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通过模块化结构实现的感觉记忆相互作用解释了视觉工作记忆中的错误。

Sensory-memory interactions via modular structure explain errors in visual working memory.

机构信息

Weiyang College, Tsinghua University, Beijing, China.

Shanghai Frontiers Science Center of Artificial Intelligence and Deep Learning, Shanghai, China.

出版信息

Elife. 2024 Oct 10;13:RP95160. doi: 10.7554/eLife.95160.

Abstract

Errors in stimulus estimation reveal how stimulus representation changes during cognitive processes. Repulsive bias and minimum variance observed near cardinal axes are well-known error patterns typically associated with visual orientation perception. Recent experiments suggest that these errors continuously evolve during working memory, posing a challenge that neither static sensory models nor traditional memory models can address. Here, we demonstrate that these evolving errors, maintaining characteristic shapes, require network interaction between two distinct modules. Each module fulfills efficient sensory encoding and memory maintenance, which cannot be achieved simultaneously in a single-module network. The sensory module exhibits heterogeneous tuning with strong inhibitory modulation reflecting natural orientation statistics. While the memory module, operating alone, supports homogeneous representation via continuous attractor dynamics, the fully connected network forms discrete attractors with moderate drift speed and nonuniform diffusion processes. Together, our work underscores the significance of sensory-memory interaction in continuously shaping stimulus representation during working memory.

摘要

在认知过程中,刺激估计中的错误揭示了刺激表示的变化。在接近基数轴时观察到的排斥偏差和最小方差是与视觉方向感知相关的众所周知的错误模式。最近的实验表明,这些错误在工作记忆期间持续演变,这对静态感觉模型和传统记忆模型都构成了挑战。在这里,我们证明这些不断演变的错误保持着特征形状,需要两个不同模块之间的网络交互。每个模块都能实现高效的感觉编码和记忆保持,而在单个模块网络中无法同时实现这两者。感觉模块表现出异质调谐,具有强烈的抑制性调制,反映了自然方向统计数据。而记忆模块单独运行时,通过连续吸引子动力学支持均匀表示,全连接网络则形成具有中等漂移速度和非均匀扩散过程的离散吸引子。总的来说,我们的工作强调了在工作记忆中不断塑造刺激表示的感觉-记忆相互作用的重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0cda/11466453/0a4983291c0f/elife-95160-fig1.jpg

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