Computational modelling of transformation invariant representations and information maintenance in spiking neural networks with ranges of axonal condu
Computational modelling of transformation invariant representations and information maintenance in spiking neural networks with ranges of axonal condu
批准号:
1789468
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2016
资助国家:
英国
项目状态:
已结题
起止时间:
2016 至 --
中文摘要
由于缺乏具有高水平、三维视觉的灵长类动物立体模型,计算视觉神经科学在高级脑功能建模和实际机器人中的应用受到了限制。直到最近,猕猴下颞叶皮层(It)中三维物体形状表征的神经生理特征才出现,为计算模型提供了复制的结果。IT的视觉表征在视觉注意(Chelazzi et al., 1993)、物体识别(Hung et al., 2005)和物体交互(Gallese et al., 1994)的基本功能中的作用,使其作为现实(物理和虚拟)和高级建模之间的模块化接口的复制,对人工智能和未来计算神经科学研究具有重要意义。本研究计划在灵长类视觉的分层VisNet模型中复制Yamane等人(2008)发现的三维物体形状的IT表示。这推动了Eguchi等人(2015)在VisNet模型中复制V4和后置IT (TEO)中二维物体形状表示特征的OCTNAI研究。Yamane等人提供的适应性刺激技术和分析将允许将模型与神经生理学结果进行直接比较。这项工作还将为IT中更高级的物体形状表示的最新特征建模提供基础。通过模拟顶叶前内皮层(AIP)在将IT形状表征映射到抓取物体的运动命令中的理论作用,将测试初始模型的高级处理表征的功能。这将结合OCTNAI在建模以头部为中心(Mender and Stringer, 2014)和以手为中心(Galeazzi et al., 2015)以自我为中心的参考框架方面的研究,目的是产生一个视觉引导的伸手和抓握的实用模型。作为研究的中心领域,该提案首先概述了IT中三维物体形状表示的特征,并描述了这些表示如何在立体版本的VisNet中自组织的假设。接下来是我目前的实习研究大纲,其目的是建立一个生物学上精确的立体视差模型,作为双目组合的模型,输入到更高层次的VisNet实验中。特别关注我在V1中对立体视觉的Topographica模型所做的扩展,以便根据最近的神经生理学结果提高其对视差表示的生物学准确性。还讨论了V2和V4中视差调优的特征,这将作为模型的中间基准。该建议指定实验来测试AIP在伸手和抓握中的理论作用。最后,概述了我适合从事这项研究的细节。
英文摘要
The application of computational visual neuroscience to the modelling of higher-level brain function and practical robotics has been limited by the absence of stereoscopic primate models of high-level, three-dimensional vision. It is only recently that neurophysiological characterisations of three-dimensional object shape representation in the macaque inferior temporal cortex (IT) have emerged, providing results for computational models to replicate. The role of IT's visual representation in the fundamental functions of visual attention (Chelazzi et al., 1993), object recognition (Hung et al., 2005) and object interactions (Gallese et al., 1994), makes its replication as a modular interface between reality (both physical and virtual) and higher-level modelling, of significant interest to artificial intelligence and of critical importance to future computational neuroscience research.This research proposal plans to replicate the IT representation of three-dimensional object shape found by Yamane et al. (2008), within the hierarchical VisNet model of primate vision. This progresses the research of Eguchi et al. (2015) of the OCTNAI in replicating characterisations of two-dimensional object shape representation in V4 and posterior IT (TEO), within the VisNet model. The adaptive stimuli technique and analysis provided by Yamane et al. will allow for a direct comparison of the model with neurophysiological results. This work will also provide the basis for modelling recent characterisations of more advanced representations of object shape in IT. The functionality of the initial model's representations for higher-level processing will be tested by modelling the theorised role of the anterior intraparietal cortex (AIP) in mapping IT shape representation to motor commands for grasping objects. This will incorporate the research of the OCTNAI in modelling head-centred (Mender and Stringer, 2014) and hand-centred (Galeazzi et al., 2015) egocentric reference frames with the aim of producing a practical model of visually guided reaching and grasping.As the central area of investigation, the proposal begins by outlining characterisations of three-dimensional object shape representation in IT and describes hypotheses of how such representations may self-organise within a stereoscopic version of VisNet. This is followed by an outline of my current internship research, which has aimed to produce a biologically accurate model of stereoscopic disparity in V1, to act as a model of binocular combination for input into higher-level VisNet experiments. In particular, it focuses on the extensions I have made to the Topographica model of stereoscopic vision in V1, in order to improve the biological accuracy of its representation of disparity in line with recent neurophysiological results. Characterisations of disparity tuning in V2 and V4 are also discussed, which will act as intermediate benchmarks for the model. The proposal specifies experiments to test the theorised role of AIP in reaching and grasping. Finally, details of my suitability for undertaking this research are outlined.
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会议论文
国内基金
海外基金
Improving modelling of compact binary evolution.
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批准号:10903001
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项目类别:青年科学基金项目
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资助金额:20.0万元
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批准年份:2009
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负责人:史蒂芬
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依托单位: