Investigating a Dual-Process Account of Learning, Memory and Cognition.

他的项目试图回答这样一个问题，即是否有令人信服的证据证明人的联想系统，并在这样做的过程中解决正在进行的更大的理论辩论，即单过程(完全命题，参见Mitchell，de Houwer，&Loviond，2009)或双过程学习和记忆描述(参见McLaren等人，2014)是更好的人类认知模型。这场辩论不仅限于学习，因为双过程解释已经被用来解释许多认知功能，如推理和决策(Evans&Stanovich，2013)。这个问题的答案将产生真正的后果。洛维邦德(见2018年参考文献)认为，临床治疗应该淡化行为部分，转而关注更具认知性的、基于对联想过程对人类精神生活贡献的怀疑的证据而进行的“谈话”部分。有鉴于此，该项目不仅有可能对科学文献做出重大贡献，而且还可以帮助我们将对学习的理解应用到焦虑和恐惧症等心理健康问题上，并为教育实践提供信息。我的方法将是同时使用经验和计算模型的视角来研究人类的峰移等现象。从经验上讲，我将使用行为学和神经科学的方法，例如脑电图法(EEG)和经颅直流电刺激法(TDCS)。脑电可以用来检查伴随任何效应的神经信号，但本质上是相互关联的。然而，使用tdcs的神经刺激将使我能够测试每个过程(联想和命题)是否可以独立调节，并使我能够推断导致任何结果的因果机制。这些经验技术将与计算模型相结合，从而能够分析支配学习的特定过程和方程式，以及刺激和对象在大脑中的表示方式。这可以用来建立现有的联想模型(例如，McLaren&Mackintosh，2002)和认知模型(例如，Lee，Hayes和Loviond，2018)。在这项研究中，亮度(从暗到亮，用X表示)和颜色(从蓝色到绿色，用Y表示)都将构成这两个维度。此后，刺激值将表示为(X，Y)，范围从深蓝(1，1)到淡绿色(11，11)，中点为中亮蓝绿(6，6)。参与者最初将接受两个刺激--3，5和9，7--的训练，这两个刺激分别与左和右两个类别相关。由于这些刺激明显比彼此更亮和更暗，这将导致引入管理亮度维度(3和9)的规则。然后，他们将接受另外两种刺激--5，5和7，7--的训练，这两种刺激的颜色与最初的训练刺激相同，但在亮度和黑暗程度上没有那么极端。这有助于进一步建立关于亮度维度的规则，并且还将确保向颜色维度累积了足够的联想强度。如果参与者关注的是亮度维度，因为这在训练期间最明显地相关，那么双加工账户将在测试该维度(刺激颜色保持不变)时预测基于规则的反应。此外，当参与者接受颜色维度测试时，这一解释还可以预测峰值漂移。之后，参与者将接受采访，以确定他们是否使用了任何规则，或者注意到了刺激和类别之间的任何关系。还将对该实验进行计算模拟，并将结果与模型结果进行比较。

his project seeks to answer the question of whether there is compelling evidence for an associative system in people, and in doing so resolve the larger ongoing theoretical debate of whether single process (entirely propositional, see Mitchell, De Houwer, & Lovibond, 2009) or dual-process accounts of learning and memory (see McLaren et al., 2014) are the better model for human cognition. This debate is not limited to learning, as dual-processes accounts have been used to explain many cognitive functions such as reasoning and decision making (Evans & Stanovich, 2013). An answer to this question would have real consequences. Lovibond (see 2018 reference for an example) has argued that clinical therapies should de-emphasise the behavioural component and focus instead on the more cognitive, "talking" part based on evidence casting doubt on the contribution made by associative processes to human mental life. Given this, the project has not only the potential to significantly contribute to the scientific literature, but to also help us apply our understanding of learning to mental health issues such as anxiety and phobias, as well as informing educational practice. My approach will be to use both an empirical and a computational modelling perspective to study phenomena such as peak shift in humans. Empirically, I will employ both behavioural and neuroscientific methods, such as electroencephalography (EEG) and transcranial direct current stimulation (tDCS). EEG can be used to examine the neural signatures that accompany any effect but is essentially correlational in nature. Neurostimulation using tDCS, however, will allow me to test whether each process (associative and propositional) can be independently modulated and enable me to infer the causal mechanisms responsible for any effect. These empirical techniques will be combined with computational modelling that will allow analysis of the specific processes and equations that govern learning, as well as how stimuli and objects are represented in the mind. This can be used to build upon existing associative (e.g., McLaren & Mackintosh, 2002) and cognitive (e.g., Lee, Hayes and Lovibond, 2018) models.An example of a study that would help distinguish between dual and single-process theories is one in which two dimensions are tested. In this study, both brightness (ranging from dark to bright, denoted by X) and colour (ranging from blue to green, denoted by Y) would constitute the two dimensions. Henceforth, the stimulus values will be represented as (X,Y) and range from dark blue (1,1) to light green (11,11), with a midpoint of medium bright blueish-green (6,6). Participants would initially be trained with two stimuli - 3,5 and 9,7 - that are associated with two categories, left and right, respectively. As these stimuli are obviously brighter and darker than one another, this will lead to induction of a rule governing the brightness dimension (3 and 9). They will then be trained with two more stimuli - 5,5 and 7,7 - which are the same colour as the initial training stimuli, but not as extreme in their brightness and darkness. This serves to further establish a rule on the brightness dimension and will also ensure sufficient associative strength has accumulated to the colour dimension. If participants are attending to the brightness dimension, as this was most clearly relevant during training, a dual-process account would predict rule based responding when tested on this dimension (where the stimulus colour remains constant). Furthermore, this account would also predict peak shift when participants are tested on the colour dimension. Participants would be interviewed after to ascertain if they were using any rules or noticed any relationships between the stimuli and categories. This experiment would also be computationally simulated, and the results would be compared with that of the model.