Fast, scalable, Bayesian spike identification for multi-electrode arrays

We present an algorithm to identify individual neural spikes observed on high-density multi-electrode arrays (MEAs). Our method can distinguish large numbers of distinct neural units, even when spikes overlap, and accounts for intrinsic variability of spikes from each unit. As MEAs grow larger, it is important to find spike-identification methods that are scalable, that is, the computational cost of spike fitting should scale well with the number of units observed. Our algorithm accomplishes this goal, and is fast, because it exploits the spatial locality of each unit and the basic biophysics of extracellular signal propagation. Human intervention is minimized and streamlined via a graphical interface. We illustrate our method on data from a mammalian retina preparation and document its performance on simulated data consisting of spikes added to experimentally measured background noise. The algorithm is highly accurate

Local Difference Measures between Complex Networks for Dynamical System Model Evaluation

Acknowledgments We thank Reik V. Donner for inspiring suggestions that initialized the work presented herein. Jan H. Feldhoff is credited for providing us with the STARS simulation data and for his contributions to fruitful discussions. Comments by the anonymous reviewers are gratefully acknowledged as they led to substantial improvements of the manuscript.Peer reviewedPublisher PD

Reduced global longitudinal strain in association to increased left ventricular mass in patients with aortic valve stenosis and normal ejection fraction: a hybrid study combining echocardiography and magnetic resonance imaging

<p>Abstract</p> <p>Background</p> <p>Increased muscle mass index of the left ventricle (LVMi) is an independent predictor for the development of symptoms in patients with asymptomatic aortic stenosis (AS). While the onset of clinical symptoms and left ventricular systolic dysfunction determines a poor prognosis, the standard echocardiographic evaluation of LV dysfunction, only based on measurements of the LV ejection fraction (EF), may be insufficient for an early assessment of imminent heart failure. Contrary, 2-dimensional speckle tracking (2DS) seems to be superior in detecting subtle changes in myocardial function. The aim of the study was to assess these LV function deteriorations with global longitudinal strain (GLS) analysis and the relations to LVMi in patients with AS and normal EF.</p> <p>Methods</p> <p>50 patients with moderate to severe AS and 31 controls were enrolled. All patients underwent echocardiography, including 2DS imaging. LVMi measures were performed with magnetic resonance imaging in 38 patients with AS and indexed for body surface area.</p> <p>Results</p> <p>The total group of patients with AST showed a GLS of -15,2 ± 3,6% while the control group reached -19,5 ± 2,7% (p < 0,001). By splitting the group with AS in normal, moderate and severe increased LVMi, the GLS was -17,0 ± 2,6%, -13,2 ± 3,8% and -12,4 ± 2,9%, respectively (p = 0,001), where LVMi and GLS showed a significant correlation (r = 0,6, p < 0,001).</p> <p>Conclusions</p> <p>In conclusion, increased LVMi is reflected in abnormalities of GLS and the proportion of GLS impairment depends on the extent of LV hypertrophy. Therefore, simultaneous measurement of LVMi and GLS might be useful to identify patients at high risk for transition into heart failure who would benefit from aortic valve replacement irrespectively of LV EF.</p

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe

Persistently active neurons in human medial frontal and medial temporal lobe support working memory

Persistent neural activity is a putative mechanism for the maintenance of working memories. Persistent activity relies on the activity of a distributed network of areas, but the differential contribution of each area remains unclear. We recorded single neurons in the human medial frontal cortex and medial temporal lobe while subjects held up to three items in memory. We found persistently active neurons in both areas. Persistent activity of hippocampal and amygdala neurons was stimulus-specific, formed stable attractors and was predictive of memory content. Medial frontal cortex persistent activity, on the other hand, was modulated by memory load and task set but was not stimulus-specific. Trial-by-trial variability in persistent activity in both areas was related to memory strength, because it predicted the speed and accuracy by which stimuli were remembered. This work reveals, in humans, direct evidence for a distributed network of persistently active neurons supporting working memory maintenance

Monitoring of hard substrate communities

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Standing stocks of fishes around artificial reefs in Taiwan

[[sponsorship]]生物多樣性研究中心[[note]]已出版;有審查制度;具代表

Influence of feeding jumps on the egg-caring behaviour of male sergeant major Abudefduf vaigiensis (Pisces: Pomacentridae)

[[sponsorship]]生物多樣性研究中心[[note]]已出版;有審查制度;具代表性[[note]]http://gateway.isiknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=Drexel&SrcApp=hagerty_opac&KeyRecord=0001-3943&DestApp=JCR&RQ=IF_CAT_BOXPLOT[[note]]http://gateway.isiknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=RID&SrcApp=RID&DestLinkType=FullRecord&DestApp=ALL_WOS&KeyUT=A1984TK8550000