Deep Brain Nuclei Research Articles

Correlation between iron deposition and cognitive function in mild to moderate Alzheimer's disease based on quantitative susceptibility mapping.

Alzheimer's disease (AD) is a complex neurodegenerative disorder characterized by progressively worsening cognitive decline and memory loss. Excessive iron accumulation produces severe cognitive impairment. However, there are no uniform conclusions about changes in brain iron content in AD. This study aimed to investigate the iron content of the deep brain nuclei in AD, and its correlation with cognitive function. Thirty-one patients with mild to moderate AD, 17 patients with mild cognitive impairment (MCI), and 20 age-, sex-, and education-matched healthy controls (HC) were collected. The QSM was used to quantify the magnetic susceptibility values of the caudate nucleus, putamen, globus pallidus, substantia nigra, red nucleus, and dentate nucleus, and to analyze the differences that existed between the three groups. As well as the correlation between the magnetic susceptibility values and cognitive function was calculated. The magnetic susceptibility values of bilateral globus pallidus, left putamen, and bilateral substantia nigra were significantly higher in AD patients than in HC, and the magnetic susceptibility values of the right globus pallidus were significantly higher in AD patients than in MCI (all p < 0.05). The magnetic susceptibility values of the left dentate nucleus in the AD group were negatively correlated with the writing function of the MMSE subitem (r = -0.42, p = 0.020), and the magnetic susceptibility values of the left caudate nucleus and right dentate nucleus were significantly and negatively correlated with the naming function and language function of the MoCA subitem, respectively (r = -0.43, p = 0.019; r = -0.36, p = 0.048). Magnetic susceptibility values based on QSM correlate with cognitive function are valuable in discriminating AD from MCI and AD from HC.

Deep Brain Stimulation restores information processing in parkinsonian cortical networks.

Parkinson's disease (PD) is a neurodegenerative disorder associated with alterations of neural activity and information processing primarily in the basal ganglia and cerebral cortex. Deep brain stimulation (DBS) of the subthalamic nucleus (STN-DBS) is the most effective therapy when patients experience levodopa-induced motor complications. A growing body of evidence points towards a cortical effect of STN-DBS, restoring key electrophysiological markers, such as excessive beta band oscillations, commonly observed in PD. However, the mechanisms of STN-DBS remain elusive. Here, we aim to better characterize the cortical substrates underlying STN-DBS-induced improvement in motor symptoms. We recorded electroencephalograms (EEG) from PD patients and found that, although apparent EEG features were not different with or without therapy, EEG signals could more accurately predict limb movements under STN-DBS. To understand the origins of this enhanced information transmission under STN-DBS in the human EEG data, we investigated the information capacity and dynamics of a variety of computational models of cortical networks. The extent of improvement in decoding accuracy of complex naturalistic inputs under STN-DBS depended on the synaptic parameters of the network as well as its excitability and synchronization levels. Additionally, decoding accuracy could be optimized by adjusting STN-DBS parameters. Altogether, this work draws a comprehensive link between known alterations in cortical activity and the degradation of information processing capacity, as well as its restoration under DBS. These results also offer new perspectives for optimizing STN-DBS parameters based on clinically accessible measures of cortical information processing capacity.

A Physiological Marker for Deep Brain Ultrasonic Neuromodulation

ObjectivesTranscranial ultrasound neuromodulation (TUSN) is a noninvasive and spatially specific therapy that promises to deliver treatments tailored to the specific needs of individuals. To fulfill this promise, each treatment must be modified to adequately correct for variation across individual skulls and neural anatomy. This study examines the use of ultrasound-induced voltage potentials (measured with electroencephalography [EEG]) to guide TUSN therapies. Materials and MethodsWe measured EEG responses in two awake nonhuman primates during sonication of 12 targets surrounding two deep brain nuclei, the left and right lateral geniculate nucleus. ResultsWe report reliable ultrasound evoked potentials measured with EEG after the deep brain ultrasonic modulation in nonhuman primates. Robust responses are observed after just ten repetitions of the ultrasonic stimuli. Moreover, these potentials are only evoked for specific deep brain targets. Furthermore, a behavioral study in one subject shows a direct correspondence between the target with maximal EEG response and ultrasound-based modulation of visual choice behavior. Thus, this study provides evidence for the feasibility of EEG-based guidance for ultrasound neuromodulation therapies.

CIAO1 loss of function causes a neuromuscular disorder with compromise of nucleocytoplasmic Fe-S enzymes.

Cytoplasmic and nuclear iron-sulfur (Fe-S) enzymes that are essential for genome maintenance and replication depend on the cytoplasmic Fe-S assembly (CIA) machinery for cluster acquisition. The core of the CIA machinery consists of a complex of CIAO1, MMS19 and FAM96B. The physiological consequences of loss of function in the components of the CIA pathway have thus far remained uncharacterized. Our study revealed that patients with biallelic loss of function in CIAO1 developed proximal and axial muscle weakness, fluctuating creatine kinase elevation, and respiratory insufficiency. In addition, they presented with CNS symptoms including learning difficulties and neurobehavioral comorbidities, along with iron deposition in deep brain nuclei, mild normocytic to macrocytic anemia, and gastrointestinal symptoms. Mutational analysis revealed reduced stability of the variants compared with WT CIAO1. Functional assays demonstrated failure of the variants identified in patients to recruit Fe-S recipient proteins, resulting in compromised activities of DNA helicases, polymerases, and repair enzymes that rely on the CIA complex to acquire their Fe-S cofactors. Lentivirus-mediated restoration of CIAO1 expression reversed all patient-derived cellular abnormalities. Our study identifies CIAO1 as a human disease gene and provides insights into the broader implications of the cytosolic Fe-S assembly pathway in human health and disease.

Gadolinium Contrast Agent Deposition in Children.

Over the past few years, a large number of studies have evidenced increased signal intensity in the deep brain nuclei on unenhanced T1-MRI images achieved by the application of gadolinium-based contrast agents (GBCAs). The deposition of gadolinium in the brain, bone, and other tissues following administration of GBCAs has also been confirmed in histological studies in rodents and in necropsy studies in adults and children. Given the distinct physiological characteristics of children, this review focuses on examining the current research on gadolinium deposition in children, particularly studies utilizing novel methods and technologies. Furthermore, the article compares safety research findings of linear GBCAs and macrocyclic GBCAs in children, with the aim of offering clinicians practical guidance based on the most recent research outcomes. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 2.

Head injury: Importance of the deep brain nuclei in force transmission to the brain

Finite element modeling provides a digital representation of the human body. It is currently the most pertinent method to study the mechanisms of head injury, and is becoming a scientific reference in forensic expert reports. Improved biofidelity is a recurrent aim of research studies in biomechanics in order to improve earlier models whose mechanical properties conformed to simplified elastic behavior and mechanic laws. We aimed to study force transmission to the brain following impacts to the head, using a finite element head model with increased biofidelity. To the model developed by the Laboratory of Applied Biomechanics of Marseille, we added new brain structures (thalamus, central gray nuclei and ventricular systems) as well as three tracts involved in the symptoms of head injury: the corpus callosum, uncinate tracts and corticospinal tracts. Three head impact scenarios were simulated: an uppercut with the prior model and an uppercut with the improved model in order to compare the two models, and a lateral impact with an impact velocity of 6.5 m/s in the improved model. In these conditions, in uppercuts the maximum stress values did not exceed the injury risk threshold. On the other hand, the deep gray matter (thalamus and central gray nuclei) was the region at highest risk of injury during lateral impacts. Even if injury to the deep gray matter is not immediately life-threatening, it could explain the chronic disabling symptoms of even low-intensity head injury.

Parameter-based analysis of clinical efficacy of combined bed nucleus of the stria terminalis-nucleus accumbens deep brain stimulation for treatment-resistant depression.

Treatment-resistant depression (TRD) is a severely disabling psychiatric condition that responds poorly to conventional treatments. Deep brain stimulation (DBS) has been proposed for the treatment of patients with TRD in numerous studies. Several deep brain nuclei are considered as potential targets for TRD-DBS, but their clinical efficacy needs further validation. This study carried out dual-target combined stimulation of the bed nucleus of the stria terminalis (BNST) and nucleus accumbens (NAc) to investigate the effectiveness of the treatment for TRD patients. An 8-contact DBS electrode was used in the study with a surgical path that crossed the BNST and NAc targets. Stimulation parameters and the corresponding severity of symptoms evaluated by the 17-item Hamilton Depression Rating Scale (HAMD-17) and other scales were obtained at each follow-up. The accuracy of electrode positions, the effect of combined stimulation, and the corresponding stimulation parameters were evaluated. Sweet spot prediction models were used to assess the effective stimulation sites in the treatment. The study included 23 TRD patients undergoing DBS at a single center from March 2021 to May 2023. At the last follow-up (range 4-24 months), 14 patients had responded to the treatment (HAMD-17 score improved ≥ 50%), 7 of whom had achieved clinical remission (HAMD-17 score ≤ 7). Electrode position analysis suggested that the BNST may be more important for the improvement of depressive symptoms than the NAc. Overlapped volumes of volume of tissue activated (VTA) and BNST were significantly correlated with absolute (ρleft = -0.377, p < 0.001; ρright = -0.251, p < 0.001) and percent (ρleft = -0.249, p < 0.001; ρright = -0.098, p = 0.102) changes in HAMD-17 score. The sweet spot model of HAMD-17 improvement also suggested that the VTA overlap with the dorsal side of BNST was associated with the impact on depressive symptoms (t = -4.10, p < 0.05). Combined BNST-NAc stimulation of TRD can effectively improve depressive symptoms, in which the BNST seems to have a dominant therapeutic effect. The results of this study not only help to optimize the DBS programming parameters, but also offer an opportunity to further understand the differences between the two targets. In the future, larger prospective cohorts are needed to verify the results of combined BNST-NAc DBS.

Imaging Single-Cell Ca2+ Dynamics of Brainstem Neurons and Glia in Freely Behaving Mice.

In vivo brain imaging, using a combination of genetically encoded Ca2+ indicators and gradient refractive index (GRIN) lens, is a transformative technology that has become an increasingly potent research tool over the last decade. It allows direct visualisation of the dynamic cellular activity of deep brain neurons and glia in conscious animals and avoids the effect of anaesthesia on the network. This technique provides a step change in brain imaging where fibre photometry combines the whole ensemble of cellular activity, and multiphoton microscopy is limited to imaging superficial brain structures either under anaesthesia or in head-restrained conditions. We have refined the intravital imaging technique to image deep brain nuclei in the ventral medulla oblongata, one of the most difficult brain structures to image due to the movement of brainstem structures outside the cranial cavity during free behaviour (head and neck movement), whose targeting requires GRIN lens insertion through the cerebellum-a key structure for balance and movement. Our protocol refines the implantation method of GRIN lenses, giving the best possible approach to image deep extracranial brainstem structures in awake rodents with improved cell rejection/acceptance criteria during analysis. We have recently reported this method for imaging the activity of retrotrapezoid nucleus and raphe neurons to outline their chemosensitive characteristics. This revised method paves the way to image challenging brainstem structures to investigate their role in complex behaviours such as breathing, circulation, sleep, digestion, and swallowing, and could be extended to image and study the role of cerebellum in balance, movement, motor learning, and beyond. Key features • We developed a protocol that allows imaging from brainstem neurons and glia in freely behaving rodents. • Our refined method of GRIN lenses implantation and cell sorting approach gives the highest number of cells with the least postoperative complications. • The revised deep brainstem imaging method paves way to understand complex behaviours such as cardiorespiratory regulation, sleep, swallowing, and digestion. • Our protocol can be implemented to image cerebellar structures to understand their role in key functions such as balance, movement, motor learning, and more.

Histogram analysis of diffusion kurtosis imaging of deep brain nuclei in Parkinson's disease with different motor subtypes

To evaluate the diagnostic and differential efficacy of diffusion kurtosis imaging (DKI) histogram analysis for different motor subtypes of Parkinson's disease (PD). Seventy PD patients including 40 with postural instability and gait disorder (PIGD) and 30 with tremor-dominant (TD) and 36 healthy controls (HC) were enrolled prospectively and underwent MRI examinations. The regions of interest (ROI) in the deep brain nuclei were delineated and features were extracted on the map of mean kurtosis (MK), axial kurtosis (Ka), and radial kurtosis (Kr), respectively. The differences in histogram features between PD patients and HC and between patients with PIGD and TD were compared. The areas under the curve (AUCs) were calculated to evaluate the diagnostic efficacy of all histogram features. The correlations between histogram features and clinical indicators were evaluated. Some DKI histogram features were significantly different between PD patients and HC, and also different between patients with PIGD and TD (all p<0.05). MK of the substantia nigra pars reticulate (SNprkurtosis), Ka of the substantia nigra pars compacta (SNpc) 50 percentile (SNpcP50), and Kr of SNpc 90th percentile showed the highest AUC for distinguishing patients with PIGD from HC. MK-SNpc 10th percentile, Ka-SNpc 25th percentile, and Kr of the head of the caudate nucleus (CN) 90th percentile had the highest AUC for distinguishing patients with TD from HC. MK of the putamen 10th percentile combined with Ka of the bilateral red nucleus RNkurtosis yielded the highest diagnostic performance with an AUC of 0.762 for distinguishing patients with PIGD from TD. Certain DKI histogram features were correlated with Hoehn-Yahr (H&Y) stage, Mini Mental State Examination (MMSE) score, tremor score, and PIGD score (all p<0.05). DKI histogram analysis was useful to diagnose and discriminate different motor subtypes of PD. Certain DKI histogram features correlated with clinical indicators.

Multi-channel microelectrode arrays for detection of single-cell level neural information in the hippocampus CA1 under general anesthesia induced by low-dose isoflurane

Timely monitoring of anesthesia status during surgery is important to prevent an overdose of isoflurane anesthesia. Therefore, in-depth studies of the neural mechanisms of anesthetics are warranted. Hippocampal CA1 plays an important role during anesthesia. Currently, a high spatiotemporal resolution microdevice technology for the accurate detection of deep brain nuclei is lacking. In this research, four-shank 32-channel implantable microelectrode arrays (MEAs) were developed for the real-time recording of single-cell level neural information in rat hippocampal CA1. Platinum nanoparticles were modified onto the microelectrodes to substantially enhance the electrical properties of the microelectrode arrays. The modified MEAs exhibited low impedance (11.5 ± 1 kΩ) and small phase delay (-18.5 ± 2.54°), which enabled the MEAs to record single-cell level neural information with a high signal-to-noise ratio. The MEAs were implanted into the CA1 nuclei of the anesthetized rats, and the electrophysiological signals were recorded under different degrees of anesthesia mediated by low-dose concentrations of isoflurane. The recorded signals were analyzed in depth. Isoflurane caused an inhibition of spike firing rate in hippocampal CA1 neurons, while inducing low-frequency oscillations in CA1, thus enhancing the low-frequency power of local field potentials. In this manner, the spike firing rate and the power of local field potentials in CA1 could characterize the degree of isoflurane anesthesia. The present study provides a technical tool to study the neural mechanisms of isoflurane anesthesia and a research method for monitoring the depth of isoflurane anesthesia in clinical practice.

Highly Activated Neuronal Firings Monitored by Implantable Microelectrode Array in the Paraventricular Thalamus of Insomnia Rats

Insomnia is a common sleep disorder around the world, which is harmful to people’s health, daily life, and work. The paraventricular thalamus (PVT) plays an essential role in the sleep–wake transition. However, high temporal-spatial resolution microdevice technology is lacking for accurate detection and regulation of deep brain nuclei. The means for analyzing sleep–wake mechanisms and treating sleep disorders are limited. To detect the relationship between the PVT and insomnia, we designed and fabricated a special microelectrode array (MEA) to record electrophysiological signals of the PVT for insomnia and control rats. Platinum nanoparticles (PtNPs) were modified onto an MEA, which caused the impedance to decrease and improved the signal-to-noise ratio. We established the model of insomnia in rats and analyzed and compared the neural signals in detail before and after insomnia. In insomnia, the spike firing rate was increased from 5.48 ± 0.28 spike/s to 7.39 ± 0.65 spike/s, and the power of local field potential (LFP) decreased in the delta frequency band and increased in the beta frequency band. Furthermore, the synchronicity between PVT neurons declined, and burst-like firing was observed. Our study found neurons of the PVT were more activated in the insomnia state than in the control state. It also provided an effective MEA to detect the deep brain signals at the cellular level, which conformed with macroscopical LFP and insomnia symptoms. These results laid the foundation for studying PVT and the sleep–wake mechanism and were also helpful for treating sleep disorders.

Direct localization and delineation of human pedunculopontine nucleus based on a self-supervised magnetic resonance image super-resolution method.

The pedunculopontine nucleus (PPN) is a small brainstem structure and has attracted attention as a potentially effective deep brain stimulation (DBS) target for the treatment of Parkinson's disease (PD). However, the in vivo location of PPN remains poorly described and barely visible on conventional structural magnetic resonance (MR) images due to a lack of high spatial resolution and tissue contrast. This study aims to delineate the PPN on a high-resolution (HR) atlas and investigate the visibility of the PPN in individual quantitative susceptibility mapping (QSM) images. We combine a recently constructed Montreal Neurological Institute (MNI) space unbiased QSM atlas (MuSus-100), with an implicit representation-based self-supervised image super-resolution (SR) technique to achieve an atlas with improved spatial resolution. Then guided by a myelin staining histology human brain atlas, we localize and delineate PPN on the atlas with improved resolution. Furthermore, we examine the feasibility of directly identifying the approximate PPN location on the 3.0-T individual QSM MR images. The proposed SR network produces atlas images with four times the higher spatial resolution (from 1 to 0.25 mm isotropic) without a training dataset. The SR process also reduces artifacts and keeps superb image contrast for further delineating small deep brain nuclei, such as PPN. Using the myelin staining histological atlas as guidance, we first identify and annotate the location of PPN on the T1-weighted (T1w)-QSM hybrid MR atlas with improved resolution in the MNI space. Then, we relocate and validate that the optimal targeting site for PPN-DBS is at the middle-to-caudal part of PPN on our atlas. Furthermore, we confirm that the PPN region can be identified in a set of individual QSM images of 10 patients with PD and 10 healthy young adults. The contrast ratios of the PPN to its adjacent structure, namely the medial lemniscus, on images of different modalities indicate that QSM substantially improves the visibility of the PPN both in the atlas and individual images. Our findings indicate that the proposed SR network is an efficient tool for small-size brain nucleus identification. HR QSM is promising for improving the visibility of the PPN. The PPN can be directly identified on the individual QSM images acquired at the 3.0-T MR scanners, facilitating a direct targeting of PPN for DBS surgery.

Quantitative Susceptibility Mapping MRI in Deep-Brain Nuclei in First-Episode Psychosis.

Psychosis is related to neurochemical changes in deep-brain nuclei, particularly suggesting dopamine dysfunctions. We used an magnetic resonance imaging-based technique called quantitative susceptibility mapping (QSM) to study these regions in psychosis. QSM quantifies magnetic susceptibility in the brain, which is associated with iron concentrations. Since iron is a cofactor in dopamine pathways and co-localizes with inhibitory neurons, differences in QSM could reflect changes in these processes. We scanned 83 patients with first-episode psychosis and 64 healthy subjects. We reassessed 22 patients and 21 control subjects after 3 months. Mean susceptibility was measured in 6 deep-brain nuclei. Using linear mixed models, we analyzed the effect of case-control differences, region, age, gender, volume, framewise displacement (FD), treatment duration, dose, laterality, session, and psychotic symptoms on QSM. Patients showed a significant susceptibility reduction in the putamen and globus pallidus externa (GPe). Patients also showed a significant R2* reduction in GPe. Age, gender, FD, session, group, and region are significant predictor variables for QSM. Dose, treatment duration, and volume were not predictor variables of QSM. Reduction in QSM and R2* suggests a decreased iron concentration in the GPe of patients. Susceptibility reduction in putamen cannot be associated with iron changes. Since changes observed in putamen and GPe were not associated with symptoms, dose, and treatment duration, we hypothesize that susceptibility may be a trait marker rather than a state marker, but this must be verified with long-term studies.

Dynamic flexibility and controllability of network communities in juvenile myoclonic epilepsy

Juvenile myoclonic epilepsy (JME) is the most common syndrome within the idiopathic generalized epilepsy spectrum, manifested by myoclonic and generalized tonic-clonic seizures and spike-and-wave discharges (SWDs) on electroencephalography (EEG). Currently, the pathophysiological concepts addressing SWD generation in JME are still incomplete. In this work, we characterize the temporal and spatial organization of functional networks and their dynamic properties as derived from high-density EEG (hdEEG) recordings and MRI in 40 JME patients (25.4 ± 7.6 years, 25 females). The adopted approach allows for the construction of a precise dynamic model of ictal transformation in JME at the cortical and deep brain nuclei source levels. We implement Louvain algorithm to attribute brain regions with similar topological properties to modules during separate time windows before and during SWD generation. Afterwards, we quantify how modular assignments evolve and steer through different states towards the ictal state by measuring characteristics of flexibility and controllability. We find antagonistic dynamics of flexibility and controllability within network modules as they evolve towards and undergo ictal transformation. Prior to SWD generation, we observe concomitantly increasing flexibility (F(1,39) = 25.3, corrected p < 0.001) and decreasing controllability (F(1,39) = 55.3, p < 0.001) within the fronto-parietal module in γ-band. On a step further, during interictal SWDs as compared to preceding time windows, we notice decreasing flexibility (F(1,39) = 11.9, p < 0.001) and increasing controllability (F(1,39) = 10.1, p < 0.001) within the fronto-temporal module in γ-band. During ictal SWDs as compared to prior time windows, we demonstrate significantly decreasing flexibility (F(1,14) = 31.6; p < 0.001) and increasing controllability (F(1,14) = 44.7, p < 0.001) within the basal ganglia module. Furthermore, we show that flexibility and controllability within the fronto-temporal module of the interictal SWDs relate to seizure frequency and cognitive performance in JME patients. Our results demonstrate that detection of network modules and quantification of their dynamic properties is relevant to track the generation of SWDs. The observed flexibility and controllability dynamics reflect the reorganization of de−/synchronized connections and the ability of evolving network modules to reach a seizure-free state, respectively. These findings may advance the elaboration of network-based biomarkers and more targeted therapeutic neuromodulatory approaches in JME.

Deep learning-regularized, single-step quantitative susceptibility mapping quantification.

The purpose of the current study was to develop deep learning-regularized, single-step quantitative susceptibility mapping (QSM) quantification, directly generating QSM from the total phase map. A deep learning-regularized, single-step QSM quantification model, named SS-POCSnet, was trained with datasets created using the QSM synthesis approach in QSM reconstruction challenge 2.0. In SS-POCSnet, a data fidelity term based on a single-step model was iteratively applied that combined the spherical mean value kernel and dipole model. Meanwhile, SS-POCSnet regularized susceptibility maps, avoiding underestimating susceptibility values. We evaluated the SS-POCSnet on 10 synthetic datasets, 24 clinical datasets with lesions of cerebral microbleed (CMB) and calcification, and 10 datasets with multiple sclerosis (MS).On synthetic datasets, SS-POCSnet showed the best performance among the methods evaluated, with a normalized root mean squared error of 37.3% ± 4.2%, susceptibility-tuned structured similarity index measure of 0.823 ± 0.02, high-frequency error norm of 37.0 ± 5.7, and peak signal-to-noise ratio of 42.8 ± 1.1. SS-POCSnet also reduced the underestimations of susceptibility values in deep brain nuclei compared with those from the other models evaluated. Furthermore, SS-POCSnet was sensitive to CMB/calcification and MS lesions, demonstrating its clinical applicability. Our method also supported variable imaging parameters, including matrix size and resolution. It was concluded that deep learning-regularized, single-step QSM quantification can mitigate underestimating susceptibility values in deep brain nuclei.

Remus: System for remote deep brain interventions

SummaryTranscranial-focused ultrasound brings personalized medicine to the human brain. Ultrasound can modulate neural activity or release drugs in specific neural circuits but this personalized approach requires a system that delivers ultrasound into specified targets flexibly and on command. We developed a remote ultrasound system (Remus) that programmatically targets deep brain regions with high spatiotemporal precision and in a multi-focal manner. We validated these functions by modulating two deep brain nuclei—the left and right lateral geniculate nucleus—in a task-performing nonhuman primate. This flexible system will enable researchers and clinicians to diagnose and treat specific deep brain circuits in a noninvasive yet targeted manner, thus embodying the promise of personalized treatments of brain disorders.

O029 / #627 DEEP BRAIN STIMULATION FOR PARKINSON: AWAKE VS ASLEEP SURGICAL TECHNIQUE: TRACK 2: DEEP BRAIN STIMULATION FOR MOVEMENT DISORDERS

Electrical stimulation of deep brain nuclei is a well-stablished technique for the treatment of movement disorders, when refractory to medical management. In its early beginnings, functional neurosurgery relied in stereotactic atlases and intraoperative micro-registration in awake patients to achieve correct electrode placement (indirect method). However, the cumulative experience on target description and the evolution of MRI resolution have made it possible to accurately define the target preoperatively (direct method).

Quantitative susceptibility atlas construction in Montreal Neurological Institute space: towards histological-consistent iron-rich deep brain nucleus subregion identification.

Iron-rich deep brain nuclei (DBN) of the human brain are involved in various motoric, emotional and cognitive brain functions. The abnormal iron alterations in the DBN are closely associated with multiple neurological and psychiatric diseases. Quantitative susceptibility mapping (QSM) provides the spatial distribution of the magnetic susceptibility of human brain tissues. Compared to traditional structural imaging, QSM provides superiority for imaging the iron-rich DBN owing to the susceptibility difference existing between brain tissues. In this study, we constructed a Montreal Neurological Institute (MNI) space unbiased QSM human brain atlas via group-wise registration from 100 healthy subjects aged 19-29 years. The atlas construction process was guided by hybrid images that were fused from multi-modal magnetic resonance images (MRI). We named it as Multi-modal-fused magnetic Susceptibility (MuSus-100) atlas. The high-quality susceptibility atlas provides extraordinary image contrast between iron-rich DBN with their surroundings. Parcellation maps of DBN and their subregions that are highly related to neurological and psychiatric pathology were then manually labeled based on the atlas set with the assistance of an image border-enhancement process. Especially, the bilateral thalamus was delineated into 64 detailed subregions referring to the Schaltenbrand-Wahren stereotactic atlas. To our best knowledge, the histological-consistent thalamic nucleus parcellation map is well defined for the first time in the MNI space. Compared with existing atlases that emphasizing DBN parcellation, the newly proposed atlas outperforms on the task of atlas-guided individual brain image DBN segmentation both in accuracy and robustness. Moreover, we applied the proposed DBN parcellation map to conduct detailed identification of the pathology-related iron content alterations in subcortical nuclei for Parkinson's Disease (PD) patients. We envision that the MuSus-100 atlas can play a crucial role in improving the accuracy of DBN segmentation for the research of neurological and psychiatric disease progress and also be helpful for target planning in deep brain stimulation surgery.

Early differentiation of neurodegenerative diseases using the novel QSM technique: what is the biomarker of each disorder?

During neurodegenerative diseases, the brain undergoes morphological and pathological changes; Iron deposits are one of the causes of pathological changes in the brain. The Quantitative susceptibility mapping (QSM) technique, a type of magnetic resonance (MR) image reconstruction, is one of the newest diagnostic methods for iron deposits to detect changes in magnetic susceptibility. Numerous research projects have been conducted in this field. The purpose of writing this review article is to identify the first deep brain nuclei that undergo magnetic susceptibility changes during neurodegenerative diseases such as Alzheimer's or Parkinson's disease. The purpose of this article is to identify the brain nuclei that are prone to iron deposition in any specific disorder. In addition to the mentioned purpose, this paper proposes the optimal scan parameters and appropriate algorithms of each QSM reconstruction step by reviewing the results of different articles. As a result, The QSM technique can identify nuclei exposed to iron deposition in various neurodegenerative diseases. Also, the selection of scan parameters is different based on the sequence and purpose; an example of the parameters is placed in the tables. The BET toolbox in FSL, Laplacian-based phase-unwrapping process, the V_SHARP algorithm, and morphology-enabled dipole inversion (MEDI) method are the most widely used algorithms in various stages of QSM reconstruction.

Abnormalities in deep-brain morphology and orbitofrontal cortical thinning relate to reward processing and body mass in adolescent girls.

Research examining the neural correlates of obesity has recently expanded. However, limited attention has focused on identifying unique brain signatures associated with obesity, particularly in adolescents. The aim of this study was to use surface-based approaches to examine the integrity of brain structures involved in processing the pleasurable effects of food with body mass and food reward sensitivity in adolescent girls. Structural morphology of the nucleus accumbens, amygdala, pallidum, and orbitofrontal cortex was examined in 89 adolescent girls with body mass ranging from normal to obese. High-resolution T1-weighted MPRAGE images were used to characterize deep-brain nuclei with high-dimensional diffeomorphic mapping procedures, while cortical thickness was derived from the FreeSurfer toolkit. Results revealed that zBMI was significantly associated with the shape of the left amygdala (β = -1.1, p < 0.021, 95% CI = -2.02, -0.16), volume of the right and left pallidum (β = 49.66, p < 0.010, 95% CI = 11.74, 87.58; β = 47.87, p < 0.017, 95% CI = 8.48, 87.25), and cortical thickness of the lateral and right medial orbitofrontal cortex (β = -0.06, p < 0.001, 95% CI = -0.09, -0.04; β = -0.05, p = 0.004, 95% CI = -0.08, -0.02). Sensitivity to food reward significantly predicted volume of the right nucleus accumbens (β = 0.66, p = 0.047, 95% CI = 0.01, 1). Contrast mapping for surface shape of the amygdala revealed significant outward deformation of the posterior lateral left amygdala and an inward deformation of the basolateral left amygdala in the group with overweight/obesity. Integrity of the left amygdala and orbitofrontal cortex varies as a function of body mass, with greater localized amygdalar volume loss, pallidum volume, and increased cortical thinning of the orbitofrontal cortex occurring as weight increases. Thus, overweight/obesity may be associated with surface-based abnormalities in brain structures associated with processing of reward value related to food. Overall, findings highlight the importance of understanding changes in reward-related brain regions and how they pertain to variability in body mass in adolescent girls.