Département de Sciences Biologiques, Neurophysiology of the Visual system, Université de Montréal, Montréal, Québec.
Department of Psychology, Centre for Vision Research and Vision: Science to Applications (VISTA) Program, York University, Toronto, Ontario, Canada.
Neuroreport. 2024 Mar 20;35(5):291-298. doi: 10.1097/WNR.0000000000002012. Epub 2024 Feb 18.
Orientation selectivity is an emergent property of visual neurons across species with columnar and noncolumnar organization of the visual cortex. The emergence of orientation selectivity is more established in columnar cortical areas than in noncolumnar ones. Thus, how does orientation selectivity emerge in noncolumnar cortical areas after an adaptation protocol? Adaptation refers to the constant presentation of a nonoptimal stimulus (adapter) to a neuron under observation for a specific time. Previously, it had been shown that adaptation has varying effects on the tuning properties of neurons, such as orientation, spatial frequency, motion and so on.
We recorded the mouse primary visual neurons (V1) at different orientations in the control (preadaptation) condition. This was followed by adapting neurons uninterruptedly for 12 min and then recording the same neurons postadaptation. An orientation selectivity index (OSI) for neurons was computed to compare them pre- and post-adaptation.
We show that 12-min adaptation increases the OSI of visual neurons ( n = 113), that is, sharpens their tuning. Moreover, the OSI postadaptation increases linearly as a function of the OSI preadaptation.
The increased OSI postadaptation may result from a specific dendritic neural mechanism, potentially facilitating the rapid learning of novel features.
在具有柱状和非柱状视皮层组织的物种中，方位选择性是视觉神经元的一种涌现属性。方位选择性的出现更多地存在于柱状皮质区域，而不是非柱状皮质区域。那么，在适应方案之后，非柱状皮质区域中的方位选择性是如何出现的呢？适应是指将一个非最佳刺激（适应器）持续呈现给一个被观察的神经元一段时间。以前已经表明，适应对神经元的调谐特性（如方位、空间频率、运动等）有不同的影响。
我们在对照（预适应）条件下记录了不同方位的小鼠初级视觉神经元（V1）。然后，不间断地让神经元适应 12 分钟，然后在适应后记录相同的神经元。计算神经元的方位选择性指数（OSI）来比较它们在适应前后的差异。
我们表明，12 分钟的适应会增加视觉神经元的 OSI（n=113），即增强它们的调谐。此外，适应后的 OSI 呈线性增加，与适应前的 OSI 呈正相关。
适应后 OSI 的增加可能是由于特定的树突神经机制，有助于快速学习新的特征。
