Psychology Department, UCLA, Los Angeles, California.
Hippocampus. 2020 Apr;30(4):396-421. doi: 10.1002/hipo.23197. Epub 2020 Feb 17.
The hippocampal system contains neural populations that encode an animal's position and velocity as it navigates through space. Here, we show that such populations can embed two codes within their spike trains: a firing rate code ( R) conveyed by within-cell spike intervals, and a co-firing rate code ( ) conveyed by between-cell spike intervals. These two codes behave as conjugates of one another, obeying an analog of the uncertainty principle from physics: information conveyed in R comes at the expense of information in , and vice versa. An exception to this trade-off occurs when spike trains encode a pair of conjugate variables, such as position and velocity, which do not compete for capacity across R and . To illustrate this, we describe two biologically inspired methods for decoding R and , referred to as sigma and sigma-chi decoding, respectively. Simulations of head direction and grid cells show that if firing rates are tuned for position (but not velocity), then position is recovered by sigma decoding, whereas velocity is recovered by sigma-chi decoding. Conversely, simulations of oscillatory interference among theta-modulated "speed cells" show that if co-firing rates are tuned for position (but not velocity), then position is recovered by sigma-chi decoding, whereas velocity is recovered by sigma decoding. Between these two extremes, information about both variables can be distributed across both channels, and partially recovered by both decoders. These results suggest that populations with different spatial and temporal tuning properties-such as speed versus grid cells-might not encode different information, but rather, distribute similar information about position and velocity in different ways across R and . Such conjugate coding of position and velocity may influence how hippocampal populations are interconnected to form functional circuits, and how biological neurons integrate their inputs to decode information from firing rates and spike correlations.
海马体系统包含神经群体，当动物在空间中导航时，这些神经群体可以将动物的位置和速度编码为信号。在这里，我们表明，这些群体可以在其尖峰列车中嵌入两个代码：一个是由细胞内尖峰间隔传达的发射率代码（R），另一个是由细胞间尖峰间隔传达的共同发射率代码（）。这两个代码相互共轭，服从物理学中不确定性原理的一个类比：在 R 中传达的信息以 中的信息为代价，反之亦然。当尖峰列车编码一对共轭变量（例如位置和速度）时，这种权衡会出现例外，这些变量不会在 R 和 之间争夺容量。为了说明这一点，我们描述了两种生物启发式方法来解码 R 和 ，分别称为 sigma 和 sigma-chi 解码。头方向和网格细胞的模拟表明，如果发射率针对位置（但不是速度）进行调谐，则 sigma 解码可以恢复位置，而 sigma-chi 解码可以恢复速度。相反，在受 theta 调制的“速度细胞”之间的振荡干扰的模拟中，如果共同发射率针对位置（但不是速度）进行调谐，则 sigma-chi 解码可以恢复位置，而 sigma 解码可以恢复速度。在这两个极端之间，有关这两个变量的信息可以分布在两个通道中，并由两个解码器部分恢复。这些结果表明，具有不同空间和时间调谐特性的群体-例如速度与网格细胞-可能不会编码不同的信息，而是以不同的方式在 R 和 中分布有关位置和速度的类似信息。这种位置和速度的共轭编码可能会影响海马体群体如何相互连接以形成功能电路，以及生物神经元如何整合其输入以从发射率和尖峰相关性中解码信息。
