Anatomical Brain Imaging Research Articles

Right hemisphere stroke is linked to reduced social connectedness in the UK Biobank cohort

Social connectedness is fundamental to health and life satisfaction. Empathic capacities that support social connections are commonly impaired following damage to the brain’s right hemisphere, but how these acquired socio-emotional deficits correspond to real-world social outcomes remains unclear. Using anatomical brain imaging and behavioral data from a large sample of stroke survivors included in the UK Biobank (n = 209), we link damage to regions of the right hemisphere involved in emotion recognition to lower social relationship satisfaction and higher loneliness. The effect was driven by lesions to the right anterior insula and not explained by stroke extent and motor function; it was further corroborated by an exploratory analysis of social decline in a few participants for whom data were available from before and after a stroke to the right anterior insula (n = 3; comparison n = 13). These correlational findings provide new insight into the role of the right hemisphere in maintaining social connections and bear important implications for treatment and rehabilitation post-stroke.

MRI compared to 123I-MIBG scan for detection of central nervous system relapse in neuroblastoma.

10040 Background: Neuroblastoma (NB) relapsing in the central nervous system (CNS), though uncommon, is historically incurable. However, a multimodality approach has improved long term survival (1). Timely detection of CNS relapse may reduce or prevent morbidity and mortality. In most centers, surveillance for NB includes whole-body MIBG scans but does not require dedicated anatomical brain imaging. At Memorial Sloan Kettering Cancer Center (MSK), head MRI at regular intervals is standard. The objective of this retrospective study was to determine the optimal imaging modality for detecting CNS relapse in NB. Methods: After MSK IRB approval, records of patients with CNS NB seen at MSK from 2004-2023 were evaluated. In most cases, relapse was diagnosed at other institutions before referral to MSK. Analyzed data included symptoms and findings on brain CT/MRI and MIBG scans. Results: Of 206 patients with MIBG-avid CNS NB, 7 were excluded because they had CNS disease at diagnosis. For the remaining 199 patients, median time to CNS relapse from diagnosis was 18 months. 132 (66%) patients had CNS relapse at a median of 9.8 months after achieving complete remission. In 67 patients with prior systemic progression, median time to CNS relapse was 10.9 months from the last relapse. Relapse was isolated to CNS in 130/199 (65%) patients. 118 (59%) patients had neurological symptoms at time of CNS disease; 81(41%) were asymptomatic, relapse being detected on surveillance scans. Multiple (>1) parenchymal lesions were noted in 74 (37%), diffuse leptomeningeal disease without parenchymal involvement in 15 (7%) and solitary lesions in 110 (55%) patients. Median diameter of the largest lesion was 2.7 (range <0.5-6.8) cm. Anatomical imaging was performed with MRI (65%), CT (14%) or both (34%). Of those undergoing both scans, CNS relapse was missed on CT in 4/67 (6%) patients. 137 patients had MIBG scans before resection of CNS relapse. All sites of CNS disease noted on MRI/CT were positive by MIBG in 46 (33%) patients. However, MIBG scan was either totally or partly negative in 69 (50%) and 22 (16%) patients, respectively. Even for lesions ≥2cm in diameter, MIBG was completely negative in 27/57 (47%). MIBG positivity did not correlate with age, size >2cm, MYCN amplification or ALK mutation status (p>0.05 for each). Lesions <1cm and infratentorially located were more likely to be negative on MIBG scan (p<0.05). Lesions in symptomatic patients, dural lesions and hemorrhagic lesions were more likely to be positive on MIBG scan (p< 0.05). Conclusions: CNS relapse is isolated to the brain in most patients. MIBG scan has poor sensitivity for the detection of CNS NB, regardless of size or location. Although CT or MRI are both effective in detecting CNS relapse, the former can miss some lesions. We recommend brain MRI for surveillance of high-risk NB for ≥2 years after initial diagnosis or last systemic relapse. 1. J. Neurooncology 97:409, 2010.

Friends with benefits: Sharing large‐scale transcontinental brain MRI databases in LatAM‐FINGERS and US POINTER

AbstractBackgroundMulticentric initiatives to study brain cognition in the elderly offers us a unique collection of brain imaging data accompanied by detailed neuroclinical and neuropsychological evaluations. U.S. POINTER and LatAm‐FINGERS, part of the World Wide FINGERS, are both large‐scale investigations of lifestyle interventions and its impact on cognitive function. These large‐scale detailed data may offer an unprecedented opportunity to compare diverse populations.MethodBaseline MRI of subjects from multiple US centers (POINTER‐US), distributed in 5 geographical regions, and from 9 latin‐american countries (LatAm‐FINGERS). The protocols vary from basic (3D T1, 3D FLAIR,T2* GRE, Cor T2 hippocampus, DWI) to advanced which also included ASL, rs‐FMRI and DTI. Demographic information and clinical, cognitive and neuropsychological assessment were also included.ResultMRI data was collected from 662 participants in the United States (about 65% of the total anticipated U.S. POINTER neuroimaging sample) and from 542 subjects from 9 countries in latin‐america (about 80% of the total anticipated LatAm‐FINGERS neuroimaging sample), with around 1200 participants scanned (table1).All participants have 3D T1, 3D FLAIR, T2* GRE images and either DWI or DTI images.Comparative demographics from the 2 datasets shows similar mean age, a predominance of females, and slight differences in education (table 2). This will allow us to compare multiethnic and multicultural volumetric and functional brain MRI information, as well as disease markers, associated with thorough neurological and clinical assessment. Reasons for not acquiring MRI were mainly due to claustrophobia or scanner unavailability.ConclusionThis is an exceptional opportunity to have comparative large‐scale databases, with anatomical and functional brain imaging from different populations, allowing us to study real world diverse brain data and better understand its relationships with demographics, health and risk characteristics, and cognition.

Sex differences in the neural underpinnings of unimanual and bimanual control in adults.

While many of the movements we make throughout our day involve just one upper limb, most daily movements require a certain degree of coordination between both upper limbs. Historically, sex differences in eye-hand coordination have been observed. As well, there are demonstrated sex-specific differences in hemisphere symmetry, interhemispheric connectivity, and motor cortex organization. While it has been suggested that these anatomical differences may underlie sex-related differences in performance, sex differences in the functional neural correlate underlying bimanual performance have not been explicitly investigated. In the current study we tested the hypothesis that the functional connectivity underlying bimanual movement control differed depending on the sex of an individual. Participants underwent MRI scanning to acquire anatomical and functional brain images. During the functional runs, participants performed unimanual and bimanual coordination tasks using two button boxes. The tasks included pressing the buttons in time to an auditory cue with either their left or their right hand individually (unimanual), or with both hands simultaneously (bimanual). The bimanual task was further divided into either an in-phase (mirror/symmetrical) or anti-phase (parallel/asymmetrical) condition. Participants were provided with extensive training to ensure task comprehension, and performance error rates were found to be equivalent between men and women. A generalized psychophysiological interaction (gPPI) analysis was implemented to examine how functional connectivity in each condition was modulated by sex. In support of our hypothesis, women and men demonstrated differences in the neural correlates underlying unimanual and bimanual movements. In line with previous literature, functional connectivity patterns showed sex-related differences for right- vs left-hand movements. Sex-specific functional connectivity during bimanual movements was not a sum of the functional connectivity underlying right- and left-hand unimanual movements. Further, women generally showed greater interhemispheric functional connectivity across all conditions compared to men and had greater connectivity between task-related cortical areas, while men had greater connectivity involving the cerebellum. Sex differences in brain connectivity were associated with both unimanual and bimanual movement control. Not only do these findings provide novel insight into the fundamentals of how the brain controls bimanual movements in both women and men, they also present potential clinical implications on how bimanual movement training used in rehabilitation can best be tailored to the needs of individuals.

Accuracy and precision of navigated transcranial magnetic stimulation

Objective. Transcranial magnetic stimulation (TMS) induces an electric field (E-field) in the cortex. To facilitate stimulation targeting, image-guided neuronavigation systems have been introduced. Such systems track the placement of the coil with respect to the head and visualize the estimated cortical stimulation location on an anatomical brain image in real time. The accuracy and precision of the neuronavigation is affected by multiple factors. Our aim was to analyze how different factors in TMS neuronavigation affect the accuracy and precision of the coil–head coregistration and the estimated E-field. Approach. By performing simulations, we estimated navigation errors due to distortions in magnetic resonance images (MRIs), head-to-MRI registration (landmark- and surface-based registrations), localization and movement of the head tracker, and localization of the coil tracker. We analyzed the effect of these errors on coil and head coregistration and on the induced E-field as determined with simplistic and realistic head models. Main results. Average total coregistration accuracies were in the range of 2.2–3.6 mm and 1°; precision values were about half of the accuracy values. The coregistration errors were mainly due to head-to-MRI registration with average accuracies 1.5–1.9 mm/0.2–0.4° and precisions 0.5–0.8 mm/0.1–0.2° better with surface-based registration. The other major source of error was the movement of the head tracker with average accuracy of 1.5 mm and precision of 1.1 mm. When assessed within an E-field method, the average accuracies of the peak E-field location, orientation, and magnitude ranged between 1.5 and 5.0 mm, 0.9 and 4.8°, and 4.4 and 8.5% across the E-field models studied. The largest errors were obtained with the landmark-based registration. When computing another accuracy measure with the most realistic E-field model as a reference, the accuracies tended to improve from about 10 mm/15°/25% to about 2 mm/2°/5% when increasing realism of the E-field model. Significance. The results of this comprehensive analysis help TMS operators to recognize the main sources of error in TMS navigation and that the coregistration errors and their effect in the E-field estimation depend on the methods applied. To ensure reliable TMS navigation, we recommend surface-based head-to-MRI registration and realistic models for E-field computations.

Hybrid magnetic resonance and optoacoustic tomography (MROT) for preclinical neuroimaging

Multi-modal imaging is essential for advancing our understanding of brain function and unraveling pathophysiological processes underlying neurological and psychiatric disorders. Magnetic resonance (MR) and optoacoustic (OA) imaging have been shown to provide highly complementary contrasts and capabilities for preclinical neuroimaging. True integration between these modalities can thus offer unprecedented capabilities for studying the rodent brain in action. We report on a hybrid magnetic resonance and optoacoustic tomography (MROT) system for concurrent noninvasive structural and functional imaging of the mouse brain. Volumetric OA tomography was designed as an insert into a high-field MR scanner by integrating a customized MR-compatible spherical transducer array, an illumination module, and a dedicated radiofrequency coil. A tailored data processing pipeline has been developed to mitigate signal crosstalk and accurately register image volumes acquired with T1-weighted, angiography, and blood oxygenation level-dependent (BOLD) sequences onto the corresponding vascular and oxygenation data recorded with the OA modality. We demonstrate the concurrent acquisition of dual-mode anatomical and angiographic brain images with the scanner, as well as real-time functional readings of multiple hemodynamic parameters from animals subjected to oxygenation stress. Our approach combines the functional and molecular imaging advantages of OA with the superb soft-tissue contrast of MR, further providing an excellent platform for cross-validation of functional readings by the two modalities.

Classification of EEG signals from young adults with dyslexia combining a Brain Computer Interface device and an Interactive Linguistic Software Tool

The magnocellular pathway deficit theory has long been considered to be a possible cause for dyslexia, providing an alternative method to explain auditory and visual processing deficits. Several studies have attempted to classify these deficits with the application of machine learning in anatomical brain imaging, rendering the classification techniques using EEG graph measures both robust and reliable. In this paper, a classification of university students with and without dyslexia is attempted with the use of a Brain Computer Interface (BCI) Device and an Interactive Linguistic Software Tool in order to validate the application of such a device in classifying dyslexia in a higher education population. EEG signals acquired from a wearable, sensory EEG recording device from 12 university students with dyslexia along with 14 typically developed, age matched individuals are recorded, while participants were examined in three different experimental conditions: a) auditory discrimination, b) visual recognition c) visual recognition with background music. Spectral features extracted from each EEG rhythm (δ, θ, α, β, γ) are used to train a Random Forests classifier, aiming to identify quantitative EEG features that characterize dyslexia in different brain regions. Results show high levels of accuracy, sensitivity and specificity (above 95%) in the entire brain, followed by the left and right hemisphere, with the highest discrimination performance reported during the third experimental condition with the presence of background music. Different experimental conditions provide high classification accuracy that results in correct discrimination between higher education students with and without dyslexia.

The Diagnostic Value of a Short Memory Test: The TNI-93.

The TNI-93 is a quick memory test designed for all patients regardless of their education level. A significant proportion of patients with Alzheimer's disease (AD) are illiterate or poorly educated, and only a few memory tests are adapted for these patients. In this study we aimed at assessing the diagnostic value of the TNI-93 for diagnosis of patients with biologically confirmed amyloid status. We included all patients who had an analysis of AD cerebrospinal fluid biomarkers, a neuropsychological assessment including a TNI-93 and an anatomical brain imaging at Avicenne Hospital between January 2009 and November 2019. We compared the TNI-93 scores in patients with amyloid abnormalities (A+) and patients without amyloid abnormalities (A-) according to the AT(N) diagnostic criteria. 108 patients were included (mean age: 66.9±8.5 years old, mean education level: 8.9±5.2 years). Patients from the A + group (N= 80) were significantly more impaired than patients from the A- group (N= 28) on immediate recall (A+: 5.9±2.8; A-: 7.4±2.6; p = 0.001), free recall (A+: 3.5±2.7; A-: 5.9±2.8; p ≤ 0.001), total recall (A+: 5.7±3.5; A-:7.8±2.8; p ≤ 0.001), and on number of intrusions during the recall phase (A+: 1±1.8; A-: 0.1±0.3; p = 0.002). ROC curves revealed that the best scores to discriminate A + from A- patients were immediate recall (Area under curve (AUC): 0.70), number of encoding trials (AUC: 0.73), free recall (AUC: 0.74), and total recall (AUC: 0.74). The TNI-93's immediate, free, and total recalls are valuable tools for the 39 diagnosis of AD.

Multimodal Brain Age Prediction with Feature Selection and Comparison.

Brain age, an estimated biological age from anatomical and/or functional brain imaging data, and its deviation from the chronological age (brain age gap) have shown the potential to serve as biomarkers for characterizing typical brain development, the abnormal aging process, and early indicators of clinical neuropsychiatric problems. In this study, we leverage multimodal brain imaging data for brain age prediction. We studied and compared the performance of individual data modalities (gray matter density in components and regions of interest, cortical and subcortical anatomical features, resting-state functional connectivity) and different combinations of multiple data modalities using data collected from 1417 participants with age between 8 and 22 years. The result indicates that feature selection and multimodal imaging data can improve brain age prediction with linear support vector and partial least squares regression models. We have achieved a mean absolute error of 1.22 years on the test data with 188 features selected equally from all data sources, better than any individual source. After bias correction, the brain age gap was significantly associated with attention accuracy/speed and motor speed in addition to age. Our results conclude that traditional machine learning with proper feature selection can achieve similar if not better performance compared to complex deep learning neural network methods for the used sample size.

Localizing Epileptogenic Zone from High Density EEG Data Using Machine Learning

<span>Drug-resistant focal epilepsy is the failure of antiepileptic drugs scheduled to obtain epileptic free brain activities. In human brain, cerebral hemispheres are the most commonly involved brain regions in epilepsy. In case of antiepileptic drugs failure, surgical treatment is the best cure possible. However, correct localization of epileptogenic region is a challenging task for neurologists, while for computer scientists, automatic localization is. This research work’s aim is to explore the functional activities of all brain regions in drug-resistant focal epileptic patients and achieve high accuracy for the classification of epileptogenic region (ER) with the high-density electroencephalographic (hdEEG) data. The proposed system includes frequency analysis for feature extractions followed by individual subject’s registration of hdEEG signals with anatomical brain images for most precise localization of ER possible. The datasets attained from feature extraction process are then preprocessed for class imbalanced and then evaluated using different machine learning algorithms including the techniques under Bayesian networks, Lazy networks, Meta techniques, Rule based systems and Tree structured algorithms. Considering human brain as stationary object as well as dynamic object, frequency-based and time-frequency based features were considered in 12 subjects respectively. Through this novel approach, 99.70% accuracy is achieved to classify ER from healthy regions using KSTAR and using IBK algorithm, 91.60% accuracy has been achieved to classify generator from propagator.</span>

Open birdcage coil for head imaging at 7T.

To theoretically describe, design, and test the new geometry of the birdcage coil for 7 Tesla anatomical brain imaging, which includes a large window on top, without deliberately jeopardizing its homogeneity and efficiency. This opencage will not only improve patient comfort but also enable the volunteer to follow functional MRI stimuli. This design could also facilitate the tracking of patient compliance and enable better correction of the movement. Via the transfer matrix approach, a birdcage-like coil with a nonperiodic distribution of rungs is constructed with optimized currents in the coil rungs. Subsequently, the coil is adjusted in full-wave simulations. Then, the coil is assembled, fine-tuned, and matched on the bench. Finally, these results are confirmed experimentally on a phantom and in vivo. Indeed, the computed isolation of -14.9 dB between the feeding ports of the coil and the symmetry of the circular polarized mode pattern transmit RF magnetic field ( ) showed that the coil was properly optimized. An experimental assessment of the developed coil showed competitive transmit efficiency and coverage compared with the conventional birdcage coil of similar size. The proposed opencage coil can be designed and work without a dramatic drop of performance in terms of the field homogeneity, transmit efficiency ( / ), peak local specific absorption rate ( ) and SAR efficiency ( / ).

COVID-19-Associated Neurological Manifestations: An Emerging Electroencephalographic Literature.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread worldwide since the end of year 2019 and is currently responsive for coronavirus infectious disease 2019 (COVID-19). The first reports considered COVID-19 as a respiratory tract disease responsible for pneumonia, but numerous studies rapidly emerged to warn the medical community of COVID-19-associated neurological manifestations, including encephalopathy at the acute phase and other postinfectious manifestations. Using standard visual analysis or spectral analysis, recent studies reported electroencephalographic (EEG) findings of COVID-19 patients with various neurological symptoms. Most EEG recordings were normal or revealed non-specific abnormalities, such as focal or generalized slowing, interictal epileptic figures, seizures, or status epilepticus. Interestingly, novel EEG abnormalities over frontal areas were also described at the acute phase. Underlying mechanisms leading to brain injury in COVID-19 are still unknown and matters of debate. These frontal EEG abnormalities could emphasize the hypothesis whereby SARS-CoV-2 enters the central nervous system (CNS) through olfactory structures and then spreads in CNS via frontal lobes. This hypothesis is reinforced by the presence of anosmia in a significant proportion of COVID-19 patients and by neuroimaging studies confirming orbitofrontal abnormalities. COVID-19 represents a new viral disease characterized by not only respiratory symptoms but also a systemic invasion associated with extra-respiratory signs. Neurological symptoms must be the focus of our attention, and functional brain evaluation with EEG is crucial, in combination with anatomical and functional brain imaging, to better understand its pathophysiology. Evolution of symptoms together with EEG patterns at the distance of the acute episode should also be scrutinized.

Δυσλεξία και εγκεφαλική ασυμμετρία: ανασκόπηση μελετών ανατομικής και λειτουργικής απεικόνισης

Developmental dyslexia is a learning disorder that is marked by reading achievement that falls substantially below that expected given the individual's chronological age, measured intelligence, and age-appropriate education (ICD-10, WHO, 1993). It is estimated to affect 5-17% of the student population. It is a disorder that is neurological in nature (Habib, 2000. Σίμος, Μουζάκη, & Παπανικολάου, 2004), but which requires educational intervention. Recently, there has been considerable progress in the investigation of the neurobiological underpinnings of dyslexia. Yet, even today Orton’s 1925 hypothesis, postulating that individuals with dyslexia have not adequately developedthe typical left cerebral lateralization for language and are symmetrical or right-hemispheric dominant for language, remains timely and is under investigation. The present narrative review presents research studies that have investigated the inadequate lateralization hypothesis using anatomical and functional brain imaging. Findings show, for the largest part, that individuals with dyslexia do indeed show anatomical and functional differences in the language networks of the left hemisphere, compared to typical readers. In conclusion, inadequate lateralization is an important neurobiological factor for the development of dyslexia, albeit it is not the only one.

Age of Speech Onset in Autism Relates to Structural Connectivity in the Language Network.

Speech onset delays (SOD) and language atypicalities are central aspects of the autism spectrum (AS), despite not being included in the categorical diagnosis of AS. Previous studies separating participants according to speech onset history have shown distinct patterns of brain organization and activation in perceptual tasks. One major white matter tract, the arcuate fasciculus (AF), connects the posterior temporal and left frontal language regions. Here, we used anatomical brain imaging to investigate the properties of the AF in adolescent and adult autistic individuals with typical levels of intelligence who differed by age of speech onset. The left AF of the AS group showed a significantly smaller volume than that of the nonautistic group. Such a reduction in volume was only present in the younger group. This result was driven by the autistic group without SOD (SOD−), despite their typical age of speech onset. The autistic group with SOD (SOD+) showed a more typical AF as adults relative to matched controls. This suggests that, along with multiple studies in AS-SOD+ individuals, atypical brain reorganization is observable in the 2 major AS subgroups and that such reorganization applies mostly to the language regions in SOD− and perceptual regions in SOD+ individuals.

Technical Assessment of Ultrasonic Cerebral Tomosphygmography and New Scientific Evaluation of Its Clinical Interest for the Diagnosis of Electrohypersensitivity and Multiple Chemical Sensitivity.

Ultrasonic cerebral tomosphygmography (UCTS), also known as “encephaloscan”, is an ultrasound-based pulsatile echoencephalography for both functional and anatomical brain imaging investigations. Compared to classical imaging, UCTS makes it possible to locate precisely the spontaneous brain tissue pulsations that occur naturally in temporal lobes. Scientific publications have recently validated the scientific interest of UCTS technique but clinical use and industrial development of this ancient brain imaging technique has been stopped notably in France, not for scientific or technical reasons but due to a lack of financing support. UCTS should be fundamentally distinguished from transcranial Doppler ultrasonography (TDU), which, although it also uses pulsed ultrasounds, aims at studying the velocity of blood flow (hemodynamics) in the cerebral arteries by using Doppler effect, especially in the middle cerebral artery of both hemispheres. Instead, UCTS has the technical advantage of measuring and locating spontaneous brain tissue pulsations in temporal lobes. Recent scientific work has shown the possibility to make an objective diagnosis of electrohypersensitivity (EHS) and multiple chemical sensitivity (MCS) by using UCTS, in conjunction with TDU investigation and the detection of several biomarkers in the peripheral blood and urine of the patients. In this paper, we independently confirm the clinical interest of using UCTS for the diagnosis of EHS and MCS. Moreover, it has been shown that repetitive use of UCTS in EHS and/or MCS patients can contribute to the objective assessment of their therapeutic follow-up. Since classical CT scan and MRI are usually not contributive for the diagnosis and are poorly tolerated by these patients, UCTS should therefore be considered as one of the best imaging technique to be used for the diagnosis of these new disorders and the follow-up of patients.

Reduced gray matter volume and cortical thickness associated with traffic-related air pollution in a longitudinally studied pediatric cohort.

Early life exposure to air pollution poses a significant risk to brain development from direct exposure to toxicants or via indirect mechanisms involving the circulatory, pulmonary or gastrointestinal systems. In children, exposure to traffic related air pollution has been associated with adverse effects on cognitive, behavioral and psychomotor development. We aimed to determine whether childhood exposure to traffic related air pollution is associated with regional differences in brain volume and cortical thickness among children enrolled in a longitudinal cohort study of traffic related air pollution and child health. We used magnetic resonance imaging to obtain anatomical brain images from a nested subset of 12 year old participants characterized with either high or low levels of traffic related air pollution exposure during their first year of life. We employed voxel-based morphometry to examine group differences in regional brain volume, and with separate analyses, changes in cortical thickness. Smaller regional gray matter volumes were determined in the left pre- and post-central gyri, the cerebellum, and inferior parietal lobe of participants in the high traffic related air pollution exposure group relative to participants with low exposure. Reduced cortical thickness was observed in participants with high exposure relative to those with low exposure, primarily in sensorimotor regions of the brain including the pre- and post-central gyri and the paracentral lobule, but also within the frontal and limbic regions. These results suggest that significant childhood exposure to traffic related air pollution is associated with structural alterations in brain.

젊은 성인의 인지양식에 따른 국소 회빅질 부피의 개인차

Extant research has proposed that the Object-Spatial-Verbal cognitive style can elucidate individual differences in the preference for modality-specific information. However, no studies have yet ascertained whether this type of information processing evinces structural correlations in the brain. Therefore, the current study used voxel-based morphometry (VBM) analyses to investigate individual differences in gray matter volumes based on the Object-Spatial-Verbal cognitive style. For this purpose, ninety healthy young adults were recruited to participate in the study. They were administered the Korean version of the Object-Spatial-Verbal cognitive style questionnaire, and their anatomical brain images were scanned. The VBM results demonstrated that the participants’ verbal scores were positively correlated with regional gray matter volumes (rGMVs) in the right superior temporal sulcus/superior temporal gyrus, the bilateral parahippocampal gyrus/fusiform gyrus, and the left inferior temporal gyrus. In addition, the rGMVs in these regions were negatively correlated with the relative spatial preference scores obtained by individual participants. The findings of the investigation provide anatomical evidence that the verbal cognitive style could be decidedly relevant to higher-level language processing, but not to basic language processing.

Clinical and neural responses to cognitive behavioral therapy for functional tremor.

To evaluate changes in tremor severity and motor/emotion-processing circuits in response to cognitive behavioral therapy (CBT) delivered as treatment for functional tremor (FT), the most common functional movement disorder in adults. Fifteen patients with FT underwent fMRI with motor, basic-emotion, and intense-emotion tasks before and after 12 weeks of CBT. Baseline fMRI was compared to those of 25 healthy controls (HCs). The main clinical endpoint was the tremor score (sum of severity, duration, and incapacitation subscores) adapted from the Rating Scale for Psychogenic Movement Disorders (PMDRS) assessed by a blinded clinician. CBT responders were defined as those with PMDRS score reduction >75%. Anatomic and functional brain images were obtained with a 4T MRI system. Generalized linear model and region-of-interest analyses were used to evaluate before-versus-after treatment-related changes in brain activation. CBT markedly reduced tremor severity (p < 0.01) with remission/near remission achieved in 73.3% of the cohort. Compared to HCs, in those with FT, a functionally defined fMRI region of interest in the anterior cingulate/paracingulate cortex showed increased activation at baseline and decreased activation after CBT during basic-emotion processing (p = 0.012 for CBT responders). Among CBT responders, the change in anterior cingulate/paracingulate was more significant in those with more severe baseline depression (r = 0.75, p < 0.01). Tremor severity improved significantly after CBT. The improvement was associated with changes in the anterior cingulate/paracingulate activity, which may represent a marker of emotional dysregulation in FT and a predictor of treatment response. This study provides Class III evidence that CBT significantly improves tremor severity in patients with functional tremor.

Repetitive transcranial magnetic stimulation treatment for auditory hallucinations: Personalized or standardized targets?

Introduction Most repetitive transcranial magnetic stimulation (rTMS) studies aiming to reduce auditory verbal hallucinations (AVH) in schizophrenia target the left temporo-parietal junction (TPJ), but the efficacy of this approach remains controversial. The observed differences in efficacy could be attributed to inaccurate target localization. The two possible approaches for rTMS target localization are the Standardized Target (ST) T3P3 method and the Personalized Target (PT) method including functional or anatomical brain imaging. Recent large, parallel, double-blinded and sham-controlled studies delivering rTMS with individualized neuronavigation over Wernicke's region showed consistent improvements in AVH. Methods The purpose of this study is to compare ST and PT locations within the left TPJ. An open-source tool (GeodesicSlicer) was developed to compare the geodesic distances between stimulation site determination methods. Results This study reports a differential of approximately 3 cm between personalized and standardized methods, with the potential to explain the dissonant results found in previous rTMS studies.

An unbiased data-driven age-related structural brain parcellation for the identification of intrinsic brain volume changes over the adult lifespan

This study aims to elucidate age-related intrinsic brain volume changes over the adult lifespan using an unbiased data-driven structural brain parcellation. Anatomical brain images from a cohort of 293 healthy volunteers ranging in age from 21 to 86 years were analyzed using independent component analysis (ICA). ICA-based parcellation identified 192 component images, of which 174 (90.6%) showed a significant negative correlation with age and with some components being more vulnerable to aging effects than others. Seven components demonstrated a convex slope with aging; 3 components had an inverted U-shaped trajectory, and 4 had a U-shaped trajectory. Linear combination of 86 components provided reliable prediction of chronological age with a mean absolute prediction error of approximately 7.2 years. Structural co-variation analysis showed strong interhemispheric, short-distance positive correlations and long-distance, inter-lobar negative correlations. Estimated network measures either exhibited a U- or an inverted U-shaped relationship with age, with the vertex occurring at approximately 45–50 years. Overall, these findings could contribute to our knowledge about healthy brain aging and could help provide a framework to distinguish the normal aging processes from that associated with age-related neurodegenerative diseases.