Stemme Anja, Deco Gustavo, Busch Astrid, Schneider Werner X
Department of Psychology, Ludwig-Maximilian University Munich, Germany.
Neuroimage. 2005 Jun;26(2):454-70. doi: 10.1016/j.neuroimage.2005.01.044. Epub 2005 Mar 31.
The Wisconsin Card Sorting Test (WCST) is well known to test cognitive flexibility in terms of set-shifting capabilities. Many fMRI studies with behaving monkeys as well as human subjects have shown transient neural activity in the Prefrontal Cortex (PFC), as indicated by an increase in the fMRI signal, following a rule change in the WCST or when using a WCST-like paradigm. We present a computational model, covering a limited number of PFC neurons and using precise biophysical descriptions, which is able to simulate WCS-like tests. Further, the detailed neuronal representation of the model allows us to calculate the resulting fMRI signal. Thus, we are able to analyze the adequacy of the model and its structure by comparing the calculated fMRI signal with the experimental data which in turn provides promising insights into the neural base of the increase in the fMRI signal.
威斯康星卡片分类测试（WCST）以测试认知灵活性中的定势转换能力而闻名。许多以行为猴子和人类受试者为对象的功能磁共振成像（fMRI）研究表明，在WCST中规则改变后或使用类似WCST的范式时，前额叶皮层（PFC）会出现短暂的神经活动，这表现为fMRI信号增强。我们提出了一个计算模型，该模型涵盖有限数量的PFC神经元并使用精确的生物物理描述，能够模拟类似WCST的测试。此外，该模型详细的神经元表示使我们能够计算出产生的fMRI信号。因此，通过将计算出的fMRI信号与实验数据进行比较，我们能够分析模型及其结构的充分性，这反过来又为fMRI信号增强的神经基础提供了有前景的见解。
