Abstract concept learning in a simple neural network inspired by the insect brain.
Abstract concept learning in a simple neural network inspired by the insect brain.
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DOI：
10.1371/journal.pcbi.1006435
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发表时间：
2018-09
影响因子：
4.3
通讯作者：
Barron AB
中科院分区：
文献类型：
--
作者：
Cope AJ;Vasilaki E;Minors D;Sabo C;Marshall JAR;Barron AB
学习抽象概念的能力，如“相同”和“差异”，被认为是一种高阶认知功能，通常被认为是依赖于自上而下的新皮层处理。因此，蜜蜂显然具有这种能力是令人惊讶的。在这里，我们报告了一个蜜蜂大脑结构的模型，它可以学习相同和不同，以及一系列复杂和简单的联想学习任务。我们的模型受到蘑菇体（包括前脑束）的已知连接和属性的约束，并提供了一个很好的拟合真实的蜜蜂在所有任务中的学习率和表现，包括学习相同和不同。该模型提出了一种新的机制，用于学习与昆虫大脑兼容的“相同”和“差异”的抽象概念，并且不依赖于自上而下或执行控制处理。有必要拥有先进的神经机制来学习抽象的概念，如相同或不同吗？这些任务通常被认为是高阶认知能力，依赖于位于哺乳动物新皮层的复杂认知过程。因此，蜜蜂被证明能够学习相同和不同以及其他相关概念，这一直是令人惊讶的。为了探索像蜜蜂这样的动物是如何做到这一点的，我们在这里提出了一个简单的神经网络模型，它能够学习相同和差异，并且受到昆虫大脑已知神经系统的限制，并且缺乏任何先进的神经机制。我们提出的电路模型能够复制蜜蜂在概念学习和一系列其他联想学习任务中的表现。我们的模型提出了一个修改什么是必要的学习抽象概念。我们警告说，对排名的认知能力的拟人化假设的复杂性，并认为，通过应用神经建模，它可以表明，相对简单的神经结构足以解释不同的认知能力，和动物的范围，可能有能力。
The capacity to learn abstract concepts such as ‘sameness’ and ‘difference’ is considered a higher-order cognitive function, typically thought to be dependent on top-down neocortical processing. It is therefore surprising that honey bees apparantly have this capacity. Here we report a model of the structures of the honey bee brain that can learn sameness and difference, as well as a range of complex and simple associative learning tasks. Our model is constrained by the known connections and properties of the mushroom body, including the protocerebral tract, and provides a good fit to the learning rates and performances of real bees in all tasks, including learning sameness and difference. The model proposes a novel mechanism for learning the abstract concepts of ‘sameness’ and ‘difference’ that is compatible with the insect brain, and is not dependent on top-down or executive control processing. Is it necessary to have advanced neural mechanisms to learn abstract concepts such as sameness or difference? Such tasks are usually considered a higher order cognitive capacity, dependent on complex cognitive processes located in the mammalian neocortex. It has always been astonishing therefore that honey bees have been shown capable of learning sameness and difference, and other relational concepts. To explore how an animal like a bee might do this here we present a simple neural network model that is capable of learning sameness and difference and is constrained by the known neural systems of the insect brain, and that lacks any advanced neural mechanisms. The circuit model we propose was able to replicate bees’ performance in concept learning and a range of other associative learning tasks when tested in simulations. Our model proposes a revision of what is assumed necessary for learning abstract concepts. We caution against ranking cognitive abilities by anthropomorphic assumptions of their complexity and argue that by application of neural modelling, it can be shown that comparatively simple neural structures are sufficient to explain different cognitive capacities, and the range of animals that might be capable of them.
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DOI：
10.1523/jneurosci.4145-12.2013
发表时间：
2013-03-27
期刊：
The Journal of neuroscience : the official journal of the Society for Neuroscience
影响因子：
--
作者：
Bazhenov M;Huerta R;Smith BH
通讯作者：
Smith BH
影响因子：
1.4
作者：
BITTERMAN, ME;MENZEL, R;SCHAFER, S
通讯作者：
SCHAFER, S
影响因子：
64.8
作者：
Giurfa, M;Zhang, SW;Srinivasan, MV
通讯作者：
Srinivasan, MV
通过错误驱动的学习适应短期可塑性参数可以解释活动依赖性突触特性，连通性基序和目标特异性之间的相关性。
影响因子：
3.2
作者：
Esposito U;Giugliano M;Vasilaki E
通讯作者：
Vasilaki E
影响因子：
3
作者：
Boitard C;Devaud JM;Isabel G;Giurfa M
通讯作者：
Giurfa M