Discrete and continuous compressed information representation using phase transition phenomena

使用相变现象的离散和连续压缩信息表示

• 批准号: 16500093
• 负责人: OKADA Masato
• 金额: $ 2.44万
• 依托单位: The University of Tokyo
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (C)
• 财政年份: 2004
• 资助国家: 日本
• 起止时间: 2004 至 2007
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-16500093/
• 关键词: Information representation; Information compression; Self-organization; Localized activity; Phase transition; Spin glass; replica method; Visual cortex; 学習; 脳; 神経; ヘブ学習; 自己組織化マップ; 脳のモデル; ランダム

A number of findings suggest that the preferences of neighboring neurons in the inferior temporal (IT) cortex of macaque monkeys tend to be similar. However, recently However, Tamura, et al. found that neighboring neurons react to non-similar stimuli lb resolve this controversy, we proposed a new view of information representation in the IT cortex that takes a new view of information representation in the IT cortex that takes sparse and local neuronal excitation into account. Since the excitation is sparse, information regarding visual objects seems to be encoded in a distributed manner. The local excitation of neurons coincides with the classical notion of a column structure. Our model consists of an input layer and a nerve field having afferent connections from the input layer. The afferent connections are learned through Hebbian learning.To check abilities of the present model we employed two parallel rings in the unit sphere as an input space. The input signals have two parameters. … More One is θ; which identifies from what point of the ring the input signal emerged. The second parameter is ξ; which indicates which ring the input signal belongs to. This means that the input space contains the discrete information e and the continuous information B. We define D as distance between the two rings. When the distance D is small, only the position θ on the rings is continuously encoded using the position of local excitation. On the other hand, when the distance D is large, the center of gravity of the local excitation continues to represent the position θ on the rings, and the firing pattern within the local excitation represents ξ in a distributed manner which ring the input signal comes from. It means that there is phase transition regarding the information representationIn order to explore this phase transition phenomenon, we investigated neural network models with mexican-hat and spin glass type interaction using the statistical-mechanical methods, especially the replica method. Here we study the influence of disorder in the mexican-hat type interactions on the cooperative and uncooperative behavior of recurrent neural networks by using the replica method. Although the interaction between neurons has a dependency on distance, our model can be solved analytically. Bifurcation analysis identifies the boundaries between paramagnetic, ferromagnetic, spin-glass, and localized phases. In the localized phase, the network shows a bump like activity, which is often used as a model of spatial working memory or columnar activity in the visual cortex. Simulation results show that disordered interactions can stabilize the drift the of bump position, which is commonly observed in conventional lateral inhibition type neural networks. We also investigated the partial annealing framework in which the interaction between neurons changes. Less

许多研究结果表明，猕猴下颞叶 (IT) 皮层的邻近神经元的偏好往往相似，但最近 Tamura 等人发现邻近神经元对非相似刺激的反应解决了这一问题。在争议中，我们提出了一种IT皮层信息表示的新观点，该观点考虑了IT皮层信息表示的新观点，考虑了稀疏和局部神经激励，因为激励是稀疏的，所以关于视觉对象的信息似乎被编码了。在分布式神经元的局部激发与柱结构的经典概念一致。我们的模型由输入层和具有来自输入层的传入连接的神经场组成。传入连接是通过赫布学习来学习的。在本模型中，我们使用单位球体中的两个平行环作为输入信号，其中一个是 θ；第二个参数是 Σ，表示输入信号从环的哪个点出现。响铃输入信号所属这意味着输入空间包含离散信息e和连续信息B。我们将D定义为两个环之间的距离，当距离D很小时，仅使用环上的位置θ进行连续编码。另一方面，当距离D较大时，局部激励的重心继续表示环上的位置θ，并且局部激励内的点火模式以分布的方式表示环上的位置。输入信号来自。关于信息表示的相变为了探索这种相变现象，我们使用统计力学方法，特别是复制方法，研究了墨西哥帽和旋转玻璃类型相互作用的神经网络模型，在这里我们研究了墨西哥无序的影响。 -使用复制方法对循环神经网络的合作和不合作行为的帽子型相互作用虽然神经元之间的相互作用依赖于距离，但我们的模型可以通过分析来解决分叉分析识别顺磁，在局部阶段，网络表现出类似凹凸的活动，通常用作视觉皮层空间工作记忆或柱状活动的模型。模拟结果表明，无序的相互作用可以稳定。我们还研究了部分退火框架，其中神经元之间的相互作用变化较小。

项目成果

Statistical mechanics for neural spike data analysis using log-linear model.

使用对数线性模型进行神经尖峰数据分析的统计力学。

• 发表时间: 2005
• 期刊: Progress of Theoretical Physics Supplement 157
• 作者: Shouno;H.;Wada;K. & Okada;M.
• 通讯作者: M.

Theory of localized synfire chain: characteristic propagation speed of stable spike patterns.

局部联火链理论：稳定尖峰模式的特征传播速度。

• 发表时间: 2004
• 作者: Hamaguchi;K.;Okada;M. & Aihara;K.
• 通讯作者: K.

Population dynamics of face-responsive neurons in the inferior temporal cortex

• DOI: 10.1093/cercor/bhh209
• 发表时间: 2005-08-01
• 期刊: CEREBRAL CORTEX
• 影响因子: 3.7
• 作者: Matsumoto, N;Okada, M;Kawano, K
• 通讯作者: Kawano, K

Stochasticity in Localized Synfire Chain.

局部 Synfire 链中的随机性。

• 发表时间: 2005
• 期刊: Neurocomputing 65-66
• 作者: Hamaguchi;Okada;Yanmana;Aihara
• 通讯作者: Aihara

Effect of dendritic backpropagating action potential on neural interaction

树突反向传播动作电位对神经相互作用的影响

• 发表时间: 2005
• 期刊: Neurocomputing 65-66
• 作者: Aonishi;T.;Miyakawa;H.;Inoue;M. & Okada;M.
• 通讯作者: M.