Formation of temporal-feature maps by axonal propagation of synaptic learning

Computational maps are of central importance to a neuronal representation of the outside world. In a map, neighboring neurons respond to similar sensory features. A well studied example is the computational map of interaural time differences (ITDs), which is essential to sound localization in a variety of species and allows resolution of ITDs of the order of 10 μs. Nevertheless, it is unclear how such an orderly representation of temporal features arises. We address this problem by modeling the ontogenetic development of an ITD map in the laminar nucleus of the barn owl. We show how the owl's ITD map can emerge from a combined action of homosynaptic spike-based Hebbian learning and its propagation along the presynaptic axon. In spike-based Hebbian learning, synaptic strengths are modified according to the timing of pre- and postsynaptic action potentials. In unspecific axonal learning, a synapse's modification gives rise to a factor that propagates along the presynaptic axon and affects the properties of synapses at neighboring neurons. Our results indicate that both Hebbian learning and its presynaptic propagation are necessary for map formation in the laminar nucleus, but the latter can be orders of magnitude weaker than the former. We argue that the algorithm is important for the formation of computational maps, when, in particular, time plays a key role.

Imaging neuroscience: Principles or maps?

This article reviews some recent trends in imaging neuroscience. A distinction is made between making maps of functional responses in the brain and discerning the rules or principles that underlie their organization. After considering developments in the characterization of brain imaging data, several examples are presented that highlight the context-sensitive nature of neuronal responses that we measure. These contexts can be endogenous and physiological, reflecting the fact that each cortical area, or neuronal population, expresses its dynamics in the context of interactions with other areas. Conversely, these contexts can be experimental or psychological and can have a profound effect on the regional effects elicited. In this review we consider experimental designs and analytic strategies that go beyond cognitive subtraction and speculate on how functional imaging can be used to address both the details and principles underlying functional integration and specialization in the brain.

Gene for the catalytic subunit of mouse DNA-dependent protein kinase maps to the scid locus.

The gene encoding the catalytic subunit of DNA-dependent protein kinase (DNA-PKcs) has been proposed recently as a candidate gene for the mouse severe combined immune deficiency (scid) locus. We have used a partial cDNA clone for human DNA-PKcs to map the mouse homologue using a large interspecific backcross panel. We found that the mouse gene for DNA-PKcs does not recombine with scid, consistent with the hypothesis that scid is a mutation in the mouse gene for DNA-PKcs.

Gene for the catalytic subunit of the human DNA-activated protein kinase maps to the site of the XRCC7 gene on chromosome 8.

The DNA-activated serine/threonine protein kinase (DNA-PK) is composed of a large (approximately 460 kDa) catalytic polypeptide (DNA-PKcs) and Ku, a heterodimeric DNA-binding component (p70/p80) that targets DNA-PKcs to DNA. A 41-kbp segment of the DNA-PKcs gene was isolated, and a 7902-bp segment was sequenced. The sequence contains a polymorphic Pvu II restriction enzyme site, and comparing the sequence with that of the cDNA revealed the positions of nine exons. The DNA-PKcs gene was mapped to band q11 of chromosome 8 by in situ hybridization. This location is coincident with that of XRCC7, the gene that complements the DNA double-strand break repair and V(D)J recombination defects (where V is variable, D is diversity, and J is joining) of hamster V3 and murine severe combined immunodeficient (scid) cells.

A region of consistent deletion in neuroblastoma maps within human chromosome 1p36.2-36.3.

Deletion of the short arm of human chromosome 1 is the most common cytogenetic abnormality observed in neuroblastoma. To characterize the region of consistent deletion, we performed loss of heterozygosity (LOH) studies on 122 neuroblastoma tumor samples with 30 distal chromosome 1p polymorphisms. LOH was detected in 32 of the 122 tumors (26%). A single region of LOH, marked distally by D1Z2 and proximally by D1S228, was detected in all tumors demonstrating loss. Also, cells from a patient with a constitutional deletion of 1p36, and from a neuroblastoma cell line with a small 1p36 deletion, were analyzed by fluorescence in situ hybridization. Cells from both sources had interstitial deletions of 1p36.2-36.3 which overlapped the consensus region of LOH defined by the tumors. Interstitial deletion in the constitutional case was confirmed by allelic loss studies using the panel of polymorphic markers. Four proposed candidate genes--DAN, ID3 (heir-1), CDC2L1 (p58), and TNFR2--were shown to lie outside of the consensus region of allelic loss, as defined by the above deletions. These results more precisely define the location of a neuroblastoma suppressor gene within 1p36.2-36.3, eliminating 33 centimorgans of proximal 1p36 from consideration. Furthermore, a consensus region of loss, which excludes the four leading candidate genes, was found in all tumors with 1p36 LOH.

Aod1, the immunoregulatory locus controlling abrogation of tolerance in neonatal thymectomy-induced autoimmune ovarian dysgenesis, maps to mouse chromosome 16.

Mice thymectomized at three days of age (D3Tx) develop during adulthood a variety of organ-specific autoimmune diseases, including autoimmune ovarian dysgenesis (AOD). The phenotypic spectrum of AOD is characterized by the development of anti-ovarian autoantibodies, oophoritis, and atrophy. The D3Tx model of AOD is unique in that disease induction depends exclusively on perturbation of the normal developing immune system, is T-cell-mediated, and is strain specific. For example, D3Tx A/J mice are highly susceptible to AOD, whereas C57BL/6J mice are resistant. After D3Tx, self ovarian antigens, expressed at physiological levels, trigger an autoimmune response capable of eliciting disease. The D3Tx model provides, therefore, the opportunity to focus on the mechanisms of self-tolerance that are relevant to disease pathogenesis. Previous studies indicate that the principal mechanisms involved in AOD susceptibility are genetically controlled and govern developmental processes associated with the induction and maintenance of peripheral tolerance. We report here the mapping of the Aod1 locus to mouse chromosome 16 within a region encoding several loci of immunologic relevance, including scid, Igl1, VpreB, Igll, Igl1r, Mtv6 (Mls-3), Ly-7, Ifnar, and Ifgt.

Ordered restriction endonuclease maps of yeast artificial chromosomes created by optical mapping on surfaces.

We have developed a surface mounting technology for the rapid construction of ordered restriction maps from individual DNA molecules. Optical restriction maps constructed from yeast artificial chromosome DNA molecules mounted on specially derivatized glass surfaces are accurate and reproducible, and the technology is amenable to automation. The mounting procedures described here should also be useful for fluorescence in situ hybridization studies. We believe these improvements to optical mapping will further stimulate the development of nonelectrophoretic approaches to genome analysis.

CB-norm estimates for maps between noncommutative Lp-spaces and quantum channel theory.

In the first part of this work, we show how certain techniques from quantum information theory can be used in order to obtain very sharp embeddings between noncommutative Lp-spaces. Then, we use these estimates to study the classical capacity with restricted assisted entanglement of the quantum erasure channel and the quantum depolarizing channel. In particular, we exactly compute the capacity of the first one and we show that certain nonmultiplicative results hold for the second one.

[C II] and 12^CO(1-0) emission maps in HLSJ091828.6+514223: a strongly lensed interacting system AT z = 5.24

We present Submillimeter Array [C II] 158 μm and Karl G. Jansky Very Large Array 12^CO(1-0) line emission maps for the bright, lensed, submillimeter source at z = 5.2430 behind A 773: HLSJ091828.6+514223 (HLS0918). We combine these measurements with previously reported line profiles, including multiple 12^CO rotational transitions, [C I], water, and [N II], providing some of the best constraints on the properties of the interstellar medium in a galaxy at z > 5. HLS0918 has a total far-infrared (FIR) luminosity L_FIR(8–1000 μm) = (1.6 ± 0.1) × 10^14 L_☉ μ^–1, where the total magnification μ_total = 8.9 ± 1.9, via a new lens model from the [C II] and continuum maps. Despite a HyLIRG luminosity, the FIR continuum shape resembles that of a local LIRG. We simultaneously fit all of the observed spectral line profiles, finding four components that correspond cleanly to discrete spatial structures identified in the maps. The two most redshifted spectral components occupy the nucleus of a massive galaxy, with a source-plane separation <1 kpc. The reddest dominates the continuum map (demagnified L_FIR, component = (1.1 ± 0.2) × 10^13 L_☉) and excites strong water emission in both nuclear components via a powerful FIR radiation field from the intense star formation. A third star-forming component is most likely a region of a merging companion (ΔV ~ 500 km s^–1) exhibiting generally similar gas properties. The bluest component originates from a spatially distinct region and photodissociation region analysis suggests that it is lower density, cooler, and forming stars less vigorously than the other components. Strikingly, it has very strong [N II] emission, which may suggest an ionized, molecular outflow. This comprehensive view of gas properties and morphology in HLS0918 previews the science possible for a large sample of high-redshift galaxies once ALMA attains full sensitivity.

Black maps/vivid waters : beauty and horror in David Maisel's The Lake Project and Terminal Mirage

"This paper examines The Lake Project and Terminal Mirage, the two components of David Maisel’s Black Maps series that concern water. Like the section of the Salt Lake chosen by Robert Smithson for his seminal Spiral Jetty, the alkaline waters Maisel photographs are subject to infestations of bacteria that that give them a visceral hue. Smithson provides a reference for this work; the artists are notable for their shared site, disorienting scale, and attraction to entropy"

Growing Neural Gas approach for obtaining homogeneous maps by restricting the insertion of new nodes

The Growing Neural Gas model is used widely in artificial neural networks. However, its application is limited in some contexts by the proliferation of nodes in dense areas of the input space. In this study, we introduce some modifications to address this problem by imposing three restrictions on the insertion of new nodes. Each restriction aims to maintain the homogeneous values of selected criteria. One criterion is related to the square error of classification and an alternative approach is proposed for avoiding additional computational costs. Three parameters are added that allow the regulation of the restriction criteria. The resulting algorithm allows models to be obtained that suit specific needs by specifying meaningful parameters.

3D Maps Representation Using GNG

Current RGB-D sensors provide a big amount of valuable information for mobile robotics tasks like 3D map reconstruction, but the storage and processing of the incremental data provided by the different sensors through time quickly become unmanageable. In this work, we focus on 3D maps representation and propose the use of the Growing Neural Gas (GNG) network as a model to represent 3D input data. GNG method is able to represent the input data with a desired amount of neurons or resolution while preserving the topology of the input space. Experiments show how GNG method yields a better input space adaptation than other state-of-the-art 3D map representation methods.

Feature selection by multi-objective optimisation: Application to network anomaly detection by hierarchical self-organising maps

Feature selection is an important and active issue in clustering and classification problems. By choosing an adequate feature subset, a dataset dimensionality reduction is allowed, thus contributing to decreasing the classification computational complexity, and to improving the classifier performance by avoiding redundant or irrelevant features. Although feature selection can be formally defined as an optimisation problem with only one objective, that is, the classification accuracy obtained by using the selected feature subset, in recent years, some multi-objective approaches to this problem have been proposed. These either select features that not only improve the classification accuracy, but also the generalisation capability in case of supervised classifiers, or counterbalance the bias toward lower or higher numbers of features that present some methods used to validate the clustering/classification in case of unsupervised classifiers. The main contribution of this paper is a multi-objective approach for feature selection and its application to an unsupervised clustering procedure based on Growing Hierarchical Self-Organising Maps (GHSOMs) that includes a new method for unit labelling and efficient determination of the winning unit. In the network anomaly detection problem here considered, this multi-objective approach makes it possible not only to differentiate between normal and anomalous traffic but also among different anomalies. The efficiency of our proposals has been evaluated by using the well-known DARPA/NSL-KDD datasets that contain extracted features and labelled attacks from around 2 million connections. The selected feature sets computed in our experiments provide detection rates up to 99.8% with normal traffic and up to 99.6% with anomalous traffic, as well as accuracy values up to 99.12%.