Strauß Daniel, Bing Zhenshan, Zhuang Genghang, Huang Kai, Knoll Alois
Chair of Robotics, Artificial Intelligence and Real-time Systems, TUM School of Computation, Information and Technology, Technical University of Munich, Munich, Germany.
School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China.
Cyborg Bionic Syst. 2024 Sep 12;5:0140. doi: 10.34133/cbsystems.0140. eCollection 2024.
The medial entorhinal cortex of rodents is known to contain grid cells that exhibit precise periodic firing patterns based on the animal's position, resulting in a distinct hexagonal pattern in space. These cells have been extensively studied due to their potential to unveil the navigational computations that occur within the mammalian brain and interesting phenomena such as so-called grid cell distortions have been observed. Previous neuronal models of grid cells assumed their firing fields were independent of environmental boundaries. However, more recent research has revealed that the grid pattern is, in fact, dependent on the environment's boundaries. When rodents are placed in nonsquare cages, the hexagonal pattern tends to become disrupted and adopts different shapes. We believe that these grid cell distortions can provide insights into the underlying neural circuitry involved in grid cell firing. To this end, a calibration circuit for grid cells is proposed. Our simulations demonstrate that this circuit is capable of reproducing grid distortions observed in several previous studies. Our model also reproduces distortions in place cells and incorporates experimentally observed distortions of speed cells, which present further opportunities for exploration. It generates several experimentally testable predictions, including an alternative behavioral description of boundary vector cells that predicts behaviors in nonsquare environments different from the current model of boundary vector cells. In summary, our study proposes a calibration circuit that reproduces observed grid distortions and generates experimentally testable predictions, aiming to provide insights into the neural mechanisms governing spatial computations in mammals.
已知啮齿动物的内侧内嗅皮层包含网格细胞,这些细胞会根据动物的位置呈现精确的周期性放电模式,从而在空间中形成独特的六边形图案。由于这些细胞有可能揭示哺乳动物大脑内发生的导航计算,因此受到了广泛研究,并且观察到了诸如所谓的网格细胞畸变等有趣现象。以往的网格细胞神经元模型假定其放电场与环境边界无关。然而,最近的研究表明,事实上网格图案依赖于环境边界。当将啮齿动物置于非方形笼子中时,六边形图案往往会被打乱并呈现出不同的形状。我们认为这些网格细胞畸变能够为涉及网格细胞放电的潜在神经回路提供见解。为此,我们提出了一种网格细胞校准电路。我们的模拟表明,该电路能够重现先前多项研究中观察到的网格畸变。我们的模型还重现了位置细胞中的畸变,并纳入了实验观察到的速度细胞畸变,这为进一步探索提供了更多机会。它产生了几个可通过实验验证的预测,包括对边界向量细胞的另一种行为描述,该描述预测了非方形环境中的行为,与当前边界向量细胞模型不同。总之,我们的研究提出了一种校准电路,该电路能够重现观察到的网格畸变并产生可通过实验验证的预测,旨在为控制哺乳动物空间计算的神经机制提供见解。