Sosis Baram, Rubin Jonathan E
*Department of Mathematics, University of Pittsburgh, 301 Thackeray Hall, Pittsburgh, 15260, PA, USA.
Center for the Neural Basis of Cognition, University of Pittsburgh, 4400 Fifth Ave, Pittsburgh, 15213, PA, USA.
bioRxiv. 2024 Oct 4:2024.06.24.600372. doi: 10.1101/2024.06.24.600372.
Various mathematical models have been formulated to describe the changes in synaptic strengths resulting from spike-timing-dependent plasticity (STDP). A subset of these models include a third factor, dopamine, which interacts with spike timing to contribute to plasticity at specific synapses, notably those from cortex to striatum at the input layer of the basal ganglia. Theoretical work to analyze these plasticity models has largely focused on abstract issues, such as the conditions under which they may promote synchronization and the weight distributions induced by inputs with simple correlation structures, rather than on scenarios associated with specific tasks, and has generally not considered dopamine-dependent forms of STDP. In this paper we introduce three forms of dopamine-modulated STDP adapted from previously proposed plasticity rules. We then analyze, mathematically and with simulations, their performance in three biologically relevant scenarios. We test the ability of each of the three models to maintain its weights in the face of noise and to complete simple reward prediction and action selection tasks, studying the learned weight distributions and corresponding task performance in each setting. Interestingly, we find that each plasticity rule is well suited to a subset of the scenarios studied but falls short in others. Different tasks may therefore require different forms of synaptic plasticity, yielding the prediction that the precise form of the STDP mechanism present may vary across regions of the striatum, and other brain areas impacted by dopamine, that are involved in distinct computational functions.
已经构建了各种数学模型来描述由尖峰时间依赖性可塑性(STDP)引起的突触强度变化。这些模型的一个子集包含第三个因素——多巴胺,它与尖峰时间相互作用,以促进特定突触的可塑性,特别是基底神经节输入层中从皮质到纹状体的那些突触。分析这些可塑性模型的理论工作主要集中在抽象问题上,例如它们可能促进同步的条件以及具有简单相关结构的输入所诱导的权重分布,而不是与特定任务相关的场景,并且通常没有考虑多巴胺依赖性的STDP形式。在本文中,我们引入了三种从先前提出的可塑性规则改编而来的多巴胺调节的STDP形式。然后,我们通过数学分析和模拟,研究它们在三种生物学相关场景中的性能。我们测试这三种模型中的每一种在面对噪声时保持其权重以及完成简单奖励预测和动作选择任务的能力,研究每种设置下学习到的权重分布和相应的任务性能。有趣的是,我们发现每个可塑性规则都非常适合所研究场景的一个子集,但在其他子集中则表现不佳。因此,不同的任务可能需要不同形式的突触可塑性,由此预测,存在的STDP机制的精确形式可能在纹状体的不同区域以及受多巴胺影响的其他参与不同计算功能的脑区中有所不同。