What Does a Pigeon (Columba livia) Brain Look Like During Homing? Selective Examination of ZENK Expression.

Lesion studies have shown that the avian hippocampus plays a crucial role in homing pigeon (Columba livia) navigation. Using the expression of the immediate early gene protein ZENK in intact pigeons, the authors found regional variation in hippocampal activation as a consequence of homing and, necessarily, the behavior and internal states that accompany it. Specifically, pigeons that homed displayed a significant increase in the number of ZENK-labeled cells in the lateral hippocampal formation compared with pigeons that did not home, whereas no difference was seen in the medial hippocampus. Significant changes in ZENK expression were also found in the medial striatum, which resembles the mammalian ventral striatum. The results identify portions of the hippocampal formation and the medial striatum as sites of plasticity associated with homing. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Memory for Visuospatial Location Following Selective Hippocampal Sclerosis: The Use of Different Coordinate Systems.

This study addressed the role of the medial temporal lobe regions and, more specifically, the contribution of the human hippocampus in memory for body-centered (egocentric) and environment-centered (allocentric) spatial location. Twenty-one patients with unilateral atrophy of the hippocampus secondary to long-standing epilepsy (left, n = 7; right, n = 14) and 15 normal control participants underwent 3 tasks measuring recall of egocentric or allocentric spatial location. Patients with left hippocampal sclerosis were consistently impaired in the allocentric conditions of all 3 tasks but not in the egocentric conditions. Patients with right hippocampal sclerosis were impaired to a lesser extent and in only 2 of the 3 tasks. It was concluded that hippocampal structures are crucial for allocentric, but not egocentric, spatial memory. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Simplified nerve cell counting in the rat brainstem with the physical disector using a drawing-microscope

A simple modification of the physical disector is presented, which is used to count the number of neurons in the hypoglossal nucleus of the rat in a series of paraffin sections. One disector consists of two adjacent sections (6 μm thick) that have been Nissl-stained with cresyl fast violet. In the first step of the procedure each of the two sections is investigated separately with a drawing-microscope. The boundary of the hypoglossal nucleus and the position of neurons devoid of, or containing a part of, the cell nucleus in the plane of the section are marked on transparent paper. In the second step, these two drawings are placed one upon another, aligned and the number of cell profiles that show a cell nucleus in one but not in both drawings counted. This modification of the disector method for cell counting needs no specialized equipment, simply a light microscope with drawing apparatus, and can be combined with histochemical studies of other sections from the same tissue block.     

具有连续时延双神经元系统的双向耦合超混沌同步

近年来,混沌同步成为研究的一个热点。该文对具有连续时延双神经元系统的双向耦合超混沌同步问题的研究。首先基于Krasovskii—Lyapunov理论．给出系统同步的一个充分条件。最后通过计算机仿真表明系统在一定条件下能实现超混沌同步,证明了仿其结果和理论分析是一致的。     

单神经元模糊PID控制在光电跟踪系统中的应用

为提高ATP系统的跟踪精度和快速性,将模糊控制引入单神经元自适应PID控制中,提出单神经元模糊PID控制。它运用有监督的Hebb学习规则在线修正PID参数,而神经元的比例系数则由Sugeno模糊逻辑系统根据系统的误差和误差变化量大小进行调整,使控制系统对动态过程信息的利用程度达到最优。仿真和实验结果表明,系统不仅具有自学习和自适应能力,且动态性能和稳态性能都优于经典PID控制,超调量减小0.95%;上升时间和调节时间均减小1s左右;稳态误差减小1.19′。满足现代高精度跟踪系统的需求。     

面向神经形态感知的人工脉冲神经元的研究进展

近年来,随着人工智能技术和脉冲神经网络(SNN)的迅猛发展,人工脉冲神经元的研究逐渐兴起。人工脉冲神经元的研究对于开发具有人类智能水平的机器人、实现自主学习和自适应控制等领域具有重要的应用前景。传统的电子器件由于缺乏神经元的非线性特性,需要复杂的电路结构和大量的器件才能模拟简单的生物神经元功能,同时功耗也较高。因此,最近研究者们借鉴生物神经元的工作机制,提出了多种基于忆阻器等新型器件的人工脉冲神经元方案。这些方案具有功耗低、结构简单、制备工艺成熟等优点,并且在模拟生物神经元的多种功能等方面取得了显著进展。文章将从人工脉冲神经元的基本原理出发,综述和分析目前已有的各种实现方案。具体来说,将分别介绍基于传统电子器件和基于新型器件的人工脉冲神经元的实现方案,并对其优缺点进行比较。此外,还将介绍不同类型的人工脉冲神经元在实现触觉、视觉、嗅觉、味觉、听觉和温度等神经形态感知方面的应用,并对未来的发展进行展望。希望能够为人工脉冲神经元的研究和应用提供有益的参考和启示。     

一种大规模高维数据快速聚类算法

提出了一种面向大规模高维数据的自组织映射聚类算法. 算法通过压缩神经元的特征集合, 仅选择与神经元代表的文档类相关的特征构造神经元的特征向量, 从而减少了聚类时间. 同时由于选取的特征能够将映射到不同神经元的文档类进行有效区分, 避免了无关特征的干扰, 因而提升了聚类的精度. 实验结果表明该方法能够有效加快聚类的速度, 提升聚类的准确度, 达到比较理想的聚类效果.     

时滞影响下的环式耦合混沌神经元同步

由于突触连接,神经元之间的信息传递普遍存在着时滞效应．本文讨论时滞对四个环式耦合混沌HR（Hindmarsh—Rose）神经元的同步动力学行为影响．通过计算同步差,发现适当的时滞会诱发或增强混沌神经元间的完全同步,即时滞的作用使耦合系统在较小的耦合强度下存在稳定的同步状态．进一步还发现时滞会诱发神经元间出现相位同步,增大在相同步窗口．此外,在完全同步出现可以观察到由时滞诱发的一些复杂现象,包括近似同步与相位同步之间的转迁等．     

滞后不确定系统的无辨识自适应智能控制方法

针对带有大纯滞后、不确定性的工业过崔，提出一种无需辨识的自适应智能控制方法。该方法不需要对过程建立数学模型，只要检测过程的实际输出和期望输出，通过模糊预测控制来自正单神经元自适应PSD控制律，即可以对滞后不确定、建模困难的工业过程实现自适应控制。仿真结果表明用该方法控制滞后不确定系统具有简单、实用、鲁棒性强的特点．     

一个时延混沌系统的耦合同步及其在保密通信中的应用

近年来，混沌同步成为一个研究热点，特别是它在保密通信中的潜在应用。系统地研究了一个时延混沌神经元系统的耦合同步问题。基于Krasovskii-Lyapunov理论，分析了同步的渐近稳定性，给出并证明了判定同步的一个充分条件，并对耦合强度阈值进行了估计。计算机数值仿真结果表明，该耦合系统具有良好的同步效果和鲁棒性，证实了仿真结果与理论分析是相符的。最后基于混沌掩码技术给出了在扩展频谱保密通信中的一个应用实例。该应用系统的特点是只需传送一个标量信号就可实现同步，由于该信号直接驱动接收系统，且具有类似噪声的宽频谱特性，因此难以预测和破译，提高了通信系统的保密性能。