Generative Embedding for Model-Based Classification of fMRI Data

Decoding models, such as those underlying multivariate classification algorithms, have been increasingly used to infer cognitive or clinical brain states from measures of brain activity obtained by functional magnetic resonance imaging (fMRI). The practicality of current classifiers, however, is restricted by two major challenges. First, due to the high data dimensionality and low sample size, algorithms struggle to separate informative from uninformative features, resulting in poor generalization performance. Second, popular discriminative methods such as support vector machines (SVMs) rarely afford mechanistic interpretability. In this paper, we address these issues by proposing a novel generative-embedding approach that incorporates neurobiologically interpretable generative models into discriminative classifiers. Our approach extends previous work on trial-by-trial classification for electrophysiological recordings to subject-by-subject classification for fMRI and offers two key advantages over conventional methods: it may provide more accurate predictions by exploiting discriminative information encoded in 'hidden' physiological quantities such as synaptic connection strengths; and it affords mechanistic interpretability of clinical classifications. Here, we introduce generative embedding for fMRI using a combination of dynamic causal models (DCMs) and SVMs. We propose a general procedure of DCM-based generative embedding for subject-wise classification, provide a concrete implementation, and suggest good-practice guidelines for unbiased application of generative embedding in the context of fMRI. We illustrate the utility of our approach by a clinical example in which we classify moderately aphasic patients and healthy controls using a DCM of thalamo-temporal regions during speech processing. Generative embedding achieves a near-perfect balanced classification accuracy of 98% and significantly outperforms conventional activation-based and correlation-based methods. This example demonstrates how disease states can be detected with very high accuracy and, at the same time, be interpreted mechanistically in terms of abnormalities in connectivity. We envisage that future applications of generative embedding may provide crucial advances in dissecting spectrum disorders into physiologically more well-defined subgroups

Brain herniation in a patient with apparently normal intracranial pressure: a case report

Introduction Intracranial pressure monitoring is commonly implemented in patients with neurologic injury and at high risk of developing intracranial hypertension, to detect changes in intracranial pressure in a timely manner. This enables early and potentially life-saving treatment of intracranial hypertension. Case presentation An intraparenchymal pressure probe was placed in the hemisphere contralateral to a large basal ganglia hemorrhage in a 75-year-old Caucasian man who was mechanically ventilated and sedated because of depressed consciousness. Intracranial pressures were continuously recorded and never exceeded 17 mmHg. After sedation had been stopped, our patient showed clinical signs of transtentorial brain herniation, despite apparently normal intracranial pressures (less than 10 mmHg). Computed tomography revealed that the size of the intracerebral hematoma had increased together with significant unilateral brain edema and transtentorial herniation. The contralateral hemisphere where the intraparenchymal pressure probe was placed appeared normal. Our patient underwent emergency decompressive craniotomy and was tracheotomized early, but did not completely recover. Conclusions Intraparenchymal pressure probes placed in the hemisphere contralateral to an intracerebral hematoma may dramatically underestimate intracranial pressure despite apparently normal values, even in the case of transtentorial brain herniation

Generative Embedding for Model-Based Classification of fMRI Data

Decoding models, such as those underlying multivariate classification algorithms, have been increasingly used to infer cognitive or clinical brain states from measures of brain activity obtained by functional magnetic resonance imaging (fMRI). The practicality of current classifiers, however, is restricted by two major challenges. First, due to the high data dimensionality and low sample size, algorithms struggle to separate informative from uninformative features, resulting in poor generalization performance. Second, popular discriminative methods such as support vector machines (SVMs) rarely afford mechanistic interpretability. In this paper, we address these issues by proposing a novel generative-embedding approach that incorporates neurobiologically interpretable generative models into discriminative classifiers. Our approach extends previous work on trial-by-trial classification for electrophysiological recordings to subject-by-subject classification for fMRI and offers two key advantages over conventional methods: it may provide more accurate predictions by exploiting discriminative information encoded in ‘hidden’ physiological quantities such as synaptic connection strengths; and it affords mechanistic interpretability of clinical classifications. Here, we introduce generative embedding for fMRI using a combination of dynamic causal models (DCMs) and SVMs. We propose a general procedure of DCM-based generative embedding for subject-wise classification, provide a concrete implementation, and suggest good-practice guidelines for unbiased application of generative embedding in the context of fMRI. We illustrate the utility of our approach by a clinical example in which we classify moderately aphasic patients and healthy controls using a DCM of thalamo-temporal regions during speech processing. Generative embedding achieves a near-perfect balanced classification accuracy of 98% and significantly outperforms conventional activation-based and correlation-based methods. This example demonstrates how disease states can be detected with very high accuracy and, at the same time, be interpreted mechanistically in terms of abnormalities in connectivity. We envisage that future applications of generative embedding may provide crucial advances in dissecting spectrum disorders into physiologically more well-defined subgroups

Global and regional brain metabolic scaling and its functional consequences

Background: Information processing in the brain requires large amounts of metabolic energy, the spatial distribution of which is highly heterogeneous reflecting complex activity patterns in the mammalian brain. Results: Here, it is found based on empirical data that, despite this heterogeneity, the volume-specific cerebral glucose metabolic rate of many different brain structures scales with brain volume with almost the same exponent around -0.15. The exception is white matter, the metabolism of which seems to scale with a standard specific exponent -1/4. The scaling exponents for the total oxygen and glucose consumptions in the brain in relation to its volume are identical and equal to $0.86\pm 0.03$, which is significantly larger than the exponents 3/4 and 2/3 suggested for whole body basal metabolism on body mass. Conclusions: These findings show explicitly that in mammals (i) volume-specific scaling exponents of the cerebral energy expenditure in different brain parts are approximately constant (except brain stem structures), and (ii) the total cerebral metabolic exponent against brain volume is greater than the much-cited Kleiber's 3/4 exponent. The neurophysiological factors that might account for the regional uniformity of the exponents and for the excessive scaling of the total brain metabolism are discussed, along with the relationship between brain metabolic scaling and computation.Comment: Brain metabolism scales with its mass well above 3/4 exponen

Attitudes towards complementary and alternative medicine in chronic pain syndromes: a questionnaire-based comparison between primary headache and low back pain

<p>Abstract</p> <p>Background</p> <p>Complementary and Alternative Medicine (CAM) is widely used and popular among patients with primary headache or low back pain (LBP). Aim of the study was to analyze attitudes of headache and LBP patients towards the use of CAM.</p> <p>Methods</p> <p>Two questionnaire-based surveys were applied comparing 432 primary headache and 194 LBP patients.</p> <p>Results</p> <p>In total, 84.75% of all patients reported use of CAM; with significantly more LBP patients. The most frequently-used CAM therapies in headache were acupuncture (71.4%), massages (56.4%), and thermotherapy (29.2%), in LBP thermotherapy (77.4%), massages (62.7%), and acupuncture (51.4%). The most frequent attitudes towards CAM use in headache vs. LBP: "leave nothing undone" (62.5% vs. 52.1%; p = 0.006), "take action against the disease" (56.8% vs. 43.2%; p = 0.006). Nearly all patients with previous experience with CAM currently use CAM in both conditions (93.6% in headache; 100% in LBP). However, the majority of the patients had no previous experience.</p> <p>Conclusion</p> <p>Understanding motivations for CAM treatment is important, because attitudes derive from wishes for non-pharmacological treatment, to be more involved in treatment and avoid side effects. Despite higher age and more permanent pain in LBP, both groups show high use of CAM with only little specific difference in preferred methods and attitudes towards CAM use. This may reflect deficits and unfulfilled goals in conventional treatment. Maybe CAM can decrease the gap between patients' expectations about pain therapy and treatment reality, considering that both conditions are often chronic diseases, causing high burdens for daily life.</p

Using a genetically informative design to examine the relationship between breastfeeding and childhood conduct problems

A number of public health interventions aimed at increasing the uptake of breastfeeding are in place in the United States and other Western countries. While the physical health and nutritional benefits of breastfeeding for the mother and child are relatively well established, the evidence for psychological effects is less clear. This study aimed to examine whether there is an association between breastfeeding and later conduct problems in children. It also considered the extent to which any relationship is attributable to maternally-provided inherited characteristics that influence both likelihood of breastfeeding and child conduct problems. A prenatal cross-fostering design with a sample of 870 families with a child aged 4–11 years was used. Mothers were genetically related or unrelated to their child as a result of assisted reproductive technologies. The relationship between breastfeeding and conduct problems was assessed while controlling for theorised measured confounders by multivariate regression (e.g. maternal smoking, education, and antisocial behaviour), and for unmeasured inherited factors by testing associations separately for related and unrelated mother-child pairs. Breastfeeding was associated with lower levels of conduct disorder symptoms in offspring in middle childhood. Breastfeeding was associated with lower levels of conduct problems even after controlling for observed confounders in the genetically related group, but not in the genetically unrelated group. In contrast, maternal antisocial behaviour showed robust associations with child conduct problems after controlling for measured and inherited confounders. These findings highlight the importance of using genetically sensitive designs in order to test causal environmental influences

Genetic variants regulating ORMDL3 expression contribute to the risk of childhood asthma

Asthma is caused by a combination of poorly understood genetic and environmental factors(1,2). We have systematically mapped the effects of single nucleotide polymorphisms ( SNPs) on the presence of childhood onset asthma by genome-wide association. We characterized more than 317,000 SNPs in DNA from 994 patients with childhood onset asthma and 1,243 non-asthmatics, using family and case-referent panels. Here we show multiple markers on chromosome 17q21 to be strongly and reproducibly associated with childhood onset asthma in family and case-referent panels with a combined P value of P < 10(-12). In independent replication studies the 17q21 locus showed strong association with diagnosis of childhood asthma in 2,320 subjects from a cohort of German children (P=0.0003) and in 3,301 subjects from the British 1958 Birth Cohort (P=0.0005). We systematically evaluated the relationships between markers of the 17q21 locus and transcript levels of genes in Epstein - Barr virus (EBV)-transformed lymphoblastoid cell lines from children in the asthma family panel used in our association study. The SNPs associated with childhood asthma were consistently and strongly associated (P < 10(-22)) in cis with transcript levels of ORMDL3, a member of a gene family that encodes transmembrane proteins anchored in the endoplasmic reticulum(3). The results indicate that genetic variants regulating ORMDL3 expression are determinants of susceptibility to childhood asthma.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/62682/1/nature06014.pd

Multicenter evaluation of a lateral-flow device test for diagnosing invasive pulmonary aspergillosis in ICU patients

Introduction: The incidence of invasive pulmonary aspergillosis (IPA) in intensive care unit (ICU) patients is increasing, and early diagnosis of the disease and treatment with antifungal drugs is critical for patient survival. Serum biomarker tests for IPA typically give false-negative results in non-neutropenic patients, and galactomannan (GM) detection, the preferred diagnostic test for IPA using bronchoalveolar lavage (BAL), is often not readily available. Novel approaches to IPA detection in ICU patients are needed. In this multicenter study, we evaluated the performance of an Aspergillus lateral-flow device (LFD) test for BAL IPA detection in critically ill patients. Methods: A total of 149 BAL samples from 133 ICU patients were included in this semiprospective study. Participating centers were the medical university hospitals of Graz, Vienna and Innsbruck in Austria and the University Hospital of Mannheim, Germany. Fungal infections were classified according to modified European Organization for Research and Treatment of Cancer/Mycoses Study Group criteria. Results: Two patients (four BALs) had proven IPA, fourteen patients (sixteen BALs) had probable IPA, twenty patients (twenty-one BALs) had possible IPA and ninety-seven patients (one hundred eight BALs) did not fulfill IPA criteria. Sensitivity, specificity, negative predictive value, positive predictive value and diagnostic odds ratios for diagnosing proven and probable IPA using LFD tests of BAL were 80%, 81%, 96%, 44% and 17.6, respectively. Fungal BAL culture exhibited a sensitivity of 50% and a specificity of 85%. Conclusion: LFD tests of BAL showed promising results for IPA diagnosis in ICU patients. Furthermore, the LFD test can be performed easily and provides rapid results. Therefore, it may be a reliable alternative for IPA diagnosis in ICU patients if GM results are not rapidly available. Trial registration: ClinicalTrials.gov NCT02058316. Registered 20 January 2014

Effect of aflibercept in insufficient responders to prior anti-VEGF therapy in neovascular AMD

PURPOSE: Evaluation of three aflibercept injections at 4-week intervals in patients with neovascular AMD showing an “insufficient anatomic response” to prior anti-VEGF therapy with ranibizumab or bevacizumab. METHODS: The retrospective analysis included 96 eyes that had received at least three intravitreal 0.5 mg ranibizumab or 1.25 mg bevacizumab injections over a period of no more than 4 months prior to switching to aflibercept. In addition, the selected eyes had to have evidence of persisting or increasing sub- or intraretinal fluid, observed in optical coherence tomography (OCT). All patients received a loading dose of three intravitreal 2 mg aflibercept injections at 4-week intervals. Evaluation included central retinal thickness (CRT) and maximum pigment epithelium (PED) height measured by spectral domain OCT and best-corrected visual acuity (BCVA) prior to the switch of therapy and 4 weeks after the third aflibercept injection. RESULTS: A significant reduction of mean CRT (−39 μm; p < 0.001) and maximum PED height (−46 μm; p < 0.001) as found 4 weeks after the third aflibercept injection. Eighty-two out of 96 eyes (85 %) had a PED just prior to switching to aflibercept. There was an improvement in BCVA of 1.9 letters 4 weeks after the last aflibercept injection; the vision gain, however, did not reach statistical significance (p = 0.061). The further analysis did not show any correlation of the change in CRT, maximum PED, and BCVA with the number of prior anti-VEGF treatments. CONCLUSION: Retinal edema and PEDs regressed significantly after switching to aflibercept in patients insufficiently responding to prior therapy with ranibizumab or bevacizumab. No correlation could be found with regard to the number of prior treatments