Rhythmic neural activity synchronizes with certain rhythmic behaviors, such as breathing, sniffing, saccades, and speech. The extent to which neural oscillations synchronize with higher-level and more complex behaviors is largely unknown. Here, we investigated electrophysiological synchronization with keyboard typing, which is an omnipresent behavior daily engaged by an uncountably large number of people. Keyboard typing is rhythmic, with frequency characteristics roughly the same as neural oscillatory dynamics associated with cognitive control, notably through midfrontal theta (4–7 Hz) oscillations. We tested the hypothesis that synchronization occurs between typing and midfrontal theta and breaks down when errors are committed. Thirty healthy participants typed words and sentences on a keyboard without visual feedback, while EEG was recorded. Typing rhythmicity was investigated by interkeystroke interval analyses and by a kernel density estimation method. We used a multivariate spatial filtering technique to investigate frequency-specific synchronization between typing and neuronal oscillations. Our results demonstrate theta rhythmicity in typing (around 6.5 Hz) through the two different behavioral analyses. Synchronization between typing and neuronal oscillations occurred at frequencies ranging from 4 to 15 Hz, but to a larger extent for lower frequencies. However, peak synchronization frequency was idiosyncratic across participants, therefore not specific to theta nor to midfrontal regions, and correlated somewhat with peak typing frequency. Errors and trials associated with stronger cognitive control were not associated with changes in synchronization at any frequency. As a whole, this study shows that brain–behavior synchronization does occur during keyboard typing but is not specific to midfrontal theta.

Goal-directed behavior requires control over automatic behavior, for example, when goal-irrelevant information from the environment captures an inappropriate response and conflicts with the correct, goal-relevant action. Neural oscillations in the theta band (∼6 Hz) measured at midfrontal electrodes are thought to form an important substrate of the detection and subsequent resolution of response conflict. Here, we examined the extent to which response conflict and associated theta-band activity depend on the visual stimulus feature dimension that triggers the conflict. We used a feature-based Simon task to manipulate conflict by motion direction and stimulus color. Analyses were focused on individual differences in behavioral response conflict elicited across different stimulus dimensions and their relationship to conflict-related midfrontal theta. We first confirmed the presence of response conflict elicited by task-irrelevant motion and stimulus color, demonstrating the usefulness of our modified version of the Simon task to assess different sensory origins of response conflict. Despite titrating overall task performance, we observed large individual differences in the behavioral manifestations of response conflict elicited by the different visual dimensions. These behavioral conflict effects were mirrored in a dimension-specific relationship with conflict-related midfrontal theta power, such that, for each dimension, individual midfrontal theta power was generally higher when experienced response conflict was high. Finally, exploratory analyses of interregional functional connectivity suggested a role for phase synchronization between frontal and parietal scalp sites in modulating experienced conflict when color was the task-relevant visual dimension. Highlighting the importance of an individual differences approach in cognitive neuroscience, these results reveal large individual differences in experienced response conflict depending on the source of visual interference, which are predicted by conflict-related midfrontal theta power.

Evidence is accumulating that the classic two-stage model of visual STM (VSTM), comprising iconic memory (IM) and visual working memory (WM), is incomplete. A third memory stage, termed fragile VSTM (FM), seems to exist in between IM and WM [Vandenbroucke, A. R. E., Sligte, I. G., & Lamme, V. A. F. Manipulations of attention dissociate fragile visual STM from visual working memory. Neuropsychologia, 49, 1559–1568, 2011; Sligte, I. G., Scholte, H. S., & Lamme, V. A. F. Are there multiple visual STM stores? PLoS One, 3, e1699, 2008]. Although FM can be distinguished from IM using behavioral and fMRI methods, the question remains whether FM is a weak expression of WM or a separate form of memory with its own neural signature. Here, we tested whether FM and WM in humans are supported by dissociable time–frequency features of EEG recordings. Participants performed a partial-report change detection task, from which individual differences in FM and WM capacity were estimated. These individual FM and WM capacities were correlated with time–frequency characteristics of the EEG signal before and during encoding and maintenance of the memory display. FM capacity showed negative alpha correlations over peri-occipital electrodes, whereas WM capacity was positively related, suggesting increased visual processing (lower alpha) to be related to FM capacity. Furthermore, FM capacity correlated with an increase in theta power over central electrodes during preparation and processing of the memory display, whereas WM did not. In addition to a difference in visual processing characteristics, a positive relation between gamma power and FM capacity was observed during both preparation and maintenance periods of the task. On the other hand, we observed that theta–gamma coupling was negatively correlated with FM capacity, whereas it was slightly positively correlated with WM. These data show clear differences in the neural substrates of FM versus WM and suggest that FM depends more on visual processing mechanisms compared with WM. This study thus provides novel evidence for a dissociation between different stages in VSTM.

The perception of near-threshold visual stimuli has been shown to depend in part on the phase (i.e., time in the cycle) of ongoing alpha (8–13 Hz) oscillations in the visual cortex relative to the onset of that stimulus. However, it is currently unknown whether the phase of the ongoing alpha activity can be manipulated by top–down factors such as attention or expectancy. Using three variants of a cross-modal attention paradigm with constant predictable stimulus onsets, we examined if cues signaling to attend to either the visual or the auditory domain influenced the phase of alpha oscillations in the associated sensory cortices. Importantly, intermixed in all three experiments, we included trials without a target to estimate the phase at target presentation without contamination from the early evoked responses. For these blank trials, at the time of expected target and distractor onset, we examined (1) the degree of the uniformity in phase angles across trials, (2) differences in phase angle uniformity compared with a pretarget baseline, and (3) phase angle differences between visual and auditory target conditions. Across all three experiments, we found that, although the cues induced a modulation in alpha power in occipital electrodes, neither the visual condition nor the auditory cue condition induced any significant phase-locking across trials during expected target or distractor presentation. These results suggest that, although alpha power can be modulated by top–down factors such as attention and expectation, the phase of the ongoing alpha oscillation is not under such control.

Cognitive control allows us to adjust to environmental changes. The medial frontal cortex (MFC) is thought to detect conflicts and recruit additional resources from other brain areas including the lateral prefrontal cortices. Here we investigated how the MFC acts in concert with visual, motor, and lateral prefrontal cortices to support adaptations of goal-directed behavior. Physiologically, these interactions may occur through local and long-range synchronized oscillation dynamics, particularly in the theta range (4–8 Hz). A speeded flanker task allowed us to investigate conflict-type-specific control networks for perceptual and response conflicts. Theta power over MFC was sensitive to both perceptual and response conflict. Interareal theta phase synchrony, however, indicated a selective enhancement specific for response conflicts between MFC and left frontal cortex as well as between MFC and the presumed motor cortex contralateral to the response hand. These findings suggest that MFC theta-band activity is both generally involved in conflict processing and specifically involved in linking a neural network controlling response conflict.

Frontal oscillatory dynamics in the theta (4–8 Hz) and beta (20–30 Hz) frequency bands have been implicated in cognitive control processes. Here we investigated the changes in coordinated activity within and between frontal brain areas during feedback-based response learning. In a time estimation task, participants learned to press a button after specific, randomly selected time intervals (300–2000 msec) using the feedback after each button press (correct, too fast, too slow). Consistent with previous findings, theta-band activity over medial frontal scalp sites (presumably reflecting medial frontal cortex activity) was stronger after negative feedback, whereas beta-band activity was stronger after positive feedback. Theta-band power predicted learning only after negative feedback, and beta-band power predicted learning after positive and negative feedback. Furthermore, negative feedback increased theta-band intersite phase synchrony (a millisecond resolution measure of functional connectivity) among right lateral prefrontal, medial frontal, and sensorimotor sites. These results demonstrate the importance of frontal theta- and beta-band oscillations and intersite communication in the realization of reinforcement learning.

It has been suggested that the target areas of dopaminergic midbrain neurons, the dorsal (DS) and ventral striatum (VS), are differently involved in reinforcement learning especially as actor and critic. Whereas the critic learns to predict rewards, the actor maintains action values to guide future decisions. The different midbrain connections to the DS and the VS seem to play a critical role in this functional distinction. Here, subjects performed a dynamic, reward-based decision-making task during fMRI acquisition. A computational model of reinforcement learning was used to estimate the different effects of positive and negative reinforcements on future decisions for each subject individually. We found that activity in both the DS and the VS correlated with reward prediction errors. Using functional connectivity, we show that the DS and the VS are differentially connected to different midbrain regions (possibly corresponding to the substantia nigra [SN] and the ventral tegmental area [VTA], respectively). However, only functional connectivity between the DS and the putative SN predicted the impact of different reinforcement types on future behavior. These results suggest that connections between the putative SN and the DS are critical for modulating action values in the DS according to both positive and negative reinforcements to guide future decision making.

The nucleus accumbens is critical for reward-guided learning and decision-making. It is thought to “gate” the flow of a diverse range of information (e.g., rewarding, aversive, and novel events) from limbic afferents to basal ganglia outputs. Gating and information encoding may be achieved via cross-frequency coupling, in which bursts of high-frequency activity occur preferentially during specific phases of slower oscillations. We examined whether the human nucleus accumbens engages such a mechanism by recording electrophysiological activity directly from the accumbens of human patients undergoing deep brain stimulation surgery. Oscillatory activity in the gamma (40–80 Hz) frequency range was synchronized with the phase of simultaneous alpha (8–12 Hz) waves. Further, losing and winning small amounts of money elicited relatively increased gamma oscillation power prior to and following alpha troughs, respectively. Gamma–alpha synchronization may reflect an electrophysiological gating mechanism in the human nucleus accumbens, and the phase differences in gamma–alpha coupling may reflect a reward information coding scheme similar to phase coding.

Electroencephalogram oscillations recorded both within and over the medial frontal cortex have been linked to a range of cognitive functions, including positive and negative feedback processing. Medial frontal oscillatory characteristics during decision making remain largely unknown. Here, we examined oscillatory activity of the human medial frontal cortex recorded while subjects played a competitive decision-making game. Distinct patterns of power and cross-trial phase coherence in multiple frequency bands were observed during different decision-related processes (e.g., feedback anticipation vs. feedback processing). Decision and feedback processing were accompanied by a broadband increase in cross-trial phase coherence at around 220 msec, and dynamic fluctuations in power. Feedback anticipation was accompanied by a shift in the power spectrum from relatively lower (delta and theta) to higher (alpha and beta) power. Power and cross-trial phase coherence were greater following losses compared to wins in theta, alpha, and beta frequency bands, but were greater following wins compared to losses in the delta band. Finally, we found that oscillation power in alpha and beta frequency bands were synchronized with the phase of delta and theta oscillations (“phase–amplitude coupling”). This synchronization differed between losses and wins, suggesting that phase–amplitude coupling might reflect a mechanism of feedback valence coding in the medial frontal cortex. Our findings link medial frontal oscillations to decision making, with relations among activity in different frequency bands suggesting a phase-utilizing coding of feedback valence information.

Human self-consciousness relies on the ability to distinguish between oneself and others. We sought to explore the neural correlates involved in self-other representations by investigating two critical processes: perspective taking and agency. Although recent research has shed light on the neural processes underlying these phenomena, little is known about how they overlap or interact at the neural level. In a two-factorial functional magnetic resonance imaging (fMRI) experiment, participants played a ball-tossing game with two virtual characters (“avatars”). During an active/agency (ACT) task, subjects threw a ball to one of the avatars by pressing a button. During a passive/nonagency (PAS) task, they indicated which of the other avatars threw the ball. Both tasks were performed from a first-person perspective (1PP), in which subjects interacted from their own perspective, and a third-person perspective (3PP), in which subjects interacted from the perspective of an avatar with another location in space. fMRI analyses revealed overlapping activity in medial prefrontal regions associated with representations of one's own perspective and actions (1PP and ACT), and overlapping activity in temporal-occipital, premotor, and inferior frontal, as well as posterior parietal regions associated with representation of others' perspectives and actions (3PP and PAS). These findings provide evidence for distinct neural substrates underlying representations of the self and others and provide support for the idea that the medial prefrontal cortex crucially contributes to a neural basis of the self. The lack of a statistically significant interaction suggests that perspective taking and agency represent independent constituents of self-consciousness.

Theories of human memory have led to conflicting views regarding the relationship between working memory (WM) maintenance and episodic long-term memory (LTM) formation. Here, we tested the prediction that WM maintenance operates in two stages, and that processing during the initial stage of WM maintenance promotes successful LTM formation. Results from a functional magnetic resonance imaging study showed that activity in the dorsolateral prefrontal cortex and hippocampus during the initial stage of WM maintenance was predictive of subsequent LTM performance. In a behavioral experiment, we demonstrated that interfering with processing during the initial stage of WM maintenance impaired LTM formation. These results demonstrate that processing during the initial stage of WM maintenance directly contributes to successful LTM formation, and that this effect is mediated by a network that includes the dorsolateral prefrontal cortex and the hippocampus.