Inhibitory Control in the Absence of Awareness: Interactions Between Frontal and Motor Cortex Oscillations Mediate Implicitly Learned Responses.

Cognitive control of action is associated with conscious effort and is hypothesised to be reflected by increased frontal theta activity. However, the functional role of these increases in theta power, and how they contribute to cognitive control remains unknown. We conducted an MEG study to test the hypothesis that frontal theta oscillations interact with sensorimotor signals in order to produce controlled behaviour, and that the strength of these interactions will vary with the amount of control required. We measured neuromagnetic activity in 16 healthy adults performing a response inhibition (Go/Switch) task, known from previous work to modulate cognitive control requirements using hidden patterns of Go and Switch cues. Learning was confirmed by reduced reaction times (RT) to patterned compared to random Switch cues. Concurrent measures of pupil diameter revealed changes in subjective cognitive effort with stimulus probability, even in the absence of measurable behavioural differences, revealing instances of covert variations in cognitive effort. Significant theta oscillations were found in five frontal brain regions, with theta power in the right middle frontal and right premotor cortices parametrically increasing with cognitive effort. Similar increases in oscillatory power were also observed in motor cortical gamma, suggesting an interaction. Right middle frontal and right precentral theta activity predicted changes in pupil diameter across all experimental conditions, demonstrating a close relationship between frontal theta increases and cognitive control. Although no theta-gamma cross-frequency coupling was found, long-range theta phase coherence among the five significant sources between bilateral middle frontal, right inferior frontal, and bilateral premotor areas was found, thus providing a mechanism for the relay of cognitive control between frontal and motor areas via theta signalling. Furthermore, this provides the first evidence for the sensitivity of frontal theta oscillations to implicit motor learning and its effects on cognitive load. More generally these results present a possible a mechanism for this frontal theta network to coordinate response preparation, inhibition and execution.

Mapping neural dynamics underlying saccade preparation and execution and their relation to reaction time and direction errors.

Our ability to control and inhibit automatic behaviors is crucial for negotiating complex environments, all of which require rapid communication between sensory, motor, and cognitive networks. Here, we measured neuromagnetic brain activity to investigate the neural timing of cortical areas needed for inhibitory control, while 14 healthy young adults performed an interleaved prosaccade (look at a peripheral visual stimulus) and antisaccade (look away from stimulus) task. Analysis of how neural activity relates to saccade reaction time (SRT) and occurrence of direction errors (look at stimulus on antisaccade trials) provides insight into inhibitory control. Neuromagnetic source activity was used to extract stimulus-aligned and saccade-aligned activity to examine temporal differences between prosaccade and antisaccade trials in brain regions associated with saccade control. For stimulus-aligned antisaccade trials, a longer SRT was associated with delayed onset of neural activity within the ipsilateral parietal eye field (PEF) and bilateral frontal eye field (FEF). Saccade-aligned activity demonstrated peak activation 10ms before saccade-onset within the contralateral PEF for prosaccade trials and within the bilateral FEF for antisaccade trials. In addition, failure to inhibit prosaccades on anti-saccade trials was associated with increased activity prior to saccade onset within the FEF contralateral to the peripheral stimulus. This work on dynamic activity adds to our knowledge that direction errors were due, at least in part, to a failure to inhibit automatic prosaccades. These findings provide novel evidence in humans regarding the temporal dynamics within oculomotor areas needed for saccade programming and the role frontal brain regions have on top-down inhibitory control.

Pupillary responses and reaction times index different cognitive processes in a combined Go/Switch incidental learning task.

In previous studies we have provided evidence that performance in speeded response tasks with infrequent target stimuli reflects both automatic and controlled cognitive processes, based on differences in reaction time (RT) and task-related brain responses (Cheyne et al. 2012, Isabella et al. 2015). Here we test the hypothesis that such shifts in cognitive control may be influenced by changes in cognitive load related to stimulus predictability, and that these changes can be indexed by task-evoked pupillary responses (TEPR). We manipulated stimulus predictability using fixed stimulus sequences that were unknown to the participants in a Go/Switch task (requiring a switch response on 25% of trials) while monitoring TEPR as a measure of cognitive load in 12 healthy adults. Results showed significant improvement in performance (reduced RT, increased efficiency) for repeated sequences compared to occasional deviant sequences (10% probability) indicating that incidental learning of the predictable sequences facilitated performance. All behavioral measures varied between Switch and Go trials (RT, efficiency), however mean TEPR amplitude (mTEPR) and latency to maximum pupil dilation were particularly sensitive to Go/Switch. Results were consistent with the hypothesis that mTEPR indexes cognitive load, whereas TEPR latency indexes time to response selection, independent from response execution. The present study provides evidence that incidental pattern learning during response inhibition tasks may modulate several cognitive processes including cognitive load, effort, response selection and execution, which can in turn have differential effects on measures of performance. In particular, we demonstrate that reaction time may not be indicative of underlying cognitive load.