Chuderski Adam, Andrelczyk Krzysztof
Cognitive Science Department, Institute of Philosophy, Jagiellonian University, Grodzka 52, 31-044 Krakow, Poland.
Institute of Psychology, Jagiellonian University, Mickiewicza 3, 31-120 Krakow, Poland.
Cogn Psychol. 2015 Feb;76:78-102. doi: 10.1016/j.cogpsych.2015.01.001. Epub 2015 Feb 19.
Several existing computational models of working memory (WM) have predicted a positive relationship (later confirmed empirically) between WM capacity and the individual ratio of theta to gamma oscillatory band lengths. These models assume that each gamma cycle represents one WM object (e.g., a binding of its features), whereas the theta cycle integrates such objects into the maintained list. As WM capacity strongly predicts reasoning, it might be expected that this ratio also predicts performance in reasoning tasks. However, no computational model has yet explained how the differences in the theta-to-gamma ratio found among adult individuals might contribute to their scores on a reasoning test. Here, we propose a novel model of how WM capacity constraints figural analogical reasoning, aimed at explaining inter-individual differences in reasoning scores in terms of the characteristics of oscillatory patterns in the brain. In the model, the gamma cycle encodes the bindings between objects/features and the roles they play in the relations processed. Asynchrony between consecutive gamma cycles results from lateral inhibition between oscillating bindings. Computer simulations showed that achieving the highest WM capacity required reaching the optimal level of inhibition. When too strong, this inhibition eliminated some bindings from WM, whereas, when inhibition was too weak, the bindings became unstable and fell apart or became improperly grouped. The model aptly replicated several empirical effects and the distribution of individual scores, as well as the patterns of correlations found in the 100-people sample attempting the same reasoning task. Most importantly, the model's reasoning performance strongly depended on its theta-to-gamma ratio in same way as the performance of human participants depended on their WM capacity. The data suggest that proper regulation of oscillations in the theta and gamma bands may be crucial for both high WM capacity and effective complex cognition.
现有的几种工作记忆（WM）计算模型预测，WM容量与θ波和γ振荡频段长度的个体比率之间存在正相关关系（后来得到了实证证实）。这些模型假设，每个γ周期代表一个WM对象（例如，其特征的一种绑定），而θ周期则将这些对象整合到所维持的列表中。由于WM容量能有力地预测推理能力，因此可以预期这个比率也能预测推理任务的表现。然而，尚无计算模型解释在成年个体中发现的θ与γ比率差异如何影响他们在推理测试中的得分。在此，我们提出了一个关于WM容量如何限制图形类比推理的新模型，旨在根据大脑振荡模式的特征来解释推理得分的个体差异。在该模型中，γ周期对对象/特征之间的绑定及其在处理的关系中所起的作用进行编码。连续γ周期之间的异步性源于振荡绑定之间的侧向抑制。计算机模拟表明，要达到最高的WM容量需要达到最佳抑制水平。抑制过强时，会从WM中消除一些绑定；而抑制过弱时，绑定会变得不稳定并瓦解或分组不当。该模型恰当地复制了几种实证效应以及个体得分的分布，以及在尝试相同推理任务的100人样本中发现的相关模式。最重要的是，该模型的推理表现强烈依赖于其θ与γ的比率，就如同人类参与者的表现依赖于他们的WM容量一样。数据表明θ波和γ波振荡的适当调节对于高WM容量和有效的复杂认知可能至关重要。
