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The research team Empenn ("Brain" in Breton language) ERL U1228 is co-affiliated with Inria, Inserm (National Institute for Health and Scientific Research), CNRS (INS2I institute), and the University of Rennes I. It is a team of IRISA/UMR CNRS 6074. Empenn is located in Rennes, on the medical and scientific campus. It succeeded in 2019 to the "VisAGeS" team, created in 2006 by Inria. As for "VisAGeS", Empenn holds the accreditation number U1228, renewed by Inserm in 2022 and for a period of 6 years, after an evaluation conducted by the HCERES and Inserm.
Thanks to this unique partnership, Empenn's ambition is to establish a multidisciplinary team of researchers in information sciences and medicine. Our medium and long term objective is to introduce our fundamental research into clinical practice, while maintaining the excellence of our methodological research.
Our goal is to foster research in medical imaging, neuroinformatics and population cohorts. In particular, the Empenn team aims at the detection and development of imaging biomarkers for brain diseases and focuses its efforts on transferring this research to the clinic and clinical neuroscience in general. More specifically, the objective of Empenn is to propose new statistical and computational methods, and to measure and model morphological, structural and functional states of the brain to better diagnose, monitor and treat mental, neurological and substance use disorders. We propose to combine advanced instrumental devices and novel computational models to provide advanced diagnostic, therapeutic, and neurorehabilitation solutions for some of the major developing and aging brain disorders.
Generic and challenging research topics in this broad area include finding new ways to compare models and data, aid in decision making and interpretation, and develop feedback. These activities are carried out in close collaboration with the Neurinfo imaging platform in vivo, which is an essential environment for the experimental implementation of our research on ambitious clinical research projects and the development of new clinical applications.
Magnetic Resonance Imaging
Other modalities
Medical terminology
Methodological terminology
The scientific foundations of our team concern the design and development of new computational solutions for biological images, signals and measurements. Our goal is to develop a better understanding of the normal and pathological brain, at different scales.
This includes imaging brain pathologies in order to better understand pathological behavior from the organ level to the cellular level, and even to the molecular level (PET-MR imaging), and modeling of large groups of normal and pathological individuals (cohorts) from image descriptors. It also addresses the challenge of the discovery of episodic findings (i.e. rare events in large volumes of images and data), data mining and knowledge discovery from image descriptors, validation and certification of new drugs from imaging features, and, more generally, the integration of neuroimaging into neuroinformatics by promoting and supporting virtual organizations of biomedical actors using e-health technologies.
As shown in Figure 1, the research activities of the Empenn team closely link observations and models through the integration of clinical and multiscale data, and phenotypes (cellular, and later molecular, with structural or connectivity patterns in the first stage). Our ambition is to build personalized models of central nervous system organs and pathologies, and to compare these models with clinical research studies in order to establish a quantitative diagnosis, prevent the progression of diseases and provide new digital recovery strategies, while combining all these research areas with clinical validation. This approach is developed within a translational framework, where the data integration process to build the models is informed by specific clinical studies, and where the models are assessed regarding prospective clinical trials for diagnosis and therapy planning. All of these research activities are conducted in close collaboration with the Neurinfo platform, which benefited in 2018 from a new high-end 3T MRI system dedicated to research (3T Prisma™ system from Siemens), and through the development in the coming years of multimodal hybrid imaging (from the currently available EEG-MRI, to EEG-NIRS and PET-MRI in the future).
In this context, some of our major developments and newly arising issues and challenges include:
In terms of new major methodological challenges, we address the development of models and algorithms to reconstruct, analyze and transform the images, and to manage the mass of data to store, distribute and "semanticize" (i.e. provide a logical division of the model's components according to their meaning). As such, we expect to make methodological contributions in the fields of model inference; statistical analysis and modeling; the application of sparse representation (compressed sensing and dictionary learning) and machine learning (supervised/unsupervised classification and discrete model learning); data fusion (multimodal integration, registration, patch analysis, etc.); high-dimensional optimization; data integration; and brain-computer interfaces. As a team at the frontier between the digital sciences and clinical research in neuroscience, we do not claim to provide theoretical breakthroughs in these domains but rather to provide significant advances in using these algorithms through to the advanced applications we intend to address. In addition, we believe that by providing these significant advances using this set of algorithms, we will also contribute to exhibiting new theoretical problems that will fuel the domains of theoretical computer sciences and applied mathematics.
In summary, we expect to address the following major challenges:
These major advances are primarily developed and validated in the context of several priority applications in which we expect to play a leading role: multiple sclerosis, stroke rehabilitation, and the study and treatment of depression.
Figure 2 summarizes the scientific organization of the research team through three basic research topics in information sciences (Population Imaging, Detection and Learning, and Quantitative Imaging) and three translational axes on central nervous system diseases (Behavior, Neuro-inflammation and Recovery).
One major objective of neuroimaging researchers and clinicians is to be able to stratify brain imaging data in order to derive new and more specific population models. In practice, this requires to set up large-scale experiments that, due to the lack of resources and capabilities to recruit locally subjects who meet specific inclusion criteria, motivates the need for sharing the load.
However, building and using multi-site large-scale resources pose specific challenges to deal with the huge quantity of data produced and their diversity. Empenn focuses on two challenges in particular:
We intend to make significant contributions with major impacts in learning coupling models between functional recordings during neurofeedback procedures. These advances will provide a breakthrough in brain-computer interfaces for rehabilitation protocols. Our aim is to:
The Empenn research group focuses on the development of several quantitative techniques in magnetic resonance imaging of the brain. These methods allow for characterization of both the function and the structure of the brain with high precision. Arterial spin labelling (ASL) is a contrast agent-free imaging technique which labels arterial blood water as an endogenous tracer for perfusion and can measure resting-state cerebral blood flow. We are interested in estimating multiparametric hemodynamics using ASL, such as combined cerebral blood flow and arterial transit times, and derive statistical descriptors to represent significant differences between groups. In addition to quantitative perfusion parameters, our contributions on tissue compartment imaging aim at delineating neural circuits and characterize their microstructure properties, using both diffusion MRI and relaxometry. In diffusion MRI, arbitrary gradient waveforms were shown to exhibit higher sensitivity to microstructure parameters than standard pulsed gradients. We work on the optimization of sampling protocols in this domain, with the objective to propose sequences compatible with in vivo acquisition. Complementary to diffusion MRI, we develop methods for the reconstruction of myelin-bound, extra-axonal and cerebrospinal fluid water using multi-compartment modelling of the T2-relaxometry signal. We combine these techniques with tractography to identify trajectories of pathologies associated to the evolution of these microstructural parameters along specific fiber bundles in the brain white matter.
Advances in the field of in vivo imaging offer new opportunities for addressing the management of resistant affective disorders and their consequences (suicide risk and socio-professional impact), and the management of spatial cognition disorders after stroke and their consequences (postural perturbations and the loss of autonomy). Our objective, and the main challenge in this context, is to introduce medical image computing methods to the multidisciplinary field of behavioral disorders (cognitive disorders, particularly spatial and postural control disorders or anterograde memory impairment, mood disorders, notably resistant depression, schizophrenic disorders, pervasive developmental disorders, attention disorders, etc.) in order to gain a better understanding of the pathology and devise innovative therapeutic approaches.
We also expect to become a major player in the future and make important contributions with significant impacts, primarily in drug-resistant depression in young and old populations. In particular, we expect to provide new image-related metrics combining perfusion, metabolism and microstructural information regarding the brain in order to better characterize pathologies, provide prospective evolution values and potentially provide new brain stimulation targets that could be used in neurofeedback rehabilitation protocols or other types of brain stimulation procedures.
We aim to provide new imaging markers of mental diseases, especially in the context of mood disorders. The new biomarkers are derived from the metabolic (ASL and later ASL+PET) point of view as well as from the microstructural point of view (multicompartment diffusion MRI and relaxometry). Similarly, we expect to exhibit imaging biomarker regularities combining metabolic and structural information. Over the longer term, we expect these biomarkers to be the target of neurofeedback rehabilitation procedures. Also, over the longer term, we expect to supplement the MRI markers with molecular markers coming from new PET tracers, especially those associated with serotonin intake, at one time point or during a rehabilitation protocol under hybrid PET-EEG-MRI neurofeedback procedures.
Some of the major ongoing research issues regarding neuroimaging of neuro-inflammatory diseases concern the definition of new biomarkers to track the development of the pathology using high- dimensional data (e.g. nD+t MRI). This includes the use of white matter-specific imaging, such as magnetization transfer MRI, relaxometry and diffusion-weighted imaging (DW-MRI). Our objective is (1) to develop information-processing tools to tag the spatiotemporal evolutions of Multiple Sclerosis patterns at the brain parenchyma and spinal cord levels from their different signatures (inflammatory cells visible with USPIO or Gd contrast agents on MRI, persistent black holes, eloquent regional atrophy and microstructure signatures); and (2) to test these new tools on new imaging cohorts. In this respect, we for instance conduct studies on brain and spinal cord imaging, continuing on from the PHRC multicentric EMISEP project (PI: G. Edan), as it is very likely that lesions in the spine will directly affect the ambulatory ability of the patient (and thereby the clinical scores). In order to extend this experiment to a larger MS population, based on our expertise from the OFSEP cohort, we also plan to improve the MS therapeutic decision process through the MUSIC project (Multiple Sclerosis Imaging Check out, a public/private project) and, notably, the RHU PRIMUS project. Our goal is to develop and assess a standardized monitoring tool that provides a robust, long-term computerized MRI follow-up that will become the gold standard in clinical practice for therapeutic decisions in MS treatment. As part of this project, Empenn will share its expertise in data management systems (Shanoir and FLI-IAM) and automatic processing tools (through the medInria and Anima software repositories) to extract quantitative indices from the images.
Mental and neurological disorders are the leading cause of years lived with a disability. Treatment-resistant depression affects approximately 2% of the European population. Meanwhile, in the case of brain disorders, almost 1.5 million Europeans (15 million people worldwide) suffer a stroke event each year. Current recovery methods for brain disorders and traumatic brain injuries remain limited, preventing many from achieving full recuperation. We propose to address the issue of brain recovery by introducing new advances from recent breakthroughs in computational medical imaging, data processing and human-machine interfaces, and demonstrate how these new concepts can be used, in particular for the treatment of stroke and major depressive disorders.
We ambition to combine advanced instrumental devices (hybrid EEG, NIRS and MRI platforms), with new hybrid brain computer interface paradigms and new computational models to provide neurofeedback-based therapeutic and neuro-rehabilitation paradigms in some of the major mental and neurological disorders of the developmental and aging brain.
Neurofeedback involves using a brain-computer interface that provides an individual with real-time biofeedback about his or her brain activity in the form of sensory feedback. It enables individuals to learn to better control their brain activity, which can be measured in real time using various non-invasive sensors as described above. Although EEG is currently the only modality used by clinical practitioners in that context, it lacks specificity due to its low spatial resolution. Dynamic research into fMRI-neurofeedback has held promise for treating depression, chronic pain and stroke, since it offers the prospect of real-time imagery of the activity in deep brain structures with high spatial resolution. However, the low temporal resolution and high cost of fMRI-neurofeedback has hampered the development of many applications. We believe that the future belongs to hybrid responses that combine multimodal sensors and intend to demonstrate this in the Empenn project.
Shanoir-NG (SHAring NeurOImaging Resources - Next Generation) is an open-source web platform designed to share, archive, search and visualize medical imaging data. "Next Generation" stands for a complete technological remake released in 2020 with a new technical architecture based on microservices. It provides a user-friendly secure web access and offers an intuitive workflow to facilitate the collecting and retrieving of imaging data from multiple sources. It supports the following formats: DICOM classic/enhanced (MR, CT, PT, NM), BIDS, processed datasets (NIfTI), Bruker, EEG(BrainVision/EDF).
Shanoir-NG comes along many features such as pseudonymization of data (based on standard profiles), support for multi-centric clinical studies on subjects or group of subjects. Shanoir-NG offers an ontology-based data organization (OntoNeuroLOG). Among other things, this facilitates the reuse of data and metadata, the integration of processed data and provides traceability trough an evolutionary approach. Shanoir-NG allows researchers, clinicians, PhD students and engineers to undertake quality research projects with an emphasis on remote collaboration.
Empenn is the founding actor of an experimental research platform which was installed in August 2009 at the University Hospital of Rennes. The University of Rennes 1, Inria, CNRS for the academic side, and the University Hospital of Rennes and the Cancer Institute "Eugene Marquis" for the clinical side, are partners of this neuroinformatics platform called Neurinfo (
Neurinfo website). Concerning the Neurinfo Platform, the activity domain is a continuum between methodological and technological research built around specific clinical research projects. On the medical field, the translational research domain mainly concerns medical imaging and more specifically the clinical neurosciences. Among them are multiple sclerosis, epilepsy, neurodegenerative, neurodevelopmental and psychiatric diseases, surgical procedures of brain lesions, neuro-oncology and radiotherapy planning. Beyond these central nervous system applications, the platform is also open to alternative applications. Neurinfo ambitions to support the emergence of research projects based on their level of innovation, their pluri-disciplinarity and their ability to foster collaborations between different actors (public and private research entities, different medical specialties, different scientific profiles). In this context, a research 3T MRI system (Siemens Verio) was acquired in summer 2009 in order to develop the clinical research in the domain of morphological, functional, structural and cellular in-vivo imaging. A new 3T Siemens Prisma MRI scanner was installed at the Neuroinfo platform in February 2018. In 2014, an equipment for simultaneous recording of EEG and MRI images was acquired from Brain Product. In 2015, a mock scanner for experimental set-up was acquired as well as a High Performance Computing environment made of one large computing cluster and a data center that is shared and operated by the Inria center and IRISA (UMR CNRS 6074). The computation cluster (480 cores) and the data center (up to 150 TB) are dedicated to host and process imaging data produced by the Neurinfo platform, but also by other research partners that share their protocols on the Neurinfo neuroinformatics system (currently more than 60 sites). In 2019, an MRI and EEG-compatible fNIRS system was acquired through a co-funding from the INS2I institute of CNRS and FEDER. At the end of 2019, GIS IBISA awarded the Neurinfo platform with a complementary funding that will be dedicated to supplement the current system with additional sensors (from 8x8 optodes to 16x16 optodes). In 2022, the Regional Council of Britanny funding was renewed to provide engineer support for another year to develop and integrate this new imaging system.
Population imaging is fundamental when it comes to evaluate clinical biomarkers. In this section we summarise our contributions over the last year to this theme. We studied how analytical variability can impact fMRI results and proposed recommendations and neuroinformatics models to describe the data. We also maintained our clinical interest regarding several pathologies by exploring brain function and connectivity. Also, technical recommendations regarding multicentric imaging protocols were proposed.
In recent years, the lack of reproducibility of research findings has become an important source of concerns in many scientific fields, including functional Magnetic Resonance Imaging (fMRI). The low statistical power often observed in fMRI studies was identified as one of the leading causes of irreproducibility. The development of data sharing in the field of neuroimaging opens up new opportunities to achieve larger sample sizes by reusing existing data. FMRI studies use subject data processed with pipelines, and although most shared datasets currently include raw data, we may expect to see an increasing proportion of processed data among shared subject data in the future, for privacy and sustainability reasons. Pipelines consist of multiple steps, each with multiple possible methodological choices: this existing variability in terms of processing and analysis (analytical variability) has an impact on the results. We investigated the impact of analytical variability when combining subject data processed differently in between-group analyses. We created a set of pipelines for subject-level processing that we applied on data from the Human Connectome Project (n=1080). We then performed between-group analyses with subject data processed with different pipelines, under the null hypothesis (making any detection a false positive) using two different software packages: SPM and FSL. We compared the estimated false positive rates obtained to the nominal false positive rate. We found that the analytical variability induced by the studied parameters was found to be acceptable for some of these analyses and redhibitory for others. We concluded that different processed subject data cannot be combined without taking into account the processing applied on these data. Associated publication: 38.
Neuroimaging workflows are highly flexible leaving researchers with many possible choices at each step of their analysis. Recents studies have demonstrated how different analytical choices can substantially impact neuroimaging results, effectively leading to a "vibration of effects". This observation is not limited to brain imaging and was also made across many scientific fields. In psychology, Klau et al., 2020 showed that the vibration of effects decreases and stabilizes as sample sizes increase. We built on the results of Botvinik-Nezer et al., 2020, in which a functional Magnetic Resonance Imaging (fMRI) "many analyst" study was conducted with 70 teams. In this study, each team used their favorite pipeline to analyze the same dataset and answer 9 pre-defined hypotheses. After reproducing the pipelines used by 4 teams, we observe the impact of varying sample sizes on the vibration of effects. Using descriptions provided in the original study, we reproduced the SPM pipelines of 4 teams and replicated the results of each pipeline with different subset of participants and with the full dataset. Our findings show that, in fMRI data analysis, the vibration of effects decreases with sample size. Our results also suggest that some variability remains even for large sample sizes. Further work will be needed in order to include more pipelines and investigate which part of the pipelines are the most impactful. Associated publication:
We study the benefits of using a large public neuroimaging database composed of fMRI statistic maps, in a self-taught learning framework, for improving brain decoding on new tasks. First, we leverage the NeuroVault database to train, on a selection of relevant statistic maps, a convolutional autoencoder to reconstruct these maps. Then, we use this trained encoder to initialize a supervised convolutional neural network to classify tasks or cognitive processes of unseen statistic maps from large collections of the NeuroVault database. We show that such a self-taught learning process always improves the performance of the classifiers but the magnitude of the benefits strongly depends on the number of samples available both for pre-training and finetuning the models and on the complexity of the targeted downstream task. This work was co-supervised by Prof. Elisa Fromont from the LACODAM team. Associated publication:
The goal of the NARPS Open Pipelines Project is to provide a public codebase that reproduces the 70 pipelines chosen by the 70 teams of the NARPS study. The project is public and the code hosted on GitHub at
.This project initially emerged from the idea of creating an open repository of fMRI data analysis pipelines (as used by researchers in the field) with the broader goal to study and better understand the impact of analytical variability. NARPS – a many-analyst study in which 70 research teams were asked to analyze the same fMRI dataset with their favorite pipeline – was identified as an ideal usecase as it provides a large array of pipelines created by different labs. In addition, all teams in NARPS provided extensive (textual) description of their pipelines using the COBIDAS guidelines. All resulting statistic maps were shared on NeuroVault and can be used to assess the success of the reproductions. At the OHBM Brainhack 2022, our goal was to improve the accessibility and reusability of the database, to facilitate new contributions and to reproduce more pipelines. We focused our efforts on the first two goals. By trying to install the computing environment of the database, contributors provided feedback on the instructions and on specific issues they faced during the installation. Two major improvements were made for the download of the necessary data: the original fMRI dataset and the original results (statistic maps stored in NeuroVault) were added as submodules to the GitHub repository. Finally, propositions were made to facilitate contributions: the use of the Giraffe toolbox for people that are not familiar with NiPype and the creation of a standard template to reproduce a new pipeline. With these improvements, we hope that it will be easier for new people to contribute to reproduction of new pipelines and to grow the codebase.
As an active field of research and with the development of state-of-the-art algorithms to analyze EEG datasets, the parametrization of Electroencephalography (EEG) analysis workflows has become increasingly flexible and complex, with a great variety of methodological options and tools to be selected at each step. This high analytical flexibility can be problematic as it can yield to variability in research outcomes. Therefore, growing attention has been recently paid to understand the potential impact of different methodological decisions on the reproducibility of results. In this paper, we aim to examine how sensitive the results of EEG analyses are to variations in preprocessing with different software tools. We reanalyzed the shared EEG data (N=500) from (Williams et al. 2021) using three of the most commonly used EEG software tools: EEGLAB, Brainstorm and FieldTrip. After reproducing the same original preprocessing workflow in each software, the resulting evoked-related potentials (ERPs) were qualitatively and quantitatively compared in order to examine the degree of consistency/discrepancy between softwares. Our findings show a good degree of convergence in terms of the general profile of ERP waveforms, peak latencies and effect size estimates related to specific signal features. However, considerable variability was also observed in the magnitude of the absolute voltage observed with each software package as reflected by the similarity values and observed statistical differences at particular channels and time instants. In conclusion, we believe that this study provides valuable clues to better understand the impact of the software tool on the analysis of EEG results. This work was done in collaboration with Dr. Aya Kabbara and Dr. Mahmoud Hassan. Associated publication:
Empirical observations of how labs conduct research indicate that the adoption rate of open practices for transparent, reproducible, and collaborative science remains in its infancy. This is at odds with the overwhelming evidence for the necessity of these practices and their benefits for individual researchers, scientific progress, and society in general. To date, information required for implementing open science practices throughout the different steps of a research project is scattered among many different sources. Even experienced researchers in the topic find it hard to navigate the ecosystem of tools and to make sustainable choices. Here, we provide an integrated overview of community-developed resources that can support collaborative, open, and reproducible neuroimaging throughout the entire research cycle from inception to publication and across different neuroimaging modalities. We review tools and practices supporting study inception and planning, data acquisition, research data management, data processing and analysis, and research dissemination. We believe it will prove helpful for researchers and institutions to make a successful and sustainable move towards open and reproducible science and to eventually take an active role in its future development. This work was done as part of an international collaboration led by Drs. Guiomar Niso, Rotem Botvinik-Nezer and Jochem Rieger.
What are the standards for the reporting methods and results of fMRI studies, and how have they evolved over the years? To answer this question we reviewed 160 papers published between 2004 and 2019. Reporting styles for methods and results of fMRI studies can differ greatly between published studies. However, adequate reporting is essential for the comprehension, replication and reuse of the study (for instance in a meta-analysis). To aid authors in reporting the methods and results of their task-based fMRI study the COBIDAS report was published in 2016, which provides researchers with clear guidelines on how to report the design, acquisition, preprocessing, statistical analysis and results (including data sharing) of fMRI studies (Nichols et al. in Best Practices in Data Analysis and Sharing in Neuroimaging using fMRI, 2016). In the past reviews have been published that evaluate how fMRI methods are reported based on the 2008 guidelines, but they did not focus on how task based fMRI results are reported. This review updates reporting practices of fMRI methods, and adds an extra focus on how fMRI results are reported. We discuss reporting practices about the design stage, specific participant characteristics, scanner characteristics, data processing methods, data analysis methods and reported results. This work was part as a collaboration during the PhD thesis of Freya Acar from Uni. Ghent, co-supervised by Drs. Ruth Seurinck and Beatrijs Moerkerke. Associated publication:
Online atlasing, i.e., incrementing an atlas with new images as they are acquired, is key when performing studies on very large, or still being gathered, databases. Regular approaches to atlasing however do not focus on this aspect and impose a complete reconstruction of the atlas when adding images. We propose instead a diffeomorphic online atlasing method that allows gradual updates to an atlas. In this iterative centroid approach, we integrate new subjects in the atlas in an iterative manner, gradually moving the centroid of the images towards its final position. This leads to a computationally cheap approach since it only necessitates one additional registration per new subject added. We validate our approach on several experiments with three main goals: 1- to evaluate atlas image quality of the obtained atlases with sharpness and overlap measures, 2- to assess the deviation in terms of transformations with respect to a conventional atlasing method and 3- to compare its computational time with regular approaches of the literature. We demonstrate that the transformations divergence with respect to a state-of-the-art atlas construction method is small and reaches a plateau, that the two construction methods have the same ability to map subject homologous regions onto a common space and produce images of equivalent quality. The computational time of our approach is also drastically reduced for regular updates. Finally, we also present a direct extension of our method to update spatio-temporal atlases, especially useful for developmental studies. Associated publication:
We studied the ability and reproducibility of fNIRS to map the cortical motor areas. Simultaneously acquired fMRI was used as a reference and functional maps of both modalities were obtained from GLM analysis. NIRS results shows satisfactory reproducibility but partial agreement with fMRI
In this section, we summarize our contributions that focus on information extraction from medical imaging data. Machine learning methods have been proposed to detect brain abnormalities, in order to assist and improve the quality of a diagnosis. We also contributed to the field of bimodal EEG-fMRI neurofeedback, crucial for a better understanding of brain mechanism.
Multiple sclerosis (MS) patients often present hyper-intense T2-w lesions in the spinal cord. The severe imbalance between background and lesion classes poses a major challenge to Deep Learning segmentation approaches, requiring for ad hoc strategies. Careful selection of the loss function and adjustment of the conventional 0.5-thresholding may help mitigating this issue. Our results show the performance advantages of loss functions based on the Tversky Index and the benefits of threshold tuning over more standard settings and the state-of-the-art model for MS lesion segmentation on spinal cord MRI. Associated publication:
Stroke is one of the leading causes of long-term adult disability worldwide. Post-stroke rehabilitation is crucial for long-term patient recovery. Determining the volume and location of lesions caused by stroke is essential to guide treatment and provide effective rehabilitation. Currently, the gold standard for chronic stroke lesion segmentation is manual tracing, a procedure that requires knowledge, is time consuming and prone to inter‐rater variability. Automatic segmentation algorithms have the potential to overcome these limitations. While a large number of solutions have been proposed for the automatic segmentation of lesions in the acute phase, tools for chronic stroke lesion segmentation are underdeveloped. Methods for acute stroke are not readily applicable to chronic stroke due to the different characteristics of the imaging protocol and of the lesion itself. In the context of an M1 internship, promising results have been obtained by adapting, training, and validating a fully convolutional neural network on a public dataset (ATLAS). Further validation and optimisation on a private annotated dataset is currently underway.
The incomplete hippocampal inversion (IHI) is an atypical anatomical pattern of the hippocampus. However, the hippocampus is not a homogeneous structure, as it consists of segregated subfields with specific characteristics. While IHI is not related to whole hippocampal volume, higher IHI scores have been associated to smaller CA1 in aging. Although the segmentation of hippocampal subfields is challenging due to their small size, there are algorithms allowing their automatic segmentation. By using a Human Connectome Project dataset of healthy young adults, we first tested the inter-reliability of two methods for automatic segmentation of hippocampal subfields, and secondly, we explored the relationship between IHI and subfield volumes. Results evidenced strong correlations between volumes obtained thorough both segmentation methods. Furthermore, higher IHI scores were associated to bigger subiculum and smaller CA1 volumes. Here, we provide new insights regarding IHI subfields volumetry, and we offer support for automatic segmentation inter-method reliability.
In the context of neurofeedback (NF), simultaneous acquisitions with electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) provide more effective NF training due to their complementarity. However, the use of MRI is expensive and draining for a subject. Therefore, we would like to reduce its use. We propose a method based on a recurrent neural network that consists in learning a model from simultaneous EEG-fMRI acquisitions to predict NF-fMRI scores with EEG signals alone. Associated publication:
Quantitative imaging is essential for an accurate and specific characterisation of tissue integrity or neural activity, among others. We contributed to methods in fiber tractography, and specifically tractograms evaluation measures.
Evaluation and comparison of tractograms are crucial and open problems that need to be solved in order to evaluate the false positives rate and variability of tractography algorithms. In this context, a lot of measures have been developed and are typically used to judge the quality of a tractogram. They however do not rely on the same quantities extracted from the tractograms to compare and may thus not evaluate the same aspects of tractogram quality. To evaluate this aspect and the measures redundancy or complementarity, we perform a quantitative analysis of the most common ones, both on simulated data and in real circumstances. We also propose a new evaluation measure based on optimal transport theory. We show that, when used in conjunction, these measures can provide a more in depth comparison of tractograms and thus a more complete evaluation. Associated publication:
Our goal is also to provide new computational solutions for our target clinical applications (Alzheimer's disease, psychiatry, neurology or public health issues), allowing a more appropriate representation of the data for image analysis and detection of specific biomarkers. In this section, we present the contributions of the last year in the clinical applications of behavior and neuro-inflammation.
Mood depressive disorder (MDD) affects the emotional state as expressed as a persistent feeling of sadness and loss of interest. Antidepressant medications are first line treatment for depression. In this work, we propose to identify patterns of MDD via a cross-sectional cohort, with the assumption that alterations in brain connectivity may constitute a sensitive biomarker of depression and more specifically of poor outcome of a mood depressive episode. Using diffusion magnetic resonance imaging, we performed structural connectivity analyses using graph theory approach on a cohort of depressed patients and healthy volunteers. In order to study illness improvement, the MDD patients went through two clinical interviews at baseline and at 6 months follow-up, thus allowing us to classify them into "responders" (R) or "non-responders" (NR) based on the Clinical Global Impression-Improvement score. First, the threshold-free network-based statistics (TFNBS) was conducted to highlight the graph modifications between the different groups. Second, we performed a statistical analysis of topological metrics tests between depressed patients versus healthy controls and between R versus NR.
Major depression is a leading cause of disability due to its trend to recurrence and treatment resistance. Currently, there are no biomarkers which could potentially identify patients with risk of treatment resistance. In this original paper, we propose a two-level shape analysis of the white matter bundles based on the Large Diffeomorphic Deformation Metric Mapping framework, to study treatment resistant depression. Fiber bundles are characterised via the deformation of their center line from a centroid shape. We developed two statistical analyses at a global and a local level to identify the most relevant bundles related to treatment resistant depression. Using a prospective longitudinal cohort including 63 patients. We applied this approach at baseline on 50 white matter fiber-tracts, to predict the clinical improvement at 6 months. Our results show a strong association between three bundles and the clinical improvement 6 months after. More precisely, the rightsided thalamo-occipital fascicle and optic radiations are the most robust followed by the splenium. The present study shows the interest in considering white matter shape in the context of depression, contributing to improve our understanding of neurobiological process of treatment resistance depression. Associated publication:
Major depressive disorder (MDD) is a disease widespread all over the world associated with a large and increasing economic, societal, and personal burden. Yet, the pathophysiology underlying MDD is not well understood, and rates of either non-response to treatment or MDD recurrence remain high. Many studies have already demonstrated impaired WM integrity, which corresponds to a FA decrease in the patient group compared to control subjects, with significant results found in several brain regions. Yet, the comparison between treatment-resistant and non-treatment-resistant populations has never been addressed. The FA at the voxel level provided by the classic diffusion tensor imaging (DTI) does not accurately describe the underlying microstructure. We propose a tract-based pipeline analysis using multi-compartment models (MCM) that allows to model water diffusion under the voxel resolution.
Studies comparing children with and without a traumatic brain injury (TBI) have shown that pediatric TBI is associated with difficulties in a large range of functional domains, including emotion and behavior (Catroppa et al., 2015), as well as with changes in brain morphometry (King et al., 2019). However, whether these differences already existed before the injury remains an unsolved question. The large population-based Adolescent Brain Cognitive Development (ABCD) Study (Casey et al., 2018) provides a rare opportunity to explore it. This pre-post design study aims to examine changes in emotional and behavioral problems, and brain morphometry following pediatric mTBI. Given its exploratory nature, no a priori hypothesis is formulated. The following baseline and 2-year follow-up data from the ABCD 4.0 curated data release will be used: 1) The Parent Ohio State TBI Screen-Short Modified report (Bogner et al., 2017) to identify children with no-TBI (n=6,394; baseline mean age = 9.9years; 3102 girls) and children who sustained a mild TBI between baseline and 2-year follow-up (n=132; baseline mean age = 9.9years; 58 girls); 2) The syndrome scales of the Child Behavior Checklist (Achenbach & Rescorla, 2000), and 3) Volumes and cortical thickness in 68 Desikan regions (Desikan et al., 2006) computed on T1-weighted images by the ABCD group. Scanner effects will be removed before analyses using longitudinal ComBat (Beer et al., 2020). Sex and parental education will be included as covariates. Multigroup latent change score models will be constructed with the lavaan 0.6-8 package (Rosseel, 2012) to estimate latent difference scores between baseline and follow-up for child behavior and brain structure. Group differences in 4 parameters of interest (mean of the baseline score, rate of change over time, and variances of the baseline and of the change) will be tested using chi-square difference tests (Kievit et al., 2018). Associated publication:
Although alcohol advertising content regulation has been adopted in many countries, its effects remain under-investigated. The IMAJ project is a multidisciplinary collaboration involving different research groups in Rennes. First results, focusing on the effect of ad content on the reward circuit showed significant increase in activation in the fusiform gyrus, the amygdala, the medial and lateral orbito frontal cortex, caudate nucleus and hippocampus when participants were exposed to attractive ad contents for alcohol brands compared to informative ones. Focusing the analysis on the effect of warnings show that image based warnings reduce activation in the reward circuit. The changes in activations in brain areas linked to emotions and the reward system plead for regulation of alcohol ad contents.
Impaired memory is a hallmark of prodromal Alzheimer's disease (AD). Prior knowledge associated with the memoranda improves memory in healthy individuals, but we ignore whether the same occurs in early AD. We used functional MRI to investigate whether prior knowledge enhances memory encoding in early AD, and whether the nature of this prior knowledge matters. Patients with early AD and Controls underwent a task-based fMRI experiment where they learned face-scene associations. Famous faces carried pre-experimental knowledge (PEK), while unknown faces with which participants were familiarized prior to learning carried experimental knowledge (EK). Surprisingly, PEK strongly enhanced subsequent memory in healthy controls, but importantly not in patients. Partly nonoverlapping brain networks supported PEK vs. EK associative encoding in healthy controls. No such networks were identified in patients. In addition, patients displayed impaired activation in a right sub hippocampal region where activity predicted successful associative memory formation for PEK stimuli. Despite the limited sample sizes of this study, these findings suggest that the role prior knowledge in new learning might have been so far overlooked and underestimated in AD patients. Prior knowledge may drive critical differences in the way healthy elderly and early AD patients learn novel associations. Associated publication:
Background The search of biomarkers in the field of depression requires easy implementable tests that are biologically rooted. Qualitative analysis of verbal fluency tests (VFT) are good candidates, but its cerebral correlates are unknown. Methods We collected qualitative semantic and phonemic VFT scores along with grey and white matter anatomical MRI of depressed (n = 26) and healthy controls (HC, n = 25) women. Qualitative VFT variables are the "clustering score" (i.e. the ability to produce words within subcategories) and the "switching score" (i.e. the ability to switch between clusters). The clustering and switching scores were automatically calculated using a data-driven approach. Brain measures were cortical thickness (CT) and fractional anisotropy (FA). We tested for associations between CT, FA and qualitative VFT variables within each group. Results Patients had reduced switching VFT scores compared to HC. Thicker cortex was associated with better switching score in semantic VFT bilaterally in the frontal (superior, rostral middle and inferior gyri), parietal (inferior parietal lobule including the supramarginal gyri), temporal (transverse and fusiform gyri) and occipital (lingual gyri) lobes in the depressed group. Positive association between FA and the switching score in semantic VFT was retrieved in depressed patients within the corpus callosum, right inferior fronto-occipital fasciculus, right superior longitudinal fasciculus extending to the anterior thalamic radiation (all p < 0.05, corrected). Conclusion Together, these results suggest that automatic qualitative VFT scores are associated with brain anatomy and reinforce its potential use as a surrogate for depression cerebral bases. Associated publication:
Emotional eating is commonly defined as the tendency to (over)eat in response to emotion. Insofar as it involves the (over) consumption of high-calorie palatable foods, emotional eating is a maladaptive behavior that can lead to eating disorders, and ultimately to metabolic disorders and obesity. Emotional eating is associated with eating disorder subtypes and with abnormalities in emotion processing at a behavioral level. However, not enough is known about the neural pathways involved in both emotion processing and food intake. In this review, we provide an overview of recent neuroimaging studies, highlighting the brain correlates between emotions and eating behavior that may be involved in emotional eating. Interaction between neural and neuro-endocrine pathways (HPA axis) may be involved. In addition to behavioral interventions, there is a need for a holistic approach encompassing both neural and physiological levels to prevent emotional eating. Based on recent imaging, this review indicates that more attention should be paid to prefrontal areas, the insular and orbitofrontal cortices, and reward pathways, in addition to regions that play a major role in both the cognitive control of emotions and eating behavior. Identifying these brain regions could allow for neuromodulation interventions, including neurofeedback training, which deserves further investigation. Associated publication:
The way different food consumption habits in healthy normal-weight individuals can shape their emotional and cognitive relationship with food and further disease susceptibility has been poorly investigated. Documenting the individual consumption of Western-type foods (i.e., high-calorie, sweet, fatty, and/or salty) in relation to psychological traits and brain responses to food-related situations can shed light on the early neurocognitive susceptibility to further diseases and disorders. We aimed to explore the relationship between eating habits, psychological components of eating, and brain responses as measured by blood oxygen level-dependent functional magnetic resonance imaging (fMRI) during a cognitive food choice task and using functional connectivity (FC) during resting-state fMRI (rsfMRI) in a population of 50 healthy normal-weight young women. A Food Consumption Frequency Questionnaire (FCFQ) was used to classify them on the basis of their eating habits and preferences by principal component analysis (PCA). Based on the PCA, we defined two eating habit profiles, namely, prudent-type consumers (PTc, N = 25) and Western-type consumers (WTc, N = 25), i.e., low and high consumers of western diet (WD) foods, respectively. The first two PCA dimensions, PCA1 and PCA2, were associated with different psychological components of eating and brain responses in regions involved in reward and motivation (striatum), hedonic evaluation (orbitofrontal cortex, OFC), decision conflict (anterior cingulate cortex, ACC), and cognitive control of eating (prefrontal cortex). PCA1 was inversely correlated with the FC between the right nucleus accumbens and the left lateral OFC, while PCA2 was inversely correlated with the FC between the right insula and the ACC. Our results suggest that, among a healthy population, distinct eating profiles can be detected, with specific correlates in the psychological components of eating behavior, which are also related to a modulation in the reward and motivation system during food choices. We could detect different patterns in brain functioning at rest, with reduced connectivity between the reward system and the frontal brain region in Western-type food consumers, which might be considered as an initial change toward ongoing modified cortico-striatal control. Associated publication:
The anatomical substrate of motor disability in MS patients is not fully understood. Studying the distribution of corticospinal tracts (CST) lesions per side, from the brain to the end of the thoracic spinal cord (SC) could provide a better association with patient motor deficits evaluated per limb. Objectives: i) To describe lesion preferential location along the CST; ii) To investigate the association between CST lesions and motor functional consequences, as measured using the EDSS, and the ASIA motor scores and electrophysiology (Central motor conduction time (CMCT)) per limb. Methods: 21 relapsing remitting MS (median EDSS=2.5) and 9 progressive MS patients (median EDSS=5.2) with clinical pyramidal symptoms were scanned on a 3T Siemens MRI scanner. White matter lesions were segmented on 3D FLAIR for the brain, on T2* for cervical SC and T2 for thoracic SC. For each patient, registration to an atlas was computed using Anima and SCT toolboxes. Lesion volume fraction along the CST (defined as "lesion volume along the CST"/"overall CST volume") was calculated separately for the both sides on 3 regions: brain including brainstem, C1 to C7 (C1C7) and T1 to T10 (T1T10). Finally, the relationships between lesion volume fraction and the associated lateralized disability scores were assessed using multiple linear models, adjusting for age and disease duration. Results: In MS patients, lesion volume fraction was higher in the C1C7 portion compared to the brain and T1T10 portion (all p's<.001; mean=2%, 10% and 2%, for brain, C1C7 and T1T10, resp). No evidence of correlation was found between lateralized lesion volume fraction in each portion of the CST and EDSS score or ASIA score per limb, except for a mild correlation between EDSS and lesion volume fraction on the right CST (standardized beta=.39, p=.041). We observed strong positive associations between lesion volume fraction in C1C7 and CMCT for superior and inferior limbs on the right side and for superior limbs on the left side (all std-beta>.6; all p's<.005). Finally, we observed a mild positive association between lesion volume fraction in T1T10 and CMCT for inferior limbs on the left side (std-beta=.53; p=.02). Conclusions: CST damage is not homogeneous along the tract and predominates in the cervical portion. It has clear consequences on motor conduction velocities measured using electrophysiology. Future work will include an assessment of lesion severity to better explain lesion consequences on motor disability. Associated publication:
Magnetization transfer ratio (MTR) has shown promise to assess tissue microstructure modification in MS patients. To date, such exploration has been limited to the brain and the cervical spinal cord (SC) portions of the central nervous system (CNS). Studying the MTR abnormalities in the whole SC could provide a better association with ambulatory disability in MS patients. The objectives are i) to compare mean MTR values in MS patients and healthy controls (HC) according to the SC level; ii ) to describe the link between MTR measurements at the cervical and thoracic SC levels; iii) to evaluate the link between MTR measures and disability according to the spinal cord level. For that purpose, 21 relapsing remitting MS (RRMS; median EDSS=2.5), 10 progressive MS patients (PMS; median EDSS=5.25) and 13 HC were scanned on a 3T Siemens MRI scanner. The imaging protocol included 3 MT imaging acquisition slabs to cover the whole SC. For each subject, MTR maps and vertebra labeling were computed using the SCT toolbox. MTR means were computed in semi-automatic delineated SC for the following vertebral levels: C4 to C6, T4 to T6, T9 to T10. Group differences as well as correlations with lesions in the whole SC and EDSS were assessed controlling for age. Evidence of group difference was only found in the cervical SC (C4C6; mean MTR=41.7pu, 39.4pu, 35.4pu for HC, RRMS and PMS resp.; p<.001). No evidence for group difference was found in the thoracic SC. A positive association was found between the mean MTR in the cervical SC and in the thoracic SC (r=.45, p=.01 for T4T6 and r=.54, p=.002 for T9T10) in MS patients. We observed negative associations between mean MTR in the cervical SC and the EDSS score (r=-.51, p=.004) and between mean MTR in the cervical SC and the SC lesion load (r=-.6, p<.001), while no clear evidence of correlation was found between SC lesion load and EDSS score (r=.35; p=.084). No evidence of correlation was found between mean MTR in the thoracic cord and EDSS score. To conclude, the microstructural damage in the SC of MS patients seems to be predominant in the cervical SC and is linked to the lesion load and the disability. In our sample data, the added value of exploring thoracic SC in addition to cervical SC using MTR to explain disability in MS patients seems limited. Potential explanations could be the presence of higher variabilities in MTR measurement in the thoracic SC or the preferential location of MS lesions in the cervical SC. Associated publication:
A collaboration between Siemens, Empenn and the Neurinfo platform is in place and formalized by a research contract. Thanks to this agreement, the Neurinfo platform has received the object code of MRI sequences under development at Siemens for evaluation in clinical research. In addition, the Neurinfo platform has received the source code of selected MRI sequences. As a result, MRI sequences can be developed on site by our team. For example, an MRI diffusion sequence was modified to load arbitrarly diffusion gradient waveforms for the FastMicroDiff project (led by E. Caruyer).
The GLIMR COST Action (PI: Esther Warnert, Erasmus MC, Netherlands) aims to build a pan-European and multidisciplinary network of international experts in glioma research, patient organisations, data scientists, and MR imaging scientists by uniting the glioma imaging community within Europe and progressing the development and application of advanced MR imaging for improved decision making in diagnosis, patient monitoring, and assessment of treatment response in clinical trials and clinical practice. Camille Maumet leads the work package "WG2 - Multi-site data integration" with Cyril Pernet (University of Edinburgh, UK). GliMR's first grant period ran from September 2019 to April 2020, during which several meetings were held and projects were initiated, such as reviewing the current knowledge on advanced MRI; developing a General Data Protection Regulation (GDPR) compliant consent form; and setting up the website. A publication led by Patricia Clement (Ghent University, Belgium) was published in 2021 describing the results of this GliMR's first grant period 14. The Action overcomes the pre-existing limitations of glioma research and is funded until September 2023. New members will be accepted during its entire duration.


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Crowdfunding is closer to reality!
Well, this just in from a dispatch on Capitol Hill: The Senate has passed legislation that will essentially legalize crowdfunding in startups by practically anyone, even your mom. U.S. Senators Scott Brown (R-Mass.), Jeff Merkley (D-Oreg.), and Michael Bennet (D-Colo.) collectively introduced the "CROWDFUND Act" (S. 2190) earlier this month, which adds measures to the House of Rep's now well-known JOBS Act to ensure that companies would be able to use SEC-approved crowdfunding platforms to raise money from "small-dollar investors."
While the CROWDFUND Act passed 73-26, and received bipartisan support, as one might expect when the potential for any old investor to enter the well-guarded circle of angel investing (especially in Silicon Valley) comes around, both the JOBS Act and the CROWDFUND Act have been controversial in the business community. Many worry that lowering the barriers to investing in startups could increase the amount of fraud inherent to the process.
With these dangers in mind, certain measures have been written into the bill to protect both startups and their non-accredit investors. Under the amended legislation, entrepreneurs will be able to raise up to $1 million per year through SEC-registered crowdfunding portals. The bill also limits the amount of money people can invest based on their income.
For example, investors with an income of less than $100K will be capped at 5 percent, or $2K investments, and those with incomes over $100K will be capped at 10 percent, or $10K. On top of that, the bill also requires crowdfunding sites to provide protection, including investor education materials that inform people to "the risks associated with small issuers and illiquidity."
Both bills have yet to be reconciled and signed, but support is reaching a new high, and the passage through the Senate is auspicious to say the least, especially as this marks the first time that crowdfunding legislation has ever been passed in the Senate.
Last week, Ryan Caldbeck, the founder of equity-based crowdfunding startup CircleUp, penned a guest post for TechCrunch talking about how the JOBS Act could "change startup investing forever." Caldbeck touches on the important point that, today, angel investing is generally reserved for about 1 percent of the population, and, in fact, less than 1 percent of small businesses receive outside equity investment.
The entrepreneur makes the argument that crowdfunding could "open up new funding possibilities for neglected areas of the economy," as crowdfunding investors will bring their own individual insights to growing consumer brands that are finding early traction. He gives the example of a baby food company that can now have 50 parents who know and trust the brand, and lend financial support to the company to help it achieve the next level of growth. With influencers and vocal representatives of small brands now able to invest their own money, they will likely be motivated to do even more in favor of the startup to help it grow.
Additionally, Caldbeck argues that the CROWDFUND Act's passage could bring a new level of transparency to the funding process, potentially doing away with the current process of private investor meetings, and bringing it into a wider community space where companies can share their information more broadly.
AngelList, for one, has been loud in its support of the JOBS Act, and today Co-founder Naval Ravikant said he thought the passage was a great thing for startups and investors and that he was very happy with the outcome.
Of course, on the other side, SEC Chairman Mary L. Schapiro has added her voice to the criticism of the JOBS Act, saying that it removes too many investor protections, and opens up the more vulnerable to "fraudulent schemes disguised as investment opportunities." The New York Times also published a snarky opinion piece that goes a long way to drive that point home.
Meanwhile, entrepreneurs across the board seem to be in favor, and crowdfunding sites are naturally in support, as the WSJ points out, a site called Crowdfunder already has $13.59 million committed to 925 founders and companies from 986 crowd-investors.
Original story by Rip Empson

subset: commoncrawl


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Fabrizio Romano has confirmed that Liverpool will be prioritising 'new midfielders' next year.
This update comes on Twitter with the Italian also reporting that Alex Oxlade-Chamberlain is expected to see his contract through to completion next summer.
Alex Oxlade-Chamberlain, expected to leave Liverpool in 2023 as free agent. There are no talks to extend his contract as things stand. 🚨🔴 #LFC
New midfielders will be the priority for Liverpool on the market next year. pic.twitter.com/PPIDhbFN6I
— Fabrizio Romano (@FabrizioRomano) November 20, 2022
Whether 'midfielders' specifically means two new options spread across as many windows, or three, remains to be seen, though it's clear that some serious recruitment will be required to address both the ageing midfield department and potentially as many as three exits in 2023 as contracts expire.
READ MORE: Manuel Neuer tells Liverpool target to join Bayern in latest presser
It's not necessarily groundbreaking news for those keeping a close eye on the club, though it's critical that we don't feel our current struggles can be fixed with just one midfield signing alone.
A transfer of Jude Bellingham's calibre would be significant for our fortunes over the course of the next decade or so, without question.
However, it has to be said that Fabinho's form in 2022/23 has highlighted the clear need for a new holding midfielder to provide competition and relieve our No.3 should his performances continue to be found wanting before the January window.
EOTK Insider: 🏆 Liverpool's Two World Cup Winners and 14 Finalists, ahead of Qatar


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Mowing Techniques for Stripes
When it comes to maintaining a beautiful and well-manicured lawn, mowing techniques play a crucial role. One popular technique that can enhance the visual appeal of your lawn is creating stripes. Stripes add a touch of elegance and professionalism to your lawn, making it stand out from the rest. In this article, we will explore the various mowing techniques for stripes and how you can achieve that perfect striped look for your lawn.
Choosing the Right Lawn Mower
The first step in achieving a striped lawn is choosing the right lawn mower. While any lawn mower can create stripes, certain types are more effective than others. The most common type of mower used for striping is a rotary mower with a rear roller. The roller flattens the grass in one direction, creating the desired stripe effect. It is important to ensure that the mower's blades are sharp and properly adjusted to achieve clean and crisp stripes.
Preparing the Lawn
Before you start mowing, it is essential to prepare your lawn properly. Remove any debris, such as sticks or stones, that may obstruct the mower's path. Trim the edges of the lawn using a string trimmer or edger to create a clean and defined border. Additionally, make sure the grass is at the right height for striping. Ideally, the grass should be around 2.5 to 3 inches tall for the best results.
Mowing Patterns
There are several mowing patterns you can use to create stripes on your lawn. The most common pattern is the straight stripe pattern, where you mow in straight lines from one end of the lawn to the other. This pattern is simple and creates a classic striped look. Another popular pattern is the checkerboard pattern, where you mow in alternating directions to create a grid-like effect. Experiment with different patterns to find the one that suits your lawn and personal preference.
Technique for Creating Stripes
To create stripes, you need to mow in a specific way. Start by mowing the perimeter of the lawn in a clockwise or counterclockwise direction, depending on your preference. This will create a border around the lawn. Next, choose a starting point in the middle of the lawn and mow in straight lines towards the border, slightly overlapping each pass. As you mow, the roller on the mower will flatten the grass in one direction, creating the desired stripe effect.
Maintaining the Stripes
Once you have achieved the desired striped look, it is important to maintain it. Regular mowing is essential to keep the stripes looking crisp and defined. Aim to mow your lawn once a week, or as needed, to prevent the grass from growing too tall and losing the striped effect. Additionally, make sure to alternate the direction of mowing each time to prevent the grass from leaning in one direction.
Benefits of Striped Lawns
Creating stripes on your lawn offers several benefits beyond the aesthetic appeal. Stripes can make your lawn appear larger and more spacious, giving it a grander look. They also create a sense of order and symmetry, making your lawn look well-maintained and cared for. Additionally, striped lawns can enhance the overall curb appeal of your property, increasing its value and making it more attractive to potential buyers.
Troubleshooting Common Issues
While mowing techniques for stripes are relatively straightforward, there are some common issues that you may encounter. One common problem is uneven striping, where the stripes appear wavy or inconsistent. This can be caused by uneven ground or improper mowing technique. To fix this issue, make sure to mow at a consistent speed and overlap each pass slightly. Another issue is grass clippings accumulating in the stripes, which can be resolved by using a grass catcher attachment or raking the clippings after mowing.
In conclusion, mowing techniques for stripes can transform an ordinary lawn into a visually stunning masterpiece. By choosing the right lawn mower, preparing the lawn properly, and using the correct mowing patterns and techniques, you can achieve that perfect striped look. Remember to maintain the stripes regularly and troubleshoot any issues that may arise. With a little practice and attention to detail, you can create a lawn that will be the envy of the neighborhood.


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Daisy Dukes 'n Cowboy Boots
"When big-city lawyer, Nolan Anderson, rolls into her small West Texas town, Ferina Kincaid goes into a tailspin of worry over losing her family's ranch. She knows he's been hired by town banker and long-time Kincaid nemesis, Lance Morrison, to bring havoc to her world. Morrison owns the land adjacent to Ferina's property and will stop at nothing to take what is rightfully hers, even if it means digging up the past and hurting innocent bystanders. Dishonest cowhands are cheap in Brewster County, and the banker has enough men and cash to outlast and ruin her with his dirty tricks and vandalism. Hiring Nolan is just the latest of Morrison's devious shenanigans, which have turned Kincaid Ranch upside-down, and—with more than just her land at stake—Ferina fears she's no match for this too-handsome, smooth-talking lawyer."
"A breezy romance that may appeal to fans of Jodi Thomas or Anna Schmidt."
—Kirkus Reviews
"The story is cute, funny, and heartwarming, with some nice spicy love scenes to top it all off. If you're into CHick Lit at all, you're going to lobe it!"
—Taylor Jones, Reviewer
"Daisy Dukes 'N Cowboy Boots is a charming, touching, and downright delightful story, filled with enchanting characters and hilarious situations—a thoroughly enjoyable read."
—Regan Murphy, Reviewer
Latest Blog
The Dixie Apocalypse, by Richard Fossey
In Richard Fossey's, The Dixie Apocalypse, it's not one disaster that strikes, leaving humanity in peril, but a lagnappe of misfortune that leaves the United States in ruins. In the new times, Willoughby Burns, a former lawyer and professor...
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Sometimes celebrities surprise us with unexpected airport outfits, like when Kate Beckinsale wore 6-inch platform boots or when Cate Blanchett traveled in a full three-piece suit. More often than not, however, celebrities wear relatable airport outfits that center around everyone's favorite shoes: sneakers.
Bella Hadid loves flying in her Converse Chuck Taylor All-Star High-Top Sneakers ($65), while Chloë Grace Moretz is partial to her Vans Old Skool Sneakers ($70). Kate Winslet has been photographed traveling in Superga sneakers, which happen to be a favorite of Kate Middleton's. Scroll down to shop other sneakers worn by Rihanna, Alessandra Ambrosio, and Emily Ratajkowski.


text:
Torquay youngsters pause and read to celebrate World Book Day
"Despite the lockdown, we have made sure pupils are encouraged to continue their reading and develop essential skills"
TEACHER Jake Jones found the perfect quiet spot to join his pupils for a 'pause and read' moment to celebrate World Book Day.
The Warberry Primary School teacher took his book and retreated up the ladder to the loft to find a peaceful spot to read.
It was all part of the Learning Academy Partnership's events to mark the big book day.
The primary academy trust, which supports schools across Devon through their trust and the acclaimed Ilsham English Hub, invited students to 'pause and read'.
Staff and pupils were encouraged to stop what they are doing and read for 10 minutes, and many of them also joined in with the usual tradition of dressing up as a beloved book character.
The 'home heroes' loved taking part remotely sharing their favourite books, dressing up as favourite book characters and reading in unusual places.
Mr Jones found a very quiet space at home for the 'pause and read'.
Pupils loved identifying the masked readers, reading in unusual places, sharing stories, listening to their favourite stories, recreating book covers and listening to 153 authors wishing them Happy World Book Day!
At Warberry in Torquay, they had virtual meetings with their classes to celebrate the joy of reading.
Children brought along their favourite books for book talk and an opportunity to recommend their home books to their friends.
They also had cosy story times with children joining meetings wearing their pyjamas whilst snuggled up in bed, ready to listen to their teacher sharing stories.
At Ellacombe in Torquay, the pupils took the characters from their favourite stories and transformed into potatoes.
Classes had online 'potato parties' where everyone bought along their decorated potato and had lots of fun trying to figure out which story characters the children had chosen to create.
Tracey Cleverly, interim chief executive of the trust, said: "World Book Day is always a date in the calendar we take full advantage of, and this year has been no different.
"Despite the lockdown, we have made sure pupils are encouraged to continue their reading and develop those essential skills they need for their learning.
"I have been delighted to see our staff grip this initiative and encourage our pupils to embrace the world of reading and literature, to grow their imagination and let their minds run free.
"We are committed to supporting our pupils, through our work in the trust, but also the English Hub, to deliver the very best outcomes for our pupils, and ensure they are avid readers and learners from the earliest ages."
Emma Bone, strategic lead for Ilsham English Hub, added: "During the most recent lockdown, where schools have been closed to many pupils, developing reading and sharing that love of books and literature has been at the forefront of our curriculum offer across the trust and is one of our key drivers as one of the national English Hubs.
"We are delighted to see so many pupils embracing World Book Day, and continue to excel in their reading and learning at this challenging time.
"I look forward to welcoming pupils back to school to continue engaging them with the wonderful work of reading."
Shine a spotlight on Torquay, Devon by becoming an Area Ambassador.


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image courtesy wikipedia
Villarreal have agreed to travel to Scotland to play Motherwell, a club based in North Lanarkshire, on August 2, 2008. The match will be a tribute to Phil O'Donnell, the Motherwell captain who collapsed and died during a match against Dundee United at the end of 2007. At the match, the main stand of Fir Park will be named for O'Donnell, and money raised at the match will go into an educational trust for his children. Should be an interesting match, and a good cause!
EDIT: This BBC story is in contrast to other reports that have the match against Zaragoza scheduled for August 2. I tend to trust the BBC, so perhaps the match in Teruel will be moved.


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Raze Collective is on the search for new ideas and new perspectives. Our artists development program Let Us Raze You is back for the second year and this time we are going bigger. More money, more support, more performance opportunity.
They are looking for 5 aspiring queer performance makers who have at least two year of experience to develop a 20min work in progress performance.
Find out more over on the Write A Play website.
Deadline: 6 April 2022
Source: Write A Play


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Royal Australian Air Force bases Curtin and Learmonth are set for major upgrades under construction approved by the Department of Defence.
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The Western Australian bases, outside Derby and Exmouth, respectively, are announced to receive upgraded runways, taxiways, parking areas, aeronautical ground lighting, asphalting, and the enhancement of culverts and drainage under construction anticipated to be completed in 2028.
CIMIC Group's CPB Contractors has been selected by the Australian government's Department of Defence to undertake the early contractor involvement development phase for the upgrades.
"CPB Contractors has successfully delivered upgrades at RAAF bases Pearce, Amberley, and Williamtown and will be applying this experience to ensure that normal operations continue without disruption while works are underway," according to CPB Contractors managing director Jason Spears.
Our teams will be supporting the participation of local industry in line with CPB Contractors' ongoing commitment to building industry capacity and capability through the delivery of major projects, including these two important Defence airbases."
The ECI phase will be completed in 2024.
CIMIC Group executive chairman Juan Santamaria said CPB Contractors will focus on safe and certain delivery of Defence's requirements for both bases.
"Our relationship with the Department of Defence stretches over decades and we are pleased to continue to be relied upon to deliver infrastructure upgrades for these vital airbases," he said.


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How To Negotiate Your Salary In The Netherlands
Expat News - Published date: .
One of the most common questions I get from my clients is, "How do I negotiate my salary in the Netherlands?" Who do... Read more
Top 3 Motivations For Hiring A Trainer, Coach Or Mentor
Expat News - Published date: .
You may have noticed that in the Netherlands every other person is a coach of some sort. A phenomenon that hardly exists... Read more
More Future-proof Skills To Safeguard Your Job In 2030
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This is the second part of the article which I wrote two months ago. In the first one, I talked about skills related to ... Read more


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MCQ Questions on Goodwill: Below, You will find a list of Commerce MCQ Questions as per the latest prescribed syllabus. Ace up your preparation with the Objective Questions available on Goodwill and enhance your subject knowledge. Understand the concept clearly by consistently practicing the Multiple Choice Questions and score well in your exams.
MCQ Questions on Goodwill
1. Goodwill is defined as
(a) Intangible asset
(b) Fictitious asset
(c) Current asset
(d) Liquid asset
Answer: (a)
2. Break-even indicates
(a) Revenues are more than cost
(b) Revenues and cost are equal
(c) Costs are more than revenue
(d) None of the Above
Answer: (b)
3. The excess amount which the firm can get on selling its assets over and above the saleable value of its assets is called
(a) Surplus
(b) Super Profit
(c) Reserve
(d) Goodwill
Answer: (d)
4. A firm's goodwill is not affected by
(a) Location of the firm
(b) The reputation of the Firm
(c) Better Customer Service
(d) None of the Above
Answer: (d)
5. Weighted average method of calculating goodwill is used when
(a) Profits are not equal
(b) Profits show a trend
(c) Profits are Fluctuating
(d) None of the Above
Answer: (b)
6. Under the capitalisation method, the formula for calculating the goodwill is
(a) Super profits multiplied by the rate of return
(b) Average profits multiplied by the rate of return
(c) Super profits divided by the rate of return
(d) Average profits divided by the rate of return
Answer: (c)
7. The total capital employed in the company is ₹8,00,000 a reasonable rate of return is 15% and the profit of the year is 412,00,000. The value of goodwill of the company as per the capitalization method will be
(a) ₹ 82,00,000
(b) ₹ 12,00,000
(c) ₹ 72,00,000
(d) ₹ 42,00,000
Answer: (c)
8. A firm earns ₹1,00,000. The normal rate of return is 10%. The assets of the company amounted to ₹11,00,000 and liabilities to ₹1,00,000. Value of goodwill by the capitalization of average actual profit will be
(a) ₹ 2,00,000
(b) ₹ 10,000
(c) ₹ 5,000
(d) ₹ 1,00,000
Answer: (d)
9. When there is a change in the current partners' association that results in ending the existing agreement and initiate a formation of a new agreement is known as
(a) Revaluation of Partnership
(b) Reconstitution of Partnership
(c) Realization of Partnership
(d) None of the Above
Answer: (b)
10. X, Y, and Z are partners in a company sharing profits in the ratio 4:3: 2. Their balance sheet as at 31-3-2016 showed a debit balance of Profit and Loss A/c ₹1,80,000. From 1-4-2016 they will share profits equally. In the journal entry to give effect to the above arrangement when X, Y, and Z decide not to close the profit and loss account.
(a) Dr X by ₹ 20,000, Cr Z by ₹20,000
(b) Cr X by ₹ 20,000, Dr Z by ₹20,000
(c) Dr X by ₹ 40,000, Cr Z by ₹40,000
(d) Cr X by ₹ 20,000, Dr Z by ₹20,000
Answer: (a)