Temporal frequency dependence of the polarity inversion between upper and lower visual field in the pattern-onset steady-state visual evoked potential.

PURPOSE: According to the cruciform model, the upper and lower halves of the visual field representation in the primary visual cortex are located mainly on the opposite sides of the calcarine sulcus. Such a shape would have consequences for the surface-recorded visual evoked potential (VEP), as V1 responses to stimulation of the upper and lower hemifield manifest with opposite polarity (i.e., polarity inversion). However, the steady-state VEP results from a complex superposition of response components from different cortical sources, which can obscure the inversion of polarity. The present study assesses the issue for different stimulation frequencies which result in different patterns of superposition in the steady-state response. METHODS: Sequences of brief pattern-onset stimuli were presented at different stimulation rates ranging from 2 Hz (transient VEP) to 13 Hz (steady-state VEP). The upper and lower hemifields were tested separately and simultaneously. The data were assessed both in the time domain and in the frequency domain. RESULTS: Comparing the responses to the stimulation of upper and lower hemifield, polarity inversion was present within a limited time interval following individual stimulus onsets. With increasing frequency, this resulted in an approximate inversion of the full steady-state response and consequently in a phase shift of approximately 180° in the time-domain response. Polarity inversion was more prominent at electrode Pz, also for transient responses. Our data also demonstrated that the sum of the hemifield responses is a good approximation of the full-field response. CONCLUSION: While the basic phenomenon of polarity inversion occurs irrespective of the stimulus frequency, its relative impact on the steady-state response as a whole is the largest for high stimulation rates. We propose that this is because longer-lasting response components from other visual areas are not well represented in the steady-state VEP at higher frequencies.

"I Spy with my Little Eye, Something that is a Face ": A Brain Network for Illusory Face Detection.

The most basic aspect of face perception is simply detecting the presence of a face, which requires the extraction of features that it has in common with other faces. Putatively, it is caused by matching high-dimensional sensory input with internal face templates, achieved through a top-down mediated coupling between prefrontal regions and brain areas in the occipito-temporal cortex ("core system of face perception"). Illusory face detection tasks can be used to study these top-down influences. In the present functional magnetic resonance imaging study, we showed that illusory face perception activated just as real faces the core system, albeit with atypical left-lateralization of the occipital face area. The core system was coupled with two distinct brain regions in the lateral prefrontal (inferior frontal gyrus, IFG) and orbitofrontal cortex (OFC). A dynamic causal modeling (DCM) analysis revealed that activity in the core system during illusory face detection was upregulated by a modulatory face-specific influence of the IFG, not as previously assumed by the OFC. Based on these findings, we were able to develop the most comprehensive neuroanatomical framework of illusory face detection until now.

Towards minimizing efforts for Morphing Attacks-Deep embeddings for morphing pair selection and improved Morphing Attack Detection.

Face Morphing Attacks pose a threat to the security of identity documents, especially with respect to a subsequent access control process, because they allow both involved individuals to use the same document. Several algorithms are currently being developed to detect Morphing Attacks, often requiring large data sets of morphed face images for training. In the present study, face embeddings are used for two different purposes: first, to pre-select images for the subsequent large-scale generation of Morphing Attacks, and second, to detect potential Morphing Attacks. Previous studies have demonstrated the power of embeddings in both use cases. However, we aim to build on these studies by adding the more powerful MagFace model to both use cases, and by performing comprehensive analyses of the role of embeddings in pre-selection and attack detection in terms of the vulnerability of face recognition systems and attack detection algorithms. In particular, we use recent developments to assess the attack potential, but also investigate the influence of morphing algorithms. For the first objective, an algorithm is developed that pairs individuals based on the similarity of their face embeddings. Different state-of-the-art face recognition systems are used to extract embeddings in order to pre-select the face images and different morphing algorithms are used to fuse the face images. The attack potential of the differently generated morphed face images will be quantified to compare the usability of the embeddings for automatically generating a large number of successful Morphing Attacks. For the second objective, we compare the performance of the embeddings of two state-of-the-art face recognition systems with respect to their ability to detect morphed face images. Our results demonstrate that ArcFace and MagFace provide valuable face embeddings for image pre-selection. Various open-source and commercial-off-the-shelf face recognition systems are vulnerable to the generated Morphing Attacks, and their vulnerability increases when image pre-selection is based on embeddings compared to random pairing. In particular, landmark-based closed-source morphing algorithms generate attacks that pose a high risk to any tested face recognition system. Remarkably, more accurate face recognition systems show a higher vulnerability to Morphing Attacks. Among the systems tested, commercial-off-the-shelf systems were the most vulnerable to Morphing Attacks. In addition, MagFace embeddings stand out as a robust alternative for detecting morphed face images compared to the previously used ArcFace embeddings. The results endorse the benefits of face embeddings for more effective image pre-selection for face morphing and for more accurate detection of morphed face images, as demonstrated by extensive analysis of various designed attacks. The MagFace model is a powerful alternative to the often-used ArcFace model in detecting attacks and can increase performance depending on the use case. It also highlights the usability of embeddings to generate large-scale morphed face databases for various purposes, such as training Morphing Attack Detection algorithms as a countermeasure against attacks.

Predictive Attributes for Developing Long COVID-A Study Using Machine Learning and Real-World Data from Primary Care Physicians in Germany.

(1) In the present study, we used data comprising patient medical histories from a panel of primary care practices in Germany to predict post-COVID-19 conditions in patients after COVID-19 diagnosis and to evaluate the relevant factors associated with these conditions using machine learning methods. (2) Methods: Data retrieved from the IQVIATM Disease Analyzer database were used. Patients with at least one COVID-19 diagnosis between January 2020 and July 2022 were selected for inclusion in the study. Age, sex, and the complete history of diagnoses and prescription data before COVID-19 infection at the respective primary care practice were extracted for each patient. A gradient boosting classifier (LGBM) was deployed. The prepared design matrix was randomly divided into train (80%) and test data (20%). After optimizing the hyperparameters of the LGBM classifier by maximizing the F2 score, model performance was evaluated using several test metrics. We calculated SHAP values to evaluate the importance of the individual features, but more importantly, to evaluate the direction of influence of each feature in our dataset, i.e., whether it is positively or negatively associated with a diagnosis of long COVID. (3) Results: In both the train and test data sets, the model showed a high recall (sensitivity) of 81% and 72% and a high specificity of 80% and 80%; this was offset, however, by a moderate precision of 8% and 7% and an F2-score of 0.28 and 0.25. The most common predictive features identified using SHAP included COVID-19 variant, physician practice, age, distinct number of diagnoses and therapies, sick days ratio, sex, vaccination rate, somatoform disorders, migraine, back pain, asthma, malaise and fatigue, as well as cough preparations. (4) Conclusions: The present exploratory study describes an initial investigation of the prediction of potential features increasing the risk of developing long COVID after COVID-19 infection by using the patient history from electronic medical records before COVID-19 infection in primary care practices in Germany using machine learning. Notably, we identified several predictive features for the development of long COVID in patient demographics and their medical histories.

Developmental changes within the extended face processing network: A cross-sectional functional magnetic resonance imaging study.

In the field of face processing, the so-called "core network" has been intensively researched. Its neural activity can be reliably detected in children and adults using functional magnetic resonance imaging (fMRI). However, the core network's counterpart, the so-called "extended network," has been less researched. In the present study, we compared children's and adults' brain activity in the extended system, in particular in the amygdala, the insula, and the inferior frontal gyrus (IFG). Using fMRI, we compared the brain activation pattern between children aged 7-9 years and adults during an emotional face processing task. On the one hand, children showed increased activity in the extended face processing system in relation to adults, particularly in the left amygdala, the right insula, and the left IFG. On the other hand, lateralization indices revealed a "leftward bias" in children's IFG compared to adults. These results suggest that brain activity associated with face processing is characterized by a developmental decrease in activity. They further show that the development is associated with a rightward migration of face-related IFG activation, possibly due to the competition for neural space between several developing brain functions ("developmental competition hypothesis").

Exosomal mitochondrial tRNAs and miRNAs as potential predictors of inflammation in renal proximal tubular epithelial cells.

Exosomes have emerged as a valuable repository of novel biomarkers for human diseases such as chronic kidney disease (CKD). From a healthy control group, we performed microRNA (miRNA) profiling of urinary exosomes and compared it with a cell culture model of renal proximal tubular epithelial cells (RPTECs). Thereby, a large fraction of abundant urinary exosomal miRNAs could also be detected in exosomes derived from RPTECs, indicating them as a suitable model system for investigation of CKD. We subsequently analyzed exosomes from RPTECs in pro-inflammatory and pro-fibrotic states, mimicking some aspects of CKD. Following cytokine treatment, we observed a significant increase in exosome release and identified 30 dysregulated exosomal miRNAs, predominantly associated with the regulation of pro-inflammatory and pro-fibrotic-related pathways. In addition to miRNAs, we also identified 16 dysregulated exosomal mitochondrial RNAs, highlighting a pivotal role of mitochondria in sensing renal inflammation. Inhibitors of exosome biogenesis and release significantly altered the abundance of selected candidate miRNAs and mitochondrial RNAs, thus suggesting distinct sorting mechanisms of different non-coding RNA (ncRNA) species into exosomes. Hence, these two exosomal ncRNA species might be employed as potential indicators for predicting the pathogenesis of CKD and also might enable effective monitoring of the efficacy of CKD treatment.

The Trajectory of Hemispheric Lateralization in the Core System of Face Processing: A Cross-Sectional Functional Magnetic Resonance Imaging Pilot Study.

Face processing is mediated by a distributed neural network commonly divided into a "core system" and an "extended system." The core system consists of several, typically right-lateralized brain regions in the occipito-temporal cortex, including the occipital face area (OFA), the fusiform face area (FFA) and the posterior superior temporal sulcus (pSTS). It was recently proposed that the face processing network is initially bilateral and becomes right-specialized in the course of the development of reading abilities due to the competition between language-related regions in the left occipito-temporal cortex (e.g., the visual word form area, VWFA) and the FFA for common neural resources. In the present pilot study, we assessed the neural face processing network in 12 children (aged 7-9 years) and 10 adults with functional magnetic resonance imaging (fMRI). The hemispheric lateralization of the core face regions was compared between both groups. The study had two goals: First, we aimed to establish an fMRI paradigm suitable for assessing activation in the core system of face processing in young children at the single subject level. Second, we planned to collect data for a power analysis to calculate the necessary group size for a large-scale cross-sectional imaging study assessing the ontogenetic development of the lateralization of the face processing network, with focus on the FFA. It was possible to detect brain activity in the core system of 75% of children at the single subject level. The average scan-to-scan motion of the included children was comparable to adults, ruling out that potential activation differences between groups are caused by unequal motion artifacts. Hemispheric lateralization of the FFA was 0.07 ± 0.48 in children (indicating bilateral activation) and -0.32 ± 0.52 in adults (indicating right-hemispheric dominance). These results thus showed, as expected, a trend for increased lateralization in adults. The estimated effect size for the FFA lateralization difference was d = 0.78 (indicating medium to large effects). An adequately powered follow-up study (sensitivity 0.8) testing developmental changes of FFA lateralization would therefore require the inclusion of 18 children and 26 adults.

Long-Term Neuroanatomical Consequences of Childhood Maltreatment: Reduced Amygdala Inhibition by Medial Prefrontal Cortex.

Similar to patients with Major depressive disorder (MDD), healthy subjects at risk for depression show hyperactivation of the amygdala as a response to negative emotional expressions. The medial prefrontal cortex is responsible for amygdala control. Analyzing a large cohort of healthy subjects, we aimed to delineate malfunction in amygdala regulation by the medial prefrontal cortex in subjects at increased risk for depression, i.e., with a family history of affective disorders or a personal history of childhood maltreatment. We included a total of 342 healthy subjects from the FOR2107 cohort (www.for2107.de). An emotional face-matching task was used to identify the medial prefrontal cortex and right amygdala. Dynamic Causal Modeling (DCM) was conducted and neural coupling parameters were obtained for healthy controls with and without particular risk factors for depression. We assigned a genetic risk if subjects had a first-degree relative with an affective disorder and an environmental risk if subjects experienced childhood maltreatment. We then compared amygdala inhibition during emotion processing between groups. Amygdala inhibition by the medial prefrontal cortex was present in subjects without those two risk factors, as indicated by negative model parameter estimates. Having a genetic risk (i.e., a family history) did not result in changes in amygdala inhibition compared to no risk subjects. In contrast, childhood maltreatment as environmental risk has led to a significant reduction of amygdala inhibition by the medial prefrontal cortex. We propose a mechanistic explanation for the amygdala hyperactivity in subjects with particular risk for depression, in particular childhood maltreatment, caused by a malfunctioned amygdala downregulation via the medial prefrontal cortex. As childhood maltreatment is a major environmental risk factor for depression, we emphasize the importance of this potential early biomarker.

Two-Tactor Vibrotactile Navigation Information for the Blind: Directional Resolution and Intuitive Interpretation.

Lacking vision, blind people have to exploit other senses for navigation. Using the tactile rather than the auditory sense avoids masking important environmental information. Directional information is particularly important and traditionally conveyed through an array of tactors, each coding one direction. Here, we present a different approach to represent arbitrary directions with only two tactors. We tested intuitiveness, plasticity, and variability of direction perception in a behavioral experiment in 33 seeing participants.

Changes in the miRNA-mRNA Regulatory Network Precede Motor Symptoms in a Mouse Model of Multiple System Atrophy: Clinical Implications.

Multiple system atrophy (MSA) is a fatal rapidly progressive α-synucleinopathy, characterized by α-synuclein accumulation in oligodendrocytes. It is accepted that the pathological α-synuclein accumulation in the brain of MSA patients plays a leading role in the disease process, but little is known about the events in the early stages of the disease. In this study we aimed to define potential roles of the miRNA-mRNA regulatory network in the early pre-motor stages of the disease, i.e., downstream of α-synuclein accumulation in oligodendroglia, as assessed in a transgenic mouse model of MSA. We investigated the expression patterns of miRNAs and their mRNA targets in substantia nigra (SN) and striatum, two brain regions that undergo neurodegeneration at a later stage in the MSA model, by microarray and RNA-seq analysis, respectively. Analysis was performed at a time point when α-synuclein accumulation was already present in oligodendrocytes at neuropathological examination, but no neuronal loss nor deficits of motor function had yet occurred. Our data provide a first evidence for the leading role of gene dysregulation associated with deficits in immune and inflammatory responses in the very early, non-symptomatic disease stages of MSA. While dysfunctional homeostasis and oxidative stress were prominent in SN in the early stages of MSA, in striatum differential gene expression in the non-symptomatic phase was linked to oligodendroglial dysfunction, disturbed protein handling, lipid metabolism, transmembrane transport and altered cell death control, respectively. A large number of putative miRNA-mRNAs interaction partners were identified in relation to the control of these processes in the MSA model. Our results support the role of early changes in the miRNA-mRNA regulatory network in the pathogenesis of MSA preceding the clinical onset of the disease. The findings thus contribute to understanding the disease process and are likely to pave the way towards identifying disease biomarkers for early diagnosis of MSA.

dDsk2 regulates H2Bub1 and RNA polymerase II pausing at dHP1c complex target genes.

dDsk2 is a conserved extraproteasomal ubiquitin receptor that targets ubiquitylated proteins for degradation. Here we report that dDsk2 plays a nonproteolytic function in transcription regulation. dDsk2 interacts with the dHP1c complex, localizes at promoters of developmental genes and is required for transcription. Through the ubiquitin-binding domain, dDsk2 interacts with H2Bub1, a modification that occurs at dHP1c complex-binding sites. H2Bub1 is not required for binding of the complex; however, dDsk2 depletion strongly reduces H2Bub1. Co-depletion of the H2Bub1 deubiquitylase dUbp8/Nonstop suppresses this reduction and rescues expression of target genes. RNA polymerase II is strongly paused at promoters of dHP1c complex target genes and dDsk2 depletion disrupts pausing. Altogether, these results suggest that dDsk2 prevents dUbp8/Nonstop-dependent H2Bub1 deubiquitylation at promoters of dHP1c complex target genes and regulates RNA polymerase II pausing. These results expand the catalogue of nonproteolytic functions of ubiquitin receptors to the epigenetic regulation of chromatin modifications.

The PHD domain is required to link Drosophila Pygopus to Legless/beta-catenin and not to histone H3.

In Drosophila Pygopus (Pygo) and Legless (Lgs)/BCL9 are integral components of the nuclear Wnt/Wg signaling machine. Despite intense research, ideas that account for their mode of action remain speculative. One proposition, based on a recently discovered function of PHD fingers, is that Pygo, through its PHD, may decipher the histone code. We found that human, but not Drosophila, Pygo robustly interacts with a histone-H3 peptide methylated at lysine-4. The different binding behavior is due to a single amino acid change that appears unique to Drosophilidae Pygo proteins. Rescue experiments with predicted histone binding mutants showed that in Drosophila the ability to bind histones is not essential. Further experiments with Pygo-Lgs fusions instead demonstrated that the crucial role of the PHD is to provide an interaction motif to bind Lgs. Our results reveal an interesting evolutionary dichotomy in Pygo structure-function, as well as evidence underpinning the chain of adaptors model.