Illusory object recognition is either perceptual or cognitive in origin depending on decision confidence.

We occasionally misinterpret ambiguous sensory input or report a stimulus when none is presented. It is unknown whether such errors have a sensory origin and reflect true perceptual illusions, or whether they have a more cognitive origin (e.g., are due to guessing), or both. When participants performed an error-prone and challenging face/house discrimination task, multivariate electroencephalography (EEG) analyses revealed that during decision errors (e.g., mistaking a face for a house), sensory stages of visual information processing initially represent the presented stimulus category. Crucially however, when participants were confident in their erroneous decision, so when the illusion was strongest, this neural representation flipped later in time and reflected the incorrectly reported percept. This flip in neural pattern was absent for decisions that were made with low confidence. This work demonstrates that decision confidence arbitrates between perceptual decision errors, which reflect true illusions of perception, and cognitive decision errors, which do not.

Action Planning Renders Objects in Working Memory More Attentionally Salient.

A rapidly growing body of work suggests that visual working memory (VWM) is fundamentally action oriented. Consistent with this, we recently showed that attention is more strongly biased by VWM representations of objects when we plan to act on those objects in the future. Using EEG and eye tracking, here, we investigated neurophysiological correlates of the interactions between VWM and action. Participants (n = 36) memorized a shape for a subsequent VWM test. At test, a probe was presented along with a secondary object. In the action condition, participants gripped the actual probe if it matched the memorized shape, whereas in the control condition, they gripped the secondary object. Crucially, during the VWM delay, participants engaged in a visual selection task, in which they located a target as fast as possible. The memorized shape could either encircle the target (congruent trials) or a distractor (incongruent trials). Replicating previous findings, we found that eye gaze was biased toward the VWM-matching shape and, importantly, more so when the shape was directly associated with an action plan. Moreover, the ERP results revealed that during the selection task, future action-relevant VWM-matching shapes elicited (1) a stronger Ppc (posterior positivity contralateral), signaling greater attentional saliency; (2) an earlier PD (distractor positivity) component, suggesting faster suppression; (3) a larger inverse (i.e., positive) sustained posterior contralateral negativity in incongruent trials, consistent with stronger suppression of action-associated distractors; and (4) an enhanced response-locked positivity over left motor regions, possibly indicating enhanced inhibition of the response associated with the memorized item during the interim task. Overall, these results suggest that action planning renders objects in VWM more attentionally salient, supporting the notion of selection-for-action in working memory.

Mechanisms of human dynamic object recognition revealed by sequential deep neural networks.

Humans can quickly recognize objects in a dynamically changing world. This ability is showcased by the fact that observers succeed at recognizing objects in rapidly changing image sequences, at up to 13 ms/image. To date, the mechanisms that govern dynamic object recognition remain poorly understood. Here, we developed deep learning models for dynamic recognition and compared different computational mechanisms, contrasting feedforward and recurrent, single-image and sequential processing as well as different forms of adaptation. We found that only models that integrate images sequentially via lateral recurrence mirrored human performance (N = 36) and were predictive of trial-by-trial responses across image durations (13-80 ms/image). Importantly, models with sequential lateral-recurrent integration also captured how human performance changes as a function of image presentation durations, with models processing images for a few time steps capturing human object recognition at shorter presentation durations and models processing images for more time steps capturing human object recognition at longer presentation durations. Furthermore, augmenting such a recurrent model with adaptation markedly improved dynamic recognition performance and accelerated its representational dynamics, thereby predicting human trial-by-trial responses using fewer processing resources. Together, these findings provide new insights into the mechanisms rendering object recognition so fast and effective in a dynamic visual world.

A Silent Disco: Differential Effects of Beat-based and Pattern-based Temporal Expectations on Persistent Entrainment of Low-frequency Neural Oscillations.

The brain uses temporal structure in the environment, like rhythm in music and speech, to predict the timing of events, thereby optimizing their processing and perception. Temporal expectations can be grounded in different aspects of the input structure, such as a regular beat or a predictable pattern. One influential account posits that a generic mechanism underlies beat-based and pattern-based expectations, namely, entrainment of low-frequency neural oscillations to rhythmic input, whereas other accounts assume different underlying neural mechanisms. Here, we addressed this outstanding issue by examining EEG activity and behavioral responses during silent periods following rhythmic auditory sequences. We measured responses outlasting the rhythms both to avoid confounding the EEG analyses with evoked responses, and to directly test whether beat-based and pattern-based expectations persist beyond stimulation, as predicted by entrainment theories. To properly disentangle beat-based and pattern-based expectations, which often occur simultaneously, we used non-isochronous rhythms with a beat, a predictable pattern, or random timing. In Experiment 1 (n = 32), beat-based expectations affected behavioral ratings of probe events for two beat-cycles after the end of the rhythm. The effects of pattern-based expectations reflected expectations for one interval. In Experiment 2 (n = 27), using EEG, we found enhanced spectral power at the beat frequency for beat-based sequences both during listening and silence. For pattern-based sequences, enhanced power at a pattern-specific frequency was present during listening, but not silence. Moreover, we found a difference in the evoked signal following pattern-based and beat-based sequences. Finally, we show how multivariate pattern decoding and multiscale entropy-measures sensitive to non-oscillatory components of the signal-can be used to probe temporal expectations. Together, our results suggest that the input structure used to form temporal expectations may affect the associated neural mechanisms. We suggest climbing activity and low-frequency oscillations may be differentially associated with pattern-based and beat-based expectations.

The Distractor Positivity Component and the Inhibition of Distracting Stimuli.

There has been a long-lasting debate about whether salient stimuli, such as uniquely colored objects, have the ability to automatically distract us. To resolve this debate, it has been suggested that salient stimuli do attract attention but that they can be suppressed to prevent distraction. Some research supporting this viewpoint has focused on a newly discovered ERP component called the distractor positivity (PD), which is thought to measure an inhibitory attentional process. This collaborative review summarizes previous research relying on this component with a specific emphasis on how the PD has been used to understand the ability to ignore distracting stimuli. In particular, we outline how the PD component has been used to gain theoretical insights about how search strategy and learning can influence distraction. We also review alternative accounts of the cognitive processes indexed by the PD component. Ultimately, we conclude that the PD component is a useful tool for understanding inhibitory processes related to distraction and may prove to be useful in other areas of study related to cognitive control.

Arousal state affects perceptual decision-making by modulating hierarchical sensory processing in a large-scale visual system model.

Arousal levels strongly affect task performance. Yet, what arousal level is optimal for a task depends on its difficulty. Easy task performance peaks at higher arousal levels, whereas performance on difficult tasks displays an inverted U-shape relationship with arousal, peaking at medium arousal levels, an observation first made by Yerkes and Dodson in 1908. It is commonly proposed that the noradrenergic locus coeruleus system regulates these effects on performance through a widespread release of noradrenaline resulting in changes of cortical gain. This account, however, does not explain why performance decays with high arousal levels only in difficult, but not in simple tasks. Here, we present a mechanistic model that revisits the Yerkes-Dodson effect from a sensory perspective: a deep convolutional neural network augmented with a global gain mechanism reproduced the same interaction between arousal state and task difficulty in its performance. Investigating this model revealed that global gain states differentially modulated sensory information encoding across the processing hierarchy, which explained their differential effects on performance on simple versus difficult tasks. These findings offer a novel hierarchical sensory processing account of how, and why, arousal state affects task performance.

Perceptual learning in humans: An active, top-down-guided process.

Deep neural network (DNN) models of human-like vision are typically built by feeding blank slate DNN visual images as training data. However, the literature on human perception and perceptual learning suggests that developing DNNs that truly model human vision requires a shift in approach in which perception is not treated as a largely bottom-up process, but as an active, top-down-guided process.

Leveraging Spiking Deep Neural Networks to Understand the Neural Mechanisms Underlying Selective Attention.

Spatial attention enhances sensory processing of goal-relevant information and improves perceptual sensitivity. Yet, the specific neural mechanisms underlying the effects of spatial attention on performance are still contested. Here, we examine different attention mechanisms in spiking deep convolutional neural networks. We directly contrast effects of precision (internal noise suppression) and two different gain modulation mechanisms on performance on a visual search task with complex real-world images. Unlike standard artificial neurons, biological neurons have saturating activation functions, permitting implementation of attentional gain as gain on a neuron's input or on its outgoing connection. We show that modulating the connection is most effective in selectively enhancing information processing by redistributing spiking activity and by introducing additional task-relevant information, as shown by representational similarity analyses. Precision only produced minor attentional effects in performance. Our results, which mirror empirical findings, show that it is possible to adjudicate between attention mechanisms using more biologically realistic models and natural stimuli.

No Effect of Transcranial Direct Current Stimulation over Left Dorsolateral Prefrontal Cortex on Temporal Attention.

Selection mechanisms that dynamically gate only relevant perceptual information for further processing and sustained representation in working memory are critical for goal-directed behavior. We examined whether this gating process can be modulated by transcranial direct current stimulation (tDCS) over left dorsolateral prefrontal cortex (lDLPFC)-a region known to play a key role in working memory and conscious access. Specifically, we examined the effects of tDCS on the magnitude of the "attentional blink" (AB), a deficit in identifying the second of two targets presented in rapid succession. Thirty-four participants performed an AB task before (baseline), during and after 20 min of 1-mA anodal and cathodal tDCS in two separate sessions. On the basis of previous reports linking individual differences in AB magnitude to individual differences in DLPFC activity and on the basis of suggestions that effects of tDCS depend on baseline brain activity levels, we hypothesized that anodal tDCS over lDLPFC would modulate the magnitude of the AB as a function of individual baseline AB magnitude. Behavioral results did not provide support for this hypothesis. At the group level, we also did not observe any significant effects of tDCS, and a Bayesian analysis revealed strong evidence that tDCS to lDLPFC did not affect AB performance. Together, these findings do not support the idea that there is an optimal level of prefrontal cortical excitability for cognitive function. More generally, they add to a growing body of work that challenges the idea that the effects of tDCS can be predicted from baseline levels of behavior.

Representational dynamics preceding conscious access.

Our senses are continuously bombarded with more information than our brain can process up to the level of awareness. The present study aimed to enhance understanding on how attentional selection shapes conscious access under conditions of rapidly changing input. Using an attention task, EEG, and multivariate decoding of individual target- and distractor-defining features, we specifically examined dynamic changes in the representation of targets and distractors as a function of conscious access and the task-relevance (target or distractor) of the preceding item in the RSVP stream. At the behavioral level, replicating previous work and suggestive of a flexible gating mechanism, we found a significant impairment in conscious access to targets (T2) that were preceded by a target (T1) followed by one or two distractors (i.e., the attentional blink), but striking facilitation of conscious access to targets shown directly after another target (i.e., lag-1 sparing and blink reversal). At the neural level, conscious access to T2 was associated with enhanced early- and late-stage T1 representations and enhanced late-stage D1 representations, and interestingly, could be predicted based on the pattern of EEG activation well before T1 was presented. Yet, across task conditions, we did not find convincing evidence for the notion that conscious access is affected by rapid top-down selection-related modulations of the strength of early sensory representations induced by the preceding visual event. These results cannot easily be explained by existing accounts of how attentional selection shapes conscious access under rapidly changing input conditions, and have important implications for theories of the attentional blink and consciousness more generally.

Subjective visibility report is facilitated by conscious predictions only.

Predictions in the visual domain have been shown to modulate conscious access. Yet, little is known about how predictions may do so and to what extent they need to be consciously implemented to be effective. To address this, we administered an attentional blink (AB) task in which target 1 (T1) identity predicted target 2 (T2) identity, while participants rated their perceptual awareness of validly versus invalidly predicted T2s (Experiment 1 & 2) or reported T2 identity (Experiment 3). Critically, we tested the effects of conscious and non-conscious predictions, after seen and unseen T1s, on T2 visibility. We found that valid predictions increased subjective visibility reports and discrimination of T2s, but only when predictions were generated by a consciously accessed T1, irrespective of the timing at which the effects were measured (short vs. longs lags). These results further our understanding of the intricate relationship between predictive processing and consciousness.

Learning What Is Irrelevant or Relevant: Expectations Facilitate Distractor Inhibition and Target Facilitation through Distinct Neural Mechanisms.

It is well known that attention can facilitate performance by top-down biasing processing of task-relevant information in advance. Recent findings from behavioral studies suggest that distractor inhibition is not under similar direct control but strongly dependent on expectations derived from previous experience. Yet, how expectations about distracting information influence distractor inhibition at the neural level remains unclear. The current study addressed this outstanding question in three experiments in which search displays with repeating distractor or target locations across trials allowed human observers (male and female) to learn which location to selectively suppress or boost. Behavioral findings demonstrated that both distractor and target location learning resulted in more efficient search, as indexed by faster response times. Crucially, distractor learning benefits were observed without target location foreknowledge, unaffected by the number of possible target locations, and could not be explained by priming alone. To determine how distractor location expectations facilitated performance, we applied a spatial encoding model to EEG data to reconstruct activity in neural populations tuned to distractor or target locations. Target location learning increased neural tuning to target locations in advance, indicative of preparatory biasing. This sensitivity increased after target presentation. By contrast, distractor expectations did not change preparatory spatial tuning. Instead, distractor expectations reduced distractor-specific processing, as reflected in the disappearance of the Pd event-related potential component, a neural marker of distractor inhibition, and decreased decoding accuracy. These findings suggest that the brain may no longer process expected distractors as distractors, once it has learned they can safely be ignored.SIGNIFICANCE STATEMENT We constantly try hard to ignore conspicuous events that distract us from our current goals. Surprisingly, and in contrast to dominant attention theories, ignoring distracting, but irrelevant, events does not seem to be as flexible as is focusing our attention on those same aspects. Instead, distractor suppression appears to strongly rely on learned, context-dependent expectations. Here, we investigated how learning about upcoming distractors changes distractor processing and directly contrasted the underlying neural dynamics to target learning. We show that, while target learning enhanced anticipatory sensory tuning, distractor learning only modulated reactive suppressive processing. These results suggest that expected distractors may no longer be considered distractors by the brain once it has learned that they can safely be ignored.

Beat-based and Memory-based Temporal Expectations in Rhythm: Similar Perceptual Effects, Different Underlying Mechanisms.

Predicting the timing of incoming information allows the brain to optimize information processing in dynamic environments. Behaviorally, temporal expectations have been shown to facilitate processing of events at expected time points, such as sounds that coincide with the beat in musical rhythm. Yet, temporal expectations can develop based on different forms of structure in the environment, not just the regularity afforded by a musical beat. Little is still known about how different types of temporal expectations are neurally implemented and affect performance. Here, we orthogonally manipulated the periodicity and predictability of rhythmic sequences to examine the mechanisms underlying beat-based and memory-based temporal expectations, respectively. Behaviorally and using EEG, we looked at the effects of beat-based and memory-based expectations on auditory processing when rhythms were task-relevant or task-irrelevant. At expected time points, both beat-based and memory-based expectations facilitated target detection and led to attenuation of P1 and N1 responses, even when expectations were task-irrelevant (unattended). For beat-based expectations, we additionally found reduced target detection and enhanced N1 responses for events at unexpected time points (e.g., off-beat), regardless of the presence of memory-based expectations or task relevance. This latter finding supports the notion that periodicity selectively induces rhythmic fluctuations in neural excitability and furthermore indicates that, although beat-based and memory-based expectations may similarly affect auditory processing of expected events, their underlying neural mechanisms may be different.

No Evidence that Predictions and Attention Modulate the First Feedforward Sweep of Cortical Information Processing.

Predictive coding models propose that predictions (stimulus likelihood) reduce sensory signals as early as primary visual cortex (V1), and that attention (stimulus relevance) can modulate these effects. Indeed, both prediction and attention have been shown to modulate V1 activity, albeit with fMRI, which has low temporal resolution. This leaves it unclear whether these effects reflect a modulation of the first feedforward sweep of visual information processing and/or later, feedback-related activity. In two experiments, we used electroencephalography and orthogonally manipulated spatial predictions and attention to address this issue. Although clear top-down biases were found, as reflected in pre-stimulus alpha-band activity, we found no evidence for top-down effects on the earliest visual cortical processing stage (<80 ms post-stimulus), as indexed by the amplitude of the C1 event-related potential component and multivariate pattern analyses. These findings indicate that initial visual afferent activity may be impenetrable to top-down influences by spatial prediction and attention.

Dynamic Interactions between Top-Down Expectations and Conscious Awareness.

It is well known that top-down expectations affect perceptual processes. Yet, remarkably little is known about the relationship between expectations and conscious awareness. We address three crucial outstanding questions: (1) how do expectations affect the likelihood of conscious stimulus perception?; (2) does the brain register violations of expectations nonconsciously?; and (3) do expectations need to be conscious to influence perceptual decisions? Using human participants, we performed three experiments in which we manipulated stimulus predictability within the attentional blink paradigm, while combining visual psychophysics with electrophysiological recordings. We found that valid stimulus expectations increase the likelihood of conscious access of stimuli. Furthermore, our findings suggest a clear dissociation in the interaction between expectations and consciousness: conscious awareness seems crucial for the implementation of top-down expectations, but not for the generation of bottom-up stimulus-evoked prediction errors. These results constrain and update influential theories about the role of consciousness in the predictive brain.SIGNIFICANCE STATEMENT While the relationship between expectations and conscious awareness plays a major role in many prediction-based theories of brain functioning, thus far few empirical studies have examined this relationship. Here, we address this gap in knowledge in a set of three experiments. Our results suggest that the effect of expectations on conscious awareness varies between different steps of the hierarchy of predictive processing. While the active use of top-down expectations for perceptual decisions requires conscious awareness, prediction errors can be triggered outside of conscious awareness. These results constrain and update influential theories about the role of consciousness in the predictive brain.

Contributions of the Ventral Striatum to Conscious Perception: An Intracranial EEG Study of the Attentional Blink.

The brain is limited in its capacity to consciously process information, necessitating gating of information. While conscious perception is robustly associated with sustained, recurrent interactions between widespread cortical regions, subcortical regions, including the striatum, influence cortical activity. Here, we examined whether the ventral striatum, given its ability to modulate cortical information flow, contributes to conscious perception. Using intracranial EEG, we recorded ventral striatum activity while 7 patients performed an attentional blink task in which they had to detect two targets (T1 and T2) in a stream of distractors. Typically, when T2 follows T1 within 100-500 ms, it is often not perceived (i.e., the attentional blink). We found that conscious T2 perception was influenced and signaled by ventral striatal activity. Specifically, the failure to perceive T2 was foreshadowed by a T1-induced increase in α and low ß oscillatory activity as early as 80 ms after T1, indicating that the attentional blink to T2 may be due to very early T1-driven attentional capture. Moreover, only consciously perceived targets were associated with an increase in θ activity between 200 and 400 ms. These unique findings shed new light on the mechanisms that give rise to the attentional blink by revealing that conscious target perception may be determined by T1 processing at a much earlier processing stage than traditionally believed. More generally, they indicate that ventral striatum activity may contribute to conscious perception, presumably by gating cortical information flow. SIGNIFICANCE STATEMENT: What determines whether we become aware of a piece of information or not? Conscious access has been robustly associated with activity within a distributed network of cortical regions. Using intracranial electrophysiological recordings during an attentional blink task, we tested the idea that the ventral striatum, because of its ability to modulate cortical information flow, may contribute to conscious perception. We find that conscious perception is influenced and signaled by ventral striatal activity. Short-latency (80-140 ms) striatal responses to a first target determined conscious perception of a second target. Moreover, conscious perception of the second target was signaled by longer-latency (200-400 ms) striatal activity. These results suggest that the ventral striatum may be part of a subcortical network that influences conscious experience.

Oscillatory Mechanisms of Response Conflict Elicited by Color and Motion Direction: An Individual Differences Approach.

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

Boosting Cognition: Effects of Multiple-Session Transcranial Direct Current Stimulation on Working Memory.

Transcranial direct current stimulation (tDCS) is a promising tool for neurocognitive enhancement. Several studies have shown that just a single session of tDCS over the left dorsolateral pFC (lDLPFC) can improve the core cognitive function of working memory (WM) in healthy adults. Yet, recent studies combining multiple sessions of anodal tDCS over lDLPFC with verbal WM training did not observe additional benefits of tDCS in subsequent stimulation sessions nor transfer of benefits to novel WM tasks posttraining. Using an enhanced stimulation protocol as well as a design that included a baseline measure each day, the current study aimed to further investigate the effects of multiple sessions of tDCS on WM. Specifically, we investigated the effects of three subsequent days of stimulation with anodal (20 min, 1 mA) versus sham tDCS (1 min, 1 mA) over lDLPFC (with a right supraorbital reference) paired with a challenging verbal WM task. WM performance was measured with a verbal WM updating task (the letter n-back) in the stimulation sessions and several WM transfer tasks (different letter set n-back, spatial n-back, operation span) before and 2 days after stimulation. Anodal tDCS over lDLPFC enhanced WM performance in the first stimulation session, an effect that remained visible 24 hr later. However, no further gains of anodal tDCS were observed in the second and third stimulation sessions, nor did benefits transfer to other WM tasks at the group level. Yet, interestingly, post hoc individual difference analyses revealed that in the anodal stimulation group the extent of change in WM performance on the first day of stimulation predicted pre to post changes on both the verbal and the spatial transfer task. Notably, this relationship was not observed in the sham group. Performance of two individuals worsened during anodal stimulation and on the transfer tasks. Together, these findings suggest that repeated anodal tDCS over lDLPFC combined with a challenging WM task may be an effective method to enhance domain-independent WM functioning in some individuals, but not others, or can even impair WM. They thus call for a thorough investigation into individual differences in tDCS respondence as well as further research into the design of multisession tDCS protocols that may be optimal for boosting cognition across a wide range of individuals.

Proactive, but Not Reactive, Distractor Filtering Relies on Local Modulation of Alpha Oscillatory Activity.

Filter mechanisms that prevent irrelevant information from consuming the limited storage capacity of visual STM are critical for goal-directed behavior. Alpha oscillatory activity has been related to proactive filtering of anticipated distraction. Yet, distraction in everyday life is not always anticipated, necessitating rapid, reactive filtering mechanisms. Currently, the oscillatory mechanisms underlying reactive distractor filtering remain unclear. In the current EEG study, we investigated whether reactive filtering of distractors also relies on alpha-band oscillatory mechanisms and explored possible contributions by oscillations in other frequency bands. To this end, participants performed a lateralized change detection task in which a varying and unpredicted number of distractors were presented both in the relevant hemifield, among targets, and in the irrelevant hemifield. Results showed that, whereas proactive distractor filtering was accompanied by lateralization of alpha-band activity over posterior scalp regions, reactive distractor filtering was not associated with modulations of oscillatory power in any frequency band. Yet, behavioral and post hoc ERP analyses clearly showed that participants selectively encoded relevant information. On the basis of these results, we conclude that reactive distractor filtering may not be realized through local modulation of alpha-band oscillatory activity.

The integration of negative affect, pain and cognitive control in the cingulate cortex.

It has been argued that emotion, pain and cognitive control are functionally segregated in distinct subdivisions of the cingulate cortex. However, recent observations encourage a fundamentally different view. Imaging studies demonstrate that negative affect, pain and cognitive control activate an overlapping region of the dorsal cingulate--the anterior midcingulate cortex (aMCC). Anatomical studies reveal that the aMCC constitutes a hub where information about reinforcers can be linked to motor centres responsible for expressing affect and executing goal-directed behaviour. Computational modelling and other kinds of evidence suggest that this intimacy reflects control processes that are common to all three domains. These observations compel a reconsideration of the dorsal cingulate's contribution to negative affect and pain.