The influence of inter-regional delays in generating large-scale brain networks of phase synchronization.

Large-scale networks of phase synchronization are considered to regulate the communication between brain regions fundamental to cognitive function, but the mapping to their structural substrates, i.e., the structure-function relationship, remains poorly understood. Biophysical Network Models (BNMs) have demonstrated the influences of local oscillatory activity and inter-regional anatomical connections in generating alpha-band (8-12 Hz) networks of phase synchronization observed with Electroencephalography (EEG) and Magnetoencephalography (MEG). Yet, the influence of inter-regional conduction delays remains unknown. In this study, we compared a BNM with standard "distance-dependent delays", which assumes constant conduction velocity, to BNMs with delays specified by two alternative methods accounting for spatially varying conduction velocities, "isochronous delays" and "mixed delays". We followed the Approximate Bayesian Computation (ABC) workflow, i) specifying neurophysiologically informed prior distributions of BNM parameters, ii) verifying the suitability of the prior distributions with Prior Predictive Checks, iii) fitting each of the three BNMs to alpha-band MEG resting-state data (N = 75) with Bayesian optimization for Likelihood-Free Inference (BOLFI), and iv) choosing between the fitted BNMs with ABC model comparison on a separate MEG dataset (N = 30). Prior Predictive Checks revealed the range of dynamics generated by each of the BNMs to encompass those seen in the MEG data, suggesting the suitability of the prior distributions. Fitting the models to MEG data yielded reliable posterior distributions of the parameters of each of the BNMs. Finally, model comparison revealed the BNM with "distance-dependent delays", as the most probable to describe the generation of alpha-band networks of phase synchronization seen in MEG. These findings suggest that distance-dependent delays might contribute to the neocortical architecture of human alpha-band networks of phase synchronization. Hence, our study illuminates the role of inter-regional delays in generating the large-scale networks of phase synchronization that might subserve the communication between regions vital to cognition.

Plasmids Shaped the Recent Emergence of the Major Nosocomial Pathogen Enterococcus faecium.

Enterococcus faecium is a gut commensal of humans and animals but is also listed on the WHO global priority list of multidrug-resistant pathogens. Many of its antibiotic resistance traits reside on plasmids and have the potential to be disseminated by horizontal gene transfer. Here, we present the first comprehensive population-wide analysis of the pan-plasmidome of a clinically important bacterium, by whole-genome sequence analysis of 1,644 isolates from hospital, commensal, and animal sources of E. faecium Long-read sequencing on a selection of isolates resulted in the completion of 305 plasmids that exhibited high levels of sequence modularity. We further investigated the entirety of all plasmids of each isolate (plasmidome) using a combination of short-read sequencing and machine-learning classifiers. Clustering of the plasmid sequences unraveled different E. faecium populations with a clear association with hospitalized patient isolates, suggesting different optimal configurations of plasmids in the hospital environment. The characterization of these populations allowed us to identify common mechanisms of plasmid stabilization such as toxin-antitoxin systems and genes exclusively present in particular plasmidome populations exemplified by copper resistance, phosphotransferase systems, or bacteriocin genes potentially involved in niche adaptation. Based on the distribution of k-mer distances between isolates, we concluded that plasmidomes rather than chromosomes are most informative for source specificity of E. faeciumIMPORTANCEEnterococcus faecium is one of the most frequent nosocomial pathogens of hospital-acquired infections. E. faecium has gained resistance against most commonly available antibiotics, most notably, against ampicillin, gentamicin, and vancomycin, which renders infections difficult to treat. Many antibiotic resistance traits, in particular, vancomycin resistance, can be encoded in autonomous and extrachromosomal elements called plasmids. These sequences can be disseminated to other isolates by horizontal gene transfer and confer novel mechanisms to source specificity. In our study, we elucidated the total plasmid content, referred to as the plasmidome, of 1,644 E. faecium isolates by using short- and long-read whole-genome technologies with the combination of a machine-learning classifier. This was fundamental to investigate the full collection of plasmid sequences present in our collection (pan-plasmidome) and to observe the potential transfer of plasmid sequences between E. faecium hosts. We observed that E. faecium isolates from hospitalized patients carried a larger number of plasmid sequences compared to that from other sources, and they elucidated different configurations of plasmidome populations in the hospital environment. We assessed the contribution of different genomic components and observed that plasmid sequences have the highest contribution to source specificity. Our study suggests that E. faecium plasmids are regulated by complex ecological constraints rather than physical interaction between hosts.

Bankruptcy analysis with self-organizing maps in learning metrics.

We introduce a method for deriving a metric, locally based on the Fisher information matrix, into the data space. A self-organizing map (SOM) is computed in the new metric to explore financial statements of enterprises. The metric measures local distances in terms of changes in the distribution of an auxiliary random variable that reflects what is important in the data. In this paper the variable indicates bankruptcy within the next few years. The conditional density of the auxiliary variable is first estimated, and the change in the estimate resulting from local displacements in the primary data space is measured using the Fisher information matrix. When a self-organizing map is computed in the new metric it still visualizes the data space in a topology-preserving fashion, but represents the (local) directions in which the probability of bankruptcy changes the most.

Self organization of a massive document collection.

This article describes the implementation of a system that is able to organize vast document collections according to textual similarities. It is based on the self-organizing map (SOM) algorithm. As the feature vectors for the documents statistical representations of their vocabularies are used. The main goal in our work has been to scale up the SOM algorithm to be able to deal with large amounts of high-dimensional data. In a practical experiment we mapped 6,840,568 patent abstracts onto a 1,002,240-node SOM. As the feature vectors we used 500-dimensional vectors of stochastic figures obtained as random projections of weighted word histograms.

Optimal resource allocation for novelty detection in a human auditory memory.

A theory of resource allocation for neuronal low-level filtering is presented, based on an analysis of optimal resource allocation in simple environments. A quantitative prediction of the theory was verified in measurements of the magnetic mismatch response (MMR), an auditory event-related magnetic response of the human brain. The amplitude of the MMR was found to be directly proportional to the information conveyed by the stimulus. To the extent that the amplitude of the MMR can be used to measure resource usage by the auditory cortex, this finding supports our theory that, at least for early auditory processing, energy resources are used in proportion to the information content of incoming stimulus flow.

Systematic screening for genetic polymorphism in human platelet glycoprotein Ibalpha.

Glycoprotein Ibalpha (GP Ibalpha; CD 42b; hereafter GPIBA) is a component of the cell surface receptor for the von Willebrand factor (vWf) on platelets. Immunizations against various platelet surface antigens play a major role in neonatal alloimmune thrombocytopenia and in post-transfusion purpura. Only one antigenic polymorphism in GPIBA has thus far been established: the HPA-2 (Ko) alloantigen system. To screen other polymorphisms in GPIBA systematically, we analyzed the whole coding sequence of the GPIBA gene in 50 Finnish blood donors using the single-strand conformation polymorphism method. In addition to the known polymorphisms, we detected three others. Sequencing of the gene segments carrying the new polymorphisms revealed that none of them changed the predicted amino acid sequence. Polymorphism designated RS was located five base pairs upstream from the initiation codon at position 3064 and had the gene frequency of 16% for R and 84% for S, respectively, in the Finnish population, and it was detectable by the restriction enzyme Hae III. The EF polymorphism was at position 3842 (Asn242) and the gene frequencies were 97% for E and 3% for F. The KL polymorphism was at position 4142 (Arg342) and the gene frequencies were 98% for K and 2% for L. The five polymorphic positions in GPIBA formed altogether six different alleles of the gene. The data suggest that there are only a few variable amino acids in GPIBA.

Self-organizing map in recognition of topographic patterns of EEG spectra.

The self-organizing map, a neural network algorithm, was applied to the recognition of topographic patterns in clinical 22-channel EEG. Inputs to the map were extracted from short-time power spectra of all channels. Each location on a self-organized map entails a model for a cluster of similar input patterns; the best-matching model determines the location of a sample on the map. Thus, an instantaneous topographic EEG pattern corresponds to the location of the sample, and changes with time correspond to the trajectories of consecutive samples. EEG segments of "alpha," "alpha attenuation," "theta of drowsiness," "eye movements," "EMG artifact," and "electrode artifacts" were selected and labeled by visual inspection of the original records. The map locations of the labeled segments were different; the map thus distinguished between them. The locations of individual EEG's on the "alpha-area" of the map were also different. The clustering and easily understandable visualization of topographic EEG patterns are obtainable on a self-organized map in real time.