Leanne Boucher

Inhibitory control in mind and brain: An interactive race model of countermanding saccades

The stop-signal task has been used to study normal cognitive control and clinical dysfunction. Its utility is derived from a race model that accounts for performance and provides an estimate of the time it takes to stop a movement. This model posits a race between go and stop processes with stochastically independent finish times. However, neurophysiological studies demonstrate that the neural correlates of the go and stop processes produce movements through a network of interacting neurons. The juxtaposition of the computational model with the neural data exposes a paradox-how can a network of interacting units produce behavior that appears to be the outcome of an independent race? The authors report how a simple, competitive network can solve this paradox and provide an account of what is measured by stop-signal reaction time.

Influence of history on saccade countermanding performance in humans and macaque monkeys

The stop-signal or countermanding task probes the ability to control action by requiring subjects to withhold a planned movement in response to an infrequent stop signal which they do with variable success depending on the delay of the stop signal. We investigated whether performance of humans and macaque monkeys in a saccade countermanding task was influenced by stimulus and performance history. In spite of idiosyncrasies across subjects several trends were evident in both humans and monkeys. Response time decreased after successive trials with no stop signal. Response time increased after successive trials with a stop signal. However, post-error slowing was not observed. Increased response time was observed mainly or only after cancelled (signal inhibit) trials and not after noncancelled (signal respond) trials. These global trends were based on rapid adjustments of response time in response to momentary fluctuations in the fraction of stop signal trials. The effects of trial sequence on the probability of responding were weaker and more idiosyncratic across subjects when stop signal fraction was fixed. However, both response time and probability of responding were influenced strongly by variations in the fraction of stop signal trials. These results indicate that the race model of countermanding performance requires extension to account for these sequential dependencies and provide a basis for physiological studies of executive control of countermanding saccade performance.

Response Inhibition and Response Monitoring in a Saccadic Countermanding Task in Schizophrenia

BACKGROUND Cognitive control deficits are pervasive in individuals with schizophrenia (SZ) and are reliable predictors of functional outcome, but the specificity of these deficits and their underlying neural mechanisms have not been fully elucidated. The objective of the present study was to determine the nature of response inhibition and response monitoring deficits in SZ and their relationship to symptoms and social and occupational functioning with a behavioral paradigm that provides a translational approach to investigating cognitive control. METHODS Seventeen patients with SZ and 16 demographically matched healthy control subjects participated in a saccadic countermanding task. Performance on this task is approximated as a race between movement generation and inhibition processes; this race model provides an estimate of the time needed to cancel a planned movement. Response monitoring can be assessed by reaction time adjustments on the basis of trial history. RESULTS Saccadic reaction time was normal, but patients required more time to inhibit a planned saccade. The latency of the inhibitory process was associated with the severity of negative symptoms and poorer occupational functioning. Both groups slowed down significantly after correctly cancelled and erroneously noncancelled stop signal trials, but patients slowed down more than control subjects after correctly inhibited saccades. CONCLUSIONS These results suggest that SZ is associated with a difficulty in inhibiting planned movements and an inflated response adjustment effect after inhibiting a saccade. Furthermore, behavioral results are consistent with potential abnormalities in frontal and supplementary eye fields in patients with SZ.

Proactive Inhibitory Control and Attractor Dynamics in Countermanding Action: A Spiking Neural Circuit Model

Flexible behavior depends on the brains ability to suppress a habitual response or to cancel a planned movement whenever needed. Such inhibitory control has been studied using the countermanding paradigm in which subjects are required to withhold an imminent movement when a stop signal appears infrequently in a fraction of trials. To elucidate the circuit mechanism of inhibitory control of action, we developed a recurrent network model consisting of spiking movement (GO) neurons and fixation (STOP) neurons, based on neurophysiological observations in the frontal eye field and superior colliculus of behaving monkeys. The model places a premium on the network dynamics before the onset of a stop signal, especially the experimentally observed high baseline activity of fixation neurons, which is assumed to be modulated by a persistent top-down control signal, and their synaptic interaction with movement neurons. The model simulated observed neural activity and fit behavioral performance quantitatively. In contrast to a race model in which the STOP process is initiated at the onset of a stop signal, in our model whether a movement will eventually be canceled is determined largely by the proactive top-down control and the stochastic network dynamics, even before the appearance of the stop signal. A prediction about the correlation between the fixation neural activity and the behavioral outcome was verified in the neurophysiological data recorded from behaving monkeys. The proposed mechanism for adjusting control through tonically active neurons that inhibit movement-producing neurons has significant implications for exploring the basis of impulsivity associated with psychiatric disorders.

Saccades operate in violation of Hick’s law

Hick’s law states that response times (RTs) increase in proportion to the logarithm of the number of potential stimulus-response (S-R) alternatives. We hypothesized that time-consuming processes associated with response selection contribute significantly to this effect. We also hypothesized that the latency of saccades might not conform to Hick’s law since visually guided saccades can be automatically selected using topographically organized pathways that convert spatially coded visual activity into spatially coded motor commands. We evaluated these hypotheses by examining three response modalities for their compliance with Hick’s law: saccades directed to a visual target (prosaccades), saccades directed away from the target (antisaccades) and manual responses in which each digit was associated with a specific target location (key-press responses). Both antisaccades and key-press responses conformed to Hick’s law but saccade latencies were completely unaffected by S-R uncertainty. The significance of these findings is considered in terms of the processes of response selection and premotor programming.

Neural Basis of Adaptive Response Time Adjustment during Saccade Countermanding

Humans and macaque monkeys adjust their response time adaptively in stop-signal (countermanding) tasks, responding slower after stop-signal trials than after control trials with no stop signal. We investigated the neural mechanism underlying this adaptive response time adjustment in macaque monkeys performing a saccade countermanding task. Earlier research showed that movements are initiated when the random accumulation of presaccadic movement-related activity reaches a fixed threshold. We found that a systematic delay in response time after stop-signal trials was accomplished not through a change of threshold, baseline, or accumulation rate, but instead through a change in the time when activity first began to accumulate. The neurons underlying movement initiation have been identified with stochastic accumulator models of response time performance. Therefore, this new result provides surprising new insights into the neural instantiation of stochastic accumulator models and the mechanisms through which executive control can be exerted.

Executive Control of Gaze by the Frontal Lobes

Executive control requires controlling the initiation of movements, judging the consequences of actions, and adjusting performance accordingly. We have investigated the role of different areas in the frontal lobe in executive control expressed by macaque monkeys performing a saccade stop signal task. Certain neurons in the frontal eye field respond to visual stimuli, and others control the production of saccadic eye movements. Neurons in the supplementary eye field do not control directly the initiation of saccades but, instead, signal the production of errors, the anticipation and delivery of reinforcement, and the presence of response conflict. Neurons in the anterior cingulate cortex signal the production of errors and the anticipation and delivery of reinforcement, but not the presence of response conflict. Intracranial local field potentials in the anterior cingulate cortex of monkeys indicate that these medial frontal signals can contribute to event-related potentials related to performance monitoring. Electrical stimulation of the supplementary eye field improves performance in the task by elevating saccade latency. An interactive race model shows how interacting units produce behavior that can be described as the outcome of a race between independent processes and how conflict between gaze-holding and gaze-shifting neurons can be used to adjust performance.

Stopping eye and hand movements: Are the processes independent?

To explore how eye and hand movements are controlled in a stop task, we introduced effector uncertainty by instructing subjects to initiate and occasionally inhibit eye, hand, or eye + hand movements in response to a color-coded foveal or tone-coded auditory stop signal. Regardless of stop signal modality, stop signal reaction time was shorter for eye movements than for hand movements, but notably did not vary with knowledge about which movement to cancel. Most errors on eye + hand stopping trials were combined eye + hand movements. The probability and latency of signal respond eye and hand movements corresponded to predictions of Logan and Cowan’s (1984) race model applied to each effector independently.

Nonindependent and nonstationary response times in stopping and stepping saccade tasks

Saccade stop signal and target step tasks are used to investigate the mechanisms of cognitive control. Performance of these tasks can be explained as the outcome of a race between stochastic go and stop processes. The race model analyses assume that response times (RTs) measured throughout an experimental session are independent samples from stationary stochastic processes. This article demonstrates that RTs are neither independent nor stationary for humans and monkeys performing saccade stopping and target-step tasks. We investigate the consequences that this has on analyses of these data. Nonindependent and nonstationary RTs artificially flatten inhibition functions and account for some of the systematic differences in RTs following different types of trials. However, nonindependent and nonstationary RTs do not bias the estimation of the stop signal RT. These results demonstrate the robustness of the race model to some aspects of nonindependence and nonstationarity and point to useful extensions of the model.

Afferent delays and the mislocalization of perisaccadic stimuli.

Determining the precise moment a visual stimulus appears is difficult because visual response latencies vary. This temporal uncertainty could cause localization errors to brief visual targets presented before and during eye movements if the oculomotor system cannot determine the position of the eye at the time the stimulus appeared. We investigated the effect of varying neural processing time on localization accuracy for perisaccadic visual targets that differed in luminance. Although systematic errors in localization were observed, the effect of luminance was surprisingly small. We explore several hypotheses that may explain why processing delays are not more disruptive to localization performance.