Boyd Isaac Paul, Nocon Jian Carlo, Gritton Howard, Han Xue, Sen Kamal
Neurophotonics Center, Boston University, Boston, Massachusetts, United States.
Center for Systems Neuroscience, Boston University, Boston, Massachusetts, United States.
J Neurophysiol. 2025 Jul 1;134(1):53-66. doi: 10.1152/jn.00283.2024. Epub 2025 May 13.
Cortical circuits feature both excitatory and inhibitory cells that underlie the encoding of dynamic sensory stimuli, e.g., speech, music, odors, and natural scenes. Although previous studies have shown that inhibition plays an important role in shaping the neural code, how excitatory and inhibitory cells coordinate to enhance encoding of temporally dynamic stimuli is not fully understood. Recent experimental recordings in the mouse auditory cortex have shown that optogenetic suppression of parvalbumin neurons results in a decrease of neural discriminability of dynamic stimuli. Here, we present a multilayer model of a cortical circuit that mechanistically explains these results. The model is based on parvalbumin neurons that respond to both stimulus onsets and offsets, as observed experimentally, and incorporates characteristic short-term synaptic plasticity profiles of excitatory and parvalbumin neurons. We also explore different network architectures consistent with experimental results. The model reveals that tuning the relative strengths of onset and offset inputs to parvalbumin neurons and network parameters generates different regimes of coding dominated by rapid firing rate modulations or spike timing. Moreover, the model replicates the experimentally observed reduction in neural discrimination performance during optogenetic suppression of parvalbumin neurons. These results suggest that distinct onset and offset inputs to parvalbumin neurons enhance cortical discriminability of dynamic stimuli by encoding distinct temporal features, enhancing temporal coding, and reducing cortical noise. Here, we propose a model for the mechanisms that underlie neuron responses in the auditory cortex. This study focuses on a cortical circuit involving excitatory and inhibitory (parvalbumin) neurons. Using physiologically relevant parameters in the proposed model network, we show that we can recreate observed results in live studies.
皮质回路包含兴奋性和抑制性细胞，它们是动态感觉刺激（如语音、音乐、气味和自然场景）编码的基础。尽管先前的研究表明抑制在塑造神经编码中起重要作用，但兴奋性和抑制性细胞如何协同以增强对时间动态刺激的编码仍未完全理解。最近在小鼠听觉皮层的实验记录表明，光遗传学抑制小白蛋白神经元会导致动态刺激的神经辨别能力下降。在此，我们提出了一个皮质回路的多层模型，从机制上解释了这些结果。该模型基于实验观察到的对刺激起始和结束均有反应的小白蛋白神经元，并纳入了兴奋性和小白蛋白神经元的特征性短期突触可塑性特征。我们还探索了与实验结果一致的不同网络架构。该模型表明，调整小白蛋白神经元起始和结束输入的相对强度以及网络参数会产生由快速发放率调制或尖峰时间主导的不同编码模式。此外，该模型重现了光遗传学抑制小白蛋白神经元期间实验观察到的神经辨别性能下降。这些结果表明，对小白蛋白神经元不同的起始和结束输入通过编码不同的时间特征、增强时间编码和降低皮质噪声来增强动态刺激的皮质辨别能力。在此，我们提出了一个关于听觉皮层神经元反应基础机制的模型。本研究聚焦于一个涉及兴奋性和抑制性（小白蛋白）神经元的皮质回路。在所提出的模型网络中使用生理相关参数，我们表明我们可以重现活体研究中观察到的结果。
