Joshua Brown

The anterior cingulate cortex (ACC) and the related medial wall play a critical role in recruiting cognitive control. Although ACC exhibits selective error and conflict responses, it has been unclear how these develop and become context-specific. With use of a modified stop-signal task, we show from integrated computational neural modeling and neuroimaging studies that ACC learns to predict error likelihood in a given context, even for trials in which there is no error or response conflict. These results support a more general error-likelihood theory of ACC function based on reinforcement learning, of which conflict and error detection are special cases.

The medial prefrontal cortex (mPFC) and especially anterior cingulate cortex is central to higher cognitive function and many clinical disorders, yet its basic function remains in dispute. Various competing theories of mPFC have treated effects of errors, conflict, error likelihood, volatility and reward, using findings from neuroimaging and neurophysiology in humans and monkeys. No single theory has been able to reconcile and account for the variety of findings. Here we show that a simple model based on standard learning rules can simulate and unify an unprecedented range of known effects in mPFC. The model reinterprets many known effects and suggests a new view of mPFC, as a region concerned with learning and predicting the likely outcomes of actions, whether good or bad. Cognitive control at the neural level is then seen as a result of evaluating the probable and actual outcomes of one's actions.

Consensus is emerging that the medial frontal lobe of the brain is involved in monitoring performance, but precisely what is monitored remains unclear. A saccade-countermanding task affords an experimental dissociation of neural signals of error, reinforcement, and conflict. Single-unit activity was monitored in the anterior cingulate cortex of monkeys performing this task. Neurons that signaled errors were found, half of which responded to the omission of earned reinforcement. A further diversity of neurons signaled earned or unexpected reinforcement. No neurons signaled the form of conflict engendered by interruption of saccade preparation produced in this task. These results are consistent with the hypothesis that the anterior cingulate cortex monitors the consequences of actions.

Dopamine and the prefrontal cortex are critical for thought and behaviour. Recently, computational models have tried to elucidate the specific and intricate roles of dopamine in the prefrontal cortex, at the neurophysiological, system and behavioral levels, with varying degrees of success.

Working memory (WM) enables the online maintenance and manipulation of information and is central to intelligent cognitive functioning. Much research has investigated executive processes of WM in order to understand the operations that make WM “work.” However, there is yet little consensus regarding how executive processes of WM are organized. Here, we used quantitative meta-analysis to summarize data from 36 experiments that examined executive processes of WM. Experiments were categorized into 4 component functions central to WM: protecting WM from external distraction (distractor resistance), preventing irrelevant memories from intruding into WM (intrusion resistance), shifting attention within WM (shifting), and updating the contents of WM (updating). Data were also sorted by content (verbal, spatial, object). Meta-analytic results suggested that rather than dissociating into distinct functions, 2 …

Success requires deciding among alternatives, controlling the initiation of movements, and judging the consequences of actions. When alternatives are difficult to distinguish, habitual responses must be overcome, or consequences are uncertain, deliberation is necessary and a supervisory system exerts control over the processes that produce sensory-guided movements. We have investigated these processes by recording neural activity in the frontal lobe of macaque monkeys performing a countermanding task. Distinct neurons in the frontal eye field respond to visual stimuli or control the production of the movements. In the supplementary eye field and anterior cingulate cortex, neurons appear not to control directly movement initiation but instead signal the production of errors, the anticipation and delivery of reinforcement, and the presence of processing conflict. These signals form the core of current models of …

How does the brain learn to balance between reactive and planned behaviors? The basal ganglia (BG) and frontal cortex together allow animals to learn planned behaviors that acquire rewards when prepotent reactive behaviors are insufficient. This paper proposes a new model, called TELOS, to explain how laminar circuitry of the frontal cortex, exemplified by the frontal eye fields, interacts with the BG, thalamus, superior colliculus, and inferotemporal and parietal cortices to learn and perform reactive and planned eye movements. The model is formulated as fourteen computational hypotheses. These specify how strategy priming and action planning (in cortical layers III, Va and VI) are dissociated from movement execution (in layer Vb), how the BG help to choose among and gate competing plans, and how a visual stimulus may serve either as a movement target or as a discriminative cue to move elsewhere. The …

A feature of human cognition is the ability to monitor and adjust one’s own behavior under changing circumstances. A dynamic balance between controlled and rapid responding is needed to adapt to a fluctuating environment. We suggest that cognitive control may include, among other things, two distinct processes. Incongruent stimuli may drive top-down facilitation of task-relevant responses to bias performance toward exploitation vs. exploration. Task or response switches may generally slow responses to bias toward accuracy vs. speed and exploration vs. exploitation. Behavioral results from a task switching study demonstrate these two distinct processes as revealed by higher-order sequential effects. A computational model implements the two conflict-control mechanisms, which allow it to capture many complex and novel sequential effects. Lesion studies with the model demonstrate that the model is unable to …

The stop-signal or countermanding task probes the ability to control action by requiring subjects to withhold a planned movement in response to an infrequent stop signal which they do with variable success depending on the delay of the stop signal. We investigated whether performance of humans and macaque monkeys in a saccade countermanding task was influenced by stimulus and performance history. In spite of idiosyncrasies across subjects several trends were evident in both humans and monkeys. Response time decreased after successive trials with no stop signal. Response time increased after successive trials with a stop signal. However, post-error slowing was not observed. Increased response time was observed mainly or only after cancelled (signal inhibit) trials and not after noncancelled (signal respond) trials. These global trends were based on rapid adjustments of response time in response to …

The recently proposed error-likelihood hypothesis suggests that anterior cingulate cortex (ACC) and surrounding areas will become active in proportion to the perceived likelihood of an error. The hypothesis was originally derived from a computational model prediction. The same computational model now makes a further prediction that ACC will be sensitive not only to predicted error likelihood, but also to the predicted magnitude of the consequences, should an error occur. The product of error likelihood and predicted error consequence magnitude collectively defines the general “expected risk” of a given behavior in a manner analogous but orthogonal to subjective expected utility theory. New fMRI results from an incentive change signal task now replicate the errorlikelihood effect, validate the further predictions of the computational model, and suggest why some segments of the population may fail to …

The medial prefrontal cortex (mPFC) has been the subject of intense interest as a locus of cognitive control. Several computational models have been proposed to account for a range of effects, including error detection, conflict monitoring, error likelihood prediction, and numerous other effects observed with single‐unit neurophysiology, fMRI, and lesion studies. Here, we review the state of computational models of cognitive control and offer a new theoretical synthesis of the mPFC as signaling response–outcome predictions. This new synthesis has two interacting components. The first component learns to predict the various possible outcomes of a planned action, and the second component detects discrepancies between the actual and intended responses; the detected discrepancies in turn update the outcome predictions. This single construct is consistent with a wide array of performance monitoring effects in …

The goal of this study was to determine whether the activity of neurons in the supplementary eye field (SEF) is sufficient to control saccade initiation in macaque monkeys performing a saccade countermanding (stop signal) task. As previously observed, many neurons in the SEF increase the discharge rate before saccade initiation. However, when saccades are canceled in response to a stop signal, effectively no neurons with presaccadic activity display discharge rate modulation early enough to contribute to saccade cancellation. Moreover, SEF neurons do not exhibit a specific threshold discharge rate that could trigger saccade initiation. Yet, we observed more subtle relations between SEF activation and saccade production. The activity of numerous SEF neurons was correlated with response time and varied with sequential adjustments in response latency. Trials in which monkeys canceled or produced a …

The inferior frontal gyrus/anterior insula (IFG/AI) and anterior cingulate cortex (ACC) are key regions involved in risk appraisal during decision making, but accounts of how these regions contribute to decision making under risk remain contested. To help clarify the roles of these and other related regions, we used a modified version of the Balloon Analogue Risk Task (Lejuez et al., Journal of Experimental Psychology: Applied, 8, 75–84, 2002) to distinguish between decision-making and feedback-related processes when participants decided to pursue a gain as the probability of loss increased parametrically. Specifically, we set out to test whether the ACC and IFG/AI regions correspond to loss aversion at the time of decision making in a way that is not confounded with either reward-seeking or infrequency effects. When participants chose to discontinue inflating the balloon (win option), we observed greater …

The lateral frontal cortex (LFC) is thought to represent contextual and rule-based information that allows adaptive behavior according to circumstance. Recent progress has suggested that the representations of the LFC vary along its rostral–caudal axis with more abstract, higher level representations associated with rostral areas of the LFC and more concrete, lower level representations associated with caudal areas of the LFC. Here, we investigated this proposal. Subjects responded to stimuli based upon a nested series of contextual cues stored in working memory (WM) while being scanned with fMRI. Higher level context cues denoted an abstract rule set while lower level context cues provided more concrete information. Using multi-variate pattern analysis (MVPA), we found varying forms of representation along the rostral–caudal axis of the LFC depending on the type of information stored in WM. Rostral areas …

Anterior cingulate and dorsolateral prefrontal cortex (ACC and dlPFC, respectively) are core components of the cognitive control network. Activation of these regions is routinely observed in tasks that involve monitoring the external environment and maintaining information in order to generate appropriate responses. Despite the ubiquity of studies reporting coactivation of these two regions, a consensus on how they interact to support cognitive control has yet to emerge. In this letter, we present a new hypothesis and computational model of ACC and dlPFC. The error representation hypothesis states that multidimensional error signals generated by ACC in response to surprising outcomes are used to train representations of expected error in dlPFC, which are then associated with relevant task stimuli. Error representations maintained in dlPFC are in turn used to modulate predictive activity in ACC in order to generate …