Fruit flies exhibit versatile and sophisticated capabilities of stimulus discrimination and "attention"-like behavior. They are particularly attuned to recognizing novelty. This proposal outlines a plan to delineate the network and neural principles underlying the fruit fly's ability to perform these information-processing functions, and then to employ them as the basis for a computational device. This multi-step program will be begun by defining the circuitry in the fruit fly subserving its recognition, selective attention, and novelty responses, analyzing the contributions, connections, and interactions of these circuit elements both behaviorally and physiogically, and then introducing this neural architecture as the basis for the computer-simulated brain in a brain-based device capable of displaying novelty recognition. We will use techniques of gene targeting that we have developed previously to identify the parts of the brain contributing to recognition, selective attention, and novelty responses. We will map the sites in the nervous system mediating the effect by manipulating neural activity. This will be achieved in two opposing ways: one way by blocking activity and the other by increasing activity. These perturbations will be targeted to different, restricted parts of the brain by means of a set of genetically engineered fly strains we have developed and used over the years. In this manner, we will map the funcitonal circuitry mediating a fruit fly's novelty response by increasing or decreasing excitability in restricted brain regions. Aim 1: Analyze the complex, organizational architecture by which the fruit fly's nervous system achieves behaviorally the recognition of novelty. Aim 2: Map the distribution of the 20-30 Hz LFP response in various brain regions, and the role of coherence between these brain regions in the generation of the fruit fly's novelty response. Brain-based devices provide the groundwork for the development of intelligent machines that follow neurobiological rather than computational principles in their construction. As is the case with animals, the behaviors of brain-based devices emerge solely as a result of internally generated activity of their nervous systems rather than of responses to any programmed instructions from computer software. Such devices are particularly useful in situations of novelty where computation is not possible in principle or in cases of great local complexity where programming proves infeasible. Such a device must confront novel situations and complex sets of parameters that must be dealt with rapidly. Our goal is to implement principles from the fruit fly system into such a device, using as our platform an existing brain-based device developed at The Neurosciences Institute. Aim 3: Introduce a simulated neural architecture based on the functional network for novelty detection defined in Aims 1 & 2 into a brain-based device. The long-term goal of this work is to understand the principles upon which the nervous system of the fruit fly operates as the basis for neurobiologically inspired computational devices. The principles underlying nervous system function hold promise for developing a new generation of devices that would be more capable of adaptive behavior than current systems. The most sophisticated behavior seen in either biological or artificial agents is shown by organisms whose behavior is guided by a nervous system. The fruit fly offers the requisite complexity to be of value in this endeavor, while being simple enough (i.e., small enough in neuron number) to be amenable to analysis. Most importantly, it offers sophistication afforded by a multi-disciplinary experimental approach (genetics, anatomy, physiology and behavior) to be followed by computer simulation and device implementation.
