Evoked cortical responses do not follow a rigid input–output function but are dynamically shaped by intrinsic neural properties at the time of stimulation. Recent research has emphasized the role of oscillatory activity in determining cortical excitability. Here we employed EEG-guided transcranial magnetic stimulation (TMS) during non-rapid eye movement sleep to examine whether the spontaneous <1 Hz neocortical slow oscillation (SO) is associated with corresponding fluctuations of evoked responses. Whereas the SO's alternating phases of global depolarization (up-state) and hyperpolarization (down-state) are clearly associated with fluctuations in spontaneous neuronal excitation, less is known about state-dependent shifts in neocortical excitability. In 12 human volunteers, single-pulse TMS of the primary motor cortical hand area (M1_HAND) was triggered online by automatic detection of SO up-states and down-states in the EEG. State-dependent changes in cortical excitability were traced by simultaneously recording motor-evoked potentials (MEPs) and TMS-evoked EEG potentials (TEPs). Compared to wakefulness and regardless of SO state, sleep MEPs were smaller and delayed whereas sleep TEPs were fundamentally altered, closely resembling a spontaneous SO. However, both MEPs and TEPs were consistently larger when evoked during SO up-states than during down-states, and ampliudes within each SO state depended on the actual EEG potential at the time and site of stimulation. These results provide first-time evidence for a rapid state-dependent shift in neocortical excitability during a neuronal oscillation in the human brain. We further demonstrate that EEG-guided temporal neuronavigation is a powerful tool to investigate the phase-dependent effects of neuronal oscillations on perception, cognition, and motor control.

Meta-analytic evidence showed robust associations between the alliance in psychotherapeutic dyads and treatment outcomes. Recent studies have indicated that facets of positive mental health are add...

Test items become easier when a representational picture visualizes the text item stem; this is referred to as the multimedia effect in testing. To uncover the processes underlying this effect and to understand how pictures affect students' item-solving behavior, we recorded the eye movements of sixty-two schoolchildren solving multiple-choice (MC) science items either with or without a representational picture. Results show that the time students spent fixating the picture was compensated for by less time spent reading the corresponding text. In text-picture items, students also spent less time fixating incorrect answer options; a behavior that was associated with better test scores in general. Detailed gaze likelihood analyses revealed that the picture received particular attention right after item onset and in the later phase of item solving. Hence, comparable to learning, pictures in tests seemingly boost students' performance because they may serve as mental scaffolds, supporting comprehension and decision making

Digital tests make it possible to identify student effort by means of response times, specifically, unrealistically fast responses that are defined as rapid-guessing behavior (RGB). In this study, we used latent class and growth curve models to examine (1) how student characteristics (i.e., gender, school type, general cognitive abilities, and working-memory capacity) are related to the onset point of RGB and its development over the course of a test session (i.e., item positions). Further, we examined (2) the extent to which repeated ratings of task enjoyment (i.e., intercept and slope parameters) are related to the onset and the development of RGB over the course of the test. For this purpose, we analyzed data from N = 401 students from fifth and sixth grades in Germany (n = 247 academic track; n = 154 non-academic track). All participants solved 36 science items under low-stakes conditions and rated their current task enjoyment after each science item, constituting a micro-longitudinal design that allowed students' motivational state to be tracked over the entire test session. In addition, they worked on tests that assessed their general cognitive abilities and working-memory capacity. The results show that students' gender was not significantly related to RGB but that students' school type (which is known to be closely related to academic abilities in the German school system), general cognitive abilities, and their working-memory capacity were significant predictors of an early RGB onset and a stronger RGB increase across testing time. Students' initial rating of task enjoyment was associated with RGB, but only a decline in students' task enjoyment was predictive of earlier RGB onset. Overall, non-academic-school attendance was the most powerful predictor of RGB, together with students' working-memory capacity. The present findings add to the concern that there is an unfortunate relation between students' test-effort investment and their academic and general cognitive abilities. This challenges basic assumptions about motivation-filtering procedures and may threaten a valid interpretation of results from large-scale testing programs that rely on school-type comparisons.