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Studies on the mode of tangential migration of developing GABAergic neurons, with special reference to their birthdate 发育中的gaba能神经元切向迁移模式的研究,特别参考它们的出生日期
Pub Date : 2005-07-19 DOI: 10.1109/DEVLRN.2005.1490975
S. Tada, F. Murakami
Appropriate arrangement of neurons in the cerebral cortex during development is important to establish higher functions in adulthood such as learning and memory. During development, neurons migrate from their born site to their final destination. There are excitatory projection neurons and inhibitory interneurons in the cerebral cortex. These two types of neurons migrate with each characteristic mode of migration. Projection neurons are born in the ventricular zone and migrate radially to their final position in the cerebral cortex, whereas GABAergic neurons are born in the medial ganglionic eminence (MGE) and migrate tangentially to the cortex. The mode of tangential migration seems to be more complicated than that of radial migration. There seems to be lack of detailed information about the mode of tangential migration. In the present study, we examined mode of tangential migration of developing GABAergic neurons which were destined to be cortical GABAergic neurons, with special reference to their birth date, by using BrdU (bromodeoxyuridine, which is incorporated into cells of mitotic phase) labeling
发育过程中大脑皮层神经元的合理排列对于成年后学习和记忆等高级功能的建立至关重要。在发育过程中,神经元从它们的出生位置迁移到它们的最终目的地。大脑皮层有兴奋性投射神经元和抑制性中间神经元。这两种类型的神经元以各自特有的迁移方式迁移。投射神经元产生于脑室区并径向迁移至大脑皮层的最终位置,而gaba能神经元产生于内侧神经节隆起(MGE)并切向迁移至皮层。切向迁移模式似乎比径向迁移模式更为复杂。似乎缺乏关于切向迁移模式的详细信息。在本研究中,我们使用BrdU(溴脱氧尿苷,有丝分裂期细胞内的结合物)标记,研究了发育中的gabaergy神经元的切向迁移模式,并特别参考了它们的出生日期
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引用次数: 0
Dynamic Hierarchical Firing within a Single Layered Network: A Model of the PFC 单层网络中的动态分层触发:PFC模型
Pub Date : 2005-07-19 DOI: 10.1109/DEVLRN.2005.1490942
M. Watanabe, K. Aihara
We propose a single layered neural network model of the prefrontal cortex which shows dynamic hierarchical firing, that is to say, sensory input is gradually translated into motor output along time. Such hierarchical firing is actually observed in the monkey prefrontal cortex (PFC), but its development remains an open question. The numerical analysis of the model indicated that the feedback signals from the premotor cortex may play an important role in the development of hierarchical firing
我们提出了一个单层的前额叶皮层神经网络模型,该模型显示了动态的分层放电,也就是说,随着时间的推移,感觉输入逐渐转化为运动输出。这种分层放电实际上在猴子的前额叶皮层(PFC)中被观察到,但它的发育仍然是一个悬而未决的问题。模型的数值分析表明,来自运动前皮层的反馈信号可能在分层放电的发展中起重要作用
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引用次数: 0
Does Pointing Comprehension Disturb Controlling Action? :Evidence from 2-year-old children 手指理解会干扰控制动作吗?来自2岁儿童的证据
Pub Date : 2005-07-19 DOI: 10.1109/DEVLRN.2005.1490952
Y. Moriguchi, S. Itakura
This study investigated whether 2-year-old children failed to control actions when they were given wrong social cues by another person in a searching task. In a control session, children observed an experimenter hid a toy in one of three cups. Then they were allowed to search a toy. In a test session, children observed a toy was hidden in one of three cups. Then one experimenter asked the other experimenter to point the cup in which a toy was hidden. After she pointed the wrong cup in which there was no toy; children were allowed to search a toy. Result indicated that children were more likely to fail to search a toy in the test session than in the control session. This suggested that children made a strong representation when they were given wrong social cues by another person and could not inhibit the representation when they search a toy. This is the first study which suggested that children social cognition disturb their controlling actions
这项研究调查了2岁的孩子在搜索任务中,当别人给他们错误的社交线索时,他们是否无法控制自己的行为。在对照实验中,孩子们观察实验者将一个玩具藏在三个杯子中的一个里。然后他们被允许搜查一个玩具。在一个测试阶段,孩子们观察到一个玩具藏在三个杯子中的一个。然后一名实验者让另一名实验者指着藏着玩具的杯子。在她指错了没有玩具的杯子之后;孩子们被允许搜查玩具。结果表明,孩子们在测试阶段比在控制阶段更容易找不到玩具。这表明,当别人给孩子错误的社交线索时,他们会产生强烈的表征,而当他们寻找玩具时,他们无法抑制这种表征。这是第一次有研究表明儿童的社会认知会干扰他们的控制行为
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引用次数: 3
It's a Child's Game: Investigating Cognitive Development with Playing Robots 这是一个孩子的游戏:通过玩机器人调查认知发展
Pub Date : 2005-07-19 DOI: 10.1109/DEVLRN.2005.1490970
Birger Johansson Lund
To study and simulate cognitive development, it is useful to find a natural domain where many cognitive functions are needed and, but where the complexity of the environment and task is reasonable. We suggest that childrens games constitute a suitable domain. The ability to play is a very fundamental part of children's daily life and it is crucial for the future development of our behaviors in Bekoff and Byers (1998). In the individual domain, the coordination of the body is an important feature of play. When a child plays, it refines its motor and sensory skills and develops more advanced movement patterns e.g. in running or cycling. When playing among other individuals, cognitive functions for social interactions and coordination and emotional control are also used. Trafton et al. (2003) programmed a robot to model a 3-4 year old child playing hide and seek. The robot moves around in their laboratory and tries to hide behind different objects and learn which hiding places what are good ones. Games like hide and seek, tag and other popular children's games were used. By bringing the best developmental and learning models together, hopes to find out more about the mechanisms of cognitive development
为了研究和模拟认知发展,找到一个需要许多认知功能的自然领域是有用的,但环境和任务的复杂性是合理的。我们建议儿童游戏构成一个合适的领域。Bekoff和Byers(1998)认为,玩耍的能力是儿童日常生活中非常基本的一部分,对我们未来的行为发展至关重要。在个人领域,身体的协调性是玩耍的一个重要特征。当孩子玩耍时,他们的运动和感觉技能会得到完善,并发展出更高级的运动模式,例如跑步或骑自行车。当与其他个体一起游戏时,也会使用社会互动、协调和情绪控制的认知功能。Trafton等人(2003)编写了一个机器人来模拟一个3-4岁的孩子玩捉迷藏。机器人在他们的实验室里四处移动,试图躲在不同的物体后面,并了解哪些藏身之处是好的。游戏像捉迷藏,标签和其他流行的儿童游戏被使用。通过将最好的发展和学习模型结合在一起,希望找到更多关于认知发展机制的信息
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引用次数: 8
Familiar Behaviors Evaluation for a Robotic Interface of Practicality and Familiarity 机器人界面实用性和熟悉性的熟悉行为评价
Pub Date : 2005-07-19 DOI: 10.1109/DEVLRN.2005.1490965
D. Yamamoto, M. Doi, N. Matsuhira, H. Ueda, M. Kidode
Robotic interfaces for home applications need a combination of practical behaviors and familiar behaviors. Recently, robotic interfaces have been attracting attention in view of their potential to serve as intermediaries between complicated information equipment and users. Such an interface requires practical behaviors to execute the user's orders securely, and also familiar behaviors to accept the user's orders exactly. Following the example of Piaget's circular reactions, the robot repeats the user's instructions. For example, when the robot interface receives user's channel change request, it not only changes the channel but also speaks in a friendly manner, e.g. saying "the 4th channel, the 4th channel." The user naturally thinks that the robot understands the request exactly. Based on this concept, a new robotic interface combines practicality and familiarity. In this paper, the effects of familiar behaviors installed in a robotic information home appliance, "ApriAlphatrade", are studied. The experimental results show that the task execution with speech repetition, object gazing and moving to object has the highest score for the familiar factor. Elderly people tend to prefer familiar behaviors more than young people do
家庭应用的机器人界面需要实际行为和熟悉行为的结合。最近,机器人界面由于具有作为复杂信息设备和用户之间的中介的潜力而引起了人们的注意。这样的界面需要实用的行为来安全地执行用户的命令,也需要熟悉的行为来准确地接受用户的命令。以皮亚杰的循环反应为例,机器人重复用户的指令。例如,当机器人界面接收到用户的频道切换请求时,它不仅会切换频道,还会友好地说话,例如说“第四频道,第四频道”。用户自然会认为机器人完全理解了用户的请求。基于这个概念,一种新的机器人界面结合了实用性和熟悉性。本文研究了安装在机器人信息家电“ApriAlphatrade”中的熟悉行为的影响。实验结果表明,语音重复、注视目标和移动目标的任务执行在熟悉因素上得分最高。老年人比年轻人更喜欢熟悉的行为
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引用次数: 14
Lexicon Acquisition based on Behavior Learning 基于行为学习的词汇习得
Pub Date : 2005-07-19 DOI: 10.1109/DEVLRN.2005.1490947
S. Takamuku, Yasutake Takahashi, M. Asada
Studies on lexicon acquisition systems are gaining attention in hope for a natural human-robot interface and a test environment for theories of infant lexicon acquisition. This paper presents a system that forms word categories based on object-oriented behaviors. By using physical experiences, the system is able to generalize names to objects with various visual features. The system was implemented to a mobile robot acquiring lexicon about object categories with different rolling preferences. The system successfully acquired the lexicon and generalized the names to objects with various visual features in accordance with their rolling preferences
词汇习得系统的研究越来越受到人们的关注,以期为婴儿词汇习得理论提供一个自然的人机界面和测试环境。本文提出了一个基于面向对象行为的词类生成系统。通过使用物理经验,系统能够将名称概括为具有各种视觉特征的物体。以移动机器人为例,实现了该系统对具有不同滚动偏好的物体类别词汇的获取。该系统成功地获取了词汇,并根据物体的滚动偏好将其名称泛化为具有各种视觉特征的物体
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引用次数: 4
Competition between Spatial and Temporal Factors in Simple Apparent Motion is Modulated by Laterality 在简单视运动中,空间因子和时间因子之间的竞争是由横向调节的
Pub Date : 2005-07-19 DOI: 10.1109/DEVLRN.2005.1490974
K. Sakamoto, T. Onizawa, M. Yano
When spots are presented successively, apparent motions are perceived. Computationally, motion competition in apparent motion is an ill-posed problem and to reveal the underlying mechanisms is an important issue not only in cognitive science but also in computer vision. Our previous studies by Sugiura et al. (1998) revealed how the spatial and temporal factors counterbalance in motion competition and found that the counterbalancing relation was modulated by the directional condition between the competing motions, that is, whether the two motions were directed to the same or opposite direction. However, it was not clear which caused this effect, the directional difference of the motions or laterality, namely, the difference between bi-hemispheric and mono-hemispheric motion processes. Here, we show that this directional modulation is originated from laterality. This fact suggests that cortico-cortical interaction is responsible for spatiotemporal integration for perception of moving objects in complex environments
当点连续出现时,可以感知到明显的运动。在计算上,视运动中的运动竞争是一个不适定问题,揭示其潜在机制是认知科学和计算机视觉领域的一个重要问题。我们在Sugiura等(1998)的研究中揭示了运动竞争中空间和时间因素是如何平衡的,并发现这种平衡关系是由竞争运动之间的方向条件调节的,即两个运动是朝向相同还是相反的方向。然而,造成这种影响的原因尚不清楚,是运动的方向性差异还是偏侧性,即双半球和单半球运动过程的差异。在这里,我们表明这种方向调制是由侧向性引起的。这一事实表明,皮层-皮层相互作用负责在复杂环境中感知移动物体的时空整合
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引用次数: 0
Cognitive Substrates: What They Are and What They Learn 认知底物:它们是什么和它们学习什么
Pub Date : 2005-07-19 DOI: 10.1109/DEVLRN.2005.1490955
A. I. Kovacs, H. Ueno
The fabrication of veritable cognizers relies on an understanding of possible substrates of cognition. Cognitive substrates are subsystems of cognizers, though cognition itself is not a property of them alone but from interaction with the rest of a cognizer and the environment. Ultimately, all cognitive functions including cognitive development and learning need to be explained in terms of processes in cognitive substrates without recourse to logically incoherent reified knowledge, concept structures, behaviors, etc. We describe what cognitive substrates are and where they fit in. We discuss what learning means from the view of cognitive substrates and what can and must be learned by them. We conclude that learning is ongoing change in the system organization of the cognitive substrate itself and that the only representation available in a cognitive substrate is about the innards of the cognizer itself. The only models that can exist in and be learned by a cognitive substrate are not of the external environment or objects and events in it, but of the processes and states the system engages in when interacting with the environment or things in the world
真正认知者的制造依赖于对可能的认知底物的理解。认知底物是认知者的子系统,尽管认知本身并不是它们单独的属性,而是与认知者的其余部分和环境相互作用的结果。最终,包括认知发展和学习在内的所有认知功能都需要根据认知基底的过程来解释,而不需要求助于逻辑上不连贯的物化知识、概念结构、行为等。我们描述了认知底物是什么以及它们在哪里适用。我们从认知底物的角度讨论了学习的意义,以及他们可以和必须学习什么。我们得出的结论是,学习是认知基础本身的系统组织的持续变化,认知基础中唯一可用的表征是关于认知者自身的内部。唯一可以存在于认知基质中并被其学习的模型不是外部环境或其中的物体和事件,而是系统在与环境或世界上的事物相互作用时所参与的过程和状态
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引用次数: 0
Kernel Isomap on Noisy Manifold 噪声流形上的核等距映射
Pub Date : 2005-07-19 DOI: 10.1109/DEVLRN.2005.1490986
Heeyoul Choi, Seungjin Choi
In the human brain, it is well known that perception is based on similarity rather than coordinates and it is carried out on the manifold of data set. Isomap (Tenenbaum et al., 2000) is one of widely-used low-dimensional embedding methods where approximate geodesic distance on a weighted graph is used in the framework of classical scaling (metric MDS). In this paper, we consider two critical issues missing in Isomap: (1) generalization property; (2) topological stability and present our robust kernel Isomap method, armed with such two properties. The useful behavior and validity of our robust kernel Isomap, is confirmed through numerical experiments with several data sets including real world data
众所周知,在人脑中,感知是基于相似性而不是坐标的,它是在数据集的流形上进行的。Isomap (Tenenbaum et al., 2000)是一种广泛使用的低维嵌入方法,它在经典尺度(metric MDS)框架中使用加权图上的近似测地线距离。本文考虑了Isomap中缺少的两个关键问题:(1)泛化性质;(2)拓扑稳定性,提出了鲁棒核Isomap方法。通过实际数据集的数值实验,验证了鲁棒核等高图的有效性和实用性
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引用次数: 22
Real-Time Multi-View Face Tracking for Human-Robot Interaction 面向人机交互的实时多视图人脸跟踪
Pub Date : 2005-07-19 DOI: 10.1109/DEVLRN.2005.1490961
K. An, Dong Hyun Yoo, Sung-Uk Jung, M. Chung
For face tracking in a video sequence, various face tracking algorithms have been proposed. However, most of them have difficulty in finding the initial position and size of a face automatically. In this paper, we present a fast and robust method for fully automatic multi-view face detection and tracking. Using a small number of critical rectangle features selected and trained by the Adaboost learning algorithm, we can detect the initial position, size and view of a face correctly. Once a face is reliably detected, we can extract face and upper body color distribution from the detected facial regions and upper body regions for building robust color modeling respectively. Simultaneously, each color modeling is performed by using k-means clustering and multiple Gaussian models. Then, fast and efficient multi-view face tracking is executed by using several critical features. Our proposed algorithm is robust to rotation, partial occlusions, and scale changes in front of dynamic, unstructured background. In addition, our proposed method is computationally efficient. Therefore, it can be executed in real-time
对于视频序列中的人脸跟踪,已经提出了各种各样的人脸跟踪算法。然而,它们大多难以自动找到人脸的初始位置和大小。本文提出了一种快速、鲁棒的全自动多视角人脸检测与跟踪方法。利用Adaboost学习算法选择和训练的少量关键矩形特征,我们可以正确地检测人脸的初始位置、大小和视图。一旦人脸被可靠地检测到,我们就可以从检测到的面部区域和上半身区域中分别提取人脸和上半身的颜色分布,分别建立鲁棒的颜色建模。同时,使用k-means聚类和多个高斯模型对每种颜色进行建模。然后,利用几个关键特征实现快速高效的多视图人脸跟踪。我们提出的算法对动态、非结构化背景前的旋转、部分遮挡和尺度变化具有鲁棒性。此外,我们提出的方法计算效率高。因此,它可以实时执行
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引用次数: 2
期刊
Proceedings. The 4nd International Conference on Development and Learning, 2005.
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