Functional heterogeneity of conflict, error, task-switching, and unexpectedness effects within medial prefrontal cortex

Neural mechanisms underpinning metacognitive shifts driven by non-informative predictions

Humans constantly make predictions and such predictions allow us to prepare for future events. Yet, such benefits may come with drawbacks as premature predictions may potentially bias subsequent judgments. Here we examined how prediction influences our perceptual decisions and subsequent confidence judgments, on scenarios where the predictions were arbitrary and independent of the identity of the upcoming stimuli. We defined them as invalid and non-informative predictions. Behavioral results showed that, such non-informative predictions biased perceptual decisions in favor of the predicted choice, and such prediction-induced perceptual bias further increased the metacognitive efficiency. The functional MRI results showed that activities in the medial prefrontal cortex (mPFC) and subgenual anterior cingulate cortex (sgACC) encoded the response consistency between predictions and perceptual decisions. Activity in mPFC predicted the strength of this congruency bias across individuals. Moreover, the parametric encoding of confidence in putamen was modulated by prediction-choice consistency, such that activity in putamen was negatively correlated with confidence rating after inconsistent responses. These findings suggest that predictions, while made arbitrarily, orchestrate the neural representations of choice and confidence judgment.

Anterior cingulate cortex provides the neural substrates for feedback-driven iteration of decision and value representation

Adjusting decision-making under uncertain and dynamic situations is the hallmark of intelligence. It requires a system capable of converting feedback information to renew the internal value. The anterior cingulate cortex (ACC) involves in error and reward events that prompt switching or maintenance of current decision strategies. However, it is unclear whether and how the changes of stimulus-action mapping during behavioral adaptation are encoded, nor how such computation drives decision adaptation. Here, we tracked ACC activity in male mice performing go/no-go auditory discrimination tasks with manipulated stimulus-reward contingencies. Individual ACC neurons integrate the outcome information to the value representation in the next-run trials. Dynamic recruitment of them determines the learning rate of error-guided value iteration and decision adaptation, forming a non-linear feedback-driven updating system to secure the appropriate decision switch. Optogenetically suppressing ACC significantly slowed down feedback-driven decision switching without interfering with the execution of the established strategy.

Functional diversity of dopamine axons in prefrontal cortex during classical conditioning

Midbrain dopamine neurons impact neural processing in the prefrontal cortex (PFC) through mesocortical projections. However, the signals conveyed by dopamine projections to the PFC remain unclear, particularly at the single-axon level. Here, we investigated dopaminergic axonal activity in the medial PFC (mPFC) during reward and aversive processing. By optimizing microprism-mediated two-photon calcium imaging of dopamine axon terminals, we found diverse activity in dopamine axons responsive to both reward and aversive stimuli. Some axons exhibited a preference for reward, while others favored aversive stimuli, and there was a strong bias for the latter at the population level. Long-term longitudinal imaging revealed that the preference was maintained in reward- and aversive-preferring axons throughout classical conditioning in which rewarding and aversive stimuli were paired with preceding auditory cues. However, as mice learned to discriminate reward or aversive cues, a cue activity preference gradually developed only in aversive-preferring axons. We inferred the trial-by-trial cue discrimination based on machine learning using anticipatory licking or facial expressions, and found that successful discrimination was accompanied by sharper selectivity for the aversive cue in aversive-preferring axons. Our findings indicate that a group of mesocortical dopamine axons encodes aversive-related signals, which are modulated by both classical conditioning across days and trial-by-trial discrimination within a day.

Interruption Value Type and Source Matter in Different Phases of an Interruption Process: Emotional/Cognitive Impact and Neural Evidence

OBJECTIVE

To examine the effect of interruption value type (utilitarian, hedonic) and source (external, internal) in different phases of an interruption process.

BACKGROUND

Prior studies on interruption mostly focused on the cognitive outcomes of utilitarian interruptions. Hedonic interruptions are common in life; however, they are not sufficiently explored through research. Hedonic value is closely associated with emotional experiences, and, in turn, influences behaviors. Moreover, the way the effect of values is moderated by interruptions initiated by intrinsic motives is worth exploring.

METHOD

A 2 × 2 mixed design experiment was conducted with 48 participants who were asked to respond to instant messages during the writing task. The interruption value was induced by work or non-work tasks. The interruption source was manipulated by providing an alert. Functional near-infrared spectroscopy, behavioral data, and subjective measurements were collected and analyzed.

RESULTS

Hedonic interruptions increased emotional valence, while utilitarian interruptions decreased it. These effects were strengthened by internal interruptions. The effect of interruption value type on work exhaustion was also moderated by the source. Interruption value type and source influenced the attention allocation before an interruption occurred. Hedonic interruptions led to longer resumption lags, whereas utilitarian interruptions required longer interruption durations. Internal interruptions led to improved performance in the resumed task.

CONCLUSION

Interruption source modulate the effect of interruption value type, especially on emotional experience and attention allocation before an interruption occurs.

APPLICATION

Self-initiated hedonic interruptions have emotional benefits, while alerts for utilitarian interruptions will improve attention on the main task before interruptions.

Success versus failure in cognitive control: Meta-analytic evidence from neuroimaging studies on error processing

Brain mechanisms of error processing have often been investigated using response interference tasks and focusing on the posterior medial frontal cortex, which is also implicated in resolving response conflict in general. Thereby, the role other brain regions may play has remained undervalued. Here, activation likelihood estimation meta-analyses were used to synthesize the neuroimaging literature on brain activity related to committing errors versus responding successfully in interference tasks and to test for commonalities and differences. The salience network and the temporoparietal junction were commonly recruited irrespective of whether responses were correct or incorrect, pointing towards a general involvement in coping with situations that call for increased cognitive control. The dorsal posterior cingulate cortex, posterior thalamus, and left superior frontal gyrus showed error-specific convergence, which underscores their consistent involvement when performance goals are not met. In contrast, successful responding revealed stronger convergence in the dorsal attention network and lateral prefrontal regions. Underrecruiting these regions in error trials may reflect failures in activating the task-appropriate stimulus-response contingencies necessary for successful response execution.

The dorsomedial prefrontal cortex represents subjective value across effort-based and risky decision-making

Decisions that require taking effort costs into account are ubiquitous in real life. The neural common currency theory hypothesizes that a particular neural network integrates different costs (e.g., risk) and rewards into a common scale to facilitate value comparison. Although there has been a surge of interest in the computational and neural basis of effort-related value integration, it is still under debate if effort-based decision-making relies on a domain-general valuation network as implicated in the neural common currency theory. Therefore, we comprehensively compared effort-based and risky decision-making using a combination of computational modeling, univariate and multivariate fMRI analyses, and data from two independent studies. We found that effort-based decision-making can be best described by a power discounting model that accounts for both the discounting rate and effort sensitivity. At the neural level, multivariate decoding analyses indicated that the neural patterns of the dorsomedial prefrontal cortex (dmPFC) represented subjective value across different decision-making tasks including either effort or risk costs, although univariate signals were more diverse. These findings suggest that multivariate dmPFC patterns play a critical role in computing subjective value in a task-independent manner and thus extend the scope of the neural common currency theory.

Success versus failure in cognitive control: meta-analytic evidence from neuroimaging studies on error processing

Brain mechanisms of error processing have often been investigated using response interference tasks and focusing on the posterior medial frontal cortex, which is also implicated in resolving response conflict in general. Thereby, the role other brain regions may play has remained undervalued. Here, activation likelihood estimation meta-analyses were used to synthesize the neuroimaging literature on brain activity related to committing errors versus responding successfully in interference tasks and to test for commonalities and differences. The salience network and the temporoparietal junction were commonly recruited irrespective of whether responses were correct or incorrect, pointing towards a general involvement in coping with situations that call for increased cognitive control. The dorsal posterior cingulate cortex, posterior thalamus, and left superior frontal gyrus showed error-specific convergence, which underscores their consistent involvement when performance goals are not met. In contrast, successful responding revealed stronger convergence in the dorsal attention network and lateral prefrontal regions. Underrecruiting these regions in error trials may reflect failures in activating the task-appropriate stimulus-response contingencies necessary for successful response execution.

Two modes of midfrontal theta suggest a role in conflict and error processing

Midfrontal theta increases during scenarios when conflicts are successfully resolved. Often considered a generic signal of cognitive control, its temporal nature has hardly been investigated. Using advanced spatiotemporal techniques, we uncover that midfrontal theta occurs as a transient oscillation or "event" at single trials with their timing reflecting computationally distinct modes. Single-trial analyses of electrophysiological data from participants performing the Flanker (N = 24) and Simon task (N = 15) were used to probe the relationship between theta and metrics of stimulus-response conflict. We specifically investigated "partial errors", in which a small burst of muscle activity in the incorrect response effector occurred, quickly followed by a correction. We found that transient theta events in single trials could be categorized into two distinct theta modes based on their relative timing to different task events. Theta events from the first mode occurred briefly after the task stimulus and might reflect conflict-related processing of the stimulus. In contrast, theta events from the second mode were more likely to occur around the time partial errors were committed, suggesting they were elicited by a potential upcoming error. Importantly, in trials in which a full error was committed, this "error-related theta" occurred too late with respect to the onset of the erroneous muscle response, supporting the role of theta also in error correction. We conclude that different modes of transient midfrontal theta can be adopted in single trials not only to process stimulus-response conflict, but also to correct erroneous responses.

The first year in formal schooling improves working memory and academic abilities

Neurocognition and academic abilities during the period of 4 and 7 years of age are impacted by both the transition from kindergarten to primary school and age-related developmental processes. Here, we used a school cut-off design to tease apart the impact of formal schooling from age, on working memory (WM) function, vocabulary, and numeracy scores. We compared two groups of children with similar age, across two years: first-graders (FG), who were enrolled into primary school the year that they became eligible and kindergarteners (KG), who were deferred school entry until the following year. All children completed a change detection task while brain activation was recorded using portable functional near-infrared spectroscopy, a vocabulary assessment, and a numeracy screener. Our results revealed that FG children showed greater improvement in WM performance and greater engagement of a left-lateralized fronto-parietal network compared to KG children. Further, they also showed higher gains in vocabulary and non-symbolic numeracy scores. This improvement in vocabulary and non-symbolic numeracy scores following a year in primary school was predicted by WM function. Our findings contribute to a growing body of literature examining neurocognitive and academic benefits conferred to children following exposure to formal schooling.

Neural circuits underlying language control and modality control in bilinguals: An fMRI study

Human communication not only involves the need to switch between the modalities of speaking and listening, but for bilinguals, it can also involve switching between languages. It is unknown as to whether modality and language switching share underlying control mechanisms or whether one type of switching affects control processes involved in the other. The present study uses behavioral and fMRI measures to examine neural circuits of control during communicative situations that required Chinese-English bilinguals to switch between modalities and their two languages according to associated color cues. The results showed that for both language and modality control, similar brain regions were recruited during speech production and comprehension. For modality control, the specific control processes partly depended on the corresponding modality. Finally, switching between modalities appears to exert more influence on language control in production compared to comprehension. These findings offer a first detailed characterization of the neural bases involved in control mechanisms in bilingual communication.

Compulsive alcohol drinking in rodents is associated with altered representations of behavioral control and seeking in dorsal medial prefrontal cortex

A key feature of compulsive alcohol drinking is continuing to drink despite negative consequences. To examine the changes in neural activity that underlie this behavior, compulsive alcohol drinking was assessed in a validated rodent model of heritable risk for excessive drinking (alcohol preferring (P) rats). Neural activity was measured in dorsal medial prefrontal cortex (dmPFC-a brain region involved in maladaptive decision-making) and assessed via change point analyses and novel principal component analyses. Neural population representations of specific decision-making variables were measured to determine how they were altered in animals that drink alcohol compulsively. Compulsive animals showed weakened representations of behavioral control signals, but strengthened representations of alcohol seeking-related signals. Finally, chemogenetic-based excitation of dmPFC prevented escalation of compulsive alcohol drinking. Collectively, these data indicate that compulsive alcohol drinking in rats is associated with alterations in dmPFC neural activity that underlie diminished behavioral control and enhanced seeking.

An Exploratory Study on Resting-State Functional Connectivity in Individuals with Disorganized Attachment: Evidence for Key Regions in Amygdala and Hippocampus

Studies comparing organized (O) and unresolved/disorganized (UD) attachment have consistently shown structural and functional brain abnormalities, although whether and how attachment patterns may affect resting state functional connectivity (RSFC) is still little characterized. Here, we investigated RSFC of temporal and limbic regions of interest for UD attachment. Participants’ attachment was classified via the Adult Attachment Interview, and all participants underwent clinical assessment. Functional magnetic resonance imaging data were collected from 11 UD individuals and seven matched O participants during rest. A seed-to-voxel analysis was performed, including the anterior and the posterior cingulate cortex, the bilateral insula, amygdala and hippocampus as seed regions. No group differences in the clinical scales emerged. Compared to O, the UD group showed lower RSFC between the left amygdala and the left cerebellum (lobules VIII), and lower functional coupling between the right hippocampus and the posterior portion of the right middle temporal gyrus. Moreover, UD participants showed higher RSFC between the right amygdala and the anterior cingulate cortex. Our findings suggest RSFC alterations in regions associated with encoding of salient events, emotion processing, memories retrieval and self-referential processing in UD participants, highlighting the potential role of attachment experiences in shaping brain abnormalities also in non-clinical UD individuals.

Neural correlates of interoceptive accuracy: Beyond cardioception

Interoceptive accuracy (IAc), the precision with which one assesses the signals arising from one's own body, is receiving increasing attention in the literature. IAc has mainly been approached as an individual trait and has been investigated through the cardiac modality using mostly non-ecological methods. Such studies consensually designate the anterior insular cortex as the main brain correlate of IAc. However, there is a lack of brain imaging studies investigating IAc in a broader and more ecological way. Here, we used a novel ecological task in which participants monitored their general bodily reactions to external events and investigated brain regions subtending intraindividual (i.e. trial-by-trial) variations of IAc. At each trial, participants had to rate the intensity of their bodily reactions to an emotional picture. We recorded participants' skin conductance response (SCR) to the picture as an indicator of actual physiological response intensity. We fitted a functional magnetic resonance imaging (fMRI) model using, as regressors, the SCR value, the rating and the product of the two (as a proxy of participants' IAc) obtained trial per trial. We observed that activity in the dorsomedial prefrontal cortex (dmPFC) increased when individuals' IAc decreased. This result reveals general mechanism of error processing in intraindividual variations of IAc, which are unspecific to interoception. Our result has a practical impact in the clinical domain. Namely, it supports the predictive coding framework whereby IAc deficits may reflect impairments in processing a mismatch between actual interoceptive signals and predictions.

The Error-Related Negativity Predicts Self-Control Failures in Daily Life

Adaptive behavior critically depends on performance monitoring (PM), the ability to monitor action outcomes and the need to adapt behavior. PM-related brain activity has been linked to guiding decisions about whether action adaptation is warranted. The present study examined whether PM-related brain activity in a flanker task, as measured by electroencephalography (EEG), was associated with adaptive behavior in daily life. Specifically, we were interested in the employment of self-control, operationalized as self-control failures (SCFs), and measured using ecological momentary assessment. Analyses were conducted using an adaptive elastic net regression to predict SCFs from EEG in a sample of 131 participants. The model was fit using within-subject averaged response-locked EEG activity at each electrode and time point within an epoch surrounding the response. We found that higher amplitudes of the error-related negativity (ERN) were related to fewer SCFs. This suggests that lower error-related activity may relate to lower recruitment of interventive self-control in daily life. Altered cognitive control processes, like PM, have been proposed as underlying mechanisms for various mental disorders. Understanding how alterations in PM relate to regulatory control might therefore aid in delineating how these alterations contribute to different psychopathologies.

Stress reduces both model-based and model-free neural computations during flexible learning

Stressful events are thought to impair the flexible adaptation to changing environments, yet the underlying mechanisms are largely unknown. Here, we combined computational modeling and functional magnetic resonance imaging (fMRI) to elucidate the neurocomputational mechanisms underlying stress-induced deficits in flexible learning. Healthy participants underwent a stress or control manipulation before they completed, in the MRI scanner, a Markov decision task, frequently used to dissociate model-based and model-free contributions to choice, with repeated reversals of reward contingencies. Our results showed that stress attenuated the behavioral sensitivity to reversals in reward contingencies. Computational modeling further indicated that stress specifically affected the use of value computations for subsequent action selection. This reduced application of learned information on subsequent behavior was paralleled by a stress-induced reduction in inferolateral prefrontal cortex activity during model-free computations. For model-based learning, stress decreased specifically posterior, but not anterior, hippocampal activity, pointing to a functional segregation of model-based processing and its modulation by stress along the hippocampal longitudinal axis. Our findings shed light on the mechanisms underlying deficits in flexible learning under stress and indicate that, in highly dynamic environments, stress may hamper both model-based and model-free contributions to adaptive behavior.

Movement errors during skilled motor performance engage distinct prediction error mechanisms

The brain detects deviations from intended behaviors by estimating the mismatch between predicted and actual outcomes. Axiomatic to these computations are salience and valence prediction error signals, which alert the brain to the occurrence and value of unexpected events. Despite the theoretical assertion of these prediction error signals, it is unknown whether and how brain mechanisms underlying their computations support error processing during skilled motor behavior. Here we demonstrate, with functional magnetic resonance imaging, that internal detection, i.e., without externally-provided feedback, of self-generated movement errors evokes instantaneous activity increases within the salience network and delayed lingering decreases within the nucleus accumbens - a key structure in the reward valuation pathway. A widespread suppression within the sensorimotor network was also observed. Our findings suggest that neural computations of salience and valence prediction errors during skilled motor behaviors operate on different time-scales and, therefore, may contribute differentially to immediate and longer-term adaptive processes.

Network Localization of Executive Function Deficits in Patients with Focal Thalamic Lesions

The human thalamus has been suggested to be involved in executive function, based on animal studies and correlational evidence from functional neuroimaging in humans. Human lesion studies, examining behavioral deficits associated with focal brain injuries, can directly test the necessity of the human thalamus for executive function. The goal of our study was to determine the specific lesion location within the thalamus as well as the potential disruption of specific thalamocortical functional networks, related to executive dysfunction. We assessed executive function in 15 patients with focal thalamic lesions and 34 comparison patients with lesions that spared the thalamus. We found that patients with mediodorsal thalamic lesions exhibited more severe impairment in executive function when compared to both patients with thalamic lesions that spared the mediodorsal nucleus and to comparison patients with lesions outside the thalamus. Furthermore, we employed a lesion network mapping approach to map cortical regions that show strong functional connectivity with the lesioned thalamic subregions in the normative functional connectome. We found that thalamic lesion sites associated with more severe deficits in executive function showed stronger functional connectivity with ACC, dorsomedial PFC, and frontoparietal network, compared to thalamic lesions not associated with executive dysfunction. These are brain regions and functional networks whose dysfunction could contribute to impaired executive functioning. In aggregate, our findings provide new evidence that delineates a thalamocortical network for executive function.

Single Neurons in Anterior Cingulate Cortex Signal the Need to Change Action During Performance of a Stop-change Task that Induces Response Competition

Several human imaging studies have suggested that anterior cingulate cortex (ACC) is highly active when participants receive competing inputs, and that these signals may be important for influencing the downstream planning of actions. Despite increasing evidence from several neuroimaging studies, no study has examined ACC activity at the level of the single neuron in rodents performing similar tasks. To fill this gap, we recorded from single neurons in ACC while rats performed a stop-change task. We found higher firing on trials with competing inputs (STOP trials), and that firing rates were positively correlated with accuracy and movement speed, suggesting that when ACC was engaged, rats tended to slow down and perform better. Finally, firing was the strongest when STOP trials were preceded by GO trials and was reduced when rats adapted their behavior on trials subsequent to a STOP trial. These data provide the first evidence that activity of single neurons in ACC is elevated when 2 responses are in competition with each other when there is a need to change the course of action to obtain reward.

The tenacious brain: How the anterior mid-cingulate contributes to achieving goals

Tenacity-persistence in the face of challenge-has received increasing attention, particularly because it contributes to better academic achievement, career opportunities and health outcomes. We review evidence from non-human primate neuroanatomy and structural and functional neuroimaging in humans suggesting that the anterior mid cingulate cortex (aMCC) is an important network hub in the brain that performs the cost/benefit computations necessary for tenacity. Specifically, we propose that its position as a structural and functional hub allows the aMCC to integrate signals from diverse brain systems to predict energy requirements that are needed for attention allocation, encoding of new information, and physical movement, all in the service of goal attainment. We review and integrate research findings from studies of attention, reward, memory, affect, multimodal sensory integration, and motor control to support this hypothesis. We close by discussing the implications of our framework for educational achievement, exercise and eating disorders, successful aging, and neuropsychiatric disorders such as depression and dementia.

Common and distinct neural correlates of dual-tasking and task-switching: a meta-analytic review and a neuro-cognitive processing model of human multitasking

Although there are well-known limitations of the human cognitive system in performing two tasks simultaneously (dual-tasking) or alternatingly (task-switching), the question for a common vs. distinct neural basis of these multitasking limitations is still open. We performed two Activation Likelihood Estimation meta-analyses of neuroimaging studies on dual-tasking or task-switching and tested for commonalities and differences in the brain regions associated with either domain. We found a common core network related to multitasking comprising bilateral intraparietal sulcus (IPS), left dorsal premotor cortex (dPMC), and right anterior insula. Meta-analytic contrasts revealed eight fronto-parietal clusters more consistently activated in dual-tasking (bilateral frontal operculum, dPMC, and anterior IPS, left inferior frontal sulcus and left inferior frontal gyrus) and, conversely, four clusters (left inferior frontal junction, posterior IPS, and precuneus as well as frontomedial cortex) more consistently activated in task-switching. Together with sub-analyses of preparation effects in task-switching, our results argue against purely passive structural processing limitations in multitasking. Based on these findings and drawing on current theorizing, we present a neuro-cognitive processing model of multitasking.

Differential dysfunctions related to alcohol and cannabis use disorder symptoms in reward and error-processing neuro-circuitries in adolescents

Alcohol and cannabis are two of the most commonly used substances by adolescents and are associated with adverse medical and psychiatric outcomes. These adverse psychiatric outcomes may reflect the negative impact of alcohol and/or cannabis abuse on neural systems mediating reward and/or error detection. However, work indicative of this has mostly been conducted in adults with Alcohol and/or Cannabis Use Disorder (i.e., AUD and CUD), with relatively little work in adolescent patients. Furthermore, of the work that has been conducted in adolescents, groups were based on categorical diagnoses of AUD and/or CUD, so the relationship between AUD and/or CUD symptom severity in adolescents and neural dysfunction is unclear. We used a Monetary Incentive Delay (MID) task to examine the relationship between AUDIT and/or CUDIT scores and functional integrity of neuro-circuitries mediating reward processing and error detection within 150 adolescents. Our findings indicate that AUDIT score is negatively related to activity in reward processing neuro-circuitry in adolescents. However, CUDIT score is negatively related to activity in brain regions involved in error detection. Each of these relationships reflected a medium effect size (Partial-η2 0.09-0.14). These data suggest differential impacts of AUD and CUD on reward versus error detection neuro-circuitries within the adolescent brain.

Context-dependent modulation of cognitive control involves different temporal profiles of fronto-parietal activity

To efficiently deal with quickly changing task demands, we often need to organize our behaviour on different time scales. For example, to ignore irrelevant and select relevant information, cognitive control might be applied in reactive (short time scale) or proactive (long time scale) mode. These two control modes play a pivotal role in cognitive-neuroscientific theorizing but the temporal dissociation of the underlying neural mechanisms is not well established empirically. In this fMRI study, a cognitive control task was administered in contexts with mainly congruent (MC) and mainly incongruent (MI) trials to induce reactive and proactive control, respectively. Based on behavioural profiles, we expected cognitive control in the MC context to be characterized by transient activity (measured on-trial) in task-relevant areas. In the MI context, cognitive control was expected to be reflected in sustained activity (measured in the intertrial interval) in similar or different areas. Results show that in the MC context, on-trial transient activity (incongruent - congruent trials) was increased in fronto-parietal areas, compared to the MI context. These areas included dorsolateral prefrontal cortex (dlPFC) and intraparietal sulcus (IPS). In the MI context, sustained activity in similar fronto-parietal areas during the intertrial interval was increased, compared to the MC context. These results illuminate how context-dependent reactive and proactive control subtend the same brain areas but operate on different time scales.

Beta and Theta Oscillations Differentially Support Free Versus Forced Control over Multiple-Target Search

Many important situations require human observers to simultaneously search for more than one object. Despite a long history of research into visual search, the behavioral and neural mechanisms associated with multiple-target search are poorly understood. Here we test the novel theory that the efficiency of looking for multiple targets critically depends on the mode of cognitive control the environment affords to the observer. We used an innovative combination of electroencephalogram (EEG) and eye tracking while participants searched for two targets, within two different contexts: either both targets were present in the search display and observers were free to prioritize either one of them, thus enabling proactive control over selection; or only one of the two targets would be present in each search display, which requires reactive control to reconfigure selection when the wrong target has been prioritized. During proactive control, both univariate and multivariate signals of beta-band (15-35 Hz) power suppression before display onset predicted switches between target selections. This signal originated over midfrontal and sensorimotor regions and has previously been associated with endogenous state changes. In contrast, imposed target selections requiring reactive control elicited prefrontal power enhancements in the delta/theta band (2-8 Hz), but only after display onset. This signal predicted individual differences in associated oculomotor switch costs, reflecting reactive reconfiguration of target selection. The results provide compelling evidence that multiple target representations are differentially prioritized during visual search, and for the first time reveal distinct neural mechanisms underlying proactive and reactive control over multiple-target search.SIGNIFICANCE STATEMENT Searching for more than one object in complex visual scenes can be detrimental for search performance. Although perhaps annoying in daily life, this can have severe consequences in professional settings such as medical and security screening. Previous research has not yet resolved whether multiple-target search involves changing priorities in what people attend to, and how such changes are controlled. We approached these questions by concurrently measuring cortical activity and eye movements using EEG and eye tracking while observers searched for multiple possible targets. Our findings provide the first unequivocal support for the existence of two modes of control during multiple-target search, which are expressed in qualitatively distinct time-frequency signatures of the EEG both before and after visual selection.

Neural Evidence of Hierarchical Cognitive Control during Haptic Processing: An fMRI Study

Interacting with our immediate surroundings requires constant manipulation of objects. Dexterous manipulation depends on comparison between actual and predicted sensory input, with these predictions calculated by means of lower- and higher-order corollary discharge signals. However, there is still scarce knowledge about the hierarchy in the neural architecture supporting haptic monitoring during manipulation. The present study aimed to assess this issue focusing on the cross talk between lower-order sensory and higher-order associative regions. We used functional magnetic resonance imaging in humans during a haptic discrimination task in which participants had to judge whether a touched shape or texture corresponded to an expected stimulus whose name was previously presented. Specialized haptic regions identified with an independent localizer task did not differ between expected and unexpected conditions, suggesting their lack of involvement in tactile monitoring. When presented stimuli did not match previous expectations, the left supramarginal gyrus (SMG), middle temporal, and medial prefrontal cortices were activated regardless of the nature of the haptic mismatch (shape/texture). The left primary somatosensory area (SI) responded differently to unexpected shapes and textures in line with a specialized detection of haptic mismatch. Importantly, connectivity analyses revealed that the left SMG and SI were more functionally coupled during unexpected trials, emphasizing their interaction. The results point for the first time to a hierarchical organization in the neural substrates underlying haptic monitoring during manipulation with the SMG as a higher-order hub comparing actual and predicted somatosensory input, and SI as a lower-order site involved in the detection of more specialized haptic mismatch.

Motivation in the Service of Allostasis: The Role of anterior Mid Cingulate Cortex

In this article, we suggest that motivation serves to anticipate the energy of the body and meet those needs before they arise, called allostasis. We describe motivation as the output of energy computations that include estimates about future energy/metabolic needs and the value of effort required for potential behaviors (i.e., whether the cost of effort is worthwhile). We bring neuroscience evidence to bear to support this hypothesis. We outline a system of brain networks that have been shown to be important for motivation, and focus in on one hub in this network, the anterior mid-cingulate cortex (aMCC), and discuss its importance for establishing motivation in the service of allostasis. We present evidence that the aMCC, positioned at the intersection of multiple brain networks, is wired to integrate signals relating to allostasis with its sensory consequences, termed interoception, as well as with cognitive control processes, sensory and motor functions. This integration guides the nervous system towards the optimal effort required to achieve a desired goal. Across a variety of task domains, we discuss the role of aMCC in motivation, including a) processing of the value of prior and expected rewards, b) assessment of energetic costs in the brain and the body, c) selectively learning and encoding prediction errors (unexpected changes) that are relevant for allostasis, d) computations for monitoring of internal states of the body and e) modulating the internal state of the body to prepare for action. Finally, we discuss the link between individual differences in aMCC processing and variation in two extreme ends of the range of motivational states, tenacity and apathy.

Neural correlates of correct and failed response inhibition in heavy versus light social drinkers: an fMRI study during a go/no-go task by healthy participants

The ability to suppress responses that are inappropriate, as well as the mechanisms monitoring the accuracy of actions in order to compensate for errors, is central to human behavior. Neural alterations that prevent stopping an inaccurate response, combined with a decreased ability of error monitoring, are considered to be prominent features of alcohol abuse. Moreover, (i) alterations of these processes have been reported in heavy social drinkers (i.e. young healthy individuals who do not yet exhibit a state of alcohol dependence); and (ii) through longitudinal studies, these alterations have been shown to underlie subsequent disinhibition that may lead to future alcohol use disorders. In the present functional magnetic resonance imaging study, using a contextual Go/No-Go task, we investigated whether different neural networks subtended correct inhibitions and monitoring mechanisms of failed inhibitory trials in light versus heavy social drinkers. We show that, although successful inhibition did not lead to significant changes, neural networks involved in error monitoring are different in light versus heavy drinkers. Thus, while light drinkers exhibited activations in their right inferior frontal, right middle cingulate and left superior temporal areas; heavy drinkers exhibited activations in their right cerebellum, left caudate nucleus, left superior occipital region, and left amygdala. These data are functionally interpreted as reflecting a "visually-driven emotional strategy" vs. an "executive-based" neural response to errors in heavy and light drinkers, respectively. Such a difference is interpreted as a key-factor that may subtend the transition from a controlled social heavy consumption to a state of clinical alcohol dependence.

Dissociable neural mechanisms track evidence accumulation for selection of attention versus action

Decision-making is typically studied as a sequential process from the selection of what to attend (e.g., between possible tasks, stimuli, or stimulus attributes) to which actions to take based on the attended information. However, people often process information across these various levels in parallel. Here we scan participants while they simultaneously weigh how much to attend to two dynamic stimulus attributes and what response to give. Regions of the prefrontal cortex track information about the stimulus attributes in dissociable ways, related to either the predicted reward (ventromedial prefrontal cortex) or the degree to which that attribute is being attended (dorsal anterior cingulate cortex, dACC). Within the dACC, adjacent regions track correlates of uncertainty at different levels of the decision, regarding what to attend versus how to respond. These findings bridge research on perceptual and value-based decision-making, demonstrating that people dynamically integrate information in parallel across different levels of decision-making.

The effect of feature-based attention on flanker interference processing: An fMRI-constrained source analysis

The present study examined whether feature-based cueing affects early or late stages of flanker conflict processing using EEG and fMRI. Feature cues either directed participants' attention to the upcoming colour of the target or were neutral. Validity-specific modulations during interference processing were investigated using the N200 event-related potential (ERP) component and BOLD signal differences. Additionally, both data sets were integrated using an fMRI-constrained source analysis. Finally, the results were compared with a previous study in which spatial instead of feature-based cueing was applied to an otherwise identical flanker task. Feature-based and spatial attention recruited a common fronto-parietal network during conflict processing. Irrespective of attention type (feature-based; spatial), this network responded to focussed attention (valid cueing) as well as context updating (invalid cueing), hinting at domain-general mechanisms. However, spatially and non-spatially directed attention also demonstrated domain-specific activation patterns for conflict processing that were observable in distinct EEG and fMRI data patterns as well as in the respective source analyses. Conflict-specific activity in visual brain regions was comparable between both attention types. We assume that the distinction between spatially and non-spatially directed attention types primarily applies to temporal differences (domain-specific dynamics) between signals originating in the same brain regions (domain-general localization).

Heuristic and optimal policy computations in the human brain during sequential decision-making

Optimal decisions across extended time horizons require value calculations over multiple probabilistic future states. Humans may circumvent such complex computations by resorting to easy-to-compute heuristics that approximate optimal solutions. To probe the potential interplay between heuristic and optimal computations, we develop a novel sequential decision-making task, framed as virtual foraging in which participants have to avoid virtual starvation. Rewards depend only on final outcomes over five-trial blocks, necessitating planning over five sequential decisions and probabilistic outcomes. Here, we report model comparisons demonstrating that participants primarily rely on the best available heuristic but also use the normatively optimal policy. FMRI signals in medial prefrontal cortex (MPFC) relate to heuristic and optimal policies and associated choice uncertainties. Crucially, reaction times and dorsal MPFC activity scale with discrepancies between heuristic and optimal policies. Thus, sequential decision-making in humans may emerge from integration between heuristic and optimal policies, implemented by controllers in MPFC.

Alhough humans often make a series of related decisions, it is unknown whether this is done by relying on optimal or heuristic strategies. Here, the authors show that humans rely on both the best heuristic and the optimal policy, and that these strategies are controlled by parts of the medial prefrontal cortex.

Distinct Roles for the Anterior Cingulate and Dorsolateral Prefrontal Cortices During Conflict Between Abstract Rules

Distinct patterns of activity within the anterior cingulate cortex (ACC) and dorsolateral prefrontal cortex (dlPFC) reported in neuroimaging studies during tasks involving conflict between competing responses have often been cited as evidence for their key contributions to conflict-monitoring and behavioral adaptation, respectively. However, supporting evidence from neuropsychological patients has been scarce and contradictory. We administered a well-studied analog of the Wisconsin Card Sorting Test, designed to elicit conflict between 2 abstract rules, to a cohort of 6 patients with damage to ACC or dlPFC. Patients who had sustained more significant damage to the ACC were not impaired either on a measure of "conflict cost" nor on measures of "conflict-induced behavioral adaptation." In contrast, damage to dlPFC did not affect the conflict cost measure but abolished the patients' ability to adapt their behavior following exposure to conflict, compared with controls. This pattern of results complements the findings from nonhuman primates with more circumscribed lesions to ACC or dlPFC on the same task and provides converging evidence that ACC is not necessary for performance when conflict is elicited between 2 abstract rules, whereas dlPFC plays a fundamental role in behavioral adaptation.

Predicting Motivation: Computational Models of PFC Can Explain Neural Coding of Motivation and Effort-based Decision-making in Health and Disease

Human behavior is strongly driven by the pursuit of rewards. In daily life, however, benefits mostly come at a cost, often requiring that effort be exerted to obtain potential benefits. Medial PFC (MPFC) and dorsolateral PFC (DLPFC) are frequently implicated in the expectation of effortful control, showing increased activity as a function of predicted task difficulty. Such activity partially overlaps with expectation of reward and has been observed both during decision-making and during task preparation. Recently, novel computational frameworks have been developed to explain activity in these regions during cognitive control, based on the principle of prediction and prediction error (predicted response-outcome [PRO] model [Alexander, W. H., & Brown, J. W. Medial prefrontal cortex as an action-outcome predictor. Nature Neuroscience, 14, 1338-1344, 2011], hierarchical error representation [HER] model [Alexander, W. H., & Brown, J. W. Hierarchical error representation: A computational model of anterior cingulate and dorsolateral prefrontal cortex. Neural Computation, 27, 2354-2410, 2015]). Despite the broad explanatory power of these models, it is not clear whether they can also accommodate effects related to the expectation of effort observed in MPFC and DLPFC. Here, we propose a translation of these computational frameworks to the domain of effort-based behavior. First, we discuss how the PRO model, based on prediction error, can explain effort-related activity in MPFC, by reframing effort-based behavior in a predictive context. We propose that MPFC activity reflects monitoring of motivationally relevant variables (such as effort and reward), by coding expectations and discrepancies from such expectations. Moreover, we derive behavioral and neural model-based predictions for healthy controls and clinical populations with impairments of motivation. Second, we illustrate the possible translation to effort-based behavior of the HER model, an extended version of PRO model based on hierarchical error prediction, developed to explain MPFC-DLPFC interactions. We derive behavioral predictions that describe how effort and reward information is coded in PFC and how changing the configuration of such environmental information might affect decision-making and task performance involving motivation.

Computational Models of Anterior Cingulate Cortex: At the Crossroads between Prediction and Effort

In the last two decades the anterior cingulate cortex (ACC) has become one of the most investigated areas of the brain. Extensive neuroimaging evidence suggests countless functions for this region, ranging from conflict and error coding, to social cognition, pain and effortful control. In response to this burgeoning amount of data, a proliferation of computational models has tried to characterize the neurocognitive architecture of ACC. Early seminal models provided a computational explanation for a relatively circumscribed set of empirical findings, mainly accounting for EEG and fMRI evidence. More recent models have focused on ACC's contribution to effortful control. In parallel to these developments, several proposals attempted to explain within a single computational framework a wider variety of empirical findings that span different cognitive processes and experimental modalities. Here we critically evaluate these modeling attempts, highlighting the continued need to reconcile the array of disparate ACC observations within a coherent, unifying framework.

Dorsal Anterior Cingulate, Medial Superior Frontal Cortex, and Anterior Insula Show Performance Reporting-Related Late Task Control Signals

The cingulo-opercular network (including the dorsal anterior cingulate and bilateral anterior insula) shows 3 distinct task-control signals across a wide variety of tasks, including trial-related signals that appear to come online at or near the end of the trial. Previous work suggests that there are separable responses in this network for errors and ambiguity, implicating multiple types of processing units within these regions. Using a unique paradigm, we directly show that these separable responses withhold activity to the end of the trial, in the service of reporting performance back into the task set. Participants performed a slow reveal task where images were presented behind a black mask which was gradually degraded, and they pressed a button when they could recognize the object that was being revealed. A behavioral pilot was used to identify ambiguous stimuli. We found interactive effects of accuracy and ambiguity, which suggests that these regions are computing and utilizing information, at one time, about both types of performance indices. Importantly, we showed a relationship between cingulo-opercular activity and behavioral performance, suggesting a role for these regions in performance reporting, per se. We discuss these results in the context of task control.

Contextual effects on cognitive control and BOLD activation in single versus mixed saccade tasks

The context or trial history of a task influences response efficiency in mixed paradigms based on cognitive control demands for task set selection. In the current study, the impact of context on prosaccade and antisaccade trials in single and mixed tasks was investigated with BOLD fMRI. Prosaccades require a look towards a newly appearing target, while antisaccades require cognitive control for prepotent response inhibition and generation of a saccade to the opposite location. Results indicated slower prosaccade reaction times and more antisaccade errors for switched than repeated or single trials, and slower antisaccade reaction times for single than mixed trials. BOLD activation was greater for the mixed than the single context in frontal eye fields and precuneus, while switch trials had greater activation than repeat trials in posterior parietal and middle occipital cortex. Greater antisaccade activation was observed overall in saccade circuitry, although effects were evident primarily for the mixed task when considered separately. Finally, an interaction was observed in superior frontal cortex, precuneus, anterior cingulate, and thalamus with strong responses for antisaccade switch trials in the latter two regions. Altogether this response pattern demonstrated the sensitivity of cognitive control to changing task conditions, especially due to task switching costs. Such context-specific differences highlight the importance of trial history when assessing cognitive control.

Attentional deployment impacts neural response to regret

Regret results from comparing non-optimal outcomes containing both gain and loss parts to better alternatives during decision-making. The present fMRI study aimed to explore whether levels of regret could change when gain or loss part of a non-optimal outcome was focused during a sequential risk taking task, i.e. the effect of an important emotional regulation strategy named as attentional deployment on regret. Participants were asked to open a series of boxes consecutively and decided when to stop. Each box contained a reward, except for one containing a devil to zero one’s gain in the trial. After participants stopped, both collected gains and missed chances were revealed. Besides, participants were induced to focus on collected gains (GF) or missed chances (MF), by highlighting different parts of the outcome with red squares. Behaviorally, participants rated less regret to their decisions in GF than MF context. Moreover, participants tended to be less risk-taking after GF context relative to MF. At the neural level, bilateral straitum showed increased activations in both optimal outcome and GF context. However, right MFG and IPL only showed stronger activation in GF than MF context. Additionally, pgACC and mPFC activations were found only in optimal outcome.

Automated classification of pain perception using high-density electroencephalography data

The translation of brief, millisecond-long pain-eliciting stimuli to the subjective perception of pain is associated with changes in theta, alpha, beta, and gamma oscillations over sensorimotor cortex. However, when a pain-eliciting stimulus continues for minutes, regions beyond the sensorimotor cortex, such as the prefrontal cortex, are also engaged. Abnormalities in prefrontal cortex have been associated with chronic pain states, but conventional, millisecond-long EEG paradigms do not engage prefrontal regions. In the current study, we collected high-density EEG data during an experimental paradigm in which subjects experienced a 4-s, low- or high-intensity pain-eliciting stimulus. EEG data were analyzed using independent component analyses, EEG source localization analyses, and measure projection analyses. We report three novel findings. First, an increase in pain perception was associated with an increase in gamma and theta power in a cortical region that included medial prefrontal cortex. Second, a decrease in lower beta power was associated with an increase in pain perception in a cortical region that included the contralateral sensorimotor cortex. Third, we used machine learning for automated classification of EEG data into low- and high-pain classes. Theta and gamma power in the medial prefrontal region and lower beta power in the contralateral sensorimotor region served as features for classification. We found a leave-one-out cross-validation accuracy of 89.58%. The development of biological markers for pain states continues to gain traction in the literature, and our findings provide new information that advances this body of work.NEW & NOTEWORTHY The development of a biological marker for pain continues to gain traction in literature. Our findings show that high- and low-pain perception in human subjects can be classified with 89% accuracy using high-density EEG data from prefrontal cortex and contralateral sensorimotor cortex. Our approach represents a novel neurophysiological paradigm that advances the literature on biological markers for pain.

Pain and motor processing in the human cerebellum

Pain-related adaptations in movement require a network architecture that allows for integration across pain and motor circuits. Previous studies addressing this issue have focused on cortical areas such as the midcingulate cortex. Here, we focus on pain and motor processing in the human cerebellum. The goal of this study was to identify areas of activation in the cerebellum, which are common to pain and motor processing, and to determine whether the activation is limited to the superior and inferior cerebellar motor maps or extends into multimodal areas of the posterior cerebellum. Our observations identified overlapping activity in left and right lobules VI and VIIb during pain and motor processing. Activation in these multimodal regions persisted when pain and motor processes were combined within the same trial, and activation in contralateral left lobule VIIb persisted when stimulation was controlled for. Functional connectivity analyses revealed significant correlations in the BOLD time series between multimodal cerebellar regions and sensorimotor regions in the cerebrum including anterior midcingulate cortex, supplementary motor area, and thalamus. The current findings are the first to show multimodal processing in lobules VI and VIIb for motor control and pain processing and suggest that the posterior cerebellum may be important in understanding pain-related adaptations in motor control.

Tell me twice: A multi-study analysis of the functional connectivity between the cerebrum and cerebellum after repeated trait information

This multi-study analysis (6 fMRI studies; 142 participants) explores the functional activation and connectivity of the cerebellum with the cerebrum during repeated behavioral information uptake informing about personality traits of different persons. The results suggest that trait repetition recruits activity in areas belonging to the mentalizing and executive control networks in the cerebrum, and the executive control areas in the cerebellum. Cerebral activation was observed in the executive control network including the posterior medial frontal cortex (pmFC), the bilateral prefrontal cortex (PFC) and bilateral inferior parietal cortex (IPC), in the mentalizing network including the bilateral middle temporal cortex (MTC) extending to the right superior temporal cortex (STC), as well as in the visual network including the left cuneus (Cun) and the left inferior occipital cortex. Moreover, cerebellar activation was found bilaterally in lobules VI and VII belonging to the executive control network. Importantly, significant patterns of functional connectivity were found linking these cerebellar executive areas with cerebral executive areas in the medial pmFC, the left PFC and the left IPC, and mentalizing areas in the left MTC. In addition, connectivity was found between the cerebral areas in the left hemisphere involved in the executive and mentalizing networks, as well as with their homolog areas in the right hemisphere. The discussion centers on the role of these cerebello-cerebral connections in matching internal predictions generated by the cerebellum with external information from the cerebrum, presumably involving the sequencing of behaviors.

Neural Response during the Activation of the Attachment System in Patients with Borderline Personality Disorder: An fMRI Study

Individuals with borderline personality disorder (BPD) are characterized by emotional instability, impaired emotion regulation and unresolved attachment patterns associated with abusive childhood experiences. We investigated the neural response during the activation of the attachment system in BPD patients compared to healthy controls using functional magnetic resonance imaging (fMRI). Eleven female patients with BPD without posttraumatic stress disorder (PTSD) and 17 healthy female controls matched for age and education were telling stories in the scanner in response to the Adult Attachment Projective Picture System (AAP), an eight-picture set assessment of adult attachment. The picture set includes theoretically-derived attachment scenes, such as separation, death, threat and potential abuse. The picture presentation order is designed to gradually increase the activation of the attachment system. Each picture stimulus was presented for 2 min. Analyses examine group differences in attachment classifications and neural activation patterns over the course of the task. Unresolved attachment was associated with increasing amygdala activation over the course of the attachment task in patients as well as controls. Unresolved controls, but not patients, showed activation in the right dorsolateral prefrontal cortex (DLPFC) and the rostral cingulate zone (RCZ). We interpret this as a neural signature of BPD patients’ inability to exert top-down control under conditions of attachment distress. These findings point to possible neural mechanisms for underlying affective dysregulation in BPD in the context of attachment trauma and fear.

Salience Network Activity in Perceptual Decisions

The dorsal anterior cingulate cortex (dACC) and the anterior insulae (AIs) are coactivated in various perceptual decision-making (PDM) tasks and form the salience network (SN): a key network in sensory perception and the coordination of behavioral responses. However, what the functional role of SN is, how these key SN nodes interact with each other to form a network in a perceptual decision, and how the network depends on the perceptual difficulty remain largely unknown. In the present study, we measured blood oxygen level-dependent (BOLD) signals using functional magnetic resonance imaging (fMRI). During four PDM tasks (1) face-house discrimination, (2) happy-angry face discrimination, (3) audiovisual asynchrony and synchrony perception, and a (4) random dot motion direction task, we varied the task difficulty and examined the interactions between these SN nodes. In all the experiments, behavioral accuracy decreased and response time increased with task difficulty. The BOLD signal increased in SN nodes with the ambiguity in the sensory information. We also found that there were significant directed functional connections between AIs and dACC in all four tasks and that the interactions between these nodes increased with task difficulty. The observed difficulty-dependent functional architecture of SN suggests that the dACC and AIs are part of a large-scale cognitive system that facilitates sensory integration in PDM.

Neural dissociations between meaningful and mere inconsistency in impression updating

Recent neuroimaging work has identified a network of regions that work in concert to update impressions of other people, particularly in response to inconsistent behavior. However, the specific functional contributions of these regions to the updating process remain unclear. Using fMRI, we tested whether increases in activity triggered by inconsistent behavior reflect changes in the stored representations of other people in response to behavioral inconsistency, or merely a response to the inconsistency itself. Participants encountered a series of individuals whose behavior either changed in an attributionally meaningful fashion or was merely inconsistent with the immediately preceding behavior. We observed that left ventrolateral prefrontal cortex (vlPFC) and left inferior frontal gyrus (IFG) were preferentially recruited in response to unexpected, immoral behavior, whereas a separate set of regions (including dorsal anterior cingulate cortex, posterior cingulate cortex and temporoparietal junction/inferior parietal lobule) was preferentially recruited in response to more mundane inconsistencies in behavior. These results shed light on the distributed systems supporting impression updating. Specifically, while many regions supporting updating may primarily respond to moment-to-moment changes in behavior, a subset of regions (e.g. vlPFC and IFG) may contribute to updating person representations in response to trait-relevant changes in behavior.

Cascade of neural processing orchestrates cognitive control in human frontal cortex

Rapid and flexible interpretation of conflicting sensory inputs in the context of current goals is a critical component of cognitive control that is orchestrated by frontal cortex. The relative roles of distinct subregions within frontal cortex are poorly understood. To examine the dynamics underlying cognitive control across frontal regions, we took advantage of the spatiotemporal resolution of intracranial recordings in epilepsy patients while subjects resolved color-word conflict. We observed differential activity preceding the behavioral responses to conflict trials throughout frontal cortex; this activity was correlated with behavioral reaction times. These signals emerged first in anterior cingulate cortex (ACC) before dorsolateral prefrontal cortex (dlPFC), followed by medial frontal cortex (mFC) and then by orbitofrontal cortex (OFC). These results disassociate the frontal subregions based on their dynamics, and suggest a temporal hierarchy for cognitive control in human cortex.

DOI:http://dx.doi.org/10.7554/eLife.12352.001

The brain adapts to control our behavior in different ways depending on the specific situation, which is particularly useful when deciding how to interpret conflicting sets of information. The 'Stroop task' is a classic demonstration of this process. In this task, individuals are shown words where the color and the meaning of the text conflict – for example, the word 'green' is written in blue. When asked what the color of the text is, individuals must suppress the instinct to read the word. This causes them to make more mistakes and take longer to decide on an answer than when they perform the same task using words that have no conflict (for example, when “red” is written in red).

Previous work has suggested that several regions within part of the brain called the frontal cortex play a role in this cognitive control process. However, the relative contributions of each of these regions, and the order in which they are activated, remain unclear. This is in part due to the fact that accurately measuring the electrical activity of the frontal cortex requires implanting electrodes into the brain.

Tang et al. took advantage of a rare opportunity to record this activity from a group of patients who had electrodes implanted in their frontal cortex to treat epilepsy. The electrical signals recorded by these electrodes as the subjects performed the Stroop task revealed that four regions in the frontal cortex altered their activity during trials where the color and the meaning of a word conflicted. These responses corresponded with the subject’s reaction time, changed depending on the exact nature of the task, and even reflected the subjects’ errors. These responses arose at different times in different regions, allowing Tang et al. to suggest how signals flow through the frontal cortex during cognitive control.

In the future it will be important to further understand how the regions of the frontal cortex identified by Tang et al. interact with each other and to establish their roles in cognitive control. These observations could then be used to produce a theoretical framework that describes how the brain adapts behavior to different circumstances.

DOI:http://dx.doi.org/10.7554/eLife.12352.002

Hierarchical Error Representation: A Computational Model of Anterior Cingulate and Dorsolateral Prefrontal Cortex

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 better estimates of the likely outcomes of actions. We formalize the error representation hypothesis in a new computational model based on our previous model of ACC. The hierarchical error representation (HER) model of ACC/dlPFC suggests a mechanism by which hierarchically organized layers within ACC and dlPFC interact in order to solve sophisticated cognitive tasks. In a series of simulations, we demonstrate the ability of the HER model to autonomously learn to perform structured tasks in a manner comparable to human performance, and we show that the HER model outperforms current deep learning networks by an order of magnitude.

Anticipating conflict: Neural correlates of a Bayesian belief and its motor consequence

Previous studies have examined the neural correlates of proactive control using a variety of behavioral paradigms; however, the neural network relating the control process to its behavioral consequence remains unclear. Here, we applied a dynamic Bayesian model to a large fMRI data set of the stop signal task to address this issue. By estimating the probability of the stop signal - p(Stop) - trial by trial, we showed that higher p(Stop) is associated with prolonged go trial reaction time (RT), indicating proactive control of motor response. In modeling fMRI signals at trial and target onsets, we distinguished activities of proactive control, prediction error, and RT slowing. We showed that the anterior pre-supplementary motor area (pre-SMA) responds specifically to increased stop signal likelihood, and its activity is correlated with activations of the posterior pre-SMA and bilateral anterior insula during prolonged response times. This directional link is also supported by Granger causality analysis. Furthermore, proactive control, prediction error, and time-on-task are each mapped to distinct areas in the medial prefrontal cortex. Together, these findings dissect regional functions of the medial prefrontal cortex in cognitive control and provide system level evidence associating conflict anticipation with its motor consequence.