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.

The extrastriate visual area of the macaque monkey called MT or V5, receives its input from multiple sources. We have previously examined the synaptic connections made by V1 cells that project to MT (Anderson et al., 1998). Here, we provide a similar analysis of the projection from V2 to MT. The major target of the V2 projection in MT is layer 4, where it forms clusters of asymmetric (excitatory) synapses. Unlike the V1 projection, it also forms synapses in layers 1 and 2 and does not form synapses in layer 6. The most frequently encountered targets of boutons labeled from V2 were spines (67% in layer 4; 82% in layer 2/3). Unusually, only 5/12 boutons examined in layer 1 actually formed synapses. Unlike the V1 projection, multisynaptic boutons were rare (mean, 1.1 synapses per bouton vs. 1.7 for the V1 projection). Like the V1 projection, the input to MT from any point in V2 is sparse (contributing approximately 4-6% of the asymmetric synapses in the densest clusters in layer 4). The synapses of the V2 projection were similar in size to those of the V1 projection (0.1 microm(2) vs. 0.09 microm(2)) and both formed more complex postsynaptic densities on spines than on dendritic shafts. The clear differences between the V1 and V2 projection to MT indicate that their functions are complementary rather than completely overlapping.

/pdf/connection-from-cortical-area-v2-to-mt-in-macaque-monkey-3jgnx5p6f9.pdf

Connection from cortical area V2 to MT in macaque monkey.

Publisher Summary This chapter illustrates the mechanisms of gamma-aminobutyric acid (GABA)-mediated synaptic inhibition. In the neocortex, there is no structural evidence for the pre-synaptic inhibitory mechanisms that were described by Eccles in the spinal cord. Therefore, it is assumed that cortical inhibition acts primarily through post-synaptic mechanisms. The action of the inhibitory synapses is to produce an outward current that opposes the inward current produced by the excitatory synapses. In theoretical analyses of post-synaptic inhibition, it has been convenient to divide the post-synaptic effects into two types: hyperpolarizing inhibition and shunting inhibition. Both act by increasing the permeability or conductance of the membrane to ions whose reversal potentials are near (shunting) or more negative (hyperpolarizing) than the resting membrane potential. This distinction between shunting and hyperpolarizing inhibition is to some extent artificial, particularly in whole animal recordings, where the concept of a resting membrane potential has to be considerably stretched to be an accurate description of the data.

Chapter 21 GABA-mediated inhibition in the neural networks of visual cortex

Thirty-four years since the small nervous system of the nematode C. elegans was manually reconstructed in the electron microscope (EM)1, ‘high-throughput’ EM techniques now enable the dense reconstruction of neural circuits within increasingly large brain volumes at synaptic resolution2–6. As with C. elegans, however, a key limitation for inferring brain function from neuronal wiring diagrams is that it remains unknown how the structure of a synapse seen in EM relates to its physiological transmission strength. Here, we related structure and function of the same synapses to bridge this gap: we combined paired whole-cell recordings of synaptically connected pyramidal neurons in slices of mouse somatosensory cortex with correlated light microscopy and high-resolution EM of all putative synaptic contacts between the neurons. We discovered a linear relationship between synapse size (postsynaptic density area) and synapse strength (excitatory postsynaptic potential amplitude), which provides an experimental foundation for assigning the actual physiological weights to synaptic connections seen in the EM. Furthermore, quantal analysis revealed that the number of vesicle release sites exceeded the number of anatomical synapses formed by a connection by a factor of at least 2.6, which challenges the current understanding of synaptic release in neocortex and suggests that neocortical synapses operate with multivesicular release, like hippocampal synapses7–11. Thus, neocortical synapses are more complex computational devices and may modulate their strength more flexibly than previously thought, with the corollary that the canonical neocortical microcircuitry possesses significantly higher computational power than estimated by current models.

https://biorxiv.org/content/biorxiv/early/2019/12/13/2019.12.13.875971.full-text.pdf

Structure and function of a neocortical synapse

Neurons in primary visual cortex of many mammals are clustered according to their preference to stimulus parameters such as orientation and spatial frequency. Nevertheless, responses to complex visual stimuli are highly heterogeneous between adjacent neurons. To investigate the relation between these observations, we recorded from pairs of neighboring neurons in area 17 of anesthetized cats in response to stimuli of differing complexity: sinusoidal drifting gratings, binary dense noise, and natural movies. Comparisons of the tuning curves revealed similar orientation and direction preferences for neighboring neurons, but large differences in preferred phase, direction selectivity, and tuning width of spatial frequency. No pair was similar across all tuning properties. The neurons' firing rates averaged across multiple stimulus repetitions (the “signal”) were also compared. Binned between 10 and 200 ms, the correlation between these signals was close to zero in the median across all pairs for all stimulus classes. Signal correlations agreed poorly with differences in tuning properties, except for receptive field offset and relative modulation (i.e., the strength of phase modulation). Nonetheless, signal correlations for different stimulus classes were well correlated with each other, even for gratings and movies. Conversely, trial-to-trial fluctuations (termed “noise”) were poorly correlated between neighboring neurons, suggesting low degrees of common input. In response to gratings and visual noise, signal and noise correlations were well correlated with each other, but less so for responses to movies. These findings have relevance for our understanding of the processing of natural stimuli in a functionally heterogeneous cortical network.

https://www.jneurosci.org/content/jneuro/33/17/7325.full.pdf

Functional Heterogeneity in Neighboring Neurons of Cat Primary Visual Cortex in Response to Both Artificial and Natural Stimuli

The major target of the V4 projection in V2 is layer 1, where it forms a tangential spread of asymmetric (excitatory) synapses. This is characteristic of a "feedback" projection. Some axons formed discrete clusters of bouton terminaux between lengths of myelinated axon, while others were unbranched and formed a continuous distribution of en passant boutons with no intercalated myelin. Minor projections were found in layers 2/3 and 6. Dendritic spines were the most frequently encountered targets of the V4 projection (80% in layer 1 and layer 2/3, 94% in layer 6). The remaining targets were dendritic shafts. In layer 1, 69% of target dendrites (12% of all targets) had characteristics identifying them as smooth (GABAergic) cells. In layer 2/3 and layer 6 virtually all the shaft synapses were on smooth dendrites (86% and 100%, respectively). Multisynaptic boutons were rare (mean 1.1 synapses per bouton). Synapses formed in layer 6 were smaller than those of layer 1 (mean area 0.073 microm(2) vs. 0.117 microm(2)). Synapses formed with spines had a more complex postsynaptic density than those formed with dendritic shafts. With respect to targets and synaptic type and size and morphology of synapses, the feedback projection from V4 to V2 resembles those of feedforward projections. The principal difference between the feedforward and feedback projection is in the lamina location of their terminal boutons. The concentration of the V4 projection on layer 1, where it forms asymmetric synapses mainly with spines, suggests that it excites the distal apical dendrites of pyramidal cells.

/pdf/synaptic-connection-from-cortical-area-v4-to-v2-in-macaque-2dsls5iqc4.pdf

Kevan A. C. Martin

Papers

Connection from cortical area V2 to MT in macaque monkey.

Chapter 21 GABA-mediated inhibition in the neural networks of visual cortex

Structure and function of a neocortical synapse

Functional Heterogeneity in Neighboring Neurons of Cat Primary Visual Cortex in Response to Both Artificial and Natural Stimuli

Synaptic connection from cortical area V4 to V2 in macaque monkey.