de la Rocha Jaime, Marchetti Cristina, Schiff Max, Reyes Alex D
Center for Neural Science, New York University, New York, New York 10003, USA.
J Neurosci. 2008 Sep 10;28(37):9151-63. doi: 10.1523/JNEUROSCI.1789-08.2008.
The frequency-intensity receptive fields (RF) of neurons in primary auditory cortex (AI) are heterogeneous. Some neurons have V-shaped RFs, whereas others have enclosed ovoid RFs. Moreover, there is a wide range of temporal response profiles ranging from phasic to tonic firing. The mechanisms underlying this diversity of receptive field properties are yet unknown. Here we study the characteristics of thalamocortical (TC) and intracortical connectivity that give rise to the individual cell responses. Using a mouse auditory TC slice preparation, we found that the amplitude of synaptic responses in AI varies non-monotonically with the intensity of the stimulation in the medial geniculate nucleus (MGv). We constructed a network model of MGv and AI that was simulated using either rate model cells or in vitro neurons through an iterative procedure that used the recorded neural responses to reconstruct network activity. We compared the receptive fields and firing profiles obtained with networks configured to have either cotuned excitatory and inhibitory inputs or relatively broad, lateral inhibitory inputs. Each of these networks yielded distinct response properties consistent with those documented in vivo with natural stimuli. The cotuned network produced V-shaped RFs, phasic-tonic firing profiles, and predominantly monotonic rate-level functions. The lateral inhibitory network produced enclosed RFs with narrow frequency tuning, a variety of firing profiles, and robust non-monotonic rate-level functions. We conclude that both types of circuits must be present to account for the wide variety of responses observed in vivo.
初级听觉皮层(AI)中神经元的频率 - 强度感受野(RF)是异质性的。一些神经元具有V形感受野,而另一些则具有封闭的卵形感受野。此外,存在从相位性放电到紧张性放电的广泛时间响应模式。这种感受野特性多样性背后的机制尚不清楚。在这里,我们研究了引起单个细胞反应的丘脑皮质(TC)和皮质内连接的特征。使用小鼠听觉TC切片制备,我们发现AI中突触反应的幅度随内侧膝状体核(MGv)刺激强度非单调变化。我们构建了MGv和AI的网络模型,通过使用记录的神经反应来重建网络活动的迭代过程,用速率模型细胞或体外神经元对其进行模拟。我们比较了配置为具有共调谐兴奋性和抑制性输入或相对宽泛的侧向抑制性输入的网络所获得的感受野和放电模式。这些网络中的每一个都产生了与体内自然刺激所记录的反应特性一致的独特反应特性。共调谐网络产生V形感受野、相位 - 紧张性放电模式以及主要是单调的速率 - 水平函数。侧向抑制网络产生具有窄频率调谐的封闭感受野、各种放电模式以及强大的非单调速率 - 水平函数。我们得出结论,这两种类型的电路都必须存在,才能解释在体内观察到的广泛反应。