New York Medical College, Valhalla, NY, 10595, USA.
Biochem Biophys Res Commun. 2024 Aug 20;721:150141. doi: 10.1016/j.bbrc.2024.150141. Epub 2024 May 18.
The applicability of computational and dynamical systems models to organisms is scrutinized, using examples from developmental biology and cognition. Developmental morphogenesis is dependent on the inherent material properties of developing animal (metazoan) tissues, a non-computational modality, but cell differentiation, which utilizes chromatin-based revisable memory banks and program-like function-calling, via the developmental gene co-expression system unique to the metazoans, has a quasi-computational basis. Multi-attractor dynamical models are argued to be misapplied to global properties of development, and it is suggested that along with computationalism, classic forms of dynamicism are similarly unsuitable to accounting for cognitive phenomena. Proposals are made for treating brains and other nervous tissues as novel forms of excitable matter with inherent properties which enable the intensification of cell-based basal cognition capabilities present throughout the tree of life. Finally, some connections are drawn between the viewpoint described here and active inference models of cognition, such as the Free Energy Principle.
使用来自发育生物学和认知科学的例子,仔细研究了计算和动力系统模型在生物体中的适用性。发育形态发生依赖于发育动物(后生动物)组织的固有材料特性,这是非计算模态,但细胞分化利用基于染色质的可重写记忆库和类似程序的功能调用,通过后生动物特有的发育基因共表达系统,具有准计算基础。多吸引子动力模型被认为不适用于发育的全局性质,并且有人认为,与计算主义一样,经典形式的动力论也同样不适合解释认知现象。有人提出将大脑和其他神经组织视为具有内在属性的新型可兴奋物质,这些属性能够增强存在于整个生命之树中的基于细胞的基本认知能力。最后,这里描述的观点与认知的主动推理模型(如自由能原理)之间建立了一些联系。