ISSN 0439-755X
CN 11-1911/B
主办:中国心理学会
   中国科学院心理研究所
出版:科学出版社

心理学报 ›› 2025, Vol. 57 ›› Issue (2): 218-231.doi: 10.3724/SP.J.1041.2025.0218

• 研究报告 • 上一篇    下一篇

多种情感与认知任务驱动下大脑可泛化神经表征的发育模式

郝磊1,2, 许天委3, 周文龙3, 杨杰3, 彭思雅2, 刘明兰4, 徐家华5, 王延培2, 谭淑平5, 高家红6, 贺永2, 陶沙2, 董奇2, 秦绍正2   

  1. 1西南大学教师教育学院, 重庆 400715;
    2北京师范大学认知神经科学与学习国家重点实验室&IDG/麦戈文脑科学研究院, 北京 100875;
    3琼台师范学院海南省儿童认知与行为发展重点实验室, 海口 571127;
    4重庆市北碚区教师进修学院, 重庆 400700;
    5北京回龙观医院, 北京 100096;
    6北京大学前沿交叉学科研究院&IDG/麦戈文脑科学研究院, 北京 100871
  • 收稿日期:2024-03-10 发布日期:2024-12-20 出版日期:2025-02-25
  • 通讯作者: 秦绍正, E-mail: szqin@bnu.edu.cn
  • 基金资助:
    国家自然科学基金(32200871, 32130045, 32361163611, 82021004), 科技创新2030(2022ZD0211000, 2021ZD0200500), 高等学校学科创新引智基地(B21036), 重庆市自然科学基金面上项目(CSTB2023NSCQ-MSX0209), 海南省哲学社会科学规划课题(HNSK (ZC)22-206), 海南省自然科学基金面上项目(823MS063), 重庆市教育科学“十四五”规划重点课题(2021-10-073)资助

Developmental differences in generalizable neural representations driven by multiple emotional and cognitive tasks

HAO Lei1,2, XU Tianwei3, ZHOU Wenlong3, YANG Jie3, PENG Siya2, LIU Minglan4, XU Jiahua5, WANG Yanpei2, TAN Shuping5, GAO Jiahong6, HE Yong2, TAO Sha2, DONG Qi2, QIN Shaozheng2   

  1. 1College of Teacher Education, Southwest University, Chongqing 400715, China;
    2State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China;
    3Qiongtai Normal University Key Laboratory Of Child Cognition & Behavior Development Of Hainan Province, Haikou 571127, China;
    4Beibei Teacher Training College, Chongqing 400700, China;
    5Beijing HuiLongGuan Hospital, Peking University, Beijing 100096, China;
    6Center for MRI Research, Academy for Advanced Interdisciplinary Studies & McGovern Institute for Brain Research, Peking University, Beijing 100871, China
  • Received:2024-03-10 Online:2024-12-20 Published:2025-02-25

摘要: 从脑智发育视角来讲, 神经系统随着心理发展会产生出一系列具有功能特异化(specialization)且高度协同的模块。这些模块之间究竟如何协同支撑儿童情感与认知功能发展呢?本研究综合利用多个经典的情感与认知任务范式(含注意网络测试、情绪匹配和工作记忆任务)以及层级化(hierarchical)的多体素神经表征建模方法, 重点考察7~12岁学龄儿童多元需求(multi-demand)额顶系统在情感与认知任务驱动下的通用性(task-general)作用以及分层级神经表征的组织方式。结果表明:儿童低年龄组、儿童高年龄组和成人组被试均表现出了多元需求额顶系统(包括顶内沟和额眼区域)共同参与多种情感与认知任务的现象, 即跨任务共同激活; 值得强调的是, 学龄儿童多元需求额顶系统表现出了更低水平的跨任务神经表征可泛化性(generalizability), 而作为控制分析的前扣带回、背外侧前额叶和前脑岛则没有表现出组间的可泛化性差异。我们推测多元需求额顶系统在发育中可能作为一个潜在的通用性“枢纽”, 通过组构性(compositionality)的信息组织方式, 实现不同任务目标驱动下分层级的神经表征与计算, 进而支撑情感与认知功能随龄的发展。本研究突破了当前单任务范式视角下的发展认知神经科学研究框架, 有望为理解跨情感与认知领域的脑智发育工作原理和开发人工智能新型算法提供新的启示。

关键词: 情感与认知, 脑智发育, 特异化, 神经表征, 可泛化

Abstract: From the perspective of development, childhood is one of the most critical stage during brain development: neural system and cognitive behavior undergo a prolonged and intricate developmental process. A central question in developmental cognitive neuroscience pertains to how our brain develop highly specialized yet interacting neural modules to support a wide spectrum of cognitive and emotional functions. It is still inconclusive how these neural systems interplay and work together to promote cognitive and emotional maturation.
The early maturational perspective believed that as the anatomical structure of a specific cortical area matures, each neural module will “perform their duties” to support the development of corresponding cognitive functions. Later, the interactive specialization theory argued that there is a special brain function module with the properties of a general developmental architecture to support the development of different cognitive abilities, which can co-activate in multiple neurobiological models. Recently, researchers proposed a multi-demand system model, where the frontal-parietal network system supports various cognitive functions through diverse neural activation modes, fostering cognitive flexibility, and playing a role in coordinating and integrating different levels of neural computing resources across cognitive domains during children’s brain development. Based on the interactive specialization and multi-demand system model, the present study put forward the scientific questions: whether the multi-demand frontal-parietal system have a general neural representation pattern under different cognitive subdomain tasks, and how this pattern supports the development of children’s multiple cognitive domains through a hierarchical distributed neural representation organization.
Integrating traditional developmental psychology with non-invasive functional magnetic resonance imaging in cognitive neuroscience, we used multiple task paradigm (attention network test, numerical N-Back working memory and emotion matching tasks) across cognitive domains and innovative hierarchical distributed neural representation modeling to explore a general neural representation framework and its developmental rules for multiple cognitive domains. By building hierarchical distributed neural representation modeling method across multiple cognitive domains, we systematically investigate the developmental patterns of neural information representation in children and adults. The results indicated that both children and adults exhibited the phenomenon of the multiple-demand frontoparietal system (including the intraparietal sulcus and frontal eye area) jointly participating in a variety of emotional and cognitive tasks, that is, co-activation across tasks; it is worth emphasizing that the multiple-demand frontoparietal system in children showed lower levels of generalizability of neural representations across tasks, whereas the anterior cingulate gyrus, dorsolateral prefrontal cortex, and anterior insula, which were used as control analyses, did not show differences in generalizability between the groups.
We speculate that the multi-demand frontoparietal system may serve as a potential universal “hub” during development. Through compositional information coding organization, it can enable hierarchical neural representation and computation driven by different task goals, thereby supports the development of emotional and cognitive functions with age. This study breaks through the current research framework of developmental cognitive neuroscience from the perspective of a single-task paradigm and is expected to provide new insights into the working principles of brain development across emotional and cognitive domains, as well as to inspire the new artificial intelligence algorithms.

Key words: emotion and cognition, cognitive and brain development, specialization, neural representation, generalization

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