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Relations between Poles and Jews deteriorated significantly in the three decades leading up to World War I. Many reasons for this phenomenon can be given, for example: economic competition, a general atmosphere of acute nationalism, increased migration, perceived threats to traditional forms of life and religion. Exacerbating all of these factors, however, was the fact of Polish statelessness and the extreme sensitivity of Poles to perceived threats to their culture and nation. In particular within the Russian Empire, Poles perceived the very future of their nation at risk. In such circumstances the continued existence of Jewish cultural difference combined with the development of specifically Jewish forms of national awakening (e.g., the Bund and Zionism) were understood by many in Polish society as ingratitude and collaboration with the Russian occupier

Abstract Objective The piriform cortex is considered to be highly epileptogenic. Its resection during epilepsy surgery is a predictor for postoperative seizure freedom in temporal lobe epilepsy. Epilepsy is associated with a dysfunction of the blood–brain barrier. We investigated blood–brain barrier dysfunction in the piriform cortex of people with temporal lobe epilepsy using quantitative T1‐relaxometry. Methods Gadolinium‐based contrast agent was administered ictally and interictally in 37 individuals before undergoing quantitative T1‐relaxometry. Postictal and interictal images were co‐registered, and subtraction maps were created as biomarkers for peri‐ictal (∆qT1interictal‐postictal) and interictal (∆qT1noncontrast‐interictal) blood–brain barrier dysfunction. Values were extracted for the piriform cortex, hippocampus, amygdala, and the whole cortex. Results In temporal lobe epilepsy (n = 14), ∆qT1noncontrast‐interictal was significantly higher in the piriform cortex than in the whole cortex (p = 0.02). In extratemporal lobe epilepsy (n = 23), ∆qT1noncontrast‐interictal was higher in the hippocampus than in the whole cortex (p = 0.05). Across all individuals (n = 37), duration of epilepsy was correlated with ∆qT1noncontrast‐interictal (ß = 0.001, p

The building sector worldwide is responsible for massive CO2 emissions. These emissions stem from both existing and newly constructed buildings, particularly from the extraction and production of materials. Solutions include promoting circular construction, smart investments, and political measures. However, information on materials, quantities, and routes is often incomplete or inaccessible. The “Colouring Dresden” project aims to gather, explore, and communicate knowledge about buildings via the open platform “Colouring Dresden”, part of the international Colouring Cities Research Programme (CCRP). It is Germany’s first citizen science project focused on data collection and disclosure about the built environment, especially buildings. In collaboration with stakeholders, the project developed research questions, adapted the platform, prioritized data collection features, and established citizen science actions and communication channels for knowledge transfer. These actions and knowledge transfer were crucial to the project’s success. Various evaluation methods assessed their suitability in citizen science, providing insights into participant motivation, interests, and benefits for science, society, and individuals. The evaluation revealed significant differences in response quantity and data quality during data collection. The results demonstrate that citizen science projects can be effective in the built environment context, offering insights into appropriate action formats and evaluation methods. This contributes to the advancement of citizen science in Germany, enabling targeted planning of future urban citizen science projects to enhance participant motivation and collect information to reduce CO2 emissions in the building sector.

Abstract Podocyte detachment due to mechanical stress is a common issue in hypertension-induced kidney disease. This study highlights the role of zyxin for podocyte stability and function. We have found that zyxin is significantly up-regulated in podocytes after mechanical stretch and relocalizes from focal adhesions to actin filaments. In zyxin knockout podocytes, we found that the loss of zyxin reduced the expression of vinculin and VASP as well as the expression of matrix proteins, such as fibronectin. This suggests that zyxin is a central player in the translation of mechanical forces in podocytes. In vivo, zyxin is highly up-regulated in patients suffering from diabetic nephropathy and in hypertensive DOCA-salt treated mice. Furthermore, zyxin loss in mice resulted in proteinuria and effacement of podocyte foot processes that was measured by super resolution microscopy. This highlights the essential role of zyxin for podocyte maintenance in vitro and in vivo, especially under mechanical stretch.

Abstract A crucial step in the clinical adaptation of an AI-based tool is an external, independent validation. The aim of this study was to investigate brain atrophy in patients with confirmed, progressed Huntington's disease using a certified software for automated volumetry and to compare the results with the manual measurement methods used in clinical practice as well as volume calculations of the caudate nuclei based on manual segmentations. Twenty-two patients were included retrospectively, consisting of eleven patients with Huntington's disease and caudate nucleus atrophy and an age- and sex-matched control group. To quantify caudate head atrophy, the frontal horn width to intercaudate distance ratio and the intercaudate distance to inner table width ratio were obtained. The software mdbrain was used for automated volumetry. Manually measured ratios and automatically measured volumes of the groups were compared using two-sample t-tests. Pearson correlation analyses were performed. The relative difference between automatically and manually determined volumes of the caudate nuclei was calculated. Both ratios were significantly different between the groups. The automatically and manually determined volumes of the caudate nuclei showed a high level of agreement with a mean relative discrepancy of − 2.3 ± 5.5%. The Huntington's disease group showed significantly lower volumes in a variety of supratentorial brain structures. The highest degree of atrophy was shown for the caudate nucleus, putamen, and pallidum (all p

Abstract Coming from a disadvantaged background can have negative impact on an individual’s educational trajectory. Some people however seem unaffected and cope well with the demands and challenges posed by school education, despite growing up in adverse conditions, a phenomenon termed academic resilience. While it is uncertain which underlying factors make some people more likely to circumvent unfavorable odds than others, both socioeconomic status (SES) and cognitive ability have robustly been linked to school performance. The objective of the present work is to investigate if individual cognitive abilities and SES interact in their effect on grades. For this purpose, we analyzed SES, cognitive, and school performance data from 5001 participants from the Adolescent Brain Cognitive Development (ABCD) Study. Ordinal logistic regression models suggest similar patterns of associations between three SES measures (parental education, income-to-needs ratio, and neighborhood deprivation) and grades at two timepoints, with no evidence for interaction effects between SES and time. Parental education and income-to-needs ratio were associated with grades at both timepoints, irrespective of whether cognitive abilities were modeled or not. Neighborhood deprivation, in contrast, was only a statistically significant predictor of reported grades when cognitive abilities were not factored in. Cognitive abilities interacted with parental education level, meaning that they could be a safeguard against effects of SES on school performance.

Abstract Background Dental caries diagnosis requires the manual inspection of diagnostic bitewing images of the patient, followed by a visual inspection and probing of the identified dental pieces with potential lesions. Yet the use of artificial intelligence, and in particular deep-learning, has the potential to aid in the diagnosis by providing a quick and informative analysis of the bitewing images. Methods A dataset of 13,887 bitewings from the HUNT4 Oral Health Study were annotated individually by six different experts, and used to train three different object detection deep-learning architectures: RetinaNet (ResNet50), YOLOv5 (M size), and EfficientDet (D0 and D1 sizes). A consensus dataset of 197 images, annotated jointly by the same six dental clinicians, was used for evaluation. A five-fold cross validation scheme was used to evaluate the performance of the AI models. Results The trained models show an increase in average precision and F1-score, and decrease of false negative rate, with respect to the dental clinicians. When compared against the dental clinicians, the YOLOv5 model shows the largest improvement, reporting 0.647 mean average precision, 0.548 mean F1-score, and 0.149 mean false negative rate. Whereas the best annotators on each of these metrics reported 0.299, 0.495, and 0.164 respectively. Conclusion Deep-learning models have shown the potential to assist dental professionals in the diagnosis of caries. Yet, the task remains challenging due to the artifacts natural to the bitewing images.

PurposeNeuroglial tumors are frequently associated with pharmacorefractory epilepsies. However, comprehensive knowledge about long-term outcomes after epilepsy surgery and the main prognostic factors for outcome is still limited. We sought to evaluate long-term outcomes and potential influencing factors in a large cohort of patients who underwent surgery for neuroglial tumors in a single-center setting.MethodsThe study analyzed the outcomes of 107 patients who underwent epilepsy surgery for neuroglial tumors between 2001 and 2020 at the Department of Epileptology, University Hospital Bonn, in Germany. The outcomes were evaluated using Engel classification. Differences in outcome related to potential prognostic factors were examined using the Chi2-test, Fisher’s exact test and sign test. Additionally, stepwise logistic regression analysis was employed to identify independent prognostic factors.ResultsComplete seizure freedom (Engel Class IA) was achieved in 75% of the operated patients at 12 months, and 56% at the last follow-up visit (70.4 ± 6.2 months, median: 40 months). Completeness of resection was a crucial factor for both 12-month follow-up outcomes and the longest available outcomes, whereas lobar tumor localization, histology (ganglioglioma vs. dysembryoplastic neuroepithelial tumor), history of bilateral tonic–clonic seizures prior to surgery, invasive diagnostics, side of surgery (dominant vs. non-dominant hemisphere), age at epilepsy onset, age at surgery, and epilepsy duration did not consistently impact postsurgical outcomes. Among temporal lobe surgeries, patients who underwent lesionectomy and lesionectomy, including hippocampal resection, demonstrated similar outcomes.ConclusionNeuroglial tumors present as excellent surgical substrates in treating structural epilepsy. To achieve an optimal postsurgical outcome, a complete lesion resection should be pursued whenever possible.

Abstract Automated detection of lesions using artificial intelligence creates new standards in medical imaging. For people with epilepsy, automated detection of focal cortical dysplasias (FCDs) is widely used because subtle FCDs often escape conventional neuroradiological diagnosis. Accurate recognition of FCDs, however, is of outstanding importance for affected people, as surgical resection of the dysplastic cortex is associated with a high chance of postsurgical seizure freedom. Here, we make publicly available a dataset of 85 people affected by epilepsy due to FCD type II and 85 healthy control persons. We publish 3D-T1 and 3D-FLAIR, manually labeled regions of interest, and carefully selected clinical features. The open presurgery MRI dataset may be used to validate existing automated algorithms of FCD detection as well as to create new approaches. Most importantly, it will enable comparability of already existing approaches and support a more widespread use of automated lesion detection tools.

Abstract Retinal disease accounts significantly for visual impairment and blindness. An important role in the pathophysiology of retinal disease and aging is attributed to lipofuscin, a complex of fluorescent metabolites. Fundus autofluorescence (AF) imaging allows non-invasive mapping of lipofuscin and is a key technology to diagnose and monitor retinal disease. However, currently used short-wavelength (SW) excitation light has several limitations, including glare and discomfort during image acquisition, reduced image quality in case of lens opacities, limited visualization of the central retina, and potential retinal light toxicity. Here, we establish a novel imaging modality which uses red excitation light (R-AF) and overcomes these drawbacks. R-AF images are high-quality, high-contrast fundus images and image interpretation may build on clinical experience due to similar appearance of pathology as on SW-AF images. Additionally, R-AF images may uncover disease features that previously remained undetected. The R-AF signal increases with higher abundance of lipofuscin and does not depend on photopigment bleaching or on the amount of macular pigment. Improved patient comfort, limited effect of cataract on image quality, and lack of safety concerns qualify R-AF for routine clinical monitoring, e.g. for patients with age-related macular degeneration, Stargardt disease, or for quantitative analysis of AF signal intensity.

Abstract Objective Ictal single photon emission computed tomography (SPECT) can be used as an advanced diagnostic modality to detect the seizure onset zone in the presurgical evaluation of people with epilepsy. In addition to visual assessment (VSA) of ictal and interictal SPECT images, postprocessing methods such as ictal‐interictal SPECT analysis using SPM (ISAS) can visualize regional ictal blood flow differences. We aimed to evaluate and differentiate the diagnostic value of VSA and ISAS in the Bonn cohort. Methods We included 161 people with epilepsy who underwent presurgical evaluation at the University Hospital Bonn between 2008 and 2020 and received ictal and interictal SPECT and ISAS. We retrospectively assigned SPECT findings to one of five categories according to their degree of concordance with the clinical focus hypothesis. Results Seizure onset zones could be identified more likely on a sublobar concordance level by ISAS than by VSA (31% vs. 19% of cases; OR = 1.88; 95% Cl [1.04, 3.42]; P = 0.03). Both VSA and ISAS more often localized a temporal seizure onset zone than an extratemporal one. Neither VSA nor ISAS findings were predicted by the latency between seizure onset and tracer injection (P = 0.75). In people who underwent successful epilepsy surgery, VSA and ISAS indicated the correct resection site in 54% of individuals, while MRI and EEG showed the correct resection localization in 96% and 33% of individuals, respectively. It was more likely to become seizure‐free after epilepsy surgery if ISAS or VSA had been successful. There was no MR‐negative case with successful surgery, indicating that ictal SPECT is more useful for confirmation than for localization. Significance The results of the most extensive clinical study of ictal SPECT to date allow an assessment of the diagnostic value of this elaborate examination and emphasize the importance of postprocessing routines.

Chang et al. classify people with Temporal Lobe Epilepsy (TLE), Alzheimer’s disease and healthy controls using a convolutional neural network algorithm applied to magnetic resonance imaging (MRI) scans. People with TLE can be distinguished, including those without easily identifiable TLE-associated MRI features.

Abstract Currently, little is known about the spatial distribution of white matter hyperintensities (WMH) in the brain of patients with Systemic Lupus erythematosus (SLE). Previous lesion markers, such as number and volume, ignore the strategic location of WMH. The goal of this work was to develop a fully-automated method to identify predominant patterns of WMH across WM tracts based on cluster analysis. A total of 221 SLE patients with and without neuropsychiatric symptoms from two different sites were included in this study. WMH segmentations and lesion locations were acquired automatically. Cluster analysis was performed on the WMH distribution in 20 WM tracts. Our pipeline identified five distinct clusters with predominant involvement of the forceps major, forceps minor, as well as right and left anterior thalamic radiations and the right inferior fronto-occipital fasciculus. The patterns of the affected WM tracts were consistent over the SLE subtypes and sites. Our approach revealed distinct and robust tract-based WMH patterns within SLE patients. This method could provide a basis, to link the location of WMH with clinical symptoms. Furthermore, it could be used for other diseases characterized by presence of WMH to investigate both the clinical relevance of WMH and underlying pathomechanism in the brain.

IntroductionSystemic lupus erythematosus (SLE) is an autoimmune connective tissue disease affecting multiple organs in the human body, including the central nervous system. Recently, an artificial intelligence method called BrainAGE (Brain Age Gap Estimation), defined as predicted age minus chronological age, has been developed to measure the deviation of brain aging from a healthy population using MRI. Our aim was to evaluate brain aging in SLE patients using a deep-learning BrainAGE model.MethodsSeventy female patients with a clinical diagnosis of SLE and 24 healthy age-matched control females, were included in this post-hoc analysis of prospectively acquired data. All subjects had previously undergone a 3 T MRI acquisition, a neuropsychological evaluation and a measurement of neurofilament light protein in plasma (NfL). A BrainAGE model with a 3D convolutional neural network architecture, pre-trained on the 3D-T1 images of 1,295 healthy female subjects to predict their chronological age, was applied on the images of SLE patients and controls in order to compute the BrainAGE. SLE patients were divided into 2 groups according to the BrainAGE distribution (high vs. low BrainAGE).ResultsBrainAGE z-score was significantly higher in SLE patients than in controls (+0.6 [±1.1] vs. 0 [±1.0], p = 0.02). In SLE patients, high BrainAGE was associated with longer reaction times (p = 0.02), lower psychomotor speed (p = 0.001) and cognitive flexibility (p = 0.04), as well as with higher NfL after adjusting for age (p = 0.001).ConclusionUsing a deep-learning BrainAGE model, we provide evidence of increased brain aging in SLE patients, which reflected neuronal damage and cognitive impairment.

Abstract Objective Recently, we showed that resection of at least 27% of the temporal part of piriform cortex (PiC) strongly correlated with seizure freedom 1 year following selective amygdalo‐hippocampectomy (tsSAHE) in patients with mesial temporal lobe epilepsy (mTLE). However, the impact of PiC resection on long‐term seizure outcome following tsSAHE is currently unknown. The aim of this study was to evaluate the impact of PiC resection on long‐term seizure outcome in patients with mTLE treated with tsSAHE. Methods Between 2012 and 2017, 64 patients were included in the retrospective analysis. Long‐term follow‐up (FU) was defined as at least 2 years postoperatively. Seizure outcome was assessed according to the International League against Epilepsy (ILAE). The resected proportions of hippocampus, amygdala, and PiC were volumetrically assessed. Results The mean FU duration was 3.75 ± 1.61 years. Patients with ILAE class 1 revealed a significantly larger median proportion of resected PiC compared to patients with ILAE class 2–6 [46% (IQR 31–57) vs. 16% (IQR 6–38), p = 0.001]. Resected proportions of hippocampus and amygdala did not significantly differ for these groups. Among those patients with at least 27% resected proportion of PiC, there were significantly more patients with seizure freedom compared to the patients with

Epilepsy is a brain network disorder with associated genetic risk factors. Here, the authors show that spatial patterns of transcriptomic vulnerability co-vary with structural brain network alterations in focal and generalized epilepsy.

For over a century, phenomenology has been a major philosophical movement [...]

Abstract Objective Using multimodal imaging, we tested the hypothesis that patients after hemispherotomy recruit non‐primary motor areas and non‐pyramidal descending motor fibers to restore motor function of the impaired limb. Methods Functional and structural MRI data were acquired in a group of 25 patients who had undergone hemispherotomy and in a matched group of healthy controls. Patients’ motor impairment was measured using the Fugl‐Meyer Motor Assessment. Cortical areas governing upper extremity motor‐control were identified by task‐based functional MRI. The resulting areas were used as nodes for functional and structural connectivity analyses. Results In hemispherotomy patients, movement of the impaired upper extremity was associated to widespread activation of non‐primary premotor areas, whereas movement of the unimpaired one and of the control group related to activations prevalently located in the primary motor cortex (all p ≤ 0.05, FWE‐corrected). Non‐pyramidal tracts originating in premotor/supplementary motor areas and descending through the pontine tegmentum showed relatively higher structural connectivity in patients (p

Abstract Selective amygdalohippocampectomy is an effective treatment for patients with therapy-refractory temporal lobe epilepsy but may cause visual field defect (VFD). Here, we aimed to describe tissue-specific pre- and postoperative imaging correlates of the VFD severity using whole-brain analyses from voxel- to network-level. Twenty-eight patients with temporal lobe epilepsy underwent pre- and postoperative MRI (T1-MPRAGE and Diffusion Tensor Imaging) as well as kinetic perimetry according to Goldmann standard. We probed for whole-brain gray matter (GM) and white matter (WM) correlates of VFD using voxel-based morphometry and tract-based spatial statistics, respectively. We furthermore reconstructed individual structural connectomes and conducted local and global network analyses. Two clusters in the bihemispheric middle temporal gyri indicated a postsurgical GM volume decrease with increasing VFD severity (FWE-corrected p

Abstract Arterial spin labeling (ASL) is increasingly applied for cerebral blood flow mapping, but $${\text{T}}_{{2}}$$ T 2 relaxation of the ASL signal magnetization is often ignored, although it may be clinically relevant. To investigate the extent, to which quantitative $${\text{T}}_{{2}}$$ T 2 values in gray matter (GM) obtained by pseudocontinuous ASL (pCASL) perfusion MRI can be reproduced, are reliable and a potential neuroscientific biomarker, a prospective study was performed with ten healthy volunteers (5F,28 ± 3y) at a 3 T scanner. A $${\text{T}}_{{2}}$$ T 2 -prepared pCASL sequence enabled the measurement of quantitative $${\text{T}}_{{2}}$$ T 2 and perfusion maps. $${\text{T}}_{{2}}$$ T 2 times were modeled per voxel and analyzed within four GM-regions-of-interest (ROI). The intraclass correlation coefficients (ICCs) of the quantified ASL- $${\text{T}}_{{2}}$$ T 2 varied across brain regions. When averaged across subjects and postlabeling delays (PLDs), the ICCs ranged from reasonable values in parietal regions (ICC = 0.56) to smaller values in frontal regions (ICC = 0.36). Corresponding subject-averaged within-subject coefficients of variation (WSCVs) showed good test–retest measurement precision ( $${\text{WSCV}}_{{{\text{PLD}}}} \le 0.14$$ WSCV PLD ≤ 0.14 for all PLDs), but more pronounced inter-subject variance. Reliability and precision of quantified ASL- $${\text{T}}_{{2}}$$ T 2 were region-, PLD- and subject-specific, showing fair to robust results in occipital, parietal and temporal ROIs. The results give rise to consider the method for future cerebral studies, where variable perfusion or altered $${\text{T}}_{{2}}$$ T 2 times are suspected.

There are many ways to acquire and process diffusion MRI (dMRI) data for group studies, but it is unknown which maximizes the sensitivity to white matter (WM) pathology. Inspired by this question, we analyzed data acquired for diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) at 3T (3T-DTI and 3T-DKI) and DTI at 7T in patients with systemic lupus erythematosus (SLE) and healthy controls (HC). Parameter estimates in 72 WM tracts were obtained using TractSeg. The impact on the sensitivity to WM pathology was evaluated for the diffusion protocol, the magnetic field strength, and the processing pipeline. Sensitivity was quantified in terms of Cohen's d for group comparison. Results showed that the choice of diffusion protocol had the largest impact on the effect size. The effect size in fractional anisotropy (FA) across all WM tracts was 0.26 higher when derived by DTI than by DKI and 0.20 higher in 3T compared with 7T. The difference due to the diffusion protocol was larger than the difference due to magnetic field strength for the majority of diffusion parameters. In contrast, the difference between including or excluding different processing steps was near negligible, except for the correction of distortions from eddy currents and motion which had a clearly positive impact. For example, effect sizes increased on average by 0.07 by including motion and eddy correction for FA derived from 3T-DTI. Effect sizes were slightly reduced by the incorporation of denoising and Gibbs-ringing removal (on average by 0.011 and 0.005, respectively). Smoothing prior to diffusion model fitting generally reduced effect sizes. In summary, 3T-DTI in combination with eddy current and motion correction yielded the highest sensitivity to WM pathology in patients with SLE. However, our results also indicated that the 3T-DKI and 7T-DTI protocols used here may be adjusted to increase effect sizes.

Childhood is a period of extensive cortical and neural development. Among other things, axons in the brain gradually become more myelinated, promoting the propagation of electrical signals between different parts of the brain, which in turn may facilitate skill development. Myelin is difficult to assess in vivo, and measurement techniques are only just beginning to make their way into standard imaging protocols in human cognitive neuroscience. An approach that has been proposed as an indirect measure of cortical myelin is the T1w/T2w ratio, a contrast that is based on the intensities of two standard structural magnetic resonance images. Although not initially intended as such, researchers have recently started to use the T1w/T2w contrast for between-subject comparisons of cortical data with various behavioral and cognitive indices. As a complement to these earlier findings, we computed individual cortical T1w/T2w maps using data from the Adolescent Brain Cognitive Development study (N = 960; 449 females; aged 8.9 to 11.0 years) and related the T1w/T2w maps to indices of cognitive ability; in contrast to previous work, we did not find significant relationships between T1w/T2w values and cognitive performance after correcting for multiple testing. These findings reinforce existent skepticism about the applicability of T1w/T2w ratio for inter-individual comparisons.

Artificial intelligence has recently gained popularity across different medical fields to aid in the detection of diseases based on pathology samples or medical imaging findings. Brain magnetic resonance imaging (MRI) is a key assessment tool for patients with temporal lobe epilepsy (TLE). The role of machine learning and artificial intelligence to increase detection of brain abnormalities in TLE remains inconclusive. We used support vector machine (SV) and deep learning (DL) models based on region of interest (ROI-based) structural (n = 336) and diffusion (n = 863) brain MRI data from patients with TLE with (“lesional”) and without (“non-lesional”) radiographic features suggestive of underlying hippocampal sclerosis from the multinational (multi-center) ENIGMA-Epilepsy consortium. Our data showed that models to identify TLE performed better or similar (68–75%) compared to models to lateralize the side of TLE (56–73%, except structural-based) based on diffusion data with the opposite pattern seen for structural data (67–75% to diagnose vs. 83% to lateralize). In other aspects, structural and diffusion-based models showed similar classification accuracies. Our classification models for patients with hippocampal sclerosis were more accurate (68–76%) than models that stratified non-lesional patients (53–62%). Overall, SV and DL models performed similarly with several instances in which SV mildly outperformed DL. We discuss the relative performance of these models with ROI-level data and the implications for future applications of machine learning and artificial intelligence in epilepsy care.

Cerebral lesions may cause degeneration and neuroplastic reorganization in both the ipsi- and the contralesional hemisphere, presumably creating an imbalance of primarily inhibitory interhemispheric influences produced via transcallosal pathways. The two hemispheres are thought to mutually hamper neuroplastic reorganization of the other hemisphere. The results of preceding degeneration and neuroplastic reorganization of white matter may be reflected by Diffusion Tensor Imaging-derived diffusivity parameters such as fractional anisotropy (FA). In this study, we applied Diffusion Tensor Imaging (DTI) to contrast the white matter status of the contralesional hemisphere of young lesioned brains with and without contralateral influences by comparing patients after hemispherotomy to those who had not undergone neurosurgery. DTI was applied to 43 healthy controls (26 females, mean age ± SD: 25.07 ± 11.33 years) and two groups of in total 51 epilepsy patients with comparable juvenile brain lesions (32 females, mean age ± SD: 25.69 ± 12.77 years) either after hemispherotomy (30 of 51 patients) or without neurosurgery (21 of 51 patients), respectively. FA values were compared between these groups using the unbiased tract-based spatial statistics approach. A voxel-wise ANCOVA controlling for age at scan yielded significant group differences in FA. A post hoc t-test between hemispherotomy patients and healthy controls revealed widespread supra-threshold voxels in the contralesional hemisphere of hemispherotomy patients indicating comparatively higher FA values (p < 0.05, FWE-corrected). The non-surgery group, in contrast, showed extensive supra-threshold voxels indicating lower FA values in the contralesional hemisphere as compared to healthy controls (p < 0.05, FWE-corrected). Whereas lower FA values are suggestive of pronounced contralesional degeneration in the non-surgery group, higher FA values in the hemispherotomy group may be interpreted as a result of preceding plastic remodeling. We conclude that, whether juvenile brain lesions are associated with contralesional degeneration or reorganization partly depends on the ipsilesional hemisphere. Contralesional reorganization as observed in hemispherotomy patients was most likely enabled by the complete neurosurgical deafferentation of the ipsilesional hemisphere and, thereby, the disinhibition of the neuroplastic potential of the contralesional hemisphere. The main argument of this study is that hemispherotomy may be seen as a major plastic stimulus and as a prerequisite for contralesional neuroplastic remodeling in patients with juvenile brain lesions.

En nuestra sección de clásicos queremos hacerle un reconocimiento a otro de los pioneros del psicoanálisis como lo fue Theodor Reik

Limbic encephalitis (LE) is an autoimmune syndrome often associated with temporal lobe epilepsy. Recent research suggests that particular structural changes in LE depend on the type of the associated antibody and occur in both mesiotemporal gray matter and white matter regions. However, it remains questionable to what degree conventional diffusion tensor imaging (DTI)-methods reflect alterations in white matter microstructure, since these methods do not account for crossing fibers. To address this methodological shortcoming, we applied fixel-based analysis as a novel technique modeling distinct fiber populations. For our study, 19 patients with LE associated with autoantibodies against glutamic acid decarboxylase 65 (GAD-LE, mean age = 35.9 years, 11 females), 4 patients with LE associated with autoantibodies against leucine-rich glioma-inactivated 1 (LGI1-LE, mean age = 63.3 years, 2 females), 5 patients with LE associated with contactin-associated protein-like 2 (CASPR2, mean age = 57.4, 0 females), 20 age- and gender-matched control patients with hippocampal sclerosis (19 GAD-LE control patients: mean age = 35.1 years, 11 females; 4 LGI1-LE control patients: mean age = 52.6 years, 2 females; 5 CASPR2-LE control patients: mean age = 42.7 years, 0 females; 10 patients are included in more than one group) and 33 age- and gender-matched healthy control subjects (19 GAD-LE healthy controls: mean age = 34.6 years, 11 females; 8 LGI1-LE healthy controls: mean age = 57.0 years, 4 females, 10 CASPR2-LE healthy controls: mean age = 57.2 years, 0 females; 4 subjects are included in more than one group) underwent structural imaging and DTI at 3 T and neuropsychological testing. Patient images were oriented according to lateralization in EEG resulting in an affected and unaffected hemisphere. Fixel-based metrics fiber density (FD), fiber cross-section (FC), and fiber density and cross-section (FDC = FD · FC) were calculated to retrieve information about white matter integrity both on the micro- and the macroscale. As compared to healthy controls, patients with GAD-LE showed significantly (family-wise error-corrected, p