Dominick Purpura Department of Neuroscience.
Dominick Purpura Department of Neuroscience,
J Neurosci. 2019 Aug 21;39(34):6714-6727. doi: 10.1523/JNEUROSCI.0035-19.2019. Epub 2019 Jun 24.
Our understanding of the neural basis of perceptual decision making has been built in part on relating co-fluctuations of single neuron responses to perceptual decisions on a trial-by-trial basis. The strength of this relationship is often compared across neurons or brain areas, recorded in different sessions, animals, or variants of a task. We sought to extend our understanding of perceptual decision making in three ways. First, we measured neuronal activity simultaneously in early [primary visual cortex (V1)] and midlevel (V4) visual cortex while macaque monkeys performed a fine orientation discrimination perceptual task. This allowed a direct comparison of choice signals in these two areas, including their dynamics. Second, we asked how our ability to predict animals' decisions would be improved by considering small simultaneously-recorded neuronal populations rather than individual units. Finally, we asked whether predictions would be improved by taking into account the animals' choice and reward histories, which can strongly influence decision making. We found that responses of individual V4 neurons were weakly predictive of decisions, but only in a brief epoch between stimulus offset and the indication of choice. In V1, few neurons showed significant decision-related activity. Analysis of neuronal population responses revealed robust choice-related information in V4 and substantially weaker signals in V1. Including choice- and reward-history information improved performance further, particularly when the recorded populations contained little decision-related information. Our work shows the power of using neuronal populations and decision history when relating neuronal responses to the perceptual decisions they are thought to underlie. Decades of research has provided a rich description of how visual information is represented in the visual cortex. Yet how cortical responses relate to visual perception remains poorly understood. Here we relate fluctuations in small neuronal population responses, recorded simultaneously in primary visual cortex (V1) and area V4 of monkeys, to perceptual reports in an orientation discrimination task. Choice-related signals were robust in V4, particularly late in the behavioral trial, but not in V1. Models that include both neuronal responses and choice-history information were able to predict a substantial portion of decisions. Our work shows the power of integrating information across neurons and including decision history in relating neuronal responses to perceptual decisions.
我们对感知决策的神经基础的理解部分是基于在逐次试验的基础上将单个神经元反应的共同波动与感知决策联系起来。通常会在不同的会话、动物或任务变体中记录不同神经元或脑区的这种关系强度进行比较。我们试图从三个方面扩展我们对感知决策的理解。首先,当猕猴执行精细方向辨别感知任务时,我们同时测量早期[初级视觉皮层 (V1)]和中脑 (V4) 视觉皮层的神经元活动。这允许直接比较这两个区域的选择信号,包括它们的动态。其次,我们询问通过考虑同时记录的小神经元群体而不是单个单元,我们预测动物决策的能力将如何提高。最后,我们询问通过考虑动物的选择和奖励历史是否可以改善预测,这些历史可以强烈影响决策。我们发现,单个 V4 神经元的反应可以微弱地预测决策,但仅在刺激结束和选择指示之间的短暂时期内。在 V1 中,很少有神经元表现出与决策相关的活动。对神经元群体反应的分析显示,V4 中存在强大的选择相关信息,而 V1 中的信号则弱得多。包含选择和奖励历史信息可进一步提高性能,特别是当记录的群体包含很少的决策相关信息时。我们的工作表明,当将神经元反应与它们所依据的感知决策联系起来时,使用神经元群体和决策历史的力量。几十年的研究提供了丰富的描述,说明了视觉信息在视觉皮层中的表示方式。然而,皮质反应与视觉感知的关系仍然知之甚少。在这里,我们将猴子初级视觉皮层 (V1) 和 V4 区域同时记录的小神经元群体反应的波动与方向辨别任务中的感知报告联系起来。选择相关的信号在 V4 中非常强大,尤其是在行为试验的后期,但在 V1 中则不然。包含神经元反应和选择历史信息的模型能够预测相当一部分决策。我们的工作表明,整合跨神经元的信息并在将神经元反应与感知决策联系起来时包含决策历史的力量。