Department of Neuroscience, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania 19104.
Institute of Neuroscience (Paris-Saclay Institute of Neuroscience, Unit of Neuroscience, Information, and Complexity), Paris-Saclay University, Centre National de la Recherche Scientifique, 91198 Gif-sur-Yvette, France.
J Neurosci. 2021 Sep 15;41(37):7797-7812. doi: 10.1523/JNEUROSCI.0928-20.2021. Epub 2021 Jul 28.
The spatial organization and dynamic interactions between excitatory and inhibitory synaptic inputs that define the receptive field (RF) of simple cells in the cat primary visual cortex (V1) still raise the following paradoxical issues: (1) stimulation of simple cells in V1 with drifting gratings supports a wiring schema of spatially segregated sets of excitatory and inhibitory inputs activated in an opponent way by stimulus contrast polarity and (2) in contrast, intracellular studies using flashed bars suggest that although ON and OFF excitatory inputs are indeed segregated, inhibitory inputs span the entire RF regardless of input contrast polarity. Here, we propose a biologically detailed computational model of simple cells embedded in a V1-like network that resolves this seeming contradiction. We varied parametrically the RF-correlation-based bias for excitatory and inhibitory synapses and found that a moderate bias of excitatory neurons to synapse onto other neurons with correlated receptive fields and a weaker bias of inhibitory neurons to synapse onto other neurons with anticorrelated receptive fields can explain the conductance input, the postsynaptic membrane potential, and the spike train dynamics under both stimulation paradigms. This computational study shows that the same structural model can reproduce the functional diversity of visual processing observed during different visual contexts. Identifying generic connectivity motives in cortical circuitry encoding for specific functions is crucial for understanding the computations implemented in the cortex. Indirect evidence points to correlation-based biases in the connectivity pattern in V1 of higher mammals, whereby excitatory and inhibitory neurons preferentially synapse onto neurons respectively with correlated and anticorrelated receptive fields. A recent intracellular study questions this push-pull hypothesis, failing to find spatial anticorrelation patterns between excitation and inhibition across the receptive field. We present here a spiking model of V1 that integrates relevant anatomic and physiological constraints and shows that a more versatile motif of correlation-based connectivity with selectively tuned excitation and broadened inhibition is sufficient to account for the diversity of functional descriptions obtained for different classes of stimuli.
猫初级视皮层 (V1) 中简单细胞的兴奋性和抑制性突触输入的空间组织和动态相互作用仍然提出了以下矛盾问题:(1) 用漂移光栅刺激 V1 中的简单细胞支持空间分离的兴奋性和抑制性输入集合的布线模式,这些输入集合通过刺激对比度极性以相反的方式激活;(2) 相比之下,使用闪烁条的细胞内研究表明,尽管 ON 和 OFF 兴奋性输入确实是分离的,但抑制性输入跨越整个 RF,无论输入对比度极性如何。在这里,我们提出了一个嵌入 V1 样网络中的简单细胞的生物详细计算模型,该模型解决了这一看似矛盾的问题。我们参数化地改变了基于 RF 相关的兴奋性和抑制性突触的偏差,发现兴奋性神经元的适度偏差,即与具有相关 RF 的其他神经元形成突触,以及抑制性神经元的较弱偏差,即与具有反相关 RF 的其他神经元形成突触,可以解释在两种刺激模式下的电导输入、突触后膜电位和尖峰序列动力学。这项计算研究表明,相同的结构模型可以再现不同视觉环境下观察到的视觉处理的功能多样性。确定皮质电路中编码特定功能的通用连接动机对于理解皮质中的计算至关重要。间接证据表明,在高等哺乳动物的 V1 中存在基于相关性的连接模式偏见,其中兴奋性和抑制性神经元分别优先与具有相关和反相关 RF 的神经元形成突触。最近的一项细胞内研究对这种推拉假说提出了质疑,未能在整个 RF 中找到兴奋和抑制之间的空间反相关性模式。我们在这里提出了一个 V1 的尖峰模型,该模型整合了相关的解剖和生理约束,并表明基于相关性的连接具有更灵活的模式,选择性调节兴奋和拓宽抑制作用,足以解释为不同刺激类别的获得的功能描述的多样性。