Pulvermüller Friedemann, Garagnani Max
Brain Language Laboratory, Department of Philosophy, Freie Universität Berlin, Berlin, Germany.
Brain Language Laboratory, Department of Philosophy, Freie Universität Berlin, Berlin, Germany; School of Computing and Mathematics, Plymouth University, Plymouth, UK.
Cortex. 2014 Aug;57:1-21. doi: 10.1016/j.cortex.2014.02.015. Epub 2014 Mar 11.
Memory cells, the ultimate neurobiological substrates of working memory, remain active for several seconds and are most commonly found in prefrontal cortex and higher multisensory areas. However, if correlated activity in "embodied" sensorimotor systems underlies the formation of memory traces, why should memory cells emerge in areas distant from their antecedent activations in sensorimotor areas, thus leading to "disembodiment" (movement away from sensorimotor systems) of memory mechanisms? We modelled the formation of memory circuits in six-area neurocomputational architectures, implementing motor and sensory primary, secondary and higher association areas in frontotemporal cortices along with known between-area neuroanatomical connections. Sensorimotor learning driven by Hebbian neuroplasticity led to formation of cell assemblies distributed across the different areas of the network. These action-perception circuits (APCs) ignited fully when stimulated, thus providing a neural basis for long-term memory (LTM) of sensorimotor information linked by learning. Subsequent to ignition, activity vanished rapidly from APC neurons in sensorimotor areas but persisted in those in multimodal prefrontal and temporal areas. Such persistent activity provides a mechanism for working memory for actions, perceptions and symbols, including short-term phonological and semantic storage. Cell assembly ignition and "disembodied" working memory retreat of activity to multimodal areas are documented in the neurocomputational models' activity dynamics, at the level of single cells, circuits, and cortical areas. Memory disembodiment is explained neuromechanistically by APC formation and structural neuroanatomical features of the model networks, especially the central role of multimodal prefrontal and temporal cortices in bridging between sensory and motor areas. These simulations answer the "where" question of cortical working memory in terms of distributed APCs and their inner structure, which is, in part, determined by neuroanatomical structure. As the neurocomputational model provides a mechanistic explanation of how memory-related "disembodied" neuronal activity emerges in "embodied" APCs, it may be key to solving aspects of the embodiment debate and eventually to a better understanding of cognitive brain functions.
记忆细胞作为工作记忆的最终神经生物学基质，能活跃数秒，且最常见于前额叶皮质和更高层次的多感觉区域。然而，如果“具身化”感觉运动系统中的相关活动是记忆痕迹形成的基础，那么为什么记忆细胞会出现在远离其在感觉运动区域先前激活部位的区域，从而导致记忆机制的“去具身化”（从感觉运动系统脱离）呢？我们在六区域神经计算架构中对记忆回路的形成进行了建模，在额颞叶皮质中实现了运动和感觉的初级、次级及更高层次的联合区域，以及已知的区域间神经解剖连接。由赫布神经可塑性驱动的感觉运动学习导致了分布在网络不同区域的细胞集合的形成。这些动作 - 感知回路（APCs）在受到刺激时会完全激活，从而为通过学习关联起来的感觉运动信息的长期记忆（LTM）提供了神经基础。激活之后，感觉运动区域的APC神经元活动迅速消失，但多模态前额叶和颞叶区域的神经元活动持续存在。这种持续的活动为动作、感知和符号的工作记忆提供了一种机制，包括短期语音和语义存储。在神经计算模型的活动动态中，在单细胞、回路和皮质区域层面都记录了细胞集合激活以及活动向多模态区域的“去具身化”工作记忆退缩。记忆去具身化通过APC的形成以及模型网络的结构神经解剖特征从神经机制上得到了解释，特别是多模态前额叶和颞叶皮质在连接感觉和运动区域方面的核心作用。这些模拟从分布式APC及其内部结构的角度回答了皮质工作记忆的“位置”问题，而分布式APC及其内部结构部分由神经解剖结构决定。由于神经计算模型为记忆相关的“去具身化”神经元活动如何在“具身化”的APCs中出现提供了一个机械性解释，它可能是解决具身化争论的某些方面以及最终更好地理解认知脑功能的关键。
