Frémaux Nicolas, Gerstner Wulfram
School of Computer Science and Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne Lausanne, Switzerland.
Front Neural Circuits. 2016 Jan 19;9:85. doi: 10.3389/fncir.2015.00085. eCollection 2015.
Classical Hebbian learning puts the emphasis on joint pre- and postsynaptic activity, but neglects the potential role of neuromodulators. Since neuromodulators convey information about novelty or reward, the influence of neuromodulators on synaptic plasticity is useful not just for action learning in classical conditioning, but also to decide "when" to create new memories in response to a flow of sensory stimuli. In this review, we focus on timing requirements for pre- and postsynaptic activity in conjunction with one or several phasic neuromodulatory signals. While the emphasis of the text is on conceptual models and mathematical theories, we also discuss some experimental evidence for neuromodulation of Spike-Timing-Dependent Plasticity. We highlight the importance of synaptic mechanisms in bridging the temporal gap between sensory stimulation and neuromodulatory signals, and develop a framework for a class of neo-Hebbian three-factor learning rules that depend on presynaptic activity, postsynaptic variables as well as the influence of neuromodulators.
经典的赫布学习强调突触前和突触后活动的协同作用,但忽略了神经调质的潜在作用。由于神经调质传递有关新奇性或奖励的信息,因此神经调质对突触可塑性的影响不仅对经典条件反射中的动作学习有用,而且对于决定“何时”响应感觉刺激流创建新记忆也很有用。在本综述中,我们关注突触前和突触后活动与一个或几个相位性神经调质信号相结合的时间要求。虽然本文重点关注概念模型和数学理论,但我们也讨论了一些关于神经调质对尖峰时间依赖性可塑性调节的实验证据。我们强调了突触机制在弥合感觉刺激与神经调质信号之间时间差距方面的重要性,并为一类依赖于突触前活动、突触后变量以及神经调质影响的新赫布三因素学习规则建立了一个框架。