Facts and Figures: Neuro-functional foundations and cognitive processes of numerical magnitude processing and arithmetic fact retrieval

事实与数字：数值幅度处理和算术事实检索的神经功能基础和认知过程

• 批准号: 400857833
• 负责人: Professor Dr. Hans-Otto Karnath
• 金额: --
• 依托单位: Sektion Neuropsychologie
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2018
• 资助国家: 德国
• 起止时间: 2017-12-31 至 2022-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/400857833?language=en
• 关键词: Facts; Figures; Neuro; functional; foundations

The present project aims at identifying cognitive processes and neuro-functional foundations of numerical magnitude information and arithmetic fact retrieval by means of multivariate lesion analysis and diffusion tensor imaging (DTI). The distinction between these two representations is the most significant procedural differentiation in numerical cognition according to the triple-code model. Static and dynamic aspects (neuro-cognitive plasticity) of numerical magnitude processing and arithmetic fact retrieval as well as their functional-anatomical foundations will be assessed in stroke patients and healthy controls via parallelized cross-sectional and longitudinal experimental (training-) studies at different time onsets. Spatial-numerical associations are examined as an indicator for the processing of numerical magnitude. The parallelized experimental design enables to address identical questions regarding magnitude processing and arithmetic fact retrieval in stroke patients and healthy controls. On this occasion, analysing different patient groups by means of multivariate lesion analysis and DTI allow to identify causal relationships of cognitive processing and the underlying neural correlates. At the same time, the influence of pathological interferences can be excluded by examining healthy controls in parallelized experiments. Based on the assumptions of the triple-code model it is possible to predict differential performance in various numerical tasks in both, healthy controls and stroke patients, the latter at certain times post infarct. More precisely, multivariate lesion analysis immediately following a stroke allows for differential causal structure-function mapping (i.e. functional deficits in numerical (sub)processes due to lesioned parts of the networks underlying numerical cognition) and whether certain parts of white and grey matter have to be lesioned simultaneously. In the chronic phase of a stroke, potential re-organisation processes within and between the neural networks of numerical magnitude and arithmetic fact retrieval can be investigated (i.e. whether certain cognitive (sub)processes can be taken over by other neuro-anatomical regions to compensate for functional deficits). The longitudinal comparison allows for drawing conclusions whether certain lesion patterns in the acute phase can predict the course of numerical impairments. By means of DTI possible fiber disconnections can be identified and analyzed, which might impair functionally unimpaired brain regions. In sum, the results gained from the proposed project would extend our understanding of (un)impaired number processing, permit prognostic statements and allow for implications for diagnosis and intervention of numerical impairments.

本项目旨在通过多元病变分析和扩散张量成像（DTI）识别认知过程和数值大小信息和算术事实检索的神经功能基础。根据三重编码模型，这两种表征之间的区别是数字认知中最重要的程序差异。静态和动态方面（神经认知可塑性）的数值大小处理和算术事实检索，以及他们的功能解剖基础，将评估中风患者和健康对照组通过平行的横截面和纵向实验（培训）研究在不同的时间发作。空间-数字关联被视为数字量级处理的指标。平行化的实验设计能够解决中风患者和健康对照中关于幅度处理和算术事实检索的相同问题。在这种情况下，通过多变量病变分析和DTI分析不同的患者群体，可以确定认知处理和潜在神经相关性的因果关系。同时，可以通过检查平行实验中的健康对照来排除病理干扰的影响。基于三重编码模型的假设，有可能预测健康对照和中风患者（后者在梗死后的某些时间）在各种数值任务中的差异表现。更确切地说，中风后立即进行的多变量损伤分析允许差异因果结构-功能映射（即，由于数字认知网络的受损部分而导致的数字（子）过程中的功能缺陷）以及白色和灰质的某些部分是否必须同时受损。在中风的慢性期，可以研究数值大小和算术事实检索的神经网络内和之间的潜在重组过程（即，某些认知（子）过程是否可以由其他神经解剖区域接管以补偿功能缺陷）。纵向比较可以得出结论，是否在急性期的某些病变模式可以预测的过程中的数字损伤。通过DTI可以识别和分析可能的纤维中断，这可能会损害功能未受损的大脑区域。总之，从拟议的项目中获得的结果将扩大我们的理解（非）受损的数字处理，允许预后的声明，并允许数字损伤的诊断和干预的影响。