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

https://www2.econ.iastate.edu/tesfatsi/DeepLearningInNeuralNetworksOverview.JSchmidhuber2015.pdf

Deep learning in neural networks

We have developed a near-real-time computer system that can locate and track a subject's head, and then recognize the person by comparing characteristics of the face to those of known individuals. The computational approach taken in this system is motivated by both physiology and information theory, as well as by the practical requirements of near-real-time performance and accuracy. Our approach treats the face recognition problem as an intrinsically two-dimensional (2-D) recognition problem rather than requiring recovery of three-dimensional geometry, taking advantage of the fact that faces are normally upright and thus may be described by a small set of 2-D characteristic views. The system functions by projecting face images onto a feature space that spans the significant variations among known face images. The significant features are known as "eigenfaces," because they are the eigenvectors (principal components) of the set of faces; they do not necessarily correspond to features such as eyes, ears, and noses. The projection operation characterizes an individual face by a weighted sum of the eigenface features, and so to recognize a particular face it is necessary only to compare these weights to those of known individuals. Some particular advantages of our approach are that it provides for the ability to learn and later recognize new faces in an unsupervised manner, and that it is easy to implement using a neural network architecture.

/pdf/eigenfaces-for-recognition-1vpm5kz4jh.pdf

Eigenfaces for recognition

▪ Abstract The prefrontal cortex has long been suspected to play an important role in cognitive control, in the ability to orchestrate thought and action in accordance with internal goals. Its neural basis, however, has remained a mystery. Here, we propose that cognitive control stems from the active maintenance of patterns of activity in the prefrontal cortex that represent goals and the means to achieve them. They provide bias signals to other brain structures whose net effect is to guide the flow of activity along neural pathways that establish the proper mappings between inputs, internal states, and outputs needed to perform a given task. We review neurophysiological, neurobiological, neuroimaging, and computational studies that support this theory and discuss its implications as well as further issues to be addressed

/pdf/an-integrative-theory-of-prefrontal-cortex-function-2j9unprn5f.pdf

An integrative theory of prefrontal cortex function

A baseline or control state is fundamental to the understanding of most complex systems. Defining a baseline state in the human brain, arguably our most complex system, poses a particular challenge. Many suspect that left unconstrained, its activity will vary unpredictably. Despite this prediction we identify a baseline state of the normal adult human brain in terms of the brain oxygen extraction fraction or OEF. The OEF is defined as the ratio of oxygen used by the brain to oxygen delivered by flowing blood and is remarkably uniform in the awake but resting state (e.g., lying quietly with eyes closed). Local deviations in the OEF represent the physiological basis of signals of changes in neuronal activity obtained with functional MRI during a wide variety of human behaviors. We used quantitative metabolic and circulatory measurements from positron-emission tomography to obtain the OEF regionally throughout the brain. Areas of activation were conspicuous by their absence. All significant deviations from the mean hemisphere OEF were increases, signifying deactivations, and resided almost exclusively in the visual system. Defining the baseline state of an area in this manner attaches meaning to a group of areas that consistently exhibit decreases from this baseline, during a wide variety of goal-directed behaviors monitored with positron-emission tomography and functional MRI. These decreases suggest the existence of an organized, baseline default mode of brain function that is suspended during specific goal-directed behaviors.

/pdf/a-default-mode-of-brain-function-zwenkbmjw7.pdf

A default mode of brain function.

Human amygdala compared to orbitofrontal cortex connectivity, and emotion

Objective:
To investigate the relation between parental age, and behavioral, cognitive and brain differences in the children.

Method:
Data with children aged 9–11 of 8709 mothers with parental age 15–45 years were analyzed from the Adolescent Brain Cognitive Development (ABCD) study. A general linear model was used to test the associations of the parental age with brain structure, and behavioral and cognitive problems scores.

Results:
Behavioral and cognitive problems were greater in the children of the younger mothers, and were associated with lower volumes of cortical regions in the children. There was a linear correlation between the behavioral and cognitive problems scores, and the lower brain volumes (r > 0.6), which was evident when parental age was included as a stratification factor. The regions with lower volume included the anterior cingulate cortex, medial and lateral orbitofrontal cortex and amygdala, parahippocampal gyrus and hippocampus, and temporal lobe (FDR corrected p < 0.01). The lower cortical volumes and areas in the children significantly mediated the association between the parental age and the behavioral and cognitive problems in the children (all p < 10−4). The effects were large, such as the 71.4% higher depressive problems score, and 27.5% higher rule-breaking score, in the children of mothers aged 15–19 than the mothers aged 34–35.

Conclusions:
Lower parental age is associated with behavioral problems and reduced cognitive performance in the children, and these differences are related to lower volumes and areas of some cortical regions which mediate the effects in the children. The findings are relevant to psychiatric understanding and assessment.

Association between parental age, brain structure, and behavioral and cognitive problems in children.

In this paper the different types of neural processing involved in motivational behavior will be considered. This processing involves, for feeding, the example of motivational behavior considered here, a number of different processes. These processes include first identification of which environmental stimuli are food, often with the assistance of prior learning. Second, modulation of neuronal responses by motivation occurs, so that for example some neurons respond to food only when the animal is hungry. This provides specificity to motivational behavior: when the animal is hungry, behavioral responses occur to food but not to water. Third, this processing must gain access to motor output mechanisms, so that behavioral responses such as feeding or drinking can be produced. Evidence that the neural control of feeding is organized in this way at least in higher vertebrates is provided below, and particular attention is paid to the operation of these neural controls in species as close to man as possible, macaque monkeys, to ensure that the results are as relevant to the controls of food intake and their abnormalities in man as possible.

Edmund T. Rolls

Papers

Human amygdala compared to orbitofrontal cortex connectivity, and emotion

Association between parental age, brain structure, and behavioral and cognitive problems in children.

Neurophysiological Processing Related to Feeding in the Monkey

Absolute refractory period of neurones involved in drinking elicited by electrical stimulation of the lateral hypothalamus.

Neural Mechanisms of Visual Memory: A Neurocomputational Perspective