The resting human brain and motor learning.

Functionally related brain networks are engaged even in the absence of an overt behavior. The role of this resting state activity, evident as low-frequency fluctuations of BOLD (see [1] for review, [2-4]) or electrical [5, 6] signals, is unclear. Two major proposals are that resting state activity supports introspective thought or supports responses to future events [7]. An alternative perspective is that the resting brain actively and selectively processes previous experiences [8]. Here we show that motor learning can modulate subsequent activity within resting networks. BOLD signal was recorded during rest periods before and after an 11 min visuomotor training session. Motor learning but not motor performance modulated a fronto-parietal resting state network (RSN). Along with the fronto-parietal network, a cerebellar network not previously reported as an RSN was also specifically altered by learning. Both of these networks are engaged during learning of similar visuomotor tasks [9-22]. Thus, we provide the first description of the modulation of specific RSNs by prior learning--but not by prior performance--revealing a novel connection between the neuroplastic mechanisms of learning and resting state activity. Our approach may provide a powerful tool for exploration of the systems involved in memory consolidation

The Design of a Best Execution Market

The notion of best execution on securities markets is manifold. Best execution has different meanings to different market participants, therefore, it is difficult to find a unique market structure that meets this requirements for all the participants. Traditional market structures are either static or flexible, meaning that an individual market participant has no influence regarding the concrete market structure’s characteristics, like e. g. the price discovery mechanism, trading frequency or the market transparency. Traditional market structures are either static or flexible, meaning that an individual market participant has no influence regarding the Focussing on customer orientation, we propose a new type of market structure: the dynamic market model, where participants individually choose the characteristics of the market structure for each transaction they perform. Furthermore, this paper offers an approach to design dynamic market models from scratch. We briefly sketch the necessary steps towards a dynamic market model. Traditional market structures are either static or flexible, meaning that an individual market participant has no influence regarding the Finally, we present AMTRAS; the prototype of an electronic trading system that was conceived and implemented following the aforementioned approach. AMTRAS is an software-agent based bond trading system designed for the need of institutional investors. It implements a dynamic market model, a sophisticated product- and partner matching scheme as well as an innovative price discovery approach

Heparan sulfate and heparin interactions with proteins.

Heparan sulfate (HS) polysaccharides are ubiquitous components of the cell surface and extracellular matrix of all multicellular animals, whereas heparin is present within mast cells and can be viewed as a more sulfated, tissuespecific, HS variant. HS and heparin regulate biological processes through interactions with a large repertoire of proteins. Owing to these interactions and diverse effects observed during in vitro, ex vivo and in vivo experiments, manifold biological/pharmacological activities have been attributed to them. The properties that have been thought to bestow protein binding and biological activity upon HS and heparin vary from high levels of sequence specificity to a dependence on charge. In contrast to these opposing opinions, we will argue that the evidence supports both a level of redundancy and a degree of selectivity in the structure–activity relationship. The relationship between this apparent redundancy, the multi-dentate nature of heparin and HS polysaccharide chains, their involvement in protein networks and the multiple binding sites on proteins, each possessing different properties, will also be considered. Finally, the role of cations in modulating HS/heparin activity will be reviewed and some of the implications for structure–activity relationships and regulation will be discussed

Training of Instrumentalists and Development of New Technologies on SOFIA

This white paper is submitted to the Astronomy and Astrophysics 2010 Decadal Survey (Astro2010)1 Committee on the State of the Profession to emphasize the potential of the Stratospheric Observatory for Infrared Astronomy (SOFIA) to contribute to the training of instrumentalists and observers, and to related technology developments. This potential goes beyond the primary mission of SOFIA, which is to carry out unique, high priority astronomical research. SOFIA is a Boeing 747SP aircraft with a 2.5 meter telescope. It will enable astronomical observations anywhere, any time, and at most wavelengths between 0.3 microns and 1.6 mm not accessible from ground-based observatories. These attributes, accruing from the mobility and flight altitude of SOFIA, guarantee a wealth of scientific return. Its instrument teams (nine in the first generation) and guest investigators will do suborbital astronomy in a shirt-sleeve environment. The project will invest $10M per year in science instrument development over a lifetime of 20 years. This, frequent flight opportunities, and operation that enables rapid changes of science instruments and hands-on in-flight access to the instruments, assure a unique and extensive potential - both for training young instrumentalists and for encouraging and deploying nascent technologies. Novel instruments covering optical, infrared, and submillimeter bands can be developed for and tested on SOFIA by their developers (including apprentices) for their own observations and for those of guest observers, to validate technologies and maximize observational effectiveness.Comment: 10 pages, no figures, White Paper for Astro 2010 Survey Committee on State of the Professio

Reduced Susceptibility to Interference in the Consolidation of Motor Memory before Adolescence

Are children superior to adults in consolidating procedural memory? This notion has been tied to “critical,” early life periods of increased brain plasticity. Here, using a motor sequence learning task, we show, in experiment 1, that a) the rate of learning during a training session, b) the gains accrued, without additional practice, within a 24 hours post-training interval (delayed consolidation gains), and c) the long-term retention of these gains, were as effective in 9, 12 and 17-year-olds and comparable to those reported for adults. However, a follow-up experiment showed that the establishment of a memory trace for the trained sequence of movements was significantly more susceptible to interference by a subsequent motor learning experience (practicing a reversed movement sequence) in the 17-year-olds compared to the 9 and 12-year-olds. Unlike the 17-year-olds, the younger age-groups showed significant delayed gains even after interference training. Altogether, our results indicate the existence of an effective consolidation phase in motor learning both before and after adolescence, with no childhood advantage in the learning or retention of a motor skill. However, the ability to co-consolidate different, successive motor experiences, demonstrated in both the 9 and 12-year-olds, diminishes after puberty, suggesting that a more selective memory consolidation process takes over from the childhood one. Only the adult consolidation process is gated by a recency effect, and in situations of multiple, clashing, experiences occurring within a short time-interval, adults may less effectively establish in memory experiences superseded by newer ones

Exhaustive expansion: A novel technique for analyzing complex data generated by higher-order polychromatic flow cytometry experiments

<p>Abstract</p> <p>Background</p> <p>The complex data sets generated by higher-order polychromatic flow cytometry experiments are a challenge to analyze. Here we describe Exhaustive Expansion, a data analysis approach for deriving hundreds to thousands of cell phenotypes from raw data, and for interrogating these phenotypes to identify populations of biological interest given the experimental context.</p> <p>Methods</p> <p>We apply this approach to two studies, illustrating its broad applicability. The first examines the longitudinal changes in circulating human memory T cell populations within individual patients in response to a melanoma peptide (gp100_209-2M) cancer vaccine, using 5 monoclonal antibodies (mAbs) to delineate subpopulations of viable, gp100-specific, CD8+ T cells. The second study measures the mobilization of stem cells in porcine bone marrow that may be associated with wound healing, and uses 5 different staining panels consisting of 8 mAbs each.</p> <p>Results</p> <p>In the first study, our analysis suggests that the cell surface markers CD45RA, CD27 and CD28, commonly used in historical lower order (2-4 color) flow cytometry analysis to distinguish memory from naïve and effector T cells, may not be obligate parameters in defining central memory T cells (T_CM). In the second study, we identify novel phenotypes such as CD29+CD31+CD56+CXCR4+CD90+Sca1-CD44+, which may characterize progenitor cells that are significantly increased in wounded animals as compared to controls.</p> <p>Conclusions</p> <p>Taken together, these results demonstrate that Exhaustive Expansion supports thorough interrogation of complex higher-order flow cytometry data sets and aids in the identification of potentially clinically relevant findings.</p