首页> 外文学位 >Nonlinear integration across the spatiotemporal receptive-field: Tactile feature-selectivity of neurons in the primary somatosensory cortex.
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Nonlinear integration across the spatiotemporal receptive-field: Tactile feature-selectivity of neurons in the primary somatosensory cortex.

机译:跨时空接受域的非线性整合:主要体感皮层神经元的触觉特征选择性。

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摘要

As organisms, our perceptions of the sensory world are mediated through neural activity at multiple stages within our brains. Broadly speaking, sensory neuroscience deals with two main lines of questioning: the encoding process quantifies how features of a sensory stimulus cause sequences of action-potentials evoked by a neuron, which are stereotyped fluctuations of its membrane potential. In contrast, in decoding we ask how to obtain an optimal estimate of a sensory stimulus through observations of neural action potentials.; We used the rat whisker (vibrissa) pathway, a high-acuity tactile sensory system, as an experimental model with which to answer both of these questions. During in-vivo experiments with anesthetized animals, we recorded single-neuron activity in the layer-IV of the primary somatosensory cortex (S1) in response to controlled deflections of one or two vibrissa.; Characterization of the encoding pathway involved two steps; firstly, we showed that S1 neurons encode deflection transients through phasic increases in their firing rates. Increases in the deflection angular velocity led to corresponding increases in magnitude, shortening of latency, and slight increases in the temporal precision of the response. Secondly, we showed that neural responses were strongly shaped by the timescale of suppression evoked by the neural pathway. The nonlinear dynamics of response suppression were predictable from simpler measurements made in the laboratory. We subsequently combined velocity-tuning and the history-dependence of S1 responses to create a Markov response model. This model, a novel contribution, accurately predicted measured responses to deflection patterns inspired by the velocity and temporal structures of naturalistic stimuli.; We subsequently used this model to (1) optimally detect neural responses, and (2) compute estimates of the sensory stimulus using a Bayesian decoding framework. Despite the significant role of response dynamics in shaping the activity evoked by different kinematic and behavioral parameters; texture-specific information were recoverable by an ideal-observer of the neural response. Together, these results characterize important principles by which a tactile sensory pathway encodes stimuli, and identify the factors that limit the amount of recoverable sensory information. The paradigm developed here is sufficiently general to be applicable to other sensory pathways.
机译:作为生物体,我们对感觉世界的感知是通过大脑内多个阶段的神经活动介导的。广义上讲,感觉神经科学涉及两个主要问题:编码过程量化了感觉刺激的特征如何引起神经元诱发的动作电位序列,这些动作电位是其膜电位的定型波动。相反,在解码中,我们问如何通过观察神经动作电位来获得最佳的感觉刺激估计。我们使用大鼠晶须(触须)路径(一种高敏触觉系统)作为实验模型来回答这两个问题。在对麻醉动物进行的体内实验中,我们记录了初级体感皮层(S1)的IV层中的单个神经元活动,以响应一个或两个触须的受控偏转。编码途径的表征包括两个步骤。首先,我们证明了S1神经元通过其发声速率的阶段性增加来编码偏转瞬变。偏转角速度的增加导致幅度相应增加,等待时间缩短,响应的时间精度略有增加。其次,我们表明神经反应受到神经途径引起的抑制时间尺度的强烈影响。响应抑制的非线性动力学可以通过实验室中更简单的测量来预测。随后,我们结合速度调整和S1响应的历史依赖性来创建Markov响应模型。这个模型是一种新颖的贡献,它可以准确地预测对变形模式的测量响应,该变形模式是受自然刺激的速度和时间结构所激发的。随后,我们使用该模型来(1)​​最佳地检测神经反应,以及(2)使用贝叶斯解码框架来计算感觉刺激的估计值。尽管响应动力学在塑造由不同运动学和行为参数引起的活动中起着重要作用;神经反应的理想观察者可以恢复特定纹理的信息。总之,这些结果表征了触觉感觉途径编码刺激的重要原理,并确定了限制可恢复感觉信息量的因素。这里开发的范式足够通用,可以应用于其他感觉途径。

著录项

  • 作者

    Seyed Boloori, Alireza.;

  • 作者单位

    Harvard University.;

  • 授予单位 Harvard University.;
  • 学科 Biology Neuroscience.; Engineering General.
  • 学位 Ph.D.
  • 年度 2007
  • 页码 149 p.
  • 总页数 149
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 神经科学;工程基础科学;
  • 关键词

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