Mechanisms and evolution of signal pattern recognition

描述（由申请人提供）：拟议研究的总体目标是获得有关信号模式识别机制和演变的知识。这项研究利用了青蛙中声学通信的优势，作为探索的模型系统：（1）传达生物学重要信息的信号的物理特性组合;（2）神经系统处理和提取这些信息的操作原理;（3）信号模式识别中的进化变化模式。 因为青蛙不需要声学经验来产生或识别信号，这个系统可以产生与婴儿识别和区分语音类似问题的知识。也就是说，所有的语言都来自一组共同的语音片段，而几乎没有语言经验的婴儿可以区分甚至在他们最终学习的语言中没有出现的语音片段。因此，这项研究解决了有关模式识别的先天机制的问题，这些机制使正常语言的发展成为可能，而正常语言反过来对人类心理健康很重要。 这项拟议中的研究将使用模拟男性交流声音的计算机合成信号的回放;女性对这些声音做出积极的趋声性反应，并区分一个或多个属性的细微差异。该研究解决了基于信号的频率内容和细尺度时间特性差异的鉴别标准的相互作用。这些相互作用将在两个密切相关的物种中进行量化;然后将这些结果用于选择与其他七个或多或少密切相关的物种进行的试验。这些数据，结合独立得出的所有九个物种的系统发育关系的估计，将被用来评估模式识别可能已经演变。还将确定可以解释进化趋势的机制和环境因素。最终，这项研究将是重要的框架可检验的假设的感觉机制的模式识别和指导执行这样的研究。

DESCRIPTION (provided by applicant): The overall goal of the proposed research is to gain knowledge about mechanisms and evolution of signal pattern recognition. The research exploits the advantages of acoustic communication in frogs as a model system for exploring: (1) combinations of physical properties of signals that convey biologically significant information; (2) the operating principles by which nervous systems processes and extract such information; and (3) patterns of evolutionary change in signal pattern recognition. Because frogs do not require acoustic experience to produce or to recognize signals, this system can yield knowledge bearing on analogous problems in the recognition and discrimination of speech sounds by infants. That is, all languages draw from a common set of phonetic segments, and infants with little linguistic experience can discriminate among phonetic segments that do not even occur in the language that they will ultimately learn. This research thus addresses questions about inborn mechanisms of pattern recognition that make possible the development of normal speech, which, in turn, is important for human mental health. The proposed research will use playbacks of computer-synthesized signals that simulate male communication sounds; females respond to these sounds with positive phonotaxis and discriminate subtle differences in one or more properties. The research addresses interactions of discrimination criteria based on the frequency content of the signal and differences in fine-scale temporal properties. These interactions will be quantified in two closely related species; these results will then be used to select tests to be conducted with seven other species that are more or less closely related. These data, in conjunction with an independently derived estimate of the phylogenetic relationships of all nine species, will be used to assess how pattern recognition might have evolved. Mechanistic and environmental factors that could explain evolutionary trends will also be identified. Ultimately, this research will be important for framing testable hypotheses about sensory mechanisms underlying pattern recognition and for guiding the execution of such studies.