349 research outputs found
Non-convex Global Minimization and False Discovery Rate Control for the TREX
The TREX is a recently introduced method for performing sparse
high-dimensional regression. Despite its statistical promise as an alternative
to the lasso, square-root lasso, and scaled lasso, the TREX is computationally
challenging in that it requires solving a non-convex optimization problem. This
paper shows a remarkable result: despite the non-convexity of the TREX problem,
there exists a polynomial-time algorithm that is guaranteed to find the global
minimum. This result adds the TREX to a very short list of non-convex
optimization problems that can be globally optimized (principal components
analysis being a famous example). After deriving and developing this new
approach, we demonstrate that (i) the ability of the preexisting TREX heuristic
to reach the global minimum is strongly dependent on the difficulty of the
underlying statistical problem, (ii) the new polynomial-time algorithm for TREX
permits a novel variable ranking and selection scheme, (iii) this scheme can be
incorporated into a rule that controls the false discovery rate (FDR) of
included features in the model. To achieve this last aim, we provide an
extension of the results of Barber & Candes (2015) to establish that the
knockoff filter framework can be applied to the TREX. This investigation thus
provides both a rare case study of a heuristic for non-convex optimization and
a novel way of exploiting non-convexity for statistical inference
Central nervous system neuronal surface antibody associated syndromes: review and guidelines for recognition
The concept of antibody mediated CNS disorders is relatively recent. The classical CNS paraneoplastic neurological syndromes are thought to be T cell mediated, and the onconeural antibodies merely biomarkers for the presence of the tumour. Thus it was thought that antibodies rarely, if ever, cause CNS disease. Over the past 10 years, identification of autoimmune forms of encephalitis with antibodies against neuronal surface antigens, particularly the voltage gated potassium channel complex proteins or the glutamate N-methyl-D-aspartate receptor, have shown that CNS disorders, often without associated tumours, can be antibody mediated and benefit from immunomodulatory therapies. The clinical spectrum of these diseases is not yet fully explored, there may be others yet to be discovered and some types of more common disorders (eg, epilepsy or psychosis) may prove to have an autoimmune basis. Here, the known conditions associated with neuronal surface antibodies are briefly reviewed, some general aspects of these syndromes are considered and guidelines that could help in the recognition of further disorders are suggested
Wie zuverlässig ist die Verwirklichung von Stichprobenverfahren? Random route versus Einwohnermeldeamtsstichprobe
Am Beispiel einer 1988 vom Deutschen Jugendinstitut durchgeführten Umfrage, bei der die Stichprobe einmal über eine Auswahl aus den Einwohnermeldeamtsdateien, zum anderen über ein random route-Verfahren gezogen wurde, wird die Repräsentativität beider Verfahren an den Ergebnissen des Mikrozensus getestet. Es wird ermittelt, daß die großen Abweichungen im random route-Verfahren auf die Manipulation der Interviewer bei der Auswahl der Interviewpartner zurückzuführen ist. Professionalität, d.h. die Durchführung einer weitaus höheren Zahl an Interviews als vorgegeben, führt zu höheren Manipulationseffekten. Die Einschränkung der Manipulationsmöglichkeiten durch Vorgabe der Zielpersonen verbessert dagegen die Qualität der Daten. (psz
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The importance of early immunotherapy in patients with faciobrachial dystonic seizures.
Faciobrachial dystonic seizures and limbic encephalitis closely associate with antibodies to leucine-rich glioma-inactivated 1 (LGI1). Here, we describe 103 consecutive patients with faciobrachial dystonic seizures and LGI1 antibodies to understand clinical, therapeutic and serological differences between those with and without cognitive impairment, and to determine whether cessation of faciobrachial dystonic seizures can prevent cognitive impairment. The 22/103 patients without cognitive impairment typically had normal brain MRI, EEGs and serum sodium levels (P < 0.0001). Overall, cessation of faciobrachial dystonic seizures with antiepileptic drugs alone occurred in only 9/89 (10%) patients. By contrast, 51% showed cessation of faciobrachial dystonic seizures 30 days after addition of immunotherapy (P < 0.0001), with earlier cessation in cognitively normal patients (P = 0.038). Indeed, expedited immunotherapy (P = 0.031) and normal cognition (P = 0.0014) also predicted reduced disability at 24 months. Furthermore, of 80 patients with faciobrachial dystonic seizures as their initial feature, 56% developed cognitive impairment after 90 days of active faciobrachial dystonic seizures. Whereas only one patient developed cognitive impairment after cessation of faciobrachial dystonic seizures (P < 0.0001). All patients had IgG4-LGI1 antibodies, but those with cognitive impairment had higher proportions of complement-fixing IgG1 antibodies (P = 0.03). Both subclasses caused LGI1-ADAM22 complex internalization, a potential non-inflammatory epileptogenic mechanism. In summary, faciobrachial dystonic seizures show striking time-sensitive responses to immunotherapy, and their cessation can prevent the development of cognitive impairment.awx323media15681705685001
ХУЛІГАНСТВО ТА ЙОГО ХАРАКТЕРИСТИКА
Abstract BACKGROUND: Temporal lobe gray-white matter abnormalities (GWMA) are frequent morphological aberrances observed on MRI in patients with temporal lobe epilepsy (TLE) in addition to hippocampal sclerosis (HS). OBJECTIVE: To study the influence of temporal pole GWMA on clinical characteristics and seizure outcome in patients with HS operated on for TLE. METHODS: A cohort of 370 patients undergoing surgery for intractable TLE was prospectively collected in an epilepsy surgery data base. Clinical characteristics and seizure outcome of all 58 TLE patients with identified HS and GWMA (group 1) were compared with those of a matched control group of 58 HS patients without GWMA (group 2). Both groups were further subdivided into patients undergoing transsylvian selective amygdalohippocampectomy (sAH) and anterior temporal lobectomy with amygdalohippocampectomy (ATL). RESULTS: The HS plus GWMA patients were significantly younger at epilepsy onset than those without GWMA. In the HS plus GWMA group, 41% of patients were younger than 2 years when they experienced their first seizure in contrast to only 17% of patients with pure HS (P = .004). Seizure outcome was not statistically different between the 2 groups: 75.9% of the patients in group 1 were seizure free (Engel class I) compared with 81% of patients in group 2. Seizure outcome in both groups was about equally successful with selective amygdalohippocampectomy and anterior temporal lobectomy (ns). CONCLUSION: Limited and standard resections in TLE patients with HS are equally successful regardless of the presence of GWMA
Epileptic monocular nystagmus and ictal diplopia as cortical and subcortical dysfunction
AbstractWe present the case of a patient with ictal monocular nystagmus and ictal diplopia who became seizure-free after resection of a right frontal focal cortical dysplasia (FCD), type 2B. Interictal neuroophthalmological examination showed several beats of a monocular nystagmus and a spasm of the contralateral eye. An exclusively ictal monocular epileptic nystagmus could be an argument for an exclusively cortical involvement in monocular eye movement control. The interictal findings in our patient, however, argue for an irregular ictal activation of both the cortical frontal eye field and the brainstem
Quantifying the Confidence in fMRI-Based Language Lateralisation Through Laterality Index Deconstruction
Wegrzyn M, Mertens M, Bien C, Woermann FG, Labudda K. Quantifying the Confidence in fMRI-Based Language Lateralisation Through Laterality Index Deconstruction. Frontiers in Neurology. 2019;10: 655.In epilepsy patients, language lateralisation is an important part of the presurgical diagnostic process. Using task-based fMRI, language lateralisation can be determined by visual inspection of activity patterns or by quantifying the difference in left- and right-hemisphere activity using variations of a basic formula [(L-R)/(L+R)]. However, the values of this laterality index (LI) depend on the choice of activity thresholds and regions of interest. The diagnostic utility of the U also depends on how its continuous values are translated into categorical decisions about a patient's language lateralisation. Here, we analysed fMRI data from 712 epilepsy patients who performed a verbal fluency task. Each fMRI data set was evaluated by a trained human rater as depicting left-sided, right-sided, or bilateral lateralisation or as being inconclusive. We used data-driven methods to define the activity thresholds and regions of interest used for LI computation and to define a classification scheme that allowed us to translate the U values into categorical decisions. By deconstructing the LI into measures of laterality (L-R) and strength (L+R), we also modelled the relationship between activation strength and conclusiveness of a data set. In a held-out data set, predictions reached 91% correct when using only conclusive data and 82% when inconclusive data were included. Although only trained on human evaluations of fMRIs, the approach generalised to the prediction of language Wada test results, allowing for significant above-chance accuracies. Compared against different existing methods of U-computation, our approach improved the identification and exclusion of inconclusive cases and ensured that decisions for the remaining data could be made with consistently high accuracies. We discuss how this approach can support clinicians in assessing fMRI data on a single-case level, deciding whether lateralisation can be determined with sufficient certainty or whether additional information is needed
Ocean mover’s distance: using optimal transport for analysing oceanographic data
Remote sensing observations from satellites and global biogeochemical models have combined to revolutionize the study of ocean biogeochemical cycling, but comparing the two data streams to each other and across time remains challenging due to the strong spatial-temporal structuring of the ocean. Here, we show that the Wasserstein distance provides a powerful metric for harnessing these structured datasets for better marine ecosystem and climate predictions. The Wasserstein distance complements commonly used point-wise difference methods such as the root-mean-squared error, by quantifying differences in terms of spatial displacement in addition to magnitude. As a test case, we consider chlorophyll (a key indicator of phytoplankton biomass) in the northeast Pacific Ocean, obtained from model simulations, in situ measurements, and satellite observations. We focus on two main applications: (i) comparing model predictions with satellite observations, and (ii) temporal evolution of chlorophyll both seasonally and over longer time frames. The Wasserstein distance successfully isolates temporal and depth variability and quantifies shifts in biogeochemical province boundaries. It also exposes relevant temporal trends in satellite chlorophyll consistent with climate change predictions. Our study shows that optimal transport vectors underlying the Wasserstein distance provide a novel visualization tool for testing models and better understanding temporal dynamics in the ocean
Ocean mover’s distance: using optimal transport for analysing oceanographic data
Remote sensing observations from satellites and global biogeochemical models have combined to revolutionize the study of ocean biogeochemical cycling, but comparing the two data streams to each other and across time remains challenging due to the strong spatial-temporal structuring of the ocean. Here, we show that the Wasserstein distance provides a powerful metric for harnessing these structured datasets for better marine ecosystem and climate predictions. The Wasserstein distance complements commonly used point-wise difference methods such as the root-mean-squared error, by quantifying differences in terms of spatial displacement in addition to magnitude. As a test case, we consider chlorophyll (a key indicator of phytoplankton biomass) in the northeast Pacific Ocean, obtained from model simulations, in situ measurements, and satellite observations. We focus on two main applications: (i) comparing model predictions with satellite observations, and (ii) temporal evolution of chlorophyll both seasonally and over longer time frames. The Wasserstein distance successfully isolates temporal and depth variability and quantifies shifts in biogeochemical province boundaries. It also exposes relevant temporal trends in satellite chlorophyll consistent with climate change predictions. Our study shows that optimal transport vectors underlying the Wasserstein distance provide a novel visualization tool for testing models and better understanding temporal dynamics in the ocean
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