Borstel Kim J, Stevenson Paul A
Department of Physiology of Animals and Behaviour, Institute of Biology, Faculty of Life Sciences, Leipzig University, Leipzig, Germany.
Front Behav Neurosci. 2021 Sep 28;15:741439. doi: 10.3389/fnbeh.2021.741439. eCollection 2021.
Numerous invertebrates have contributed to our understanding of the biology of learning and memory. In most cases, learning performance is documented for groups of individuals, and nearly always based on a single, typically binary, behavioural metric for a conditioned response. This is unfortunate for several reasons. Foremost, it has become increasingly apparent that invertebrates exhibit inter-individual differences in many aspects of their behaviour, and also that the conditioned response probability for an animal group does not adequately represent the behaviour of individuals in classical conditioning. Furthermore, a binary response character cannot yield a graded score for each individual. We also hypothesise that due to the complexity of a conditioned response, a single metric need not reveal an individual's full learning potential. In this paper, we report individual learning scores for freely moving adult male crickets () based on a multi-factorial analysis of a conditioned response. First, in an absolute conditioning paradigm, we video-tracked the odour responses of animals that, in previous training, received either odour plus reward (sugar water), reward alone, or odour alone to identify behavioural predictors of a conditioned response. Measures of these predictors were then analysed using binary regression analysis to construct a variety of mathematical models that give a probability for each individual that it exhibited a conditioned response ( ). Using standard procedures to compare model accuracy, we identified the strongest model which could reliably discriminate between the different odour responses. Finally, in a differential appetitive olfactory paradigm, we employed the model after training to calculate the of animals to a conditioned, and to an unconditioned odour, and from the difference a learning index for each animal. Comparing the results from our multi-factor model with a single metric analysis (head bobbing in response to a conditioned odour), revealed advantageous aspects of the model. A broad distribution of model-learning scores, with modes at low and high values, support the notion of a high degree of variation in learning capacity, which we discuss.
许多无脊椎动物有助于我们理解学习与记忆的生物学机制。在大多数情况下，学习表现是针对个体群体记录的，而且几乎总是基于条件反应的单一（通常是二元的）行为指标。出于几个原因，这很不幸。首先，越来越明显的是，无脊椎动物在其行为的许多方面表现出个体间差异，而且动物群体的条件反应概率并不能充分代表经典条件作用中个体的行为。此外，二元反应特征无法为每个个体产生分级分数。我们还假设，由于条件反应的复杂性，单一指标不一定能揭示个体的全部学习潜力。在本文中，我们基于对条件反应的多因素分析，报告了自由活动的成年雄性蟋蟀（ ）的个体学习分数。首先，在绝对条件作用范式中，我们对动物的气味反应进行视频跟踪，这些动物在先前的训练中，要么接受气味加奖励（糖水）、单独奖励，要么单独接受气味，以确定条件反应的行为预测指标。然后使用二元回归分析对这些预测指标的测量值进行分析，构建各种数学模型，为每个个体表现出条件反应（ ）的概率赋值。使用标准程序比较模型准确性，我们确定了能够可靠区分不同气味反应的最强模型。最后，在差别性嗅觉偏好范式中，我们在训练后使用该模型计算动物对条件气味和非条件气味的 ，并根据差异计算每个动物的学习指数。将我们的多因素模型结果与单一指标分析（对条件气味的头部摆动）进行比较，揭示了该模型的优势方面。模型学习分数的广泛分布，在低值和高值处有峰值，支持了学习能力存在高度差异的观点，我们对此进行了讨论。
