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

本项目旨在通过多变量病变分析和扩散张量成像(DTI)识别数字幅度信息和算术事实提取的认知过程和神经功能基础。根据三码模型，这两种表征之间的差异是数字认知中最显著的程序性差异。在中风患者和健康对照组中，将通过不同时间的平行横断面和纵向实验(训练)研究，评估数字幅度处理和算术事实提取的静态和动态方面(神经认知可塑性)及其功能解剖学基础。空间-数字关联被视为数字大小加工的一个指示器。平行实验设计能够解决中风患者和健康对照组中关于量值处理和算术事实提取的相同问题。在这种情况下，通过多变量病变分析和DTI分析不同的患者组，可以确定认知处理的因果关系和潜在的神经相关性。同时，通过平行实验检查健康对照，可以排除病理性干扰的影响。基于三码模型的假设，可以预测健康人和中风患者在不同数字任务中的不同表现，后者在梗死后的特定时间。更准确地说，中风后立即进行的多变量病变分析允许不同的因果结构-功能映射(即，由于支持数字认知的网络受损部分而导致的数字(亚)过程中的功能缺陷)，以及是否必须同时损害白质和灰质的某些部分。在中风的慢性期，可以研究数值大小和算术事实提取的神经网络内部和之间的潜在重组过程(即，某些认知(子)过程是否可以被其他神经解剖区域接管以弥补功能缺陷)。纵向比较可以得出结论，急性期的某些病变模式是否可以预测数字损伤的过程。通过DTI可以识别和分析可能的纤维连接中断，这可能会损害大脑功能未受损的区域。总之，拟议项目的结果将扩大我们对(非)受损数字加工的理解，允许进行预测陈述，并允许对数字障碍的诊断和干预产生影响。

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.