Exploring tinnitus-like central hyperactivity in a large language model-based computational analog of hearing loss

Tinnitus is commonly associated with maladaptive neural plasticity following hearing loss. Although large language models (LLMs) share similarities with the human brain in language processing and representation, their potential for modeling tinnitus-related neural mechanisms remains limited. This study aimed to develop an LLM-based framework to investigate tinnitus-related maladaptive neural plasticity. An LLM was partitioned into eight independently trainable regions. An exploratory computational analogy of deafferentation-related changes associated with peripheral hearing loss was developed by applying token-specific high-frequency attenuation during training on a commonsense reasoning task. Region-specific contributions to tinnitus-like excess activity were quantified using region-wise plasticity ablation, selectively disabling plasticity in one region at a time. Representational relationships among regions were evaluated using centered kernel alignment. The computational deafferentation analog largely preserved task accuracy but showed increased activity. Region 1 was the only region with a net suppressive contribution to excess activity, whereas region 2 exhibited the largest positive contribution; regions 6 and 8 also contributed positively. Regions 1 and 2 remained representationally distinct across all conditions. Deafferentation tended to reduce region 1-region 2 similarity, whereas plasticity ablation in most regions, except for regions 6 and 8, tended to increase it. The proposed LLM-based framework captured network-level functional dissociations consistent with current theories of hearing loss-associated tinnitus, identifying distinct suppressive, transformation, and higher-order modulatory roles. These findings highlight the potential of LLMs to investigate maladaptive neural changes underlying tinnitus. This framework may provide the foundation for constructing patient-specific digital twins.