND patients from healthy controls in different centres and its robustness against inter-scanner variability. In order to generalize its use across different centres and aim for clinical application, future studies should work towards optimization of acquisition parameters and include neurological and psychiatric control groups presenting with similar symptoms.

The Curative Effect of Pregabalin in the Treatment of Postherpetic Neuralgia Analyzed by Deep Learning-Based Brain Resting-State Functional Magnetic Resonance Images

This work aimed to investigate the brain resting-state functional magnetic resonance imaging (fMRI) technology based on the depth autoencoders algorithm and to evaluate the clinically curative effect of pregabalin in the treatment of postherpetic neuralgia (PHN). In this study, 40 patients with PHN were selected and rolled randomly into a treatment group and a control group (20 cases in each group). Then, a depth autoencoders algorithm was constructed and applied in the brain resting-state fMRI technology. The brains of 40 patients with PHN treated with pregabalin were scanned, and the time curve extracted from MRI images was convolved by linear drift removal bandpass filtering to reduce low-frequency drift and high-frequency noise, so the low-frequency amplitude was calculated. Based on the low-frequency amplitude method, the calculated low-frequency signal energy was eventually divided by the total power of the entire frequency band to obtain the low-frequency amplitude rate value. The amplitude of low-frequency fluctuation (ALFF) and fractional ALFF (f-ALFF) before and after treatment were compared between the treatment group and the control group, and the visual analog scale (VAS) after treatment was also observed. After 4 weeks of taking the drug, the VAS scores of patients from the treatment group in the first week (6.5 ± 0.8 points), the second week (6.5 ± 0.8 points), the third week (3.1 ± 0.3 points), and the fourth week (2.3 ± 0.4 points) after treatment were lower steeply than the scores before treatment (8.3 ± 1.1 points) (P < 0.05). Resting-state fMRI images showed that the f-ALFF of the 4 brain areas in the treatment group was higher than that of the control group, mainly including the bilateral frontal lobes, bilateral parietal lobes, left parietal lobes, and right posterior cerebellar lobes. Besides, the f-ALFF of the 6 brain areas in the treatment group was lower than that of the control group, mainly including the right frontal lobe, right parietal lobe, right middle frontal gyrus, precuneus, left frontal lobe, and superior frontal gyrus. In conclusion, the resting-state fMRI technology based on the depth autoencoders algorithm could efficiently display the brain area characteristic changes of patients with PHN before and after treatment, thereby providing a reference for the diagnosis of the patient's condition.

Resting-state functional nuclear magnetic resonance imaging in patients with bipolar disorder: Beyond euthymia

INTRODUCTION

Functional nuclear magnetic resonance imaging in the resting state (R-fMRI) allows the identification of complete functional connectivity networks and the possible neuronal correlations of psychiatric disorders. The literature on R-fMRI and bipolar disorder (BD) will be reviewed, emphasising the findings in the phases of mania, hypomania and depression.

METHODS

It is a narrative review of the literature in which articles were searched in PubMed and Embase, with the key words in English "bipolar disorder" AND "resting state", without limit on the date of publication.

RESULTS

The studies of BD patients in the mania and hypomania phases who underwent R-fMRI show concordant results in terms of decreased functional cerebral connectivity between the amygdala and some cortical regions, which indicates that this functional connection would have some implication in the normal affect regulation. Patients in the depressive phase show a decrease in functional brain connectivity, but as there are several anatomical structures involved and neural networks reported in the studies, it is not possible to compare them.

CONCLUSIONS

There is a decrease in functional connectivity in patients with BD, but current evidence does not allow establishing specific changes in specific functional brain connectivity networks. However, there are already some findings that show correlation with the patients' symptoms.

Common and specific patterns of functional and structural brain alterations in schizophrenia and bipolar disorder: a multimodal voxel-based meta-analysis

BACKGROUND

Schizophrenia and bipolar disorder have been linked to alterations in the functional activity and grey matter volume of some brain areas, reflected in impaired regional homogeneity and aberrant voxel-based morphometry. However, because of variable findings and methods used across studies, identifying patterns of brain alteration in schizophrenia and bipolar disorder has been difficult.

METHODS

We conducted a meta-analysis of differences in regional homogeneity and voxel-based morphometry between patients and healthy controls for schizophrenia and bipolar disorder separately, using seed-based d mapping.

RESULTS

We included 45 publications on regional homogeneity (26 in schizophrenia and 19 in bipolar disorder) and 190 publications on voxel-based morphometry (120 in schizophrenia and 70 in bipolar disorder). Patients with schizophrenia showed increased regional homogeneity in the frontal cortex and striatum and the supplementary motor area; they showed decreased regional homogeneity in the insula, primary sensory cortex (visual and auditory cortices) and sensorimotor cortex. Patients with bipolar disorder showed increased regional homogeneity in the frontal cortex and striatum; they showed decreased regional homogeneity in the insula. Patients with schizophrenia showed decreased grey matter volume in the superior temporal gyrus, inferior frontal gyrus, cingulate cortex and cerebellum. Patients with bipolar disorder showed decreased grey matter volume in the insula, cingulate cortex, frontal cortex and thalamus. Overlap analysis showed that patients with schizophrenia displayed decreased regional homogeneity and grey matter volume in the left insula and left superior temporal gyrus; patients with bipolar disorder displayed decreased regional homogeneity and grey matter volume in the left insula.

LIMITATIONS

The small sample size for our subgroup analysis (unmedicated versus medicated patients and substantial heterogeneity in the results for some regions could limit the interpretability and generalizability of the results.

CONCLUSION

Patients with schizophrenia and bipolar disorder shared a common pattern of regional functional and structural alterations in the insula and frontal cortex. Patients with schizophrenia showed more widespread functional and structural impairment, most prominently in the primary sensory motor areas.

Weaker connectivity in resting state networks is associated with disinhibited eating in older adults

Background/objectives

Obesity affects more than forty percent of adults over the age of sixty. Aberrant eating styles such as disinhibition have been associated with the engagement of brain networks underlying executive functioning, attentional control, and interoception. However, these effects have been exclusively studied in young samples overlooking those most at risk of obesity related harm.

Methods

Here we assessed associations between resting-state functional connectivity and disinhibited eating (using the Three Factor Eating Questionnaire) in twenty-one younger (aged 19–34 years, BMI range: 18–31) and twenty older (aged 60–73 years, BMI range: 19–32) adults matched for BMI. The Alternative Healthy Eating Index was used to quantify diet quality.

Results

Older, compared to younger, individuals reported lower levels of disinhibited eating, consumed a healthier diet, and had weaker connectivity in the frontoparietal (FPN) and default mode (DMN) networks. In addition, associations between functional connectivity and eating behaviour differed between the two age groups. In older adults, disinhibited eating was associated with weaker connectivity in the FPN and DMN––effects that were absent in the younger sample. Importantly, these effects could not be explained by differences in habitual diet.

Conclusions

These findings point to a change in interoceptive signalling as part of the ageing process, which may contribute to behavioural changes in energy intake, and highlight the importance of studying this under researched population.

It Is Time to Study Overlapping Molecular and Circuit Pathophysiologies in Alzheimer's and Lewy Body Disease Spectra

Alzheimer's disease (AD) is the leading cause of dementia due to neurodegeneration and is characterized by extracellular senile plaques composed of amyloid β1 - 42 (Aβ) as well as intracellular neurofibrillary tangles consisting of phosphorylated tau (p-tau). Dementia with Lewy bodies constitutes a continuous spectrum with Parkinson's disease, collectively termed Lewy body disease (LBD). LBD is characterized by intracellular Lewy bodies containing α-synuclein (α-syn). The core clinical features of AD and LBD spectra are distinct, but the two spectra share common cognitive and behavioral symptoms. The accumulation of pathological proteins, which acquire pathogenicity through conformational changes, has long been investigated on a protein-by-protein basis. However, recent evidence suggests that interactions among these molecules may be critical to pathogenesis. For example, Aβ/tau promotes α-syn pathology, and α-syn modulates p-tau pathology. Furthermore, clinical evidence suggests that these interactions may explain the overlapping pathology between AD and LBD in molecular imaging and post-mortem studies. Additionally, a recent hypothesis points to a common mechanism of prion-like progression of these pathological proteins, via neural circuits, in both AD and LBD. This suggests a need for understanding connectomics and their alterations in AD and LBD from both pathological and functional perspectives. In AD, reduced connectivity in the default mode network is considered a hallmark of the disease. In LBD, previous studies have emphasized abnormalities in the basal ganglia and sensorimotor networks; however, these account for movement disorders only. Knowledge about network abnormalities common to AD and LBD is scarce because few previous neuroimaging studies investigated AD and LBD as a comprehensive cohort. In this paper, we review research on the distribution and interactions of pathological proteins in the brain in AD and LBD, after briefly summarizing their clinical and neuropsychological manifestations. We also describe the brain functional and connectivity changes following abnormal protein accumulation in AD and LBD. Finally, we argue for the necessity of neuroimaging studies that examine AD and LBD cases as a continuous spectrum especially from the proteinopathy and neurocircuitopathy viewpoints. The findings from such a unified AD and Parkinson's disease (PD) cohort study should provide a new comprehensive perspective and key data for guiding disease modification therapies targeting the pathological proteins in AD and LBD.

Progress of Acupuncture Therapy in Diseases Based on Magnetic Resonance Image Studies: A Literature Review

The neural mechanisms of acupuncture are not well-understood. Over the past decades, an increasing number of studies have used MRI to investigate the response of the brain to acupuncture. The current review aims to provide an update on acupuncture therapy in disease. The PubMed, Embase, Web of Science, and Cochrane Library databases were searched from inception to January 31, 2021. Article selection and data extraction were conducted by two review authors. A total of 107 publications about MRI in acupuncture were included, the collective findings of which were as follows: (1) stroke and GB34 (Yanglingquan) are the most studied disease and acupoint. Related studies suggested that the mechanism of acupuncture treatment for stroke may associate with structural and functional plasticity, left and right hemispheres balance, and activation of brain areas related to movement and cognition. GB34 is mainly used in stroke and Parkinson's disease, which mainly activates brain response in the premotor cortex, the supplementary motor area, and the supramarginal gyrus; (2) resting-state functional MRI (rs-fMRI) and functional connectivity (FC) analysis are the most frequently used approaches; (3) estimates of efficacy and brain response to acupuncture depend on the type of sham acupuncture (SA) used for comparison. Brain processing after acupuncture differs between patients and health controls (HC) and occurs mainly in disorder-related areas. Factors that influence the effect of acupuncture include depth of needling, number and locations of acupoints, and deqi and expectation effect, each contributing to the brain response. While studies using MRI have increased understanding of the mechanism underlying the effects of acupuncture, there is scope for development in this field. Due to the small sample sizes, heterogeneous study designs, and analytical methods, the results were inconsistent. Further studies with larger sample sizes, careful experimental design, multimodal neuroimaging techniques, and standardized methods should be conducted to better explain the efficacy and specificity of acupuncture, and to prepare for accurate efficacy prediction in the future.

Increased attentional network activity in premature ejaculation patients with anxiety revealed by resting-state functional magnetic resonance imaging

Psychological account hypothesizes that premature ejaculation (PE) is a learned pattern of rapid ejaculation maintained by anxiety about sexual failure, whereas neuropsychological accounts hypothesizes that PE is the result of dysfunction of central nervous system regulating ejaculatory. However, the central neural mechanism underlying PE patients with anxiety remains unclear. Resting-state functional magnetic resonance imaging (fMRI) data were collected in 20 PE (diagnoses based on PE Guidelines drafted by the International Society for Sexual Medicine [ISSM]) patients with anxiety and 25 matched healthy controls (HCs) from January 2019 to December 2020. The values of fractional amplitude of low-frequency fluctuation (fALFF) were compared between groups. Moreover, the correlations between fALFF and the severity of PE and anxiety of patients were examined. PE patients with anxiety had increased fALFF values in the right inferior frontal gyrus (opercular part) and middle frontal gyrus. In addition, significant positive correlations were found between the scores of PE diagnostic tool (PEDT) and fALFF values of the right inferior frontal gyrus (opercular part), as well as the right middle frontal gyrus. Moreover, fALFF values of the right inferior frontal gyrus (opercular part) and middle frontal gyrus were positively correlated with the scores of self-rating anxiety scale (SAS). Our results suggested that increased attentional network activity might play a critical role in the neural basis of PE patients with anxiety.

Functional Connectivity in Parkinson's Disease Patients with Mild Cognitive Impairment

Objective

To explore the alteration of pattens of anatomical and functional connectivity (FC) of posterior cingulate cortex (PCC) in Parkinson’s disease (PD) patients with cognitive dysfunction and the relationship between the connection strengths and cognitive state.

Methods

We prospectively enrolled 20 PD patients with mild cognitive impairment (PD-MCI), 13 PD patients with normal cognition (PD-NC) and 13 healthy controls (HCs). By collecting, preprocessing and FC analyzing resting-state functional magnetic resonance imaging (rs-fMRI) data, we extracted default mode network (DMN) patterns, compared the differences in DMN between the three groups and the analyzed the correlation between FC value with the commonly used neuropsychological testing.

Results

The PD-MCI showed significant worse performances in general cognition, and PD-NC and HCs showed comparable performances of cognitive function. Cognitive-related differences in DMN were detected in the bilateral precuneus (BPcu). Compared with the HCs, PD-NC and PD-MCI showed significantly decreased FC within BPcu (both P < 0.001). For PD-MCI, the rho of the Fisher’s Z-transformed FC (zFC) value within BPcu with the TMTA, DSST and CFT-20min were 0.50, 0.66 and 0.47, respectively. For PD-NC, the rho of the zFC value within BPcu with the MMSE was 0.58.

Discussion

BPcu was the cognitive-related region in DMN. As cognition declines, FC within BPcu weakens. For PD-MCI, the higher the FC values within BPcu were likely to be related to the better the performances of TMTA, DSST and CFT-20 min DR, which needs to be further confirmed by large-sample studies.

Disrupted Spontaneous Neural Activity in Patients With Thyroid-Associated Ophthalmopathy: A Resting-State fMRI Study Using Amplitude of Low-Frequency Fluctuation

PURPOSE

The purpose of the study was to investigate the brain functional alteration in patients with thyroid-associated ophthalmopathy (TAO) by evaluating the spontaneous neural activity changes using resting-state functional magnetic resonance imaging (rs-fMRI) with the amplitude of low-frequency fluctuation (ALFF) method.

MATERIALS AND METHODS

The rs-fMRI data of 30 TAO patients (15 active and 15 inactive) and 15 healthy controls (HCs) were included for analyses. The ALFF values were calculated and compared among groups. Correlations between ALFF values and clinical metrics were assessed.

RESULTS

Compared with HCs, active TAOs showed significantly decreased ALFF values in the left middle occipital gyrus, superior occipital gyrus, and cuneus. Compared with inactive TAOs, active TAOs showed significantly increased ALFF values in the bilateral precuneus. Additionally, inactive TAOs showed significantly decreased ALFF values in the left middle occipital gyrus, superior occipital gyrus, cuneus, and bilateral precuneus than HCs. The ALFF value in the right precuneus of TAOs was positively correlated with clinical activity score (r = 0.583, P < 0.001) and Mini-Mental State Examination (MMSE) score (r = 0.377, P = 0.040), and negatively correlated with disease duration (r = -0.382, P = 0.037). Moreover, the ALFF value in the left middle occipital gyrus of TAOs was positively correlated with visual acuity (r = 0.441, P = 0.015).

CONCLUSION

TAO patients had altered spontaneous brain activities in the left occipital lobe and bilateral precuneus. The neuropsychological aspect of the disease should be noticed during clinical diagnosis and treatment.

Review of the Role of the Brain in Chemotherapy-Induced Peripheral Neuropathy

Chemotherapy-induced peripheral neuropathy (CIPN) is a common, debilitating, and dose-limiting side effect of many chemotherapy regimens yet has limited treatments due to incomplete knowledge of its pathophysiology. Research on the pathophysiology of CIPN has focused on peripheral nerves because CIPN symptoms are felt in the hands and feet. However, better understanding the role of the brain in CIPN may accelerate understanding, diagnosing, and treating CIPN. The goals of this review are to (1) investigate the role of the brain in CIPN, and (2) use this knowledge to inform future research and treatment of CIPN. We identified 16 papers using brain interventions in animal models of CIPN and five papers using brain imaging in humans or monkeys with CIPN. These studies suggest that CIPN is partly caused by (1) brain hyperactivity, (2) reduced GABAergic inhibition, (3) neuroinflammation, and (4) overactivation of GPCR/MAPK pathways. These four features were observed in several brain regions including the thalamus, periaqueductal gray, anterior cingulate cortex, somatosensory cortex, and insula. We discuss how to leverage this knowledge for future preclinical research, clinical research, and brain-based treatments for CIPN.

Dynamic functional connectivity in adolescence-onset major depression: relationships with severity and symptom dimensions

BACKGROUND

The spatial functional chronnectome is an innovative mathematical model designed to capture dynamic features in the organization of brain function derived from resting-state functional magnetic resonance imaging (rs-fMRI) data. Measurements of dynamic functional connectivity (dFC) have been developed from this model to quantify the brain dynamical self-reconfigurations at different spatial and temporal scales. This study examined whether two spatiotemporal dFC quantifications were linked to late adolescence-onset major depressive disorder (AO-MDD), and scaled with depression and symptom severity measured with the Montgomery-Asberg depression rating scale (MADRS) Methods: Thirty-five AO-MDD patients (21±6y) and fifty-three age- and gender-matched healthy young participants (20±3y) underwent 3T MRI structural and rs-fMRI acquisitions. The chronnectome here comprised seven individualized functional networks portrayed along 132 temporal overlapping windows, each framing 110s of resting brain activity Results: Based on voxelwise analyses, AO-MDD patients demonstrated significantly reduced temporal variability within the bilateral prefrontal cortex in five functional networks including the limbic network, the default-mode network (DMN) and frontoparietal network (FPN). Furthermore, the limbic network appeared to be particularly involved in this sample, and was associated with MADRS scores, and its progressive dynamic inflexibility was linked to sadness. DMN and FPN dynamics scaled with negative thoughts and neurovegetative symptoms, respectively Conclusions: This triple-network imbalance could delay spatiotemporal integration, while across-subject symptom variability would be network-specific. Therefore, the present approach supports that brain network dynamics underlie patients' symptom heterogeneity in AO-MDD.

Functional connectivity changes in cerebral small vessel disease - a systematic review of the resting-state MRI literature

BACKGROUND

Cerebral small vessel disease (CSVD) is a common neurological disease present in the ageing population that is associated with an increased risk of dementia and stroke. Damage to white matter tracts compromises the substrate for interneuronal connectivity. Analysing resting-state functional magnetic resonance imaging (fMRI) can reveal dysfunctional patterns of brain connectivity and contribute to explaining the pathophysiology of clinical phenotypes in CSVD.

MATERIALS AND METHODS

This systematic review provides an overview of methods and results of recent resting-state functional MRI studies in patients with CSVD. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) protocol, a systematic search of the literature was performed.

RESULTS

Of 493 studies that were screened, 44 reports were identified that investigated resting-state fMRI connectivity in the context of cerebral small vessel disease. The risk of bias and heterogeneity of results were moderate to high. Patterns associated with CSVD included disturbed connectivity within and between intrinsic brain networks, in particular the default mode, dorsal attention, frontoparietal control, and salience networks; decoupling of neuronal activity along an anterior-posterior axis; and increases in functional connectivity in the early stage of the disease.

CONCLUSION

The recent literature provides further evidence for a functional disconnection model of cognitive impairment in CSVD. We suggest that the salience network might play a hitherto underappreciated role in this model. Low quality of evidence and the lack of preregistered multi-centre studies remain challenges to be overcome in the future.

Prefrontal network dysfunctions in rapid eye movement sleep behavior disorder

INTRODUCTION

Resting-state functional connectivity magnetic resonance imaging (rsfcMRI) of rapid eye movement (REM) sleep behavior disorder (RBD) may provide an early biomarker of α-synucleinopathy. However, few rsfcMRI studies have examined cognitive networks. To elucidate brain network changes in RBD, we performed rsfcMRI in patients with polysomnography-confirmed RBD and healthy controls (HCs), with a sufficiently large sample size in each group.

METHODS

We analyzed rsfcMRI data from 50 RBD patients and 70 age-matched HCs. Although RBD patients showed no motor signs, some exhibited autonomic and cognitive problems. Several resting-state functional networks were extracted by group independent component analysis from HCs, including the executive-control (ECN), default-mode (DMN), basal ganglia (BGN), and sensory-motor (SMN) networks. Functional connectivity (FC) was compared between groups using dual regression analysis. In the RBD group, correlation analysis was performed between FC and clinical/cognitive scales.

RESULTS

Patients with RBD showed reduced striatal-prefrontal FC in ECN, consistent with executive dysfunctions. No abnormalities were found in DMN. In the motor networks, we identified reduced midbrain-pallidum FC in BGN and reduced motor and somatosensory cortex FC in SMN.

CONCLUSION

We found abnormal ECN and normal DMN as a possible hallmark of cognitive dysfunctions in early α-synucleinopathies. We replicated abnormalities in BGN and SMN corresponding to subclinical movement disorder of RBD. RsfcMRI may provide an early biomarker of both cognitive and motor network dysfunctions of α-synucleinopathies.

Crosstalk between Depression and Dementia with Resting-State fMRI Studies and Its Relationship with Cognitive Functioning

Alzheimer’s disease (AD) is the most common type of dementia, and depression is a risk factor for developing AD. Epidemiological studies provide a clinical correlation between late-life depression (LLD) and AD. Depression patients generally remit with no residual symptoms, but LLD patients demonstrate residual cognitive impairment. Due to the lack of effective treatments, understanding how risk factors affect the course of AD is essential to manage AD. Advances in neuroimaging, including resting-state functional MRI (fMRI), have been used to address neural systems that contribute to clinical symptoms and functional changes across various psychiatric disorders. Resting-state fMRI studies have contributed to understanding each of the two diseases, but the link between LLD and AD has not been fully elucidated. This review focuses on three crucial and well-established networks in AD and LLD and discusses the impacts on cognitive decline, clinical symptoms, and prognosis. Three networks are the (1) default mode network, (2) executive control network, and (3) salience network. The multiple properties emphasized here, relevant for the hypothesis of the linkage between LLD and AD, will be further developed by ongoing future studies.

Specific Gray Matter Volume Changes of the Brain in Unipolar and Bipolar Depression

To identify the common and specific structural basis of bipolar depression (BD) and unipolar depression (UD) is crucial for clinical diagnosis. In this study, a total of 85 participants, including 22 BD patients, 36 UD patients, and 27 healthy controls, were enrolled. A voxel-based morphology method was used to identify the common and specific changes of the gray matter volume (GMV) to determine the structural basis. Significant differences in GMV were found among the three groups. Compared with healthy controls, UD patients showed decreased GMV in the orbital part of the left inferior frontal gyrus, whereas BD patients showed decreased GMV in the orbital part of the left middle frontal gyrus. Compared with BD, UD patients have increased GMV in the left supramarginal gyrus and middle temporal gyrus. Our results revealed different structural changes in UD and BD patients suggesting BD and UD have different neurophysiological underpinnings. Our study contributes toward the biological determination of morphometric changes, which could help to discriminate between UD and BD.

Magnetic Resonance Imaging Studies on Acupuncture Therapy in Depression: A Systematic Review

Accumulating studies had been performed using magnetic resonance imaging (MRI) to understand the neural mechanism of acupuncture therapy for depression. However, inconsistencies remain due to differences in research designs and MRI analytical methods. Therefore, we aim to summarize the current MRI research and provide useful information for further research by identifying papers published in English and Chinese about MRI studies on acupuncture for depression up to November 2020. A total of 22 studies met the inclusion criteria, including 810 depression patients and 416 health controls (HCs). The applied designs of these studies are mainly random control trial and pre-post designs. The MRI analytical methods are mainly (fractional) amplitude of low-frequency fluctuation (fALFF/ALFF) and functional connectivity (FC), whereas a small subset of studies used voxel-based morphometry (VBM) and diffusion tensor imaging (DTI). The most consistent functional MRI (fMRI) results showed increased N-acetylaspartate/creatine (NAA/Cr) ratios, increased ALFF in the right precuneus, decreased ALFF in the inferior frontal gyrus (IFG), and increased FC of the anterior cingulate cortex (ACC). In contrast, no significant neurological changes were identified in any of the DTI or VBM studies. However, clear, reliable conclusions cannot be drawn due to the use of different designs, analytical methods, seed points selected, types of depression, acupuncture points, and so on. Improved report specifications, well-designed studies, consistent analytical methods, and larger sample sizes will enable the field to better elucidate the underlying mechanisms of acupuncture in depressed patients.

Resting-state functional nuclear magnetic resonance imaging in patients with bipolar disorder: beyond euthymia

INTRODUCTION

Functional nuclear magnetic resonance imaging in the resting state (R-fMRI) allows the identification of complete functional connectivity networks and the possible neuronal correlations of psychiatric disorders. The literature on R-fMRI and bipolar disorder (BD) will be reviewed, emphasising the findings in the phases of mania, hypomania and depression.

METHODS

It is a narrative review of the literature in which articles were searched in PubMed and Embase, with the key words in English "bipolar disorder" AND "resting state", without limit on the date of publication.

RESULTS

The studies of BD patients in the mania and hypomania phases who underwent R-fMRI show concordant results in terms of decreased functional cerebral connectivity between the amygdala and some cortical regions, which indicates that this functional connection would have some implication in the normal affect regulation. Patients in the depressive phase show a decrease in functional brain connectivity, but as there are several anatomical structures involved and neural networks reported in the studies, it is not possible to compare them.

CONCLUSIONS

There is a decrease in functional connectivity in patients with BD, but current evidence does not allow establishing specific changes in specific functional brain connectivity networks. However, there are already some findings that show correlation with the patients' symptoms.

QEEG coherence patterns related to mathematics ability in children

The current study investigates the utility of resting-state EEG coherence values in predicting standardized math scores in children. Quantitative EEG and standardized academic achievement analyses were performed on 60 school-aged children. Analyses assessing intrahemispheric coherence at rest were conducted across the sample of participants and several coherence networks were extracted and compared to standardized math achievement values. Specifically, networks that included Brodmann area 40 (a brain region involved in the cognitive processes responsible for mathematics performance) and whose coherence values were significantly correlated with standardized math scores were examined. Results indicate a total of four coherence networks, two in each hemisphere, that have utility in predicting general math skills in children. In addition to BA 40, these coherence networks include BAs in the right temporal lobe, right frontoparietal lobe, left superior temporal lobe, and the left medial prefrontal cortex. These findings address the current dearth of research on the neurological connectivity patterns that are foundational for mathematics abilities in children. Further, these results lay a foundation for the supplementary use of EEG in the assessment and identification practices surrounding math learning disabilities in children and additionally provide a neurocognitive framework upon which intervention research may be targeted.

Aberrant Awake Spontaneous Brain Activity in Obstructive Sleep Apnea: A Review Focused on Resting-State EEG and Resting-State fMRI

As one of the most common sleep-related respiratory disorders, obstructive sleep apnea (OSA) is characterized by excessive snoring, repetitive apnea, arousal, sleep fragmentation, and intermittent nocturnal hypoxemia. Focused on the resting-state brain imaging techniques, we reviewed the OSA-related resting-state electroencephalogram and resting-state functional magnetic resonance imaging (rsfMRI) studies. Compared with the healthy control group, patients with OSA presented increased frontal and central δ/θ powers during resting-state wakefulness, and their slow-wave activity showed a positive correlation with apnea–hypopnea index. For rsfMRI, the prefrontal cortex and insula may be the vital regions for OSA and are strongly related to the severity of the disease. Meanwhile, some large-scale brain networks, such as the default-mode network, salience network, and central executive network, play pivotal roles in the pathology of OSA. We then discussed the contribution of resting-state brain imaging as an evaluation approach for disease interventions. Finally, we briefly introduced the effects of OSA-related physiological and mental diseases and discussed some future research directions from the perspective of resting-state brain imaging.

Distinct patterns of thought mediate the link between brain functional connectomes and well-being

Ongoing thought patterns constitute important aspects of both healthy and abnormal human cognition. However, the neural mechanisms behind these daily experiences and their contribution to well-being remain a matter of debate. Here, using resting-state fMRI and retrospective thought sampling in a large neurotypical cohort (n = 211), we identified two distinct patterns of thought, broadly describing the participants' current concerns and future plans, that significantly explained variability in the individual functional connectomes. Consistent with the view that ongoing thoughts are an emergent property of multiple neural systems, network-based analysis highlighted the central importance of both unimodal and transmodal cortices in the generation of these experiences. Importantly, while state-dependent current concerns predicted better psychological health, mediating the effect of functional connectomes, trait-level future plans were related to better social health, yet with no mediatory influence. Collectively, we show that ongoing thoughts can influence the link between brain physiology and well-being.

Abnormal resting-state functional connectivity of hippocampal subfields in patients with major depressive disorder

BACKGROUND

Many studies have found that the hippocampus plays a very important role in major depressive disorder (MDD). The hippocampus can be divided into three subfields: the cornu ammonis (CA), dentate gyrus (DG) and subiculum. Each subfield of the hippocampus has a unique function and are differentially associated with the pathological mechanisms of MDD. However, no research exists to describe the resting state functional connectivity of each hippocampal subfield in MDD.

METHODS

Fifty-five patients with MDD and 25 healthy controls (HCs) matched for gender, age and years of education were obtained. A seed-based method that imposed a template on the whole brain was used to assess the resting-state functional connectivity (rsFC) of each hippocampal subfield.

RESULTS

Patients with MDD demonstrated increased connectivity in the left premotor cortex (PMC) and reduced connectivity in the right insula with the CA seed region. Increased connectivity was reported in the left orbitofrontal cortex (OFC) and left ventrolateral prefrontal cortex (vlPFC) with the DG seed region. The subiculum seed region revealed increased connectivity with the left premotor cortex (PMC), the right middle frontal gyrus (MFG), the left ventrolateral prefrontal cortex (vlPFC) and reduced connectivity with the right insula. ROC curves confirmed that the differences between groups were statistically significant.

CONCLUSION

The results suggest that the CA, DG and subiculum have significant involvement with MDD. Specifically, the abnormal functional connectivity of the CA may be related to bias of coding and integration of information in patients with MDD. The abnormal functional connectivity of the DG may be related to the impairment of working memory in patients with MDD, and the abnormal functional connectivity of the subiculum may be related to cognitive impairment and negative emotions in patients with MDD.

Methylphenidate Alters Functional Connectivity of Default Mode Network in Drug-Naive Male Adults With ADHD

Objective: This study evaluated the hypothesis that methylphenidate immediate release (MPH-IR) treatment would improve Default Mode Network (DMN) within-connectivity. Method: Resting-state functional connectivity of the main nodes of DMN was evaluated in a highly homogeneous sample of 18 drug-naive male adult participants with ADHD. Results: Comparing resting-state functional connectivity functional magnetic resonance imaging (R-fMRI) scans before and after MPH treatment focusing exclusively on within-DMN connectivity, we evidenced the strengthening of functional connectivity between two nodes of the DMN: posterior cingulate cortex (PCC) and left lateral parietal cortex (LLP). Conclusion: Our results contribute to the further understanding on how MPH affects functional connectivity within DMN of male adults with ADHD and corroborate the hypothesis of ADHD being a delayed neurodevelopmental disorder.

Common and distinct neural activities in frontoparietal network in first-episode bipolar disorder and major depressive disorder: Preliminary findings from a follow-up resting state fMRI study

BACKGROUND

It is difficult to distinguish bipolar disorder (BD) from major depressive disorder (MDD), especially with the initial depressive episode. In this study, we compared neural activities of BD and MDD patients during the first-episode (FE) to investigate common and distinct neural activities and further explore predictive indicators in the two diseases.

METHODS

FE-MDD patients were performed resting state functional magnetic resonance imaging and followed up after scanning. After follow-up, FE-MDD patients were regrouped into FE-BD and FE-MDD patients. The study included 24 FE-BD patients, 28 FE-MDD patients, and 30 age- and sex-matched healthy controls (HC) to investigate neural activities with regional homogeneity (ReHo) analysis among the 3 groups.

RESULTS

Compared to HC, FE-BD patients displayed significantly higher ReHo values in the superior frontal gyrus, the medial superior frontal gyrus within right-side cerebral hemisphere than FE-MDD patients and HC. Compared to HC, FE-BD and FE-MDD patients displayed significant decreased ReHo values in the paracentral lobule, the precuneus and the median cingulate and paracingulate gyrus within bilateral cerebral hemisphere, and the postcentral gyrus and the precentral gyrus within the right-side. FE-BD displayed significant lower ReHo values than FE-MDD patients in these regions.

LIMITATIONS

The potential effects of medicine, age, course of disease and handedness on results could not be ignored.

CONCLUSIONS

Abnormal neural activities of frontoparietal network may provide common and distinct markers to affective disorders and scientific basis for further prediction researches of affective disorders.

Abnormal resting-state regional homogeneity in unmedicated bipolar II disorder

BACKGROUND

Previous studies demonstrated that patients with bipolar disorder (BD) exhibited abnormal neural activity in multiple brain regions. However, no study has been conducted to identify regional intrinsic neural activity changes in BD II. In the present study, we used the regional homogeneity (ReHo) approach to explore the regional abnormal neural activity in bipolar II disorder METHODS: One hundred unmedicated patients with BD II depression and 100 healthy controls (HC) underwent the resting-state functional magnetic resonance imaging. The ReHo values of each voxel was calculated in the whole brain. The two-sample t-test and threshold-free cluster enhancement (TFCE) correction were applied for the ReHo analysis.

RESULTS

Compared with the HC group, the BD II group showed significantly decreased ReHo in the left orbitofrontal cortex, and increased ReHo in the right precentral gyrus, right supplementary motor area and bilateral middle occipital gyrus (P < .05, TFCE corrected).

LIMITATIONS

This study lacks the evidence of brain structural changes, and used the cross-sectional design which did not explore local alterations of remitted and manic patients.

CONCLUSION

Our findings revealed abnormal local intrinsic neural activity during resting state which may contribute to the pathophysiology of bipolar II disorder. Particularly the disrupted balance between the prefrontal cortex and primary sensorimotor regions provides evidence for the unique pathological mechanism underlying BD.

Attentional engagement increases inferior frontal gyrus activity and mutes limbic activity in pediatric bipolar disorder: Meta-analyses of fMRI studies

OBJECTIVES

Attention deficit has been shown to exist in adult and pediatric bipolar disorder across the life span. Given that emotion dysregulation is central to bipolar disorder, this study hypothesizes that emotional circuitry regions are altered along with anomalies in the attentional systems during cognitive deployment in bipolar disorder.

METHODS

An activation likelihood estimation meta-analysis of attentional activities using GingerALE software was completed for adult and pediatric bipolar disorder populations in all published studies till December 2017. The meta-analysis of all fMRI studies included a total of ten pediatric studies (comprised of pediatric bipolar disorder (PBD) and typically developing (TD) groups) and nine adult patient studies (comprised of adult bipolar disorder (ABD) and healthy control (HC) groups).

RESULTS

While engaged in attentional tasks, increased activation was seen in inferior frontal gyrus with decreased activation in limbic regions in subjects with PBD, relative to TD. Differential patterns of underactivity were also noted in the dorsal attentional system i.e., frontostriatal circuit (dorsolateral prefrontal cortex, anterior cingulate cortex, right lentiform nucleus and right globus pallidus) in PBD patients relative to the TD. However, we did not see any significant differences between the adult groups i.e., ABD vs. HC.

CONCLUSIONS

In PBD, deploying attentional system potentially improves the fronto-limbic affective circuitry function, despite impaired dorsal attentional system i.e., fronto-striatal circuitry. In contrast, these neural correlates underlying attentional engagement appeared to be not significant in adult BD.

LIMITATIONS

We examined the PBD vs. TD and the ABD vs. HC separately instead of four-way contrast (dual meta-analytic study). Also, attentional tasks were not unidimensional and tend to capture selective and sustained attention along with response inhibition, thereby recruiting multiple brain circuits.

Resting state connectivity best predicts alcohol use severity in moderate to heavy alcohol users

BACKGROUND

In the United States, 13% of adults are estimated to have alcohol use disorder (AUD). Most studies examining the neurobiology of AUD treat individuals with this disorder as a homogeneous group; however, the theories of the neurocircuitry of AUD call for a quantitative and dimensional approach. Previous imaging studies find differences in brain structure, function, and resting-state connectivity in AUD, but few use a multimodal approach to understand the association between severity of alcohol use and the brain differences.

METHODS

Adults (ages 22-60) with problem drinking patterns (n = 59) completed a behavioral and neuroimaging protocol at the National Institutes of Health. Alcohol severity was quantified with the Alcohol Use Disorders Identification Test (AUDIT). In a 3 T MRI scanner, participants underwent a structural MRI as well as resting-state, monetary incentive delay, and face matching fMRI scans. Machine learning was applied and trained using the neural data from MRI scanning. The model was tested for generalizability in a validation sample (n = 24).

RESULTS

The resting state-connectivity features model best predicted AUD severity in the naïve sample, compared to task fMRI, structural MRI, combined MRI features, or demographic features. Network connectivity features between salience network, default mode network, executive control network, and sensory networks explained 33% of the variance associated with AUDIT in this model.

CONCLUSIONS

These findings indicate that the neural effects of AUD vary according to severity. Our results emphasize the utility of resting state fMRI as a neuroimaging biomarker for quantitative clinical evaluation of AUD.

Towards artificial intelligence in mental health by improving schizophrenia prediction with multiple brain parcellation ensemble-learning

In the literature, there are substantial machine learning attempts to classify schizophrenia based on alterations in resting-state (RS) brain patterns using functional magnetic resonance imaging (fMRI). Most earlier studies modelled patients undergoing treatment, entailing confounding with drug effects on brain activity, and making them less applicable to real-world diagnosis at the point of first medical contact. Further, most studies with classification accuracies >80% are based on small sample datasets, which may be insufficient to capture the heterogeneity of schizophrenia, limiting generalization to unseen cases. In this study, we used RS fMRI data collected from a cohort of antipsychotic drug treatment-naive patients meeting DSM IV criteria for schizophrenia (N = 81) as well as age- and sex-matched healthy controls (N = 93). We present an ensemble model -- EMPaSchiz (read as ‘Emphasis’; standing for ‘Ensemble algorithm with Multiple Parcellations for Schizophrenia prediction’) that stacks predictions from several ‘single-source’ models, each based on features of regional activity and functional connectivity, over a range of different a priori parcellation schemes. EMPaSchiz yielded a classification accuracy of 87% (vs. chance accuracy of 53%), which out-performs earlier machine learning models built for diagnosing schizophrenia using RS fMRI measures modelled on large samples (N > 100). To our knowledge, EMPaSchiz is first to be reported that has been trained and validated exclusively on data from drug-naive patients diagnosed with schizophrenia. The method relies on a single modality of MRI acquisition and can be readily scaled-up without needing to rebuild parcellation maps from incoming training images.

Reduced Interhemispheric Functional Connectivity in Obsessive-Compulsive Disorder Patients

Background: Neuroimaging studies have shown that the high synchrony of spontaneous neural activity in the homotopic regions between hemispheres is an important functional structural feature of normal human brains, and this feature is abnormal in the patients with various mental disorders. However, little is known about this feature in obsessive-compulsive disorder (OCD). This study aimed to further analyze the underlying neural mechanisms of OCD and to explore whether clinical characteristics are correlated with the alerted homotopic connectivity in patients with OCD. Methods: Using voxel-mirrored homotopic connectivity (VMHC) during resting state, we compared 46 OCD patients and 46 healthy controls (HCs) matched for age, gender, and education level. A partial correlation analysis was used to investigate the relationship between altered VMHC and clinical characteristics in patients with OCD. Results: Patients with OCD showed lower VMHC than HCs in fusiform gyrus/inferior occipital gyrus, lingual gyrus, postcentral gyrus/precentral gyrus, putamen, and orbital frontal gyrus. A significant positive correlation was observed between altered VMHC in the angular gyrus/middle occipital gyrus and illness duration in patients. Conclusions: Interhemispheric functional imbalance may be an essential aspect of the pathophysiological mechanism of OCD, which is reflected not only in the cortico-striato-thalamo-cortical (CSTC) loop but also elsewhere in the brain.

Increased Alcohol Seeking in Mice Lacking Gpr88 Involves Dysfunctional Mesocorticolimbic Networks

BACKGOUND

Alcohol use disorder (AUD) is devastating and poorly treated, and innovative targets are actively sought for prevention and treatment. The orphan G protein-coupled receptor GPR88 is enriched in mesocorticolimbic pathways, and Gpr88 knockout mice show hyperactivity and risk-taking behavior, but a potential role for this receptor in drug abuse has not been examined.

METHODS

We tested Gpr88 knockout mice for alcohol-drinking and -seeking behaviors. To gain system-level understanding of their alcohol endophenotype, we also analyzed whole-brain functional connectivity in naïve mice using resting-state functional magnetic resonance imaging.

RESULTS

Gpr88 knockout mice showed increased voluntary alcohol drinking at both moderate and excessive levels, with intact alcohol sedation and metabolism. Mutant mice also showed increased operant responding and motivation for alcohol, while food and chocolate operant self-administration were unchanged. Alcohol place conditioning and alcohol-induced dopamine release in the nucleus accumbens were decreased, suggesting reduced alcohol reward in mutant mice that may partly explain enhanced alcohol drinking. Seed-based voxelwise functional connectivity analysis revealed significant remodeling of mesocorticolimbic centers, whose hallmark was predominant weakening of prefrontal cortex, ventral tegmental area, and amygdala connectional patterns. Also, effective connectivity from the ventral tegmental area to the nucleus accumbens and amygdala was reduced.

CONCLUSIONS

Gpr88 deletion disrupts executive, reward, and emotional networks in a configuration that reduces alcohol reward and promotes alcohol seeking and drinking. The functional connectivity signature is reminiscent of alterations observed in individuals at risk for AUD. The Gpr88 gene, therefore, may represent a vulnerability/resilience factor for AUD, and a potential drug target for AUD treatment.

Possible Biological Mechanisms Linking Mental Health and Heat-A Contemplative Review

This review provides examples of possible biological mechanisms that could, at least partly, explain the existing epidemiological evidence of heatwave-related exacerbation of mental disease morbidity. The author reviews the complicated central processes involved in the challenge of maintaining a stable body temperature in hot environments, and the maladaptive effects of certain psychiatric medicines on thermoregulation. In addition, the author discusses some alternative mechanisms, such as interrupted functional brain connectivity and the effect of disrupted sleep, which may further increase the vulnerability of mental health patients during heatwaves.

Hypersynchrony in MEG spectral amplitude in prospectively-identified 6-month-old infants prenatally exposed to alcohol

Early identification of children who experience developmental delays due to prenatal alcohol exposure (PAE) remains a challenge for individuals who do not exhibit facial dysmorphia. It is well-established that children with PAE may still exhibit the cognitive and behavioral difficulties, and individuals without facial dysmorphia make up the majority of individuals affected by PAE. This study employed a prospective cohort design to capture alcohol consumption patterns during pregnancy and then followed the infants to 6 months of age. Infants were assessed using magnetoencephalography to capture neurophysiological indicators of brain development and the Bayley Scales of Infant Development-III to measure behavioral development. To account for socioeconomic and family environmental factors, we employed a two-by-two design with pregnant women who were or were not using opioid maintenance therapy (OMT) and did or did not consume alcohol during pregnancy. Based on prior studies, we hypothesized that infants with PAE would exhibit broad increased spectral amplitude relative to non-PAE infants. We also hypothesized that the developmental shift from low to high frequency spectral amplitude would be delayed in infants with PAE relative to controls. Our results demonstrated broadband increased spectral amplitude, interpreted as hypersynchrony, in PAE infants with no significant interaction with OMT. Unlike prior EEG studies in neonates, our results indicate that this hypersynchrony was highly lateralized to left hemisphere and primarily focused in temporal/lateral frontal regions. Furthermore, there was a significant positive correlation between estimated number of drinks consumed during pregnancy and spectral amplitude revealing a dose-response effect of increased hypersynchrony corresponding to greater alcohol consumption. Contrary to our second hypothesis, we did not see a significant group difference in the contribution of low frequency to high frequency amplitude at 6 months of age. These results provide new evidence that hypersynchrony, previously observed in neonates prenatally exposed to high levels of alcohol, persists until 6 months of age and this measure is detectable with low to moderate exposure of alcohol with a dose-response effect. These results indicate that hypersynchrony may provide a sensitive early marker of prenatal alcohol exposure in infants up to 6 months of age.

Effects of Field-Map Distortion Correction on Resting State Functional Connectivity MRI

Magnetic field inhomogeneities cause geometric distortions of echo planar images used for functional magnetic resonance imaging (fMRI). To reduce this problem, distortion correction (DC) with field map is widely used for both task and resting-state fMRI (rs-fMRI). Although DC with field map has been reported to improve the quality of task fMRI, little is known about its effects on rs-fMRI. Here, we tested the influence of field-map DC on rs-fMRI results using two rs-fMRI datasets derived from 40 healthy subjects: one with DC (DC+) and the other without correction (DC−). Independent component analysis followed by the dual regression approach was used for evaluation of resting-state functional connectivity networks (RSN). We also obtained the ratio of low-frequency to high-frequency signal power (0.01–0.1 Hz and above 0.1 Hz, respectively; LFHF ratio) to assess the quality of rs-fMRI signals. For comparison of RSN between DC+ and DC− datasets, the default mode network showed more robust functional connectivity in the DC+ dataset than the DC− dataset. Basal ganglia RSN showed some decreases in functional connectivity primarily in white matter, indicating imperfect registration/normalization without DC. Supplementary seed-based and simulation analyses supported the utility of DC. Furthermore, we found a higher LFHF ratio after field map correction in the anterior cingulate cortex, posterior cingulate cortex, ventral striatum, and cerebellum. In conclusion, field map DC improved detection of functional connectivity derived from low-frequency rs-fMRI signals. We encourage researchers to include a DC step in the preprocessing pipeline of rs-fMRI analysis.

Interhemispheric Resting-State Functional Connectivity Predicts Severity of Idiopathic Normal Pressure Hydrocephalus

Idiopathic normal pressure hydrocephalus (iNPH) is characterized by a clinical triad (gait disturbance, dementia, and urinary incontinence), and by radiological findings of enlarged ventricles reflecting disturbance of central spinal fluid circulation. A diagnosis of iNPH is sometimes challenging, and the pathophysiological mechanisms underlying the clinical symptoms of iNPH remain largely unknown. Here, we used an emerging MRI technique, resting-state functional connectivity MRI (rsfcMRI), to develop a subsidiary diagnostic technique and to explore the underlying pathophysiological mechanisms of iNPH. rsfcMRI data were obtained from 11 patients with iNPH and 11 age-matched healthy volunteers, yielding rsfcMRI-derived functional connectivity (FC) from both groups. A linear support vector machine classifier was trained to distinguish the patterns of FCs of the patients with iNPH from those of the healthy volunteers. After dimensional reduction, the support vector machine successfully classified the two groups with an accuracy of 80%. Moreover, we found that rsfcMRI-derived FC carried information to predict the severity of the triad in iNPH. FCs relevant to the classification of severity were mainly based on interhemispheric connectivity, suggesting that disruption of the corpus callosum fibers due to ventricular enlargement may explain the triad of iNPH. The present results support the usefulness of rsfcMRI as a tool to understand pathophysiology of iNPH, and also to help with its clinical diagnosis.