Caglayan Alican, Stumpenhorst Katharina, Winter York
Institute for Biology, Humboldt University, Berlin, Germany.
Excellenzcluster NeuroCure, Charité Universitätsmedizin Berlin, Berlin, Germany.
Front Behav Neurosci. 2021 Dec 9;15:777767. doi: 10.3389/fnbeh.2021.777767. eCollection 2021.
Ceasing an ongoing motor response requires action cancelation. This is impaired in many pathologies such as attention deficit disorder and schizophrenia. Action cancelation is measured by the stop signal task that estimates how quickly a motor response can be stopped when it is already being executed. Apart from human studies, the stop signal task has been used to investigate neurobiological mechanisms of action cancelation overwhelmingly in rats and only rarely in mice, despite the need for a genetic model approach. Contributing factors to the limited number of mice studies may be the long and laborious training that is necessary and the requirement for a very loud (100 dB) stop signal. We overcame these limitations by employing a fully automated home-cage-based setup. We connected a home-cage to the operant box via a gating mechanism, that allowed individual ID chipped mice to start sessions voluntarily. Furthermore, we added a negative reinforcement consisting of a mild air puff with escape option to the protocol. This specifically improved baseline inhibition to 94% (from 84% with the conventional approach). To measure baseline inhibition the stop is signaled immediately with trial onset thus measuring action restraint rather than action cancelation ability. A high baseline allowed us to measure action cancelation ability with higher sensitivity. Furthermore, our setup allowed us to reduce the intensity of the acoustic stop signal from 100 to 70 dB. We constructed inhibition curves from stop trials with daily adjusted delays to estimate stop signal reaction times (SSRTs). SSRTs (median 88 ms) were lower than reported previously, which we attribute to the observed high baseline inhibition. Our automated training protocol reduced training time by 17% while also promoting minimal experimenter involvement. This sensitive and labor efficient stop signal task procedure should therefore facilitate the investigation of action cancelation pathologies in genetic mouse models.
停止正在进行的运动反应需要动作取消。这在许多病理状态下会受损,如注意力缺陷障碍和精神分裂症。动作取消通过停止信号任务来测量,该任务估计当运动反应已经在执行时能够多快被停止。除了人体研究外,尽管需要遗传模型方法,但停止信号任务已被大量用于研究大鼠动作取消的神经生物学机制,而在小鼠中使用得很少。小鼠研究数量有限的促成因素可能是所需的漫长且费力的训练以及对非常响亮(100分贝)停止信号的要求。我们通过采用基于全自动化笼内的设置克服了这些限制。我们通过一个门控机制将笼内环境与操作性条件反射箱相连,该机制允许带有个体识别芯片的小鼠自愿开始实验。此外,我们在实验方案中增加了一种由轻微吹气并带有逃避选项组成的负强化。这特别将基线抑制提高到了94%(传统方法为84%)。为了测量基线抑制,在试验开始时立即发出停止信号,从而测量动作抑制而非动作取消能力。高基线使我们能够以更高的灵敏度测量动作取消能力。此外,我们的设置使我们能够将声学停止信号的强度从100分贝降低到70分贝。我们根据每日调整延迟的停止试验构建抑制曲线,以估计停止信号反应时间(SSRTs)。SSRTs(中位数88毫秒)低于先前报道的值,我们将其归因于观察到的高基线抑制。我们的自动化训练方案将训练时间减少了17%,同时还减少了实验者的参与。因此,这种灵敏且高效省力的停止信号任务程序应有助于在遗传小鼠模型中研究动作取消相关的病理状态。