Liu Feng, Wang Xiao-Jing
Department of Physics, Nanjing University, Nanjing, PR China.
PLoS Comput Biol. 2008 Dec;4(12):e1000253. doi: 10.1371/journal.pcbi.1000253. Epub 2008 Dec 26.
Perception involves two types of decisions about the sensory world: identification of stimulus features as analog quantities, or discrimination of the same stimulus features among a set of discrete alternatives. Veridical judgment and categorical discrimination have traditionally been conceptualized as two distinct computational problems. Here, we found that these two types of decision making can be subserved by a shared cortical circuit mechanism. We used a continuous recurrent network model to simulate two monkey experiments in which subjects were required to make either a two-alternative forced choice or a veridical judgment about the direction of random-dot motion. The model network is endowed with a continuum of bell-shaped population activity patterns, each representing a possible motion direction. Slow recurrent excitation underlies accumulation of sensory evidence, and its interplay with strong recurrent inhibition leads to decision behaviors. The model reproduced the monkey's performance as well as single-neuron activity in the categorical discrimination task. Furthermore, we examined how direction identification is determined by a combination of sensory stimulation and microstimulation. Using a population-vector measure, we found that direction judgments instantiate winner-take-all (with the population vector coinciding with either the coherent motion direction or the electrically elicited motion direction) when two stimuli are far apart, or vector averaging (with the population vector falling between the two directions) when two stimuli are close to each other. Interestingly, for a broad range of intermediate angular distances between the two stimuli, the network displays a mixed strategy in the sense that direction estimates are stochastically produced by winner-take-all on some trials and by vector averaging on the other trials, a model prediction that is experimentally testable. This work thus lends support to a common neurodynamic framework for both veridical judgment and categorical discrimination in perceptual decision making.
将刺激特征识别为模拟量,或在一组离散选项中区分相同的刺激特征。传统上,如实判断和分类辨别被概念化为两个不同的计算问题。在这里,我们发现这两种决策类型可以由共享的皮质回路机制来支持。我们使用连续循环网络模型来模拟两项猴子实验,在实验中,要求受试者对随机点运动的方向进行二选一的强制选择或如实判断。模型网络具有一系列钟形的群体活动模式,每个模式代表一个可能的运动方向。缓慢的循环兴奋是感觉证据积累的基础,其与强烈的循环抑制的相互作用导致决策行为。该模型在分类辨别任务中再现了猴子的表现以及单神经元活动。此外,我们研究了方向识别是如何由感觉刺激和微刺激的组合来决定的。使用群体向量测量方法,我们发现当两个刺激相距较远时,方向判断体现为胜者全得(群体向量与连贯运动方向或电诱发运动方向一致),而当两个刺激彼此接近时,则体现为向量平均(群体向量落在两个方向之间)。有趣的是,对于两个刺激之间广泛的中间角距离范围,网络显示出一种混合策略,即方向估计在某些试验中由胜者全得随机产生,而在其他试验中由向量平均产生,这是一个可通过实验验证的模型预测。因此,这项工作为感知决策中的如实判断和分类辨别提供了一个共同的神经动力学框架。