404079 079van Gaal and LammeThe Neuroscientist

NROXXX10.1177/1073858411404

Review

Unconscious High-Level Information Processing: Implication for Neurobiological Theories of Consciousness

The Neuroscientist XX(X) 1­–15 © The Author(s) 2011 Reprints and permission: http://www. sagepub.com/journalsPermissions.nav DOI: 10.1177/1073858411404079 http://nro.sagepub.com

Simon van Gaal1,2,3 and Victor A. F. Lamme1,4

Abstract Theories about the neural correlates and functional relevance of consciousness have traditionally assigned a crucial role to the prefrontal cortex in generating consciousness as well as in orchestrating high-level conscious control over behavior. However, recent neuroscientific findings show that prefrontal cortex can be activated unconsciously. The depth, direction, and scope of these activations depend on several top-down factors such as the task being probed (task-set, strategy) and on (temporal/spatial) attention. Regardless, such activations—when mediated by feedforward activation only—do not lead to a conscious sensation. Although unconscious, these prefrontal activations are functional, in the sense that they are associated with behavioral effects of cognitive control, such as response inhibition, task switching, conflict monitoring, and error detection. These findings challenge the pivotal role of the prefrontal cortex in consciousness. Instead, it appears that specific brain areas (or cognitive modules) may support specific cognitive functions but that consciousness is independent of this. Conscious sensations arise only when the brain areas involved engage in recurrent interactions enabling the long-lasting exchange of information between brain regions. Moreover, recent evidence suggests that also the state of consciousness, for example, in vegetative state patients or during sleep and anesthesia, is closely related to the scope and extent of residual recurrent interactions among brain regions. Keywords consciousness, unconscious processes, feedforward sweep, recurrent processing, cognitive control Common sense suggests that our choices are primarily influenced by consciously perceived information, which can be used to cautiously weigh available options to make an optimal decision. However, scientific data suggest otherwise. Carefully developed experiments on braindamaged patients as well as healthy volunteers have revealed that at least part of our everyday behaviors probably unfold entirely automatically and unconsciously, without requiring any conscious or voluntary control. This suggests that there is a distinction between absorbing and acting on—say—visual information, versus consciously seeing. Accepting this idea has consequences. It immediately brings to mind the question whether all cognitive and neural operations are initiated unconsciously or whether this might only be the case for highly trained (e.g., driving a car) or very “simple” behaviors (e.g., specific motor responses). Maybe very complex cognitive operations do require consciousness. In the present review we focus on behavioral and neuroimaging studies that examined the scope and limits of unconscious information processing. Besides understanding the role of unconscious processes in our everyday behavior

and decisions, these studies might eventually help us to understand the neural mechanisms and (potential) function of consciousness.

Loss of Consciousness in Brain-Damaged Patients Sometimes consciousness is lost because of brain damage. For example, when people suffer from damage to the primary visual cortex (V1), they lose their ability to 1

Cognitive Neuroscience Group, Department of Psychology, University of Amsterdam, Amsterdam, the Netherlands 2 Inserm, Cognitive Neuroimaging Unit, Gif-sur-Yvette, France 3 Commissarìat à l’Energie Atomique, Neurospin Center, Gif-sur-Yvette, France 4 Cognitive Science Center, University of Amsterdam, Amsterdam, the Netherlands Corresponding Author: Simon van Gaal, INSERM, Cognitive Neuroimaging Unit, Gif sur Yvette, France Email: [email protected]

Downloaded from nro.sagepub.com at Universiteit van Amsterdam SAGE on June 2, 2011

2

The Neuroscientist XX(X)

detect visual stimuli presented in the visual hemifield contralateral to their lesion. Notwithstanding the lack of conscious experience, some of these patients are still able to categorize or respond to stimuli presented in the blind part of their visual field when asked for a forced-choice response (often to their own surprise). Such “blindsight” patients have, for example, been shown to be able to track moving stimuli, point to objects, classify the color of stimuli, and recognize facial expressions in their “blind” hemifield (for review, see Cowey 2010). Further, it has been shown that unconscious emotional stimuli—threatening (Vuilleumier and others 2003) as well as nonthreatening (Williams and Mattingley 2004)—are still processed and even trigger fast bodily reactions in (affective) blindsight (Tamietto and others 2009). The patients themselves often claim to have no conscious awareness at all of any of these features. These results reveal that a substantial amount of perceptual processing can occur in absence of consciousness yet influence behavior, probably via subcortical processing routes bypassing V1. Similar conclusions can be drawn for other awarenessrelated clinical syndromes. Unilateral damage to a variety of cortical and subcortical regions, particularly the parietal and frontal cortex and the thalamus in the right hemisphere, sometimes leads to deficit in reporting or attending to stimuli presented in the contralesional visual field, a clinical syndrome called (unilateral spatial) neglect. Some of these patients are unable to report stimuli that are presented in the left visual field when these are presented together with other stimuli in the unaffected right visual field; however, when the same stimuli are presented in isolation they can be consciously reported (visual extinction). Although these patients are unable to report about the stimuli presented in their neglected part of their outside world, it has been shown that neglected information is still processed at several levels in the processing hierarchy (Driver and Mattingley 1998; Rees and others 2000), as evidenced by the processing of faces or other objects (Rees, Wojciulik, and others 2002; Vuilleumier and others 2003), semantics (Rusconi and others 2006; Sackur and others 2008), emotions (Vuilleumier and others 2002), and even visual illusions in their neglected visual field (Vuilleumier and others 2001). Overall, these and other seminal patient studies have established one important issue: there is extensive neural and cognitive processing in the absence of consciousness. Further evidence for the unconscious processing of information is derived from studies on healthy participants.

Manipulating Consciousness in Healthy Subjects To explore conscious and unconscious influences on perception and cognition in healthy people, cognitive

Figure 1. Typical masking paradigms. An exemplary sequence of events in (a) a metacontrast masking task and a pattern masking task (b).

scientists have designed many experimental protocols in which the perception of a (visual) stimulus is carefully manipulated. In a laboratory setting, masking is the most common and productive method of choice. In typical backward masking experiments (Fig. 1a), participants have to quickly respond to a target (e.g., a large arrow contour) that is rapidly preceded (<100 ms) by another stimulus (e.g., a small arrow), the so-called prime. Because the prime is presented very briefly and fits within the contour of the target (the metacontrast “mask”), its visibility is strongly reduced (Breitmeyer and Ogmen 2006; Klotz and Neumann 1999). Under the right conditions the prime can even be impossible to see. Importantly, the same briefly presented stimulus is perfectly visible when presented in isolation. Even fully masked and hence unconscious stimuli can still influence perceptual and behavioral processes, as evidenced by faster response times and fewer errors when the prime and the target are pointing in the same direction (congruent trials) than when they are pointing in different directions (incongruent trials). Apparently, the direction of the prime-arrow can activate a corresponding response tendency in the absence of conscious awareness of the stimulus itself. The masked priming task can also be performed by using slightly more abstract stimuli, such as words or numbers. For instance, in the task depicted in Fig. 1b, participants have to respond to target numbers larger than five with their right hand and to target numbers smaller than five with their left hand. Before each target a prime number is presented. Because the prime number is presented briefly and sandwiched between random letter strings, it cannot be perceived consciously (a phenomenon termed pattern masking). Again, participants are faster and produce fewer errors to congruent prime-target pairs than to incongruent ones, indicating that, also at a slightly more abstract level, unconscious information is able to influence our behavior. These effects are still observed when the prime is a written word (e.g., six) and

Downloaded from nro.sagepub.com at Universiteit van Amsterdam SAGE on June 2, 2011

3

van Gaal and Lamme

Figure 2. Conscious and unconscious processing of words. (a) When a word is briefly presented and is preceded and followed by blank screens, the word is visible (left panel). However, when a set of randomly oriented squares (the mask) is presented just before and after the word, it becomes invisible (right panel). (b) fMRI activations to visible (visible word vs. blank) and invisible words (masked word vs. blank). Adapted by permission from Macmillan Publishers Ltd: Nature Neuroscience (Dehaene and others), copyright (2001).

the target an Arabic digit (e.g., 1) and vice versa. Although sometimes debated (Damian 2001), these results suggest that priming depends on the prime-target similarity at the semantic level. These unconsciously triggered action tendencies can be recorded in the corresponding motor cortex, the final cortical stage of the motor execution program (Dehaene and others 1998), revealing that masked stimuli are able to penetrate all the way up to the motor cortex, without eliciting a conscious percept. Specific regions in the parietal cortex seem to code for the actual quantity of unconsciously presented numbers (Naccache and Dehaene 2001). Accumulating evidence suggests that unconscious information can in fact be processed extensively in a broad range of brain regions. To illustrate, Dehaene and colleagues (2001) briefly flashed words on a computer screen that were either masked or not. Therefore, in one condition these words were perfectly visible (because of the absence of forward and backward masks), whereas in another condition the words were not. Unconscious words still activated cortical regions in the left fusiform cortex, known as the visual word form area (see Fig 2), and the precentral cortex (but see Diaz and McCarthy

2007 for more extensive unconscious activations in a similar task). In contrast, conscious words triggered a large-scale neural network of brain regions, including areas in visual, parietal, and frontal cortex (see also GrillSpector and others 2000). Interestingly, repetition priming, the phenomenon that the Bold signal attenuates upon repetition of the same object (Grill-Spector and Malach 2001), is present in the visual word form area when a word is repeated in a different case (e.g., NOTE–note) or even in a different script, as observed when words were presented in either Kanji or Kana in Japanese speakers (Nakamura and others 2005). Follow-up studies have revealed a hierarchical organization of this region. In its most posterior part, masked repetition priming depends on single letters at a specific location, whereas increasingly more anterior priming becomes more location invariant and in its most anterior part whole words might become encoded (Dehaene and others 2004; Dehaene and others 2001). Interestingly, activity in this region is modulated even when different words with the same meaning are repeated (e.g., idea-notion; Devlin and others 2004) or when words are handwritten and therefore difficult to decipher (Qiao and others 2010). Further evidence for extensive unconscious semantic processing comes from a series of studies on the N400 event-related potential (ERP) component. The N400 is a well-known ERP component dominant over centroparietal electrode sites and is thought to reflect semantic processing (Lau and others 2008). ERP studies have shown that when a masked word (e.g., table) is rapidly followed by a related conscious target word (chair), it elicits a smaller N400 than when the same prime word is followed by an unrelated conscious target word (dog) (Deacon and others 2000; Kiefer and Spitzer 2000). Similar results have been obtained when one word was presented during the attentional blink (Luck and others 1996; Rolke and others 2001). In this respect, it should be noted that some authors have not found N400 modulations to unconscious stimuli, probably because of a relatively long temporal interval between stimuli in those studies (e.g., Brown and Hagoort 1993; Kiefer and Spitzer 2000), highlighting the fleeting nature of unconscious representations. Recently, there has been an explosion of demonstrations of unconscious information processing at various levels of the cortical hierarchy. To illustrate, it has been shown that the orientation of a stimulus can be decoded from activity in V1, even when heavy masking prevents subjects from consciously perceiving the stimulus (Haynes and Rees 2005). Further, as has been shown in brain-damaged patients, unconscious emotional material activates several nodes in the emotional circuit, most prominently the amygdala (Naccache and others 2005; Tamietto and de Gelder 2010; Whalen and others 2004) but possibly also the orbitofrontal cortex (Vuilleumier

Downloaded from nro.sagepub.com at Universiteit van Amsterdam SAGE on June 2, 2011

4

The Neuroscientist XX(X)

and others 2002). Extrastriate visual cortex can be activated unconsciously by material other than words, as evidenced by imaging studies using face or house pictures, activating the fusiform face area (FFA) and parahippocampal place area (PPA) in the ventral stream, respectively (Kouider and others 2009; Sterzer and others 2008). Masked pictures of tools activate cortical regions along the dorsal visual stream (including V3a, V7, and the intraparietal sulcus), probably because these regions are important for the manual handling of such devices (Fang and He 2005). The human reward circuit can be influenced by unconscious visual stimuli, which can subsequently bias our decisions and motivations. Pessiglione and colleagues (2007) showed that masked monetary incentives (a pound or a penny) activated the basal ganglia and increased the effort put into the task at hand when there was more money at stake (see also Aarts and others 2008; Bijleveld and others 2010). Somewhat later those investigators showed that subjects can unconsciously learn to associate one stimulus with reward and another stimulus with loss in a decision-making experiment. Even without the conscious processing of these cues (because of heavy masking), the brain actually used this information to bias decision making about whether to play or not in a sort of lottery (Pessiglione and others 2008). Although the majority of studies into unconscious perception are performed in the visual domain, unconscious priming effects extend beyond vision. For example, when spoken words are masked by random speech sounds, repetition priming effects can be observed in the auditory and insular cortex for unconscious (masked) words that are followed by the same conscious target word compared with unconscious words followed by an unrelated target word (Kouider and others 2010). Similarly, undetected thresholdlevel auditory noise activates the auditory cortex (Sadaghiani and others 2009), and unperceived tactile stimuli have been shown to modulate neural responses in the somatosensory cortex (Palva and others 2005). Overall, the results reviewed above paint a picture of local and specific effects of unconscious information on many subcortical and posterior brain areas, with increasingly more complex operations gradually activating more anterior regions. Although this neural activation in itself is insufficient to elicit a conscious percept, it is functional and capable of influencing many perceptual, emotional, motivational, motor, and decision-related processes.

Top-Down Modulations on Unconscious Information Processing Is the unconscious activation of brain structures fully automatic, or, alternatively, is it “smarter” and sensitive

to top-down cognitive processes, such as attention, strategy, and task-set? Although it has been assumed for a long time that unconscious process were rather automatic and inflexible (see Hommel 2007 for a review), recent studies demonstrated otherwise. For example, temporal attention and spatial attention play crucial roles in the impact that stimuli have on behavior and brain activity, and, importantly, this is true for conscious as well as unconscious stimuli. In a seminal study, Naccache and others (2002) showed that the magnitude of the masked number priming effect depended on the extent to which participants can predict when in time a prime-target pair will be presented. Recently, these results have been replicated by several others (Fabre and others 2007; Kiefer and Brendel 2006), highlighting the crucial role of temporal attention on unconscious information processing. The same is true for spatial attention. When a masked stimulus is presented at an attended location, the subsequent impact on the response to the visible target is larger than when attention is allocated elsewhere. This has been demonstrated in normal subjects (Bahrami and others 2007; Finkbeiner and Palermo 2009; Kentridge and others 2008; Kiefer and Brendel 2006; Marzouki and others 2007; Sumner and others 2006) as well as blindsight patients (Kentridge and others 1999, 2004). Not only does attention bias the unconscious processing of information, but even attention itself can be attracted unconsciously (for review, see Mulckhuyse and Theeuwes 2010). To illustrate, Jiang and colleagues (2006) showed masked erotic pictures of women or men left or right of fixation to male and female subjects. Behavioral results showed the attentional capture to male pictures for female (heterosexual) subjects and attentional capture to female pictures for male (heterosexual) subjects. Threatening (Lin and others 2009) or emotional stimuli (Vuilleumier and Schwartz 2001) as well as eye gaze directions (Sato and others 2007) can capture our attention outside the scope of awareness. Lower-level stimulus attributes, such as subliminal 50-Hz flicker (Bauer and others 2009) or subliminal orientation (Rajimerhr 2004), are also able to do so. Besides attention, a top-down task-set further determines the extent and scope of unconscious information processing. In a study performed by Nakamura and others (2007), participants viewed a sequence of events, consisting of forward masks, a word prime, a backward mask, and finally a visible target. Participants either had to read aloud the visible target or had to categorize it as representing natural or artificial objects. Intriguingly, the topdown instructed task-set changed the processing routes taken by the unconscious words in the cortical circuitry for reading (see also Nakamura and others 2006). Along similar lines, Kiefer and Martens (2010) recently showed that the N400 ERP component to unrelated prime-target pairs was enhanced when a semantic task-set was induced

Downloaded from nro.sagepub.com at Universiteit van Amsterdam SAGE on June 2, 2011

5

van Gaal and Lamme immediately before each trial and was attenuated by a perceptual task-set (see also Martens and others 2011). Other behavioral studies have further demonstrated a topdown modulation role of strategy, intentions, and task instructions (e.g., Ansorge and Neumann 2005; Greenwald and others 2003; Kunde and others 2003; Van den Bussche and others 2008). Taken together, accumulating evidence suggests that unconscious processes are much less automatic than previously assumed. They are influenced by various top-down effects such as temporal and spatial attention, cognitive intentions, and strategy, thereby showing that people can exert conscious control over processes that are triggered unconsciously.

Are There Any Limits to Unconscious Information Processing? The above-outlined reports of high-level characteristics of unconscious information processing naturally impose the question whether there are any limits to unconscious cognition. To test this issue, several authors have recently set out to explore whether prefrontal cognitive (control) functions can be activated in the absence of consciousness. The prefrontal cortex is thought to represent the highest level of the cortical hierarchy and is traditionally strongly associated with consciousness and flexible (conscious) control over behavior (Dehaene and Naccache 2001; Hommel 2007; Mayr 2004; Rees, Kreiman, and others 2002; Umilta 1988). Lau and Passingham (2007) used functional MRI to test whether task-set preparation can be triggered unconsciously. In their experiment, participants were cued to perform either a phonological or a semantic judgment on an upcoming word. On each trial, this conscious instruction cue was preceded by a conscious or unconscious prime associated with the same or the alternative task (congruent vs. incongruent trials; for a similar behavioral version of this experiment, see Mattler 2003). By using a U-shaped masking design, the stimulus onset asynchrony (SOA) between prime and instruction cue was longer for unconscious primes than for the conscious primes. Therefore, an unconscious prime had probably more time to evoke its effect than a conscious prime. When participants were unconsciously primed to perform the phonological task, there was increased activity in a cortical network associated with this task (premotor cortex) and decreased activity in the cortical network associated with the semantic task (inferior frontal cortex and middle temporal gyrus) and vice versa. These results demonstrate that task-related neural networks, incorporating prefrontal cortex, can be modulated

unconsciously. Further, the authors showed that unconscious primes triggered stronger activity in the dorsolateral prefrontal cortex compared with conscious primes, irrespective of the specific task being cued. Along similar lines, we and others have recently probed the possibility to trigger inhibitory control unconsciously (Hughes and others 2009; van Gaal, Lamme, and others 2011; van Gaal and others 2008; van Gaal and others 2010; van Gaal and others 2009). Inhibitory control is a rather extreme form of cognitive control that allows people to cancel a planned or already initiated action, and it is probably mediated by a set of regions in the prefrontal cortex and basal ganglia (Aron 2007). In one of our experiments participants had to respond to a visible Go stimulus (a white annulus), unless it was preceded by a NoGo cue (a small white square). In contrast, when the visible Go-annulus was preceded by a Go cue (a small white diamond), subjects were instructed to press the button as fast as possible. By manipulating the duration of the Go/NoGo cue, the duration of the Go-annulus, and the delay between both, on half of the trials the Go/NoGo cue was clearly visible. However, crucially, on the other half of the trials the Go/NoGo cue was not perceived (i.e., unconscious) because the Go-annulus acted as an effective metacontrast mask (Fig. 3a). On these latter trials participants only perceived the Go-annulus and therefore pressed the response button as fast as possible (as instructed). Crucially, unconscious NoGo cues still evoked a slowdown in manual responses to the visible Go–annulus (compared with trials containing an unconscious Go cue), as if participants had attempted to inhibit their response but just failed to do so completely. The fMRI results revealed that unconscious NoGo cues could reach cortical areas involved in inhibitory control, particularly in the pre–supplementary motor area (pre-SMA) and the inferior frontal cortex (IFC), bordering the anterior insula (AI) (van Gaal and others 2010). These activations were truly functional, because the strength of activation in this prefrontal “inhibition network” correlated with the extent of slowdown on the Go annulus. Interestingly, compared with the local and relatively restricted activations triggered by unconscious NoGo cues, response inhibition on conscious NoGo cues was associated with a more extended frontoparietal inhibition network, including dorsolateral and parietal cortex (Fig. 3b). This is in line with many other studies that have showed that the activation pattern elicited by conscious stimuli is generally more widespread than the relatively local (but high-level) activations observed on unconscious stimuli (see also Fig. 2). More recently, we recorded EEG during performance on a stop task in which subjects had to respond to a visible Go stimulus unless it was rapidly followed by a (conscious or unconscious) stop-signal. Although presented

Downloaded from nro.sagepub.com at Universiteit van Amsterdam SAGE on June 2, 2011

6

The Neuroscientist XX(X)

Figure 3. Neural activations triggered by conscious and unconscious NoGo signals. (a) The duration of the diamond/square (Go/ NoGo cue), the duration of the visible metacontrast Go-annulus, and the stimulus onset asynchrony between them were varied. Therefore, the Go-annulus was unsuccessful in masking the preceding Go/NoGo cue on some occasions (conscious cues) but rendered it invisible at others (unconscious cues). Based on the visibility and the configuration of the cue, four conditions were created: trials with 1) a conscious NoGo cue, 2) a conscious Go cue, 3) an unconscious NoGo cue, and 4) an unconscious Go cue. All trials were mixed pseudorandomly in a block. (b) Consciously triggered NoGo inhibition is associated with a (largely rightlateralized) frontoparietal inhibition network, whereas unconsciously triggered NoGo inhibition is associated with more local neural activations in bilateral inferior frontal cortices/anterior insula and the pre–supplementary motor area. Figure adapted with permission from van Gaal and others (2010). Copyright 2010 by the Society for Neuroscience.

after the visible Go stimulus, unconscious stop-signals still slowed down responses to the Go stimulus. This behavioral effect was accompanied by larger prefrontal ERP components (N2 and P3) to unconscious stop-signals compared with a control condition (van Gaal, Lamme, and others 2011). Whether the prefrontal cortex becomes involved unconsciously also depends on the top-down instructed task-set (van Gaal and others 2008). In one experiment, participants were instructed to respond to a visible Go signal (black metacontrast mask) and withhold their response when a NoGo signal preceded it. For one group of subjects, a gray circle served as a NoGo signal, whereas in another group the NoGo signal was a black cross. In both groups, in one condition, a gray circle preceded the Go signal and was perfectly masked (i.e., unconscious). Therefore, the masked gray circle was associated with inhibition in one group (and served as an unconscious NoGo signal) but not in the other (and was task-irrelevant because these subjects had to inhibit to the black cross, see Fig. 4). When Go trials were directly compared with unconscious gray circle trials (both perceptually similar), EEG recordings revealed an early occipital event that represented the visual encoding of the unconscious gray

circle in both experiments. However, crucially, a second frontal event was unique to unconscious NoGo signals (left panel) and shows the subsequent implementation of inhibitory control in the prefrontal cortex. This frontal component correlated strongly with the extent of slowdown observed on trials containing an unconscious NoGo signal. These results clearly show that task-set (or task relevance) boosts the extent and depth to which an unconscious stimulus is processed. This extends previous work which showed that unattended but potentially conscious stimuli, for example, presented during the attentional blink (Sergent and others 2005), are processed less extensively than attended stimuli. Here it was shown that the same is true for fully unconscious stimuli. Interestingly, task-sets can be set up extremely quickly, because even trial-by-trial instructions about the association of a stimulus with either stopping or going can determine whether an unconscious stimulus proceeds all the way up to the prefrontal cortex or whether it dies out along its way up in the cortical hierarchy (Wokke and others, submitted). Further evidence for high-level prefrontal computations comes from studies on conflict monitoring/resolution, a high-level cognitive function, mediated mainly by the medial frontal cortex (MFC), including the anterior

Downloaded from nro.sagepub.com at Universiteit van Amsterdam SAGE on June 2, 2011

7

van Gaal and Lamme

Figure 4. The depth of processing of unconscious information depends on the current task-set. Top panels, experimental design of two Go/NoGo tasks. In one experiment, the unconscious (masked) gray circle was associated with response inhibition (left panel) and served as an unconscious NoGo signal, whereas in the other it was not associated with response inhibition (right panel). Bottom panels show scalp voltage maps of activations evoked by an unconscious gray circle. Task-relevant unconscious NoGo signals evoke two neural events: an early occipital event and a later frontocentral event (left panel). The first event represents the visual encoding of the unconscious stimulus and is also present when the gray circle has no behavioral relevance (right panel). The frontal event is only present when the gray circle is associated with stopping and represents the implementation of inhibitory control in the prefrontal cortex (PFC). Figure adapted with permission from van Gaal and others (2008). Copyright 2008 by the Society for Neuroscience.

cingulate cortex (ACC) and the pre-SMA (Botvinick and others 2001; Carter and van Veen 2007; Ridderinkhof and others 2004). Wolbers and colleagues (2006) studied the strategic control over unconscious conflict by using a task in which they varied the number of trials per block with a congruent and an incongruent prime-target pair. The preSMA was more active in blocks with mostly incongruent trials (in this case, conflict needs to be overcome on many trials) compared with blocks with mostly congruent trials (in which conflict needs to be overcome on only few trials). This suggests that the pre-SMA might have an overarching role in the strategic control over the processing of

unconsciously presented conflicting stimuli. Recently it has been demonstrated that individual differences in preSMA gray-matter density seem to be related to subjects’ ability to overcome conscious and unconscious conflictinducing stimuli in a typical masked priming task (van Gaal, Scholte, and others 2011) (see Fig. 5). These studies suggest that unconscious conflict-inducing stimuli can evoke MFC-related conflict monitoring systems (but see Dehaene and others 2003 for the absence of unconsciously triggered ACC conflict-related activity). Masked priming studies have demonstrated that unconscious primes initially facilitate responses (as

Downloaded from nro.sagepub.com at Universiteit van Amsterdam SAGE on June 2, 2011

8

The Neuroscientist XX(X)

Figure 5. Examples of prefrontal brain regions that have been shown to become activated on unconsciously presented stimuli or during undetected events. From left to right, prefrontal cortex and its involvement in unconsciously triggered task-set preparation (Lau and Passingham 2007), unconsciously evoked response conflict (gray-matter results, van Gaal Scholte, and others 2011), unnoticed response errors (Hester and others 2005), and the undetected violation of implicitly learned sequences (or undetected conflict, Ursu and others 2009). Reprinted with permission from Lau and Passingham 2007 (copyright 2007 from Society for Neuroscience), van Gaal, Sholte, and others 2011 (copyright 2011 MIT Press), Hester and others 2005 (copyright 2005 Elsevier), and Ursu and others 2009 (copyright 2009 Elsevier).

discussed above) but somewhat later, when the delay between prime and target is increased (>100 ms), are followed by automatic inhibition of these responses (Eimer and Schlaghecken 2003). This leads to the counterintuitive observation that reaction times are faster to incongruent trials compared with congruent trials. Recently, Sumner and others (2007) showed that a patient with a highly specific SMA lesion did not show automatic inhibition of unconscious primes in a manual version of a masked priming task. Another patient, with a very specific lesion in the supplementary eye fields (SEFs), did not show automatic inhibition over unconscious primes in an oculomotor version of the task but performed similar as controls in the manual version. More recent studies have confirmed the crucial role of the SMA in the control over unconsciously triggered irrelevant action (manual) tendencies by using fMRI (Boy, Husain, and others 2010) as well as measures of GABA concentration (Boy, Evans, and others 2010). Similar findings are evident from studies using tasks in which subjects accidentally miss crucial external events or internally triggered motor output because of lapses in attention, general distraction, or increased automaticity of behavior. In this respect, one main domain of interest is related to the consequence of unnoticed (i.e., “unconscious”) errors (for review, see Ullsperger and others 2010). The first to examine this issue were Nieuwenhuis and colleagues (2001), who used an antisaccade task in which participants had to look in the opposite direction of a briefly flashed cue in the periphery of their visual field. Although otherwise instructed, subjects often fail to do so and look initially to the side of the

presented cue and only later shift their gaze toward the other direction. When asked after each trial, subjects often reported not to have made an error, whereas actually they did (also termed error blindness). Crucially, such unaware errors are still accompanied by a fast response-locked ERP component, the error-related negativity (ERN), probably originating from the medial frontal cortex (for an independent replication, see Endrass and others 2007). Only when the error was detected, a longer latency error positivity (Pe; P3-like wave) was observed. Subsequent ERP studies confirmed that unnoticed response errors indeed still trigger an ERN (Hughes and Yeung 2011; Maier and others 2008; O’Connell and others 2007), and fMRI studies have shown increased activation in the ACC for undetected errors, whereas conscious errors were uniquely associated with increased activity in dorsolateral, insular, and parietal cortices (Hester and others 2005; Klein and others 2007) (Fig. 5). Whether the ERN is still present when errors are committed because the relevant stimulus is fully unconscious (instead of just unnoticed) is still unclear because one recent ERP study showed the presence of an ERN when stimuli were presented at very low contrast (and were therefore missed) (Pavone and others 2009). However, another study did not observe an ERN when using masking (Woodman 2010). Response errors on fully unconscious NoGo stimuli (because of effective masking) have been shown to trigger post-error slowing mechanisms and elicit rapid top-down modulations over visual processing to prevent future errors (Cohen and others 2009), illustrating that unconscious errors affect subsequent information processing and behavior.

Downloaded from nro.sagepub.com at Universiteit van Amsterdam SAGE on June 2, 2011

9

van Gaal and Lamme In the domain of conflict resolution it has been shown that prefrontal areas, including ventral lateral PFC and the ACC, register when an implicitly learned rule is suddenly violated (and subjects fail to notice these violations) (Berns and others 1997; Rose and others 2005; Ursu and others 2009). For example, in a study by Ursu and colleagues (2009), subjects performed a dual task in which they had to press one of four buttons depending on the location of an unfamiliar face stimulus on the screen. Further, subjects had to memorize the faces because they were asked for recognition later. Importantly, the location of the stimulus followed a probabilistic sequence of which subjects were unaware. Although this rule remained implicit to the subjects, there was stronger ACC activity for trials that violated the underlying rule (“highconflict trials”) versus trials that followed that rule (“lowconflict trials”) (Fig. 5). Another interesting study was performed by Stephan and colleagues (2002), who studied the conscious and unconscious adjustments in tapping to changes in an auditory rhythm. The investigators showed that when participants were unaware of their adjustments to changes in a beat (because these changes were very subtle), cortical activity was observed in the bilateral ventral mediofrontal cortex and the right inferior parietal cortex. In contrast, explicit awareness of changes in the rhythm (attributable to larger changes in the actual beat) and subsequent adjustments in tapping led to additional activity in several regions, including the premotor cortex, ACC, and ventrolateral and dorsolateral prefrontal cortices. Overall, these recent findings suggest that several high-level PFC-mediated cognitive functions can be triggered unconsciously (although absence of evidence for these effects is also sometimes reported, e.g., Dehaene and others 2003). Importantly, the prefrontal activations seem truly functional in a sense that the cognitive functions mediated by these regions are initiated as soon as these regions are activated (e.g., task-switching, response inhibition, or conflict and error detection). However, crucially, irrespective of these high-level activations, a conscious (visual) experience is still absent. Apparently, something is lacking from the activation to generate consciousness. Although several theoretical possibilities have been postulated (see Seth 2007; Tononi and Koch 2008 for an overview) recent evidence suggests that one crucial factor is missing in such instances: the dynamic exchange of information between brain regions mediated by recurrent neural interactions (Dehaene and others 2006; Lamme and Roelfsema 2000). To motivate the crucial role of recurrent interactions in consciousness, we briefly summarize the literature providing support for this hypothesis.

A Potential Neural Signature of Consciousness Every time a visual stimulus is presented, it travels quickly from the retina through several stages of the cortical (and cognitive) hierarchy, referred to as the fast feedforward sweep (FFS) of information processing (Lamme and Roelfsema 2000). Each time information reaches a successive stage in this hierarchy, a higherlevel area starts to send information back automatically to lower-level areas through feedback connections, a phenomenon called recurrent processing (RP). Several lines of evidence suggest that the FFS remains unconscious, whereas RP is required for consciousness. For example, in the context of masking, it has been shown repeatedly that masking disrupts RP but leaves the FFS relatively intact (Del Cul and others 2007; Fahrenfort and others 2007; Koivisto and Revonsuo 2010; Lamme and others 2002). Also, conscious stimuli have been observed to trigger increased long-range oscillatory synchrony (a hallmark of RP) between distant brain regions, whereas unconscious stimuli do not (or much less so) (Gaillard and others 2009). Further, RP between V1 and higher visual areas is consistently correlated with the ability of animals (Super and others 2001) and humans (Haynes and others 2005) to report the presence or absence of a stimulus. Even in brain-damaged patients with disorders of consciousness (DOC) (e.g., coma, vegetative state, and minimally conscious state), the extent of residual neural communication between brain regions is strongly correlated with their level of consciousness (Bekinschtein, Dehaene, and others 2009; Vanhaudenhuyse and others 2010). Also in healthy subjects, the loss of consciousness attributable to anesthesia is accompanied by a selective disruption in RP (Alkire and others 2008; Lamme and others 1998). Last, but not least, transcranial magnetic stimulation (TMS) studies have shown a crucial role for RP in consciousness, with respect to both the content of consciousness (Pascual-Leone and Walsh 2001) and the level of consciousness, for example, in sleep (Massimini and others 2005). Interestingly, blindsight phenomena can be induced temporarily in healthy human subjects by applying TMS over the visual cortex around 100 ms after stimulus presentation, thereby disrupting RP but leaving the initial feedforward sweep intact (Jolij and Lamme 2005; Ro and others 2004). In sum, single-cell recordings in monkeys and TMS, fMRI, intracranial, and EEG experiments in humans have revealed that the feedforward sweep probably remains unconscious, whereas RP is necessary for conscious awareness. A crucial aspect of the FFS is that it probably

Downloaded from nro.sagepub.com at Universiteit van Amsterdam SAGE on June 2, 2011

10

The Neuroscientist XX(X)

decays rapidly while traveling up the cortical hierarchy, whereas RP promotes a long-lasting, large-scale pattern of reverberating activation (also termed global ignition) (Dehaene and others 2006; Dehaene and Naccache 2001).

Implications, Open Questions, and Future Outlook The evidence supporting that unconscious information can influence several stages in the cortical and cognitive hierarchy is rapidly accumulating. The studies reviewed here have demonstrated that which cognitive or perceptual function is executed depends on which brain area (i.e., cognitive module) is activated by the unconscious FFS. The depth, direction, and scope of the FFS depend mainly on the task being probed (task-set and strategy) and on (temporal and spatial) attention. However, this neural activity does not determine whether a conscious sensation is produced. This depends mainly on whether the brain areas involved engage in recurrent interactions, which enables a long-lasting and widespread propagation of signals enabling communication and exchange of information between brain regions (Dehaene and others 2006). These studies also suggest that although consciousness and attention have long been thought to be intimately related (Posner 1994), consciousness and attention are actually independent dimensions of the human mind (Koch and Tsuchiya 2007; Lamme 2003). Given that the FFS can reach even areas in the prefrontal cortex, does that mean that all cognitive functions can be executed unconsciously? At the moment, that is an open question. Indeed, it might be the case that the FFS is able to trigger all (sub)cortical brain regions and thereby all possible cognitive functions supported by these regions. However, it might also be that some brain regions are not stimulus driven in any way and consequently cannot be reached by the FFS alone. To activate these regions, RP and the broadcasting of signals might be a necessary condition. If that turns out to be the case, the most likely candidate regions for this seem to be the domain-generic regions in dorsolateral prefrontal and parietal cortex (Dehaene and others 2006; Jack and Shallice 2001). If so, this means that the cognitive functions associated with these regions are truly bound to consciousness. However, possibly, future experiments might demonstrate that also these brain regions can be activated unconsciously (see, e.g., Lau and Passingham 2007; Naccache and Dehaene 2001). Then, the function of consciousness might not be related to a specific brain region and its associated function but more so to other specific attributes of RP, such as the ability to combine information from multiple sources, enabling flexibility over information processing (Sackur and Dehaene 2009), and the possibility to durably maintain information across time, mechanisms that have been

proposed to be necessary to facilitate novel (nonautomatic) behavior and cognition (Baumeister and others, forthcoming; Dehaene and Naccache 2001). As has been hypothesized recently, recurrent interactions between brain regions (and thus consciousness) might also be linked to synaptic plasticity and therefore (long-term) learning (Lamme 2010). Feedforward activations (and thus unconscious processes) might not evoke such long-term changes to the brain. The results reviewed here have profound implications for how to detect consciousness in brain-damaged noncommunicative (DOC) patients. Generally, to what extent these patients are still conscious of their environment is mainly gauged using detailed behavioral tests in which patients are asked to respond to visual, auditory, or tactile stimuli. But what if their ability to communicate is lost but consciousness itself is not and remains present? Ideally, we don’t want to ask about conscious experience but rather want to look for it in the brain directly (Laureys 2005; Owen and Coleman 2008). Recently, scientists started to do so and showed “islands of brain activity” when patients were presented with auditory (e.g., their own name) or tactile stimuli, sometimes even in highlevel brain regions (Owen and Coleman 2008). For example, it has been shown that some vegetative patients still show increased brain responses to semantic ambiguous words in a sentence, suggesting the residual ability to process some semantic aspects of speech (Coleman and others 2007). Also the residual processing of emotional content, such as the patient’s own name, has been established in these patients (Di and others 2007). Although these results are intriguing, we are not sure how to interpret them, all the more because the evidence reviewed here shows that the activation of specific parts of the brain, even in high-level brain regions, does not necessarily generate consciousness. We need a proven neural signature of consciousness that we can track in the brains of DOC patients. Dynamic recurrent interactions between brain regions, facilitating long-lasting communication, might fit that bill. Recent studies have tested whether the presence or absence of these characteristics can infer the level of consciousness in DOC patients and have done so with great success (Bekinschtein, Dehaene, and others 2009; Bekinschtein, Shalom, and others 2009; Vanhaudenhuyse and others 2010). Several studies have reported functional connectivity analyses to test for preserved interactions between brain regions and have shown that the level of consciousness of DOC patients is strongly related to the extent of residual neural interactions during rest (Vanhaudenhuyse and others 2010) as well as during stimulus presentation (e.g., for painful stimuli) (Boly and others 2008; Laureys and others 2002). Finally, because unconscious activations die out quickly, “brain reading” paradigms in which patients have to

Downloaded from nro.sagepub.com at Universiteit van Amsterdam SAGE on June 2, 2011

11

van Gaal and Lamme imagine a certain activity (e.g., playing tennis) over a prolonged period of time (>30 s) might also prove to be a successful approach to determine the level of consciousness in DOC patients (Monti and others 2010; Owen and others 2006). Although we should be extremely cautious when dealing with these issues, tracking RP-related processes in DOC patients might turn out to be fruitful in establishing their residual conscious experience, without having to rely on some form of behavioral report. Declaration of Conflicting Interests The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding The authors disclosed receipt of the following financial support for the research and/or authorship of this article: This work is supported by an Advanced Investigator Grant from the European Research Council to VAFL and a Rubicon grant from the Netherlands Society for Scientific Research (NWO) to SvG.

References Aarts H, Custers R, Marien H. 2008. Preparing and motivating behavior outside of awareness. Science 319:1639–1639. Alkire MT, Hudetz AG, Tononi G. 2008. Consciousness and anesthesia. Science 322: 876–80. Ansorge U, Neumann O. 2005. Intentions determine the effect of invisible metacontrast-masked primes: evidence for topdown contingencies in a peripheral cuing task. J Exp Psychol Hum Percept Perform 31:762–77. Aron AR. 2007. The neural basis of inhibition in cognitive control. Neuroscientist 13:214–28. Bahrami B, Lavie N, Rees G. 2007. Attentional load modulates responses of human primary visual cortex to invisible stimuli. Curr Biol 17:509–13. Bauer F, Cheadle SW, Parton A, Muller HJ, Usher M. 2009. Gamma flicker triggers attentional selection without awareness. Proc Natl Acad Sci U S A 106:1666–71. Baumeister RF, Masicampo EJ, Vohs, K.D. Forthcoming. Do conscious thoughts cause behavior? Annu Rev Psychol. Bekinschtein TA, Dehaene S, Rohaut B, Tadel F, Cohen L, Naccache, L. 2009. Neural signature of the conscious processing of auditory regularities. Proc Natl Acad Sci U S A 106:1672–77. Bekinschtein TA, Shalom DE, Forcato C, Herrera M, Coleman MR, Manes FF, and others. 2009. Classical conditioning in the vegetative and minimally conscious state. Nat Neurosci 12:1343–9. Berns GS, Cohen JD, Mintun MA. 1997. Brain regions responsive to novelty in the absence of awareness. Science 276:1272–5. Bijleveld E, Custers R, Aarts H. 2010. Unconscious reward cues increase invested effort, but do not change speed-accuracy tradeoffs. Cognition 115:330–5.

Boly M, Faymonville ME, Schnakers C, Peigneux P, Lambermont B, Phillips C, and others. 2008. Perception of pain in the minimally conscious state with PET activation: an observational study. Lancet Neurol 7:1013–20. Botvinick MM, Braver TS, Barch DM, Carter CS, Cohen JD. 2001. Conflict monitoring and cognitive control. Psychol Rev 108:624–52. Boy F, Evans CJ, Edden RA, Singh KD, Husain M, Sumner P. 2010. Individual differences in subconscious motor control predicted by GABA concentration in SMA. Curr Biol 20:1779–85. Boy F, Husain M, Singh KD, Sumner P. 2010. Supplementary motor area activations in unconscious inhibition of voluntary action. Exp Brain Res 206:441–8. Breitmeyer BG, Ogmen H, editor. 2006. Visual masking: time slices through conscious and unconscious vision. Oxford, UK: Oxford University Press. Brown CM, Hagoort P. 1993. The processing nature of the N400: Evidence from masked priming. J Cogn Neurosci 5:33–44. Carter CS, van Veen V. 2007. Anterior cingulate cortex and conflict detection: an update of theory and data. Cogn Affect Behav Neurosci 7:367–79. Cohen MX, van Gaal S, Ridderinkhof KR, Lamme VAF. 2009. Unconscious errors enhance prefrontal-occipital oscillatory synchrony. Front Hum Neurosci 3:54. Coleman MR, Rodd JM, Davis MH, Johnsrude IS, Menon DK, Pickard JD, and others. 2007. Do vegetative patients retain aspects of language comprehension? Evidence from fMRI. Brain 130:2494–507. Cowey A. 2010. The blindsight saga. Exp Brain Res 200:3–24. Damian MF. 2001. Congruity effects evoked by subliminally presented primes: automaticity rather than semantic processing. J Exp Psychol Hum Percept Perform 27:154–65. Deacon D, Hewitt S, Yang C, Nagata M. 2000. Event-related potential indices of semantic priming using masked and unmasked words: evidence that the N400 does not reflect a post-lexical process. Cogn Brain Res 9:137–46. Dehaene S, Artiges E, Naccache L, Martelli C, Viard A, Schurhoff F, and others. 2003. Conscious and subliminal conflicts in normal subjects and patients with schizophrenia: The role of the anterior cingulate. Proc Natl Acad Sci U S A 100:13722–7. Dehaene S, Changeux J-P, Naccache L, Le Clec’H G, Koechlin E, Mueller M, and others. 1998. Imaging unconscious semantic priming. Nature 395:597–600. Dehaene S, Changeux JP, Naccache L, Sackur J, Sergent C. 2006. Conscious, preconscious, and subliminal processing: a testable taxonomy. Trends Cogn Sci 10:204–11. Dehaene S, Jobert A, Naccache L, Ciuciu P, Poline JB, Le Bihan D, and others. 2004. Letter binding and invariant recognition of masked words: behavioral and neuroimaging evidence. Psychol Sci 15:307–13.

Downloaded from nro.sagepub.com at Universiteit van Amsterdam SAGE on June 2, 2011

12

The Neuroscientist XX(X)

Dehaene S, Naccache L. 2001. Towards a cognitive neuroscience of consciousness: basic evidence and a workspace framework. Cognition 79:1–37. Dehaene S, Naccache L, Cohen L, Le Bihan D, Mangin JF, Poline JB, and others. 2001. Cerebral mechanisms of word masking and unconscious repetition priming. Nat Neurosci 4:752–8. Del Cul A, Baillet S, Dehaene S. 2007. Brain dynamics underlying the nonlinear threshold for access to consciousness. PLoS Biol 5, e260. doi:210.1371/journal.pbio.0050260. Devlin JT, Jamison HL, Matthews PM, Gonnerman LM. 2004. Morphology and the internal structure of words. Proc Natl Acad Sci USA 101:14984–8. Di HB, Yu SM, Weng XC, Laureys S, Yu D, Li JQ, and others. 2007. Cerebral response to patient’s own name in the vegetative and minimally conscious states. Neurology 68:895–9. Diaz TD, McCarthy G. 2007. Unconscious word processing engages a distributed network of brain regions. J Cogn Neurosci 19:1768–75. Driver J, Mattingley JB. 1998. Parietal neglect and visual awareness. Nat Neurosci 1:17–22. Eimer M, Schlaghecken F. 2003. Response facilitation and inhibition in subliminal priming. Biol Psychol 64:7–26. Endrass T, Reuter B, Kathmann N. 2007. ERP correlates of conscious error recognition: aware and unaware errors in an antisaccade task. Eur J Neurosci 26:1714–20. Fabre L, Lemaire P, Grainger J. 2007. Attentional modulation of masked repetition and categorical priming in young and older adults. Cognition 105:513–32. Fahrenfort JJ, Scholte HS, Lamme VAF. 2007. Masking disrupts reentrant processing in human visual cortex. J Cogn Neurosci 19:1488–97. Fang F, He S. 2005. Cortical responses to invisible objects in the human dorsal and ventral pathways. Nat Neurosci 8:1380–5. Finkbeiner M, Palermo R. 2009. The role of spatial attention in nonconscious processing: a comparison of face and nonface stimuli. Psychol Sci 20:42–51. Gaillard R, Dehaene S, Adam C, Clemenceau S, Hasboun D, Baulac M, and others. 2009. Converging intracranial markers of conscious access. PloS Biol 7, e1000061. doi:1000010.1001371/journal.pbio.1000061. Greenwald AG, Abrams RL, Naccache L Dehaene S. 2003. Long-term semantic memory versus contextual memory in unconscious number processing. J Exp Psychol Learn Mem Cogn 29:235–47. Grill-Spector K, Kushnir T, Hendler T, Malach R. 2000. The dynamics of object-selective activation correlate with recognition performance in humans. Nat Neurosci 3:837–43. Grill-Spector K, Malach R. 2001. fMR-adaptation: a tool for studying the functional properties of human cortical neurons. Acta Psychol 107:293–321.

Haynes JD, Driver J, Rees G. 2005. Visibility reflects dynamic changes of effective connectivity between V1 and fusiform cortex. Neuron 46:811–21. Haynes JD, Rees G. 2005. Predicting the orientation of invisible stimuli from activity in human primary visual cortex. Nat Neurosci 8:686–91. Hester R, Foxe JJ, Molholm S, Shpaner M, Garavan H. 2005. Neural mechanisms involved in error processing: A comparison of errors made with and without awareness. Neuroimage 27:602–8. Hommel B. 2007. Consciousness and control: not identical twins. Journal of Consciousness Studies 14:155–67. Hughes G, Velmans M, De Fockert J. 2009. Unconscious priming of a no-go response. Psychophysiology 46:1258–69. Hughes G, Yeung N. 2011. Dissociable correlates of response conflict and error awareness in error-related brain activity. Neuropsychologia 49:405–15. Jack AI, Shallice T. 2001. Introspective physicalism as an approach to the science of consciousness. Cognition 79: 161–96. Jiang Y, Costello P, Fang F, Huang M, He S. 2006. A genderand sexual orientation-dependent spatial attentional effect of invisible images. Proc Natl Acad Sci U S A 103: 17048–52. Jolij J, Lamme VAF. 2005. Repression of unconscious information by conscious processing: evidence from affective blindsight induced by transcranial magnetic stimulation. Proc Natl Acad Sci U S A 102:10747–51. Kentridge RW, Heywood CA, Weiskrantz L. 1999. Attention without awareness in blindsight. Proc Biol Sci 266: 1805–11. Kentridge RW, Heywood CA, Weiskrantz L. 2004. Spatial attention speeds discrimination without awareness in blindsight. Neuropsychologia 42:831–5. Kentridge RW, Nijboer TC, Heywood CA. 2008. Attended but unseen: visual attention is not sufficient for visual awareness. Neuropsychologia 46:864–9. Kiefer M, Brendel D. 2006. Attentional modulation of unconscious “automatic” processes: evidence from event-related potentials in a masked priming paradigm. J Cogn Neurosci 18:184–98. Kiefer M, Martens U. 2010. Attentional sensitization of unconscious cognition: task sets modulate subsequent masked semantic priming. J Exp Psychol Gen 139:464–89. Kiefer M, Spitzer M. 2000. Time course of conscious and unconscious semantic brain activation. Neuroreport 11:2401–7. Klein TA, Endrass T, Kathmann N, Neumann J, von Cramon DY, Ullsperger M. 2007. Neural correlates of error awareness. Neuroimage 34:1774–81. Klotz W, Neumann O. 1999. Motor activation without conscious discrimination in metacontrast masking. J Exp Psychol Hum Percept Perform 25:976–92.

Downloaded from nro.sagepub.com at Universiteit van Amsterdam SAGE on June 2, 2011

13

van Gaal and Lamme Koch C, Tsuchiya N. 2007. Attention and consciousness: two distinct brain processes. Trends Cogn Sci 11:16–22. Koivisto M, Revonsuo A. 2010. Event-related brain potential correlates of visual awareness. Neurosci Biobehav Rev 34:922–34. Kouider S, de Gardelle V, Dehaene S, Dupoux E, Pallier C. 2010. Cerebral bases of subliminal speech priming. Neuroimage 49:922–9. Kouider S, Eger E, Dolan R, Henson RN. 2009. Activity in face-responsive brain regions is modulated by invisible, attended faces: evidence from masked priming. Cereb Cortex 19:13–23. Kunde W, Kiesel A, Hoffmann J. 2003. Conscious control over the content of unconscious cognition. Cognition 88: 223–42. Lamme VAF. 2003. Why visual attention and awareness are different. Trends Cogn Sci 7:12–8. Lamme VAF. 2010. On how neuroscience will change or view on consciousness. Cogn Neurosci 1:204–40. Lamme VAF, Roelfsema PR. 2000. The distinct modes of vision offered by feedforward and recurrent processing. Trends Neurosci 23:571–9. Lamme VAF, Zipser K, Spekreijse H. 1998. Figure-ground activity in primary visual cortex is suppressed by anesthesia. Proc Natl Acad Sci U S A 95:3263–8. Lamme VAF, Zipser K, Spekreijse H. 2002. Masking interrupts figure-ground signals in V1. J Cogn Neurosci 14:1044–53. Lau EF, Phillips C, Poeppel D. 2008. A cortical network for semantics: (de)constructing the N400. Nat Rev Neurosci 9:920–33. Lau HC, Passingham RE. 2007. Unconscious activation of the cognitive control system in the human prefrontal cortex. J Neurosci 27:5805–11. Laureys S. 2005. The neural correlate of (un)awareness: lessons from the vegetative state. Trends Cogn Sci 9:556–9. Laureys S, Faymonville ME, Peigneux P, Damas P, Lambermont B, Del Fiore G, and others. 2002. Cortical processing of noxious somatosensory stimuli in the persistent vegetative state. Neuroimage 17:732–41. Lin JY, Murray SO, Boynton GM. 2009. Capture of attention to threatening stimuli without perceptual awareness. Curr Biol 19:1118–22. Luck SJ, Vogel EK, Shapiro KL. 1996. Word meanings can be accessed but not reported during the attentional blink. Nature 383:616–8. Maier M, Steinhauser M, Hubner R. 2008. Is the error-related negativity amplitude related to error detectability? Evidence from effects of different error types. J Cogn Neurosci 20:2263–73. Martens U, Ansorge U, Kiefer M. 2011. Controlling the unconscious: attentional task sets modulate subliminal semantic and visuomotor processes differentially. Psychol Sci 22:282–91.

Marzouki Y, Grainger J, Theeuwes J. 2007. Exogenous spatial cueing modulates subliminal masked priming. Acta Psychol 126:34–45. Massimini M, Ferrarelli F, Huber R, Esser SK, Singh H, Tononi G. 2005. Breakdown of cortical effective connectivity during sleep. Science 309:2228–32. Mattler U. 2003. Priming of mental operations by masked stimuli. Percept Psychophys 65:167–87. Mayr U. 2004. Conflict, consciousness, and control. Trends Cogn Sci 8:145–8. Monti MM, Vanhaudenhuyse A, Coleman MR, Boly M, Pickard JD, Tshibanda L, and others. 2010. Willful modulation of brain activity in disorders of consciousness. N Engl J Med 362:579–89. Mulckhuyse M, Theeuwes J. 2010. Unconscious attentional orienting to exogenous cues: a review of the literature. Acta Psychol 134:299–309. Naccache L, Blandin E, Dehaene S. 2002. Unconscious masked priming depends on temporal attention. Psychol Sci 13: 416–24. Naccache L, Dehaene S. 2001. The priming method: Imaging unconscious repetition priming reveals an abstract representation of number in the parietal lobes. Cereb Cortex 11:966–74. Naccache L, Gaillard R, Adam C, Hasboun D, Clemenceau S, Baulac M, and others. 2005. A direct intracranial record of emotions evoked by subliminal words. Proc Natl Acad Sci U S A 102:7713–7. Nakamura K, Dehaene S, Jobert A, Le Bihan D, Kouider S. 2005. Subliminal convergence of kanji and kana words: Further evidence for functional parcellation of the posterior temporal cortex in visual word perception. J Cogn Neurosci 17:954–68. Nakamura K, Dehaene S, Jobert A, Le Bihan D, Kouider S. 2007. Task-specific change of unconscious neural priming in the cerebral language network. Proc Natl Acad Sci U S A 104:19643–8. Nakamura K, Hara N, Kouider S, Takayama Y, Hanajima R, Sakai K, and others. 2006. Task-guided selection of the dual neural pathways for reading. Neuron 52:557–64. Nieuwenhuis S, Ridderinkhof KR, Blom J, Band GPH, Kok A. 2001. Error-related brain potentials are differentially related to awareness of response errors: evidence from an antisaccade task. Psychophysiology 38:752–60. O’Connell RG, Dockree PM, Bellgrove MA, Kelly SP, Heste, R, Garavan H, and others. 2007. The role of cingulate cortex in the detection of errors with and without awareness: a highdensity electrical mapping study. Eur J Neurosci 25: 2571–9. Owen AM, Coleman MR. 2008. Functional neuroimaging of the vegetative state. Nat Rev Neurosci 9:235–43. Owen AM, Coleman MR, Boly M, Davis MH, Laureys S, Pickard JD. 2006. Detecting awareness in the vegetative state. Science 313:1402.

Downloaded from nro.sagepub.com at Universiteit van Amsterdam SAGE on June 2, 2011

14

The Neuroscientist XX(X)

Palva S, Linkenkaer-Hansen K, Naatnen R, Palva JM. 2005. Early neural correlates of conscious somatosensory perception. J Neurosci 25:5248–58. Pascual-Leone A, Walsh V. 2001. Fast backprojections from the motion to the primary visual area necessary for visual awareness. Science 292:510–2. Pavone EF, Marzi CA, Girelli M. 2009. Does subliminal visual perception have an error-monitoring system? Eur J Neurosci 30:1424–31. Pessiglione M, Petrovic P, Daunizeau J, Palminteri S, Dolan JD, Frith CD. 2008. Subliminal instrumental conditioning demonstrated in the human brain. Neuron 59:561–7. Pessiglione M, Schmidt L, Draganski B, Kalisch R, Lau H, Dolan RJ, and others. 2007. How the brain translates money into force: a neuroimaging study of subliminal motivation. Science 316:904–6. Posner M. 1994. Attention: the mechanisms of consciousness. PNAS 91:7398–403. Qiao E, Vinckier F, Szwed M, Naccache L, Valabregue R, Dehaene S, and others. 2010. Unconsciously deciphering handwriting: subliminal invariance for handwritten words in the visual word form area. Neuroimage 49:1786–99. Rajimerhr R. 2004. Unconscious orientation processing. Neuron 41:663–73. Rees G, Kreiman G, Koch C. 2002. Neural correlates of consciousness in humans. Nat Rev Neurosci 3:261–70. Rees G, Wojciulik E, Clarke K, Husain M, Frith C, Driver J. 2000. Unconscious activation of visual cortex in the damaged right hemisphere of a parietal patient with extinction. Brain 123:1624–33. Rees G, Wojciulik E, Clarke K, Husain M, Frith C, Driver J. 2002. Neural correlates of conscious and unconscious vision in parietal extinction. Neurocase 8:387–93. Ridderinkhof KR, Ullsperger M, Crone EA, Nieuwenhuis S. 2004. The role of the medial frontal cortex in cognitive control. Science 306:443–7. Ro T, Shelton D, Lee O L, Chang E. 2004. Extrageniculate mediation of unconscious vision in transcranial magnetic stimulation-induced blindsight. Proc Natl Acad Sci U S A 101:9933–5. Rolke B, Heil M, Streb J, Hennighausen E. 2001. Missed prime words within the attentional blink evoke an N400 semantic priming effect. Psychophysiology 38:165–74. Rose M, Haider H, Buchel C. 2005. Unconscious detection of implicit expectancies. J Cogn Neurosci 17:918–27. Rusconi E, Priftis K, Rusconi ML, Umilta C. 2006. Arithmetic priming from neglected numbers. Cogn Neuropsychol 23:227–39. Sackur J, Dehaene S. 2009. The cognitive architecture for chaining of two mental operations. Cognition 111:187–211. Sackur J, Naccache L, Pradat-Diehl P, Azouvi P, Mazevet D, Katz R, and others. 2008. Semantic processing of neglected numbers. Cortex 44:673–82.

Sadaghiani S, Hesselmann G, Kleinschmidt A. 2009. Distributed and antagonistic contributions of ongoing activity fluctuations to auditory stimulus detection. J Neurosci 29: 13410–17. Sato W, Okada T, Toichi M. 2007. Attentional shift by gaze is triggered without awareness. Exp Brain Res 183:87–94. Sergent C, Baillet S, Dehaene S. 2005. Timing of the brain events underlying access to consciousness during the attentional blink. Nat Neurosci 8:1391–1400. Seth A. 2007. Models of consciousness. Scholarpedia 2:1328. Stephan KM, Thaut MH, Wunderlich G, Schicks W, Tian B, Tellmann L, and others. 2002. Conscious and subconscious sensorimotor synchronization—prefrontal cortex and the influence of awareness. Neuroimage 15:345–52. Sterzer P, Haynes JD, Rees G. 2008. Fine-scale activity patterns in high-level visual areas encode the category of invisible objects. J Vis 8: 10.1–12. Sumner P, Nachev P, Morris P, Peters AM, Jackson SR, Kennard C, and others. 2007. Human medial frontal cortex mediates unconscious inhibition of voluntary action. Neuron 54,:697–711. Sumner P, Tsai P, Yu K, Nachev P. 2006. Attentional modulation of sensorimotor processes in the absence of perceptual awareness. Proc Natl Acad Sci U S A 103:10520–5. Super H, Spekreijse H, Lamme VAF. 2001. Two distinct modes of sensory processing observed in monkey primary visual cortex (V1). Nat Neurosci 4:304–10. Tamietto M, Castelli L, Vighetti S, Perozzo P, Geminiani G, Weiskrantz L, and others. 2009. Unseen facial and bodily expressions trigger fast emotional reactions. Proc Natl Acad Sci U S A 106:17661–6. Tamietto M, de Gelder B. 2010. Neural bases of the nonconscious perception of emotional signals. Nat Rev Neurosci 11:697–709. Tononi G, Koch C. 2008. The neural correlates of consciousness— an update. Ann N Y Acad Sci 1124:239–61. Ullsperger M, Harsay HA, Wessel JR, Ridderinkhof KR. 2010. Conscious perception of errors and its relation to the anterior insula. Brain Struct Funct 214:629–43. Umilta C. 1988. The control operations of consciousness. In: Marcel AJ, Bisiach E, editors. Consciousness in contemporary science. Oxford, UK: Oxford University Press, pp. 334–56. Ursu S, Clark KA, Aizenstein HJ, Stenger VA, Carter CS. 2009. Conflict-related activity in the caudal anterior cingulate cortex in the absence of awareness. Biol Psychol 80: 279–86. Van den Bussche E, Segers G, Reynvoet B. 2008. Conscious and unconscious proportion effects in masked priming. Conscious Cogn 17:1345–58. van Gaal S, Lamme VAF, Fahrenfort JJ, Ridderinkhof KR. 2011. Dissociable brain mechanisms underlying the conscious and unconscious control of behavior. J Cogn Neurosci 23:91–105. van Gaal S, Ridderinkhof KR, Fahrenfort JJ, Scholte HS, Lamme VAF. 2008. Frontal cortex mediates unconsciously triggered inhibitory control. J Neurosci 28:8053–62.

Downloaded from nro.sagepub.com at Universiteit van Amsterdam SAGE on June 2, 2011

15

van Gaal and Lamme van Gaal S, Ridderinkhof KR, Scholte HS, Lamme VAF. 2010. Unconscious activation of the prefrontal no-go network. J Neurosci 30:4143–50. van Gaal S, Ridderinkhof KR, van den Wildenberg WPM, Lamme VAF. 2009. Dissociating consciousness from inhibitory control: evidence for unconsciously triggered inhibitory control in the stop-signal paradigm. J Exp Psychol Hum Percept Perform 35:1129–39. van Gaal S, Scholte HS, Lamme VAF, Fahrenfort JJ, Ridderinkhof KR. 2011. Pre-SMA gray-matter density predicts individual differences in action selection in the face of conscious and unconscious response conflict. J Cogn Neurosci 23:382–90. Vanhaudenhuyse A, Noirhomme Q, Tshibanda LJ, Bruno MA, Boveroux P, Schnakers C, and others. 2010. Default network connectivity reflects the level of consciousness in non-communicative brain-damaged patients. Brain 133: 161–71. Vuilleumier P, Armony JL, Clarke K, Husain M, Driver J, Dolan RJ. 2002. Neural response to emotional faces with and without awareness: event-related fMRI in a parietal patient with visual extinction and spatial neglect. Neuropsychologia 40:2156–66. Vuilleumier P, Sagiv N, Hazeltinei E, Poldrack RA, Swick D, Rafal RD, and others. 2003. Neural fate of seen and unseen

faces in visuospatial neglect: a combined event-related functional MRI and event-related potential study. Proc Natl Acad Sci U S A 98:3495–500. Vuilleumier P, Schwartz S. 2001. Beware and be aware: capture of spatial attention by fear-related stimuli in neglect. Neuroreport 12:1119–22. Vuilleumier P, Valenza N, Landis T. 2001. Explicit and implicit perception of illusory contours in unilateral spatial neglect: behavioral and anatomical correlates of preattentive grouping mechanisms. Neuropsychologia 39:597–610. Whalen PJ, Kagan J, Cook RG, Davis FC, Kim H, Polis S, and others. 2004. Human amygdala responsivity to masked fearful eye whites. Science 306:2061. Williams M, Mattingley J. 2004. Unconscious perception of non-threatening facial emotion in parietal extinction. Exp Brain Res 154:403–6. Wokke ME, van Gaal S, Scholte HS, Ridderinkhof KR, Lamme VAF. Submitted. The flexibility of unconscious cognition. Wolbers T, Schoell ED, Verleger R, Kraft S, McNamara A, Jaskowski P, and others. 2006. Changes in connectivity profiles as a mechanism for strategic control over interfering subliminal information. Cereb Cortex 16:857–64. Woodman GF. 2010. Masked targets trigger event-related potentials index shifts of attention but not error detection. Psychophysiology 47:410–4.

Downloaded from nro.sagepub.com at Universiteit van Amsterdam SAGE on June 2, 2011