Neural language models, particularly large-scale ones, have been consistently
proven to be most effective in predicting brain neural activity across a range
of studies. However, previous research overlooked the comparison of these
models with psychologically plausible ones. Moreover, evaluations were reliant
on limited, single-modality, and English cognitive datasets. To address these
questions, we conducted an analysis comparing encoding performance of various
neural language models and psychologically plausible models. Our study utilized
extensive multi-modal cognitive datasets, examining bilingual word and
discourse levels. Surprisingly, our findings revealed that psychologically
plausible models outperformed neural language models across diverse contexts,
encompassing different modalities such as fMRI and eye-tracking, and spanning
languages from English to Chinese. Among psychologically plausible models, the
one incorporating embodied information emerged as particularly exceptional.
This model demonstrated superior performance at both word and discourse levels,
exhibiting robust prediction of brain activation across numerous regions in
both English and Chinese.

比较神经语言模型和心理可信模型，发现心理可信模型在多种多样的背景下（包括多模态数据集、不同语言等）表现更优，尤其是在融合具象信息的心理可信模型中，对单词和段落层面的大脑活动预测表现最佳。

脑语言表征导航：神经语言模型与心理合理模型的比较分析

Navigating Brain Language Representations: A Comparative Analysis of  Neural Language Models and Psychologically Plausible Models

Interactions with large language models have led to the suggestion that these
models may be conscious. From the perspective of neuroscience, this position is
difficult to defend. For one, the architecture of large language models is
missing key features of the thalamocortical system that have been linked to
conscious awareness in mammals. Secondly, the inputs to large language models
lack the embodied, embedded information content characteristic of our sensory
contact with the world around us. Finally, while the previous two arguments can
be overcome in future AI systems, the third one might be harder to bridge in
the near future. Namely, we argue that consciousness might depend on having
'skin in the game', in that the existence of the system depends on its actions,
which is not true for present-day artificial intelligence.

该论文研究了大型语言模型是否具有自我意识，从神经科学的角度出发，作者认为这一观点难以被证实，因为这种模型缺少与哺乳动物意识密切相关的丘脑皮质系统的关键特征，且这些模型的输入缺乏与我们周围世界的感官接触特征的具体信息。作者认为，意识存在于 “皮肤在游戏中” 的情境中，而目前的人工智能系统尚未具备这一特征。