Neural Correlates of Human Associative Learning

Lesion studies in animals have associated the amygdala mainly with aversive conditioning,both cued and contextual.However,neurophysiological studies indicate that the amygdala has a role in the processing of positive emotions in some kinds of stimulusreward learning.The aim of the current study was to extend these findings to humans.Functional magnetic resonance imaging was applied to investigate the neural basis of aversive and appetitive conditioning.In the first study,aversive electrical shocks were deli...     

Role of experience and oscillations in transforming a rate code into a temporal code

In the vast majority of brain areas, the firing rates of neurons, averaged over several hundred milliseconds to several seconds, can be strongly modulated by, and provide accurate information about, properties of their inputs. This is referred to as the rate code. However, the biophysical laws of synaptic plasticity require precise timing of spikes over short timescales (<10 ms). Hence it is critical to understand the physiological mechanisms that can generate precise spike timing in vivo, and the relationship between such a temporal code and a rate code. Here we propose a mechanism by which a temporal code can be generated through an interaction between an asymmetric rate code and oscillatory inhibition. Consistent with the predictions of our model, the rate and temporal codes of hippocampal pyramidal neurons are highly correlated. Furthermore, the temporal code becomes more robust with experience. The resulting spike timing satisfies the temporal order constraints of hebbian learning. Thus, oscillations and receptive field asymmetry may have a critical role in temporal sequence learning.     

Postsynaptic hyperpolarization during conditioning reversibly blocks induction of long-term potentiation

Activity-induced changes in the efficacy of synaptic transmission between neurones are central to several prominent theories of learning. In both in vivo and in vitro preparations of the hippocampus, a conditioning high-frequency stimulus delivered to afferent fibres results in a long-term potentiation of synaptic transmission at those inputs. Evidence has been provided supporting both presynaptic and postsynaptic sites as loci where critical events occur in the development of potentiation. In this study we report that long-term potentiation is reversibly blocked by intracellular injection of hyperpolarizing current in the postsynaptic cell during the conditioning high-frequency stimulus, suggesting the involvement of a voltage-dependent postsynaptic mechanism.     

Neurons in medial prefrontal cortex signal memory for fear extinction

Conditioned fear responses to a tone previously paired with a shock diminish if the tone is repeatedly presented without the shock, a process known as extinction. Since Pavlov it has been hypothesized that extinction does not erase conditioning, but forms a new memory. Destruction of the ventral medial prefrontal cortex, which consists of infralimbic and prelimbic cortices, blocks recall of fear extinction, indicating that medial prefrontal cortex might store long-term extinction memory. Here we show that infralimbic neurons recorded during fear conditioning and extinction fire to the tone only when rats are recalling extinction on the following day. Rats that froze the least showed the greatest increase in infralimbic tone responses. We also show that conditioned tones paired with brief electrical stimulation of infralimbic cortex elicit low freezing in rats that had not been extinguished. Thus, stimulation resembling extinction-induced infralimbic tone responses is able to simulate extinction memory. We suggest that consolidation of extinction learning potentiates infralimbic activity, which inhibits fear during subsequent encounters with fear stimuli.     

Cortical substrates for exploratory decisions in humans

Decision making in an uncertain environment poses a conflict between the opposing demands of gathering and exploiting information. In a classic illustration of this 'exploration-exploitation' dilemma, a gambler choosing between multiple slot machines balances the desire to select what seems, on the basis of accumulated experience, the richest option, against the desire to choose a less familiar option that might turn out more advantageous (and thereby provide information for improving future decisions). Far from representing idle curiosity, such exploration is often critical for organisms to discover how best to harvest resources such as food and water. In appetitive choice, substantial experimental evidence, underpinned by computational reinforcement learning (RL) theory, indicates that a dopaminergic, striatal and medial prefrontal network mediates learning to exploit. In contrast, although exploration has been well studied from both theoretical and ethological perspectives, its neural substrates are much less clear. Here we show, in a gambling task, that human subjects' choices can be characterized by a computationally well-regarded strategy for addressing the explore/exploit dilemma. Furthermore, using this characterization to classify decisions as exploratory or exploitative, we employ functional magnetic resonance imaging to show that the frontopolar cortex and intraparietal sulcus are preferentially active during exploratory decisions. In contrast, regions of striatum and ventromedial prefrontal cortex exhibit activity characteristic of an involvement in value-based exploitative decision making. The results suggest a model of action selection under uncertainty that involves switching between exploratory and exploitative behavioural modes, and provide a computationally precise characterization of the contribution of key decision-related brain systems to each of these functions.     

Blocking of acquisition but not expression of conditioned fear-potentiated startle by NMDA antagonists in the amygdala

Receptors for N-methyl-D-aspartate (NMDA) seem to have a critical role in synaptic plasticity. NMDA antagonists (such as AP5) prevent induction of long-term potentiation, an activity-dependent enhancement of synaptic efficacy mediated by neural mechanisms that might also underlie learning and memory. They also attenuate memory formation in several behavioural tasks; there are few data, however, implicating an NMDA-sensitive measure of conditioning based on local infusion of antagonists into a brain area tightly coupled to the behavioural response used to assess conditioning. We now show that NMDA antagonists infused into the amygdala block the acquisition, but not the expression, of fear conditioning measured with a behavioural assay mediated by a defined neural circuit (fear-potentiation of the acoustic startle reflex). This effect showed anatomical and pharmacological specificity, and was not attributable to reduced salience of the stimuli of light or shock used in training. The data indicate that an NMDA-dependent process in the amygdala subserves associative fear conditioning.     

Neuronal correlate of visual associative long-term memory in the primate temporal cortex

In human long-term memory, ideas and concepts become associated in the learning process. No neuronal correlate for this cognitive function has so far been described, except that memory traces are thought to be localized in the cerebral cortex; the temporal lobe has been assigned as the site for visual experience because electric stimulation of this area results in imagery recall and lesions produce deficits in visual recognition of objects. We previously reported that in the anterior ventral temporal cortex of monkeys, individual neurons have a sustained activity that is highly selective for a few of the 100 coloured fractal patterns used in a visual working-memory task. Here I report the development of this selectivity through repeated trials involving the working memory. The few patterns for which a neuron was conjointly selective were frequently related to each other through stimulus-stimulus association imposed during training. The results indicate that the selectivity acquired by these cells represents a neuronal correlate of the associative long-term memory of pictures.     

数据分布特性对空调系统能耗预测的影响

空调系统能耗预测是实现智能调控、能源需求管理、系统节能的重要手段和前提之一,当前的空调系统能耗预测主要是基于机器学习算法。诸多机器学习算法的重要理论前提是数据的分布应尽量满足正态分布,然而空调系统的实际运行数据很少能满足正态分布特性,目前的研究鲜有涉及数据分布特性对空调系统能耗预测的影响。首先基于实际项目的空调系统能耗数据,从偏度和峰度两个指标分析了实际能耗数据分布与正态分布呈现出的偏离;然后通过对数变换对能耗数据进行数据变换,使能耗数据更接近于正态分布;接着以常见的4种能耗预测机器学习算法(广义线性回归算法、支持向量回归算法、人工神经网络算法、随机森林算法)对原始数据和经过数据变换后的数据分别进行空调系统能耗预测工作,分析负荷预测结果的RMSE和R~2统计量。结果对比发现,数据的分布特性对能耗预测有着重要的影响,合适的数据变换可以有效地提高空调系统能耗预测机器学习算法模型的预测效果。     

Towards Fast and Efficient Algorithm for Learning Bayesian Network

Learning Bayesian network structure is one of the most exciting challenges in machine learning. Discovering a correct skeleton of a directed acyclic graph(DAG) is the foundation for dependency analysis algorithms for this problem. Considering the unreliability of high order condition independence(CI) tests, and to improve the efficiency of a dependency analysis algorithm, the key steps are to use few numbers of CI tests and reduce the sizes of conditioning sets as much as possible. Based on these reasons and inspired by the algorithm PC, we present an algorithm, named fast and efficient PC(FEPC), for learning the adjacent neighbourhood of every variable. FEPC implements the CI tests by three kinds of orders, which reduces the high order CI tests significantly. Compared with current algorithm proposals, the experiment results show that FEPC has better accuracy with fewer numbers of condition independence tests and smaller size of conditioning sets. The highest reduction percentage of CI test is 83.3% by EFPC compared with PC algorithm.     

概念设计中机器学习技术的运用

设计中开发计算理论的一个挑战是必须能支持计算机的有效运用，这一机制允许从设计专家那儿或设计样例中取得产生，累加和转换的设计知识。而其中的一个方法是把机器学习机制综合成基于知识的支持系统，以模拟设计过程初级阶段，使设计成为一个增加和诱导学习的过程。模拟的需要产生于在不同的提取阶段获取，提炼和转移设计知识的需求，从而使得能轻而易举的熟练操作。在设计中，现有的知识产生于过去的设计解决方案，而过去的解决方案提供的反馈信息能更新和提高设计理论知识基础。但是，没有学习接受能力，设计系统不能反映设计家们在这一领域的成长经历，也不能反映设计家们从以往设计案例中提取知识的能力。在此提出了方案设计和效力评价中的三种方法。     

Corticostriatal plasticity is necessary for learning intentional neuroprosthetic skills

The ability to learn new skills and perfect them with practice applies not only to physical skills but also to abstract skills, like motor planning or neuroprosthetic actions. Although plasticity in corticostriatal circuits has been implicated in learning physical skills, it remains unclear if similar circuits or processes are required for abstract skill learning. Here we use a novel behavioural task in rodents to investigate the role of corticostriatal plasticity in abstract skill learning. Rodents learned to control the pitch of an auditory cursor to reach one of two targets by modulating activity in primary motor cortex irrespective of physical movement. Degradation of the relation between action and outcome, as well as sensory-specific devaluation and omission tests, demonstrate that these learned neuroprosthetic actions are intentional and goal-directed, rather than habitual. Striatal neurons change their activity with learning, with more neurons modulating their activity in relation to target-reaching as learning progresses. Concomitantly, strong relations between the activity of neurons in motor cortex and the striatum emerge. Specific deletion of striatal NMDA receptors impairs the development of this corticostriatal plasticity, and disrupts the ability to learn neuroprosthetic skills. These results suggest that corticostriatal plasticity is necessary for abstract skill learning, and that neuroprosthetic movements capitalize on the neural circuitry involved in natural motor learning.     

Associative long-term depression in the hippocampus induced by hebbian covariance

A brief, high-frequency activation of excitatory synapses in the hippocampus produces a long-lasting increase in synaptic strengths called long-term potentiation (LTP). A test input, which by itself does not have a long-lasting effect on synaptic strengths, can be potentiated through association when it is activated at the same time as a separate conditioning input. Neural network modelling studies have also predicted that synaptic strengths should be weakened when test and conditioning inputs are anti-correlated. Evidence for such heterosynaptic depression in the hippocampus has been found for inputs that are inactive or weakly active during the stimulation of a conditioning input, but this depression does not depend on any pattern of test input activity and does not seem to last as long as LTP. We report here an associative long-term depression (LTD) in field CA1 that is produced when a low-frequency test input is negatively correlated in time with a high-frequency conditioning input. LTD of synaptic strength is also produced by activating presynaptic terminals while a postsynaptic neuron is hyperpolarized. This confirms theoretical predictions that the mechanism for associative LTD is homosynaptic and follows a hebbian covariance rule.     

融合非偏好注意力跨度的预训练语言模型

语言模型是自然语言处理领域最重要的任务之一,并以迁移学习的方式影响着机器翻译、机器阅读理解、自动文本摘要等诸多下游任务。依托多头自注意力构建的大规模预训练语言模型在特征提取和文本表征能力上相较之前的神经网络模型取得了较大提升,却也极大地增加了模型训练的时空复杂度。为此,从模糊群决策的角度出发,将毕达哥拉斯模糊非偏好函数用作多头注意力跨度范围的先验,提出一种自适应的注意力跨度调节机制,较大程度地改善了模型捕捉长距离文本依赖的能力,并使模型的整体计算复杂度相较原始Transformer结构维持在较低水平。公开语言模型数据集上的实验表明：所提方法在困惑度指标上取得了较好的性能,超越了多种以往的方法。     

Rigorous location of phase transitions in hard optimization problems

It is widely believed that for many optimization problems, no algorithm is substantially more efficient than exhaustive search. This means that finding optimal solutions for many practical problems is completely beyond any current or projected computational capacity. To understand the origin of this extreme 'hardness', computer scientists, mathematicians and physicists have been investigating for two decades a connection between computational complexity and phase transitions in random instances of constraint satisfaction problems. Here we present a mathematically rigorous method for locating such phase transitions. Our method works by analysing the distribution of distances between pairs of solutions as constraints are added. By identifying critical behaviour in the evolution of this distribution, we can pinpoint the threshold location for a number of problems, including the two most-studied ones: random k-SAT and random graph colouring. Our results prove that the heuristic predictions of statistical physics in this context are essentially correct. Moreover, we establish that random instances of constraint satisfaction problems have solutions well beyond the reach of any analysed algorithm.     

Interactive memory systems in the human brain.

Learning and memory in humans rely upon several memory systems, which appear to have dissociable brain substrates. A fundamental question concerns whether, and how, these memory systems interact. Here we show using functional magnetic resonance imaging (FMRI) that these memory systems may compete with each other during classification learning in humans. The medial temporal lobe and basal ganglia were differently engaged across subjects during classification learning depending upon whether the task emphasized declarative or nondeclarative memory, even when the to-be-learned material and the level of performance did not differ. Consistent with competition between memory systems suggested by animal studies and neuroimaging, activity in these regions was negatively correlated across individuals. Further examination of classification learning using event-related FMRI showed rapid modulation of activity in these regions at the beginning of learning, suggesting that subjects relied upon the medial temporal lobe early in learning. However, this dependence rapidly declined with training, as predicted by previous computational models of associative learning.     

A neuronal analogue of state-dependent learning

State-dependent learning is a phenomenon in which the retrieval of newly acquired information is possible only if the subject is in the same sensory context and physiological state as during the encoding phase. In spite of extensive behavioural and pharmacological characterization, no cellular counterpart of this phenomenon has been reported. Here we describe a neuronal analogue of state-dependent learning in which cortical neurons show an acetylcholine-dependent expression of an acetylcholine-induced functional plasticity. This was demonstrated on neurons of rat somatosensory 'barrel' cortex, whose tunings to the temporal frequency of whisker deflections were modified by cellular conditioning. Pairing whisker stimulation with acetylcholine applied iontophoretically yielded selective lasting modification of responses, the expression of which depended on the presence of exogenous acetylcholine. Administration of acetylcholine during testing revealed frequency-specific changes in response that were not expressed when tested without acetylcholine or when the muscarinic antagonist, atropine, was applied concomitantly. Our results suggest that both acquisition and recall can be controlled by the cortical release of acetylcholine.     

独立同均匀分布随机变量和的高阶矩的计算

考虑到均匀分布与随机变量和的高阶矩的重要性,利用组合数学中的多项式定理和第二类Stirling数对独立同U(0,1)随机变量和的高阶矩进行了计算,得到了相应的计算公式。并以此为基础利用二项式定理,得到了独立同U(a,b)随机变量和的高阶矩的计算公式。最后给出了计算实例。     

Lesions of the human amygdala impair enhanced perception of emotionally salient events

Commensurate with the importance of rapidly and efficiently evaluating motivationally significant stimuli, humans are probably endowed with distinct faculties and maintain specialized neural structures to enhance their detection. Here we consider that a critical function of the human amygdala is to enhance the perception of stimuli that have emotional significance. Under conditions of limited attention for normal perceptual awareness-that is, the attentional blink-we show that healthy observers demonstrate robust benefits for the perception of verbal stimuli of aversive content compared with stimuli of neutral content. In contrast, a patient with bilateral amygdala damage has no enhanced perception for such aversive stimulus events. Examination of patients with either left or right amygdala resections shows that the enhanced perception of aversive words depends specifically on the left amygdala. All patients comprehend normally the affective meaning of the stimulus events, despite the lack of evidence for enhanced perceptual encoding of these events in patients with left amygdala lesions. Our results reveal a neural substrate for affective influences on perception, indicating that similar neural mechanisms may underlie the affective modulation of both recollective and perceptual experience.     

一种“时-空”域自动视频分割算法

为了进行基于对象的视频编码,视频图像往往需要被分割成单独的个体.提出了一种从时域到空域的自动视频分割算法.在时间域阶段,通过对相邻两帧变化部分的检测,找到运动目标的初步定位.在空间域阶段,采用预测分水岭算法对运动目标进行精确定位.两种方法互相补充,互相增强.另外为了解决分水岭的过分割问题,算法在小波变换后的图像上进行.实验结果表明,提出的方法不仅分割效果好,而且计算时间少,分割的结果具有更准确的语义信息和实用性.     

浅水池热源热泵的可行性研究

文章采用集总参数法和有限差分法,用编制的程序对浅水池的蓄热量进行了非稳态传热计算,并给出了各不同参数对其传热的影响;结果表明浅水池具有一定的蓄热能力,浅水池热源热泵作为小型建筑的主要空调冷热源和大型建筑的辅助设备都是切实可行的。