The ability to manipulate logical-mathematical symbols (LMS), encompassing
tasks such as calculation, reasoning, and programming, is a cognitive skill
arguably unique to humans. Considering the relatively recent emergence of this
ability in human evolutionary history, it has been suggested that LMS
processing may build upon more fundamental cognitive systems, possibly through
neuronal recycling. Previous studies have pinpointed two primary candidates,
natural language processing and spatial cognition. Existing comparisons between
these domains largely relied on task-level comparison, which may be confounded
by task idiosyncrasy. The present study instead compared the neural correlates
at the domain level with both automated meta-analysis and synthesized maps
based on three representative LMS tasks, reasoning, calculation, and mental
programming. Our results revealed a more substantial cortical overlap between
LMS processing and spatial cognition, in contrast to language processing.
Furthermore, in regions activated by both spatial and language processing, the
multivariate activation pattern for LMS processing exhibited greater
multivariate similarity to spatial cognition than to language processing. A
hierarchical clustering analysis further indicated that typical LMS tasks were
indistinguishable from spatial cognition tasks at the neural level, suggesting
an inherent connection between these two cognitive processes. Taken together,
our findings support the hypothesis that spatial cognition is likely the basis
of LMS processing, which may shed light on the limitations of large language
models in logical reasoning, particularly those trained exclusively on textual
data without explicit emphasis on spatial content.

逻辑数学符号处理可能建立在更基本的认知系统之上，可能通过神经回收实现，而空间认知与逻辑数学符号处理之间存在更大的皮层重叠性，这为大型语言模型在逻辑推理方面的局限性提供了启示。