Bossens Christophe, Op de Beeck Hans P
Laboratory for Biological Psychology, KU Leuven Leuven, Belgium.
Front Behav Neurosci. 2016 Dec 23;10:235. doi: 10.3389/fnbeh.2016.00235. eCollection 2016.
The visual system processes visual input in a hierarchical manner in order to extract relevant features that can be used in tasks such as invariant object recognition. Although typically investigated in primates, recent work has shown that rats can be trained in a variety of visual object and shape recognition tasks. These studies did not pinpoint the complexity of the features used by these animals. Many tasks might be solved by using a combination of relatively simple features which tend to be correlated. Alternatively, rats might extract complex features or feature combinations which are nonlinear with respect to those simple features. In the present study, we address this question by starting from a small stimulus set for which one stimulus-response mapping involves a simple linear feature to solve the task while another mapping needs a well-defined nonlinear combination of simpler features related to shape symmetry. We verified computationally that the nonlinear task cannot be trivially solved by a simple V1-model. We show how rats are able to solve the linear feature task but are unable to acquire the nonlinear feature. In contrast, humans are able to use the nonlinear feature and are even faster in uncovering this solution as compared to the linear feature. The implications for the computational capabilities of the rat visual system are discussed.
视觉系统以分层方式处理视觉输入，以便提取可用于诸如不变物体识别等任务的相关特征。尽管通常在灵长类动物中进行研究，但最近的研究表明，大鼠可以接受各种视觉物体和形状识别任务的训练。这些研究并未明确这些动物所使用特征的复杂性。许多任务可能通过使用倾向于相关的相对简单特征的组合来解决。或者，大鼠可能提取相对于那些简单特征而言是非线性的复杂特征或特征组合。在本研究中，我们通过从一个小的刺激集开始来解决这个问题，对于该刺激集，一种刺激 - 反应映射涉及一个简单的线性特征来解决任务，而另一种映射需要与形状对称相关的更简单特征的明确非线性组合。我们通过计算验证了简单的V1模型无法轻易解决非线性任务。我们展示了大鼠如何能够解决线性特征任务，但无法获取非线性特征。相比之下，人类能够使用非线性特征，并且与线性特征相比，在发现该解决方案时甚至更快。我们还讨论了对大鼠视觉系统计算能力的影响。
