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Small Networks Encode Decision-Making in Primary Auditory Cortex

机译：小型网络在主要听觉皮层中编码决策

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Sensory detection tasks enhance representations of behaviorally meaningful stimuli in primary auditory cortex (A1). However, it remains unclear how A1 encodes decision-making. Neurons in A1 layer 2/3 (L2/3) show heterogeneous stimulus selectivity and complex anatomical connectivity, and receive input from prefrontal cortex. Thus, task-related modulation of activity in A1 L2/3 might differ across subpopulations. To study the neural coding of decision-making, we used two-photon imaging in A1 L2/3 of mice performing a tone-detection task. Neural responses to targets showed attentional gain and encoded behavioral choice. To characterize network representation of behavioral choice, we analyzed functional connectivity using Granger causality, pairwise noise correlations, and neural decoding. During task performance, small groups of four to five neurons became sparsely linked, locally clustered, and rostro-caudally oriented, while noise correlations both increased and decreased. Our results suggest that sensory-based decision-making involves small neural networks driven by the sum of sensory input, attentional gain, and behavioral choice.
机译：感官检测任务在主要听觉皮层（A1）中增强了行为有意义的刺激的表示。但是，它仍然尚不清楚A1编码决策如何。 A1层2/3（L2 / 3）中的神经元显示出异构刺激选择性和复杂的解剖连接，并从预逆转皮层接收输入。因此，A1 L2 / 3中的任务相关调制可能在亚步骤中不同。为了研究决策的神经编码，我们在执行音调检测任务的A1 L2 / 3小鼠中使用了双光子成像。对目标的神经响应表现出注意的增益和编码的行为选择。为了表征行为选择的网络表示，我们使用Granger因果关系，成对噪声相关和神经解码分析了功能连接。在任务性能期间，四到五个神经元的小组变得稀疏地连接，局部聚类和梁尾导向，而噪声相关性增加和减少。我们的研究结果表明，基于感官的决策涉及由感官输入，注意力增益和行为选择的总和驱动的小神经网络。

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