Department of Mathematics and Statistics, Boston University, Boston, MA 02215;
Department of Mathematics and Statistics, Boston University, Boston, MA 02215.
Proc Natl Acad Sci U S A. 2019 Apr 23;116(17):8564-8569. doi: 10.1073/pnas.1812535116. Epub 2019 Apr 8.
Classical accounts of biased competition require an input bias to resolve the competition between neuronal ensembles driving downstream processing. However, flexible and reliable selection of behaviorally relevant ensembles can occur with unbiased stimulation: striatal D1 and D2 spiny projection neurons (SPNs) receive balanced cortical input, yet their activity determines the choice between GO and NO-GO pathways in the basal ganglia. We here present a corticostriatal model identifying three mechanisms that rely on physiological asymmetries to effect rate- and time-coded biased competition in the presence of balanced inputs. First, tonic input strength determines which one of the two SPN phenotypes exhibits a higher mean firing rate. Second, low-strength oscillatory inputs induce higher firing rate in D2 SPNs but higher coherence between D1 SPNs. Third, high-strength inputs oscillating at distinct frequencies can preferentially activate D1 or D2 SPN populations. Of these mechanisms, only the latter accommodates observed rhythmic activity supporting rule-based decision making in prefrontal cortex.
经典的有偏差竞争理论需要输入偏差来解决驱动下游处理的神经元集合之间的竞争。然而,在没有偏差刺激的情况下,灵活可靠的行为相关集合选择也可以发生:纹状体 D1 和 D2 棘突投射神经元 (SPN) 接收平衡的皮质输入,但它们的活动决定了基底神经节中 GO 和 NO-GO 通路之间的选择。我们在这里提出了一个皮质纹状体模型,该模型确定了三种机制,这些机制依赖于生理不对称性,在存在平衡输入的情况下实现了基于速率和时间的有偏差竞争。首先,强直输入强度决定了两种 SPN 表型中的哪一种表现出更高的平均放电率。其次,低强度的振荡输入会在 D2 SPN 中诱导更高的放电率,但在 D1 SPN 之间产生更高的相干性。第三,以不同频率振荡的高强度输入可以优先激活 D1 或 D2 SPN 群体。在这些机制中,只有后者适应了观察到的支持前额叶皮层基于规则的决策的节律性活动。