Proactive and reactive inhibitory control in rats

Jeffrey D Mayse,Shih-Chieh Lin,Geoffrey M Nelson,Michela Gallagher,Pul Park

doi:10.3389/fnins.2014.00104

Abstract

Inhibiting actions inappropriate for the behavioral context, or inhibitory control, is essential for survival and involves both reactively stopping the current prepared action and proactively adjusting behavioral tendencies to increase future performance. A powerful paradigm widely used in basic and clinical research to study inhibitory control is the stop signal task (SST). Recent years have seen a surging interest in translating the SST to rodents to study the neural mechanisms underlying inhibitory control. However, significant differences in task designs and behavioral strategies between rodent and primate studies have made it difficult to directly compare the two literatures. In this study, we developed a rodent-appropriate SST and characterized both reactive and proactive control in rats. For reactive inhibitory control, we found that, unlike in primates, incorrect stop trials in rodents result from two independent types of errors: an initial failure-to-stop error or, after successful stopping, a subsequent failure-to-wait error. Conflating failure-to-stop and failure-to-wait errors systematically overestimates the covert latency of reactive inhibition, the stop signal reaction time (SSRT). To correctly estimate SSRT, we developed and validated a new method that provides an unbiased SSRT estimate independent of the ability to wait. For proactive inhibitory control, we found that rodents adjust both their reaction time and the ability to stop following failure-to-wait errors and successful stop trials, but not after failure-to-stop errors. Together, these results establish a valid rodent model that utilizes proactive and reactive inhibitory control strategies similar to primates, and highlight the importance of dissociating initial stopping from subsequent waiting in studying mechanisms of inhibitory control using rodents.

Highlights

Inhibitory control, or the ability to inhibit actions inappropriate for the context, is essential for meeting the shifting demands of complex environments (Logan et al, 1997)
To test if the two types of Stop trial errors were independent of each other, we investigated whether the proportion and speed of each type of error changed as a function of stop signal delays (SSDs), and whether animals attempted to collect reward following each type of error
Having demonstrated that rats exhibited reactive inhibitory control similar to primates, we further examined whether rats employed proactive control strategies in the stop signal task (SST) by adjusting the speed of their responses based on the outcome of previous trials (Emeric et al, 2007; Li et al, 2008b; Verbruggen and Logan, 2009; Ide and Li, 2011; Pouget et al, 2011; Bissett and Logan, 2012; Ide et al, 2013; Beuk et al, 2014)

Summary

Introduction

Inhibitory control, or the ability to inhibit actions inappropriate for the context, is essential for meeting the shifting demands of complex environments (Logan et al, 1997). Successful inhibitory control can be achieved through both proactive and reactive control strategies, respectively involving preparation to stop prior to stimulus onset and stimulus-driven processing at stimulus onset (Li et al, 2006a; Aron, 2011). One important paradigm to study inhibitory control is the stop signal task (SST). In the SST, subjects need to rapidly cancel a prepotent behavioral response when the go signal is occasionally followed by a stop signal. The SST is uniquely powerful in that it allows for the quantitative estimation of the latency of reactive inhibition, the stop signal reaction time (SSRT) (Logan and Cowan, 1984; Logan et al, 1984). Subjects employ proactive inhibition in the SST to adjust response speed following errors or stop trials (Emeric et al, 2007; Verbruggen and Logan, 2009; Bissett and Logan, 2012). Understanding the neural mechanisms of inhibitory control is critical because elevated SSRT is a widely observed feature of cognitive impairment across many neuropsychiatric disorders, including Parkinson’s disease (Gauggel et al, 2004; Mirabella et al, 2011), attention-deficit hyperactivity disorder (McAlonan et al, 2009), and normal cognitive aging (Andrés et al, 2008; Coxon et al, 2012; Hu et al, 2013)

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