Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.
Laboratoire de Neurosciences Cognitives et Computationnelles, INSERM U960, Ecole Normale Supérieure - PSL Research University, Paris, France.
Front Neural Circuits. 2021 Sep 20;15:716965. doi: 10.3389/fncir.2021.716965. eCollection 2021.
Working memory function is severely limited. One key limitation that constrains the ability to maintain multiple items in working memory simultaneously is so-called swap errors. These errors occur when an inaccurate response is in fact accurate relative to a non-target stimulus, reflecting the failure to maintain the appropriate association or "binding" between the features that define one object (e.g., color and location). The mechanisms underlying feature binding in working memory remain unknown. Here, we tested the hypothesis that features are bound in memory through synchrony across feature-specific neural assemblies. We built a biophysical neural network model composed of two one-dimensional attractor networks - one for color and one for location - simulating feature storage in different cortical areas. Within each area, gamma oscillations were induced during bump attractor activity through the interplay of fast recurrent excitation and slower feedback inhibition. As a result, different memorized items were held at different phases of the network's oscillation. These two areas were then reciprocally connected via weak cortico-cortical excitation, accomplishing binding between color and location through the synchronization of pairs of bumps across the two areas. Encoding and decoding of color-location associations was accomplished through rate coding, overcoming a long-standing limitation of binding through synchrony. In some simulations, swap errors arose: "color bumps" abruptly changed their phase relationship with "location bumps." This model, which leverages the explanatory power of similar attractor models, specifies a plausible mechanism for feature binding and makes specific predictions about swap errors that are testable at behavioral and neurophysiological levels.
工作记忆功能严重受限。限制同时在工作记忆中维持多个项目的能力的一个关键限制是所谓的交换错误。当不准确的响应实际上相对于非目标刺激是准确的时，就会发生这些错误，这反映了未能保持一个对象（例如颜色和位置）的特征之间的适当关联或“绑定”。工作记忆中特征绑定的机制仍然未知。在这里，我们测试了这样一种假设，即特征通过跨特定于特征的神经集合的同步在记忆中绑定。我们构建了一个生物物理神经网络模型，由两个一维吸引子网络组成 - 一个用于颜色，一个用于位置 - 模拟不同皮质区域中的特征存储。在每个区域中，通过快速递归兴奋和较慢的反馈抑制的相互作用，在凸起吸引子活动期间诱导伽马振荡。结果，不同的记忆项目处于网络振荡的不同相位。然后，这两个区域通过弱皮质 - 皮质兴奋相互连接，通过跨越两个区域的对的凸起的同步来完成颜色和位置之间的绑定。颜色 - 位置关联的编码和解码是通过速率编码完成的，克服了通过同步进行绑定的长期限制。在一些模拟中，出现了交换错误：“颜色凸起”突然改变了它们与“位置凸起”的相位关系。该模型利用了类似吸引子模型的解释能力，为特征绑定指定了一个合理的机制，并对行为和神经生理学水平可测试的交换错误做出了具体预测。
