NSF Award
0523216
Fruit flies exhibit versatile and sophisticated capabilities of stimulus discrimination and<br/>"attention"-like behavior. They are particularly attuned to recognizing novelty. This proposal<br/>outlines a plan to delineate the network and neural principles underlying the fruit fly's ability to<br/>perform these information-processing functions, and then to employ them as the basis for a<br/>computational device. This multi-step program will be begun by defining the circuitry in the fruit<br/>fly subserving its recognition, selective attention, and novelty responses, analyzing the<br/>contributions, connections, and interactions of these circuit elements both behaviorally and<br/>physiogically, and then introducing this neural architecture as the basis for the computer-simulated<br/>brain in a brain-based device capable of displaying novelty recognition.<br/>We will use techniques of gene targeting that we have developed previously to identify<br/>the parts of the brain contributing to recognition, selective attention, and novelty responses. We<br/>will map the sites in the nervous system mediating the effect by manipulating neural activity.<br/>This will be achieved in two opposing ways: one way by blocking activity and the other by<br/>increasing activity. These perturbations will be targeted to different, restricted parts of the brain<br/>by means of a set of genetically engineered fly strains we have developed and used over the<br/>years. In this manner, we will map the funcitonal circuitry mediating a fruit fly's novelty<br/>response by increasing or decreasing excitability in restricted brain regions.<br/>Aim 1: Analyze the complex, organizational architecture by which the fruit fly's nervous system<br/>achieves behaviorally the recognition of novelty.<br/>Aim 2: Map the distribution of the 20-30 Hz LFP response in various brain regions, and the role<br/>of coherence between these brain regions in the generation of the fruit fly's novelty response.<br/>Brain-based devices provide the groundwork for the development of intelligent machines<br/>that follow neurobiological rather than computational principles in their construction. As is the<br/>case with animals, the behaviors of brain-based devices emerge solely as a result of internally<br/>generated activity of their nervous systems rather than of responses to any programmed<br/>instructions from computer software. Such devices are particularly useful in situations of novelty<br/>where computation is not possible in principle or in cases of great local complexity where<br/>programming proves infeasible. Such a device must confront novel situations and complex sets of<br/>parameters that must be dealt with rapidly. Our goal is to implement principles from the fruit fly<br/>system into such a device, using as our platform an existing brain-based device developed at The<br/>Neurosciences Institute.<br/>Aim 3: Introduce a simulated neural architecture based on the functional network for novelty<br/>detection defined in Aims 1 & 2 into a brain-based device.<br/>The long-term goal of this work is to understand the principles upon which the nervous<br/>system of the fruit fly operates as the basis for neurobiologically inspired computational devices.<br/>The principles underlying nervous system function hold promise for developing a new generation<br/>of devices that would be more capable of adaptive behavior than current systems. The most<br/>sophisticated behavior seen in either biological or artificial agents is shown by organisms whose<br/>behavior is guided by a nervous system. The fruit fly offers the requisite complexity to be of<br/>value in this endeavor, while being simple enough (i.e., small enough in neuron number) to be<br/>amenable to analysis. Most importantly, it offers sophistication afforded by a multi-disciplinary<br/>experimental approach (genetics, anatomy, physiology and behavior) to be followed by computer<br/>simulation and device implementation.
