Dnepropetrovsk National University, Ukraine.
Neural Netw. 2011 Jun;24(5):407-16. doi: 10.1016/j.neunet.2011.03.005. Epub 2011 Mar 11.
The role of 'noisy' excitation in synchronizing interneuron networks with shunting synapses was studied. The excitatory input was simulated as a Poisson pattern of presynaptic conductance with varying frequencies and amplitudes. We find that higher excitation frequencies induce stronger synchronisation of the network. Within the range of 1-10000 Hz, only frequencies between 20 Hz and 200 Hz affected network synchronisation. No detectable network synchronisation was found at excitation frequencies below 20 Hz, and the network's synchronisation was either almost independent of the external input or falling down to zero when the input frequency was greater than 200 Hz. Thus the network transformed the input signals with frequencies above 20 Hz into output signals with the network's synchronisation frequency. The network's synchronisation frequency in our model ranged from 20 to 68 Hz depending on the frequency of the excitatory input. We conclude that a network of interconnected interneurons is capable of converting an asynchronous excitatory input into a synchronous inhibitory output as a frequency amplifier with the amplification coefficient dependent on the number of converging excitatory inputs. Another important result of our work revealed that the external frequency may affect, in opposite ways, the frequency of the network with shunting synapses depending on the excitatory synaptic conductance and the magnitude of leak conductance.
研究了“噪声”兴奋在具有分流突触的中间神经元网络中同步的作用。兴奋性输入被模拟为具有不同频率和幅度的突触前电导的泊松模式。我们发现,较高的激励频率会引起更强的网络同步。在 1-10000 Hz 的范围内,只有 20 Hz 到 200 Hz 之间的频率会影响网络同步。在低于 20 Hz 的激励频率下,无法检测到网络同步,而当输入频率大于 200 Hz 时,网络同步要么几乎不受外部输入的影响,要么降至零。因此,网络将频率高于 20 Hz 的输入信号转换为具有网络同步频率的输出信号。在我们的模型中,网络的同步频率范围为 20 到 68 Hz,具体取决于兴奋性输入的频率。我们得出结论,相互连接的中间神经元网络能够将异步兴奋性输入转换为同步抑制性输出,作为一个频率放大器,其放大系数取决于汇聚兴奋性输入的数量。我们工作的另一个重要结果表明,外部频率可能会以相反的方式影响具有分流突触的网络的频率,具体取决于兴奋性突触电导和漏导的大小。