Double-wavelet transform for multi-subject resting state functional magnetic resonance imaging data.

Sports-related concussions are currently diagnosed through multi-domain assessment by a medical professional and may utilize neurocognitive testing as an aid. However, these tests have only been able to detect differences in the days to week post-concussion. Here, we investigate a measure of brain function, namely resting state functional connectivity, which may detect residual brain differences in the weeks to months after concussion. Twenty-one student athletes (9 concussed within 6months of enrollment; 12 non-concussed; between ages 18 and 22years) were recruited for this study. All participants completed the Wisconsin Card Sorting Task and the Color-Word Interference Test. Neuroimaging data, specifically resting state functional Magnetic Resonance Imaging data, were acquired to examine resting state functional connectivity. Two sample t-tests were used to compare the neurocognitive scores and resting state functional connectivity patterns among concussed and non-concussed participants. Correlations between neurocognitive scores and resting state functional connectivity measures were also determined across all subjects. There were no significant differences in neurocognitive performance between concussed and non-concussed groups. Concussed subjects had significantly increased connections between areas of the brain that underlie executive function. Across all subjects, better neurocognitive performance corresponded to stronger brain connectivity. Even at rest, brains of concussed athletes may have to 'work harder' than their healthy peers to achieve similar neurocognitive results. Resting state brain connectivity may be able to detect prolonged brain differences in concussed athletes in a more quantitative manner than neurocognitive test scores.

The pathogenesis of insomnia is related to the dysfunction of the thalamus. Transcutaneous auricular vagus nerve stimulation (taVNS) has proved to be effective in treating insomnia. However, whether taVNS alleviates insomnia through modulating thalamus-related functional connectivity remains unclear. To elucidate the instant modulating effects of taVNS on the resting state functional connectivity (RSFC) of the thalamus, 20 patients with insomnia disorder were recruited to receive taVNS treatment and their resting state functional magnetic resonance imaging (fMRI) data were collected immediately before and after stimulation. The fMRI data were compared with 20 age- and gender-matched healthy subjects who received no stimulation and had RSFC fMRI data collected once. RSFC analyses of the thalamus were performed in both groups. In addition to assessing the group differences between ID patients and healthy controls regarding the RSFC of the thalamus, we examined the taVNS-induced changes of RSFC of the thalamus in ID patients. Before taVNS treatment, the ID patients showed increased RSFC of the thalamus with the right insula and inferior frontal gyrus than healthy controls. After taVNS treatment, the RSFC between the thalamus and the right angular gyrus, left anterior cingulate gyrus, and precuneus were significantly decreased in patients. This study provides insights into the instant brain effects involving the thalamus-related functional connectivity of taVNS performed on insomnia disorder patients.

Dimensional Brain-Behavior Relationships in Children with Attention-Deficit/Hyperactivity Disorder

ObjectiveTo observe characteristics of the amplitudes of low-frequency oscillation (LFO) in first-episode drug-naive patients with major depressive disorder (MDD).MethodsAmplitudes of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF) were computed using resting-state functional magnetic resonance imaging (rs-fMRI) data of 39 first-episode drug-naive patients with MDD and 37 healthy controls.ResultsALFF and fALFF in the left cerebellum were significantly higher in patients with MDD compared to control group, while ALFF in the right rolandic operculum was significantly lower (all p < 0.001, AlphaSim correction).ConclusionAbnormal neurological activity in multiple brain regions in first-episode drug-naive patients with MDD may be involved in the neurobiological mechanisms of MDD and should be considered in future studies.

The carotenoids lutein (L) and zeaxanthin (Z) accumulate in retinal regions of the eye and have long been shown to benefit visual health. A growing literature suggests cognitive benefits as well, particularly in older adults. The present randomized controlled trial sought to investigate the effects of L and Z on brain function using resting state functional magnetic resonance imaging (fMRI). It was hypothesized that L and Z supplementation would (1) improve intra-network integrity of default mode network (DMN) and (2) reduce inter-network connectivity between DMN and other resting state networks. 48 community-dwelling older adults (mean age = 72years) were randomly assigned to receive a daily L (10mg) and Z (2mg) supplement or a placebo for 1year. Resting state fMRI data were acquired at baseline and post-intervention. A dictionary learning and sparse coding computational framework, based on machine learning principles, was used to investigate intervention-related changes in functional connectivity. DMN integrity was evaluated by calculating spatial overlap rate with a well-established DMN template provided in the neuroscience literature. Inter-network connectivity was evaluated via time series correlations between DMN and nine other resting state networks. Contrary to expectation, results indicated that L and Z significantly increased rather than decreased inter-network connectivity (Cohen's d = 0.89). A significant intra-network effect on DMN integrity was not observed. Rather than restoring what has been described in the available literature as a "youth-like" pattern of intrinsic brain activity, L and Z may facilitate the aging brain's capacity for compensation by enhancing integration between networks that tend to be functionally segregated earlier in the lifespan.

Major depressive disorder (MDD) is a leading cause of disability worldwide, yet current treatment strategies remain limited in their mechanistic diversity. Recent evidence has highlighted a promising novel pharmaceutical target—the KCNQ-type potassium channel—for the treatment of depressive disorders, which may exert a therapeutic effect via functional changes within the brain reward system, including the ventral striatum. The current study assessed the effects of the KCNQ channel opener ezogabine (also known as retigabine) on reward circuitry and clinical symptoms in patients with MDD. Eighteen medication-free individuals with MDD currently in a major depressive episode were enrolled in an open-label study and received ezogabine up to 900 mg/day orally over the course of ten weeks. Resting state functional magnetic resonance imaging data were collected at baseline and post-treatment to examine brain reward circuitry. Reward learning was measured using a computerized probabilistic reward task. After treatment with ezogabine, subjects exhibited a significant reduction of depressive symptoms (Montgomery-Asberg Depression Rating Scale score change: −13.7±9.7, p<0.001, d=2.08) and anhedonic symptoms (Snaith-Hamilton Pleasure Scale score change: −6.1±5.3, p<0.001, d=1.00), which remained significant even after controlling for overall depression severity. Improvement in depression was associated with decreased functional connectivity between the ventral caudate and clusters within the mid-cingulate cortex and posterior cingulate cortex (n=14, voxel-wise p<0.005). In addition, a subgroup of patients tested with a probabilistic reward task (n=9) showed increased reward learning following treatment. These findings highlight the KCNQ-type potassium channel as a promising target for future drug discovery efforts in mood disorders.

Dynamic functional connectivity (DFC) obtained from resting state functional magnetic resonance imaging (fMRI) data has been shown to provide novel insights into brain function which may be obscured by static functional connectivity (SFC). Further, DFC, and by implication how different brain regions may engage or disengage with each other over time, has been shown to be behaviorally relevant and more predictive than SFC of behavioral performance and/or diagnostic status. DFC is not a directional entity and may capture neural synchronization. However, directional interactions between different brain regions is another putative mechanism by which neural populations communicate. Accordingly, static effective connectivity (SEC) has been explored as a means of characterizing such directional interactions. But investigation of its dynamic counterpart, i.e., dynamic effective connectivity (DEC), is still in its infancy. Of particular note are methodological insufficiencies in identifying DEC configurations that are reproducible across time and subjects as well as a lack of understanding of the behavioral relevance of DEC obtained from resting state fMRI. In order to address these issues, we employed a dynamic multivariate autoregressive (MVAR) model to estimate DEC. The method was first validated using simulations and then applied to resting state fMRI data obtained in-house (N = 21), wherein we performed dynamic clustering of DEC matrices across multiple levels [using adaptive evolutionary clustering (AEC)] – spatial location, time, and subjects. We observed a small number of directional brain network configurations alternating between each other over time in a quasi-stable manner akin to brain microstates. The dominant and consistent DEC network patterns involved several regions including inferior and mid temporal cortex, motor and parietal cortex, occipital cortex, as well as part of frontal cortex. The functional relevance of these DEC states were determined using meta-analyses and pertained mainly to memory and emotion, but also involved execution and language. Finally, a larger cohort of resting-state fMRI and behavioral data from the Human Connectome Project (HCP) (N = 232, Q1–Q3 release) was used to demonstrate that metrics derived from DEC can explain larger variance in 70 behaviors across different domains (alertness, cognition, emotion, and personality traits) compared to SEC in healthy individuals.

This study investigated the relationship between different disfluency types (i.e., repetitions, prolongations, and blocks) and resting state functional connectivity in the feedback (FB) and feedforward (FF) control networks in 20 adults who stutter. Frequency of each disfluency type was coded in speech samples derived from the Stuttering Severity Instrument, and functional connectivity between brain regions of interest was derived from resting state functional magnetic resonance imaging scans. We used LASSO regressions to identify the connections that most strongly predicted each disfluency type. Both repetitions and prolongations were significantly associated with increased connectivity in left ventral motor cortex - right ventral premotor cortex, which is hypothesized to be involved in FB control of speech. In contrast, blocks were significantly associated with reduced connectivity in right anterior cerebellum - left ventral lateral thalamic nucleus and increased connectivity in left presupplementary motor area - left posterior inferior frontal sulcus, both of which are hypothesized to be involved in FF control of speech. Our findings suggest that repetitions and prolongations may be associated with increased reliance on FB-based corrective mechanisms, whereas blocks may be associated with disrupted FF-based initiation mechanisms. These neural underpinnings may correspond to different challenges in terminating or initiating motor commands and underscore the nuanced neurobiological processes underlying speech disfluencies.

Brief interventions for alcohol use disorder (AUD) are generally efficacious, albeit with variability in response. Resting state functional connectivity (rsFC) may characterize neurobiological indicators that predict the response to brief interventions and is the focus of the current investigation. Forty-six individuals with AUD (65.2% female) completed a resting state functional magnetic resonance imaging (fMRI) scan immediately followed by a brief intervention aimed at reducing alcohol consumption. Positive clinical response was defined as a reduction in alcohol consumption by at least one World Health Organization (WHO) risk drinking level at 3-month follow-up. rsFC was analyzed using seed-to-voxel analysis with seed regions from four networks: salience network, reward network, frontoparietal network, and default mode network. At baseline, responders had greater rsFC between the following seed regions in relation to voxel-based clusters than non-responders: (i) anterior cingulate cortex (ACC) in relation to left postcentral gyrus and right supramarginal gyrus (salience network); (ii) right posterior parietal cortex in relation to right ventral ACC (salience network); (iii) right interior frontal gyrus (IFG) pars opercularis in relation to right cerebellum and right occipital fusiform gyrus (frontoparietal); and (iv) right primary motor cortex in relation to left thalamus (default mode). Lower rsFC in responders vs. nonresponders was seen between the (i) right rostral prefrontal cortex in relation to left IFG pars triangularis (frontoparietal); (ii) right IFG pars triangularis in relation to right cerebellum (frontoparietal); (iii) right IFG pars triangularis in relation to right frontal eye fields and right angular gyrus (frontoparietal); and (iv) right nucleus accumbens in relation to right orbital frontal cortex and right insula (reward). Resting state functional connectivity in the frontoparietal, salience, and reward networks predicts the response to a brief intervention in individuals with AUD and could reflect greater receptivity or motivation for behavior change.

Many unsupervised methods are widely used for parcellating the brain. However, unsupervised methods aren’t able to integrate prior information, obtained from such as exiting functional neuroanatomy studies, to parcellate the brain, whereas the prior information guided semi-supervised method can generate more reliable brain parcellation. In this study, we propose a novel semi-supervised clustering method for parcellating the brain into spatially and functionally consistent parcels based on resting state functional magnetic resonance imaging (fMRI) data. Particularly, the prior supervised and spatial information is integrated into spectral clustering to achieve reliable brain parcellation. The proposed method has been validated in the hippocampus parcellation based on resting state fMRI data of 20 healthy adult subjects. The experimental results have demonstrated that the proposed method could successfully parcellate the hippocampus into head, body and tail parcels. The distinctive functional connectivity patterns of these parcels have further demonstrated the validity of the parcellation results. The effects of aging on the three hippocampus parcels’ functional connectivity were also explored across the healthy adult subjects. Compared with state-of-the-art methods, the proposed method had better performance on functional homogeneity. Furthermore, the proposed method had good test–retest reproducibility validated by parcellating the hippocampus based on three repeated resting state fMRI scans from 24 healthy adult subjects.

Objective: Gastrointestinal (GI) symptoms are fairly common somatic symptoms in depressed patients. The purpose of this study is to explore the influence of concomitant GI symptoms on fractional amplitude of low-frequency fluctuation (fALFF) patterns in patients with major depressive disorders (MDD) and investigate the connection between aberrant fALFF and clinical characteristics. Methods: This study included 35 MDD patients with GI symptoms (GI-MDD patients), 17 MDD patients without GI symptoms (nGI-MDD patients) and 28 healthy controls (HCs). The fALFF method was used to analyze the resting state functional magnetic resonance imaging data. The correlation analysis and pattern classification were employed to investigate the relationship of fALFF pattern with clinical characteristics in the patients. Results: GI-MDD patients exhibited higher scores in HRSD-17 scores and suffered more severe insomnia, anxiety/somatization and weight loss than nGI-MDD patients. GI-MDD patients showed higher fALFF in the right superior frontal gyrus (SFG)/middle frontal gyrus (MFG) and lower fALFF in the left superior medial prefrontal cortex (MPFC) compared with nGI-MDD patients. A combination of the fALFF values of these two clusters could be applied to discriminate GI-MDD patients from nGI-MDD patients with an accuracy, a sensitivity and a specificity of 86.54%, 94.29% and 70.59%, respectively. Conclusion: GI-MDD patients showed more severe depressive symptoms. Increased fALFF in the right SFG/MFG and decreased fALFF in the left superior MPFC might be distinctive neurobiological features of MDD patients with GI symptoms.

Brain Connectivity: A Journal of Clinical Neurology, Neuroscience, and Neuroimaging Advancing the Field of Neurology.

A preliminary study of functional connectivity in comorbid adolescent depression

Neurocognitive models of pediatric irritability suggest a prominent role of anger; however, few studies have investigated anger-related biases and their neural correlates. Resting state functional connectivity (rsFC) of the amygdala was examined in relation to anger attribution bias (AAB) in a sample of young children (5-9 years old; N = 60; 55% White, 26.7% Hispanic) with clinically significant irritability characterized by impairing emotional outbursts (IEOs). Children completed a resting state functional magnetic resonance imaging scan as well as the assessment of children's emotional skills (ACES), which yields three measures of AAB in the context of social situations, social behaviors, and facial expressions. ACES scores were entered into a general linear model to examine associations with rsFC of the bilateral amygdalae. Children with IEOs exhibited significant biases in attributing anger to others across all three ACES domains. Greater biases toward attributing anger in social situations were associated with reduced rsFC of the bilateral amygdalae with the fusiform/lingual gyri and lateral occipital cortex. Alternatively, greater biases toward attributing anger to facial expressions positively predicted right amygdala-precuneus rsFC. Greater bias toward attributing anger to others based on their behaviors was associated with heightened rsFC of the right amygdala with the left middle frontal gyrus. Findings extend previous work implicating functional connections among regions of default mode and frontoparietal networks in pediatric irritability. Longitudinal studies are needed to further investigate the putative role of AAB in the etiology and long-term outcomes of pediatric irritability. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Background:The cannabinoid cannabinoid type 1 (CB1) neutral antagonist tetrahydrocannabivarin (THCv) has been suggested as a possible treatment for obesity, but without the depressogenic side-effects of inverse antagonists such as Rimonabant. However, how THCv might affect the resting state functional connectivity of the human brain is as yet unknown.Method:We examined the effects of a single 10mg oral dose of THCv and placebo in 20 healthy volunteers in a randomized, within-subject, double-blind design. Using resting state functional magnetic resonance imaging and seed-based connectivity analyses, we selected the amygdala, insula, orbitofrontal cortex, and dorsal medial prefrontal cortex (dmPFC) as regions of interest. Mood and subjective experience were also measured before and after drug administration using self-report scales.Results:Our results revealed, as expected, no significant differences in the subjective experience with a single dose of THCv. However, we found reduced resting state functional connectivity between the amygdala seed region and the default mode network and increased resting state functional connectivity between the amygdala seed region and the dorsal anterior cingulate cortex and between the dmPFC seed region and the inferior frontal gyrus/medial frontal gyrus. We also found a positive correlation under placebo for the amygdala-precuneus connectivity with the body mass index, although this correlation was not apparent under THCv.Conclusion:Our findings are the first to show that treatment with the CB1 neutral antagonist THCv decreases resting state functional connectivity in the default mode network and increases connectivity in the cognitive control network and dorsal visual stream network. This effect profile suggests possible therapeutic activity of THCv for obesity, where functional connectivity has been found to be altered in these regions.