How (not) to demonstrate unconscious priming: Overcoming issues with post-hoc data selection, low power, and frequentist statistics.

One widely used scientific approach to studying consciousness involves contrasting conscious operations with unconscious ones. However, challenges in establishing the absence of conscious awareness have led to debates about the extent and existence of unconscious processes. We collected experimental data on unconscious semantic priming, manipulating prime presentation duration to highlight the critical role of the analysis approach in attributing priming effects to unconscious processing. We demonstrate that common practices like post-hoc data selection, low statistical power, and frequentist statistical testing can erroneously support claims of unconscious priming. Conversely, adopting best practices like direct performance-awareness contrasts, Bayesian tests, and increased statistical power can prevent such erroneous conclusions. Many past experiments, including our own, fail to meet these standards, casting doubt on previous claims about unconscious processing. Implementing these robust practices will enhance our understanding of unconscious processing and shed light on the functions and neural mechanisms of consciousness.

A disinhibitory circuit mechanism explains a general principle of peak performance during mid-level arousal.

Perceptual decision-making is highly dependent on the momentary arousal state of the brain, which fluctuates over time on a scale of hours, minutes, and even seconds. The textbook relationship between momentary arousal and task performance is captured by an inverted U-shape, as put forward in the Yerkes-Dodson law. This law suggests optimal performance at moderate levels of arousal and impaired performance at low or high arousal levels. However, despite its popularity, the evidence for this relationship in humans is mixed at best. Here, we use pupil-indexed arousal and performance data from various perceptual decision-making tasks to provide converging evidence for the inverted U-shaped relationship between spontaneous arousal fluctuations and performance across different decision types (discrimination, detection) and sensory modalities (visual, auditory). To further understand this relationship, we built a neurobiologically plausible mechanistic model and show that it is possible to reproduce our findings by incorporating two types of interneurons that are both modulated by an arousal signal. The model architecture produces two dynamical regimes under the influence of arousal: one regime in which performance increases with arousal and another regime in which performance decreases with arousal, together forming an inverted U-shaped arousal-performance relationship. We conclude that the inverted U-shaped arousal-performance relationship is a general and robust property of sensory processing. It might be brought about by the influence of arousal on two types of interneurons that together act as a disinhibitory pathway for the neural populations that encode the available sensory evidence used for the decision.

Catecholaminergic neuromodulation and selective attention jointly shape perceptual decision-making.

Perceptual decisions about sensory input are influenced by fluctuations in ongoing neural activity, most prominently driven by attention and neuromodulator systems. It is currently unknown if neuromodulator activity and attention differentially modulate perceptual decision-making and/or whether neuromodulatory systems in fact control attentional processes. To investigate the effects of two distinct neuromodulatory systems and spatial attention on perceptual decisions, we pharmacologically elevated cholinergic (through donepezil) and catecholaminergic (through atomoxetine) levels in humans performing a visuo-spatial attention task, while we measured electroencephalography (EEG). Both attention and catecholaminergic enhancement improved decision-making at the behavioral and algorithmic level, as reflected in increased perceptual sensitivity and the modulation of the drift rate parameter derived from drift diffusion modeling. Univariate analyses of EEG data time-locked to the attentional cue, the target stimulus, and the motor response further revealed that attention and catecholaminergic enhancement both modulated pre-stimulus cortical excitability, cue- and stimulus-evoked sensory activity, as well as parietal evidence accumulation signals. Interestingly, we observed both similar, unique, and interactive effects of attention and catecholaminergic neuromodulation on these behavioral, algorithmic, and neural markers of the decision-making process. Thereby, this study reveals an intricate relationship between attentional and catecholaminergic systems and advances our understanding about how these systems jointly shape various stages of perceptual decision-making.

Predictions and rewards affect decision-making but not subjective experience.

To survive, organisms constantly make decisions to avoid danger and maximize rewards in information-rich environments. As a result, decisions about sensory input are not only driven by sensory information but also by other factors, such as the expected rewards of a decision (known as the payoff matrix) or by information about temporal regularities in the environment (known as cognitive priors or predictions). However, it is unknown to what extent these different types of information affect subjective experience or whether they merely result in nonperceptual response criterion shifts. To investigate this question, we used three carefully matched manipulations that typically result in behavioral shifts in decision criteria: a visual illusion (Müller-Lyer condition), a punishment scheme (payoff condition), and a change in the ratio of relevant stimuli (base rate condition). To gauge shifts in subjective experience, we introduce a task in which participants not only make decisions about what they have just seen but are also asked to reproduce their experience of a target stimulus. Using Bayesian ordinal modeling, we show that each of these three manipulations affects the decision criterion as intended but that the visual illusion uniquely affects sensory experience as measured by reproduction. In a series of follow-up experiments, we use computational modeling to show that although the visual illusion results in a distinct drift-diffusion (DDM) parameter profile relative to nonsensory manipulations, reliance on DDM parameter estimates alone is not sufficient to ascertain whether a given manipulation is perceptual or nonperceptual.

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 Scientific Study of Consciousness Cannot and Should Not Be Morally Neutral.

A target question for the scientific study of consciousness is how dimensions of consciousness, such as the ability to feel pain and pleasure or reflect on one's own experience, vary in different states and animal species. Considering the tight link between consciousness and moral status, answers to these questions have implications for law and ethics. Here we point out that given this link, the scientific community studying consciousness may face implicit pressure to carry out certain research programs or interpret results in ways that justify current norms rather than challenge them. We show that because consciousness largely determines moral status, the use of nonhuman animals in the scientific study of consciousness introduces a direct conflict between scientific relevance and ethics-the more scientifically valuable an animal model is for studying consciousness, the more difficult it becomes to ethically justify compromises to its well-being for consciousness research. Finally, in light of these considerations, we call for a discussion of the immediate ethical corollaries of the body of knowledge that has accumulated and for a more explicit consideration of the role of ideology and ethics in the scientific study of consciousness.

An academic survey on theoretical foundations, common assumptions and the current state of consciousness science.

We report the results of an academic survey into the theoretical and methodological foundations, common assumptions, and the current state of the field of consciousness research. The survey consisted of 22 questions and was distributed on two different occasions of the annual meeting of the Association of the Scientific Study of Consciousness (2018 and 2019). We examined responses from 166 consciousness researchers with different backgrounds (e.g. philosophy, neuroscience, psychology, and computer science) and at various stages of their careers (e.g. junior/senior faculty and graduate/undergraduate students). The results reveal that there remains considerable discussion and debate between the surveyed researchers about the definition of consciousness and the way it should be studied. To highlight a few observations, a majority of respondents believe that machines could have consciousness, that consciousness is a gradual phenomenon in the animal kingdom, and that unconscious processing is extensive, encompassing both low-level and high-level cognitive functions. Further, we show which theories of consciousness are currently considered most promising by respondents and how supposedly different theories cluster together, which dependent measures are considered best to index the presence or absence of consciousness, and which neural measures are thought to be the most likely signatures of consciousness. These findings provide us with a snapshot of the current views of researchers in the field and may therefore help prioritize research and theoretical approaches to foster progress.

Attenuated alpha oscillation and hyperresponsiveness reveals impaired perceptual learning in migraineurs.

BACKGROUND: Anomalous phantom visual perceptions coupled to an aversion and discomfort to some visual patterns (especially grating in mid-range spatial frequency) have been associated with the hyperresponsiveness in migraine patients. Previous literature has found fluctuations of alpha oscillation (8-14 Hz) over the visual cortex to be associated with the gating of the visual stream. In the current study, we examined whether alpha activity was differentially modulated in migraineurs in anticipation of an upcoming stimulus as well as post-stimulus periods. METHODS: We used EEG to examine the brain activity in a group of 28 migraineurs (17 with aura /11 without) and 29 non-migraineurs and compared their alpha power in the pre/post-stimulus period relative to the onset of stripped gratings. RESULTS: Overall, we found that migraineurs had significantly less alpha power prior to the onset of the stimulus relative to controls. Moreover, migraineurs had significantly greater post-stimulus alpha suppression (i.e event-related desynchronization) induced by the grating in 3 cycles per degree at the 2nd half of the experiment. CONCLUSIONS: These findings, taken together, provide strong support for the presence of the hyperresponsiveness of the visual cortex of migraine sufferers. We speculate that it could be the consequence of impaired perceptual learning driven by the dysfunction of GABAergic inhibitory mechanism.

Broadband Dynamics Rather than Frequency-Specific Rhythms Underlie Prediction Error in the Primate Auditory Cortex.

Detection of statistical irregularities, measured as a prediction error response, is fundamental to the perceptual monitoring of the environment. We studied whether prediction error response is associated with neural oscillations or asynchronous broadband activity. Electrocorticography was conducted in three male monkeys, who passively listened to the auditory roving oddball stimuli. Local field potentials (LFPs) recorded over the auditory cortex underwent spectral principal component analysis, which decoupled broadband and rhythmic components of the LFP signal. We found that the broadband component captured the prediction error response, whereas none of the rhythmic components were associated with statistical irregularities of sounds. The broadband component displayed more stochastic, asymmetrical multifractal properties than the rhythmic components, which revealed more self-similar dynamics. We thus conclude that the prediction error response is captured by neuronal populations generating asynchronous broadband activity, defined by irregular dynamic states, which, unlike oscillatory rhythms, appear to enable the neural representation of auditory prediction error response.SIGNIFICANCE STATEMENT This study aimed to examine the contribution of oscillatory and asynchronous components of auditory local field potentials in the generation of prediction error responses to sensory irregularities, as this has not been directly addressed in the previous studies. Here, we show that mismatch negativity-an auditory prediction error response-is driven by the asynchronous broadband component of potentials recorded in the auditory cortex. This finding highlights the importance of nonoscillatory neural processes in the predictive monitoring of the environment. At a more general level, the study demonstrates that stochastic neural processes, which are often disregarded as neural noise, do have a functional role in the processing of sensory information.

Preserved sensory processing but hampered conflict detection when stimulus input is task-irrelevant.

Conflict detection in sensory input is central to adaptive human behavior. Perhaps unsurprisingly, past research has shown that conflict may even be detected in the absence of conflict awareness, suggesting that conflict detection is an automatic process that does not require attention. To test the possibility of conflict processing in the absence of attention, we manipulated task relevance and response overlap of potentially conflicting stimulus features across six behavioral tasks. Multivariate analyses on human electroencephalographic data revealed neural signatures of conflict only when at least one feature of a conflicting stimulus was attended, regardless of whether that feature was part of the conflict, or overlaps with the response. In contrast, neural signatures of basic sensory processes were present even when a stimulus was completely unattended. These data reveal an attentional bottleneck at the level of objects, suggesting that object-based attention is a prerequisite for cognitive control operations involved in conflict detection.

Focusing your attention on one thing can leave you surprisingly unaware of what goes on around you. A classic experiment known as 'the invisible gorilla' highlights this phenomenon. Volunteers were asked to watch a clip featuring basketball players, and count how often those wearing white shirts passed the ball: around half of participants failed to spot that someone wearing a gorilla costume wandered into the game and spent nine seconds on screen. Yet, things that you are not focusing on can sometimes grab your attention anyway. Take for example, the 'cocktail party effect', the ability to hear your name among the murmur of a crowded room. So why can we react to our own names, but fail to spot the gorilla? To help answer this question, Nuiten et al. examined how paying attention affects the way the brain processes input. Healthy volunteers were asked to perform various tasks while the words 'left' or 'right' played through speakers. The content of the word was sometimes consistent with its location ('left' being played on the left speaker), and sometimes opposite ('left' being played on the right speaker). Processing either the content or the location of the word is relatively simple for the brain; however detecting a discrepancy between these two properties is challenging, requiring the information to be processed in a brain region that monitors conflict in sensory input. To manipulate whether the volunteers needed to pay attention to the words, Nuiten et al. made their content or location either relevant or irrelevant for a task. By analyzing brain activity and task performance, they were able to study the effects of attention on how the word properties were processed. The results showed that the volunteers' brains were capable of dealing with basic information, such as location or content, even when their attention was directed elsewhere. But discrepancies between content and location could only be detected when the volunteers were focusing on the words, or when their content or location was directly relevant to the task. The findings by Nuiten et al. suggest that while performing a difficult task, our brains continue to react to basic input but often fail to process more complex information. This, in turn, has implications for a range of human activities such as driving. New technology could potentially help to counteract this phenomenon, aiming to direct attention towards complex information that might otherwise be missed.

The human visual system differentially represents subjectively and objectively invisible stimuli.

The study of unconscious processing requires a measure of conscious awareness. Awareness measures can be either subjective (based on participant's report) or objective (based on perceptual performance). The preferred awareness measure depends on the theoretical position about consciousness and may influence conclusions about the extent of unconscious processing and about the neural correlates of consciousness. We obtained functional magnetic resonance imaging (fMRI) measurements from 43 subjects while they viewed masked faces and houses that were either subjectively or objectively invisible. Even for objectively invisible (perceptually indiscriminable) stimuli, we found significant category information in both early, lower-level visual areas and in higher-level visual cortex, although representations in anterior, category-selective ventrotemporal areas were less robust. For subjectively invisible stimuli, similar to visible stimuli, there was a clear posterior-to-anterior gradient in visual cortex, with stronger category information in ventrotemporal cortex than in early visual cortex. For objectively invisible stimuli, however, category information remained virtually unchanged from early visual cortex to object- and category-selective visual areas. These results demonstrate that although both objectively and subjectively invisible stimuli are represented in visual cortex, the extent of unconscious information processing is influenced by the measurement approach. Furthermore, our data show that subjective and objective approaches are associated with different neural correlates of consciousness and thus have implications for neural theories of consciousness.

High-pass filtering artifacts in multivariate classification of neural time series data.

BACKGROUND: Traditionally, EEG/MEG data are high-pass filtered and baseline-corrected to remove slow drifts. Minor deleterious effects of high-pass filtering in traditional time-series analysis have been well-documented, including temporal displacements. However, its effects on time-resolved multivariate pattern classification analyses (MVPA) are largely unknown. NEW METHOD: To prevent potential displacement effects, we extend an alternative method of removing slow drift noise - robust detrending - with a procedure in which we mask out all cortical events from each trial. We refer to this method as trial-masked robust detrending. RESULTS: In both real and simulated EEG data of a working memory experiment, we show that both high-pass filtering and standard robust detrending create artifacts that result in the displacement of multivariate patterns into activity silent periods, particularly apparent in temporal generalization analyses, and especially in combination with baseline correction. We show that trial-masked robust detrending is free from such displacements. COMPARISON WITH EXISTING METHOD(S): Temporal displacement may emerge even with modest filter cut-off settings such as 0.05 Hz, and even in regular robust detrending. However, trial-masked robust detrending results in artifact-free decoding without displacements. Baseline correction may unwittingly obfuscate spurious decoding effects and displace them to the rest of the trial. CONCLUSIONS: Decoding analyses benefit from trial-masked robust detrending, without the unwanted side effects introduced by filtering or regular robust detrending. However, for sufficiently clean data sets and sufficiently strong signals, no filtering or detrending at all may work adequately. Implications for other types of data are discussed, followed by a number of recommendations.

Criteria for empirical theories of consciousness should focus on the explanatory power of mechanisms, not on functional equivalence.

Doerig and colleagues put forward the notion that we need hard and theory-neutral criteria by which to arbitrate between empirical (mechanistic) theories of consciousness. However, most of the criteria that they propose are not theory neutral because they focus on functional equivalence between systems. Because empirical theories of consciousness are mechanistic rather than functionalist, we think these criteria are not helpful when arbitrating between them.

Multivariate analysis of EEG activity indexes contingent attentional capture.

An extensive body of work has shown that attentional capture is contingent on the goals of the observer: Capture is strongly reduced or even eliminated when an irrelevant singleton stimulus does not match the target-defining properties (Folk et al., 1992). There has been a long-standing debate on whether attentional capture can be explained by goal-driven and/or stimulus-driven accounts. Here, we shed further light on this matter by using EEG activity (raw EEG and alpha power) to provide a time-resolved index of attentional orienting towards salient stimuli that either matched or did not match target-defining properties. A search display containing the target stimulus was preceded by a spatially uninformative singleton cue that either matched the color of the upcoming target (contingent cues), or that appeared in an irrelevant color (non-contingent cues). Multivariate analysis of raw EEG and alpha power revealed preferential tuning to the location of both contingent and non-contingent cues, with a stronger bias towards contingent than non-contingent cues. The time course of these effects, however, depended on the neural signal. Raw EEG data revealed attentional orienting towards the contingent cue early on in the trial (>156 ms), while alpha power revealed sustained spatial selection in the cued locations at a later moment in the trial (>250 ms). Moreover, while raw EEG showed stronger capture by contingent cues during this early time window, an advantage for contingent cues arose during a later time window in alpha band activity. Thus, our findings suggest that raw EEG activity and alpha-band power tap into distinct neural processes that index separate aspects of covert spatial attention.

An investigation of how relative precision of target encoding influences metacognitive performance.

Detection failures in perceptual tasks can result from different causes: sometimes we may fail to see something because perceptual information is noisy or degraded, and sometimes we may fail to see something due to the limited capacity of attention. Previous work indicates that metacognitive capacities for detection failures may differ depending on the specific stimulus visibility manipulation employed. In this investigation, we measured metacognition while matching performance in two visibility manipulations: phase-scrambling and the attentional blink. As in previous work, metacognitive asymmetries emerged: despite matched type 1 performance, metacognitive ability (measured by area under the ROC curve) for reporting stimulus absence was higher in the attentional blink condition, which was mainly driven by metacognitive ability in correct rejection trials. We performed Signal Detection Theoretic (SDT) modeling of the results, showing that differences in metacognition under equal type I performance can be explained when the variance of the signal and noise distributions are unequal. Specifically, the present study suggests that phase scrambling signal trials have a wider distribution (more variability) than attentional blink signal trials, leading to a larger area under the ROC curve for attentional blink trials where subjects reported stimulus absence. These results provide a theoretical basis for the origin of metacognitive differences on trials where subjects report stimulus absence, and may also explain previous findings where the absence of evidence during detection tasks results in lower metacognitive performance when compared to categorization.

Decreased Alertness Reconfigures Cognitive Control Networks.

Humans' remarkable capacity to flexibly adapt their behavior based on rapid situational changes is termed cognitive control. Intuitively, cognitive control is thought to be affected by the state of alertness; for example, when drowsy, we feel less capable of adequately implementing effortful cognitive tasks. Although scientific investigations have focused on the effects of sleep deprivation and circadian time, little is known about how natural daily fluctuations in alertness in the regular awake state affect cognitive control. Here we combined a conflict task in the auditory domain with EEG neurodynamics to test how neural and behavioral markers of conflict processing are affected by fluctuations in alertness. Using a novel computational method, we segregated alert and drowsy trials from two testing sessions and observed that, although participants (both sexes) were generally sluggish, the typical conflict effect reflected in slower responses to conflicting information compared with nonconflicting information, as well as the moderating effect of previous conflict (conflict adaptation), were still intact. However, the typical neural markers of cognitive control-local midfrontal theta-band power changes-that participants show during full alertness were no longer noticeable when alertness decreased. Instead, when drowsy, we found an increase in long-range information sharing (connectivity) between brain regions in the same frequency band. These results show the resilience of the human cognitive control system when affected by internal fluctuations of alertness and suggest that there are neural compensatory mechanisms at play in response to physiological pressure during diminished alertness.SIGNIFICANCE STATEMENT The normal variability in alertness we experience in daily tasks is rarely taken into account in cognitive neuroscience. Here we studied neurobehavioral dynamics of cognitive control with decreasing alertness. We used the classic Simon task where participants hear the word "left" or "right" in the right or left ear, eliciting slower responses when the word and the side are incongruent-the conflict effect. Participants performed the task both while fully awake and while getting drowsy, allowing for the characterization of alertness modulating cognitive control. The changes in the neural signatures of conflict from local theta oscillations to a long-distance distributed theta network suggest a reconfiguration of the underlying neural processes subserving cognitive control when affected by alertness fluctuations.

Boosts in brain signal variability track liberal shifts in decision bias.

Adopting particular decision biases allows organisms to tailor their choices to environmental demands. For example, a liberal response strategy pays off when target detection is crucial, whereas a conservative strategy is optimal for avoiding false alarms. Using conventional time-frequency analysis of human electroencephalographic (EEG) activity, we previously showed that bias setting entails adjustment of evidence accumulation in sensory regions (Kloosterman et al., 2019), but the presumed prefrontal signature of a conservative-to-liberal bias shift has remained elusive. Here, we show that a liberal bias shift is reflected in a more unconstrained neural regime (boosted entropy) in frontal regions that is suited to the detection of unpredictable events. Overall EEG variation, spectral power and event-related potentials could not explain this relationship, highlighting that moment-to-moment neural variability uniquely tracks bias shifts. Neural variability modulation through prefrontal cortex appears instrumental for permitting an organism to adapt its biases to environmental demands.

Frontal cortex differentiates between free and imposed target selection in multiple-target search.

Cognitive control can involve proactive (preparatory) and reactive (corrective) mechanisms. Using a gaze-contingent eye tracking paradigm combined with fMRI, we investigated the involvement of these different modes of control and their underlying neural networks, when switching between different targets in multiple-target search. Participants simultaneously searched for two possible targets presented among distractors, and selected one of them. In one condition, only one of the targets was available in each display, so that the choice was imposed, and reactive control would be required. In the other condition, both targets were present, giving observers free choice over target selection, and allowing for proactive control. Switch costs emerged only when targets were imposed and not when target selection was free. We found differential levels of activity in the frontoparietal control network depending on whether target switches were free or imposed. Furthermore, we observed core regions of the default mode network to be active during target repetitions, indicating reduced control on these trials. Free and imposed switches jointly activated parietal and posterior frontal cortices, while free switches additionally activated anterior frontal cortices. These findings highlight unique contributions of proactive and reactive control during visual search.

EEG dynamics reveal a dissociation between storage and selective attention within working memory.

Selective attention plays a prominent role in prioritizing information in working memory (WM), improving performance for attended representations. However, it remains unclear whether unattended WM representations suffer from information loss. Here we tested the hypothesis that within WM, selectively attending to an item and stopping storing other items are independent mechanisms. We recorded EEG while participants performed a WM recall task in which the item most likely to be tested was cued retrospectively during retention. By manipulating retro-cue reliability (i.e., the ratio of valid to invalid cue trials), we varied the incentive to retain non-cued items. Storage and selective attention in WM were measured during the retention interval by contralateral delay activity (CDA) and contralateral alpha power suppression, respectively. Soon after highly reliable cues, the cued item was attended, and non-cued items suffered information loss. However, for less reliable cues, initially the cued item was attended, but unattended items were kept in WM. Later during the delay, previously unattended items suffered information loss despite now attention being reallocated to their locations, presumably to strengthen their weakening traces. These results show that storage and attention in WM are distinct processes that can behave differently depending on the relative importance of representations.

Humans can efficiently look for but not select multiple visual objects.

The human brain recurrently prioritizes task-relevant over task-irrelevant visual information. A central question is whether multiple objects can be prioritized simultaneously. To answer this, we let observers search for two colored targets among distractors. Crucially, we independently varied the number of target colors that observers anticipated, and the number of target colors actually used to distinguish the targets in the display. This enabled us to dissociate the preparation of selection mechanisms from the actual engagement of such mechanisms. Multivariate classification of electroencephalographic activity allowed us to track selection of each target separately across time. The results revealed only small neural and behavioral costs associated with preparing for selecting two objects, but substantial costs when engaging in selection. Further analyses suggest this cost is the consequence of neural competition resulting in limited parallel processing, rather than a serial bottleneck. The findings bridge diverging theoretical perspectives on capacity limitations of feature-based attention.