Neuromodulation of Eating Disorders: A Review of Underlying Neural Network Activity and Neuromodulatory Treatments.

Eating disorders are a group of psychiatric conditions that involve pathological relationships between patients and food. The most prolific of these disorders are anorexia nervosa, bulimia nervosa, and binge eating disorder. The current standard of care involves psychotherapy, pharmacotherapy, and the management of comorbid conditions, with nutritional rehabilitation reserved for severe cases of anorexia nervosa. Unfortunately, many patients often fail to respond, leaving a concerning treatment gap between the current and requisite treatments for eating disorders. To better understand the neurobiology underlying these eating disorders, investigations have been undertaken to characterize the activity of various neural networks, primarily those activated during tasks of executive inhibition, reward processing, and self-reference. Various neuromodulatory techniques have been proposed to stimulate these networks with the goal of improving patients' BMI and mental health. The aim of this review is to compile a comprehensive summarization of the current literature regarding the underlying neural connectivity of anorexia nervosa, bulimia nervosa, and binge eating disorder as well as the numerous neuromodulatory modalities that have been investigated. Importantly, we aimed to summarize the most significant clinical trials to date as well as to provide an updated assessment of the role of deep brain stimulation, summarizing numerous recently published clinical studies that have greatly contributed to the literature. In this review, we found therapeutic evidence for transcranial magnetic stimulation and transcranial direct current stimulation in treating individuals suffering from anorexia nervosa, bulimia nervosa, and binge eating disorder. We also found significant evidence for the role of deep brain stimulation, particularly as an escalatory therapy option for the those who failed standard therapy. Finally, we hope to provide promising directions for future clinical investigations.

Functional connectivity and complexity analyses of resting-state fMRI in pre-adolescents demonstrating the behavioral symptoms of ADHD.

Attention deficit hyperactivity disorder (ADHD) has been characterized by impairments among distributed functional brain networks, e.g., the frontoparietal network (FPN), default mode network (DMN), reward and motivation-related circuits (RMN), and salience network (SAL). In the current study, we evaluated the complexity and functional connectivity (FC) of resting state fMRI (rsfMRI) in pre-adolescents with the behavioral symptoms of ADHD, for pathology-relevant networks. We leveraged data from the Adolescent Brain and Cognitive Development (ABCD) Study. The final study sample included 63 children demonstrating the behavioral features of ADHD and 92 healthy control children matched on age, sex, and pubertal development status. For selected regions in the relevant networks, ANCOVA compared multiscale entropy (MSE) and FC between the groups. Finally, differences in the association between MSE and FC were evaluated. We found significantly reduced MSE along with increased FC within the FPN of pre-adolescents demonstrating the behavior symptoms of ADHD compared to matched healthy controls. Significant partial correlations between MSE and FC emerged in the FPN and RMN in the healthy controls however the association was absent in the participants demonstrating the behavior symptoms of ADHD. The current findings of complexity and FC in ADHD pathology support hypotheses of altered function of inhibitory control networks in ADHD.

Task-Evoked Neural Activity During Reward Anticipation and Inhibitory Control in Preadolescent Binge Eating Disorder.

PURPOSE: Behavioral features of binge eating disorder (BED) suggest abnormalities in reward and inhibitory control. Studies of adult populations suggest functional abnormalities in reward and inhibitory control networks. Despite behavioral markers often developing in children, the neurobiology of pediatric BED remains unstudied. METHODS: Fifty eight preadolescent children (aged 9-10 years) with BED and 68 age, body mass index and developmentally matched control children were extracted from the 3.0 baseline (Year 0) release of the Adolescent Brain Cognitive Development Study. We investigated task-evoked blood-oxygen-level-dependent response during functional magnetic resonance imaging, as participants completed the monetary incentive delay task and the stop signal task. We indexed group differences in regions of interest in the reward (orbitofrontal cortex, nucleus accumbens) and inhibitory control (dorsolateral prefrontal cortex, anterior cingulate cortex). RESULTS: No significant group differences emerged during tasks of inhibitory control among children with BED and children without BED. Similarly, no significant group differences emerged during the anticipation or receipt of reward among children with BED and children without BED. DISCUSSION: Preadolescent children with BED do not demonstrate abnormal neural activity in prominent nodes of reward or inhibitory control circuitry during tasks of inhibitory control, reward anticipation, and reward receipt, relative to children without BED who also had a similar body mass index.

Vessel density mapping of small cerebral vessels on 3D high resolution black blood MRI.

Small cerebral blood vessels are largely inaccessible to existing clinical in vivo imaging technologies. This study aims to present a novel analysis pipeline for vessel density mapping of small cerebral blood vessels from high-resolution 3D black-blood MRI at 3T. Twenty-eight subjects (10 under 35 years old, 18 over 60 years old) were imaged with the T1-weighted turbo spin-echo with variable flip angles (T1w TSE-VFA) sequence optimized for black-blood small vessel imaging with iso-0.5 mm spatial resolution (interpolated from 0.51×0.51×0.64 mm3) at 3T. Hessian-based vessel segmentation methods (Jerman, Frangi and Sato filter) were evaluated by vessel landmarks and manual annotation of lenticulostriate arteries (LSAs). Using optimized vessel segmentation, large vessel pruning and non-linear registration, a semiautomatic pipeline was proposed for quantification of small vessel density across brain regions and further for localized detection of small vessel changes across populations. Voxel-level statistics was performed to compare vessel density between two age groups. Additionally, local vessel density of aged subjects was correlated with their corresponding gross cognitive and executive function (EF) scores using Montreal Cognitive Assessment (MoCA) and EF composite scores compiled with Item Response Theory (IRT). Jerman filter showed better performance for vessel segmentation than Frangi and Sato filter which was employed in our pipeline. Small cerebral blood vessels including small artery, arterioles, small veins, and venules on the order of a few hundred microns can be delineated using the proposed analysis pipeline on 3D black-blood MRI at 3T. The mean vessel density across brain regions was significantly higher in young subjects compared to aged subjects. In the aged subjects, localized vessel density was positively correlated with MoCA and IRT EF scores. The proposed pipeline is able to segment, quantify, and detect localized differences in vessel density of small cerebral blood vessels based on 3D high-resolution black-blood MRI. This framework may serve as a tool for localized detection of small vessel density changes in normal aging and cerebral small vessel disease.

Age-Related Decline in BBB Function is More Pronounced in Males than Females.

The blood-brain barrier (BBB) plays a pivotal role in protecting the central nervous system (CNS), shielding it from potential harmful entities. A natural decline of BBB function with aging has been reported in both animal and human studies, which may contribute to cognitive decline and neurodegenerative disorders. Limited data also suggest that being female may be associated with protective effects on BBB function. Here we investigated age and sex-dependent trajectories of perfusion and BBB water exchange rate (kw) across the lifespan in 186 cognitively normal participants spanning the ages of 8 to 92 years old, using a novel non-invasive diffusion prepared pseudo-continuous arterial spin labeling (DP-pCASL) MRI technique. We found that the pattern of BBB kw decline with aging varies across brain regions. Moreover, results from our novel DP-pCASL technique revealed a remarkable decline in BBB kw beginning in the early 60s, which was more pronounced in males. In addition, we observed sex differences in parietotemporal and hippocampal regions. Our findings provide in vivo results demonstrating sex differences in the decline of BBB function with aging, which may serve as a foundation for future investigations into perfusion and BBB function in neurodegenerative and other brain disorders.

Cerebral blood flow and white matter alterations in adults with phenylketonuria.

BACKGROUND: Phenylketonuria (PKU) represents a congenital metabolic defect that disrupts the process of converting phenylalanine (Phe) into tyrosine. Earlier investigations have revealed diminished cognitive performance and changes in brain structure and function (including the presence of white matter lesions) among individuals affected by PKU. However, there exists limited understanding regarding cerebral blood flow (CBF) and its potential associations with cognition, white matter lesions, and metabolic parameters in patients with PKU, which we therefore aimed to investigate in this study. METHOD: Arterial spin labeling perfusion MRI was performed to measure CBF in 30 adults with early-treated classical PKU (median age 35.5 years) and 59 healthy controls (median age 30.0 years). For all participants, brain Phe levels were measured with 1H spectroscopy, and white matter lesions were rated by two neuroradiologists on T2 weighted images. White matter integrity was examined with diffusion tensor imaging (DTI). For patients only, concurrent plasma Phe levels were assessed after an overnight fasting period. Furthermore, past Phe levels were collected to estimate historical metabolic control. On the day of the MRI, each participant underwent a cognitive assessment measuring IQ and performance in executive functions, attention, and processing speed. RESULTS: No significant group difference was observed in global CBF between patients and controls (F (1, 87) = 3.81, p = 0.054). Investigating CBF on the level of cerebral arterial territories, reduced CBF was observed in the left middle and posterior cerebral artery (MCA and PCA), with the most prominent reduction of CBF in the anterior subdivision of the MCA (F (1, 87) = 6.15, p = 0.015, surviving FDR correction). White matter lesions in patients were associated with cerebral blood flow reduction in the affected structure. Particularly, patients with lesions in the occipital lobe showed significant CBF reductions in the left PCA (U = 352, p = 0.013, surviving FDR correction). Additionally, axial diffusivity measured with DTI was positively associated with CBF in the ACA and PCA (surviving FDR correction). Cerebral blood flow did not correlate with cognitive performance or metabolic parameters. CONCLUSION: The relationship between cerebral blood flow and white matter indicates a complex interplay between vascular health and white matter alterations in patients with PKU. It highlights the importance of considering a multifactorial model when investigating the impact of PKU on the brain.

Retinal perfusion is linked to cognition and brain MRI biomarkers in Black Americans.

INTRODUCTION: We investigated whether retinal capillary perfusion is a biomarker of cerebral small vessel disease and impaired cognition among Black Americans, an understudied group at higher risk for dementia. METHODS: We enrolled 96 Black Americans without known cognitive impairment. Four retinal perfusion measures were derived using optical coherence tomography angiography. Neurocognitive assessment and brain magnetic resonance imaging (MRI) were performed. Multiple linear regression analyses were performed. RESULTS: Lower retinal capillary perfusion was correlated with worse Oral Symbol Digit Test (P < = 0.005) and Fluid Cognition Composite scores (P < = 0.02), but not with the Crystallized Cognition Composite score (P > = 0.41). Lower retinal perfusion was also correlated with higher free water and peak width of skeletonized mean diffusivity, and lower fractional anisotropy (all P < 0.05) on MRI (N = 35). DISCUSSION: Lower retinal capillary perfusion is associated with worse information processing, fluid cognition, and MRI biomarkers of cerebral small vessel disease, but is not related to crystallized cognition.

A Pilot Study of the Effect of Transcutaneous Spinal Cord Stimulation on Micturition-Related Brain Activity and Lower Urinary Tract Symptoms After Stroke.

PURPOSE: Transcutaneous spinal cord stimulation (TSCS) is a novel neuromodulation modality developed to promote functional restoration in patients with neurological injury or disease. Previous pilot data suggest that lower urinary tract dysfunction (LUTD) due to stroke may be partially alleviated by TSCS. In this study, we examine the mechanism of this effect by evaluating bladder-related brain activity in patients before and after TSCS therapy and comparing it to healthy volunteers. MATERIALS AND METHODS: Patients who developed storage LUTD after a stroke and healthy volunteers without LUTD were recruited. Patients and healthy volunteers underwent simultaneous urodynamics and functional MRI. Patients then completed 24 biweekly sessions of TSCS and underwent another simultaneous urodynamics-functional MRI study. Clinical outcomes were assessed using validated questionnaires and voiding diary. RESULTS: Fifteen patients and 16 healthy volunteers completed the study. Following TSCS, patients exhibited increased blood-oxygen-level-dependent activity in areas including periaqueductal grey, the insula, the lateral prefrontal cortex, and motor cortex. Prior to TSCS therapy, healthy controls exhibited higher blood-oxygen-level-dependent activity in 17 regions, including multiple regions in the prefrontal cortex and basal ganglia. These differences were attenuated after TSCS with no frontal brain differences remaining between healthy volunteers and stroke participants who completed therapy. Neuroimaging changes were complemented by clinically significant improvements in questionnaire scores and voiding diary parameters. CONCLUSIONS: TSCS therapy modulated bladder-related brain activity, reducing differences between healthy volunteers and stroke patients with LUTD. These changes, alongside improved clinical outcomes, suggest TSCS as a promising approach for LUTD management.

Transformer-based deep learning denoising of single and multi-delay 3D arterial spin labeling.

PURPOSE: To present a Swin Transformer-based deep learning (DL) model (SwinIR) for denoising single-delay and multi-delay 3D arterial spin labeling (ASL) and compare its performance with convolutional neural network (CNN) and other Transformer-based methods. METHODS: SwinIR and CNN-based spatial denoising models were developed for single-delay ASL. The models were trained on 66 subjects (119 scans) and tested on 39 subjects (44 scans) from three different vendors. Spatiotemporal denoising models were developed using another dataset (6 subjects, 10 scans) of multi-delay ASL. A range of input conditions was tested for denoising single and multi-delay ASL, respectively. The performance was evaluated using similarity metrics, spatial SNR and quantification accuracy of cerebral blood flow (CBF), and arterial transit time (ATT). RESULTS: SwinIR outperformed CNN and other Transformer-based networks, whereas pseudo-3D models performed better than 2D models for denoising single-delay ASL. The similarity metrics and image quality (SNR) improved with more slices in pseudo-3D models and further improved when using M0 as input, but introduced greater biases for CBF quantification. Pseudo-3D models with three slices achieved optimal balance between SNR and accuracy, which can be generalized to different vendors. For multi-delay ASL, spatiotemporal denoising models had better performance than spatial-only models with reduced biases in fitted CBF and ATT maps. CONCLUSIONS: SwinIR provided better performance than CNN and other Transformer-based methods for denoising both single and multi-delay 3D ASL data. The proposed model offers flexibility to improve image quality and/or reduce scan time for 3D ASL to facilitate its clinical use.

Multi-Site Cross-Site Inter-Rater and Test-Retest Reliability and Construct Validity of the MarkVCID White Matter Hyperintensity Growth and Regression Protocol.

BACKGROUND: White matter hyperintensities (WMH) that occur in the setting of vascular cognitive impairment and dementia (VCID) may be dynamic increasing or decreasing volumes or stable over time. Quantifying such changes may prove useful as a biomarker for clinical trials designed to address vascular cognitive-impairment and dementia and Alzheimer's Disease. OBJECTIVE: Conducting multi-site cross-site inter-rater and test-retest reliability of the MarkVCID white matter hyperintensity growth and regression protocol. METHODS: The NINDS-supported MarkVCID Consortium evaluated a neuroimaging biomarker developed to track WMH change. Test-retest and cross-site inter-rater reliability of the protocol were assessed. Cognitive test scores were analyzed in relation to WMH changes to explore its construct validity. RESULTS: ICC values for test-retest reliability of WMH growth and regression were 0.969 and 0.937 respectively, while for cross-site inter-rater ICC values for WMH growth and regression were 0.995 and 0.990 respectively. Word list long-delay free-recall was negatively associated with WMH growth (p < 0.028) but was not associated with WMH regression. CONCLUSIONS: The present data demonstrate robust ICC validity of a WMH growth/regression protocol over a one-year period as measured by cross-site inter-rater and test-retest reliability. These data suggest that this approach may serve an important role in clinical trials of disease-modifying agents for VCID that may preferentially affect WMH growth, stability, or regression.

Functional Connectivity and Complexity Analyses of Resting-State fMRI in Pre-Adolescents with ADHD.

Attention deficit hyperactivity disorder (ADHD) has been characterized by impairments among distributed functional brain networks, e.g., the frontoparietal network (FPN), default mode network (DMN), and reward and motivation-related circuits (RMN). In the current study, we evaluated the complexity and functional connectivity (FC) of resting state fMRI (rsfMRI) in pre-adolescents with ADHD for pathology-relevant networks. We leveraged data from the Adolescent Brain and Cognitive Development (ABCD) Study. The final study sample included 63 children with ADHD and 92 healthy control children matched on age, sex, and pubertal development status. For selected regions in relevant networks, ANCOVA compared multiscale entropy (MSE) and FC between the groups. Finally, differences in the association between MSE and FC were evaluated. We found significantly reduced MSE along with increased FC within the FPN of pre-adolescents with ADHD compared to matched healthy controls. Significant partial correlations between MSE and FC emerged in fewer regions in the participants with ADHD than in the controls. The observation of reduced entropy is consistent with existing literature using rsfMRI and other neuroimaging modalities. The current findings of complexity and FC in ADHD support hypotheses of altered function of inhibitory control networks in ADHD.

FMRI Complexity Correlates with Tau-PET and Cognitive Decline in Late-Onset and Autosomal Dominant Alzheimer's Disease.

BACKGROUND: Neurofibrillary tangle pathology detected with tau-PET correlates closely with neuronal injury and cognitive symptoms in Alzheimer's disease (AD). Complexity of rs-fMRI has been demonstrated to decrease with cognitive decline in AD. OBJECTIVE: We hypothesize that the rs-fMRI complexity provides an index for tau-related neuronal injury and cognitive decline in the AD process. METHODS: Data was obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI3) and the Estudio de la Enfermedad de Alzheimer en Jalisciences (EEAJ) study. Associations between tau-PET and rs-fMRI complexity were calculated. Potential pathways relating complexity to cognitive function mediated through tau-PET were assessed by path analysis. RESULTS: We found significant negative correlations between rs-fMRI complexity and tau-PET in medial temporal lobe of both cohorts, and associations of rs-fMRI complexity with cognitive scores were mediated through tau-PET. CONCLUSION: The association of rs-fMRI complexity with tau-PET and cognition, suggests that a reduction in complexity is indicative of tau-related neuropathology and cognitive decline in AD processes.

A window to the brain: ultrasound imaging of human neural activity through a permanent acoustic window.

Recording human brain activity is crucial for understanding normal and aberrant brain function. However, available recording methods are either highly invasive or have relatively low sensitivity. Functional ultrasound imaging (fUSI) is an emerging technique that offers sensitive, large-scale, high-resolution neural imaging. However, fUSI cannot be performed through adult human skull. Here, we use a polymeric skull replacement material to create an acoustic window allowing ultrasound to monitor brain activity in fully intact adult humans. We design the window through experiments in phantoms and rodents, then implement it in a participant undergoing reconstructive skull surgery. Subsequently, we demonstrate fully non-invasive mapping and decoding of cortical responses to finger movement, marking the first instance of high-resolution (200 µm) and large-scale (50 mmx38 mm) brain imaging through a permanent acoustic window.

Sweet taste preference is associated with greater hypothalamic response to glucose and longitudinal weight gain.

The hypothalamus has an abundant expression of sweet taste receptors that play a role in glucose sensing and energy homeostasis. Evidence suggests that liking "sweets" can be associated with weight gain, but the relationship between sweet taste preference and hypothalamic regulation of appetite is unknown. This study tested the hypothesis that sweet taste preference is associated with increased hypothalamic activation in response to glucose (a purported neural marker for weight gain risk) and greater longitudinal increases in body mass index (BMI). Fifty-four adults aged 18-35 years with a mean (± SD) BMI of 27.99 ± 5.32 kg/m2 completed the study. Height and weight were measured at baseline and 6-12 months later in a subset of 36 participants. Sweet taste preference was assessed via the Monell 2-series, forced-choice tracking procedure. Arterial spin labeling magnetic resonance imaging was performed before and after oral glucose ingestion to determine hypothalamic blood flow response to glucose. Linear models were used to examine relationships between sweet taste preference and the hypothalamic response to glucose and longitudinal changes in BMI, adjusting for age, sex, and baseline BMI. Sweet taste preference was positively associated with glucose-linked hypothalamic blood flow (beta = 0.017, p = 0.043), adjusted for age, sex and BMI. We also observed a positive association between sweet taste preference and longitudinal change in BMI (beta = 0.088, p = 0.015), adjusted for age, sex and baseline BMI. These findings suggest that heightened sweet taste preference is associated with glucose-linked hypothalamic activation and may be linked to increased susceptibility for weight gain.

Cross-Vendor Test-Retest Validation of Diffusion Tensor Image Analysis along the Perivascular Space (DTI-ALPS) for Evaluating Glymphatic System Function.

The diffusion tensor image analysis along the perivascular space (DTI-ALPS) method was proposed to evaluate glymphatic system (GS) function. However, few studies have validated its reliability and reproducibility. Fifty participants' DTI data from the MarkVCID consortium were included in this study. Two pipelines by using DSI studio and FSL software were developed for data processing and ALPS index calculation. The ALPS index was obtained by the average of bilateral ALPS index and was used for testing the cross-vendor, inter-rater and test-retest reliability by using R studio software. The ALPS index demonstrated favorable inter-scanner reproducibility (ICC=0.77 to 0.95, P < 0.001), inter-rater reliability (ICC=0.96 to 1, P< 0.001) and test-retest repeatability (ICC=0.89 to 0.95, P< 0.001), offering a potential biomarker for in vivo evaluation of GS function.

Transformer based deep learning denoising of single and multi-delay 3D Arterial Spin Labeling.

Purpose: To present a Swin Transformer-based deep learning (DL) model for denoising of single-delay and multi-delay 3D arterial spin labeling (ASL) and compare its performance with convolutional neural network (CNN) methods. Methods: Swin Transformer and CNN-based spatial denoising models were developed for single-delay ASL. The models were trained on 59 subjects (104 scans) and tested on 44 subjects (57 scans) from 3 different vendors. Spatiotemporal denoising models were developed using another dataset (6 subjects, 10 scans) of multi-delay ASL. A range of input conditions was tested for denoising single and multi-delay ASL respectively. The performance was evaluated using similarity metrics, spatial signal-to-noise ratio (SNR) and quantification accuracy of cerebral blood flow (CBF) and arterial transit time (ATT). Results: Swin Transformer outperformed CNN-based networks, whereas pseudo-3D models showed better performance than 2D models for denoising single-delay ASL. The similarity metrics and image quality (SNR) improved with more slices in pseudo-3D models, and further improved when using M0 as input but introduced greater biases for CBF quantification. Pseudo-3D models with 3 slices as input achieved optimal balance between SNR and accuracy, which can be generalized to different vendors. For multi-delay, spatiotemporal denoising models had better performance than spatial-only models with reduced biases in fitted CBF and ATT maps. Conclusions: Swin Transformer DL models provided better performance than CNN methods for denoising both single and multi-delay 3D ASL data. The proposed model offers flexibility to improve image quality and/or reduce scan time for 3D ASL to facilitate its clinical use.