Amplitude Of Low-frequency Fluctuation Research Articles

Quantification of Glutathione and Its Associated Spontaneous Neuronal Activity in Major Depressive Disorder and Obsessive-Compulsive Disorder

BackgroundGlutathione (GSH) is a crucial antioxidant in the human brain. Although proton magnetic resonance spectroscopy using the Mescher-Garwood point-resolved spectroscopy sequence is highly recommended, limited literature has measured cortical GSH using this method in major psychiatric disorders. MethodsBy combining magnetic resonance spectroscopy and resting-state functional magnetic resonance imaging, we quantified brain GSH and glutamate in the medial prefrontal cortex and precuneus and explored relationships between GSH levels and intrinsic neuronal activity as well as clinical symptoms among healthy control (HC) participants (n = 30), people with major depressive disorder (MDD) (n = 28), and people with obsessive-compulsive disorder (OCD) (n = 28). ResultsGSH concentrations were lower in the medial prefrontal cortex and precuneus in both the MDD and OCD groups than in the HC group. In the HC group, positive correlations were noted between GSH and glutamate levels and between GSH and fractional amplitude of low-frequency fluctuations in both regions. However, while these correlations were absent in both patient groups, there was a weak positive correlation between glutamate and fractional amplitude of low-frequency fluctuations. Moreover, GSH levels were negatively correlated with depressive and compulsive symptoms in MDD and OCD, respectively. ConclusionsThese findings suggest that reduced GSH levels and an imbalance between GSH and glutamate could increase oxidative stress and alter neurotransmitter signaling, thereby leading to disruptions in GSH-related neurochemical-neuronal coupling and psychopathologies across MDD and OCD. Understanding these mechanisms could provide valuable insights into the processes that underlie these disorders and potentially become a springboard for future directions and advancing our knowledge of their neurobiological foundations.

The abnormalities of brain function in females with primary insomnia: a resting-state functional magnetic resonance imaging study.

The neuropathologic mechanism of primary insomnia (PI) of females remains unclear. This study aims to investigate the features of amplitude of low-frequency fluctuations (ALFF) and regional homogeneity (ReHo) in females with PI using functional magnetic resonance imaging (fMRI), and then explore the abnormalities of functional connectivity (FC). A total of 39 female PI patients and 31 female healthy controls (HC) were enrolled in the study. The sleep condition was assessed using the Pittsburgh Sleep Quality Index (PSQI), and Insomnia Severity Index (ISI), and their depressive symptom was evaluated using the Hamilton Depression Scale (HAMD-24). The rs-fMRI was once conducted for every subject. ReHo, ALFF, and ROI-based FC were used to analyze the changes of brain function. ALFF values were increased in the Cerebelum_4_5_L, as well as decreased ALFF in the bilateral Frontal_Sup_Medial (SFGmed), Angular_L (ANG.L), Parietal_Inf_R (IPL.R), SupraMarginal_R (SMG.R), and Postcentral_R (PoCG.R). ReHo values were increased in the Temporal_Pole_Mid_R (TPOsup.R), as well as decreased ReHo in the Insula_R (INS.R), Frontal_Inf_Oper_R (ORBinf.R), Putamen_R (PUT.R), Rolandic_Oper_R (ROL.R), bilateral Cingulum_Post (PCG), bilateral Frontal_Sup_Medial (SFGmed), bilateral anterior cingulate and paracingulate gyri (ACG), and the bilateral precuneus (PCUN). Across the entire brain, there was a decline in the FC between Angular_R and Frontal_Sup_Medial_L. Alterations in brain regions of female patients with PI involved multiple functional networks, including the default mode network, the salience network, the central executive network, and the limbic network. Reduced coordination between functional networks may be an important mechanism for insomnia and may lead to reduced cognitive function and decision-making ability.

Altered Resting-State Brain Entropy in Cerebral Small Vessel Disease Patients with Cognitive Impairment.

Objective: Cerebral small vessel disease (CSVD) is a primary vascular disease of cognitive impairment. Previous studies have predominantly focused on brain linear features. However, the nonlinear measure, brain entropy (BEN), has not been elaborated. Thus, this study aims to investigate if BEN abnormalities could manifest in CSVD patients with cognitive impairment. Methods: Thirty-four CSVD patients with cognitive impairment and 37 healthy controls (HCs) were recruited. Analysis of gray matter approximate entropy (ApEn) and sample entropy (SampEn) which are two indices of BEN was calculated. To explore whether BEN can provide unique information, we further performed brain linear methods, namely, amplitude of low frequency fluctuation (ALFF) and regional homogeneity (ReHo), to observe their differences. The ratios of BEN/ALFF and BEN/ReHo which represent the coupling of nonlinear and linear features were introduced. Correlation analysis was conducted between imaging indices and cognition. Subsequently, the linear support vector machine (SVM) was used to assess their discriminative ability. Results: CSVD patients exhibited lower ApEn and SamEn values in sensorimotor areas, which were correlated with worse memory and executive function. In addition, the results of BEN showed little overlap with ALFF and ReHo in brain regions. Correlation analysis also revealed a relationship between the two ratios and cognition. SVM analysis using BEN and its ratios as features achieved an accuracy of 74.64% (sensitivity: 86.49%, specificity: 61.76%, and AUC: 0.82439). Conclusion: Our study reveals that the reduction of sensorimotor system complexity is correlated with cognition. BEN exhibits distinctive characteristics in brain activity. Combining BEN and the ratios can be new biomarkers to diagnose CSVD with cognitive impairment. Impact Statement Cerebral small vessel disease (CSVD) is regarded as the most important vascular disease of cognitive impairment. However, conventional brain imaging fails to adequately elucidate the pathogenesis of cognitive disorder related to CSVD. In this regard, exploring brain entropy (BEN) based on resting-state functional magnetic resonance imaging (rs-fMRI) represents a relatively novel and unexplored approach in the context of CSVD. This approach provides novel insights into the pathogenesis, diagnosis, and rehabilitation of cognitive disorder associated with CSVD.

Efficacy of Digital Dance on Brain Imagery, Cognition, and Health: Randomized Controlled Trial.

Multidomain interventions have demonstrable benefits for promoting healthy aging, but self-empowerment strategies to sustain long-term gains remain elusive. This study evaluated the effects of digital somatosensory dance game participation on brain imagery changes as primary outcomes and other physical and mental health measures as secondary outcomes related to healthy aging. Between August 31, 2020, and June 27, 2021, this randomized controlled trial recruited 60 eligible participants older than 55 years with no recent engagement in digital dance games. A computer-generated randomization sequence was used to allocate participants 1:1, without stratification, to an intervention group (n=30) who underwent digital somatosensory dance game training or a control group (n=30). An anonymized code masked the intervention allocations from the investigators, and individuals who assigned the interventions were not involved in analyzing the study data. The intervention entailed two 30-minute dance game sessions per week for 6 months, and the control group received healthy aging education. Primary outcomes were brain imagery changes. All variables were measured at baseline and the 6-month follow-up, and intervention effects were estimated using t tests with intention-to-treat analyses. Compared with the control group, intervention participants had significantly different brain imagery in the gray matter volume (GMV) of the left putamen (estimate 0.016, 95% CI 0.008 to 0.024; P<.001), GMV of the left pallidum (estimate 0.02, 95% CI 0.006 to 0.034; P=.004), and fractional amplitude of low frequency fluctuations of the left pallidum (estimate 0.262, 95% CI 0.084 to 0.439; P=.004). Additionally, the intervention group had different imagery in the cerebellum VI GMV (estimate 0.011, 95% CI 0.003 to 0.02; P=.01). The intervention group also had improved total Montreal Cognitive Assessment scores (estimate 1.2, 95% CI 0.27 to -2.13; P<.01), quality of life (estimate 7.08, 95% CI 2.35 to 11.82; P=.004), and time spent sitting on weekdays (estimate -1.96, 95% CI -3.33 to -0.60; P=.005). Furthermore, dance performance was significantly associated with cognitive performance (P=.003), health status (P=.14), resilience (P=.007), and demoralization (P<.001). Digital somatosensory dance game participation for 6 months was associated with brain imagery changes in multiple regions involving somatosensory, motor, visual, and attention functions, which were consistent with phenotypic improvements associated with healthy aging. ClinicalTrials.gov NCT05411042; https://clinicaltrials.gov/study/NCT05411042.

Reliability of brain metrics derived from a Time-Domain Functional Near-Infrared Spectroscopy System

With the growing interest in establishing brain-based biomarkers for precision medicine, there is a need for noninvasive, scalable neuroimaging devices that yield valid and reliable metrics. Kernel’s second-generation Flow2 Time-Domain Functional Near-Infrared Spectroscopy (TD-fNIRS) system meets the requirements of noninvasive and scalable neuroimaging, and uses a validated modality to measure brain function. In this work, we investigate the test-retest reliability (TRR) of a set of metrics derived from the Flow2 recordings. We adopted a repeated-measures design with 49 healthy participants, and quantified TRR over multiple time points and different headsets—in different experimental conditions including a resting state, a sensory, and a cognitive task. Results demonstrated high reliability in resting state features including hemoglobin concentrations, head tissue light attenuation, amplitude of low frequency fluctuations, and functional connectivity. Additionally, passive auditory and Go/No-Go inhibitory control tasks each exhibited similar activation patterns across days. Notably, areas with the highest reliability were in auditory regions during the auditory task, and right prefrontal regions during the Go/No-Go task, consistent with prior literature. This study underscores the reliability of Flow2-derived metrics, supporting its potential to actualize the vision of using brain-based biomarkers for diagnosis, treatment selection and treatment monitoring of neuropsychiatric and neurocognitive disorders.

Acupuncture Modulation of Chronic Neuropathic Pain and Its Association With Brain Functional Properties

Chronic neuropathic pain has been one of the prominent causes of disability, and acupuncture has shown promise in treatment. The present study aimed to characterize acupuncture modulation of chronic neuropathic pain and explore the related functional brain changes. Sixty chronic sciatica patients were divided into acupuncture- or sham acupuncture groups and received 10 sessions of treatment during 4 weeks. The visual analog scale for leg pain, oswestry disability index (ODI), and resting-state functional magnetic resonance images were assessed at baseline and after treatment. Then, fractional amplitudes of low-frequency fluctuations (fALFF) and support vector regression analyses were performed. Compared with sham acupuncture, acupuncture significantly improved symptoms, including visual analog scale for leg pain and ODI. In addition, acupuncture exhibited increased fALFF of the right superior parietal lobule (SPL) and right postcentral gyrus. Furthermore, the actual 4-week ODI values were positively correlated with the support vector regression-predicted values based on the right SPL fALFF and baseline clinical measurements. These results indicate that the spontaneous neural activity of the right SPL and right postcentral gyrus may be involved in the modulation of acupuncture in chronic neuropathic pain. In addition, the spontaneous neural activity of the right SPL might be used as the predictor of response to acupuncture therapy. PerspectiveThis clinical neuroimaging study elucidated the neural basis of acupuncture in chronic sciatica. Neurological indicators and clinical measurements could be used as potential predictors of acupuncture response. This study combines neuroimaging and artificial intelligence techniques to highlight the potential of acupuncture for the treatment of chronic neuropathic pain. Trial registration numberChinese Clinical Trial Registry, ChiCTR2100044585, http://www.chictr.org.cn.

A radiomics approach for predicting gait freezing in Parkinson's disease based on resting-state functional magnetic resonance imaging indices: a cross-sectional study.

Freezing of gait is a significant and debilitating motor symptom often observed in individuals with Parkinson's disease. Resting-state functional magnetic resonance imaging, along with its multi-level feature indices, has provided a fresh perspective and valuable insight into the study of freezing of gait in Parkinson's disease. It has been revealed that Parkinson's disease is accompanied by widespread irregularities in inherent brain network activity. However, the effective integration of the multi-level indices of resting-state functional magnetic resonance imaging into clinical settings for the diagnosis of freezing of gait in Parkinson's disease remains a challenge. Although previous studies have demonstrated that radiomics can extract optimal features as biomarkers to identify or predict diseases, a knowledge gap still exists in the field of freezing of gait in Parkinson's disease. This cross-sectional study aimed to evaluate the ability of radiomics features based on multi-level indices of resting-state functional magnetic resonance imaging, along with clinical features, to distinguish between Parkinson's disease patients with and without freezing of gait. We recruited 28 patients with Parkinson's disease who had freezing of gait (15 men and 13 women, average age 63 years) and 30 patients with Parkinson's disease who had no freezing of gait (16 men and 14 women, average age 64 years). Magnetic resonance imaging scans were obtained using a 3.0T scanner to extract the mean amplitude of low-frequency fluctuations, mean regional homogeneity, and degree centrality. Neurological and clinical characteristics were also evaluated. We used the least absolute shrinkage and selection operator algorithm to extract features and established feedforward neural network models based solely on resting-state functional magnetic resonance imaging indicators. We then performed predictive analysis of three distinct groups based on resting-state functional magnetic resonance imaging indicators indicators combined with clinical features. Subsequently, we conducted 100 additional five-fold cross-validations to determine the most effective model for each classification task and evaluated the performance of the model using the area under the receiver operating characteristic curve. The results showed that when differentiating patients with Parkinson's disease who had freezing of gait from those who did not have freezing of gait, or from healthy controls, the models using only the mean regional homogeneity values achieved the highest area under the receiver operating characteristic curve values of 0.750 (with an accuracy of 70.9%) and 0.759 (with an accuracy of 65.3%), respectively. When classifying patients with Parkinson's disease who had freezing of gait from those who had no freezing of gait, the model using the mean amplitude of low-frequency fluctuation values combined with two clinical features achieved the highest area under the receiver operating characteristic curve of 0.847 (with an accuracy of 74.3%). The most significant features for patients with Parkinson's disease who had freezing of gait were amplitude of low-frequency fluctuation alterations in the left parahippocampal gyrus and two clinical characteristics: Montreal Cognitive Assessment and Hamilton Depression Scale scores. Our findings suggest that radiomics features derived from resting-state functional magnetic resonance imaging indices and clinical information can serve as valuable indices for the identification of freezing of gait in Parkinson's disease.

Decreased resting-state brain function in older adults predicts enlarged representational momentum.

Representational momentum (RM) refers to the phenomenon in which an observer's judgment of the final location of a previously viewed moving target is often displaced forward in the direction of motion. This phenomenon is an adaptive mechanism that compensates for neural processing delays and is closely associated with visual cortex function. However, the impact of age-related decline of visual cortex function on the manifestations of RM remains unclear. The present study examined differences in the RM effect between older (N = 82) and younger adults (N = 74) using a cursor-positioning task. Additionally, resting-state functional magnetic resonance imaging was used to explore the potential neural substrates that underlie these differences, employing amplitude of low-frequency fluctuation (ALFF, reflecting the intensity of neural activity) and regional homogeneity (ReHo, reflecting the synchronization of neural activity) as indicators. Our findings indicate a significant increase in RM among older adults compared with younger adults. Neuroimaging data revealed a significant decrease in ALFF and ReHo within extensive regions of the visual cortex in older adults, validating age-related differences in this cortical area. More importantly, ALFF values in the bilateral visual area 3 and ReHo values in the bilateral visual area 2 in older adults exhibited a strong negative correlation with their RM effects. These results suggest that larger RM in older adults may be functional compensation for aging of the visual cortex. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Resting-State Network Analysis Reveals Altered Functional Brain Connectivity in Essential Tremor.

Introduction: Essential tremor (ET) comprises motor and non-motor-related features, whereas the current neuro-pathogenetic basis is still insufficient to explain the etiologies of ET. Although cerebellum-associated circuits have been discovered, the large-scale cerebral network connectivity in ET remains unclear. This study aimed to characterize the ET in terms of functional connectivity as well as network. We hypothesized that the resting-state network (RSN) within cerebrum could be altered in patients with ET. Methods: Resting-state functional magnetic resonance imaging (fMRI) was used to evaluate the inter- and intra-network connectivity as well as the functional activity in ET and normal control. Correlation analysis was performed to explore the relationship between RSN metrics and tremor features. Results: Comparison of inter-network connectivity indicated a decreased connectivity between default mode network and ventral attention network in the ET group (p < 0.05). Differences in functional activity (assessed by amplitude of low-frequency fluctuation, ALFF) were found in several brain regions participating in various RSNs (p < 0.05). The ET group generally has higher degree centrality over normal control. Correlation analysis has revealed that tremor features are associated with inter-network connectivity (|r| = 0.135-0.506), ALFF (|r| = 0.313-0.766), and degree centrality (|r| = 0.523-0.710). Conclusion: Alterations in the cerebral network of ET were detected by using resting-state fMRI, demonstrating a potentially useful approach to explore the cerebral alterations in ET.

Major depressive disorder and perceived social support: Moderated mediation model of security and brain dysfunction

Low social support increases the risk of Major depressive disorder (MDD), yet its effects on brain function are unclear. Thirty-two MDD patients with low social support, 52 with high social support, and 54 healthy controls were recruited. We investigated regional brain activity in MDD patients with low social support using resting-state functional Magnetic Resonance Imaging, employing measures such as degree centrality (DC), regional homogeneity, amplitude of low-frequency fluctuations, and fractional amplitude of low-frequency fluctuations. Abnormal regions identified in these analyses were selected as regions of interest for functional connectivity (FC) analysis. We then explored relationships among social support, brain dysfunction, MDD severity, and insecurity using partial correlation and moderated mediation models. Our findings reveal that MDD patients with low social support show decreased DC in the right superior temporal pole and right medial geniculate nucleus, coupled with increased FC between the right superior temporal pole and right inferior temporal gyrus, and the right supramarginal gyrus compared to those with high social support. Furthermore, the DC of the right medial geniculate nucleus positively correlates with social support, while the FC between the right superior temporal pole and right supramarginal gyrus negatively correlates with both social support and subjective support. Additionally, a moderated mediation model demonstrates that the FC between the right superior temporal pole and right supramarginal gyrus mediates the relationship between social support and depression severity, with security moderating this mediation. These findings underscore the impact of low social support on brain function and depression severity in MDD patients.

Milk Fat Globule-EGF Factor 8 (MFGE8) Mitigates Cognitive Impairment in Rats with Sepsis-Associated Encephalopathy: An fMRI Study.

Sepsis-associated encephalopathy (SAE) impairs hippocampal microglial efferocytosis, causing cognitive deficits. Previous research found that milk fat globule epidermal growth factor 8 protein (MFGE8) stimulates efferocytosis, reducing hippocampal inflammation in SAE rats. In this study, we explore MFGE8's role in alleviating cognitive impairment and its impact on neural activity using functional magnetic resonance imaging (fMRI). Sixty male Sprague Dawley rats were divided into four groups: Sham, cecal ligation and puncture (CLP), CLP+MFGE8, and CLP+MFGE8+CGT (Cilengitide). After CLP, CLP+MFGE8 rats received intracerebroventricular MFGE8 (3.3 µg), while CLP+MFGE8+CGT rats received intraperitoneal Cilengitide (10 mg/kg). We assessed cognitive function with the Morris water maze and open field test over five days. Eight days post-surgery, rats underwent T2-weighted magnetic resonance imaging (MRI) and resting state (rs)-fMRI scans. Brain tissues were collected for western blot, hematoxylin-eosin (HE) staining, and immunofluorescence. Statistical analysis employed one-way analysis of variance (ANOVA) followed by Tukey's post-test for multiple comparisons. MFGE8 improved neurobehavioral performance in open field task (OFT) and morris water maze (MWM) tests. fMRI indicated a significant reduction in abnormal neural activity in the right hippocampal CA1, CA3, and dentate gyrus of SAE rats following MFGE8 treatment. Voxel-based morphometry (VBM) analysis revealed decreased high-signal areas in the hippocampus, along with reduced hippocampal volume due to alleviated neural edema. Western blot analysis demonstrated that MFGE8 enhanced ras-related C3 botulinum toxin substrate 1 (Rac1) and microtubule-associated protein 1A/1B-light chain 3 (LC3) expression in the rat hippocampus, while CGT reduced these protein levels. Behavioral experiments and fMRI results confirmed that CGT reversed the cognitive effects of MFGE8 by inhibiting microglial αVβ3/αVβ5 integrin receptors. Our findings show that MFGE8 reduced amplitude of low-frequency fluctuations (ALFF) values in the right hippocampal CA1, CA3, and the dentate gyrus, mitigating abnormal neural activity and decreasing hippocampal volume. This led to an improvement in cognitive dysfunction in SAE rats. These results suggest that MFGE8 enhances microglial efferocytosis by activating αVβ3 and αVβ5 integrin receptors on microglial surfaces, ultimately improving cognitive function in SAE rats.

Abnormal functional connectivity of the putamen in obsessive-compulsive disorder

The putamen has been proposed to play a critical role in the development of obsessive-compulsive disorder (OCD). The primary objective of this study was to examine the resting-state regional activity and functional connectivity patterns of the putamen in individuals diagnosed with OCD. To achieve this, we employed resting-state functional magnetic resonance imaging (rs-fMRI) to collect data from a sample of 45 OCD patients and 53 healthy control participants. We aimed to use the regional amplitude of low-frequency fluctuation (ALFF) analysis to generate the ROI masks of the putamen and then conduct the whole brain functional connectivity of the putamen in individuals with OCD. Compared to controls, the OCD group demonstrated decreased ALFF in bilateral putamen. The right putamen also displayed decreased FC with the left putamen extending to the inferior frontal gyrus (IFG), bilateral precuneus extending to calcarine, the right middle occipital cortex extending to the right middle temporal cortex, and the left middle occipital gyrus. The decreased connectivity between the right putamen and the left IFG was negatively correlated with Yale-Brown Obsessive Compulsive scale (Y-BOCS) Obsession Scores. This study aimed to reveal the putamen changes in resting-state activity and connectivity in OCD patients, highlighting the significance of aberrant ALFF/FC of the putamen is a key characteristic of OCD.

Identifying the Shared and Dissociable Neural Bases between Self-Worth and Moral Ambivalence.

Self-ambivalence, a prevalent phenomenon in daily life, has been increasingly substantiated by research. It refers to conflicting self-views and evaluations, primarily concerning self-worth and morality. Previous behavioral research has distinguished self-worth and moral ambivalence, but it remains unclear whether they have separable neural bases. The present study addressed this question by examining resting-state brain activity (i.e., the fractional amplitude of low-frequency fluctuations, fALFF) and connectivity (i.e., resting-state functional connectivity, RSFC) in 112 college students. The results found that self-worth ambivalence was positively related to the fALFF in the orbitofrontal cortex (OFC) and left superior parietal lobule (SPL). The RSFC strength between the SPL and precuneus/posterior cingulate cortex (PCC) was positively related to self-worth ambivalence. Moral ambivalence was positively associated with the fALFF in the left SPL (extending into the temporoparietal junction) and right SPL. The RSFC strengths between the left SPL/TPJ and OFC, as well as the RSFC strengths between the right SPL as a seed and the bilateral middle and inferior temporal gyrus, were associated with moral ambivalence. Overall, the neural bases of self-worth and moral ambivalence are associated with the SPL and OFC, involved in attentional alertness and value representation, respectively. Additionally, the neural basis of moral ambivalence is associated with the TPJ, responsible for mentalizing.

The Use of fMRI Regional Analysis to Automatically Detect ADHD Through a 3D CNN-Based Approach.

Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by a reduced attention span, hyperactivity, and impulsive behaviors, which typically manifest during childhood. This study employs functional magnetic resonance imaging (fMRI) to use spontaneous brain activity for classifying individuals with ADHD, focusing on a 3D convolutional neural network (CNN) architecture to facilitate the design of decision support systems. We developed a novel deep learning model based on 3D CNNs using the ADHD-200 database, which comprises datasets from NeuroImage (NI), New York University (NYU), and Peking University (PU). We used fractional amplitude of low-frequency fluctuations (fALFF) and regional homogeneity (ReHo) data in three dimensions and performed a fivefold cross-validation to address the dataset imbalance. We aimed to verify the efficacy of our proposed 3D CNN by contrasting it with a fully connected neural network (FCNN) architecture. The 3D CNN achieved accuracy rates of 76.19% (NI), 69.92% (NYU), and 70.77% (PU) for fALFF data. The FCNN model yielded lower accuracy rates across all datasets. For generalizability, we trained on NI and NYU datasets and tested on PU. The 3D CNN achieved 69.48% accuracy on fALFF outperforming the FCNN. Our results demonstrate that using 3D CNNs for classifying fALFF data is an effective approach for diagnosing ADHD. Also, FCNN confirmed the efficiency of the designed model.

Clinical utility of fMRI in evaluating of LSD effect on pain-related brain networks in healthy subjects

ObjectiveWe aimed to evaluate the effect of Lysergic acid diethylamide (LSD) on the pain neural network (PNN) in healthy subjects using functional magnetic resonance imaging (fMRI). MethodsTwenty healthy volunteers participated in a balanced-order crossover study, receiving intravenous administration of LSD and placebo in two fMRI scanning sessions. Brain regions associated with pain processing were analyzed by amplitude of low-frequency fluctuation (ALFF), independent component analysis (ICA), functional connectivity and dynamic casual modeling (DCM). ResultsALFF analysis demonstrated that LSD effectively relieves pain due to modulation in the neural network associated with pain processing. ICA analysis showed more active voxels in anterior cingulate cortex (ACC), thalamus (THL)-left, THL-right, insula cortex (IC)-right, parietal operculum (PO)-left, PO-right and frontal pole (FP)-right in the placebo session than the LSD session. There were more active voxels in FP-left and IC-left in the LSD session compared to the placebo session. Functional brain connectivity was observed between THL-left and PO-right and between PO-left with FP-left, FP-right and IC-left in the placebo session. In the LSD session, functional connectivity of PO-left with FP-left and FP-right was observed. The effective connectivity between left anterior insula cortex (lAIC)-lAIC, lAIC-dorsolateral prefrontal cortex (dlPFC) and secondary somatosensory cortex (SII)-dlPFC were significantly different. Finally, the correlation between fMRI biomarkers and clinical pain criteria was calculated. ConclusionThis study enhances our understanding of the LSD effect on the architecture and neural behavior of pain in healthy subjects and provides great promise for future research in the field of cognitive science and pharmacology.

Structure-function interrelationships and associated neurotransmitter profiles in drug-naïve benign childhood epilepsy with central-temporal spikes patients.

To explore the interrelationships between structural and functional changes as well as the potential neurotransmitter profile alterations in drug-naïve benign childhood epilepsy with central-temporal spikes (BECTS) patients. Structural magnetic resonance imaging (sMRI) and resting-state functional MRI data from 20 drug-naïve BECTS patients and 33 healthy controls (HCs) were acquired. Parallel independent component analysis (P-ICA) was used to identify covarying components among gray matter volume (GMV) maps and fractional amplitude of low-frequency fluctuations (fALFF) maps. Furthermore, we explored the spatial correlations between GMV/fALFF changes derived from P-ICA and neurotransmitter maps in JuSpace toolbox. A significantly positive correlation (p < 0.001) was identified between one structural component (GMV_IC6) and one functional component (fALFF_IC4), which showed significant group differences between drug-naïve BECTS patients and HCs (GMV_IC6: p < 0.01; fALFF_IC4: p < 0.001). GMV_IC6 showed increased GMV in the frontal lobe, temporal lobe, thalamus, and precentral gyrus as well as fALFF_IC4 had enhanced fALFF in the cerebellum in drug-naïve BECTS patients compared to HCs. Moreover, significant correlations between GMV alterations in GMV_IC6 and the serotonin (5HT1a: p < 0.001; 5HT2a: p < 0.001), norepinephrine (NAT: p < 0.001) and glutamate systems (mGluR5: p < 0.001) as well as between fALFF alterations in fALFF_IC4 and the norepinephrine system (NAT: p < 0.001) were detected. The current findings suggest co-altered structural/functional components that reflect the correlation of language and motor networks as well as associated with the serotonergic, noradrenergic, and glutamatergic neurotransmitter systems. The relationship between anatomical brain structure and intrinsic neural activity was evaluated using a multimodal fusion analysis and neurotransmitters which might provide an important window into the multimodal neural and underlying molecular mechanisms of benign childhood epilepsy with central-temporal spikes. Structure-function relationships in drug-naïve benign childhood epilepsy with central-temporal spikes (BECTS) patients were explored. The interrelated structure-function components were found and correlated with the serotonin, norepinephrine, and glutamate systems. Co-altered structural/functional components reflect the correlation of language and motor networks and correlate with the specific neurotransmitter systems.

Intrinsic Infant Hippocampal Function Supports Inhibitory Processing.

Impaired cerebral inhibition is commonly observed in neurodevelopmental disorders and may represent a vulnerability factor for their development. The hippocampus plays a key role in inhibition among adults and undergoes significant and rapid changes during early brain development. Therefore, the structure represents an important candidate region for early identification of pathology that is relevant to inhibitory dysfunction. To determine whether hippocampal function corresponds to inhibition in the early postnatal period, the present study evaluated relationships between hippocampal activity and sensory gating in infants 4-20 weeks of age (N=18). Resting-state functional magnetic resonance imaging was used to measure hippocampal activity, including the amplitude of low-frequency fluctuations (ALFFs) and fractional ALFF. Electroencephalography during a paired-stimulus paradigm was used to measure sensory gating (P50). Higher activity of the right hippocampus was associated with better sensory gating (P50 ratio), driven by a reduction in response to the second stimulus. These findings suggest that meaningful effects of hippocampal function can be detected early in infancy. Specifically, higher intrinsic hippocampal activity in the early postnatal period may support effective inhibitory processing. Future work will benefit from longitudinal analysis to clarify the trajectory of hippocampal function, alterations of which may contribute to the risk of neurodevelopmental disorders and represent an intervention target.

Comparisons of the amplitude of low-frequency fluctuation and functional connectivity in major depressive disorder and social anxiety disorder: A resting-state fMRI study

BackgroundStudies comparing the brain functions of major depressive disorder (MDD) and social anxiety disorder (SAD) at the regional and network levels remain scarce. This study aimed to elucidate their pathogenesis using neuroimaging techniques and explore biomarkers that can differentiate these disorders. MethodsResting-state fMRI data were collected from 48 patients with MDD, 41 patients with SAD, and 82 healthy controls. Differences in the amplitude of low-frequency fluctuations (ALFF) among the three groups were examined to identify regions showing abnormal regional spontaneous activity. A seed-based functional connectivity (FC) analysis was conducted using ALFF results as seeds and different connections were identified between regions showing abnormal local spontaneous activity and other regions. The correlation between abnormal brain function and clinical symptoms was analyzed. ResultsPatients with MDD and SAD exhibited similar abnormal ALFF and FC in several brain regions; notably, FC between the right superior frontal gyrus (SFG) and the right posterior supramarginal gyrus (pSMG) in patients with SAD was negatively correlated with depressive symptoms. Furthermore, patients with MDD showed higher ALFF in the right SFG than HCs and those with SAD. LimitationPotential effects of medications, comorbidities, and data type could not be ignored. ConclusionMDD and SAD showed common and distinct aberrant brain function patterns at the regional and network levels. At the regional level, we found that the ALFF in the right SFG was different between patients with MDD and those with SAD. At the network level, we did not find any differences between these disorders.

Bulimia nervosa selectively reshapes the structure and intrinsic function of anterior insula subregions associated with cognition-emotion integration

BackgroundExisting evidence suggests that anterior insula plays a crucial role in cognitive control and emotional regulation and is implicated in the onset and maintenance of bulimia nervosa (BN). However, it remains unclear how structural and functional abnormalities in specific subregions of anterior insula contribute to BN. MethodsIn this study, we analyzed structural MRI and resting-state functional MRI data from 54 BN patients and 56 healthy controls (HCs). We conducted voxel-based morphometry, amplitude of low frequency fluctuation (conventional band: 0.01–0.08 Hz, slow-5: 0.01–0.027 Hz) and seed-based whole-brain functional connectivity (FC) analysis of the anterior insula subregions for both groups. Additionally, we investigated the correlation between neuroimaging findings and clinical characteristics in the BN group. ResultsOur findings revealed that BN patients exhibited reduced gray matter volume in the right dorsal anterior insula (dAI) and bilateral ventral anterior insula (vAI) and demonstrated decreased ALFF in slow-5 band of bilateral dAI. The BN group also showed increased FC between bilateral dAI and precuneus or right superior frontal gyri which significantly correlated with the severity of BN or its key symptom. In addition, the decreased FC between bilateral vAI and anterior cingulate and paracingulate gyri and/or median cingulate and paracingulate gyri were both significantly correlated with the severity and its restrained eating behavior. ConclusionsOur findings further indicate that the functional separation of anterior insula subregions may underlie the pathophysiology of BN. Notably, the vAI associated with emotional processing may serve as a promising neuroimaging biomarker which could inform therapeutic strategy.

Functional MRI-based biomarkers of insomnia with objective short sleep duration phenotype

BackgroundInsomnia disorder with objective short sleep duration (ISS) phenotype is a more serious biological subtype than insomnia with objective normal sleep duration (INS) phenotype, and the neuroimaging data is helpful to understand the pathophysiology of the ISS phenotype. This study was to compare the amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), and functional connectivity (FC) between the ISS phenotype and the INS phenotype. MethodsIn this cross-sectional study, 55 patients with insomnia disorder were recruited, and 22 of them were defined as the ISS phenotype by the objective cardiopulmonary coupling (CPC) technique. The blood oxygen level-dependent (BOLD) sequences of all participants were obtained using the 3.0 T magnetic resonance imaging system. We analyzed and compared the ALFF, ReHo, and FC between the ISS phenotype and the INS phenotype. We also conducted Pearson's correlation analysis between significant neuroimaging biomarkers and the CPC parameters. ResultsThe differences were not significant in ALFF (PFWE-corr＞0.05) or ReHo (PFWE-corr＞0.05) between the ISS phenotype and the INS phenotype. For the FC analysis, the ISS phenotype had a Hub-node of the left inferior occipital gyrus (IOG.L), with significantly decreased connections (p＜0.001) in the bilateral occipital, parietal, and temporal regions. The significant FCs were closely related to sleep parameters. ConclusionThe left inferior occipital gyrus (IOG.L), as a Hub-node with decreased functional connections, may be a potential fMRI-based biomarker of the ISS phenotype.