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随机共振耳鸣模型十年综述。从幻听感知到适应性感官优化的神经计算理论，整合信息论、适应性信号检测、多通道听觉处理和跨模态可塑性。
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| name | stochastic-resonance-tinnitus-review |
| description | 随机共振耳鸣模型十年综述。从幻听感知到适应性感官优化的神经计算理论，整合信息论、适应性信号检测、多通道听觉处理和跨模态可塑性。 |
| arxiv_id | 2606.17736 |
| authors | Patrick Krauss, Achim Schilling |
| published | 2026-06-16T00:00:00.000Z |
| categories | q-bio.NC |
主观性耳鸣——无外界声刺激下的声音感知——是听觉神经科学最具争议的现象之一。本文综述2016年提出的随机共振(SR)模型，将耳鸣相关神经过度活跃重新定义为听力损失后的适应性神经噪声上调，耳鸣作为适应性感官优化的副作用。
| 传统观点 | SR模型新观点 |
|---|---|
| 神经过度活跃 = 病理 dysfunction | 神经噪声上调 = 适应性机制 |
| 需要抑制过度活跃 | 需要优化噪声水平 |
| 关注病理治疗 | 关注信息优化原则 |
SNR(ξ) = μ/(σ_ξ) # 信噪比
I(ξ) = f(SNR) # 信息传输率
最优噪声水平: ξ_opt where dI/dξ = 0
# Step 1: 听力评估
audiogram = assess_hearing_loss()
# Step 2: 识别耳鸣频率
tinnitus_freq = identify_tinnitus_frequency()
# Step 3: 计算匹配噪声频谱
noise_spectrum = generate_matched_noise(
audiogram,
tinnitus_freq,
amplitude='near_threshold' # 近阈值强度
)
# Step 4: 持续刺激
apply_stimulation(noise_spectrum, duration=6h)
Krauss P, Schilling A. (2026) "Ten Years of the Stochastic Resonance Model of Tinnitus: From Phantom Perception to Adaptive Sensory Optimization" arXiv:2606.17736
随机共振, 耳鸣模型, 听觉神经科学, 适应性感官优化, 信息论, 神经噪声, 频谱匹配刺激, 跨模态可塑性, 预测编码, 幻听感知, 神经计算理论