Biomedical subjects
Publications and source records attributed to Nick Yeung.
A recent study indicates that alcohol consumption reduces the amplitude of the error-related negativity (ERN), a negative deflection in the electroencephalogram associated with error commission. Here, we explore possible mechanisms underlying this result in the context of two recent theories about the neural system that produces the ERN - one based on principles of reinforcement learning and the other based on response conflict monitoring.
It has been reported that it is harder to switch to a strong, well-practiced task from a weaker, less-practiced task than vice versa. Three experiments replicated this surprising asymmetry and investigated how it is affected by a reduction in interference between tasks. Experiment 1 progressively delayed the onset of the stimulus attribute associated with the stronger task. Experiments 2 and 3 separated the response sets of the tasks. Both manipulations reduced, without eliminating, interference of the stronger with the weaker task but reversed the asymmetry of switch costs, resulting in a larger cost of switching to the weaker task. The results are interpreted in terms of a model of the interactions between control input, task strength, and task priming.
Neuroimaging and computational modeling studies have led to the suggestion that response conflict monitoring by the anterior cingulate cortex plays a key role in cognitive control. For example, response conflict is high when a response must be withheld (no-go) in contexts in which there is a prepotent tendency to make an overt (go) response. An event-related brain potential (ERP) component, the N2, is more pronounced on no-go than on go trials and was previously thought to reflect the need to inhibit the go response. However, the N2 may instead reflect the high degree of response conflict on no-go trials. If so, an N2 should also be apparent when subjects make a go response in conditions in which no-go events are more common. To test this hypothesis, we collected high-density ERP data from subjects performing a go/no-go task, in which the relative frequency of go versus no-go stimuli was varied. Consistent with our hypothesis, an N2 was apparent on both go and no-go trials and showed the properties expected of an ERP measure of conflict detection on correct trials: (1) It was enhanced for low-frequency stimuli, irrespective of whether these stimuli were associated with generating or suppressing a response, and (2) it was localized to the anterior cingulate cortex. This suggests that previous conceptions of the no-go N2 as indexing response inhibition may be in need of revision. Instead, the results are consistent with the view that the N2 in go/no-go tasks reflects conflict arising from competition between the execution and the inhibition of a single response.
Conventional analysis of electroencephalography (EEG) and magnetoencephalography (MEG) often relies on averaging over multiple trials to extract statistically relevant differences between two or more experimental conditions. In this article we demonstrate single-trial detection by linearly integrating information over multiple spatially distributed sensors within a predefined time window. We report an average, single-trial discrimination performance of Az approximately 0.80 and faction correct between 0.70 and 0.80, across three distinct encephalographic data sets. We restrict our approach to linear integration, as it allows the computation of a spatial distribution of the discriminating component activity. In the present set of experiments the resulting component activity distributions are shown to correspond to the functional neuroanatomy consistent with the task (e.g., contralateral sensorymotor cortex and anterior cingulate). Our work demonstrates how a purely data-driven method for learning an optimal spatial weighting of encephalographic activity can be validated against the functional neuroanatomy.