The size and complexity of neural data is increasing at a dramatic pace due to rapid advances in experimental technologies. As a result, the data analysis techniques are shifting their focus from single-units to neural populations. We use projection methods, such as Principal Component Analysis PCA and Multiple Discriminant Analysis MDA, to facilitate the understanding and monitoring of the dynamics of neural populations recorded in the hippocampus and olfactory bulb. For the hippocampal date, we examine representation of startle episodes, in order to differentiate between somato-sensory and memory components of the hippocampal representations. For the olfactory data, we focus on how dynamics of odor responses in the olfactory receptor neurons of awake rats are shaped by the temporal features of the active odor sniffing. Our analyses indicate that the dynamics of neural representations depend non-linearly on odor identity and concentration, as well as breathing rhythms of the rats. These results include work done with graduate students Jun Xia and Jie Zhang.