Biology subjects

Schweizer, R.

Publications and source records attributed to Schweizer, R..

6 recordsLinked to original sources

bioRxiv2025

Characterization of the central sulcus pli-de-passage fronto-parietal moyen in > 1000 human brains

The pli-de-passage fronto-parietal moyen (PPfpm), a deep cerebral fold of the human brain, presents as a common though small elevation at the central sulcus (CS) fundus where it connects the pre- and postcentral gyri at the level of the sensorimotor hand area. Given the PPfpms location, single case-reports of its association with the functional sensorimotor hand area, and evidence linking it to the somato-cognitive action network, it holds potential as an anatomical landmark for the sensorimotor region. To characterize the macroscopic morphology of the PPfpm and evaluate its relevance as a reliable and easily detectable anatomical landmark, methods for observer-independent characterization of cortical sulci and structures were adapted and developed to investigate the PPfpm in a large dataset. For 1112 subjects from the Human Connectome Project Young Adult S1200 Release, CS depth profiles were computed from structural magnetic resonance imaging (MRI) data, and an algorithm was developed to automatically extract the PPfpm from these depth profiles. Based on the extraction of two key features approximating the PPfpm at its peak height (PPfpm-I) and its lateral end (PPfpm-II), a principal description of the PPfpms position and extent as influenced by hemisphere and sex was conducted. Analyses revealed the PPfpm as a near-universal cerebral fold in the adult human brain, consistently located at mid-height within the CS with a strong association to the CS sulcal pits. Though commonly of a small extent, the PPfpm can be reliably identified in CS depth profiles and in structural MRI data. By providing a systematic, modern macroanatomical characterization of the PPfpm in a large cohort with rigorous quality control, the present study demonstrates the potential of the PPfpm to serve as a robust anatomical landmark for the sensorimotor hand area of the human brain.

neuroscience↗

bioRxiv2025

Chromosome-level genome assembly of Protandrena (Anthemurgus) passiflorae (Hymenoptera: Andrenidae), a host-plant specialist bee

The passion flower bee, Protandrena (Anthemurgus) passiflorae (Robertson) is a monolectic, host-plant specialist of the passionflower plant Passiflora lutea L. Using a single adult male individual, we generated long-read PacBio HiFi, HiC, and short-read RNA sequencing data to build a well-annotated, chromosome-level genome assembly for this species. The final nuclear genome is 249 Mb with 150x coverage and with most of the genome scaffolding into 12 chromosomes. The scaffold N50 is 21.4 Mb and the genome has a Benchmarking Universal Single-Copy Ortholog (BUSCO) score of 97.2% for 5991 hymenopteran genes. BRAKER3 annotation of the genome identified 12,098 genes and 15,353 total transcripts and found that 20.27% of the genome is made up of repetitive elements. We resolved a mitochondrial genome of 12.7 kb. The P. passiflorae genome represents one of only a few published andrenid bee genomes and one of the first monolectic bees. This new high-quality genome will serve as a valuable resource for investigating the genomic basis of specialization and for providing a useful resource for studying pollinator health and conservation.

genomics↗

bioRxiv2024

The deep winding at the brain surface: replicating a historical report associating the 'bridged' central sulcus with the pli de passage fronto-parietal moyen

In 1876, the anatomist Heschl surveyed 1,087 brains identifying six cases of a unilateral bridged central sulcus (CS) at the brain surface. He also measured the height of a minor deep winding at the same location within the CS in the remaining 1,081 brains, reporting a distribution skewed towards significantly increased heights. These observations supported his hypothesis that the bridged CS represents an extreme form of the deep winding within the CS. In this replication we examined structural MRI data from an equally large dataset of 1,112 participants of the Human Connectome Project young adult (HCP-YA) dataset. Through visual inspection, we identified nine cases of a bridged CS, confirming its prevalence of less than 1%. The height of the deep winding, referred to in the HCP-YA dataset as the pli de passage fronto-parietal moyen (PPfpm), was extracted from 1,983 MRI-based hemispheric depth profiles. The resulting PPfpm height distribution, although wider, still mirrored Heschls findings, showing a similar skew towards larger heights. Further analyses of the twin data within the HCP-YA dataset indicated a slightly increased prevalence of the bridged CS in monozygotic and dizygotic twins compared to non-twin individuals, though no concordance of bridged CS was observed in monozygotic twin pairs. This replication study validates both of Heschls observations, describes additional factors that might influence the prevalence of the bridged CS, and refines the characterization of the deep winding height distribution. Together, these findings reaffirm and expand historical insights into the intricate anatomical organization of the CS.

neuroscience↗

bioRxiv2022

Tactile Stimulation Designs Adapted to Clinical Settings Result in Reliable fMRI-based Somatosensory Digit Maps

A wide range of neurological diseases with impaired motor functioning of the upper extremities are accompanied by impairments of somatosensory functioning, which are often undescribed but can provide crucial information for diagnostics, treatment selection, and follow-up. Therefore, a reliable description of the functional representation of the digits in the somatosensory cortex would be a highly valuable, but currently lacking, tool in the clinical context. Task-based functional Magnetic Resonance Imaging of passive tactile stimulation provides an indirect, but valid description of the layout of the digit map in the primary somatosensory cortex. However, to fulfill the specific requirements for clinical application, the presently established approaches need to be adapted and subsequently assessed for feasibility and retest reliability, in order to provide informative parameters for the description of the evoked digit activations. Accordingly, the present high-field 3T fMRI study compares the performance of two established digit mapping designs - travelling wave (TW) and blocked design (BD) - for passive tactile stimulation of the five digits, adapted to reduce the time requirements to just below 15 minutes. To be able to assess the retest reliability unaffected by any clinical conditions, the study was performed on neurotypical participants. The results show that both stimulation designs evoke significant and distinct activation clusters in the primary somatosensory cortex of all participants for all five digits. The average spatial locations of the center of gravities across participants show the common succession of distinct digit representation along the central sulcus. The cortical extent elicited activation, which is generally larger for the thumb and the index finger, also shows comparable average values across the two approaches. Less overlap of activation between neighboring digits was obtained in BD, consistent with the distinct single digit neuronal representations. A high retest reliability was obtained for the location of the digit activation, displaying stable center of gravity locations across sessions for both stimulation designs. This is contrasted by only medium to low retest reliability for the extent and overlap of the digit activations, indicating discrepancies across sessions. These results demonstrate the capacity of shortened fMRI digit mapping approaches (both TW and BD) to obtain the full layout of single digit cortical activations on the level of the individual, which together with the high reliability of the location of the digit representation over time indicates both approaches are clinically applicable.

neuroscience↗

bioRxiv2020

Determinants of Real-Time fMRI Neurofeedback Performance and Improvement: a Machine Learning Mega-Analysis

Real-time fMRI neurofeedback is an increasingly popular neuroimaging technique that allows an individual to gain control over his/her own brain signals, which can lead to improvements in behavior in healthy participants as well as to improvements of clinical symptoms in patient populations. However, a considerably large ratio of participants undergoing neurofeedback training do not learn to control their own brain signals and, consequently, do not benefit from neurofeedback interventions, which limits clinical efficacy of neurofeedback interventions. As neurofeedback success varies between studies and participants, it is important to identify factors that might influence neurofeedback success. Here, for the first time, we employed a big data machine learning approach to investigate the influence of 20 different design-specific (e.g. activity vs. connectivity feedback), region of interest-specific (e.g. cortical vs. subcortical) and subject-specific factors (e.g. age) on neurofeedback performance and improvement in 608 participants from 28 independent experiments. With a classification accuracy of 60% (considerably different from chance level), we identified two factors that significantly influenced neurofeedback performance: Both the inclusion of a pre-training no-feedback run before neurofeedback training and neurofeedback training of patients as compared to healthy participants were associated with better neurofeedback performance. The positive effect of pre-training no-feedback runs on neurofeedback performance might be due to the familiarization of participants with the neurofeedback setup and the mental imagery task before neurofeedback training runs. Better performance of patients as compared to healthy participants might be driven by higher motivation of patients, higher ranges for the regulation of dysfunctional brain signals, or a more extensive piloting of clinical experimental paradigms. Due to the large heterogeneity of our dataset, these findings likely generalize across neurofeedback studies, thus providing guidance for designing more efficient neurofeedback studies specifically for improving clinical neurofeedback-based interventions. To facilitate the development of data-driven recommendations for specific design details and subpopulations the field would benefit from stronger engagement in Open Science and data sharing.

neuroscience↗

bioRxiv2020

Can we predict real-time fMRI neurofeedback learning success from pre-training brain activity?

Neurofeedback training has been shown to influence behavior in healthy participants as well as to alleviate clinical symptoms in neurological, psychosomatic, and psychiatric patient populations. However, many real-time fMRI neurofeedback studies report large interindividual differences in learning success. The factors that cause this vast variability between participants remain unknown and their identification could enhance treatment success. Thus, here we employed a meta-analytic approach including data from 24 different neurofeedback studies with a total of 401 participants, including 140 patients, to determine whether levels of activity in target brain regions during pre-training functional localizer or no-feedback runs (i.e., self-regulation in the absence of neurofeedback) could predict neurofeedback learning success. We observed a slightly positive correlation between pre-training activity levels during a functional localizer run and neurofeedback learning success, but we were not able to identify common brain-based success predictors across our diverse cohort of studies. Therefore, advances need to be made in finding robust models and measures of general neurofeedback learning, and in increasing the current study database to allow for investigating further factors that might influence neurofeedback learning.

neuroscience↗