Transient activity in monkey area MT represents speed changes and is correlated with human behavioral performance.
Transient activity in monkey area MT represents speed changes and is correlated with human behavioral performance.
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DOI：
10.1152/jn.00335.2014
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发表时间：
2015-02
影响因子：
2.5
通讯作者：
Andreas Traschütz;A. Kreiter;D. Wegener
中科院分区：
文献类型：
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作者：
Andreas Traschütz;A. Kreiter;D. Wegener
中颞区（MT）的神经元对运动起始和速度变化的反应是短暂持续的放电模式。瞬态响应的延迟最近已被证明与速度变化检测任务中的反应时间相关，但尚不知道该响应的符号、幅度和延迟如何取决于速度变化的符号和幅度，以及这些瞬态是否可以被解码以解释速度变化检测行为。为了研究这个问题，我们测量了固定猕猴MT区的神经元代表性的广泛的积极和消极的速度变化，并获得了三个主要结果。首先，速度变化瞬变不仅反映了神经元的绝对速度调谐，而且还通过根据相对速度变化的幅度缩放调谐响应的附加增益来成形。第二，通过阈值模型的积极和消极的人口瞬变的一个中等数量的MT神经元解释检测的积极和消极的速度变化，分别在一个水平相当于人类的检测率相同的视觉刺激。第三，与速度检测的心理物理模型中的反应时间一样，速度变化响应时间遵循速度变化的绝对差的幂律函数。这两个神经元的代表性和其密切相关的行为措施的速度变化检测表明，MT区的神经元瞬变促进视觉输入的快速变化的检测。
Neurons in the middle temporal area (MT) respond to motion onsets and speed changes with a transient-sustained firing pattern. The latency of the transient response has recently been shown to correlate with reaction time in a speed change detection task, but it is not known how the sign, the amplitude, and the latency of this response depend on the sign and the magnitude of a speed change, and whether these transients can be decoded to explain speed change detection behavior. To investigate this issue, we measured the neuronal representation of a wide range of positive and negative speed changes in area MT of fixating macaques and obtained three major findings. First, speed change transients not only reflect a neuron's absolute speed tuning but are shaped by an additional gain that scales the tuned response according to the magnitude of a relative speed change. Second, by means of a threshold model positive and negative population transients of a moderate number of MT neurons explain detection of both positive and negative speed changes, respectively, at a level comparable to human detection rates under identical visual stimulation. Third, like reaction times in a psychophysical model of velocity detection, speed change response latencies follow a power-law function of the absolute difference of a speed change. Both this neuronal representation and its close correlation with behavioral measures of speed change detection suggest that neuronal transients in area MT facilitate the detection of rapid changes in visual input.