Background The question of whether large language models (LLMs) possess consciousness has been increasingly debated. Integrated information theory (IIT) offers a quantitative framework for assessing consciousness through a measure of integrated information.
Methods This study applied IIT principles to the architecture of transformer-based LLMs, focusing on causal integration, temporal persistence, and system irreducibility. Ablation experiments on Generative Pretrained Transformer 2 (GPT-2) were performed, selectively removing individual attention heads and measuring changes in perplexity as a behavioral proxy for integrated information to empirically approximate the measure of integrated information.
Results The ablation study of a single attention head produced minimal or negative changes in perplexity in four out of five representative sentences, indicating redundancy or noise. Only one sentence revealed a significant increase in perplexity change (ΔPPL +11.29), reflecting a localized but nonessential contribution. A comparison with biological systems demonstrated that LLMs meet the IIT criterion of differentiation, but fail to meet the criteria of integration, causal closure, and temporal persistence. These findings confirm that LLMs are architecturally decomposable, lack persistent internal states, and do not sustain global causal irreducibility. Philosophical considerations, including Searle’s Chinese Room argument, further support the idea that the linguistic fluency of LLMs arises from syntactic manipulation rather than semantic understanding.
Conclusion Current LLMs do not satisfy the structural and informational requirements of consciousness under IIT. Although capable of simulating intelligent language, LLMs remain unconscious systems with a negligible amount of integrated information, underscoring the distinction between linguistic competence and conscious experience.
We report on changes in the ascending reticular activating system (ARAS) concurrent with the recovery of impaired consciousness following rehabilitation and cranioplasty in a patient with traumatic brain injury (TBI), which were demonstrated on diffusion tensor tractography (DTT). A 34-year-old male patient was diagnosed with a traumatic intracerebral hemorrhage after falling from a height of approximately 7 m and underwent a right frontoparietotemporal decompressive craniectomy and hematoma removal. At 5 months after onset, when starting rehabilitation, the patient showed impaired consciousness, with a Glasgow Coma Scale (GCS) score of 4. Comprehensive rehabilitative therapy was provided until 14 months after onset, and his GCS score improved to 8. Cranioplasty was performed using auto-bone at 14 months after onset. One month after cranioplasty, his GCS score improved to 12. On the 15-month DTT, the deviated lower dorsal ARAS was restored on both sides, and the right side had become thicker. The right lower ventral ARAS was reconstructed, and increased neural connectivity of the upper ARAS was detected in both the prefrontal cortices. Thus, changes in the ARAS were demonstrated in a patient with TBI during recovery of consciousness following rehabilitation and cranioplasty.
Awareness during general anesthesia occurs in approximately 0.1–0.2% of cases; nevertheless, particular attention is required because it can lead to critical complications including insomnia, depression, anxiety, and post-traumatic stress disorder. To prevent these complications, bispectral index (BIS) and end-tidal anesthetic gas (ETAG) concentration monitoring are commonly used to examine patient consciousness during surgery. In the present case, an 80-year-old man was scheduled for total gastrectomy. Anesthesia was maintained using desflurane 4.0–5.0% vol, oxygen, and nitrous oxide. The authors simultaneously monitored BIS, which was maintained between 37 and 43, and ETAG, which was maintained between 0.9 and 1.2 minimum alveolar concentration (MAC). After the operation, however, the authors were surprised to learn that the patient complained of awareness during anesthesia. Although BIS and ETAG concentration monitoring are useful in preventing awareness during anesthesia, they cannot be completely trusted. Even though BIS was maintained at approximately 40 and ETAG at 0.7–1.3 MAC, awareness during anesthesia occurred.
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