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Deep brain stimulation (DBS) of the anterior limb of the internal capsule (ALIC) is a circuit-based treatment for severe, refractory obsessive-compulsive disorder (OCD). The therapeutic effects of DBS are hypothesized to be mediated by direct modulation of a distributed cortico-striato-thalmo-cortical network underlying OCD symptoms. However, the exact underlying mechanism by which DBS exerts its therapeutic effects still remains unclear. In five participants receiving DBS for severe, refractory OCD (3 responders, 2 non-responders), we conducted a DBS On/Off cycling paradigm during the acquisition of functional MRI (23 fMRI runs) to determine the network effects of stimulation across a variety of bipolar configurations. We also performed tractography using diffusion-weighted imaging (DWI) to relate the functional impact of DBS to the underlying structural connectivity between active stimulation contacts and functional brain networks. We found that therapeutic DBS had a distributed effect, suppressing BOLD activity within regions such as the orbitofrontal cortex, dorsomedial prefrontal cortex, and subthalamic nuclei compared to non-therapeutic configurations. Many of the regions suppressed by therapeutic DBS were components of the default mode network (DMN). Moreover, the estimated stimulation field from the therapeutic configurations exhibited significant structural connectivity to core nodes of the DMN. Based upon these findings, we hypothesize that the suppression of the DMN by ALIC DBS is mediated by interruption of communication through structural white matter connections surrounding the DBS active contacts.

Moyamoya is a rare chronic brain vascular disease with a set of potential life-threatening consequences due to a high probability of stroke occurrence. Here we present a case of a patient with moyamoya disease, who has been dynamically observed over more than 4 years after the first manifestation of her symptoms. In this study we report fMRI and DTI findings obtained at the final follow-up point, four years after two revascularization surgeries were successfully performed. Our findings lend support to the idea that revascularization surgery is effective in preventing future strokes, but may lead to only minor improvement in cognitive performance. [ABSTRACT FROM AUTHOR]

Neuroimaging studies have identified functional and structural brain circuits that support reading. However, much less is known about how reading-related functional dynamics are constrained by white matter structure. Network control theory proposes that cortical brain dynamics are linearly determined by the white matter connectome, using control energy to evaluate the difficulty of the transition from one cognitive state to another. Here we apply this approach to linking brain dynamics with reading ability and disability in school-age children. A total of 51 children ages 8.25 -14.6 years performed an in-scanner rhyming task in visual and auditory modalities, with orthographic (spelling) and phonological (rhyming) similarity manipulated across trials. White matter structure and fMRI activation were used conjointly to compute the control energy of the reading network in each condition relative to a null fixation state. We then tested differences in control energy across trial types, finding higher control energy during non-word trials than word trials, and during incongruent trials than congruent trials. ROI analyses further showed a dissociation between control energy of the left fusiform and superior temporal gyrus depending on stimulus modality, with higher control energy for visual modalities in fusiform and higher control energy for auditory modalities in STG. Together, this study highlights that control theory can explain variations on cognitive demands in higher-level abilities such as reading, beyond what can be inferred from either functional or structural MRI measures alone.

Alterations in grey matter (GM) and white matter (WM) are associated with memory impairment across the neurocognitive aging spectrum and theorised to spread throughout brain networks. Functional and structural connectivity (FC,SC) may explain widespread atrophy. We tested the effect of SC and FC to the hippocampus on cortical thickness (CT) of connected areas. In 419 (223 F) participants (age mean =73 ± 8) from the Alzheimer's Disease Neuroimaging Initiative, cortical regions associated with memory (Rey Auditory Verbal Learning Test) were identified using Lasso regression. Two structural equation models (SEM), for SC and resting-state FC, were fitted including CT areas, and SC and FC to the left and right hippocampus (LHIP,RHIP). LHIP (β =-0.150, p =<.001) and RHIP (β =-0.139, p =<.001) SC predicted left temporopolar/rhinal CT; RHIP SC predicted right temporopolar/rhinal CT (β =-0.191, p =<.001). LHIP SC predicted right fusiform/parahippocampal (β =-0.104, p =.011) and intraparietal sulcus/superior parietal CT (β =0.101, p =.028). Increased RHIP FC predicted higher left inferior parietal CT (β =0.132, p =.042) while increased LHIP FC predicted lower right fusiform/parahippocampal CT (β =-0.97; p =.023). The hippocampi may be epicentres for cortical thinning through disrupted connectivity. • Connectivity to the hippocampi is associated with grey matter alterations. • Both structural and functional connectivity can predict grey matter thickness. • The study supports the idea that the hippocampi are an epicentre for atrophy. [ABSTRACT FROM AUTHOR]

Post-COVID conditions (PCCs) cover a wide spectrum of lingering symptoms experienced by survivors of coronavirus disease 2019 (COVID-19). Neurological and neuropsychiatric sequelae are common in PCCs. Advanced magnetic resonance imaging (MRI) techniques can reveal subtle alterations in brain structure, function, and perfusion that underlie these sequelae. This systematic review aimed to synthesize findings from studies that used advanced MRI to characterize brain changes in individuals with PCCs. A detailed literature search was conducted in the PubMed and Scopus databases to identify relevant studies that used advanced MRI modalities, such as structural MRI (sMRI), diffusion tensor imaging (DTI), functional MRI (fMRI), and perfusion-weighted imaging (PWI), to evaluate brain changes in PCCs. Twenty-five studies met the inclusion criteria, comprising 1219 participants with PCCs. The most consistent findings from sMRI were reduced gray matter volume (GMV) and cortical thickness (CTh) in cortical and subcortical regions. DTI frequently reveals increased mean diffusivity (MD), radial diffusivity (RD), and decreased fractional anisotropy (FA) in white matter tracts (WMTs) such as the corpus callosum, corona radiata, and superior longitudinal fasciculus. fMRI demonstrated altered functional connectivity (FC) within the default mode, salience, frontoparietal, somatomotor, subcortical, and cerebellar networks. PWI showed decreased cerebral blood flow (CBF) in the frontotemporal area, thalamus, and basal ganglia. Advanced MRI shows changes in the brain networks and regions of the PCCs, which may cause neurological and neuropsychiatric problems. Multimodal neuroimaging may help understand brain-behavior relationships. Longitudinal studies are necessary to better understand the progression of these brain anomalies. [ABSTRACT FROM AUTHOR]

Aim: Alcohol use disorder (AUD) is the most prevalent form of addiction, with a great burden on society and limited treatment options. A recent clinical trial reported significant clinical benefits of deep transcranial magnetic stimulations (Deep TMS) targeting midline frontocortical areas. However, the underlying biological substrate remained elusive. Here, we report the effect of Deep TMS on the microstructure of white matter. Methods: A total of 37 (14 females) AUD treatment‐seeking patients were randomized to sham or active Deep TMS. Twenty (six females) age‐matched healthy controls were included. White matter integrity was evaluated by fractional anisotropy (FA). Secondary measures included brain functional connectivity and self‐reports of craving and drinking units in the 3 months of follow‐up period. Results: White matter integrity was compromised in patients with AUD relative to healthy controls, as reflected by the widespread reduction in FA. This alteration progressed during early abstinence (3 weeks) in the absence of Deep TMS. However, stimulation of midline frontocortical areas arrested the progression of FA changes in association with decreased craving and relapse scores. Reconstruction of axonal tracts from white‐matter regions showing preserved FA values identified cortical regions in the posterior cingulate and dorsomedial prefrontal cortices where functional connectivity was persistently modulated. These effects were absent in the sham‐stimulated group. Conclusions: By integrating brain structure and function to characterize the alcohol‐dependent brain, this study provides mechanistic insights into the TMS effect, pointing to myelin plasticity as a possible mediator. [ABSTRACT FROM AUTHOR]

Phantom limb pain (PLP) is a complicated condition with diverse clinical challenges. It consists of pain perception of a previously amputated limb. The exact pain mechanism is disputed and includes mechanisms involving cerebral, peripheral, and spinal origins. Such controversy limits researchers' and clinicians' ability to develop consistent therapeutics or management. Neuroimaging is an essential tool that can address this problem. This review explores diffusion tensor imaging, functional magnetic resonance imaging, electroencephalography, and magnetoencephalography in the context of PLP. These imaging modalities have distinct mechanisms, implications, applications, and limitations. Diffusion tensor imaging can outline structural changes and has surgical applications. Functional magnetic resonance imaging captures functional changes with spatial resolution and has therapeutic applications. Electroencephalography and magnetoencephalography can identify functional changes with a strong temporal resolution. Each imaging technique provides a unique perspective and they can be used in concert to reveal the true nature of PLP. Furthermore, researchers can utilize the respective strengths of each neuroimaging technique to support the development of innovative therapies. PLP exemplifies how neuroimaging and clinical management are intricately connected. This review can assist clinicians and researchers seeking a foundation for applications and understanding the limitations of neuroimaging techniques in the context of PLP.

Diminished motivation to pursue and obtain primary and secondary rewards has been demonstrated in anorexia nervosa (AN). However, the neurobehavioral mechanisms underlying the behavioral activation component of aberrant reward motivation remains incompletely understood. This work aims to explore this underexplored facet of reward motivation in AN. We recruited female adolescents with AN, restricting type (n = 32) and a healthy control group (n = 28). All participants underwent functional magnetic resonance imaging (fMRI) while performing a monetary reward task. Diffusion MRI data was also collected to examine the reward motivation circuit's structural connectivity. Behavioral results demonstrated slower speed of reward-seeking behavior in those with AN compared with controls. Accompanying this was lower functional connectivity and reduced white matter structural integrity of the connection between the ventral tegmental area/substantia nigra pars compacta and the nucleus accumbens within the mesolimbic circuit. Further, there was evidence of neurobehavioral decoupling in AN between reward-seeking behavior and mesolimbic regional activation and functional connectivity. Aberrant activity of the bed nucleus of the stria terminalis (BNST) and its connectivity with the mesolimbic system was also evident in AN during the reward motivation period. Our findings suggest functional and structural dysconnectivity within a mesolimbic reward circuit, neurofunctional decoupling from reward-seeking behavior, and abnormal BNST function and circuit interaction with the mesolimbic system. These results show behavioral indicators of aberrant reward motivation in AN, particularly in its activational component. This is mediated neuronally by mesolimbic reward circuit functional and structural dysconnectivity as well as neurobehavioral decoupling. Based on these findings, we suggest a novel circuit-based mechanism of impaired reward processing in AN, with the potential for translation to developing more targeted and effective treatments in this difficult-to-treat psychiatric condition.

Visual field defects (VFDs) represent a prevalent complication stemming from neurological and ophthalmic conditions. A range of factors, including tumors, brain surgery, glaucoma, and other disorders, can induce varying degrees of VFDs, significantly impacting patients' quality of life. Over recent decades, functional imaging has emerged as a pivotal field, employing imaging technology to illustrate functional changes within tissues and organs. As functional imaging continues to advance, its integration into various clinical aspects of VFDs has substantially enhanced the diagnostic, therapeutic, and management capabilities of healthcare professionals. Notably, prominent imaging techniques such as DTI, OCT, and MRI have garnered widespread adoption, yet they possess unique applications and considerations. This comprehensive review aims to meticulously examine the application and evolution of functional imaging in the context of VFDs. Our objective is to furnish neurologists and ophthalmologists with a systematic and comprehensive comprehension of this critical subject matter. [ABSTRACT FROM AUTHOR]

Cervical spondylotic myelopathy (CSM) is a degenerative disease representing the most common spinal cord disorder in the adult population. It is characterized by chronic compression leading to neurological dysfunction due to static and dynamic injury of the spinal cord in cervical spine. These insidious damage mechanisms can result in the reorganization of cortical and subcortical areas. The cerebral cortex can reorganize due to spinal cord injury and may play a role in preserving neurological function. To date, the gold standard treatment of cervical myelopathy is surgery, comprising anterior, posterior, and combined approaches. However, the complex physiologic recovery processes involving cortical and subcortical neural reorganization following surgery are still inadequately understood. It has been demonstrated that diffusion MRI and functional imaging and techniques, such as transcranial magnetic stimulation (TMS) or functional magnetic resonance imaging (fMRI), can provide new insights into the diagnosis and prognosis of CSM. This review aims to shed light on the state-of-the-art regarding the pattern of cortical and subcortical areas reorganization and recovery before and after surgery in CSM patients, underlighting the critical role of neuroplasticity. [ABSTRACT FROM AUTHOR]

Foreign accent syndrome (FAS) is characterized by new onset speech that is perceived as foreign. Available data from acquired cases suggests focal brain damage in language and sensorimotor brain networks, but little remains known about abnormal functional connectivity in idiopathic cases of FAS without structural damage. Here, connectomic analyses were completed on three patients with idiopathic FAS to investigate unique functional connectivity abnormalities underlying accent change for the first time. Machine learning (ML)-based algorithms generated personalized brain connectomes based on a validated parcellation scheme from the Human Connectome Project (HCP). Diffusion tractography was performed on each patient to rule out structural fiber damage to the language system. Resting-state-fMRI was assessed with ML-based software to examine functional connectivity between individual parcellations within language and sensorimotor networks and subcortical structures. Functional connectivity matrices were created and compared against a dataset of 200 healthy subjects to identify abnormally connected parcellations. Three female patients (28–42 years) who presented with accent changes from Australian English to Irish (n = 2) or American English to British English (n = 1) demonstrated fully intact language system structural connectivity. All patients demonstrated functional connectivity anomalies within language and sensorimotor networks in numerous left frontal regions and between subcortical structures in one patient. Few commonalities in functional connectivity anomalies were identified between all three patients, specifically 3 internal-network parcellation pairs. No common inter-network functional connectivity anomalies were identified between all patients. The current study demonstrates specific language, and sensorimotor functional connectivity abnormalities can exist and be quantitatively shown in the absence of structural damage for future study. [ABSTRACT FROM AUTHOR]

Targeting mitochondrial ion homeostasis using Kaempferol, a mitochondrial Ca2+ uniporter channel activator, improves energy metabolism and behavior soon after a traumatic brain injury (TBI) in developing rats. Because of broad TBI pathophysiology and brain mitochondrial heterogeneity, Kaempferol-mediated early-stage behavioral and brain metabolic benefits may accrue from diverse sources within the brain. We hypothesized that Kaempferol influences TBI outcome by differentially impacting the neural, vascular, and synaptic/axonal compartments. After TBI at early development (P31), functional magnetic resonance imaging and diffusion tensor imaging (DTI) were applied to determine imaging outcomes at adolescence (2 months post-injury). Vehicle and Kaempferol treatments were made at 1, 24, and 48 h post-TBI, and their effects were assessed at adolescence. A significant increase in neural connectivity was observed after Kaempferol treatment as assessed by the spatial extent and strength of the somatosensory cortical and hippocampal resting-state functional connectivity (RSFC) networks. However, no significant RSFC changes were observed in the thalamus. DTI measures of fractional anisotropy (FA) and apparent diffusion coefficient, representing synaptic/axonal and microstructural integrity, showed significant improvements after Kaempferol treatment, with highest changes in the frontal and parietal cortices and hippocampus. Kaempferol treatment also increased corpus callosal FA, indicating measurable improvement in the interhemispheric structural connectivity. TBI prognosis was significantly altered at adolescence by early Kaempferol treatment, with improved neural connectivity, neurovascular coupling, and parenchymal microstructure in select brain regions. However, Kaempferol failed to improve vasomotive function across the whole brain, as measured by cerebrovascular reactivity. The differential effects of Kaempferol treatment on various brain functional compartments support diverse cellular-level mitochondrial functional outcomes in vivo.

Background: The premonitory phase, or prodrome, of migraine, provides valuable opportunities to study attack initiation and for treating the attack before headache starts. Much that has been learned about this phase in recent times has come from the outcomes of functional imaging studies. This review will summarise these studies to date and use their results to provide some feasible insights into migraine neurobiology. Main body: The ability to scan repeatedly a patient without radiation and with non-invasive imaging modalities, as well as the recognition that human experimental migraine provocation compounds, such as nitroglycerin (NTG) and pituitary adenylate cyclase activating polypeptide (PACAP), can trigger typical premonitory symptoms (PS) and migraine-like headache in patients with migraine, have allowed feasible and reproducible imaging of the premonitory phase using NTG. Some studies have used serial scanning of patients with migraine to image the migraine cycle, including the 'pre-ictal' phase, defined by timing to headache onset rather than symptom phenotype. Direct observation and functional neuroimaging of triggered PS have also revealed compatible neural substrates for PS in the absence of headache. Various imaging methods including resting state functional MRI (rsfMRI), arterial spin labelling (ASL), positron emission tomography (PET) and diffusion tensor imaging (DTI) have been used. The results of imaging the spontaneous and triggered premonitory phase have been largely consistent and support a theory of central migraine attack initiation involving brain areas such as the hypothalamus, midbrain and limbic system. Early dysfunctional pain, sensory, limbic and homeostatic processing via monoaminergic and peptidergic neurotransmission likely manifests in the heterogeneous PS phenotype. Conclusion: Advances in human migraine research, including the use of functional imaging techniques lacking radiation or radio-isotope exposure, have led to an exciting opportunity to study the premonitory phase using repeated measures imaging designs. These studies have provided novel insights into attack initiation, migraine neurochemistry and therapeutic targets. Emerging migraine-specific therapies, such as those targeting calcitonin gene-related peptide (CGRP), are showing promise acutely when taken during premonitory phase to reduce symptoms and prevent subsequent headache. Therapeutic research in this area using PS for headache onset prediction and early treatment is likely to grow in the future. [ABSTRACT FROM AUTHOR]

An improved understanding of the neuroplastic potential of the brain has allowed advancements in neuromodulatory treatments for acute stroke patients. However, there remains a poor understanding of individual differences in treatment-induced recovery. Individualized information on connectivity disturbances may help predict differences in treatment response and recovery phenotypes. We studied the medical data of 22 ischemic stroke patients who received MRI scans and started repetitive transcranial magnetic stimulation (rTMS) treatment on the same day. The functional and motor outcomes were assessed at admission day, 1 day after treatment, 30 days after treatment, and 90 days after treatment using four validated standardized stroke outcome scales. Each patient underwent detailed baseline connectivity analyses to identify structural and functional connectivity disturbances. An unsupervised machine learning (ML) agglomerative hierarchical clustering method was utilized to group patients according to outcomes at four-time points to identify individual phenotypes in recovery trajectory. Differences in connectivity features were examined between individual clusters. Patients were a median age of 64, 50% female, and had a median hospital length of stay of 9.5 days. A significant improvement between all time points was demonstrated post treatment in three of four validated stroke scales utilized. ML- based analyses identified distinct clusters representing unique patient trajectories for each scale. Quantitative differences were found to exist in structural and functional connectivity analyses of the motor network and subcortical structures between individual clusters which could explain these unique trajectories on the Barthel Index (BI) scale but not on other stroke scales. This study demonstrates for the first time the feasibility of using individualized connectivity analyses in differentiating unique phenotypes in rTMS treatment responses and recovery. This personalized connectomic approach may be utilized in the future to better understand patient recovery trajectories with neuromodulatory treatment. [ABSTRACT FROM AUTHOR]

Autism spectrum disorder (ASD) is a wide range of diseases characterized by difficulties with social skills, repetitive activities, speech, and nonverbal communication. The Centers for Disease Control (CDC) estimates that 1 in 44 American children currently suffer from ASD. The current gold standard for ASD diagnosis is based on behavior observational tests by clinicians, which suffer from being subjective and time-consuming and afford only late detection (a child must have a mental age of at least two to apply for an observation report). Alternatively, brain imaging—more specifically, magnetic resonance imaging (MRI)—has proven its ability to assist in fast, objective, and early ASD diagnosis and detection. With the recent advances in artificial intelligence (AI) and machine learning (ML) techniques, sufficient tools have been developed for both automated ASD diagnosis and early detection. More recently, the development of deep learning (DL), a young subfield of AI based on artificial neural networks (ANNs), has successfully enabled the processing of brain MRI data with improved ASD diagnostic abilities. This survey focuses on the role of AI in autism diagnostics and detection based on two basic MRI modalities: diffusion tensor imaging (DTI) and functional MRI (fMRI). In addition, the survey outlines the basic findings of DTI and fMRI in autism. Furthermore, recent techniques for ASD detection using DTI and fMRI are summarized and discussed. Finally, emerging tendencies are described. The results of this study show how useful AI is for early, subjective ASD detection and diagnosis. More AI solutions that have the potential to be used in healthcare settings will be introduced in the future. [ABSTRACT FROM AUTHOR]

To track iron accumulation and location in the brain across adolescence, we repurposed diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) data acquired in 513 adolescents and validated iron estimates with quantitative susceptibility mapping (QSM) in 104 of these subjects. DTI and fMRI data were acquired longitudinally over 1 year in 245 male and 268 female, no-to-low alcohol-consuming adolescents (12-21 years at baseline) from the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA) study. Brain region average signal values were calculated for susceptibility to nonheme iron deposition: pallidum, putamen, dentate nucleus, red nucleus, and substantia nigra. To estimate nonheme iron, the corpus callosum signal (robust to iron effects) was divided by regional signals to generate estimated R2 (edwR2 for DTI) and R2 * (eR2 * for fMRI). Longitudinal iron deposition was measured using the normalized signal change across time for each subject. Validation using baseline QSM, derived from susceptibility-weighted imaging, was performed on 46 male and 58 female participants. Normalized iron deposition estimates from DTI and fMRI correlated with age in most regions; both estimates indicated less iron in boys than girls. QSM results correlated highly with DTI and fMRI results (adjusted R2 = 0.643 for DTI, 0.578 for fMRI). Cross-sectional and longitudinal analyses indicated an initial rapid increase in iron, notably in the putamen and red nucleus, that slowed with age. DTI and fMRI data can be repurposed for identifying regional brain iron deposition in developing adolescents as validated with high correspondence with QSM.

Traumatic brain injury (TBI) is a significant public health problem in the United States, especially for children and adolescents. Current epidemiological data estimate over 600,000 patients younger than 20 years are treated for TBI in emergency rooms annually. While many patients experience a full recovery, for others there can be long-lasting cognitive, neurological, psychological, and behavioral disruptions. TBI in youth can disrupt ongoing brain development and create added family stress during a formative period. The neuroimaging methods used to assess brain injury improve each year, providing researchers a more detailed characterization of the injury and recovery process. In this review, we cover current imaging methods used to quantify brain disruption post-injury, including structural magnetic resonance imaging (MRI), diffusion MRI, functional MRI, resting state fMRI, and magnetic resonance spectroscopy (MRS), with brief coverage of other methods, including electroencephalography (EEG), single-photon emission computed tomography (SPECT), and positron emission tomography (PET). We include studies focusing on pediatric moderate-severe TBI from 2 months post-injury and beyond. While the morbidity of pediatric TBI is considerable, continuing advances in imaging methods have the potential to identify new treatment targets that can lead to significant improvements in outcome.

To examine the roles of the default mode network (DMN) and executive control network (ECN) in prolonged recovery after mild traumatic brain injury (mTBI), and relationships with indices of white matter microstructural injury. Seventeen mTBI patients with persistent symptoms were imaged an average of 21.5 months post-injury, along with 23 healthy controls. Resting-state functional magnetic resonance imaging (rs-fMRI) was used to evaluate functional connectivity (FC) of the DMN and ECN. Diffusion tensor imaging (DTI) quantified fractional anisotropy, along with mean, axial and radial diffusivity of white matter tracts. Compared to controls, patients with mTBI had increased functional connectivity of the DMN and ECN to brain regions implicated in salience and frontoparietal networks, and increased white matter diffusivity within the cerebrum and brainstem. Among the patients, FC was correlated with better neurocognitive test scores, while diffusivity was correlated with more severe self-reported symptoms. The FC and diffusivity values within abnormal brain regions were not significantly correlated. For female mTBI patients with prolonged symptoms, hyper-connectivity may represent a compensatory response that helps to mitigate the effects of mTBI on cognition. These effects are unrelated to indices of microstructural injury, which are correlated with symptom severity, suggesting that rs-fMRI and DTI may capture distinct aspects of pathophysiology. [ABSTRACT FROM AUTHOR]

A library of non-immersive Virtual Reality (VR) tasks were developed for post-stroke rehabilitation of distal upper extremities. The objective was to evaluate the rehabilitation impact of the developed VR-tasks on a patient with chronic stroke. The study involved a 50-year-old male patient with chronic (13 month) stroke. Twenty VR therapy sessions of 45 min each were given. Clinical scales, cortical-excitability measures, functional MRI (fMRI), and diffusion tensor imaging (DTI) data were acquired pre-and post-therapy to evaluate the motor recovery. Increase in Fugl-Meyer Assessment (wrist/hand) by 2 units, Barthel Index by 5 units, Brunnstrom Stage by 1 unit, Addenbrooke's Cognitive Examination by 3 units, Wrist Active Range of Motion by 5° and decrease in Modified Ashworth Scale by 1 unit were observed. Ipsilesional Motor Evoked Potential (MEP) amplitude (obtained using Transcranial Magnetic Stimulation) was increased by 60.9µV with a decrease in Resting Motor Threshold (RMT) by 7%, and contralesional MEP amplitude was increased by 56.2µV with a decrease in RMT by 7%. The fMRI-derived Laterality Index of Sensorimotor Cortex increased in precentral-gyrus (from 0.28 to 0.33) and in postcentral-gyrus (from 0.07 to 0.3). The DTI-derived FA-asymmetry decreased in precentral-gyrus (from 0.029 to 0.024) and in postcentral-gyrus (from 0.027 to 0.017). Relative reduction in task-specific performance metrics, i.e., time taken to complete the task (31.6%), smoothness of trajectory (76.7%), and relative percentage error (80.7%), were observed from day 1 to day 20 of the VR therapy. VR therapy resulted in improvement in clinical outcomes in a patient with chronic stroke. The research also gives insights to further improve the overall system of rehabilitation. [ABSTRACT FROM AUTHOR]

The objective of our study is to discern the aberrant functional and structural brain connectivity in mental disorder patients, ultimately to develop quality therapeutic strategies. We developed a bivariate mixed-effects model to ascertain the differences in brain connectivity between healthy individuals and affected patients. The model accounts for subject-specific variability and heteroscedastic errors, enabling it to handle correlations within and across different connectivity measures. Such comprehensive accounting allowed us to identify notable connectivity differences between groups. To validate the performance of our model, we conducted a simulation study. Then, we applied our method to neuroimaging data for late-life depression patients, assessing biomarker identification compared to univariate mixed-effects models. [ABSTRACT FROM AUTHOR]

This article describes a case of Foreign accent syndrome (FAS) in an Italian woman who developed a Canadian-like foreign accent without brain damage (functional FAS). The patient underwent an in-depth neuroimaging and (neuro)psychological evaluation. Language networks in the frontotemporal-parietal areas were typically activated bilaterally through fMRI and MEG assessments based on task-based data. Resting-state fMRI showed preserved connectivity between language areas. An obsessive-compulsive personality profile and mild anxiety were found, suggesting psychological and psychiatric factors may be relevant. Accordingly with our findings, multimodal imaging is beneficial to understand FAS neurological and functional etiologies. [ABSTRACT FROM AUTHOR]

Recent advances in neuroimaging technologies have provided opportunities to acquire brain images of different modalities for studying human brain organization from both functional and structural perspectives. Analysis of images derived from various modalities involves some common goals such as dimension reduction, denoising, and feature extraction. However, since these modalities have vastly different data characteristics, the current analysis is usually performed using distinct analytical tools that are only suitable for a specific imaging modality. In this paper, we present a Distributional Independent Component Analysis (DICA) that represents a new approach that performs decomposition on the distribution level, providing a unified framework for extracting features across imaging modalities with different scales and representations. When applying DICA to fMRI images, we successfully recover well‐established brain functional networks in neuroscience literature, providing empirical validation that DICA delivers neurologically relevant findings. More importantly, we discover several structural network components when applying DICA to DTI images. Through fiber tracking, we find these DICA‐derived structural components correspond to several major white fiber bundles. To the best of our knowledge, this is the first time these fiber bundles are successfully identified via blind source separation on single subject DTI images. We also evaluate the performance of DICA as compared with existing ICA methods through extensive simulation studies. [ABSTRACT FROM AUTHOR]

Wu et al. have made an important contribution to the methodology for data‐driven analysis of MRI data. However, we wish to challenge the authors on new potential applications of their approach beyond diffusion tensor imaging data, and to think carefully about the impact of random initialization implicit in their method. We illustrate the variability found from re‐analyzing the supplied demonstration data multiple times, finding that the discovered independent components have a wide range of reliability, from nearly perfect overlap to no overlap at all. [ABSTRACT FROM AUTHOR]

Abstract Background To investigate the renal dysfunction in patients with hyperuricemia by employing a multiparametric MRI protocol, consisting of quantitative water molecule diffusion, microstructure, microscopic perfusion, and oxygenation measurements in kidneys. Materials and methods A total of 48 patients with hyperuricemia (HU) and 22 age-matched healthy control subjects (HC) were enrolled in the study. For each participant, three different functional magnetic resonance imaging (fMRI) sequences were acquired and analyzed, including intravoxel incoherent motion imaging (IVIM), diffusion tensor imaging (DTI), and blood-oxygen-level-dependent MRI (BOLD). Thereafter, an independent two-sample t-test was applied to discover the significant differences of MRI indices between the hyperuricemia (HU) and HC groups, and the specific potential biomarkers between two subgroups of HU group (asymptomatic hyperuricemia group (AH) and gouty arthritis group (GA)). Further, multivariate logistic regression analyses were performed to classify the AH from the GA group using the MRI indices with significant between-group differences. The receiver operating characteristic (ROC) curve was plotted, and the area under the ROC curve (AUC) was calculated to assess the performance of each MR index for differentiation between the AH and GA groups. Results Ten parametric values of the HU group were significantly lower than those of the HC group among the 14 fMRI parameters (P

Patients with Lewy body disease (LBD) frequently experience visual hallucinations (VH), well-formed images perceived without the presence of real stimuli. The structural and functional brain mechanisms underlying VH in LBD are still unclear. The present review summarises the current literature on the neural correlates of VH in LBD, namely Parkinson's disease (PD), and dementia with Lewy bodies (DLB). Following a systematic literature search, 56 neuroimaging studies of VH in PD and DLB were critically reviewed and evaluated for quality assessment. The main structural neuroimaging results on VH in LBD revealed grey matter loss in frontal areas in patients with dementia, and parietal and occipito-temporal regions in PD without dementia. Parietal and temporal hypometabolism was also reported in hallucinating PD patients. Disrupted functional connectivity was detected especially in the default mode network and fronto-parietal regions. However, evidence on structural and functional connectivity is still limited and requires further investigation. The current literature is in line with integrative models of VH suggesting a role of attention and perception deficits in the development of VH. However, despite the close relationship between VH and cognitive impairment, its associations with brain structure and function have been explored only by a limited number of studies.

Autism spectrum disorder (ASD) is a wide range of diseases characterized by difficulties with social skills, repetitive activities, speech, and nonverbal communication. The Centers for Disease Control (CDC) estimates that 1 in 44 American children currently suffer from ASD. The current gold standard for ASD diagnosis is based on behavior observational tests by clinicians, which suffer from being subjective and time-consuming and afford only late detection (a child must have a mental age of at least two to apply for an observation report). Alternatively, brain imaging—more specifically, magnetic resonance imaging (MRI)—has proven its ability to assist in fast, objective, and early ASD diagnosis and detection. With the recent advances in artificial intelligence (AI) and machine learning (ML) techniques, sufficient tools have been developed for both automated ASD diagnosis and early detection. More recently, the development of deep learning (DL), a young subfield of AI based on artificial neural networks (ANNs), has successfully enabled the processing of brain MRI data with improved ASD diagnostic abilities. This survey focuses on the role of AI in autism diagnostics and detection based on two basic MRI modalities: diffusion tensor imaging (DTI) and functional MRI (fMRI). In addition, the survey outlines the basic findings of DTI and fMRI in autism. Furthermore, recent techniques for ASD detection using DTI and fMRI are summarized and discussed. Finally, emerging tendencies are described. The results of this study show how useful AI is for early, subjective ASD detection and diagnosis. More AI solutions that have the potential to be used in healthcare settings will be introduced in the future.

Neuroimaging assessment of motor neuron disease has turned into a cornerstone of its clinical workup. Amyotrophic lateral sclerosis (ALS), as a paradigmatic motor neuron disease, has been extensively studied by advanced neuroimaging methods, including molecular imaging by MRI and PET, furthering finer and more specific details of the cascade of ALS neurodegeneration and symptoms, facilitated by multicentric studies implementing novel methodologies. With an increase in multimodal neuroimaging data on ALS and an exponential improvement in neuroimaging technology, the need for harmonization of protocols and integration of their respective findings into a consistent model becomes mandatory. Integration of multimodal data into a model of a continuing cascade of functional loss also calls for the best attempt to correlate the different molecular imaging measurements as performed at the shortest inter-modality time intervals possible. As outlined in this perspective article, simultaneous PET/MRI, nowadays available at many neuroimaging research sites, offers the perspective of a one-stop shop for reproducible imaging biomarkers on neuronal damage and has the potential to become the new gold standard for characterizing motor neuron disease from the clinico-radiological and neuroscientific perspectives. [ABSTRACT FROM AUTHOR]

Mild traumatic brain injury (mTBI), commonly known as concussion, is a complex neurobehavioral phenomenon affecting six in 1000 people globally each year. Symptoms last between days and years as microstructural damage to axons and neurometabolic changes result in brain network disruption. There is no clinically available objective biomarker to diagnose the severity of injury or monitor recovery. However, emerging evidence suggests eye movement dysfunction (e.g., saccades and smooth pursuits) in patients with mTBI. Patients with a higher symptom burden and prolonged recovery time following injury may show higher degrees of eye movement dysfunction. Likewise, recent advances in magnetic resonance imaging (MRI) have revealed both white matter tract damage and functional network alterations in mTBI patients, which involve areas responsible for the ocular motor control. This scoping review is presented in three sections: Section 1 explores the anatomical control of eye movements to aid the reader with interpreting the discussion in subsequent sections. Section 2 examines the relationship between abnormal MRI findings and eye tracking after mTBI based on the available evidence. Finally, Section 3 communicates gaps in our knowledge about MRI and eye tracking, which should be addressed in order to substantiate this emerging field. [ABSTRACT FROM AUTHOR]

Objective: Increasing evidence suggests that a subcortical pathway from the superior colliculus (SC) through the pulvinar to the amygdala plays a crucial role in mediating non-conscious processing in response to emotional visual stimuli. Given the atypical eye gaze and response patterns to visual affective stimuli in autism, we examined the functional and white matter structural difference of the pathway in boys with autism spectrum disorder (ASD) and typically developing (TD) boys. Methods: A total of 38 boys with ASD and 38 TD boys were included. We reconstructed the SC-pulvinar-amygdala pathway in boys with ASD and TD using tractography and analyzed tract-specific measurements to compare the white matter difference between the two groups. A region of interest-based functional analysis was also applied among the key nodes of the pathway to explore the functional connectivity network. Results: Diffusion tensor imaging analysis showed decreased fractional anisotropy (FA) in pathways for boys with ASD compared to TD. The FA change was significantly associated with the atypical communication pattern in boys with ASD. In addition, compared to TD, we found that the ASD group was associated with increased functional connectivity between the right pulvinar and the left SC. Conclusion: Our results indicated that the functional and white matter microstructure of the subcortical route to the amygdala might be altered in individuals with autism. This atypical structural change of the SC-pulvinar-amygdala pathway may be related to the abnormal communication patterns in boys with ASD. [ABSTRACT FROM AUTHOR]

Neuroimaging assessment of motor neuron disease has turned into a cornerstone of its clinical workup. Amyotrophic lateral sclerosis (ALS), as a paradigmatic motor neuron disease, has been extensively studied by advanced neuroimaging methods, including molecular imaging by MRI and PET, furthering finer and more specific details of the cascade of ALS neurodegeneration and symptoms, facilitated by multicentric studies implementing novel methodologies. With an increase in multimodal neuroimaging data on ALS and an exponential improvement in neuroimaging technology, the need for harmonization of protocols and integration of their respective findings into a consistent model becomes mandatory. Integration of multimodal data into a model of a continuing cascade of functional loss also calls for the best attempt to correlate the different molecular imaging measurements as performed at the shortest inter-modality time intervals possible. As outlined in this perspective article, simultaneous PET/MRI, nowadays available at many neuroimaging research sites, offers the perspective of a one-stop shop for reproducible imaging biomarkers on neuronal damage and has the potential to become the new gold standard for characterizing motor neuron disease from the clinico-radiological and neuroscientific perspectives.

This brain imaging study examined subjects with a history of repetitive concussive and sub-concussive impacts sustained over the course of their careers in the Canadian Football League (CFL). We hypothesized that microstructural and functional abnormalities, assessed using diffusion tensor imaging (DTI) and resting state functional magnetic resonance imaging (rsfMRI) respectively, would be present in these retired athletes, that are not present in matched controls. Seventeen aging, retired CFL players (aged 58.5±6.2y, ranged 45–66) completed three neuropsychological tests, and had anatomical, diffusion and functional MRI scans performed. Healthy age- and sex-matched control data (n = 2117) were used to develop a subject-specific and region-wise Z-scoring approach. Regional DTI fractional anisotropy (FA) and rsfMRI signal complexity (fractal dimension; FD) Z-score data was further analyzed as a subject-specific total, left, and right injury burden (IB) value for each MRI metric. Microstructural abnormality was detected in 6 of 17 subjects based on DTI FA. The rsfMRI data showed 4 subjects with higher total FDIB, and several regions had Z-score outliers detected in multiple subjects. The right pre-motor cortex, right hippocampus dentate gyrus, and right visual cortex were the most abnormally functioning grey matter brain regions. Total FAIB was negatively correlated with career length, social functioning, and significantly with emotional well-being, and positively correlated with physical health. Total FDIB was negatively correlated with energy and fatigue and general health, and positively correlated with age, career length, and education. This study provides evidence of brain changes years after professional athletes have retired.

ObjectiveIncreasing evidence suggests that a subcortical pathway from the superior colliculus (SC) through the pulvinar to the amygdala plays a crucial role in mediating non-conscious processing in response to emotional visual stimuli. Given the atypical eye gaze and response patterns to visual affective stimuli in autism, we examined the functional and white matter structural difference of the pathway in boys with autism spectrum disorder (ASD) and typically developing (TD) boys.MethodsA total of 38 boys with ASD and 38 TD boys were included. We reconstructed the SC-pulvinar-amygdala pathway in boys with ASD and TD using tractography and analyzed tract-specific measurements to compare the white matter difference between the two groups. A region of interest-based functional analysis was also applied among the key nodes of the pathway to explore the functional connectivity network.ResultsDiffusion tensor imaging analysis showed decreased fractional anisotropy (FA) in pathways for boys with ASD compared to TD. The FA change was significantly associated with the atypical communication pattern in boys with ASD. In addition, compared to TD, we found that the ASD group was associated with increased functional connectivity between the right pulvinar and the left SC.ConclusionOur results indicated that the functional and white matter microstructure of the subcortical route to the amygdala might be altered in individuals with autism. This atypical structural change of the SC-pulvinar-amygdala pathway may be related to the abnormal communication patterns in boys with ASD.

In Alzheimer Disease (AD), non-verbal skills often remain intact for far longer than verbally mediated processes. Four (1 female, 3 males) participants with early-stage Clinically Diagnosed Dementia of the Alzheimer Type (CDDAT) and eight neurotypicals (NTs; 4 females, 4 males) completed the emotional valence determination test (EVDT) while undergoing BOLD functional magnetic resonance imaging (fMRI). We expected CDDAT participants to perform just as well as NTs on the EVDT, and to display increased activity within the bilateral amygdala and right anterior cingulate cortex (r-ACC). We hypothesized that such activity would reflect an increased reliance on these structures to compensate for on-going neuronal loss in frontoparietal regions due to the disease. We used diffusion tensor imaging (DTI) to determine if white matter (WM) damage had occurred in frontoparietal regions as well. CDDAT participants had similar behavioral performance and no differences were observed in brain activity or connectivity patterns within the amygdalae or r-ACC. Decreased fractional anisotropy (FA) values were noted, however, for the bilateral superior longitudinal fasciculi and posterior cingulate cortex (PCC). We interpret these findings to suggest that emotional valence determination and non-verbal skill sets are largely intact at this stage of the disease, but signs foreshadowing future decline were revealed by possible WM deterioration. Understanding how non-verbal skill sets are altered, while remaining largely intact, offers new insights into how non-verbal communication may be more successfully implemented in the care of AD patients and highlights the potential role of DTI as a presymptomatic biomarker.

BackgroundNonhuman primate models are critical for understanding mechanisms underlying human psychopathology. We established a nonhuman primate model of anxious temperament (AT) for studying the early-life risk to develop anxiety and depression. Studies have identified the central nucleus of the amygdala (Ce) as an essential component of AT's neural substrates. Corticotropin-releasing factor (CRF) is expressed in the Ce, has a role in stress, and is linked to psychopathology. Here, in young rhesus monkeys, we combined viral vector technology with assessments of anxiety and multimodal neuroimaging to understand the consequences of chronically increased CRF in the Ce region.MethodsUsing real-time intraoperative magnetic resonance imaging-guided convection-enhanced delivery, five monkeys received bilateral dorsal amygdala Ce-region infusions of adeno-associated virus serotype 2 containing the CRF construct. Their cagemates served as unoperated control subjects. AT, regional brain metabolism, resting functional magnetic resonance imaging, and diffusion tensor imaging were assessed before and 2 months after viral infusions.ResultsDorsal amygdala CRF overexpression significantly increased AT and metabolism within the dorsal amygdala. Additionally, we observed changes in metabolism in other AT-related regions, as well as in measures of functional and structural connectivity.ConclusionsThis study provides a translational roadmap that is important for understanding human psychopathology by combining molecular manipulations used in rodents with behavioral phenotyping and multimodal neuroimaging measures used in humans. The results indicate that chronic CRF overexpression in primates not only increases AT but also affects metabolism and connectivity within components of AT's neural circuitry.

Body dysmorphic disorder (BDD) is characterized by an individual's preoccupation with a perceived defect in their appearance which to others may be barely noticeable or even completely unnoticed. It confers significant disturbances of everyday functioning in affected persons. The present review study provides an overview of neuroimaging findings on BDD. Literature on three platforms, PubMed, Google Scholar and PsycArticles of APA PsycNet, was searched for studies on patients with BBD compared with healthy controls (HCs), with a focus on neuroimaging findings. Out of an initial yield of 414 articles, 23 fulfilled inclusion criteria and were reviewed. Among the most remarkable findings were functional abnormalities in visual processing, frontostriatal and limbic systems, reduced global efficiency of White Matter (WM) connectivity, reduced cortical thickness in temporal and parietal lobes, and correlations between these neuroimaging findings and clinical variables such as symptom severity and degree of insight. Structural, volumetric and functional neuroimaging findings in BDD affected persons may help shed light on the pathophysiology and neurobiological underpinnings of this condition. Future studies should further investigate the use of imaging findings as potential prognostic biomarkers of treatment efficacy and disease outcome. [ABSTRACT FROM AUTHOR]