Most recent paper

Cerebellum. 2021 Aug 25. doi: 10.1007/s12311-021-01317-9. Online ahead of print.

ABSTRACT

Bipolar disorder (BD) is a major mental illness characterized by periods of (hypo) mania and depression with inter-episode remission periods. Functional studies in BD have consistently implicated a set of linked cortical and subcortical limbic regions in the pathophysiology of the disorder, also including the cerebellum. However, the cerebellar role in the neurobiology of BD still needs to be clarified. Seventeen euthymic patients with BD type1 (BD1) (mean age/SD, 38.64/13.48; M/F, 9/8) and 13 euthymic patients with BD type 2 (BD2) (mean age/SD, 41.42/14.38; M/F, 6/7) were compared with 37 sex- and age-matched healthy subjects (HS) (mean age/SD, 45.65/14.15; M/F, 15/22). T1 weighted and resting-state functional connectivity (FC) scans were acquired. The left and right dentate nucleus were used as seed regions for the seed based analysis. FC between each seed and the rest of the brain was compared between patients and HS. Correlations between altered cerebello-cerebral connectivity and clinical scores were then investigated. Different patterns of altered dentate-cerebral connectivity were found in BD1 and BD2. Overall, impaired dentate-cerebral connectivity involved regions of the anterior limbic network specifically related to the (hypo)manic states of BD. Cerebello-cerebral connectivity is altered in BD1 and BD2. Interestingly, the fact that these altered FC patterns persist during euthymia, supports the hypothesis that cerebello-cerebral FC changes reflect the neural correlate of subthreshold symptoms, as trait-based pathophysiology and/or compensatory mechanism to maintain a state of euthymia.

PMID:34432230 | DOI:10.1007/s12311-021-01317-9

Sleep. 2021 Aug 25:zsab209. doi: 10.1093/sleep/zsab209. Online ahead of print.

ABSTRACT

STUDY OBJECTIVES: Previous functional MRI studies have reported altered brain networks in patients with obstructive sleep apnea (OSA). However, the extent and pattern of abnormal connectivity were inconsistent across studies, and cerebrocerebellar connections have been rarely assessed. We investigated functional network changes in cerebral and cerebellar cortices of OSA patients.

METHODS: Resting-state functional MRI, polysomnography and neuropsychological (NP) test data were acquired from 74 OSA patients (age: 45.8±10.7 years) and 33 healthy subjects (39.6±9.3 years). Connectivity matrices were extracted by computing correlation coefficients from various ROIs, and Fisher r-to-z transformations. In the functional connections that showed significant group differences, linear regression was conducted to examine the association between connectivity and clinical characteristics.

RESULTS: Patients with OSA showed reduced functional connectivity (FC) in cerebrocerebellar connections linking different functional networks, and greater FC in cortical between-network connections in prefrontal regions involving the default mode network and the control network. For OSA group, we found no correlation between FC and sleep parameters including lowest SaO2 and arousal index in the connections where significant associations were observed in healthy subjects. FC changes in default mode network (DMN) areas were related to reduced verbal fluency in OSA. Lower local efficiency and lower clustering coefficient of the salience network in the left cerebellum were also observed in OSA.

CONCLUSIONS: OSA affects mainly the cerebrocerebellar pathway. The disruption of function in these connections are related to sleep fragmentation and hypoxia during sleep. These abnormal network functions, especially DMN, are suggested to participate in cognitive decline of OSA.

PMID:34432059 | DOI:10.1093/sleep/zsab209

Anat Rec (Hoboken). 2021 Aug 25. doi: 10.1002/ar.24746. Online ahead of print.

ABSTRACT

This study aimed to explore the changes in functional connections between cerebral hemispheres and local brain regions functional activities in patients with acute ischemic stroke (AIS) treated with International Standard Scalp Acupuncture (ISSA). Thirty patients with middle cerebral artery AIS in the dominant hemisphere were selected and randomly divided into two groups such as the control group and the scalp acupuncture group, with 15 patients in each group. Patients in the control group were treated with conventional Western medicine, while patients in the scalp acupuncture group received ISSA (acupuncture at the parietal midline [MS5], acupuncture at the left anterior parietotemporal oblique line [MS6] and acupuncture at the left posterior parietotemporal oblique line [MS7]) for one course of treatment. All patients were evaluated for treatment efficacy and received whole brain resting state functional magnetic resonance imaging (Rs-fMRI) scan before and after treatment. The observational indicators included: (a) the National Institutes of Health Stroke Scale (NIHSS) scores and the simplified Fugl-Meyer Assessment (SFMA) scores; (b) analyses of the amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo) and voxel-mirrored homotopic connectivity (VMHC). The results showed a significant difference in the NIHSS scores before and after treatment in the scalp acupuncture group compared with the control group (p < .05), indicating that patients improved better after scalp acupuncture treatment. Compared with the control group, the VMHC, ALFF and ReHo values in the scalp acupuncture group increased after treatment. The VMHC values increased in the brain regions dominated by bilateral BA6 and BA8; the ALFF values increased in the left BA39 and the adjacent superior temporal gyrus and middle temporal gyrus; and the ReHo values increased in the brain regions extending from left middle temporal gyrus (including BA21) to BA37, and the brain regions extending from the left BA40 and angular gyrus to BA7. The present study indicated that scalp acupuncture can specifically strengthen the functional activities of the brain regions related to sensory integration, language processing and motor coordination in the middle aged and elderly patients with AIS of the dominant cerebral hemisphere, and can strengthen bilateral frontal lobe motor control. This study may provide a scientific basis for the clinical application of ISSA treatment in patients with AIS, and may also provide a preliminary research basis for further animal experiments.

PMID:34431612 | DOI:10.1002/ar.24746

Neuropsychiatr Dis Treat. 2021 Aug 17;17:2697-2706. doi: 10.2147/NDT.S323127. eCollection 2021.

ABSTRACT

PURPOSE: The aim of this study was to compare regional homogeneity (ReHo) changes in Parkinson's disease mild cognitive impairment (PD-MCI) patients with respect to normal controls (NC) and those with cognitively normal PD (PD-CN). Further, the study investigated the relationship between ReHo changes in PD patients and neuropsychological variation.

PATIENTS AND METHODS: Thirty PD-MCI, 19 PD-CN, and 21 NC subjects were enrolled. Resting state functional magnetic resonance imaging data of all subjects were collected, and regional brain activity was measured for ReHo. Analysis of covariance for ReHo was determined between the PD-MCI, PD-CN, and NC groups. Spearman rank correlations were assessed using the ReHo maps and data from the neuropsychological tests.

RESULTS: In comparison with NC, PD-CN patients showed significantly higher ReHo values in the right middle frontal gyrus (MFG) and lower ReHo values in the left supramarginal gyrus, bilateral inferior parietal lobule (IPL), and the right postcentral gyrus (PCG). In comparison with PD-CN patients, PD-MCI patients displayed significantly higher ReHo values in the right PCG, left middle occipital gyrus (MOG) and IPL. No significant correlation between ReHo indices and the neuropsychological scales was observed.

CONCLUSION: Our finding revealed that decreases in ReHo in the default mode network (DMN) may appear before PD-related cognitive impairment. In order to preserve executive attention capacity, ReHo in the right MFG in PD patients lacking cognition impairment increased for compensation. PD-MCI showed increased ReHo in the left MOG, which might have been caused by visual and visual-spatial dysfunction, and increased ReHo in the left IPL, which might reflect network disturbance and induce cognition deficits.

PMID:34429605 | PMC:PMC8380131 | DOI:10.2147/NDT.S323127

Sci Rep. 2021 Aug 24;11(1):17079. doi: 10.1038/s41598-021-96519-w.

ABSTRACT

Primary nocturnal enuresis (PNE) affects children's physical and mental health with a high rate. However, its neural mechanism is still unclear. Studies have found that the paraventricular thalamus (PVT) is among the key brain regions implicated with awakening regulation and its control of the transition between sleep and wakening is dependent on signaling through the PVT-nucleus accumbens (NAc) pathway. So this study analyzed the function of brain regions and their connectivity of PVT and NAc. A total of twenty-six PNE and typically developing (TD) children were involved in the study and the methods of amplitude of low frequency fluctuation (ALFF), degree centrality (DC) and functional connectivity (FC) based on resting-state functional magnetic resonance imaging (rs-fMRI) were used to analyze the brain functions. Results showed that there was no statistical significant difference in ALFF and DC between PNE and TD children in bilateral PVT and NAc. And there was statistical significant difference of the comparison of the FC of left PVT (lPVT) and left NAc (lNAc) between PNE and TD children. Meanwhile, there was negative correlation between awakening score and the FC of rPVT and lNAc, and no obvious correlation between awakening score and the FC of lPVT and lNAc in PNE children. Meanwhile, there was both negative correlation between awakening score and the FC of lPVT, rPTV and lNAc in TD children. Therefore, the FC between rPVT and lNAc was more reliable in assessing the degree of awakening ability in PNE children. This finding could help establish the evaluation index of PNE.

PMID:34429478 | DOI:10.1038/s41598-021-96519-w

Psychol Med. 2021 Aug 25:1-13. doi: 10.1017/S0033291721003135. Online ahead of print.

ABSTRACT

BACKGROUND: Understanding the neurobiological underpinnings of childhood maltreatment is vital given consistent links with poor mental health. Dimensional models of adversity purport that different types of adversity likely have distinct neurobiological consequences. Adolescence is a key developmental period, during which deviations from normative neurodevelopment may have particular relevance for mental health. However, longitudinal work examining links between different forms of maltreatment, neurodevelopment, and mental health is limited.

METHODS: In the present study, we explored associations between abuse, neglect, and longitudinal development of within-network functional connectivity of the salience (SN), default mode (DMN), and executive control network in 142 community residing adolescents. Resting-state fMRI data were acquired at age 16 (T1; M = 16.46 years, s.d. = 0.52, 66F) and 19 (T2; mean follow-up period: 2.35 years). Mental health data were also collected at T1 and T2. Childhood maltreatment history was assessed prior to T1.

RESULTS: Abuse and neglect were both found to be associated with increases in within-SN functional connectivity from age 16 to 19. Further, there were sex differences in the association between neglect and changes in within-DMN connectivity. Finally, increases in within-SN connectivity were found to mediate the association between abuse/neglect and lower problematic substance use and higher depressive symptoms at age 19.

CONCLUSIONS: Our findings suggest that childhood maltreatment is associated with altered neurodevelopmental trajectories, and that changes in salience processing may be linked with risk and resilience for the development of depression and substance use problems during adolescence, respectively. Further work is needed to understand the distinct neurodevelopmental and mental health outcomes of abuse and neglect.

PMID:34429171 | DOI:10.1017/S0033291721003135

Neuroimage. 2021 Aug 21:118501. doi: 10.1016/j.neuroimage.2021.118501. Online ahead of print.

ABSTRACT

Although brain research has taken important strides in recent decades, the interaction and coupling of its different physiological levels is still not elucidated. Specifically, the molecular substrates of resting-state functional connectivity (rs-FC) remain poorly understood. The aim of this study was elucidating interactions between dopamine D2 receptors (D2R) and serotonin transporter (SERT) availabilities in the striatum (CPu) and medial prefrontal cortex (mPFC), two of the main dopaminergic and serotonergic projection areas, and the default-mode network. Additionally, we delineated its interaction with two other prominent resting-state networks (RSNs), the salience network (SN) and the sensorimotor network (SMN). To this extent, we performed simultaneous PET/fMRI scans in a total of 59 healthy rats using [11C]raclopride and [11C]DASB, two tracers used to image quantify D2R and SERT respectively. Edge, node and network-level rs-FC metrics were calculated for each subject and potential correlations with binding potentials (BPND) in the CPu and mPFC were evaluated. We found widespread negative associations between CPu D2R availability and all the RSNs investigated, consistent with the postulated role of the indirect basal ganglia pathway. Correlations between D2Rs in the mPFC were weaker and largely restricted to DMN connectivity. Strikingly, medial prefrontal SERT correlated both positively with anterior DMN rs-FC and negatively with rs-FC between and within the SN, SMN and the posterior DMN, underlining the complex role of serotonergic neurotransmission in this region. Here we show direct relationships between rs-FC and molecular properties of the brain as assessed by simultaneous PET/fMRI in healthy rodents. The findings in the present study both contribute to the basic understanding of rs-FC by revealing associations between inter-subject variances of rs-FC and receptor and transporter availabilities. Additionally, since current therapeutic strategies typically target neurotransmitter systems with the aim of normalizing brain function, delineating associations between molecular and network-level brain properties is essential and may enhance the understanding of neuropathologies and support future drug development.

PMID:34428573 | DOI:10.1016/j.neuroimage.2021.118501

IEEE J Biomed Health Inform. 2021 Aug 24;PP. doi: 10.1109/JBHI.2021.3107305. Online ahead of print.

ABSTRACT

Brain functional connectivity (FC) networks derived from resting-state functional magnetic resonance imaging (rs-fMRI) have been widely applied to automated identification of brain disorders, such as Alzheimer's disease (AD) and attention deficit hyperactivity disorder (ADHD). To generate compact representations of FC networks, various thresholding strategies have been developed to analyze brain FC networks. However, existing studies usually employ predefined thresholds or percentages of connections to threshold FC networks, thus ignoring the diversity of temporal correlation (particularly strong associations) among brain regions in same/different subject groups. Also, it is usually challenging to decide the optimal threshold or connection percentage in practice. To this end, in this paper, we propose a distribution-guided network thresholding (DNT) method for functional connectivity analysis in brain disorder identification with rs-fMRI. Specifically, for each functional connectivity of a pair of brain regions, we proposed to compute its specific threshold based on the distribution of connection strength (i.e., temporal correlation) between subject groups (e.g., patients and normal controls). The proposed DNT can adaptively yield FC-specific threshold for each connection in brain networks, thus preserving the diversity of temporal correlation among brain regions. Experiment results on both ADNI and ADHD-200 datasets demonstrate the effectiveness of our proposed DNT method in fMRI-based identification of AD and ADHD.

PMID:34428167 | DOI:10.1109/JBHI.2021.3107305

Addict Biol. 2021 Aug 24:e13080. doi: 10.1111/adb.13080. Online ahead of print.

ABSTRACT

Methamphetamine (MA) abuse has become a global public health problem due to damage to various systems throughout the body, especially the central nervous system. However, the differences in resting-state brain function between short-term and long-term abstinence, the pros and cons of treatments, and the relationship between resting-state brain function and behavioral tests are unknown. Sixty-three MA abstinent individuals were followed up for nearly 1 year and treated with three different methods. The amplitude of low-frequency fluctuation (ALFF) and regional homogeneity (ReHo) based on the Harvard-Oxford atlas (HOA) were measured by resting-state functional magnetic resonance imaging (fMRI). Impulsivity was evaluated by the Barratt Impulsivity Scale-11 (BIS-11). Brain regions with significant increases in ALFF and ReHo values in the long-term abstinent group compared to the short-term abstinent group were around the right frontal pole (McKetin et al., 2012, https://doi.org/10.1111/j.1360-0443.2012.03933.x) and right middle frontal gyrus (Wang et al., 2015, https://doi.org/10.1371/journal.pone.0133431). There were no significant differences among the three groups that experienced long-term abstinence. The changes in ALFF and ReHo in the right middle frontal gyrus were significantly associated with BIS total scores, BIS attention scores, and BIS nonplanning scores. The right middle frontal gyrus is a critical region in MA long-term abstinent individuals exposed to therapeutic intervention, and this region may be useful, when combined with BIS-11, as a potential biomarker to identify the effect of abstinence with therapeutic intervention in MA individuals.

PMID:34427375 | DOI:10.1111/adb.13080

J Psychiatr Res. 2021 Aug 20;142:369-375. doi: 10.1016/j.jpsychires.2021.08.026. Online ahead of print.

ABSTRACT

Recent advances in functional magnetic resonance imaging (fMRI) have resulted in many studies on resting-state functional connectivity (rsFC) in depressed patients. Previous studies have shown alterations between multiple brain areas, such as the prefrontal cortex, anterior cingulate cortex, and basal ganglia, but there are very few prospective studies with a longitudinal design on adolescent depression patients. We therefore investigated the change in positive rsFC in a homogeneous drug-naïve adolescent group after 12 weeks of antidepressant treatment. Functional neuroimaging data were collected and analyzed from 32 patients and 27 healthy controls. Based on previous literature, the amygdala, anterior cingulate cortex (ACC), insula, hippocampus, and dorsolateral prefrontal cortex (DLPFC) were selected as seed regions. Seed-to-voxel analyses were performed between pre- and post-treatment states as well as between the patients and controls at baseline. The positive rsFC between the right DLPFC and the left putamen/right frontal operculum were shown to be higher in patients than in the controls. The positive rsFC between the left DLPFC and left putamen/left lingual gyrus was also higher in the patients than in the controls. The positive rsFC between the right dorsal ACC and the left precentral gyrus had reduced after the 12-week antidepressant treatment. Regions involved in the frontolimbic circuit showed changes in the positive rsFC in the depressed adolescents as compared to in the healthy controls. There were also significant changes in the positive rsFC after 12-weeks of antidepressant treatment. The involved regions were associated with emotional regulation, cognitive functioning, impulse control, and visual processing.

PMID:34425489 | DOI:10.1016/j.jpsychires.2021.08.026

Brain Behav. 2021 Aug 22. doi: 10.1002/brb3.2331. Online ahead of print.

ABSTRACT

BACKGROUND: Better life satisfaction (LS) is associated with better psychological and psychiatric outcomes. To the best of our knowledge, no studies have examined prediction models for LS.

METHODS: Using resting-state functional magnetic resonance imaging (R-fMRI) data from the Human Connectome Project (HCP) Young Adult S1200 dataset, we examined whether LS is predictable from intrinsic functional connectivity (iFC). All the HCP data were subdivided into either discovery (n = 100) or validation (n = 766) datasets. Using R-fMRI data in the discovery dataset, we computed a matrix of iFCs between brain regions. Ridge regression, in combination with principal component analysis and 10-fold cross-validation, was used to predict LS. Prediction performance was evaluated by comparing actual and predicted LS scores. The generalizability of the prediction model obtained from the discovery dataset was evaluated by applying this model to the validation dataset.

RESULTS: The model was able to successfully predict LS in the discovery dataset (r = 0.381, p < .001). The model was also able to successfully predict the degree of LS (r = 0.137, 5000-repetition permutation test p = .006) in the validation dataset, suggesting that our model is generalizable to the prediction of LS in young adults. iFCs stemming from visual, ventral attention, or limbic networks to other networks (such as the dorsal attention network and default mode network) were likely to contribute positively toward predicted LS scores. iFCs within ventral attention and limbic networks also positively contributed to predicting LS. On the other hand, iFCs stemming from the visual and cerebellar networks to other networks were likely to contribute negatively to the predicted LS scores.

CONCLUSION: The present findings suggest that LS is predictable from the iFCs. These results are an important step toward identifying the neural basis of life satisfaction.

PMID:34423588 | DOI:10.1002/brb3.2331

J Med Imaging (Bellingham). 2021 Jul;8(4):046001. doi: 10.1117/1.JMI.8.4.046001. Epub 2021 Aug 16.

ABSTRACT

Purpose: Currently, functional magnetic resonance imaging (fMRI) is the most commonly used technique for obtaining dynamic information about the brain. However, because of the complexity of the data, it is often difficult to directly visualize the temporal aspect of the fMRI data. Approach: We outline a t -distributed stochastic neighbor embedding (t-SNE)-based postprocessing technique that can be used for visualization of temporal information from a 4D fMRI data. Apart from visualization, we also show its utility in detection of major changes in the brain meta-states during the scan duration. Results: The t-SNE approach is able to detect brain-state changes from task to rest and vice versa for single- and multitask fMRI data. A temporal visualization can also be obtained for task and resting state fMRI data for assessing the temporal dynamics during the scan duration. Additionally, hemodynamic delay can be quantified by comparison of the detected brain-state changes with the experiment paradigm for task fMRI data. Conclusion: The t-SNE visualization can visualize help identify major brain-state changes from fMRI data. Such visualization can provide information about the degree of involvement and attentiveness of the subject during the scan and can be potentially utilized as a quality control for subject's performance during the scan.

PMID:34423072 | PMC:PMC8366791 | DOI:10.1117/1.JMI.8.4.046001

Front Neurol. 2021 Aug 4;12:694271. doi: 10.3389/fneur.2021.694271. eCollection 2021.

ABSTRACT

Chronic pain coincides with myriad functional alterations throughout the brain and spinal cord. While spinal cord mechanisms of chronic pain have been extensively characterized in animal models and in vitro, to date, research in patients with chronic pain has focused only very minimally on the spinal cord. Previously, spinal cord functional magnetic resonance imaging (fMRI) identified regional alterations in spinal cord activity in patients (who were not taking opioids) with fibromyalgia, a chronic pain condition. Here, in patients with fibromyalgia who take opioids (N = 15), we compared spinal cord resting-state fMRI data vs. patients with fibromyalgia not taking opioids (N = 15) and healthy controls (N = 14). We hypothesized that the opioid (vs. non-opioid) patient group would show greater regional alterations in spinal cord activity (i.e., the amplitude of low frequency fluctuations or ALFF, a measure of regional spinal cord activity). However, we found that regional spinal cord activity in the opioid group was more similar to healthy controls, while regional spinal cord activity in the non-opioid group showed more pronounced differences (i.e., ventral increases and dorsal decreases in regional ALFF) vs. healthy controls. Across patient groups, self-reported fatigue correlated with regional differences in spinal cord activity. Additionally, spinal cord functional connectivity and graph metrics did not differ among groups. Our findings suggest that, contrary to our main hypothesis, patients with fibromyalgia who take opioids do not have greater alterations in regional spinal cord activity. Thus, regional spinal cord activity may be less imbalanced in patients taking opioids compared to patients not taking opioids.

PMID:34421798 | PMC:PMC8371264 | DOI:10.3389/fneur.2021.694271

Front Psychiatry. 2021 Aug 5;12:687580. doi: 10.3389/fpsyt.2021.687580. eCollection 2021.

ABSTRACT

Schizophrenia is currently thought as a disorder with dysfunctional communication within and between sensory and cognitive processes. It has been hypothesized that these deficits mediate heterogeneous and comprehensive schizophrenia symptomatology. In this study, we investigated as to how the abnormal dynamic functional architecture of sensory and cognitive networks may contribute to these symptoms in schizophrenia. We calculated a sliding-window-based dynamic functional connectivity strength (FCS) and amplitude of low-frequency fluctuation (ALFF) maps. Then, using group-independent component analysis, we characterized spatial organization of dynamic functional network (sDFN) across various time windows. The spatial architectures of FCS/ALFF-sDFN were similar with traditional resting-state functional networks and cannot be accounted by length of the sliding window. Moreover, schizophrenic subjects demonstrated reduced dynamic functional connectivity (dFC) within sensory and perceptual sDFNs, as well as decreased connectivity between these sDFNs and high-order frontal sDFNs. The severity of patients' positive and total symptoms was related to these abnormal dFCs. Our findings revealed that the sDFN during rest might form the intrinsic functional architecture and functional changes associated with psychotic symptom deficit. Our results support the hypothesis that the dynamic functional network may influence the aberrant sensory and cognitive function in schizophrenia, further highlighting that targeting perceptual deficits could extend our understanding of the pathophysiology of schizophrenia.

PMID:34421674 | PMC:PMC8374440 | DOI:10.3389/fpsyt.2021.687580

Front Aging Neurosci. 2021 Jul 30;13:688926. doi: 10.3389/fnagi.2021.688926. eCollection 2021.

ABSTRACT

BACKGROUND: Graph theory and machine learning have been shown to be effective ways of classifying different stages of Alzheimer's disease (AD). Most previous studies have only focused on inter-subject classification with single-mode neuroimaging data. However, whether this classification can truly reflect the changes in the structure and function of the brain region in disease progression remains unverified. In the current study, we aimed to evaluate the classification framework, which combines structural Magnetic Resonance Imaging (sMRI) and resting-state functional Magnetic Resonance Imaging (rs-fMRI) metrics, to distinguish mild cognitive impairment non-converters (MCInc)/AD from MCI converters (MCIc) by using graph theory and machine learning.

METHODS: With the intra-subject (MCInc vs. MCIc) and inter-subject (MCIc vs. AD) design, we employed cortical thickness features, structural brain network features, and sub-frequency (full-band, slow-4, slow-5) functional brain network features for classification. Three feature selection methods [random subset feature selection algorithm (RSFS), minimal redundancy maximal relevance (mRMR), and sparse linear regression feature selection algorithm based on stationary selection (SS-LR)] were used respectively to select discriminative features in the iterative combinations of MRI and network measures. Then support vector machine (SVM) classifier with nested cross-validation was employed for classification. We also compared the performance of multiple classifiers (Random Forest, K-nearest neighbor, Adaboost, SVM) and verified the reliability of our results by upsampling.

RESULTS: We found that in the classifications of MCIc vs. MCInc, and MCIc vs. AD, the proposed RSFS algorithm achieved the best accuracies (84.71, 89.80%) than the other algorithms. And the high-sensitivity brain regions found with the two classification groups were inconsistent. Specifically, in MCIc vs. MCInc, the high-sensitivity brain regions associated with both structural and functional features included frontal, temporal, caudate, entorhinal, parahippocampal, and calcarine fissure and surrounding cortex. While in MCIc vs. AD, the high-sensitivity brain regions associated only with functional features included frontal, temporal, thalamus, olfactory, and angular.

CONCLUSIONS: These results suggest that our proposed method could effectively predict the conversion of MCI to AD, and the inconsistency of specific brain regions provides a novel insight for clinical AD diagnosis.

PMID:34421570 | PMC:PMC8375594 | DOI:10.3389/fnagi.2021.688926

Front Hum Neurosci. 2021 Aug 5;15:685763. doi: 10.3389/fnhum.2021.685763. eCollection 2021.

ABSTRACT

Purpose: Previous studies have found that there are significant changes in functional network properties for patients with moderate to severe carotid artery stenosis. Our study aimed to explore the topology properties of brain functional network in asymptomatic patients with carotid plaque without significant stenosis. Methods: A total of 61 asymptomatic patients with carotid plaque (mean age 61.79 ± 7.35 years) and 25 healthy control subjects (HC; 58.12 ± 6.79 years) were recruited. General data collection, carotid ultrasound examination and resting state functional magnetic resonance imaging were performed on all subjects. Graph-theory was applied to examine the differences in the brain functional network topological properties between two groups. Results: In the plaque group, Eloc(P = 0.03), γ (P = 0.01), and σ (P = 0.01) were significantly higher than in the HC group. The degree centrality of left middle frontal gyrus and the nodal efficiency of left middle frontal gyrus and right inferior parietal angular gyrus were significantly higher in the plaque group than in HC. The degree centrality and betweenness centrality of right middle temporal gyrus, as well as the nodal efficiency of right middle temporal gyrus, were significantly lower in the plaque group than in HC. Conclusions: The brain functional networks of patients with carotid plaques differ from those of healthy controls. Asymptomatic patients with carotid plaques exhibit increased local and global connectivity, which may reflect subtle reorganizations in response to early brain damage.

PMID:34421560 | PMC:PMC8375554 | DOI:10.3389/fnhum.2021.685763

Front Neurosci. 2021 Jul 29;15:704920. doi: 10.3389/fnins.2021.704920. eCollection 2021.

ABSTRACT

INTRODUCTION: Premature ejaculation (PE) is a common sexual dysfunction and is found to be associated with abnormal emotion. The amygdala plays an important role in the processing of emotion. The process of ejaculation is found to be mediated by the frontal-limbic neural circuits. However, the correlations between PE and emotion are still unclear.

METHODS: Resting-state functional magnetic resonance imaging (rs-fMRI) data were acquired in 27 PE patients with stable emotion (SPE), 27 PE patients with abnormal emotion (NPE), and 30 healthy controls (HC). We used rs-fMRI to explore the underlying neural mechanisms in SPE, NPE, and HC by measuring the functional connectivity (FC). Differences of FC values among the three groups were compared when choosing bilateral amygdala as the regions of interest (ROIs). We also explored the correlations between the brain regions showing altered FC values and scores of the premature ejaculation diagnostic tool (PEDT)/Eysenck Personality Inventory about neuroticism (EPQ-N) in the PE group.

RESULTS: When the left amygdala was chosen as the ROI, the SPE group exhibited an increased FC between the left medial superior frontal gyrus (SFGmed) and amygdala compared with the NPE or HC group. When the right amygdala was chosen as the ROI, the NPE group exhibited a decreased FC between the left SFGmed and right amygdala compared with the HC group. In addition, FC values of the left SFGmed had positive correlations with PEDT and negative correlations with EPQ-N scores in the PE group. Moreover, FC values of the left superior temporal gyrus had positive correlations with EPQ-N scores in the PE group.

CONCLUSION: The increased FC values between the left SFGmed and amygdala could reflect a compensatory cortical control mechanism with the effect of stabilized emotion in the limbic regions of PE patients. Abnormal FC between these brain regions could play a critical role in the physiopathology of PE and could help us in dividing PE into more subtypes.

PMID:34421524 | PMC:PMC8375680 | DOI:10.3389/fnins.2021.704920

Brain Struct Funct. 2021 Aug 22. doi: 10.1007/s00429-021-02361-1. Online ahead of print.

ABSTRACT

Voluntary apnea showcases extreme human adaptability in trained individuals like professional free divers. We evaluated the psychological and physiological adaptation and the functional cerebral changes using electroencephalography (EEG) and functional Magnetic Resonance Imaging (fMRI) to 6.5 min of dry static apnea performed by a world champion free diver. Compared to resting state at baseline, breath holding was characterized by increased EEG power and functional connectivity in the alpha band, along with decreased delta band connectivity. fMRI connectivity was increased within the default mode network (DMN) and visual areas but decreased in pre- and postcentral cortices. While these changes occurred in regions overlapping with cerebral signatures of several meditation practices, they also display some unique features that suggest an altered somatosensory integration. As suggested by self-reports, these findings could reflect the ability of elite free divers to create a state of sensory dissociation when performing prolonged apnea.

PMID:34420066 | DOI:10.1007/s00429-021-02361-1

Dev Cogn Neurosci. 2021 Aug 14;51:101005. doi: 10.1016/j.dcn.2021.101005. Online ahead of print.

ABSTRACT

Early socioeconomic status (SES) has consistently been associated with child health and cognitive outcomes, in addition to alterations in brain function and connectivity. The goal of the present study was to probe the effects of different facets of SES (parent education, income, and neighborhood disadvantage), that likely represent varying aspects of the environment, on resting state functional connectivity (rsFC). We investigated this question in a large sample of 9475 children (aged 9-10 years) from the Adolescent Brain Cognitive Development (ABCD) Study. Specifically, we analyzed the association between household SES (parent education, income-to-needs ratio) and neighborhood disadvantage, and system-level rsFC using within-sample split-half replication. We then tested whether the associations were unique to each SES measure, and whether household SES and neighborhood disadvantage had interactive effects on rsFC. SES measures had both common and distinct effects on rsFC, with sensory-motor systems (e.g., sensorimotor network) and cognitive networks (e.g., front-parietal network) particularly implicated. Further, the association between neighborhood disadvantage and sensorimotor network connectivity was less pronounced in the presence of high income-to-needs. Findings demonstrate that different facets of SES have distinct and interacting effects on rsFC, highlighting the importance of considering different indicators when studying the effects of SES on the brain.

PMID:34419766 | DOI:10.1016/j.dcn.2021.101005

Sci Rep. 2021 Aug 20;11(1):16930. doi: 10.1038/s41598-021-96319-2.

ABSTRACT

Symptomatic overlap of depressive episodes in bipolar disorder (BD) and major depressive disorder (MDD) is a major diagnostic and therapeutic problem. Mania in medical history remains the only reliable distinguishing marker which is problematic given that episodes of depression compared to episodes of mania are more frequent and predominantly present at the beginning of BD. Resting-state functional magnetic resonance imaging (rs-fMRI) is a non-invasive, task-free, and well-tolerated method that may provide diagnostic markers acquired from spontaneous neural activity. Previous rs-fMRI studies focused on differentiating BD from MDD depression were inconsistent in their findings due to low sample power, heterogeneity of compared samples, and diversity of analytical methods. This meta-analysis investigated resting-state activity differences in BD and MDD depression using activation likelihood estimation. PubMed, Web of Science, Scopus and Google Scholar databases were searched for whole-brain rs-fMRI studies which compared MDD and BD currently depressed patients between Jan 2000 and August 2020. Ten studies were included, representing 234 BD and 296 MDD patients. The meta-analysis found increased activity in the left insula and adjacent area in MDD compared to BD. The finding suggests that the insula is involved in neural activity patterns during resting-state that can be potentially used as a biomarker differentiating both disorders.

PMID:34417487 | DOI:10.1038/s41598-021-96319-2