This study used electroencephalogram (EEG) power spectrum analyses to characterize neural activity during the intertrial interval, a period during which online cognitive adjustments in response to errors or conflict are thought to occur. EEG alpha power was quantified as an inverse index of cerebral activity during the period between each response and the next stimulus in a Stroop task. Alpha power was significantly reduced following error responses compared to correct responses, indicating greater cerebral activity following errors. Reduced alpha power was also observed following Stroop conflict trials compared to no-conflict trials, suggesting that conflict engages processes of mental adjustment. Finally, hemispheric differences in alpha power during the intertrial interval supported the complementary roles of the left and right hemispheres in behavioral activation and inhibition.

Generalized linear models (GLMs) represent a popular choice for the probabilistic characterization of neural spike responses. While GLMs are attractive for their computational tractability, they also impose strong assumptions and thus only allow for a limited range of stimulus-response relationships to be discovered. Alternative approaches exist that make only very weak assumptions but scale poorly to high-dimensional stimulus spaces. Here we seek an approach which can gracefully interpolate between the two extremes. We extend two frequently used special cases of the GLM—a linear and a quadratic model—by assuming that the spike-triggered and non-spike-triggered distributions can be adequately represented using Gaussian mixtures. Because we derive the model from a generative perspective, its components are easy to interpret as they correspond to, for example, the spike-triggered distribution and the interspike interval distribution. The model is able to capture complex dependencies on high-dimensional stimuli with far fewer parameters than other approaches such as histogram-based methods. The added flexibility comes at the cost of a non-concave log-likelihood. We show that in practice this does not have to be an issue and the mixture-based model is able to outperform generalized linear and quadratic models.

This study tested the hypothesis that individual differences in cognitive control can predict individual differences in emotion regulation. Participants completed color-word and emotional Stroop tasks while an electroencephalogram was recorded, and then they reported daily stressful events, affect, and coping for 14 days. Greater posterror slowing in the emotional Stroop task predicted greater negative affect in response to stressors and less use of task-focused coping as daily stressors increased. Participants whose neural activity best distinguished errors from correct responses tended to show less stress reactivity in daily self-reports. Finally, depression levels predicted daily affect and coping independent of cognitive control variables. The results offer qualified support for an integrated conception of cognitive and emotional self-regulation.

Microsaccades, the small saccades made when we try to keep the eyes still, were once believed to be inconsequential for vision, but recent studies suggest that they can precisely relocate gaze to tiny visual targets. Because the cerebellum is necessary for motor precision, we investigated whether microsaccades may exploit this neural machinery in monkeys. Almost all vermal Purkinje cells, which provide the eye-related output of the cerebellar cortex, were found to increase or decrease their simple spike firing rate during microsaccades. At both the single-cell and population level, microsaccade-related activity was highly similar to macrosaccade-related activity and we observed a continuous representation of saccade amplitude that spanned both the macrosaccade and microsaccade domains. Our results suggest that the cerebellum's role in fine-tuning eye movements extends even to the oculomotor system's smallest saccades and add to a growing list of observations that call into question the classical categorical distinction between microsaccades and macrosaccades.