Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
Medical Research Council Cognition and Brain Science Unit, Cambridge, UK.
Neuroimage. 2017 Oct 1;159:131-145. doi: 10.1016/j.neuroimage.2017.07.033. Epub 2017 Jul 17.
Recent evidence suggests that visual short-term memory (VSTM) capacity estimated using simple objects, such as colours and oriented bars, may not generalise well to more naturalistic stimuli. More visual detail can be stored in VSTM when complex, recognisable objects are maintained compared to simple objects. It is not yet known if it is recognisability that enhances memory precision, nor whether maintenance of recognisable objects is achieved with the same network of brain regions supporting maintenance of simple objects. We used a novel stimulus generation method to parametrically warp photographic images along a continuum, allowing separate estimation of the precision of memory representations and the number of items retained. The stimulus generation method was also designed to create unrecognisable, though perceptually matched, stimuli, to investigate the impact of recognisability on VSTM. We adapted the widely-used change detection and continuous report paradigms for use with complex, photographic images. Across three functional magnetic resonance imaging (fMRI) experiments, we demonstrated greater precision for recognisable objects in VSTM compared to unrecognisable objects. This clear behavioural advantage was not the result of recruitment of additional brain regions, or of stronger mean activity within the core network. Representational similarity analysis revealed greater variability across item repetitions in the representations of recognisable, compared to unrecognisable complex objects. We therefore propose that a richer range of neural representations support VSTM for complex recognisable objects.
最近的证据表明,使用简单物体(如颜色和定向条)估计的视觉短期记忆(VSTM)容量可能无法很好地推广到更自然的刺激。与简单物体相比,当保持复杂、可识别的物体时,VSTM 可以存储更多的视觉细节。目前还不清楚是可识别性提高了记忆精度,还是识别物体的维持是通过支持简单物体维持的相同大脑区域网络来实现的。我们使用一种新颖的刺激生成方法,沿着连续体对摄影图像进行参数扭曲,允许分别估计记忆表示的精度和保留的项目数量。刺激生成方法还旨在创建不可识别但感知匹配的刺激,以研究可识别性对 VSTM 的影响。我们改编了广泛使用的变化检测和连续报告范式,以适应复杂的摄影图像。在三个功能磁共振成像(fMRI)实验中,我们在 VSTM 中发现可识别物体的精度明显高于不可识别物体。这种明显的行为优势不是由于额外的大脑区域的招募,也不是由于核心网络内的平均活动更强。代表性相似性分析显示,与不可识别的复杂物体相比,可识别复杂物体的表示在项目重复中具有更大的可变性。因此,我们提出,更丰富的神经表示范围支持复杂可识别物体的 VSTM。