美国艾伦研究所Shawn R. Olsen团队的一项最新研究揭示了小鼠视觉系统变化检测背后的尖峰活动图。相关论文于2026年7月8日发表在《细胞》杂志上。
当小鼠执行图像变化检测任务时，课题组研究人员展示了一个跨主题视觉系统（包括皮层、丘脑和中脑）的尖峰活动数据库。使用Neuropixels探针，课题组人员记录了54只小鼠的75000个高质量单元，绘制了区域、皮质层和细胞类型特异性编码的感觉和运动信息。任务参与的调节在整个丘脑皮质层次中增加，但在中脑中最强。新的图像增加了皮层的数量，并调节了皮层晚期（而不是丘脑）的反应。种群解码和光遗传学确定了变化检测的关键时间窗口，并且与小鼠采用基于适应而不是图像比较的策略一致。这一全面的研究为理解神经网络中的感觉运动计算提供了有价值的基础。
据了解，视觉行为需要跨层次组织的大脑回路的协调活动。理解这种复杂性需要大规模（采样许多区域）和密集（记录每个区域的许多神经元）的数据集。
附：英文原文
Title: Map of spiking activity underlying change detection in the mouse visual system
Author: Corbett Bennett, Samuel D. Gale, Greggory Heller, Tamina K. Ramirez, Hannah Belski, Alex Piet, Omid Zobeiri, Adam Amster, Anton Arkhipov, Alex Cahoon, Shiella Caldejon, Mikayla Carlson, Linzy Casal, Scott F. Daniel, Colin Farrell, Marina Garrett, Ryan Gillis, Conor Grasso, Ben J. Hardcastle, Ross Hytnen, Tye Johnson, Peter Ledochowitsch, Quinn L’Heureux, Dana Mastrovito, Ethan G. McBride, Stefan Mihalas, Chris Mochizuki, Christopher B. Morrison, Chelsea Nayan, Nhan-Kiet Ngo, Kat North, Douglas R. Ollerenshaw, Ben Ouellette, Paul Rhoads, Kara Ronellenfitch, Martin Schroedter, Joshua H. Siegle, Cliff Slaughterbeck, David Sullivan, Jackie Swapp, Michael Taormina, Wayne Wakeman, Xana Waughman, Allison Williford, John W. Phillips, Peter A. Groblewski, Séverine Durand, Christof Koch, Shawn R. Olsen
Issue&Volume: 2026-07-08
Abstract: Visual behavior requires coordinated activity across hierarchically organized brain circuits. Understanding this complexity demands datasets that are both large-scale (sampling many areas) and dense (recording many neurons in each area). Here, we present a database of spiking activity across the mouse visual system—including the cortex, thalamus, and midbrain—while mice perform an image change detection task. Using Neuropixels probes, we record from >75,000 high-quality units in 54 mice, mapping area-, cortical-layer-, and cell-type-specific coding of sensory and motor information. Modulation by task engagement increased across the thalamocortical hierarchy but was strongest in the midbrain. Novel images recruited an expanded cortical population and modulated late cortical (but not thalamic) responses. Population decoding and optogenetics identified a critical time window for change detection and were consistent with mice using an adaptation-based rather than image-comparison strategy. This comprehensive resource provides a valuable substrate for understanding sensorimotor computations in neural networks.
DOI: 10.1016/j.cell.2026.06.025
Source: https://www.cell.com/cell/abstract/S0092-8674(26)00745-2