Holcman David, Tsodyks Misha
Department of Mathematics, Weizmann Institute of Science, Rehovot, Israel.
PLoS Comput Biol. 2006 Mar;2(3):e23. doi: 10.1371/journal.pcbi.0020023. Epub 2006 Mar 24.
The cerebral cortex is continuously active in the absence of external stimuli. An example of this spontaneous activity is the voltage transition between an Up and a Down state, observed simultaneously at individual neurons. Since this phenomenon could be of critical importance for working memory and attention, its explanation could reveal some fundamental properties of cortical organization. To identify a possible scenario for the dynamics of Up-Down states, we analyze a reduced stochastic dynamical system that models an interconnected network of excitatory neurons with activity-dependent synaptic depression. The model reveals that when the total synaptic connection strength exceeds a certain threshold, the phase space of the dynamical system contains two attractors, interpreted as Up and Down states. In that case, synaptic noise causes transitions between the states. Moreover, an external stimulation producing a depolarization increases the time spent in the Up state, as observed experimentally. We therefore propose that the existence of Up-Down states is a fundamental and inherent property of a noisy neural ensemble with sufficiently strong synaptic connections.
在没有外部刺激的情况下，大脑皮层仍持续活跃。这种自发活动的一个例子是在单个神经元上同时观察到的向上状态和向下状态之间的电压转换。由于这种现象可能对工作记忆和注意力至关重要，对其进行解释可能会揭示皮层组织的一些基本特性。为了确定向上-向下状态动态变化的一种可能情形，我们分析了一个简化的随机动力系统，该系统对具有活动依赖性突触抑制的兴奋性神经元互连网络进行建模。该模型表明，当总突触连接强度超过某个阈值时，动力系统的相空间包含两个吸引子，可解释为向上状态和向下状态。在这种情况下，突触噪声会导致状态之间的转换。此外，如实验观察到的那样，产生去极化的外部刺激会增加在向上状态所花费的时间。因此，我们提出向上-向下状态的存在是具有足够强突触连接的有噪声神经群体的一种基本且内在的属性。
