The Stop Signal Task for Measuring Behavioral Inhibition in Mice With Increased Sensitivity and High-Throughput
Alican Caglayan1, Katharina Stumpenhorst1, York Winter1,2
1Institute for Biology, Humboldt University, Berlin, Germany.
Abstract:
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.
Insights
Researchers developed an automated mouse model for action cancelation using a novel stop signal task. This efficient method reduces training time and facilitates studying neurological disorders in genetic models.
Area of Science:
- Neuroscience
- Behavioral Science
Background:
- Action cancelation, the ability to cease ongoing motor responses, is impaired in conditions like ADHD and schizophrenia.
- The stop signal task is a key measure for action cancelation, but its application in mice is limited by extensive training and high-intensity stop signals.
Purpose of the Study:
- To develop a more efficient and sensitive automated stop signal task for mice.
- To overcome limitations of previous mouse models for action cancelation research.
Main Methods:
- An automated home-cage setup with a gating mechanism and negative reinforcement (air puff) was used.
- The stop signal intensity was reduced from 100 dB to 70 dB.
- Inhibition curves were constructed to estimate stop signal reaction times (SSRTs).
Main Results:
- Baseline inhibition improved significantly to 94% compared to the conventional 84%.
- Automated training reduced training time by 17% with minimal experimenter involvement.
- SSRTs were found to be lower (median 88 ms) than previously reported, attributed to enhanced baseline inhibition.
Conclusions:
- The developed automated stop signal task is sensitive, labor-efficient, and reduces training time.
- This refined method facilitates the investigation of action cancelation deficits in genetic mouse models.
- The study provides a valuable tool for understanding the neurobiological basis of action cancelation impairments.
