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.

https://www.fil.ion.ucl.ac.uk/spm/doc/papers/karl_ppi.pdf

Psychophysiological and modulatory interactions in neuroimaging.

The orbitofrontal cortex (OFC) is implicated in emotion and emotion-related learning. Using event-related functional magnetic resonance imaging (fMRI), we measured brain activation in human subjects doing an emotion-related visual reversal-learning task in which choice of the correct stimulus led to a probabilistically determined 'monetary' reward and choice of the incorrect stimulus led to a monetary loss. Distinct areas of the OFC were activated by monetary rewards and punishments. Moreover, in these areas, we found a correlation between the magnitude of the brain activation and the magnitude of the rewards and punishments received. These findings indicate that one emotional involvement of the human orbitofrontal cortex is its representation of the magnitudes of abstract rewards and punishments, such as receiving or losing money.

http://www.kringelbach.org/papers/nn_Odoherty2001.pdf

Abstract reward and punishment representations in the human orbitofrontal cortex.

https://www.ece.uvic.ca/~bctill/papers/learning/Kringelbach_Rolls_2004.pdf

The functional neuroanatomy of the human orbitofrontal cortex: evidence from neuroimaging and neuropsychology

The primate orbitofrontal cortex contains the secondary taste cortex, in which the reward value of taste is represented. It also contains the secondary and tertiary olfactory cortical areas, in which information about the identity and also about the reward value of odors is represented. The orbitofrontal cortex also receives information about the sight of objects and faces from the temporal lobe cortical visual areas, and neurons in it learn and reverse the visual stimulus to which they respond when the association of the visual stimulus with a primary reinforcing stimulus (such as a taste reward) is reversed. However, the orbitofrontal cortex is involved in representing negative reinforcers (punishers) too, such as aversive taste, and in rapid stimulus–reinforcement association learning for both positive and negative primary reinforcers. In complementary neuroimaging studies in humans it is being found that areas of the orbitofrontal cortex (and connected subgenual cingulate cortex) are activated by pleasant touch, by painful touch, by rewarding and aversive taste, and by odor. Damage to the orbitofrontal cortex in humans can impair the learning and reversal of stimulus– reinforcement associations, and thus the correction of behavioral responses when these are no longer appropriate because previous reinforcement contingencies change. This evidence thus shows that the orbitofrontal cortex is involved in decoding and representing some primary reinforcers such as taste and touch; in learning and reversing associations of visual and other stimuli to these primary reinforcers; and in controlling and correcting reward-related and punishment-related behavior, and thus in emotion. The prefrontal cortex is the cortex that receives projections from the mediodorsal nucleus of the thalamus and is situated in front of the motor and premotor cortices (areas 4 and 6) in the frontal lobe. Based on the divisions of the mediodorsal nucleus, the prefrontal cortex may be divided into three main regions (Fuster, 1997). First, the magnocellular, medial, part of the mediodorsal nucleus projects to the orbital (ventral) surface of the prefrontal cortex (which includes areas 13 and 12). This part of the prefrontal cortex is called the orbitofrontal cortex, and receives information from the ventral or object-processing visual stream, and taste, olfactory and somatosensory inputs. Second, the parvocellular, lateral, part of the mediodorsal nucleus projects to the dorsolateral prefrontal cortex. This part of the prefrontal cortex receives inputs from the parietal cortex and is involved in tasks such as spatial short-term memory tasks (Fuster, 1997; Rolls

/pdf/the-orbitofrontal-cortex-and-reward-11vi53s9t3.pdf

The Orbitofrontal Cortex and Reward

The brain control of feeding and reward the nature of emotion the neural bases of emotion brain-stimulation reward pharmacology and neurochemisty of reward, and neural output systems for reward brain mechanisms for thirst sexual behaviour, reward, and brain function a theory of consciousness, and its application to understanding emotion and pleasure reward, punishment, and emotion in brain design. Appendix: Neural networks and emotion-related learning.

Edmund T. Rolls

Papers

Psychophysiological and modulatory interactions in neuroimaging.

Abstract reward and punishment representations in the human orbitofrontal cortex.

The functional neuroanatomy of the human orbitofrontal cortex: evidence from neuroimaging and neuropsychology

The Orbitofrontal Cortex and Reward

The Brain and Emotion