抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

I have developed "tennis elbow" from lugging this book around the past four weeks, but it is worth the pain, the effort, and the aspirin. It is also worth the (relatively speaking) bargain price. Including appendixes, this book contains 894 pages of text. The entire panorama of the neural sciences is surveyed and examined, and it is comprehensive in its scope, from genomes to social behaviors. The editors explicitly state that the book is designed as "an introductory text for students of biology, behavior, and medicine," but it is hard to imagine any audience, interested in any fragment of neuroscience at any level of sophistication, that would not enjoy this book. The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or

Principles of Neural Science

While logistic sigmoid neurons are more biologically plausible than hyperbolic tangent neurons, the latter work better for training multi-layer neural networks. This paper shows that rectifying neurons are an even better model of biological neurons and yield equal or better performance than hyperbolic tangent networks in spite of the hard non-linearity and non-dierentiabil ity

/pdf/deep-sparse-rectifier-neural-networks-hvuorf8vbu.pdf

Deep Sparse Rectifier Neural Networks

Research on moral judgment has been dominated by rationalist models, in which moral judgment is thought to be caused by moral reasoning. The author gives 4 reasons for considering the hypothesis that moral reasoning does not cause moral judgment; rather, moral reasoning is usually a post hoc construction, generated after a judgment has been reached. The social intuitionist model is presented as an alternative to rationalist models. The model is a social model in that it deemphasizes the private reasoning done by individuals and emphasizes instead the importance of social and cultural influences. The model is an intuitionist model in that it states that moral judgment is generally the result of quick, automatic evaluations (intuitions). The model is more consistent than rationalist models with recent findings in social, cultural, evolutionary, and biological psychology, as well as in anthropology and primatology.

https://www.motherjones.com/files/emotional_dog_and_rational_tail.pdf

The emotional dog and its rational tail: a social intuitionist approach to moral judgment.

Fluorescent calcium sensors are widely used to image neural activity. Using structure-based mutagenesis and neuron-based screening, we developed a family of ultrasensitive protein calcium sensors (GCaMP6) that outperformed other sensors in cultured neurons and in zebrafish, flies and mice in vivo. In layer 2/3 pyramidal neurons of the mouse visual cortex, GCaMP6 reliably detected single action potentials in neuronal somata and orientation-tuned synaptic calcium transients in individual dendritic spines. The orientation tuning of structurally persistent spines was largely stable over timescales of weeks. Orientation tuning averaged across spine populations predicted the tuning of their parent cell. Although the somata of GABAergic neurons showed little orientation tuning, their dendrites included highly tuned dendritic segments (5-40-µm long). GCaMP6 sensors thus provide new windows into the organization and dynamics of neural circuits over multiple spatial and temporal scales.

/pdf/ultrasensitive-fluorescent-proteins-for-imaging-neuronal-1f4lmx12cf.pdf

Ultrasensitive fluorescent proteins for imaging neuronal activity.

Receptive field properties of neurones in visual area 1 and visual area 2 in the baboon.

The axons of pyramidal neurons in the superficial layers of the neocortex of higher mammals form lateral networks of discrete clusters of synaptic boutons. In primary visual cortex the clusters are reported to link domains that share the same orientation preferences, but how individual neurons contribute to this network is unknown. Here we performed optical imaging to record the intrinsic signal, which is an indirect measure of neuronal firing, and determined the global map of orientation preferences in the cat primary visual system. In the same experiment, single cells were recorded and labelled intracellularly. We found that individual axons arborise within the retinotopic representation of the classical receptive field, but their bouton clusters were not aligned along their preferred axis of orientation along the retinotopic map. Axon clusters formed in a variety of different orientation domains, not just the like-orientation domains. This topography and heterogeneity of single-cell connectivity provides circuits for normalization and context-dependent feature processing of visual scenes.

/pdf/superficial-layer-pyramidal-cells-communicate-491ay0080v.pdf

Superficial layer pyramidal cells communicate heterogeneously between multiple functional domains of cat primary visual cortex

The axonal arbors of the different types of neocortical and thalamic neurons appear highly dissimilar when viewed in conventional 2D reconstructions. Nevertheless, we have found that their one-dimensional metrics and topologies are surprisingly similar. To discover this, we analysed the axonal branching pattern of 39 neurons (23 spiny, 13 smooth and three thalamic axons) that were filled intracellularly with horseradish peroxidase (HRP) during in vivo experiments in cat area 17. The axons were completely reconstructed and translated into dendrograms. Topological, fractal and Horton-Strahler analyses indicated that axons of smooth and spiny neurons had similar complexity, length ratios (a measure of the relative increase in the length of collateral segments as the axon branches) and bifurcation ratios (a measure of the relative increase in the number of collateral segments as the axon branches). We show that a simple random branching model (Galton-Watson process) predicts with reasonable accuracy the bifurcation ratio, length ratio and collateral length distribution of the axonal arbors.

/pdf/axons-in-cat-visual-cortex-are-topologically-self-similar-48i55ntmlj.pdf

Axons in Cat Visual Cortex are Topologically Self-similar

Simple cells in layer 4 of the primary visual cortex of the cat show contrast-invariant orientation tuning, in which the amplitude of the peak response is proportional to the stimulus contrast but the width of the tuning curve hardly changes with contrast. This study uses a detailed model of spiny stellate cells (SSCs) from cat area 17 to explain this property. The model integrates our experimental data, including morphological and intrinsic membrane properties and the number and spatial distribution of four major synaptic input sources of the SSC: the dorsal lateral geniculate nucleus (dLGN) and three cortical sources. The model also includes synaptic properties of these inputs. The cortical input served as sources of background activity, and visual stimuli was modeled as sinusoidal grating. For all contrasts, strong synaptic depression of the dLGN feedforward afferents compresses the firing rates in response to orthogonal stimuli, keeping these rates at practically the same low level. However, at preferred orientations, despite synaptic depression, firing rate changes as a function of contrast. Thus, when embedded in an active network, strong synaptic depression can explain contrast-invariant orientation tuning of simple cells. This is true also when the dLGN inputs are partially depressed as a result of their spontaneous activity and to some extent also when parameters were fitted to a more moderate level of synaptic depression. The model response is in close agreement with experimental results, in terms of both output spikes and membrane voltage (amplitude and fluctuations), with reasonable exceptions given that recurrent connections were not incorporated.

/pdf/a-biologically-realistic-model-of-contrast-invariant-yur0zwvhh9.pdf

A biologically realistic model of contrast invariant orientation tuning by thalamocortical synaptic depression

Signal restoration is necessary to perform computations of significant complexity. In digital computers each state variable is restored to a binary value, but this strategy is incompatible with analog computation. Nevertheless, cortical neurons, whose major mode of operation is analog, are able to perform prodigious feats of computation. The authors' research on visual cortex suggests that cortical neurons are able to compute reliably because they are organized into populations in which the signal at each neuron is restored to an appropriate analog value by a collective strategy. The strategy depends on feedback amplification that restores an input signal towards a stored analog memory. This principle is similar to recall by autoassociative neural networks. Networks of cortical amplifiers can solve simple visual processing tasks. They are well-suited to sensory processing because the same principle that restores their analog signals can also extract meaningful features from ambiguous sensory input. The authors describe a hybrid analog-digital CMOS architecture for constructing networks of cortical amplifiers. This neuromorphic architecture is a step towards exploring analog computers whose distributed signal restoration permits them to perform reliably sequential computations of great depth. >

/pdf/hybrid-analog-digital-architectures-for-neuromorphic-systems-4r4nn1k0rv.pdf

Kevan A. C. Martin

Papers

Receptive field properties of neurones in visual area 1 and visual area 2 in the baboon.

Superficial layer pyramidal cells communicate heterogeneously between multiple functional domains of cat primary visual cortex

Axons in Cat Visual Cortex are Topologically Self-similar

A biologically realistic model of contrast invariant orientation tuning by thalamocortical synaptic depression

Hybrid analog-digital architectures for neuromorphic systems