Diaz Jessica A, Pisauro M Andrea, Delis Ioannis, Philiastides Marios G
School of Social Sciences, College of Psychology Birmingham City University, Birmingham, United Kingdom.
School of Psychology and Neuroscience University of Glasgow, Glasgow, United Kingdom.
Imaging Neurosci (Camb). 2024 Nov 18;2. doi: 10.1162/imag_a_00338. eCollection 2024.
The prior probability of an upcoming stimulus has been shown to influence the formation of perceptual decisions. Computationally, these effects have typically been attributed to changes in the starting point (i.e., baseline) of evidence accumulation in sequential sampling models. More recently, it has also been proposed that prior probability might additionally lead to changes in the rate of evidence accumulation. Here, we introduce a neurally-informed behavioural modelling approach to understand whether prior probability influences the starting point, the rate of evidence accumulation or both. To this end, we employ a well-established visual object categorisation task for which two neural components underpinning participants' choices have been characterised using single-trial analysis of the electroencephalogram. These components are reliable measures of trial-by-trial variability in the quality of the relevant decision evidence, which we use to constrain the estimation of a hierarchical drift diffusion model of perceptual choice. We find that, unlike previous computational accounts, constraining the model with the endogenous variability in the relevant decision evidence results in prior probability effects being explained primarily by changes in the rate of evidence accumulation rather than changes in the starting point or a combination of both. Ultimately, our neurally-informed modelling approach helps disambiguate the mechanistic effect of prior probability on perceptual decision formation, suggesting that prior probability biases primarily the interpretation of sensory evidence towards the most likely stimulus.
研究表明，即将到来的刺激的先验概率会影响知觉决策的形成。从计算角度来看，这些效应通常归因于顺序抽样模型中证据积累起点（即基线）的变化。最近，也有人提出先验概率可能还会导致证据积累速率的变化。在此，我们引入一种基于神经信息的行为建模方法，以了解先验概率是影响起点、证据积累速率还是两者皆有影响。为此，我们采用了一个成熟的视觉物体分类任务，通过对脑电图的单次试验分析，已经确定了支撑参与者选择的两个神经成分。这些成分是相关决策证据质量逐次试验变异性的可靠度量，我们用它们来约束对知觉选择的分层漂移扩散模型的估计。我们发现，与以往计算模型不同，用相关决策证据中的内源性变异性来约束模型，会使得先验概率效应主要由证据积累速率的变化来解释，而非起点的变化或两者的综合作用。最终，我们基于神经信息的建模方法有助于厘清先验概率对知觉决策形成的机制性影响，表明先验概率主要将感官证据的解释偏向于最可能的刺激。
