Resting-state Research Articles

Motor impulsivity and spicy food craving: A mediation analysis of insula-based resting state functional connectivity.

In China, the rate of spicy food consumption is rising, and chili pepper is among the most popular spicy foods consumed nationwide. However, little effort has been made to understand the mechanism behind spicy food craving. This exploratory study aimed to investigate differences in insula-based resting state functional connectivity (rsFC) between spicy food cravers and non-cravers, and the association between rsFC, impulsivity and spicy food craving. A group of extreme cravers (n = 49) and a group of age- and sex-matched non-cravers (n = 46) completed a resting-state fMRI scan, during which participants were instructed to keep their eyes closed, to not think of anything in particular, and to remain awake. Participants completed the Spicy Food Craving Questionnaire, Barratt Impulsiveness Scale, Sensation Seeking Scale and Positive and Negative Affect Schedule, and rated the frequency of spicy food intake. Results revealed increased insula-occipital lobe resting-state functional connectivity in individuals with spicy food cravings, and the positive correlations between insula-middle occipital gyrus rsFC, impulsivity and spicy food craving. Specifically, the insula-middle occipital gyrus rsFC strength mediated the relationship between the motor impulsivity and spicy food craving. It is hoped that our exploratory findings may shed new insights into the neural mechanisms of spicy food craving and motivate further exploration of spicy food craving in diverse contexts and cultures.

Abnormal resting-state functional connectivity of hippocampal subregions in type 2 diabetes mellitus-associated cognitive decline.

Type 2 diabetes mellitus (T2DM) over time predisposes to inflammatory responses and abnormalities in functional brain networks that damage learning, memory, or executive function. The hippocampus is a key region often reporting connectivity abnormalities in memory disorders. Here, we investigated peripheral inflammatory responses and resting-state functional connectivity (RSFC) changes characterized of hippocampal subregions in type 2 diabetes-associated cognitive decline (T2DACD). The study included 16 patients with T2DM, 16 patients with T2DACD and 25 healthy controls (HCs). Subjects were assessed for cognitive performance, tested for the expression of inflammatory factors IL-6, IL-10 and TNF-α in peripheral serum, underwent resting-state functional magnetic resonance imaging scans, and analyzed for RSFC using the hippocampal subregions as seeds. We also calculated the correlation between cognitive performance and RSFC of hippocampal subregion, and analyzed the significantly altered RSFC values of T2DACD for Receiver Operating Characteristic (ROC) analysis. T2DACD patients showed a decline in their ability to complete cognitive assessment scales and experimental paradigms, and T2DM did not show abnormal cognitive performance. IL-6 expression was increased in peripheral serum in both T2DACD and T2DM. Compared with HCs, T2DACD showed abnormalities RSFC of the left anterior hippocampus with left precentral gyrus and left angular gyrus. T2DM showed abnormalities RSFC of the left middle hippocampus with right medial frontal gyrus, right anterior and middle hippocampus with left precuneus, left anterior hippocampus with right precuneus and right posterior middle temporal gyrus. Compared with T2DM, T2DACD showed abnormalities RSFC of the left posterior hippocampus and right middle hippocampus with left precuneus. In addition, RSFC in the left posterior hippocampus with left precuneus of T2DACD was positively correlated with Flanker conflict response time (r=0.766, P=0.001). In the ROC analysis, the significantly altered RSFC values of T2DACD achieved significant performance. T2DACD showed a significant decrease in attentional inhibition and working memory, peripheral pro-inflammatory response increased, and abnormalities RSFC of the hippocampal subregions with default mode network and sensory-motor network. T2DM did not show a significant cognitive decline, but peripheral pro-inflammatory response increased and abnormalities RSFC of the hippocampus subregions occurred in the brain. In addition, the left precuneus may be a key brain region in the conversion of T2DM to T2DACD. The results of this study may provide a basis for the preliminary diagnosis of T2DACD.

MRI economics: Balancing sample size and scan duration in brain wide association studies.

A pervasive dilemma in neuroimaging is whether to prioritize sample size or scan time given fixed resources. Here, we systematically investigate this trade-off in the context of brain-wide association studies (BWAS) using functional magnetic resonance imaging (fMRI). We find that total scan duration (sample size × scan time per participant) robustly explains individual-level phenotypic prediction accuracy via a logarithmic model, suggesting that sample size and scan time are broadly interchangeable up to 20-30 min of data. However, the returns of scan time diminish relative to sample size, which we explain with principled theoretical derivations. When accounting for fixed overhead costs associated with each participant (e.g., recruitment, non-imaging measures), prediction accuracy in many small-scale and some large-scale BWAS might benefit from longer scan time than typically assumed. These results generalize across phenotypic domains, scanners, acquisition protocols, racial groups, mental disorders, age groups, as well as resting-state and task-state functional connectivity. Overall, our study emphasizes the importance of scan time, which is ignored in standard power calculations. Standard power calculations maximize sample size, at the expense of scan time, which can result in sub-optimal prediction accuracies and inefficient use of resources. Our empirically informed reference is available for future study design: WEB_APPLICATION_LINK.

Changes in functional and structural brain connectivity following bilateral hand transplantation

As a surgical treatment following amputation or loss of an upper limb, nearly 200 hand transplantations have been completed to date. We report here a magnetic resonance imaging (MRI) investigation of functional and structural brain connectivity for a bilateral hand transplant patient (female, 60 years of age), with a preoperative baseline and three postoperative testing sessions each separated by approximately six months. We used graph theoretical analyses to estimate connectivity within and between modules (networks of anatomical nodes), particularly a sensorimotor network (SMN), from resting-state functional MRI and structural diffusion-weighted imaging (DWI). For comparison, corresponding MRI measures of connectivity were obtained from 10 healthy, age-matched controls, at a single testing session. The patient's within-module functional connectivity (both SMN and non-SMN modules), and structural within-SMN connectivity, were higher preoperatively than that of the controls, indicating a response to amputation. Postoperatively, the patient's within-module functional connectivity decreased towards the control participants' values, across the 1.5 years postoperatively, particularly for hand-related nodes within the SMN module, suggesting a return to a more canonical functional organization. Whereas the patient's structural connectivity values remained relatively constant postoperatively, some evidence suggested that structural connectivity supported the postoperative changes in within-module functional connectivity.

Whole brain causal functional connectivity analysis of noise-induced deafness based on resting state-functional magnetic resonance imaging

Objective: To investigate the changes of directional connections of auditory and non-auditory in patients with noise-induced deafness (NID) by degree centrality (DC) and Granger causality analysis (GCA), and to explore the mode of brain function remodeling after NID. Methods: In October 2023, a total of 58 patients diagnosed with NID by the Occupational Diseases Department of Yantaishan Hospital of Yantai from 2014 to 2022 were collected as case group (NID group), and 42 healthy volunteers matched by gender, age and education level were selected as the control group (HC group). Resting state-functional magnetic resonance imaging (Rs-fMRI) was perfomed and PC analysis was performed. The brain regions with statistically significant differences in DC values between groups and the bilateral Heschl regions were extracted as regions of interest (ROI) for voxel-based whole brain GCA and correlation analysis. Results: Compared with HC group, the SOG.L DC value of NID group was lower, the connectivity values of SFGdor.L to SOG.L was increased, the connectivity value of PCL.L to SOG.L was decreased, the connectivity values of ORBmid.L, PCG.R and CUN. L/R to HES.L were increased, the connectivity value of SFGdor.L to HES.L was decreased, the connectivity value of HES.L to PCUN.L was decreased, the connectivity values of ORBsup.L and PCG.R to HES.R were increased, the connectivity value of HES.R to CUN.L was decreased (P voxel level<0.01, P cluster level<0.05). The connectivity value of PCL.L to SOG.L was negatively correlated with the weighted value of the better whisper frequency (P<0.05) . Conclusion: The NID patients have abnormal directional connectivity activity in multiple brain regions, such as auditory vision, executive control, somatosensory movement, and default mode network. It is suggested that hearing loss may cause complex neural remodeling between auditory and non-auditory centers.

Abnormal Dynamic Reconfiguration of Multilayer Temporal Networks in Patients with Bipolar Disorder.

Multilayer networks have been used to identify abnormal dynamic reconfiguration in bipolar disorder (BD). However, these studies ignore the differences in information interactions between adjacent layers when constructing multilayer networks, and the analysis of dynamic reconfiguration is not comprehensive enough; Methods: Resting-state functional magnetic resonance imaging data were collected from 46 BD patients and 54 normal controls. A multilayer temporal network was constructed for each subject, and inter-layer coupling of different nodes was considered using network similarity. The promiscuity, recruitment, and integration coefficients were calculated to quantify the different dynamic reconfigurations between the two groups; Results: The global inter-layer coupling, recruitment, and integration coefficients were significantly lower in BD patients. These results were further observed in the attention network and the limbic/paralimbic and subcortical network, reflecting reduced temporal stability, intra- and inter-subnetwork communication abilities in BD patients. The whole-brain promiscuity was increased in BD patients. The same results were observed in the somatosensory/motor and auditory network, reflecting more functional interactions; Conclusions: This study discovered abnormal dynamic interactions of BD from the perspective of dynamic reconfiguration, which can help to understand the pathological mechanisms of BD.

Unearthing the hidden links: Investigating the functional connectivity between amygdala subregions and brain networks in bipolar disorder through resting-state fMRI

IntroductionBipolar disorder is a multifaceted psychiatric condition characterized by fluctuating activity levels and dysfunctional mood states, oscillating between manic and depressive episodes. These mood disturbances are accompanied by persistent functional and cognitive impairments, even during periods of euthymia. Prior studies have underscored the critical role of amygdala activity in the pathophysiology of bipolar disorder. This research aims to utilize resting-state functional Magnetic Resonance Imaging (rs-fMRI) to explore the functional modifications in the six sub-regions that compose the amygdala of individuals diagnosed with bipolar disorder. MethodThe study encompassed 80 participants, bifurcated into two groups: 40 individuals with bipolar disorder and 40 healthy controls. Each group comprised an equal gender distribution of 20 females and 20 males, ranging in age from 21 to 50 years. Using rs-fMRI, we examined the functional connectivity within six amygdala sub-regions across eight regional functional networks. ResultsComparative analysis between the control group and the bipolar patients revealed that all six amygdala sub-regions demonstrated connectivity with the eight functional brain networks. Notable similarities and disparities were observed in the connectivity patterns between the bipolar group and controls, particularly within the amygdala's sub-regions and other brain networks. The most significant functional connectivity alterations were found with the salience network and the default mode network. Additionally, alterations in the functional connectivity between the amygdala, sensory-motor, and visual networks were noted in bipolar patients. ConclusionThe study's findings highlight the distinct patterns of resting-state functional connectivity of the amygdala and various brain networks in differentiating bipolar patients from healthy controls. These variations suggest the existence of multiple pathophysiological mechanisms contributing to emotional dysregulation in bipolar disorder.

Alterations of perfusion and functional connectivity of the cingulate motor area are associated with psychomotor retardation in major depressive disorder

AbstractPsychomotor retardation, characterized by slowing of speech, thoughts, and a decrease of movements, is frequent in patients with major depressive disorder (MDD). However, its neurobiological correlates are still poorly understood. This study aimed to explore if cerebral blood flow (CBF) and resting state functional connectivity (rs-FC) of the motor network are altered in patients with MDD and if these changes are associated with psychomotor retardation. Thirty-six right-handed patients with depression and 19 right-handed healthy controls (HC) that did not differ regarding age and sex underwent arterial spin labelling (ASL) and resting-state functional MRI (rs-fMRI) scans. Psychomotor retardation was assessed with the motoric items of the core assessment of psychomotor change (CORE) questionnaire. Patients with MDD had more pronounced psychomotor retardation scores than HC. Patients with MDD had reduced CBF in bilateral cingulate motor area (CMA) and increased resting-state functional connectivity (rs-FC) between the cluster in the CMA and a cluster localized in bilateral supplementary motor areas (SMA). Furthermore, increased rs-FC between the CMA and the left SMA was associated with more pronounced psychomotor retardation. Our results suggest that reduced perfusion of the CMA and increased rs-FC between the CMA and the SMA are associated with psychomotor retardation in patients with depression.

Altered static brain activity and functional connectivity after heat stroke.

This study aimed to investigate the alteration of brain function based on resting-state functional MRI in patients after heat stroke. This study included 10 cases of patients after heat stroke and 10 cases of healthy controls. Abnormal brain function was calculated using amplitude of low-frequency fluctuations (ALFF) and degree centrality analysis, as well as functional connectivity analysis based on regions of interest (ROI). Correlation analyses were performed to evaluate the association between brain function changes and clinical scales. Combining ALFF and degree centrality results, the decreased brain regions included the left cuneus and the right angular gyrus, while the increased brain regions included the right cerebellar_Crus1. Using the left cuneus with significant differences in ALFF and degree centrality as ROI, the functional connectivity results revealed decreased brain regions including bilateral lingual gyrus, bilateral postcentral cingulate gyrus, and left precentral gyrus. The degree centrality value of the right cerebellar_Crus1 was positively correlated with glasgow coma scale (GCS) scores ( r = 0.726, P = 0.027), and the functional connectivity value of the right posterior cingulate gyrus was positively correlated with GCS scores ( r = 0.717, P = 0.030). Heat stroke patients exhibit abnormal activity in multiple brain regions, which has important clinical significance for evaluating the severity of the disease.

Divergent pattern of functional connectivity within the dorsal attention network differentiates schizophrenia and bipolar disorder patients.

Schizophrenia (SZ) and bipolar disorder (BD) share common clinical features, symptoms, and neurocognitive deficits, which results in common misdiagnosis. Recently, it has been suggested that alterations within brain networks associated with perceptual organization yield potential to distinguish SZ and BD individuals. The aim of our study was to evaluate whether functional connectivity (FC) of the dorsal attention network (DAN) may differentiate both conditions. The study involved 90 participants: 30 remitted SZ patients, 30 euthymic BD patients, and 30 healthy controls (HC). Resting state functional magnetic resonance imaging was used to compare the groups in terms of the FC within the core nodes of the DAN involving frontal eye fields (FEF) and intraparietal sulcus (IPS). BD patients presented weaker inter-hemispheric FC between right and left FEF than HC. While SZ did not differ from HC in terms of inter-FEF connectivity, they presented increased inter- and intra-hemispheric FC between FEF and IPS. When compared with BD, SZ patients showed increased FC between right FEF and other nodes of the network (bilateral IPS and left FEF). We have shown that altered resting state FC within DAN differentiates BD, SZ, and HC groups. Divergent pattern of FC within DAN, consisting of hypoconnectivity in BD and hyperconnectivity in SZ, might yield a candidate biomarker for differential diagnosis between both conditions. More highly powered studies are needed to confirm these possibilities.

A Novel Directed Seed-Based Connectivity Analysis Toolbox Applied to Human and Marmoset Resting-State FMRI

Estimating the direction of functional connectivity (FC) can help further elucidate complex brain function. However, the estimation of directed FC at the voxel level in fMRI data, and evaluating its performance, has yet to be done. We therefore developed a novel directed seed-based connectivity analysis (SCA) method based on normalized pairwise Granger causality that provides greater detail and accuracy over ROI-based methods. We evaluated its performance against 145 cortical retrograde tracer injections in male and female marmosets that were used as ground truth cellular connectivity on a voxel-by-voxel basis. The receiver operating characteristic (ROC) curve was calculated for each injection, and we achieved area under the ROC curve of 0.95 for undirected and 0.942 for directed SCA in the case of high cell count threshold. This indicates that SCA can reliably estimate the strong cellular connections between voxels in fMRI data. We then used our directed SCA method to analyze the human default mode network (DMN) and found that dlPFC (dorsolateral prefrontal cortex) and temporal lobe were separated from other DMN regions, forming part of the language-network that works together with the core DMN regions. We also found that the cerebellum (Crus I-II) was strongly targeted by the posterior parietal cortices and dlPFC, but reciprocal connections were not observed. Thus, the cerebellum may not be a part of, but instead a target of, the DMN and language-network. Summarily, our novel directed SCA method, visualized with a new functional flat mapping technique, opens a new paradigm for whole-brain functional analysis.

New Insights into Freezing of Gait in Parkinson's Disease from Spectral Dynamic Causal Modeling.

Freezing of gait is one of the most disturbing motor symptoms of Parkinson's disease (PD). However, the effective connectivity between key brain hubs that are associated with the pathophysiological mechanism of freezing of gait remains elusive. The aim of this study was to identify effective connectivity underlying freezing of gait. This study applied spectral dynamic causal modeling (DCM) of resting-state functional magnetic resonance imaging in dedicated regions of interest determined using a data-driven approach. Abnormally increased functional connectivity between the bilateral dorsolateral prefrontal cortex (DLPFC) and the bilateral mesencephalic locomotor region (MLR) was identified in freezers compared with nonfreezers. Subsequently, spectral DCM analysis revealed that increased top-down excitatory effective connectivity from the left DLPFC to bilateral MLR and an independent self-inhibitory connectivity within the left DLPFC in freezers versus nonfreezers (>99% posterior probability) were inversely associated with the severity of freezing of gait. The lateralization of these effective connectivity patterns was not attributable to the initial dopaminergic deficit nor to structural changes in these regions. We have identified novel effective connectivity and an independent self-inhibitory connectivity underlying freezing of gait. Our findings imply that modulating the effective connectivity between the left DLPFC and MLR through neurostimulation or other interventions could be a target for reducing freezing of gait in PD. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Static and temporal dynamic alterations of local functional connectivity in chronic insomnia.

Several studies have revealed altered intrinsic neural activity in chronic insomnia (CI). However, the temporal variability of intrinsic neural activity in CI is rarely mentioned. This study aimed to explore static and temporal dynamic alterations of regional homogeneity (ReHo) in CI and excavate the potential associations between these changes and clinical characteristics.Eighty-seven patients with CI and seventy-eight healthy controls (HCs) were included. Resting-state functional magnetic resonance imaging was performed on all subjects and both static and dynamic ReHo were used to detect local functional connectivity. We then tested the relationship between altered brain regions, disease duration, and clinical scales. The receiver operating characteristic curve analysis was used to reveal the potential capability of these indicators to screen CI patients from HCs.CI showed increased dynamic ReHo in the right precuneus and decreased static ReHo in the right cerebellum_6. The dynamic ReHo values of the right precuneus were negatively correlated with the self-rating depression score and the static ReHo values of the right cerebellum_6 were positively correlated with the Montreal Cognitive Assessment-Naming score. In addition, the combination of the two metrics showed a potential capacity to distinguish CI patients from HCs, which was better than a single metric alone.The present study has revealed the altered local functional connectivity under static and temporal dynamic conditions in patients with CI, and found the relationships between these changes, mood-related scales, and cognitive-related scales. These may be useful in elucidating the neurological mechanisms of CI and accompanying symptoms.

Prediction of individual performance and verbal intelligence scores from resting-state fMRI in children and adolescents.

The neuroimaging basis of intelligence remains elusive; however, there is a growing body of research employing connectome-based predictive modeling to estimate individual intelligence scores, aiming to identify the optimal set of neuroimaging features for accurately predicting an individual's cognitive abilities. Compared to adults, the disparities in cognitive performance among children and adolescents are more likely to captivate individuals' interest and attention. Limited research has been dedicated to exploring neuroimaging markers of intelligence specifically in the pediatric population. In this study, we utilized resting-state functional magnetic resonance imaging (fMRI) and intelligence quotient (IQ) scores of 170 healthy children and adolescents obtained from a public database to identify brain functional connectivity markers associated with individual intellectual behavior. Initially, we extracted and summarized relevant resting-state features from whole-brain or functional network connectivity that were most pertinent to IQ scores. Subsequently, these features were employed to establish prediction models for both performance and verbal IQ scores. Within a 10-fold cross-validation framework, our findings revealed that prediction models based on whole-brain functional connectivity effectively predicted performance IQ scores( ) but not verbal IQ scores( ). Results of prediction models based on brain functional network connectivity further demonstrated the exceptional predictive ability of the default mode network (DMN) and fronto-parietal task control network (FTPN) for performance IQ scores ( ). The above findings have also been validated using an independent dataset. Our findings suggest that the performance IQ of children and adolescents primarily relies on the connectivity of brain regions associated with DMN and FTPN. Moreover, variations in intellectual performance during childhood and adolescences are closely linked to alterations in brain functional network connectivity.

PD-ARnet: a deep learning approach for Parkinson’s disease diagnosis from resting-state fMRI

Objective. The clinical diagnosis of Parkinson's disease (PD) relying on medical history, clinical symptoms, and signs is subjective and lacks sensitivity. Resting-state fMRI (rs-fMRI) has been demonstrated to be an effective biomarker for diagnosing PD.Approach.This study proposes a deep learning approach for the automatic diagnosis of PD using rs-fMRI, named PD-ARnet. Specifically, PD-ARnet utilizes Amplitude of Low Frequency Fluctuations and Regional Homogeneity extracted from rs-fMRI as inputs. The inputs are then processed through a developed dual-branch 3D feature extractor to perform advanced feature extraction. During this process, a Correlation-Driven weighting module is applied to capture complementary information from both features. Subsequently, the Attention-Enhanced fusion module is developed to effectively merge two types of features, and the fused features are input into a fully connected layer for automatic diagnosis classification.Main results.Using 145 samples from the PPMI dataset to evaluate the detection performance of PD-ARnet, the results indicated an average classification accuracy of 91.6% (95% confidence interval [CI]: 90.9%, 92.4%), precision of 94.7% (95% CI: 94.2%, 95.1%), recall of 86.2% (95% CI: 84.9%, 87.4%), F1 score of 90.2% (95% CI: 89.3%, 91.1%), and AUC of 92.8% (95% CI: 91.1%, 95.0%).Significance.The proposed method has the potential to become a clinical auxiliary diagnostic tool for PD, reducing subjectivity in the diagnostic process, and enhancing diagnostic efficiency and consistency.

Evaluation of Intra- and Inter-Network Connectivity within Major Brain Networks in Drug-Resistant Depression Using rs-fMRI.

Background: Major Depressive Disorder (MDD) is a significant challenge in modern medicine due to its unclear underlying causes. Brain network dysfunction is believed to play a key role in its pathophysiology. Resting-state functional MRI (rs-fMRI), a neuroimaging technique, enables the in vivo assessment of functional connectivity (FC) between brain regions, offering insights into these network dysfunctions. The aim of this study was to evaluate abnormalities in FC within major brain networks in patients with drug-resistant MDD. Methods: The study group consisted of 26 patients with drug-resistant MDD and an age-matched control group (CG) of 26 healthy subjects. The rs-fMRI studies were performed on a 3T MR scanner (Philips, Ingenia) using a 32-channel head and neck coil. Imaging data were statistically analyzed, focusing on the intra- and inter-network FC of the following networks: default mode (DMN), sensorimotor (SMN), visual (VN), salience (SN), cerebellar (CN), dorsal attention (DAN), language (LN), and frontoparietal (FPN). Results: In patients with MDD, the intra-network analysis showed significantly decreased FC between nodes within VN compared to CG. In contrast, the inter-network analysis showed significantly increased FC between nodes from VN and SN or VN and DAN compared to CG. Decreased FC was found between SN and CN or SN and FPN as well as VN and DAN nodes compared to CG. Conclusions: Patients with MDD showed significant abnormalities in resting-state cortical activity, mainly regarding inter-network functional connectivity. These results contribute to the knowledge on the pathomechanism of MDD and may also be useful for developing new treatments.

From gut to brain: unveiling probiotic effects through a neuroimaging perspective-A systematic review of randomized controlled trials.

The gut-brain axis, a bidirectional communication network between the gastrointestinal system and the brain, significantly influences mental health and behavior. Probiotics, live microorganisms conferring health benefits, have garnered attention for their potential to modulate this axis. However, their effects on brain function through gut microbiota modulation remain controversial. This systematic review examines the effects of probiotics on brain activity and functioning, focusing on randomized controlled trials using both resting-state and task-based functional magnetic resonance imaging (fMRI) methodologies. Studies investigating probiotic effects on brain activity in healthy individuals and clinical populations (i.e., major depressive disorder and irritable bowel syndrome) were identified. In healthy individuals, task-based fMRI studies indicated that probiotics modulate brain activity related to emotional regulation and cognitive processing, particularly in high-order areas such as the amygdala, precuneus, and orbitofrontal cortex. Resting-state fMRI studies revealed changes in connectivity patterns, such as increased activation in the Salience Network and reduced activity in the Default Mode Network. In clinical populations, task-based fMRI studies showed that probiotics could normalize brain function in patients with major depressive disorder and irritable bowel syndrome. Resting-state fMRI studies further suggested improved connectivity in mood-regulating networks, specifically in the subcallosal cortex, amygdala and hippocampus. Despite promising findings, methodological variability and limited sample sizes emphasize the need for rigorous, longitudinal research to clarify the beneficial effects of probiotics on the gut-brain axis and mental health.

The development and structure of the HEALthy Brain and Child Development (HBCD) Study EEG protocol

The HEALthy Brain and Child Development (HBCD) Study, a multi-site prospective longitudinal cohort study, will examine human brain, cognitive, behavioral, social, and emotional development beginning prenatally and planned through early childhood. Electroencephalography (EEG) is one of two brain imaging modalities central to the HBCD Study. EEG records electrical signals from the scalp that reflect electrical brain activity. In addition, the EEG signal can be synchronized to the presentation of discrete stimuli (auditory or visual) to measure specific cognitive processes with excellent temporal precision (e.g., event-related potentials; ERPs). EEG is particularly helpful for the HBCD Study as it can be used with awake, alert infants, and can be acquired continuously across development. The current paper reviews the HBCD Study’s EEG/ERP protocol: (a) the selection and development of the tasks (Video Resting State, Visual Evoked Potential, Auditory Oddball, Face Processing); (b) the implementation of common cross-site acquisition parameters and hardware, site setup, training, and initial piloting; (c) the development of the preprocessing pipelines and creation of derivatives; and (d) the incorporation of equity and inclusion considerations. The paper also provides an overview of the functioning of the EEG Workgroup and the input from members across all steps of protocol development and piloting.

Telehealth-delivered cognitive behavioral therapy - a potential solution to improve sleep quality and normalize the salience network in fibromyalgia: a pilot randomized trial.

Our study investigated the associations between the clinical benefits of telehealth-delivered cognitive behavioral therapy for insomnia (tele-CBT-I) and the salience network in fibromyalgia (FM). Thirty-five FM patients with comorbid insomnia were recruited and assigned into two groups: the tele-CBT-I group (n = 17) or the treatment-as-usual (TAU) group (n = 18). At baseline and post-treatment, clinical status was assessed using standardized scales, including the Insomnia Severity Index (ISI), Brief Pain Inventory, Numeric Pain Rating scale, Beck Depression Intervention version II, Beck Anxiety Intervention, Situational Fatigue Scale, and Fibromyalgia Impact Questionnaires. Resting-state functional magnetic resonance imaging was collected. We compared within- and between-group differences in clinical changes and functional connectivity (FC) of the salience network. A factor analysis of significant FCs was performed. Correlation analyses between clinical symptoms and salience FCs were conducted. The tele-CBT-I group showed sleep quality improvements after treatment that were greater than those in the TAU group (p-value = 0.038). After treatment, tele-CBT-I decreased FCs of cortical regions and increased FCs of subcortical regions compared to the TAU group. Additionally, factor analysis grouped the significant FCs into cortical factors and subcortical factors. The cortical factor value, representing the involvement of specific cortical regions of the salience network by the factor analysis, was significantly associated with ISI scores in the tele-CBT-I group (p-value = 0.0002). In conclusion, tele-CBT-I might be an adjuvant approach to improve sleep quality and normalize cortical and subcortical functions of the salience network in FM patients with comorbid insomnia.

The Mindful Brain: A Systematic Review of the Neural Correlates of Trait Mindfulness.

Trait self-report mindfulness scales measure one's disposition to pay nonjudgmental attention to the present moment. Concerns have been raised about the validity of trait mindfulness scales. Despite this, there is extensive literature correlating mindfulness scales with objective brain measures, with the goal of providing insight into mechanisms of mindfulness, and insight into associated positive mental health outcomes. Here, we systematically examined the neural correlates of trait mindfulness. We assessed 68 correlational studies across structural magnetic resonance imaging, task-based fMRI, resting-state fMRI, and EEG. Several consistent findings were identified, associating greater trait mindfulness with decreased amygdala reactivity to emotional stimuli, increased cortical thickness in frontal regions and insular cortex regions, and decreased connectivity within the default-mode network. These findings converged with results from intervention studies and those that included mindfulness experts. On the other hand, the connections between trait mindfulness and EEG metrics remain inconclusive, as do the associations between trait mindfulness and between-network resting-state fMRI metrics. ERP measures from EEG used to measure attentional or emotional processing may not show reliable individual variation. Research on body awareness and self-relevant processing is scarce. For a more robust correlational neuroscience of trait mindfulness, we recommend larger sample sizes, data-driven, multivariate approaches to self-report and brain measures, and careful consideration of test-retest reliability. In addition, we should leave behind simplistic explanations of mindfulness, as there are many ways to be mindful, and leave behind simplistic explanations of the brain, as distributed networks of brain areas support mindfulness.