Loebel Alex, Nelken Israel, Tsodyks Misha
Department of Neurobiology, Weizmann Institute of Science, Rehovot Israel.
Front Neurosci. 2007 Oct 15;1(1):197-209. doi: 10.3389/neuro.01.1.1.015.2007. eCollection 2007 Nov.
We propose a model of the primary auditory cortex (A1), in which each iso-frequency column is represented by a recurrent neural network with short-term synaptic depression. Such networks can emit Population Spikes, in which most of the neurons fire synchronously for a short time period. Different columns are interconnected in a way that reflects the tonotopic map in A1, and population spikes can propagate along the map from one column to the next, in a temporally precise manner that depends on the specific input presented to the network. The network, therefore, processes incoming sounds by precise sequences of population spikes that are embedded in a continuous asynchronous activity, with both of these response components carrying information about the inputs and interacting with each other. With these basic characteristics, the model can account for a wide range of experimental findings. We reproduce neuronal frequency tuning curves, whose width depends on the strength of the intracortical inhibitory and excitatory connections. Non-simultaneous two-tone stimuli show forward masking depending on their temporal separation, as well as on the duration of the first stimulus. The model also exhibits non-linear suppressive interactions between sub-threshold tones and broad-band noise inputs, similar to the hypersensitive locking suppression recently demonstrated in auditory cortex. We derive several predictions from the model. In particular, we predict that spontaneous activity in primary auditory cortex gates the temporally locked responses of A1 neurons to auditory stimuli. Spontaneous activity could, therefore, be a mechanism for rapid and reversible modulation of cortical processing.
我们提出了一种初级听觉皮层（A1）模型，其中每个等频柱由具有短期突触抑制的递归神经网络表示。这样的网络可以发出群体尖峰，其中大多数神经元在短时间内同步放电。不同的柱以反映A1中音调拓扑图的方式相互连接，群体尖峰可以沿着该图从一个柱以时间精确的方式传播到下一个柱，这取决于呈现给网络的特定输入。因此，该网络通过嵌入连续异步活动中的精确群体尖峰序列来处理传入的声音，这两个响应成分都携带有关输入的信息并相互作用。具有这些基本特征，该模型可以解释广泛的实验结果。我们重现了神经元频率调谐曲线，其宽度取决于皮质内抑制性和兴奋性连接的强度。非同时的双音刺激根据它们的时间间隔以及第一个刺激的持续时间表现出前向掩蔽。该模型还表现出阈下音调与宽带噪声输入之间的非线性抑制相互作用，类似于最近在听觉皮层中证明的超敏锁定抑制。我们从该模型中得出了几个预测。特别是，我们预测初级听觉皮层中的自发活动会控制A1神经元对听觉刺激的时间锁定反应。因此，自发活动可能是一种快速且可逆地调节皮质处理的机制。
