Although the representations and processes underlying higher functions in the brain are still largely unknown, the organization of sensory cortices has been quite well understood for about 30 years. For example in the visual system, the Nobel prize winning studies of Hubel and Wiesel [20,22] showed that neurons in the primary visual cortex are responsive to particular features in the input, such as a line of a particular orientation at a particular location in the visual field. The inputs in the retina to which a neuron responds is called the receptive field of the neuron. All neurons in a vertical column in the cortex typically have the same receptive field and feature preferences. Vertical groups of neurons with the same orientation preference are called orientation columns and vertical groups with the same eye preference are called ocular dominance columns. These feature preferences gradually vary across the surface of the cortex in characteristic spatial patterns called cortical maps.
Often, altering the sensory environment of the young animal produces readily observable changes in the organization of the afferent connections to the cortex [21,23,24]. Based on such observations, it was generally believed that the response properties of cortical cells are defined primarily by the organization of afferents. Functionally for example the visual cortex was thought to be a collection of filters for visual input, and the properties of the filters (such as orientation preference) were thought to be defined by the patterns of afferent synapses. Possible lateral interactions between cells across the cortex were usually ignored, partly for simplicity, and partly because there did not exist sufficient neurobiological data to form well-defined theories about these interactions. Furthermore, based on early discoveries on the plasticity of the cortex (such as those of [1,4,5,24,46]), it was believed that the cortical structure was influenced by the visual environment only in early development, and that cortex was essentially static afterwards. The lateral connections were thought to play a secondary role in shaping visual cortex, with the primary role attributed to plasticity of thalamocortical afferents.
Recently, however, a number of exciting results about intracortical connectivity and dynamic processes in the cortex have emerged. Lateral connections are found to be remarkably ordered: they connect primarily areas with similar properties, such as neurons with the same orientation or eye preference in the visual cortex [13,15,28]. Such organization is not genetically determined nor static, but develops cooperatively and simultaneously with the thalamocortical afferents, and changes dynamically according to visual experience throughout life [6,7,8,26,28]). The new understanding of cortical development and function thus differs drastically from the old. Lateral interactions appear to play a much larger role both in the development and function of the cortex than previously believed, a role that we are only now beginning to understand.
A crucial part of the effort to integrate lateral interactions into the model of cortical function is computational modeling of the hypothesized structures and processes. Studying complex, dynamic phenomena such as those exhibited by the cortical circuits is usually very difficult experimentally, but computational simulations may give insight into what to look for. This book presents several such investigations, each addressing the role of lateral interactions at a different level or from a slightly different perspective. While a unified model of lateral interactions in the cortex is yet to emerge, the book can give an overview of the kinds of processes that may be going on, and thereby further our understanding of information processing in the cortex.