Neural processing of sounds in the dorsal and ventral streams of the (human) auditory cortex is optimized for analyzing fine-grained temporal and spectral information, respectively. Here we use a Wilson and Cowan firing-rate modeling framework to simulate spectro-temporal processing of sounds in these auditory streams and to investigate the link between neural population activity and behavioral results of psychoacoustic experiments. The proposed model consisted of two core (A1 and R, representing primary areas) and two belt (Slow and Fast, representing rostral and caudal processing respectively) areas, differing in terms of their spectral and temporal response properties. First, we simulated the responses to amplitude modulated (AM) noise and tones. In agreement with electrophysiological results, we observed an area-dependent transition from a temporal (synchronization) to a rate code when moving from low to high modulation rates. Simulated neural responses in a task of amplitude modulation detection suggested that thresholds derived from population responses in core areas closely resembled those of psychoacoustic experiments in human listeners. For tones, simulated modulation threshold functions were found to be dependent on the carrier frequency. Second, we simulated the responses to complex tones with missing fundamental stimuli and found that synchronization of responses in the Fast area accurately encoded pitch, with the strength of synchronization depending on number and order of harmonic components. Finally, using speech stimuli, we showed that the spectral and temporal structure of the speech was reflected in parallel by the modeled areas. The analyses highlighted that the Slow stream coded with high spectral precision the aspects of the speech signal characterized by slow temporal changes (e.g., prosody), while the Fast stream encoded primarily the faster changes (e.g., phonemes, consonants, temporal pitch). Interestingly, the pitch of a speaker was encoded both spatially (i.e., tonotopically) in Slow area and temporally in Fast area. Overall, performed simulations showed that the model is valuable for generating hypotheses on how the different cortical areas/streams may contribute toward behaviorally relevant aspects of auditory processing. The model can be used in combination with physiological models of neurovascular coupling to generate predictions for human functional MRI experiments.

中文翻译：

---

听觉皮层双流计算模型中的光谱时间处理

对（人类）听觉皮层背侧和腹侧流中声音的神经处理进行了优化，分别用于分析细粒度的时间和频谱信息。在这里，我们使用 Wilson 和 Cowan 放电率建模框架来模拟这些听觉流中声音的光谱时间处理，并研究神经群体活动与心理声学实验的行为结果之间的联系。所提出的模型由两个核心（A1 和 R，代表主要区域）和两个带（慢和快，分别代表头端和尾端处理）区域组成，它们的光谱和时间响应特性不同。首先，我们模拟了对调幅 (AM) 噪声和音调的响应。与电生理结果一致，我们观察到从低调制率到高调制率时从时间（同步）到速率代码的区域相关转换。幅度调制检测任务中的模拟神经反应表明，源自核心区域人口反应的阈值与人类听众心理声学实验的阈值非常相似。对于音调，发现模拟调制阈值函数依赖于载波频率。其次，我们模拟了对缺少基本刺激的复杂音调的响应，发现快速区域中的响应同步准确地编码了音调，同步强度取决于谐波分量的数量和阶数。最后，利用言语刺激，我们展示了语音的频谱和时间结构由建模区域并行反映。分析强调，慢流以高频谱精度对语音信号特征为缓慢的时间变化（例如韵律）的方面进行编码，而快速流主要对较快的变化（例如，音素、辅音、时间音高）进行编码。有趣的是，说话者的音调在慢速区域和快速区域在空间上（即，音调）被编码。总体而言，执行的模拟表明，该模型对于生成关于不同皮层区域/流如何对听觉处理的行为相关方面做出贡献的假设是有价值的。