Cognitive Neuroimaging Unit, INSERM, CEA, CNRS, Université Paris-Saclay, NeuroSpin center, Gif-sur-Yvette, France.
EDUWELL team, Lyon Neuroscience Research Centre, INSERM U1028, CNRS UMR5292, Lyon 1 University, Lyon, France.
Nat Commun. 2024 Jan 17;15(1):572. doi: 10.1038/s41467-024-44810-5.
Much of human culture's advanced technology owes its existence to the ability to mentally manipulate quantities. Neuroscience has described the brain regions overall recruited by numerical tasks and the neuronal codes representing individual quantities during perceptual tasks. Nevertheless, it remains unknown how quantity representations are combined or transformed during mental computations and how specific quantities are coded in the brain when generated as the result of internal computations rather than evoked by a stimulus. Here, we imaged the brains of adult human subjects at 7 Tesla during an approximate calculation task designed to disentangle in- and outputs of the computation from the operation itself. While physically presented sample numerosities were distinguished in activity patterns along the dorsal visual pathway and within frontal and occipito-temporal regions, a representation of the internally generated result was most prominently detected in higher order regions such as angular gyrus and lateral prefrontal cortex. Behavioral precision in the task was related to cross-decoding performance between sample and result representations in medial IPS regions. This suggests the transformation of sample into result may be carried out within dorsal stream sensory-motor integration regions, and resulting outputs maintained for task purposes in higher-level regions in a format possibly detached from sensory-evoked inputs.
人类文化的许多先进技术都归功于其在心理上处理数量的能力。神经科学已经描述了整体上被数字任务招募的大脑区域,以及在感知任务中表示单个数量的神经元代码。然而,目前尚不清楚数量表示在心理计算过程中是如何结合或转换的,以及当数量是由内部计算产生而不是由刺激引起时,它们在大脑中是如何被编码的。在这里,我们在 7 特斯拉的成人被试者的大脑中进行了成像,在这个近似计算任务中,我们试图将计算的输入和输出与计算本身分离开来。虽然在活动模式中沿着背侧视觉通路以及在额顶叶区域内区分了物理呈现的样本数量,但内部生成的结果的表示在更高阶的区域中最为明显,例如角回和外侧前额叶皮层。在任务中的行为精度与内侧 IPS 区域中样本和结果表示之间的交叉解码性能相关。这表明,从样本到结果的转换可能是在背侧流感觉运动整合区域内进行的,并且输出结果以可能与感觉诱发输入分离的格式在更高阶的区域中保持,以便完成任务。