James F. Cavanagh

Prelude to and resolution of an error: EEG phase synchrony reveals cognitive control dynamics during action monitoring

Error-related activity in the medial prefrontal cortex (mPFC) is thought to work in conjunction with lateral prefrontal cortex (lPFC) as a part of an action-monitoring network, where errors signal the need for increased cognitive control. The neural mechanism by which this mPFC–lPFC interaction occurs remains unknown. We hypothesized that transient synchronous oscillations in the theta range reflect a mechanism by which these structures interact. To test this hypothesis, we extracted oscillatory phase and power from current–source–density-transformed electroencephalographic data recorded during a Flanker task. Theta power in the mPFC was diminished on the trial preceding an error and increased immediately after an error, consistent with predictions of an action-monitoring system. These power dynamics appeared to take place over a response-related background of oscillatory theta phase coherence. Theta phase synchronization between FCz (mPFC) and F5/6 (lPFC) sites was robustly increased during error trials. The degree of mPFC–lPFC oscillatory synchronization predicted the degree of mPFC power on error trials, and both of these dynamics predicted the degree of posterror reaction time slowing. Oscillatory dynamics in the theta band may in part underlie a mechanism of communication between networks involved in action monitoring and cognitive control.

Subthalamic nucleus stimulation reverses mediofrontal influence over decision threshold

It takes effort and time to tame ones impulses. Although medial prefrontal cortex (mPFC) is broadly implicated in effortful control over behavior, the subthalamic nucleus (STN) is specifically thought to contribute by acting as a brake on cortico-striatal function during decision conflict, buying time until the right decision can be made. Using the drift diffusion model of decision making, we found that trial-to-trial increases in mPFC activity (EEG theta power, 4–8 Hz) were related to an increased threshold for evidence accumulation (decision threshold) as a function of conflict. Deep brain stimulation of the STN in individuals with Parkinsons disease reversed this relationship, resulting in impulsive choice. In addition, intracranial recordings of the STN area revealed increased activity (2.5–5 Hz) during these same high-conflict decisions. Activity in these slow frequency bands may reflect a neural substrate for cortico–basal ganglia communication regulating decision processes.

Theta lingua franca: A common mid-frontal substrate for action monitoring processes

We present evidence that a multitude of mid-frontal event-related potential (ERP) components partially reflect a common theta band oscillatory process. Specifically, mid-frontal ERP components in the N2 time range and error-related negativity time range are parsimoniously characterized as reflections of theta band activities. Forty participants completed three different tasks with varying stimulus-response demands. Permutation tests were used to identify the dominant time-frequency responses of stimulus- and response-locked conditions as well as the enhanced responses to novelty, conflict, punishment, and error. A dominant theta band feature was found in all conditions, and both ERP component amplitudes and theta power measures were similarly modulated by novelty, conflict, punishment, and error. The findings support the hypothesis that generic and reactive medial prefrontal cortex processes are parsimoniously reflected by theta band activities.

Frontal theta links prediction errors to behavioral adaptation in reinforcement learning

Investigations into action monitoring have consistently detailed a frontocentral voltage deflection in the event-related potential (ERP) following the presentation of negatively valenced feedback, sometimes termed the feedback-related negativity (FRN). The FRN has been proposed to reflect a neural response to prediction errors during reinforcement learning, yet the single-trial relationship between neural activity and the quanta of expectation violation remains untested. Although ERP methods are not well suited to single-trial analyses, the FRN has been associated with theta band oscillatory perturbations in the medial prefrontal cortex. Mediofrontal theta oscillations have been previously associated with expectation violation and behavioral adaptation and are well suited to single-trial analysis. Here, we recorded EEG activity during a probabilistic reinforcement learning task and fit the performance data to an abstract computational model (Q-learning) for calculation of single-trial reward prediction errors. Single-trial theta oscillatory activities following feedback were investigated within the context of expectation (prediction error) and adaptation (subsequent reaction time change). Results indicate that interactive medial and lateral frontal theta activities reflect the degree of negative and positive reward prediction error in the service of behavioral adaptation. These different brain areas use prediction error calculations for different behavioral adaptations, with medial frontal theta reflecting the utilization of prediction errors for reaction time slowing (specifically following errors), but lateral frontal theta reflecting prediction errors leading to working memory-related reaction time speeding for the correct choice.

Frontal midline theta reflects anxiety and cognitive control: meta-analytic evidence.

Evidence from imaging and anatomical studies suggests that the midcingulate cortex (MCC) is a dynamic hub lying at the interface of affect and cognition. In particular, this neural system appears to integrate information about conflict and punishment in order to optimize behavior in the face of action-outcome uncertainty. In a series of meta-analyses, we show how recent human electrophysiological research provides compelling evidence that frontal-midline theta signals reflecting MCC activity are moderated by anxiety and predict adaptive behavioral adjustments. These findings underscore the importance of frontal theta activity to a broad spectrum of control operations. We argue that frontal-midline theta provides a neurophysiologically plausible mechanism for optimally adjusting behavior to uncertainty, a hallmark of situations that elicit anxiety and demand cognitive control. These observations compel a new perspective on the mechanisms guiding motivated learning and behavior and provide a framework for understanding the role of the MCC in temperament and psychopathology.

Single-Trial Regression Elucidates the Role of Prefrontal Theta Oscillations in Response Conflict

In most cognitive neuroscience experiments there are many behavioral and experimental dynamics, and many indices of brain activity, that vary from trial to trial. For example, in studies of response conflict, conflict is usually treated as a binary variable (i.e., response conflict exists or does not in any given trial), whereas some evidence and intuition suggests that conflict may vary in intensity from trial to trial. Here we demonstrate that single-trial multiple regression of time–frequency electrophysiological activity reveals neural mechanisms of cognitive control that are not apparent in cross-trial averages. We also introduce a novel extension to oscillation phase coherence and synchronization analyses, based on “weighted” phase modulation, that has advantages over standard coherence measures in terms of linking electrophysiological dynamics to trial-varying behavior and experimental variables. After replicating previous response conflict findings using trial-averaged data, we extend these findings using single-trial analytic methods to provide novel evidence for the role of medial frontal–lateral prefrontal theta-band synchronization in conflict-induced response time dynamics, including a role for lateral prefrontal theta-band activity in biasing response times according to perceptual conflict. Given that these methods shed new light on the prefrontal mechanisms of response conflict, they are also likely to be useful for investigating other neurocognitive processes.

Common medial frontal mechanisms of adaptive control in humans and rodents

In this report we describe how common brain networks within the medial frontal cortex (MFC) facilitate adaptive behavioral control in rodents and humans. We demonstrate that after errors, low-frequency oscillations below 12 Hz are modulated over the midfrontal cortex in humans and within the prelimbic and anterior cingulate regions of the MFC in rats. These oscillations were phase locked between the MFC and motor areas in both rats and humans. In rats, single neurons that encoded prior behavioral outcomes were phase coherent with low-frequency field oscillations, particularly after errors. Inactivating the medial frontal regions in rats led to impaired behavioral adjustments after errors, eliminated the differential expression of low-frequency oscillations after errors and increased low-frequency spike-field coupling within the motor cortex. Our results describe a new mechanism for behavioral adaptation through low-frequency oscillations and elucidate how medial frontal networks synchronize brain activity to guide performance.

Frontal Theta Reflects Uncertainty and Unexpectedness during Exploration and Exploitation

In order to understand the exploitation/exploration trade-off in reinforcement learning, previous theoretical and empirical accounts have suggested that increased uncertainty may precede the decision to explore an alternative option. To date, the neural mechanisms that support the strategic application of uncertainty-driven exploration remain underspecified. In this study, electroencephalography (EEG) was used to assess trial-to-trial dynamics relevant to exploration and exploitation. Theta-band activities over middle and lateral frontal areas have previously been implicated in EEG studies of reinforcement learning and strategic control. It was hypothesized that these areas may interact during top-down strategic behavioral control involved in exploratory choices. Here, we used a dynamic reward-learning task and an associated mathematical model that predicted individual response times. This reinforcement-learning model generated value-based prediction errors and trial-by-trial estimates of exploration as a function of uncertainty. Mid-frontal theta power correlated with unsigned prediction error, although negative prediction errors had greater power overall. Trial-to-trial variations in response-locked frontal theta were linearly related to relative uncertainty and were larger in individuals who used uncertainty to guide exploration. This finding suggests that theta-band activities reflect prefrontal-directed strategic control during exploratory choices.

Task-related dissociation in ERN amplitude as a function of obsessive-compulsive symptoms

Hyperactive cortico-striatal circuits including the anterior cingulate cortex (ACC) have been implicated to underlie obtrusive thoughts and repetitive behaviors in obsessive-compulsive disorder (OCD). Larger error-related negativities (ERNs) in OCD patients during simple flanker tasks have been proposed to reflect an amplified error signal in these hyperactive circuits. Such amplified error signals typically are associated with an adaptive change in response, yet in OCD these same repetitive responses persist to the point of distress and impairment. In contrast to this repetitive character of OC behavior, larger ERN amplitudes have been linked to better avoidance learning in reinforcement learning tasks. Study I thus investigated if OC symptomatology in non-patients predicted an enhanced ERN after suboptimal choices in a probabilistic learning task. Absent any behavioral differences, higher OC symptoms predicted smaller ERNs. Study II replicated this effect in an independent sample while also replicating findings of a larger ERN in a flanker task. There were no relevant behavioral differences in reinforcement learning or error monitoring as a function of symptom score. These findings implicate different, yet overlapping neural mechanisms underlying the negative deflection in the ERP following the execution of an erroneous motor response and the one following a suboptimal choice in a reinforcement learning paradigm. OC symptomatology may be dissociated in these neural systems, with hypoactivity in a system that enables learning to avoid maladaptive choices, and hyperactivity in another system that enables the same behavior to be repeated when it was assessed as not quite good enough the first time.

fMRI and EEG predictors of dynamic decision parameters during human reinforcement learning.

What are the neural dynamics of choice processes during reinforcement learning? Two largely separate literatures have examined dynamics of reinforcement learning (RL) as a function of experience but assuming a static choice process, or conversely, the dynamics of choice processes in decision making but based on static decision values. Here we show that human choice processes during RL are well described by a drift diffusion model (DDM) of decision making in which the learned trial-by-trial reward values are sequentially sampled, with a choice made when the value signal crosses a decision threshold. Moreover, simultaneous fMRI and EEG recordings revealed that this decision threshold is not fixed across trials but varies as a function of activity in the subthalamic nucleus (STN) and is further modulated by trial-by-trial measures of decision conflict and activity in the dorsomedial frontal cortex (pre-SMA BOLD and mediofrontal theta in EEG). These findings provide converging multimodal evidence for a model in which decision threshold in reward-based tasks is adjusted as a function of communication from pre-SMA to STN when choices differ subtly in reward values, allowing more time to choose the statistically more rewarding option.