Maturana Pablo, Batrancourt Bénédicte
CRICM, UMR_S975, INSERM/CNRS, Hôpital Pitié-Salpêtrière, Paris, France.
J Physiol Paris. 2011 Jan-Jun;105(1-3):130-4. doi: 10.1016/j.jphysparis.2011.07.016. Epub 2011 Aug 10.
Networks can represent a large number of systems. Recent advances in the domain of networks have been transferred to the field of neuroscience. For example, the graph model has been used in neuroscience research as a methodological tool to examine brain networks organization, topology and complex dynamics, as well as a framework to test the structure-function hypothesis using neuroimaging data. In the current work we propose a graph-theoretical framework to represent anatomical, functional and neuropsychological assessment instruments information. On the one hand, interrelationships between anatomic elements constitute an anatomical graph. On the other hand, a functional graph contains several cognitive functions and their more elementary cognitive processes. Finally, the neuropsychological assessment instruments graph includes several neuropsychological tests and scales linked with their different sub-tests and variables. The two last graphs are connected by relations of type "explore" linking a particular instrument with the cognitive function it explores. We applied this framework to a sample of patients with focal brain damage. Each patient was related to: (i) the cerebral entities injured (assessed with structural neuroimaging data) and (ii) the neusopsychological assessment tests carried out (weight by performance). Our model offers a suitable platform to visualize patients' relevant information, facilitating the representation, standardization and sharing of clinical data. At the same time, the integration of a large number of patients in this framework will make possible to explore relations between anatomy (injured entities) and function (performance in different tests assessing different cognitive functions) and the use of neurocomputational tools for graph analysis may help diagnostic and contribute to the comprehension of neural bases of cognitive functions.
网络可以表示大量的系统。网络领域的最新进展已被应用于神经科学领域。例如，图模型已在神经科学研究中用作一种方法工具，以检查脑网络的组织、拓扑结构和复杂动态，同时也作为一个使用神经影像数据来检验结构 - 功能假设的框架。在当前的工作中，我们提出了一个图论框架来表示解剖学、功能和神经心理学评估工具的信息。一方面，解剖学元素之间的相互关系构成了解剖学图。另一方面，功能图包含几种认知功能及其更基本的认知过程。最后，神经心理学评估工具图包括几种神经心理学测试和量表，它们与不同的子测试和变量相关联。最后这两个图通过“探索”类型的关系相连，将特定工具与其所探索的认知功能联系起来。我们将这个框架应用于一组局灶性脑损伤患者。每个患者都与：（i）受损的脑实体（通过结构神经影像数据评估）以及（ii）所进行的神经心理学评估测试（按表现加权）相关。我们的模型提供了一个合适的平台来可视化患者的相关信息，便于临床数据的表示、标准化和共享。同时，将大量患者纳入这个框架将有可能探索解剖学（受损实体）与功能（在评估不同认知功能的不同测试中的表现）之间的关系，并且使用用于图分析的神经计算工具可能有助于诊断并促进对认知功能神经基础的理解。
