Interactions among neurons can take place in a wide variety of forms. It is the goal of this thesis to investigate the properties and implications of a number of these interactions that we believe are relevant for information processing in the brain. Neuroscience has progressed considerably in identifying the diverse neuronal cell-types and providing detailed information about their individual morphological, genetic and electrophysiological properties. It remains a great challenge to identify how this diversity of cells interacts at the microcircuit level. This task is made more complex by the fact that the forms of interaction are not always obvious or simple to observe, even with advanced scientific equipment. In order to achieve a better understanding and envision possible implications of the concerted activity of multiple neurons, experiments and models must often be used jointly and iteratively. In this thesis I first present the development of a computer-assisted system for multi-electrode patch-clamp that enabled new kinds of experiments, allowing qualitatively different information to be obtained concerning the interaction of multiple neurons. In the following chapters I describe the different questions addressed and approaches utilized in the investigation of neuronal interactions using multi-electrode patch-clamp experiments. The principles behind the clustered organization of synaptic connectivity in Layer V of the somatosensory cortex are the first experimental finding presented. I then quantify the ephaptic coupling between neurons and how apparently minute signals might help correlate the activity of many neurons. Next, the ubiquity of a neocortical microcircuit responsible for frequency-dependent disynaptic inhibition is demonstrated and the summation properties of this microcircuit are then analyzed. Finally a model to explain the interactions between gap junctions and synaptic transmission in the olfactory bulb is proposed.