How does the brain process natural visual stimuli to make a decision? Imagine driving through fog. An object looms ahead. What do you do? This decision requires not only identifying the object but also choosing an action based on your decision confidence. In this circumstance, confidence is making a bridge between seeing and believing. Our study unveils how the brain processes visual information to make such decisions with an assessment of confidence, using a model inspired by the visual cortex. To computationally model the process, this study uses a spiking neural network inspired by the hierarchy of the visual cortex in mammals to investigate the dynamics of feedforward object recognition and decision-making in the brain. The model consists of two modules: a temporal dynamic object representation module and an attractor neural network-based decision-making module. Unlike traditional models, ours captures the evolution of evidence within the visual cortex, mimicking how confidence forms in the brain. This offers a more biologically plausible approach to decision-making when encountering real-world stimuli. We conducted experiments using natural stimuli and measured accuracy, reaction time, and confidence. The model's estimated confidence aligns remarkably well with human-reported confidence. Furthermore, the model can simulate the human change-of-mind phenomenon, reflecting the ongoing evaluation of evidence in the brain. Also, this finding offers decision-making and confidence encoding share the same neural circuit.

中文翻译：

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物体识别任务中决策和置信度的神经计算模型

大脑如何处理自然视觉刺激来做出决定？想象一下在雾中行驶。前方出现一个物体。你做什么工作？这个决定不仅需要识别对象，还需要根据你的决策信心来选择行动。在这种情况下，信心正在搭建看到和相信之间的桥梁。我们的研究揭示了大脑如何处理视觉信息，并使用受视觉皮层启发的模型来评估置信度来做出此类决策。为了对这一过程进行计算建模，本研究使用受哺乳动物视觉皮层层次结构启发的尖峰神经网络来研究大脑中前馈对象识别和决策的动态。该模型由两个模块组成：时间动态对象表示模块和基于吸引子神经网络的决策模块。与传统模型不同，我们的模型捕捉视觉皮层内证据的演变，模仿大脑中信心的形成方式。当遇到现实世界的刺激时，这提供了一种在生物学上更合理的决策方法。我们利用自然刺激进行了实验，并测量了准确性、反应时间和置信度。该模型的估计置信度与人类报告的置信度非常吻合。此外，该模型可以模拟人类改变想法的现象，反映大脑中对证据的持续评估。此外，这一发现表明决策和置信编码共享相同的神经回路。