Department of Psychology, Faculty of Arts, University of Ljubljana, Aškerčeva 2, 1000 Ljubljana, Slovenia.
Department of Psychiatry, Yale University School of Medicine, 300 George Street, New Haven, CT 06511, USA.
Cereb Cortex. 2024 Aug 1;34(8). doi: 10.1093/cercor/bhae350.
Spatial locations can be encoded and maintained in working memory using different representations and strategies. Fine-grained representations provide detailed stimulus information, but are cognitively demanding and prone to inexactness. The uncertainty in fine-grained representations can be compensated by the use of coarse, but robust categorical representations. In this study, we employed an individual differences approach to identify brain activity correlates of the use of fine-grained and categorical representations in spatial working memory. We combined data from six functional magnetic resonance imaging studies, resulting in a sample of $155$ ($77$ women, $25 \pm 5$ years) healthy participants performing a spatial working memory task. Our results showed that individual differences in the use of spatial representations in working memory were associated with distinct patterns of brain activity. Higher precision of fine-grained representations was related to greater engagement of attentional and control brain systems throughout the task trial, and the stronger deactivation of the default network at the time of stimulus encoding. In contrast, the use of categorical representations was associated with lower default network activity during encoding and higher frontoparietal network activation during maintenance. These results may indicate a greater need for attentional resources and protection against interference for fine-grained compared with categorical representations.
空间位置可以使用不同的表示和策略在工作记忆中进行编码和保持。精细的表示提供了详细的刺激信息,但认知要求高且容易出现不精确。精细表示中的不确定性可以通过使用粗糙但稳健的分类表示来补偿。在这项研究中,我们采用个体差异方法来确定在空间工作记忆中使用精细和分类表示的大脑活动相关性。我们结合了来自六个功能磁共振成像研究的数据,结果得出了一个由 155 名(77 名女性,25±5 岁)健康参与者组成的样本,他们执行了一项空间工作记忆任务。我们的结果表明,工作记忆中空间表示的个体差异与大脑活动的不同模式相关。精细表示的精度越高,在整个任务试次中注意力和控制大脑系统的参与度就越大,在刺激编码时默认网络的去激活程度就越强。相比之下,在编码时使用分类表示与默认网络活动的降低以及维持时额顶网络激活的增加有关。这些结果可能表明,与分类表示相比,精细表示需要更多的注意力资源和对干扰的保护。