Asymmetry in neural fields: a spatiotemporal encoding mechanism
Asymmetry in neural fields: a spatiotemporal encoding mechanism
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DOI：
10.1007/s00422-012-0544-0
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发表时间：
2013-04-01
影响因子：
1.9
通讯作者：
Girau, Bernard
中科院分区：
文献类型：
--
作者：
Cerda, Mauricio;Girau, Bernard
神经场模型已经被成功地应用于模拟不同的大脑机制，如视觉注意、运动控制和记忆。大多数理论和建模工作都集中在研究神经连通性变化下这类系统的动力学，主要是神经元之间的对称连通性。然而，当神经连接不对称时，神经元群体的新特性受到的关注较少，尽管在皮质组织中观察到了不对称的活动传播。在这里，我们探索具有非对称连通性的神经场的动力学，并表明，在前向传播的情况下，它可以引导种群遵循具有更高活跃度的特定轨迹。我们发现，当输入在空间上局域时，非对称性与输入速度成线性关系，并且这种关系对于不同的核和输入形状是成立的。为了说明非对称连接的行为，我们给出了一个应用：使用非对称神经场对人体运动的标准视频序列进行编码，并与计算机视觉技术进行了比较。总体而言，我们的结果表明，非对称神经场是一种具有竞争力的时空编码方法，具有两个主要优势：在线分类和分布式操作。
Neural field models have been successfully applied to model diverse brain mechanisms like visual attention, motor control, and memory. Most theoretical and modeling works have focused on the study of the dynamics of such systems under variations in neural connectivity, mainly symmetric connectivity among neurons. However, less attention has been given to the emerging properties of neuron populations when neural connectivity is asymmetric, although asymmetric activity propagation has been observed in cortical tissue. Here we explore the dynamics of neural fields with asymmetric connectivity and show, in the case of front propagation, that it can bias the population to follow a certain trajectory with higher activation. We find that asymmetry relates linearly to the input speed when the input is spatially localized, and this relation holds for different kernels and input shapes. To illustrate the behavior of asymmetric connectivity, we present an application: standard video sequences of human motion were encoded using the asymmetric neural field and compared to computer vision techniques. Overall, our results indicate that asymmetric neural fields are a competitive approach for spatiotemporal encoding with two main advantages: online classification and distributed operation.