Modelling fast forms of visual neural plasticity using a modified second-order motion energy model

The Adelson-Bergen motion energy sensor is well established as the leading model of low-level visual motion sensing in human vision. However, the standard model cannot predict adaptation effects in motion perception. A previous paper Pavan et al.(Journal of Vision 10:1-17, 2013) presented an extension to the model which uses a first-order RC gain-control circuit (leaky integrator) to implement adaptation effects which can span many seconds, and showed that the extended model's output is consistent with psychophysical data on the classic motion after-effect. Recent psychophysical research has reported adaptation over much shorter time periods, spanning just a few hundred milliseconds. The present paper further extends the sensor model to implement rapid adaptation, by adding a second-order RC circuit which causes the sensor to require a finite amount of time to react to a sudden change in stimulation. The output of the new sensor accounts accurately for psychophysical data on rapid forms of facilitation (rapid visual motion priming, rVMP) and suppression (rapid motion after-effect, rMAE). Changes in natural scene content occur over multiple time scales, and multi-stage leaky integrators of the kind proposed here offer a computational scheme for modelling adaptation over multiple time scales. © 2014 Springer Science+Business Media New York

Recovering Dietary Information from Extant and Extinct Primates Using Plant Microremains

When reconstructing the diets of primates, researchers often rely on several well established methods, such as direct observation, studies of discarded plant parts, and analysis of macrobotanical remains in fecal matter. Most of these studies can be performed only on living primate groups, however, and the diets of extinct, subfossil, and fossil groups are known only from proxy methods. Plant microremains, tiny plant structures with distinctive morphologies, can record the exact plant foods that an individual consumed. They can be recovered from recently deceased and fossil primate samples, and can also be used to supplement traditional dietary analyses in living groups. Here I briefly introduce plant microremains, provide examples of how they have been successfully used to reconstruct the diets of humans and other species, and describe methods for their application in studies of primate dietary ecology

Pediatric T- and NK-cell lymphomas: new biologic insights and treatment strategies

T- and natural killer (NK)-cell lymphomas are challenging childhood neoplasms. These cancers have varying presentations, vast molecular heterogeneity, and several are quite unusual in the West, creating diagnostic challenges. Over 20 distinct T- and NK-cell neoplasms are recognized by the 2008 World Health Organization classification, demonstrating the diversity and potential complexity of these cases. In pediatric populations, selection of optimal therapy poses an additional quandary, as most of these malignancies have not been studied in large randomized clinical trials. Despite their rarity, exciting molecular discoveries are yielding insights into these clinicopathologic entities, improving the accuracy of our diagnoses of these cancers, and expanding our ability to effectively treat them, including the use of new targeted therapies. Here, we summarize this fascinating group of lymphomas, with particular attention to the three most common subtypes: T-lymphoblastic lymphoma, anaplastic large cell lymphoma, and peripheral T-cell lymphoma-not otherwise specified. We highlight recent findings regarding their molecular etiologies, new biologic markers, and cutting-edge therapeutic strategies applied to this intriguing class of neoplasms

ICF, An Immunodeficiency Syndrome: DNA Methyltransferase 3B Involvement, Chromosome Anomalies, and Gene Dysregulation

The immunodeficiency, centromeric region instability, and facial anomalies syndrome (ICF) is the only disease known to result from a mutated DNA methyltransferase gene, namely, DNMT3B. Characteristic of this recessive disease are decreases in serum immunoglobulins despite the presence of B cells and, in the juxtacentromeric heterochromatin of chromosomes 1 and 16, chromatin decondensation, distinctive rearrangements, and satellite DNA hypomethylation. Although DNMT3B is involved in specific associations with histone deacetylases, HP1, other DNMTs, chromatin remodelling proteins, condensin, and other nuclear proteins, it is probably the partial loss of catalytic activity that is responsible for the disease. In microarray experiments and real-time RT-PCR assays, we observed significant differences in RNA levels from ICF vs. control lymphoblasts for pro- and anti-apoptotic genes (BCL2L10, CASP1, and PTPN13); nitrous oxide, carbon monoxide, NF-κB, and TNFa signalling pathway genes (PRKCH, GUCY1A3, GUCY1B3, MAPK13; HMOX1, and MAP4K4); and transcription control genes (NR2F2 and SMARCA2). This gene dysregulation could contribute to the immunodeficiency and other symptoms of ICF and might result from the limited losses of DNA methylation although ICF-related promoter hypomethylation was not observed for six of the above examined genes. We propose that hypomethylation of satellite 2at1qh and 16qh might provoke this dysregulation gene expression by trans effects from altered sequestration of transcription factors, changes in nuclear architecture, or expression of noncoding RNAs

Spike-Based Bayesian-Hebbian Learning of Temporal Sequences

Many cognitive and motor functions are enabled by the temporal representation and processing of stimuli, but it remains an open issue how neocortical microcircuits can reliably encode and replay such sequences of information. To better understand this, a modular attractor memory network is proposed in which meta-stable sequential attractor transitions are learned through changes to synaptic weights and intrinsic excitabilities via the spike-based Bayesian Confidence Propagation Neural Network (BCPNN) learning rule. We find that the formation of distributed memories, embodied by increased periods of firing in pools of excitatory neurons, together with asymmetrical associations between these distinct network states, can be acquired through plasticity. The model's feasibility is demonstrated using simulations of adaptive exponential integrate-and-fire model neurons (AdEx). We show that the learning and speed of sequence replay depends on a confluence of biophysically relevant parameters including stimulus duration, level of background noise, ratio of synaptic currents, and strengths of short-term depression and adaptation. Moreover, sequence elements are shown to flexibly participate multiple times in the sequence, suggesting that spiking attractor networks of this type can support an efficient combinatorial code. The model provides a principled approach towards understanding how multiple interacting plasticity mechanisms can coordinate hetero-associative learning in unison

La Lanterne : journal politique quotidien

03 août 18951895/08/03 (N929,A12)