Subcortical Brain Structures Research Articles

Functional properties of eyelid conditioned responses and involved brain centers.

For almost a century the classical conditioning of nictitating membrane/eyelid responses has been used as an excellent and feasible experimental model to study how the brain organizes the acquisition, storage, and retrieval of new motor abilities in alert behaving mammals, including humans. Lesional, pharmacological, and electrophysiological approaches, and more recently, genetically manipulated animals have shown the involvement of numerous brain areas in this apparently simple example of associative learning. In this regard, the cerebellum (both cortex and nuclei) has received particular attention as a putative site for the acquisition and storage of eyelid conditioned responses, a proposal not fully accepted by all researchers. Indeed, the acquisition of this type of learning implies the activation of many neural processes dealing with the sensorimotor integration and the kinematics of the acquired ability, as well as with the attentional and cognitive aspects also involved in this process. Here, we address specifically the functional roles of three brain structures (red nucleus, cerebellar interpositus nucleus, and motor cortex) mainly involved in the acquisition and performance of eyelid conditioned responses and three other brain structures (hippocampus, medial prefrontal cortex, and claustrum) related to non-motor aspects of the acquisition process. The main conclusion is that the acquisition of this motor ability results from the contribution of many cortical and subcortical brain structures each one involved in specific (motor and cognitive) aspects of the learning process.

The IAS-MEEG Package: A Flexible Inverse Source Reconstruction Platform for Reconstruction and Visualization of Brain Activity from M/EEG Data

We present a standalone Matlab software platform complete with visualization for the reconstruction of the neural activity in the brain from MEG or EEG data. The underlying inversion combines hierarchical Bayesian models and Krylov subspace iterative least squares solvers. The Bayesian framework of the underlying inversion algorithm allows to account for anatomical information and possible a priori belief about the focality of the reconstruction. The computational efficiency makes the software suitable for the reconstruction of lengthy time series on standard computing equipment. The algorithm requires minimal user provided input parameters, although the user can express the desired focality and accuracy of the solution. The code has been designed so as to favor the parallelization performed automatically by Matlab, according to the resources of the host computer. We demonstrate the flexibility of the platform by reconstructing activity patterns with supports of different sizes from MEG and EEG data. Moreover, we show that the software reconstructs well activity patches located either in the subcortical brain structures or on the cortex. The inverse solver and visualization modules can be used either individually or in combination. We also provide a version of the inverse solver that can be used within Brainstorm toolbox. All the software is available online by Github, including the Brainstorm plugin, with accompanying documentation and test data.

Subcortical brain structure and APOE genotype: An analysis of 43,000 participants from the UK Biobank

AbstractBackgroundCarriers of the ε4 allele of the apolipoprotein (APOE) gene are at higher risk for developing Alzheimer’s disease (AD). In individuals with mild cognitive impairment or AD, the ε4 allele is associated with lower hippocampal and amygdala volumes. How ε4 affects brain structure in healthy individuals before AD symptom onset is less clear. APOE ε2 allele carriers may show slower rates of hippocampal volume loss, suggesting protection against AD. In this large‐scale analysis, we plot normative regional brain volume trajectories in adults (45‐82 years) and map regional subcortical volume differences between APOE genotypes.MethodWe used FreeSurfer 7.1 to segment average left and right accumbens, amygdala, caudate, hippocampus, pallidum, putamen, thalamus and lateral ventricle volumes from T1‐weighted brain MRI (N=43,000). Comparisons between APOE genotypes (ε2ε2, n=257; ε2ε3, n=5,479; ε3ε3, n=26,016; ε3ε4, n=10,263; ε4ε4, n=985) were made using linear mixed effect models, correcting for population structure, age, sex, and intracranial volume (ICV) as fixed effects, and site as a random effect. Results were adjusted for multiple comparisons (FDR q<0.05). Nomograms were derived by adjusting subcortical volumes for population structure, ICV, and site then fitting normative quantile regression models based on the standardized residuals for each region stratified by genotype.ResultNomograms showed similar age‐related trajectories for all APOE genotypes, with smaller gray matter volume and larger ventricle volumes with increasing age. Significantly smaller amygdala and hippocampal volumes were found in ε4ε4 compared to ε3ε4, ε3ε3, and ε2ε3 carriers, and smaller amygdala volumes in ε2ε2 versus ε3ε3 carriers. Smaller accumbens volumes were found in ε4ε4 carriers versus ε2ε3 and ε3ε3, and in ε3ε4 versus ε3ε3 and ε2ε3. Smaller thalamus volumes were found in ε3ε4 versus ε2ε3 and ε3ε3, ε4ε4 carriers had smaller volumes versus ε2ε3 and ε3ε3, and ε2ε2 carriers had smaller volumes versus ε2ε3 and ε3ε3.ConclusionIn this large sample of generally healthy individuals, APOE ε4 allele carriers exhibited lower subcortical volumes compared to those with more neutral AD genetic risk background (ε3ε3). Carriers of ε2ε2 had smaller thalamus and amygdala volumes compared to ε3ε3, suggesting differential effects of AD genetic risk across brain structures known to play a role in AD pathophysiology.

Higher arterial stiffness and systolic blood pressure are differentially associated with lower perfusion in subcortical and cortical gray matter regions

AbstractBackgroundHigher arterial stiffness is associated with lower regional cerebral blood flow (CBF) in older adults. Cortical CBF also correlates with higher systolic blood pressure (SBP). We examined relationships of lobar and deep gray matter CBF with both SBP and arterial stiffness.MethodParticipants of the Clinical Core of the Wake Forest Alzheimer’s Disease Research Center completed baseline clinical examination including measures of: arterial stiffness, blood pressure, medication review, APOE genotyping, 3T MRI, detailed cognitive testing, and cognitive adjudication. T1 structural and pseudocontinuous arterial spin labeling (pcASL) MRI were used to quantify gray matter (GM) CBF in AAL atlas regions. GM CBF was quantified into lobar (frontal, temporal, parietal, occipital), subcortical (caudate, putamen, pallidum, and thalamus), Cingulate/Insula, and posterior (cerebellum and vermis) regions. Arterial stiffness was measured twice in the supine position and averaged to quantify carotid‐femoral pulse wave velocity (cfPWV). Associations for cfPWV and systolic blood pressure (SBP) with GM CBF ROIs was examined by multivariable linear regression models adjusted for age, race, gender, education, hypertension medications, and APOE‐e4 carrier status.Result:Among 404 participants (70±8 years; 39 dementia, 139 MCI, 226 normal cognition), higher cfPWV and SBP were differentially associated with regional GM CBF (Fig 1 & 2). Higher cfPWV was associated with lower subcortical GM CBF (p=0.04) (Table 1). Higher SBP was associated with lower GM CBF in frontal (p=0.03), temporal (p=0.02) and occipital lobes (p=0.01) (Table 1).ConclusionDeep subcortical brain structures may be at greater risk of damage from high arterial stiffness because they are perfused by arteries which branch relatively upstream of other branching arteries, as evidenced by lower GM CBF. High SBP may predict vascular damage in cortical regions manifested as lower GM CBF. These differential relationships with deep and cortical perfusion support and extend prior observations in this group relating vascular risk factors to abnormalities in white matter micro‐ and macro‐ structure, lower total CBF, and lower cognitive performance.

Higher arterial stiffness and systolic blood pressure are differentially associated with lower perfusion in subcortical and cortical gray matter regions

AbstractBackgroundHigher arterial stiffness is associated with lower regional cerebral blood flow (CBF) in older adults. Cortical CBF also correlates with higher systolic blood pressure (SBP). We examined relationships of lobar and deep gray matter CBF with both SBP and arterial stiffness.MethodParticipants of the Clinical Core of the Wake Forest Alzheimer’s Disease Research Center completed baseline clinical examination including measures of: arterial stiffness, blood pressure, medication review, APOE genotyping, 3T MRI, detailed cognitive testing, and cognitive adjudication. T1 structural and pseudocontinuous arterial spin labeling (pcASL) MRI were used to quantify gray matter (GM) CBF in AAL atlas regions. GM CBF was quantified into lobar (frontal, temporal, parietal, occipital), subcortical (caudate, putamen, pallidum, and thalamus), Cingulate/Insula, and posterior (cerebellum and vermis) regions. Arterial stiffness was measured twice in the supine position and averaged to quantify carotid‐femoral pulse wave velocity (cfPWV). Associations for cfPWV and systolic blood pressure (SBP) with GM CBF ROIs was examined by multivariable linear regression models adjusted for age, race, gender, education, hypertension medications, and APOE‐e4 carrier status.ResultAmong 404 participants (70±8 years; 39 dementia, 139 MCI, 226 normal cognition), higher cfPWV and SBP were differentially associated with regional GM CBF (Fig 1 & 2). Higher cfPWV was associated with lower subcortical GM CBF (p=0.04) (Table 1). Higher SBP was associated with lower GM CBF in frontal (p=0.03), temporal (p=0.02) and occipital lobes (p=0.01) (Table 1).ConclusionDeep subcortical brain structures may be at greater risk of damage from high arterial stiffness because they are perfused by arteries which branch relatively upstream of other branching arteries, as evidenced by lower GM CBF. High SBP may predict vascular damage in cortical regions manifested as lower GM CBF. These differential relationships with deep and cortical perfusion support and extend prior observations in this group relating vascular risk factors to abnormalities in white matter micro‐ and macro‐ structure, lower total CBF, and lower cognitive performance.

Physical activity, sedentary time, and fitness in relation to brain shapes in children with overweight/obesity: Links to intelligence.

To examine the association between physical activity, sedentary time, and physical fitness with the shapes of subcortical brain structures in children with overweight/obesity. Further, we analyzed whether differences in the shapes of subcortical brain structures were related to intelligence. We hypothesized that those children with higher physical activity levels, lower sedentary time, and better fitness, would show greater expansion of the brain regions analyzed, and these expansions would be associated with higher intelligence. 100 children (10.0 ± 1.1 years, 40 girls) were included in the analyses. Physical activity and sedentary time were measured by accelerometry, and physical fitness was evaluated by a fitness battery. Shapes of subcortical brain structures were assessed by magnetic resonance imaging. Intelligence was measured by the Kaufmann Brief Intelligence test. Physical activity was related to expansion of the right/left pallidum, right/left putamen, and right thalamus (p < 0.05). Higher sedentary time was related to contraction of the left thalamus and right nucleus accumbens (p < 0.05). Higher levels of cardiorespiratory fitness were associated with expansion of the right amygdala (p=0.022). Greater strength in the upper-limb was related to expansion of the right/left pallidum and the left nucleus accumbens (p < 0.038), and contraction of the left amygdala (p=0.030). Better speed-agility was associated with expansion of the left nucleus accumbens (p=0.036). Physical activity- and fitness-related expansion of the right pallidum was associated with higher intelligence (all p < 0.05). Physical activity, sedentary time, and physical fitness were significantly related to the shapes of subcortical brain structures, which in turn were related to intelligence in children with overweight/obesity.

Mapping gene by early life stress interactions on child subcortical brain structures: A genome-wide prospective study.

Although it is well-established that both genetics and the environment influence brain development, they are typically examined separately. Here, we aimed to prospectively investigate the interactive effects of genetic variants-from a genome-wide approach-and early life stress (ELS) on child subcortical brain structures, and their association with subsequent mental health problems. Primary analyses were conducted using data from the Generation R Study (N = 2257), including genotype and cumulative prenatal and postnatal ELS scores (encompassing life events, contextual risk, parental risk, interpersonal risk, direct victimisation). Neuroimaging data were collected at age 10 years, including intracranial and subcortical brain volumes (accumbens, amygdala, caudate, hippocampus, pallidum, putamen, thalamus). Genome-wide association and genome-wide-by-environment interaction analyses (GWEIS, run separately for prenatal/postnatal ELS) were conducted for eight brain outcomes (i.e., 24 genome-wide analyses) in the Generation R Study (discovery). Polygenic scores (PGS) using the resulting weights were calculated in an independent (target) cohort (adolescent brain cognitive development Study; N = 10,751), to validate associations with corresponding subcortical volumes and examine links to later mother-reported internalising and externalising problems. One GWEIS-prenatal stress locus was associated with caudate volume (rs139505895, mapping onto PRSS12 and NDST3) and two GWEIS-postnatal stress loci with the accumbens (rs2397823 and rs3130008, mapping onto CUTA, SYNGAP1, and TABP). Functional annotation revealed that these genes play a role in neuronal plasticity and synaptic function, and have been implicated in neuro-developmental phenotypes, for example, intellectual disability, autism, and schizophrenia. None of these associations survived a more stringent correction for multiple testing across all analysis sets. In the validation sample, all PGSgenotype were associated with their respective brain volumes, but no PGSGxE associated with any subcortical volume. None of the PGS associated with internalising or externalising problems. This study lends novel suggestive insights into gene-environment interplay on the developing brain as well as pointing to promising candidate loci for future replication and mechanistic studies.

Learning to segment subcortical structures from noisy annotations with a novel uncertainty-reliability aware learning framework

Accurate segmentation of subcortical structures is an important task in quantitative brain image analysis. Convolutional neural networks (CNNs) have achieved remarkable results in medical image segmentation. However, due to the difficulty of acquiring high-quality annotations of brain subcortical structures, learning segmentation networks using noisy annotations is an inevitable topic. A common practice is to select images or pixels with reliable annotations for training, which usually may not make full use of the information from the training samples, thus affecting the performance of the learned segmentation model. To address the above problem, in this work, we propose a novel robust learning method and denote it as uncertainty-reliability awareness learning (URAL), which can make sufficient use of all training pixels. At each training iteration, the proposed method first selects training pixels with reliable annotations from the set of pixels with uncertain network prediction, by utilizing a small clean validation set following a meta-learning paradigm. Meanwhile, we propose the online prototypical soft label correction (PSLC) method to estimate the pseudo-labels of label-unreliable pixels. Then, the segmentation loss of label-reliable pixels and the semi-supervised segmentation loss of label-unreliable pixels are used to calibrate the total segmentation loss. Finally, we propose a category-wise contrastive regularization to learn compact feature representations of all uncertain training pixels. Comprehensive experiments are performed on two publicly available brain MRI datasets. The proposed method achieves the best Dice scores and MHD values on both datasets compared to several recent state-of-the-art methods under all label noise settings. Our code is available at https://github.com/neulxlx/URAL.

Fusion of quantitative susceptibility maps and T1-weighted images improve brain tissue contrast in primates

Recent progress in quantitative susceptibility mapping (QSM) has enabled the accurate delineation of submillimeter-scale subcortical brain structures in humans. However, the simultaneous visualization of cortical, subcortical, and white matter structure remains challenging, utilizing QSM data solely. Here we present TQ-SILiCON, a fusion method that enhances the contrast of cortex and subcortical structures and provides an excellent white matter delineation by combining QSM and conventional T1-weighted (T1w) images. In this study, we first applied QSM in the macaque monkey to map iron-rich subcortical structures. Implementing the same QSM acquisition and analysis methods allowed a similar accurate delineation of subcortical structures in humans. However, the QSM contrast of white and cortical gray matter was not sufficient for appropriate segmentation. Applying automatic brain tissue segmentation to TQ-SILiCON images of the macaque improved the classification of subcortical brain structures as compared to the single T1 contrast by maintaining an excellent white to cortical gray matter contrast. Furthermore, we validated our dual-contrast fusion approach in humans and similarly demonstrated improvements in automated segmentation of the cortex and subcortical structures. We believe the proposed contrast will facilitate translational studies in nonhuman primates to investigate the pathophysiology of neurodegenerative diseases that affect subcortical structures such as the basal ganglia in humans.

Corticobasal syndrome and Parkinson’s disease at the beginning: asymmetrical patterns of MRI and Blink Reflex for early diagnosis

Differential diagnosis between Parkinson’s disease (PD) and corticobasal syndrome (CBS) could be challenging at the early stage, due to the asymmetric onset of both diseases. Despite the clinical overlap, the anatomical circuits involved in these disorders are different. We evaluated R2 Blink Reflex Recovery Cycle (R2BRRC) and cortical thickness (CTh) in drug-naïve PD and CBS patients for characterizing pathophysiological mechanisms underlying these conditions. Patients with a clinically probable diagnosis of PD and possible CBS were recruited. R2BRRC was evaluated bilaterally at interstimulus intervals (ISIs) of 100–150–200–300–400–500–750 ms. Asymmetry index (AI) of R2BRRC for each ISI was computed. Patients underwent a structural brain MRI and hemisphere CTh and AI of MRI was calculated. Fourteen drug-naïve PD patients and 10 patients with early CBS diagnosis were enrolled. R2BRRC of PD patients showed an increased brainstem excitability for less affected side (LAS) stimulation at ISIs of 100 and 150 ms (p < 0.001) compared to most affected side (MAS), whereas no differences between LAS and MAS were found in CBS. AI of R2BRRC at ISI-100 ms showed significant difference, being higher in PD. CTh analysis showed significant differences between groups in hemisphere cortical volume contralateral to MAS, and, conversely, AI of MRI was significantly higher in CBS. PD patients exhibited an asymmetric pattern of brainstem excitability, compared to CBS. Conversely, CBS patients showed an asymmetric pattern of cortical atrophy. This opposite pattern of neurophysiological and structural abnormalities involving cortical and subcortical brain structures could highlight the different pathophysiological mechanisms underlying these disorders.

Anatomically curated segmentation of human subcortical structures in high resolution magnetic resonance imaging: An open science approach.

Magnetic resonance imaging (MRI)-based brain segmentation has recently been revolutionized by deep learning methods. These methods use large numbers of annotated segmentations to train algorithms that have the potential to perform brain segmentations reliably and quickly. However, training data for these algorithms are frequently obtained from automated brain segmentation systems, which may contain inaccurate neuroanatomy. Thus, the neuroimaging community would benefit from an open source database of high quality, neuroanatomically curated and manually edited MRI brain images, as well as the publicly available tools and detailed procedures for generating these curated data. Manual segmentation approaches are regarded as the gold standard for brain segmentation and parcellation. These approaches underpin the construction of neuroanatomically accurate human brain atlases. In addition, neuroanatomically precise definitions of MRI-based regions of interest (ROIs) derived from manual brain segmentation are essential for accuracy in structural connectivity studies and in surgical planning for procedures such as deep brain stimulation. However, manual segmentation procedures are time and labor intensive, and not practical in studies utilizing very large datasets, large cohorts, or multimodal imaging. Automated segmentation methods were developed to overcome these issues, and provide high data throughput, increased reliability, and multimodal imaging capability. These methods utilize manually labeled brain atlases to automatically parcellate the brain into different ROIs, but do not have the anatomical accuracy of skilled manual segmentation approaches. In the present study, we developed a custom software module for manual editing of brain structures in the freely available 3D Slicer software platform that employs principles and tools based on pioneering work from the Center for Morphometric Analysis (CMA) at Massachusetts General Hospital. We used these novel 3D Slicer segmentation tools and techniques in conjunction with well-established neuroanatomical definitions of subcortical brain structures to manually segment 50 high resolution T1w MRI brains from the Human Connectome Project (HCP) Young Adult database. The structural definitions used herein are associated with specific neuroanatomical ontologies to systematically interrelate histological and MRI-based morphometric definitions. The resulting brain datasets are publicly available and will provide the basis for a larger database of anatomically curated brains as an open science resource.

Eye Movement Abnormalities in Glaucoma Patients: A Review.

Glaucoma is a common condition that relies on careful clinical assessment to diagnose and determine disease progression. There is growing evidence that glaucoma is associated not only with loss of retinal ganglion cells but also with degeneration of cortical and subcortical brain structures associated with vision and eye movements. The effect of glaucoma pathophysiology on eye movements is not well understood. In this review, we examine the evidence surrounding altered eye movements in glaucoma patients compared to healthy controls, with a focus on quantitative eye tracking studies measuring saccades, fixation, and optokinetic nystagmus in a range of visual tasks. The evidence suggests that glaucoma patients have alterations in several eye movement domains. Patients exhibit longer saccade latencies, which worsen with increasing glaucoma severity. Other saccadic abnormalities include lower saccade amplitude and velocity, and difficulty inhibiting reflexive saccades. Fixation is pathologically altered in glaucoma with reduced stability. Optokinetic nystagmus measures have also been shown to be abnormal. Complex visual tasks (eg reading, driving, and navigating obstacles), integrate these eye movements and result in behavioral adaptations. The review concludes with a summary of the evidence and recommendations for future research in this emerging field.

Associations of medication with subcortical morphology across the lifespan in OCD: Results from the international ENIGMA Consortium

BackgroundWidely used psychotropic medications for obsessive-compulsive disorder (OCD) may change the volumes of subcortical brain structures, and differently in children vs. adults. We measured subcortical volumes cross-sectionally in patients finely stratified for age taking various common classes of OCD drugs. MethodsThe ENIGMA-OCD consortium sample (1081 medicated/1159 unmedicated OCD patients and 2057 healthy controls aged 6–65) was divided into six successive 6–10-year age-groups. Individual structural MRIs were parcellated automatically using FreeSurfer into 8 regions-of-interest (ROIs). ROI volumes were compared between unmedicated and medicated patients and controls, and between patients taking serotonin reuptake inhibitors (SRIs), tricyclics (TCs), antipsychotics (APs), or benzodiazepines (BZs) and unmedicated patients. ResultsCompared to unmedicated patients, volumes of accumbens, caudate, and/or putamen were lower in children aged 6–13 and adults aged 50–65 with OCD taking SRIs (Cohen's d = −0.24 to −0.74). Volumes of putamen, pallidum (d = 0.18–0.40), and ventricles (d = 0.31–0.66) were greater in patients aged 20–29 receiving APs. Hippocampal volumes were smaller in patients aged 20 and older taking TCs and/or BZs (d = −0.27 to −1.31). ConclusionsResults suggest that TCs and BZs could potentially aggravate hippocampal atrophy of normal aging in older adults with OCD, whereas SRIs may reduce striatal volumes in young children and older adults. Similar to patients with psychotic disorders, OCD patients aged 20–29 may experience subcortical nuclear and ventricular hypertrophy in relation to APs. Although cross-sectional, present results suggest that commonly prescribed agents exert macroscopic effects on subcortical nuclei of unknown relation to therapeutic response.

Altered asymmetries of resting-state MRI in the left thalamus of first-episode schizophrenia.

BackgroundSchizophrenia (SCZ) is a complex psychiatric disorder associated with widespread alterations in the subcortical brain structure. Hemispheric asymmetries are a fundamental organizational principle of the human brain and relate to human psychological and behavioral characteristics. We aimed to explore the state of thalamic lateralization of SCZ.MethodsWe used voxel‐based morphometry (VBM) analysis, whole‐brain analysis of low‐frequency fluctuations (ALFF), fractional amplitude of low‐frequency fluctuations (fALFF), and resting‐state seed‐based functional connectivity (FC) analysis to investigate brain structural and functional deficits in SCZ. Also, we applied Pearson's correlation analysis to validate the correlation between Positive and Negative Symptom Scale (PANSS) scores and them.ResultsCompared with healthy controls, SCZ showed increased gray matter volume (GMV) of the left thalamus (t = 2.214, p = 0.029), which positively correlated with general psychosis (r = 0.423, p = 0.010). SCZ also showed increased ALFF in the putamen, the caudate nucleus, the thalamus, fALFF in the nucleus accumbens (NAc), and the caudate nucleus, and decreased fALFF in the precuneus. The left thalamus showed significantly weaker resting‐state FC with the amygdala and insula in SCZ. PANSS negative symptom scores were negatively correlated with the resting‐state FC between the thalamus and the insula (r = −0.414, p = 0.025).ConclusionsCollectively, these results suggest the possibility of aberrant laterality in the left thalamus and its FC with other related brain regions involved in the limbic system.

Cerebral mechanism of Tuina analgesia in management of knee osteoarthritis using multimodal MRI: study protocol for a randomised controlled trial

BackgroundThe chronic pain of patients with knee osteoarthritis (KOA) seriously affects their quality of life and leads to heavy social and economic burden. As a nondrug therapy in Traditional Chinese Medicine (TCM), Tuina is generally recognised as safe and effective for reducing the chronic pain of KOA. However, the underlying central mechanisms of Tuina for improving the pain of KOA are not fully understood.Methods/designThis study will be a randomised controlled trial with a parallel-group design. A total of 60 eligible participants will be assigned to the Tuina group or healthcare education group (Education group) at 1:1 ratio using stratified randomisation with gender and age as factors. The interventions of both groups will last for 30 min per session and be conducted twice each week for 12 weeks. This study will primarily focus on pain evaluation assessed by detecting the changes in brain grey matter (GM) structure, white matter (WM) structure, and the cerebral functional connectivity (FC) elicited by Tuina treatment, e.g., thalamus, hippocampus, anterior cingulate gyrus, S1, insula, and periaqueductal grey subregions (PAG). The two groups of patients will be evaluated by clinical assessments and multimodal magnetic resonance imaging (MRI) to observe the alterations in the GM, WM, and FC of participants at the baseline and the end of 6 and 12 weeks’ treatment and still be evaluated by clinical assessments but not MRI for 48 weeks of follow-up. The visual analogue scale of current pain is the primary outcome. The Short-Form McGill Pain Questionnaire, Western Ontario and McMaster Universities Osteoarthritis Index, 36-Item Short Form Health Survey, Hamilton Depression Scale, and Hamilton Anxiety Scale will be used to evaluate the pain intensity, pain feeling, pain emotion, clinical symptoms, and quality of life, respectively. MRI assessments, clinical data evaluators, data managers, and statisticians will be blinded to the group allocation in the outcome evaluation procedure and data analysis to reduce the risk of bias. The repeated measures analysis of variance (2 groups × 6 time points ANOVA) will be used to analyse numerical variables of the clinical and neuroimaging data obtained in the study. P<0.05 will be the statistical significance level.DiscussionThe results of this randomised controlled trial with clinical assessments and multimodal MRI will help reveal the influence of Tuina treatment on the potential morphological changes in cortical and subcortical brain structures, the white matter integrity, and the functional activities and connectivity of brain regions of patients with KOA, which may provide scientific evidence for the clinical application of Tuina in the management of KOA.Trial registrationChinese Clinical Trial Registry ChiCTR2000037966. Registered on Sep. 8, 2020.DisseminationThe results will be published in peer-reviewed journals and disseminated through the study’s website, and conferences.

7T functional MRI finds no evidence for distinct functional subregions in the subthalamic nucleus during a speeded decision-making task

The subthalamic nucleus (STN) is a small, subcortical brain structure. It is a target for deep brain stimulation, an invasive treatment that reduces motor symptoms of Parkinson's disease. Side effects of DBS are commonly explained using the tripartite model of STN organization, which proposes three functionally distinct subregions in the STN specialized in cognitive, limbic, and motor processing. However, evidence for the tripartite model exclusively comes from anatomical studies and functional studies using clinical patients. Here, we provide the first experimental tests of the tripartite model in healthy volunteers using ultra-high field 7 Tesla (T) functional magnetic resonance imaging (fMRI). Thirty-four participants performed a random-dot motion decision-making task with a difficulty manipulation and a choice payoff manipulation aimed to differentially affect cognitive and limbic networks. Moreover, participants responded with their left and right index finger, differentially affecting motor networks. We analysed BOLD signal in three subregions of the STN along the dorsolateral–ventromedial axis, identified using manually delineated high resolution anatomical images and based on a previously published atlas. Using these paradigms, all segments responded equally to the experimental manipulations, and the tasks did not provide evidence for the tripartite model.

Neuropeptide System Regulation of Prefrontal Cortex Circuitry: Implications for Neuropsychiatric Disorders

Neuropeptides, a diverse class of signaling molecules in the nervous system, modulate various biological effects including membrane excitability, synaptic transmission and synaptogenesis, gene expression, and glial cell architecture and function. To date, most of what is known about neuropeptide action is limited to subcortical brain structures and tissue outside of the central nervous system. Thus, there is a knowledge gap in our understanding of neuropeptide function within cortical circuits. In this review, we provide a comprehensive overview of various families of neuropeptides and their cognate receptors that are expressed in the prefrontal cortex (PFC). Specifically, we highlight dynorphin, enkephalin, corticotropin-releasing factor, cholecystokinin, somatostatin, neuropeptide Y, and vasoactive intestinal peptide. Further, we review the implication of neuropeptide signaling in prefrontal cortical circuit function and use as potential therapeutic targets. Together, this review summarizes established knowledge and highlights unknowns of neuropeptide modulation of neural function underlying various biological effects while offering insights for future research. An increased emphasis in this area of study is necessary to elucidate basic principles of the diverse signaling molecules used in cortical circuits beyond fast excitatory and inhibitory transmitters as well as consider components of neuropeptide action in the PFC as a potential therapeutic target for neurological disorders. Therefore, this review not only sheds light on the importance of cortical neuropeptide studies, but also provides a comprehensive overview of neuropeptide action in the PFC to serve as a roadmap for future studies in this field.

Elucidating the relationship between migraine risk and brain structure using genetic data.

Migraine is a highly common and debilitating disorder that often affects individuals in their most productive years of life. Previous studies have identified both genetic variants and brain morphometry differences associated with migraine risk. However, the relationship between migraine and brain morphometry has not been examined on a genetic level, and the causal nature of the association between brain structure and migraine risk has not been determined. Using the largest available genome-wide association studies to date, we examined the genome-wide genetic overlap between migraine and intracranial volume, as well as the regional volumes of nine subcortical brain structures. We further focused the identification and biological annotation of genetic overlap between migraine and each brain structure on specific regions of the genome shared between migraine and brain structure. Finally, we examined whether the size of any of the examined brain regions causally increased migraine risk using a Mendelian randomization approach. We observed a significant genome-wide negative genetic correlation between migraine risk and intracranial volume (rG = -0.11, P = 1 × 10-3) but not with any subcortical region. However, we identified jointly associated regional genomic overlap between migraine and every brain structure. Gene enrichment in these shared genomic regions pointed to possible links with neuronal signalling and vascular regulation. Finally, we provide evidence of a possible causal relationship between smaller total brain, hippocampal and ventral diencephalon volume and increased migraine risk, as well as a causal relationship between increased risk of migraine and a larger volume of the amygdala. We leveraged the power of large genome-wide association studies to show evidence of shared genetic pathways that jointly influence migraine risk and several brain structures, suggesting that altered brain morphometry in individuals with high migraine risk may be genetically mediated. Further interrogation of these results showed support for the neurovascular hypothesis of migraine aetiology and shed light on potentially viable therapeutic targets.

Volumetric study of brain MRI in a cohort of patients with neurotransmitter disorders.

Inborn errors of neurotransmitters are rare monogenic diseases. In general, conventional neuroimaging is not useful for diagnosis. Nevertheless, advanced neuroimaging techniques could provide novel diagnosis and prognosis biomarkers. We aim to describe cerebral volumetric findings in a group of Spanish patients with neurotransmitter disorders. Fifteen 3D T1-weighted brain images from the International Working Group on Neurotransmitter related Disorders Spanish cohort were assessed (eight with monoamine and seven with amino acid disorders). Volumes of cortical and subcortical brain structures were obtained for each patient and then compared with those of two healthy individuals matched by sex and age. Regardless of the underlying disease, patients showed a smaller total cerebral tissue volume, which was apparently associated with clinical severity. A characteristic volumetric deficit pattern, including the right Heschl gyrus and the bilateral occipital gyrus, was identified. In severe cases, a distinctive pattern comprised the middle and posterior portions of the right cingulate, the left superior motor area and the cerebellum. In succinate semialdehyde dehydrogenase deficiency, volumetric affection seems to worsen over life. Despite the heterogeneity and limited size of our cohort, we found novel and relevant data. Total volume deficit appears to be a marker of severity, regardless of the specific neurotransmitter disease and irrespective of the information obtained from conventional neuroimaging. Volumetric assessment of individual brain structures could provide a deeper knowledge about pathophysiology, disease severity and specific clinical traits.

Subcortical brain structures and the risk of dementia in the Rotterdam Study.

Volumetric and morphological changes in subcortical brain structures are present in persons with dementia, but it is unknown if these changes occur prior to diagnosis. Between 2005 and 2016, 5522 Rotterdam Study participants (mean age: 64.4) underwent cerebral magnetic resonance imaging (MRI) and were followed for development of dementia until 2018. Volume and shape measures were obtained for seven subcortical structures. During 12 years of follow-up, 272 dementia cases occurred. Mean volumes of thalamus (hazard ratio [HR] per standard deviation [SD] decrease 1.94, 95% confidence interval [CI]: 1.55-2.43), amygdala (HR 1.66, 95% CI: 1.44-1.92), and hippocampus (HR 1.64, 95% CI: 1.43-1.88) were strongly associated with dementia risk. Associations for accumbens, pallidum, and caudate volumes were less pronounced. Shape analyses identified regional surface changes in the amygdala, limbic thalamus, and caudate. Structure of the amygdala, thalamus, hippocampus, and caudate is associated with risk of dementia in a large population-based cohort of older adults.