RIKEN Brain Science Institute, Wako, Saitama 351-0198, Japan.
Faculty of Informatics, Kogakuin University, Shinjuku-ku, Tokyo 163-8677, Japan.
Cereb Cortex. 2017 Jul 1;27(7):3818-3831. doi: 10.1093/cercor/bhx031.
Neurons in medial frontal cortex (MFC) receive sensory signals that are crucial for decision-making behavior. While decision-making is easy for familiar sensory signals, it becomes more elaborative when sensory signals are less familiar to animals. It remains unclear how the population of neurons enables the coordinate transformation of such a sensory input into ambiguous choice responses. Furthermore, whether and how cortical oscillations temporally coordinate neuronal firing during this transformation has not been extensively studied. Here, we recorded neuronal population responses to familiar or unfamiliar auditory cues in rat MFC and computed their probabilistic evolution. Population responses to familiar sounds organize into neuronal trajectories containing multiplexed sensory, motor, and choice information. Unfamiliar sounds, in contrast, evoke trajectories that travel under the guidance of familiar paths and eventually diverge to unique decision states. Local field potentials exhibited beta- (15-20 Hz) and gamma-band (50-60 Hz) oscillations to which neuronal firing showed modest phase locking. Interestingly, gamma oscillation, but not beta oscillation, increased its power abruptly at some timepoint by which neural trajectories for different choices were near maximally separated. Our results emphasize the importance of the evolution of neural trajectories in rapid probabilistic decisions that utilize unfamiliar sensory information.
内侧前额叶皮层(MFC)中的神经元接收对决策行为至关重要的感觉信号。虽然对于熟悉的感觉信号来说,决策很容易,但当动物对感觉信号不太熟悉时,决策就变得更加复杂了。目前尚不清楚神经元群体如何将这种感觉输入协调转化为模糊的选择反应。此外,在这种转化过程中,皮质振荡是否以及如何在时间上协调神经元的放电,还没有得到广泛的研究。在这里,我们记录了大鼠 MFC 中熟悉或不熟悉的听觉线索的神经元群体反应,并计算了它们的概率演变。对熟悉声音的群体反应组织成包含多路感觉、运动和选择信息的神经元轨迹。相比之下,不熟悉的声音则会在熟悉路径的引导下产生轨迹,并最终发散到独特的决策状态。局部场电位表现出β(15-20 Hz)和γ波段(50-60 Hz)振荡,神经元放电表现出适度的相位锁定。有趣的是,只有γ振荡而不是β振荡在某个时间点突然增加其功率,此时不同选择的神经轨迹几乎最大程度地分开。我们的研究结果强调了神经轨迹在利用不熟悉感觉信息的快速概率决策中的重要性。