The brain is a highly interconnected network of constantly interacting units. Understanding the collective behavior of these units requires a multi-dimensional approach. The results of such analyses are hard to visualize and interpret. Hence tools capable of dealing with such tasks become imperative.

We present a method that offers means of visualizing and interpreting the complex dynamics of a set of parallelly recorded units, in an intuitive manner. First, the activity of all simultaneously recorded neurons is represented in a multidimensional space. Second, the multidimensional space is projected on a lower dimensional (3D) space of colors, using 3D Kohonen Maps. The projection algorithm assigns each multidimensional pattern a color in such a way that similar patterns receive similar colors. This color-coding helps our own visual system to detect patterns of activity that would be otherwise difficult to detect. Additionally, we used a simple algorithm to identify multidimensional patterns that are stimulus-specific.