Cognitive control and automatic interference in mind and brain: A unified model of saccadic inhibition and countermanding.

Aline Bompas,Anne Eileen Campbell,Petroc Sumner

doi:10.1037/rev0000181

Abstract

Countermanding behavior has long been seen as a cornerstone of executive control—the human ability to selectively inhibit undesirable responses and change plans. However, scattered evidence implies that stopping behavior is entangled with simpler automatic stimulus-response mechanisms. Here we operationalize this idea by merging the latest conceptualization of saccadic countermanding with a neural network model of visuo-oculomotor behavior that integrates bottom-up and top-down drives. This model accounts for all fundamental qualitative and quantitative features of saccadic countermanding, including neuronal activity. Importantly, it does so by using the same architecture and parameters as basic visually guided behavior and automatic stimulus-driven interference. Using simulations and new data, we compare the temporal dynamics of saccade countermanding with that of saccadic inhibition (SI), a hallmark effect thought to reflect automatic competition within saccade planning areas. We demonstrate how SI accounts for a large proportion of the saccade countermanding process when using visual signals. We conclude that top-down inhibition acts later, piggy-backing on the quicker automatic inhibition. This conceptualization fully accounts for the known effects of signal features and response modalities traditionally used across the countermanding literature. Moreover, it casts different light on the concept of top-down inhibition, its timing and neural underpinning, as well as the interpretation of stop-signal reaction time (RT), the main behavioral measure in the countermanding literature.

Highlights

There is a long tradition in psychology and neuroscience of drawing a conceptual distinction between “top-down” volitional processes and “bottom-up” automatic responses
In our previous work on saccadic inhibition, we have referred to this divergence point as dip onset or T0 and, using DINASAUR, we have shown that T0 Ϫ stimulus onset asynchrony (SOA) directly reflects non-decision time (Bompas et al, 2017; Bompas & Sumner, 2011, 2015)
stop signal reaction time (SSRT) is sensitive to the salience of the stop signal and insensitive to fixation offsets (Camalier et al, 2007; Morein-Zamir & Kingstone, 2006), just like T0 in a saccadic inhibition paradigm (Bompas & Sumner, 2011; Reingold & Stampe, 2002). These findings suggest that SSRT likely behaves like T0, and we expect the early part of the interference from stop-signals and distractors should be very similar in saccadic inhibition and countermanding

Summary

Introduction

There is a long tradition in psychology and neuroscience of drawing a conceptual distinction between “top-down” volitional processes and “bottom-up” automatic responses. Animal brains are full of inhibitory connections (see Noorani & Carpenter, 2017 for a review), many of which can be considered very basic and automatic properties of neural maps or local networks We believe these low-level mechanisms critically shape behaviors traditionally ascribed to top-down control and, in some conditions, even form the main basis for well-known hallmarks of “control” behavior. Even though they may be rather indiscriminate and simple, the potential advantage of stimulus-driven inhibitory circuits would be their speed—a quick interruption allowing slower more complex processes time to update action plans (e.g., Schmidt & Berke, 2017). A first step is to draw modeling attempts together and develop more general models, able to predict human or animal behavior in new experimental conditions

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