Skip to main content

Umbrella menu

  • SfN.org
  • eNeuro
  • The Journal of Neuroscience
  • Neuronline
  • BrainFacts.org

Main menu

  • HOME
  • CONTENT
    • Early Release
    • Featured
    • Current Issue
    • Issue Archive
    • Collections
  • ALERTS
  • FOR AUTHORS
    • Preparing a Manuscript
    • Submission Guidelines
    • Fees
    • Journal Club
    • eLetters
    • Submit
  • EDITORIAL BOARD
  • ABOUT
    • Overview
    • Advertise
    • For the Media
    • Rights and Permissions
    • Privacy Policy
    • Feedback
  • SUBSCRIBE
  • SfN.org
  • eNeuro
  • The Journal of Neuroscience
  • Neuronline
  • BrainFacts.org

User menu

  • Log in
  • Subscribe
  • My alerts
  • My Cart

Search

  • Advanced search
Journal of Neuroscience
  • Log in
  • Subscribe
  • My alerts
  • My Cart
Journal of Neuroscience

Advanced Search

Submit a Manuscript
  • HOME
  • CONTENT
    • Early Release
    • Featured
    • Current Issue
    • Issue Archive
    • Collections
  • ALERTS
  • FOR AUTHORS
    • Preparing a Manuscript
    • Submission Guidelines
    • Fees
    • Journal Club
    • eLetters
    • Submit
  • EDITORIAL BOARD
  • ABOUT
    • Overview
    • Advertise
    • For the Media
    • Rights and Permissions
    • Privacy Policy
    • Feedback
  • SUBSCRIBE
PreviousNext
Dual Perspectives

Are the Neural Correlates of Consciousness in the Front or in the Back of the Cerebral Cortex? Clinical and Neuroimaging Evidence

Melanie Boly, Marcello Massimini, Naotsugu Tsuchiya, Bradley R. Postle, Christof Koch and Giulio Tononi
Journal of Neuroscience 4 October 2017, 37 (40) 9603-9613; DOI: https://doi.org/10.1523/JNEUROSCI.3218-16.2017
Melanie Boly
1Department of Neurology, University of Wisconsin, Madison, Wisconsin 53705,
2Department of Psychiatry, University of Wisconsin, Madison, Wisconsin 53719,
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Melanie Boly
Marcello Massimini
3Department of Biomedical and Clinical Sciences Luigi Sacco, University of Milan, Milan 20157, Italy,
4Instituto Di Ricovero e Cura a Carattere Scientifico, Fondazione Don Carlo Gnocchi, Milan 20148, Italy,
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Naotsugu Tsuchiya
5School of Psychological Sciences, Faculty of Medicine, Nursing, and Health Sciences, Monash University, Melbourne, 3800 Victoria, Australia,
6Monash Institute of Cognitive and Clinical Neuroscience, Monash University, Melbourne, 3800 Victoria, Australia,
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Naotsugu Tsuchiya
Bradley R. Postle
2Department of Psychiatry, University of Wisconsin, Madison, Wisconsin 53719,
7Department of Psychology, University of Wisconsin, Madison, Wisconsin 53705, and
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Christof Koch
8Allen Institute for Brain Science, Seattle, Washington 98109
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Giulio Tononi
2Department of Psychiatry, University of Wisconsin, Madison, Wisconsin 53719,
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data
  • Info & Metrics
  • eLetters
  • PDF
Loading

Abstract

The role of the frontal cortex in consciousness remains a matter of debate. In this Perspective, we will critically review the clinical and neuroimaging evidence for the involvement of the front versus the back of the cortex in specifying conscious contents and discuss promising research avenues.

Dual Perspectives Companion Paper: Should a Few Null Findings Falsify Prefrontal Theories of Conscious Perception?, by Brian Odegaard, Robert T. Knight, and Hakwan Lau

  • consciousness
  • frontal cortex
  • lesion studies
  • neuroimaging
  • stimulation studies

Introduction

Consciousness is subjective experience, the “what it is like” to perceive a scene, recognize a face, hear a sound, or reflect on the experience itself (Tononi et al., 2016a). Identifying the neural correlates of consciousness is important scientifically and clinically, to improve the detection of awareness and to design new therapies in patients who remain unresponsive after brain damage (Gosseries et al., 2014). Although frontal cortex is crucial for intelligent behavior and cognitive control, its involvement in consciousness remains a matter of debate (Koch et al., 2016a). It has been widely assumed that prefrontal circuits are essential for consciousness, either alone (Del Cul et al., 2009) or in conjunction with parietal areas (frontoparietal network) (Bor and Seth, 2012; Laureys and Schiff, 2012). In this Perspective, we will critically review the evidence for the role of the “front” versus the “back” of the cortex in supporting consciousness. By the “front,” we refer to prerolandic neocortex, including dorsolateral, medial prefrontal, anterior cingulate, and orbitofrontal areas. By the “back,” we refer to neocortical regions within the parietal, occipital, and lateral temporal lobes. Due to space constraints, we will not review possible contributions to consciousness of the medial temporal lobe and of the insular cortex (Craig, 2010; Seth et al., 2011; Quiroga, 2012), except for pointing out that consciousness is preserved after bilateral lesions of these areas (Corkin, 2002; Damasio et al., 2013). We will also not discuss the essential role of different brainstem and subcortical mesocircuit structures in regulating the level of consciousness (Brown et al., 2010). We emphasize, however, that consciousness is absent in vegetative state (VS) patients who suffered widespread corticothalamic damage even when brainstem activity is preserved (Laureys et al., 2004). We refer to other reviews for the complex interplay between consciousness, memory, and attention (Tononi et al., 2016b; Tsuchiya and Koch, 2016), including spatial neglect (Corbetta and Shulman, 2011). Finally, we will focus on the empirical evidence about the role of the front and the back of cortex leaving aside theoretical interpretations and predictions (Lamme, 2006; Dehaene and Changeux, 2011; Lau and Rosenthal, 2011; Boly and Seth, 2012; Tononi et al., 2016a).

Distinguishing between the neural correlates of consciousness and other neural processes

Neural correlates of consciousness: definition

The neural correlates of consciousness (NCC) are defined as the minimal neural mechanisms jointly sufficient for any one conscious percept (Crick and Koch, 1990). Content-specific NCC are the neural mechanisms specifying particular phenomenal contents within consciousness, such as colors, faces, places, or thoughts. Experimentally, content-specific NCC are typically investigated by comparing conditions where specific conscious contents are present versus absent. The full NCC can be defined as the union of all content-specific NCC (Koch et al., 2016a). Experimentally, the full NCC can be identified by comparing conditions where consciousness as a whole is present versus absent, such as dreaming versus dreamless sleep. In principle, the full NCC can also be approximated by sampling the wide range of content-specific NCC. In practice, these two approaches progress hand in hand (Boly et al., 2013).

Distilling the “true NCC”

Recent results have stressed the importance of dissociating the true NCC from other neural processes (Miller, 2007; de Graaf et al., 2012; Tsuchiya et al., 2015) that can be considered as “prerequisites” and “consequences” of consciousness (Aru et al., 2012) or alternatively as preceding and following the experience itself (Pitts et al., 2014). Here, factors that modulate the NCC without being directly involved in specifying conscious contents will be called “background conditions” (Koch et al., 2016a) of several kinds (Fig. 1). For example, global enabling factors, such as blood flow or oxygen supply to the cortex, are obviously essential for consciousness, but they do not contribute directly to its contents. Similarly, neuronal activating systems, such as cholinergic and noradrenergic neuromodulation, diffuse thalamocortical projections, and the anterior forebrain mesocircuit, are likely to influence the level of consciousness only indirectly, by modulating the activity of large parts of the full NCC (Schiff, 2010; de Graaf and Sack, 2014). Processing loops involving selective attention, working memory, or expectation may also modulate the probability of specific conscious contents indirectly, by modifying the excitability of content-specific NCC in a task-dependent manner (Aru et al., 2012) concurrently with experience (Postle, 2015; Tononi et al., 2016a). Finally, specific contents of experience are specified by the cortical NCC whether they are induced by sensory stimuli, imagined, or dreamt, suggesting that neural activity along sensory pathways serves as a reliable but indirect trigger of experiential content, rather than contributing directly to it. Similarly, neural activity along motor pathways is essential for reporting the contents of consciousness, but not for experiencing them (Tsuchiya et al., 2015).

Figure 1.
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 1.

Definition of the NCC. Content-specific NCC (red) directly contribute to phenomenal distinctions (e.g., low-level visual features, faces, or places) within consciousness. The full NCC (orange) is constituted by the union of all the content-specific NCC. Background conditions to the NCC encompass neural processes that enable or modulate the activity of the full NCC and thus influence the level of consciousness (green), including global enabling factors, such as blood flow or oxygen supply, and neuronal activating systems, such as brainstem reticular formation; neural processes that modulate the activity of only some content-specific NCC, including processing loops involving attention or working memory (beige), sensory pathways activating primary sensory cortices (pink), and outputs from the NCC (blue) involved in task-related verbal or motor reports. V1, Primary visual cortex; V2, secondary visual cortex; PPA, parahippocampal place area; M1, primary motor cortex.

Several complementary methods can be used to distill the true NCC. For the full NCC, within-state paradigms can be used to avoid confounds due to changes in behavioral state and task performance as well as to dissociate unconsciousness from unresponsiveness. For example, within either non-rapid eye movement (NREM) or REM sleep one can contrast neural activity when subjects report having dreamt (∼60% of cases in NREM sleep, ∼95% of cases in REM sleep) versus having been unconscious. Patients can also be conscious, although unresponsive and disconnected from the environment, in ∼20% of cases during anesthesia (Sanders et al., 2012) and in ∼35% of cases during complex partial seizures (Johanson et al., 2003). In such cases, methods assessing the complexity of neural EEG responses to transcranial magnetic stimulation can be used to assess the presence versus absence of consciousness in unresponsive subjects (Casarotto et al., 2016). For content-specific NCC, experiments can be carefully designed to systematically investigate possible dissociations between the experience of particular conscious contents and the engagement of various cognitive processes, such as attention, decision-making, and reporting (Aru et al., 2012; Koch and Tsuchiya, 2012; Tsuchiya et al., 2015; Tsuchiya and Koch, 2016). It is especially important to assess the association between the activity of a candidate NCC and the presence of a particular conscious content systematically, across a large number of different experiments (Crick and Koch, 1990). Machine learning approaches can also be used to identify the true NCC as the neural activity patterns most predictive for specific conscious percepts (Sandberg et al., 2014). Ideally, dissociation, association, and prediction approaches applied to lesion, stimulation, and recording studies will converge in identifying a reliable and specific content-specific NCC (Koch et al., 2016a). In that case, one should assume operationally that the relevant part of the brain contributes directly to consciousness: that is, it constitutes a part of its physical substrate (Tononi et al., 2016a). With these methodological clarifications at hand, we will now critically review evidence for the NCC in the front versus the back of the cerebral cortex.

Clinical evidence for a contribution of anterior versus posterior cortex to consciousness

Lesions

Lesion data offer strong causal evidence for the involvement or lack of involvement of different brain areas in supporting consciousness and its contents (Farah, 2004). With regards to the full NCC, several well-documented patients have been described with a normal level of consciousness after extensive frontal damage. For example, Patient A (Brickner, 1952) (Fig. 2A), after extensive surgical removal of the frontal lobes bilaterally, including Brodmann areas 8–12, 16, 24, 32, 33, and 45–47, sparing only area 6 and Broca's area (Brickner, 1936), “toured the Neurological Institute in a party of five, two of whom were distinguished neurologists, and none of them noticed anything unusual until their attention was especially called to A after the passage of more than an hour.” Patient KM (Hebb and Penfield, 1940) had a near-complete bilateral prefrontal resection for epilepsy surgery (including bilateral Brodmann areas 9–12, 32, and 45–47), after which his IQ improved. Patients undergoing bilateral resection of prefrontal cortical areas for psychosurgery (Mettler et al., 1949), including Brodmann areas 10, 11, 45, 46, 47, or 8, 9, 10, or 44, 45, 46, 10, or area 24 (ventral anterior cingulate), remained fully conscious (see also Penfield and Jasper, 1954; Kozuch, 2014; Tononi et al., 2016b). A young man who had fallen on an iron spike that completely penetrated both frontal lobes, affecting bilateral Brodmann areas 10, 11, 24, 25, 32, and 45–47, and areas 44 and 6 on the right side, went on to marry, raise two children, have a professional life, and never complained of perceptual or other deficits (Mataró et al., 2001). A young woman with massive bilateral prefrontal damage of unclear etiology, affecting the right basal, superior, medial and lateral PFC, and the left medial orbitofrontal, frontopolar, and frontal gyri (Markowitsch and Kessler, 2000), had deficits in cognitive functions supported by the frontal lobe, but her consciousness and perceptual abilities were preserved. Medial prefrontal lesions, especially those involving anterior cingulate cortex, can cause akinetic mutism (Cairns et al., 1941), where patients visually track examiners but do not respond to command. Patients who recover from this state typically report that they were conscious but lacked the motivation to respond (Damasio and Van Hoesen, 1983).

Figure 2.
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 2.

Clinical evidence. Full NCC. A, Complete bilateral prefrontal lobectomy does not noticeably change the level of consciousness. Top row, Bilateral views of the resected left and right frontal lobes (Brickner, 1936). Bottom row, Postmortem lateral views of both hemispheres (Brickner, 1952). B, Anoxic lesions of posterior corpus callosum predict permanent VS after head trauma (Kampfl et al., 1998). C, Lesions of posterior corpus callosum, with restricted diffusion extending to parieto-temporo-occipital regions, predict permanent coma after anoxic brain damage (Bianchi and Sims, 2008). Content-specific NCC. D, A recent study suggests that intrusive thoughts can be elicited by electrical stimulation of anterior cingulate cortex (Popa et al., 2016). Eliciting any experience is, however, far more common when stimulating posterior than anterior cortical structures (Selimbeyoglu and Parvizi, 2010). E, F, Direct electrical brain stimulation (DES) supports a causal role for different parts of the posterior cortex in specifying conscious content, for example, the right FFA in contributing to face percepts (Rangarajan et al., 2014) (E) and the parietal cortex contributing the feeling of intention to move (F) (Desmurget et al., 2013). SF, Superior frontal sulcus; MF, middle frontal sulcus; IF, inferior frontal sulcus; DWI, diffusion weighted imaging.

Moving to the back of the brain, broad bilateral lesions or ablations of posterior cortex are extremely rare (Cavanna and Trimble, 2006). However, traumatic lesions of the posterior corpus callosum, connecting large parts of the posterior cortex, are found in 98% of patients who remain in VS after 1 year (Kampfl et al., 1998) (Fig. 2B). Moreover, such lesions are associated with a 214-fold risk of permanent VS (Kampfl et al., 1998). Posterior corpus callosum lesions also predict permanent coma after cardiac arrest (Bianchi and Sims, 2008) (Fig. 2C). By contrast, traumatic lesions of the frontal lobe, which are found in approximately half of patients with traumatic VS in the acute phase, do not predict outcome (Kampfl et al., 1998).

With regards to content-specific NCC, there is abundant neurological evidence that lesions in the posterior cortex can cause a loss of specific contents of experience (Farah, 2004). For example, lesions of the right fusiform face area (FFA) cause prosopagnosia, an inability to recognize faces (Barton and Cherkasova, 2003). Lesions of inferolateral occipital cortex cause achromatopsia, an inability to distinguish colors (Barton, 2011) that, when severe, can be accompanied by unawareness of the deficit (von Arx et al., 2010). Other lesions of the occipital cortex lead to visual form agnosia, a selective inability to identify objects, or simultanagnosia, an inability to perceive more than one object at a time (Farah, 2004). Lesions of the postrolandic cortex lead to a loss of somatosensory percepts, and lesions of left and right angular gyrus impair the conscious understanding of speech and prosody, respectively (George et al., 1996), whereas lesions of the inferior parietal lobule cause a loss of motor awareness (Sirigu et al., 2004). Lesions in left lateral temporal cortex may also lead to selective deficits for the perception of single words or full sentences (Blumenfeld, 2011).

By contrast, there is little evidence for loss of specific conscious contents after frontal damage (Penfield and Jasper, 1954). For example, lesions of Broca's area, while impairing speech production, do not typically cause loss of conscious speech perception (Blumenfeld, 2011). Although frontal injuries can slightly increase the threshold for perceiving some brief (16 ms) and masked visual stimuli, patients still experience them (Del Cul et al., 2009), suggesting that these frontal regions may modulate the NCC (i.e., act as background conditions) rather than contributing directly to consciousness (Kozuch, 2014).

Stimulation studies

Electrical stimulation during neurosurgery is an important source of evidence for a direct contribution of different brain areas to consciousness (Penfield, 1959; Desmurget et al., 2013), as indicated by its superior value in predicting postoperative deficits compared with fMRI or diffusion tensor imaging (Borchers et al., 2011).

With regards to the full NCC, the classical study of Moruzzi and Magoun (1949) and subsequent studies showed that it is possible to restore EEG activation and behavior in anesthetized animals through electrical or pharmacological stimulation of neuronal activating systems in brainstem, thalamus, and basal forebrain. Recently, subcortical electrical stimulation has also succeeded in increasing the level of consciousness in animals with focal seizures (Kundishora et al., 2017) and in human patients after brain damage (Schiff et al., 2007). In these cases, it is likely that the effects were mediated indirectly, by modulating the excitability of the full NCC through arousal systems.

With regards to content-specific NCC, it was recognized long ago that electrical stimulation of most of the frontal cortex does not elicit content-specific changes in experience (Penfield and Jasper, 1954), although it can interfere with task execution and induce involuntary movements (Selimbeyoglu and Parvizi, 2010). Transcranial magnetic stimulation of the frontal cortex also does not seem to modify experiential content, although it can interfere with speech production (Pascual-Leone et al., 1991). Complex hallucinations, similar to those classically reported after stimulation of temporal and parahippocampal regions (Penfield and Jasper, 1954; Mégevand et al., 2014), have been occasionally reported after stimulation of the middle and inferior frontal gyrus (Blanke et al., 2000), perhaps due to a network effect. Recently, however, two case report studies described the occurrence of a will to persevere and of intrusive thoughts after stimulation of the anterior cingulate cortex (Parvizi et al., 2013) and of mid-cingulate cortex (Popa et al., 2016) (Fig. 2D), respectively.

Electrical stimulation of posterior cortex induces discrete changes in the contents of consciousness more reliably (Selimbeyoglu and Parvizi, 2010), although some posteromedial cortical areas may remain silent (Foster and Parvizi, 2017). For example, direct electrical stimulation of early visual areas induces simple visual experiences, such as phosphenes (Beauchamp et al., 2012; Winawer and Parvizi, 2016), which can also be induced by transcranial magnetic stimulation of occipital and parietal cortices (Samaha et al., 2017). Electrical stimulation of postcentral gyrus induces somatosensory percepts (Penfield and Jasper, 1954), stimulation of temporoparietal cortex induces experiences of visual motion (Rauschecker et al., 2011), while stimulation of right fusiform gyrus selectively disrupts the perception of faces (Rangarajan et al., 2014) (Fig. 2E). Moreover, the feeling of intention has been elicited in temporoparietal cortex (Desmurget et al., 2009) (Fig. 2F) and out-of-body experiences in the right angular gyrus (Blanke et al., 2002).

Together, stimulation studies support the idea that some posterior cortical regions may contribute directly to specific contents of experience, but the evidence for prefrontal regions is scarce and indirect.

Neuroimaging evidence for a contribution of the anterior versus posterior cortex to consciousness

Compared with lesions or electrical stimulations, neuroimaging studies offer less direct evidence for the contribution of any one brain region to consciousness (Farah, 2004). Indeed, functional activation maps frequently encompass brain areas that may not be directly involved in specifying experiential contents (Silvanto and Pascual-Leone, 2012; de Graaf and Sack, 2014). For example, whereas fMRI and intracranial EEG both reveal the activation of widespread bilateral temporo-occipital areas (beyond the FFA) after the presentation of faces, direct electrical stimulation disrupts face perception only when applied to the right FFA (Rangarajan et al., 2014) (Fig. 2E).

However, neuroimaging experiments can sample brain activity systematically and noninvasively in healthy volunteers (Poldrack and Farah, 2015) and, with appropriate methodologies, they can also provide valuable information about the functional specificity of brain regions (Moran and Zaki, 2013; Poldrack and Farah, 2015). For example, neuroimaging experiments can demonstrate dissociations between content-specific NCC and neural correlates of other cognitive processes (Aru et al., 2012; de Graaf et al., 2012) by relying on forward inference (Henson, 2006; Moran and Zaki, 2013). Moreover, ever-growing neuroimaging databases can demonstrate systematic associations between specific conscious contents and the activation of specific cortical areas by using meta-analytic reverse inference (Poldrack, 2006; Yarkoni et al., 2010; Moran and Zaki, 2013; Poldrack and Yarkoni, 2016). Also, multivariate decoding techniques can compare the predictive value of various NCC candidates for specific conscious percepts (Haynes, 2009; Sandberg et al., 2014).

Forward inference: dissociating the true NCC from correlated neural processes

As was argued above, the cleanest way to identify the full NCC is to use within-state, no-task paradigms (Fig. 3A–D), which avoid confounds due to behavioral state changes and dissociate consciousness from behavioral responsiveness and task performance. Within-state studies contrasting dreaming versus nondreaming during NREM sleep and REM sleep have pointed to a “posterior hot zone” in parieto-occipital areas, possibly extending to mid-cingulate regions, as a reliable NCC (Siclari et al., 2017). Within-state contrasts applied to brain-damaged patients, comparing VS to minimally conscious state (MCS), also reveal most consistent differences within posterior cortex (Vanhaudenhuyse et al., 2010; King et al., 2013; Wu et al., 2015).

Figure 3.
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 3.

Neuroimaging, Forward inference. Full NCC. A, Between-state paradigm contrasting brain activity during NREM sleep and wakefulness (Kajimura et al., 1999) shows a relative deactivation of frontoparietal cortices. B, When subjects are awoken from NREM sleep and asked if they experienced anything before being awakened, EEG data during dream experiences show reduced low-frequency activity (1–10 Hz) compared with dreamless sleep in a posterior parieto-occiptal “hot zone” (Siclari et al., 2014). C, D, Directly comparing patients in an MCS with patients in a VS reveals differences in connectivity restricted to posterior cortex. C, Vanhaudenhuyse et al. (2010). D, Wu et al. (2015). Content-specific NCC. E, F, Tasks involving reporting seen versus unseen stimuli highlight differences in frontoparietal cortices: E, Binocular rivalry (Lumer et al., 1998); F, Visual word masking tasks (Dehaene et al., 2001). G, When conscious visual perception is dissociated from behavior (i.e., button press), only differences in activity in occipital and parietal regions remain (Frässle et al., 2014). H, Conscious perception of weak somatosensory stimuli correlates with cortical changes in BOLD signal restricted to contralateral rolandic and parietal areas (Meador et al., 2017). I, J, An early “visual awareness negativity” ∼200 ms in posterior temporal and occipital areas is found in two masking paradigms: I, Koivisto and Revonsuo (2010); J, Andersen et al. (2016). C, Conscious stimulus; UC, unconscious stimulus. K, Visual one-back paradigm in patients implanted with subdural electrode arrays. The visual cortex (right of the dashed white line) responds rapidly to the seen stimulus (red), whereas frontal regions are modulated by the task (yellow) (Noy et al., 2015). L, A within-state no-task experiment (Fig. 1D), contrasting EEG activity during REM sleep dreams with and without faces, highlighted the fusiform gyrus as content-specific NCC (Siclari et al., 2014).

With regards to content-specific NCC, many experiments using bistable perception and masking paradigms have shown the activation of prefrontal areas during conscious perception of external stimuli (for a detailed review, see Dehaene and Changeux, 2011). However, these task-based paradigms recruit areas involved in attention, working memory, and other cognitive processes. If these areas are only required for reporting on the perceived stimuli and not for experiencing them, they should not be regarded as a part of the full NCC (Tsuchiya et al., 2015). The recent study of stimuli that are task irrelevant but experienced (Fig. 3E–L) has made it possible to dissociate the true NCC from various cognitive functions involved in behavioral demands (Aru et al., 2012; de Graaf et al., 2012). During both inattentional blindness (Pitts et al., 2012) and backward masking experiments (Pitts et al., 2014), the content-specific NCC for task-irrelevant percepts are located in posterior cortex, whereas a difference in frontal activity (P3 potential) is only present if stimuli are task-relevant. “No-report” paradigms have also pointed to posterior regions as the NCC, whereas frontal cortex activation is correlated with reporting (Tsuchiya et al., 2015; Koch et al., 2016a). Similar dissociations have been identified by orthogonally manipulating consciousness versus selective attention (Tsuchiya and Koch, 2016), working memory (King et al., 2016), or expectation (Melloni et al., 2011). During REM sleep, a “no-task” state, specific dream contents, such as faces, places, movement, and speech, can be predicted from posterior, but not anterior, cortex (Siclari et al., 2017). The same approach has highlighted a potential contribution of mid-cingulate cortex to conscious thought, whether during waking, NREM, or REM sleep (Perogamvros et al., 2017). Finally, when meditation practitioners become immersed in a state of vivid imagery, activity in their frontal lobe decreases (Lou et al., 1999).

Reverse inference: content-specific NCC versus non–content-specific cognitive processes

In neuroimaging studies, a content-specific NCC can be characterized as the part of the brain in which a change in activity reliably and specifically predicts a particular change in experiential content. In recent years, several open-access frameworks have been developed to pool data from thousands of neuroimaging studies and assess reliability and specificity (Eickhoff et al., 2011; Poldrack and Yarkoni, 2016). For example, the Neurosynth framework (www.neurosynth.org) (Yarkoni et al., 2011) combines an automated tool to extract activation coordinates with a taxonomy of cognitive processes. Despite significant caveats, such as the use of 3D coordinates of activity peaks rather than unthresholded statistical maps (but see Neurovault, www.neurovault.org) (Gorgolewski et al., 2016) and of functional labels assigned by investigators, these meta-analytic tools can already illustrate reverse inference and generate hypotheses. For example, in a traditional meta-analysis approach, computing the probability that different brain regions are active when the study topics include consciousness, Neurosynth activation maps display some parts of the frontal cortex (Fig. 4A). However, in a reverse inference mode, computing the probability that consciousness is mentioned in the study given the activation of different brain regions, the activation of frontal cortex disappears (Fig. 4B). By contrast, in agreement with lesion and stimulation studies, reverse inference locates the best predictor of face percepts in the right FFA (Fig. 4C,D). Content-specific results for visual words or motion, speech sounds, or touch perception are likewise regionalized to occipital, temporal, and parietal cortices. In all these cases, reverse inference does not highlight frontal areas as predictive for specific conscious contents.

Figure 4.
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 4.

Neuroimaging, Reverse inference. A, When using Neurosynth for a traditional meta-analysis, computing the probability that different brain regions are active when the topics of a study include consciousness, parts of frontal cortex show up. B, When using Neurosynth in reverse inference mode, computing the probability that consciousness is included within the topics of a study, given the activation of different parts of the brain, frontal cortex disappears. The key term “conscious” was used on the Neurosynth website to extract both “forward” meta-analysis and reverse inference analysis steps in A, B. C, The same frontal areas that identified in a traditional meta-analysis for consciousness also appear activated in a traditional meta-analysis for faces. D, In contrast, reverse inference for faces no longer identifies frontal cortex activity but rather locates the activation predicting highest probability for face percepts in the right FFA. The key term “faces” was used on the Neurosynth website to extract both “forward” meta-analysis and reverse inference analysis steps in C, D. x, y, z values represent MNI coordinates, and a color scale is used for Z values.

Neurosynth also permits the assessment of the functional specificity of brain areas at user-specified coordinates. For example, activation in the FFA (with coordinate selected from the statistical maximum of the traditional meta-analysis, [41, −49, −20]) is consistently predictive for faces (probability p = 0.88), temporo-occipital cortex for visual words ([−46, −54, −12], p = 0.86) or visual motion ([46, −68, 0], p = 0.9), superior temporal cortex for speech sounds ([−58, −10, 0], p = 0.84), and postcentral cortex for touch ([−54, −22, 20], p = 0.88). In contrast, the statistical maximum within the frontal cortex activation obtained from the traditional meta-analysis on consciousness (−47, 6, 28) is found to be most predictive for the terms “phonological” and “task” (p = 0.76 and p = 0.63, respectively).

Prospective predictive approaches: decoding consciousness in individual trials/subjects

Ideally, decoding approaches would identify the true NCC as neural activity patterns most predictive for the presence of a given conscious content (Sandberg et al., 2014). Unlike classical statistical analysis, decoding approaches also assess reproducibility as the percentage of accurate classification among single trials (Haynes, 2009). With respect to the full NCC, the best predictors for differentiating MCS from VS using PET or fMRI were located in parietal, temporal, and occipital cortices (Demertzi et al., 2015; Stender et al., 2016) (Fig. 5, top). An online prospective approach based on EEG markers of arousal in posterior cortex was able to predict consciousness (dreaming) versus unconsciousness during NREM sleep with 85% accuracy (Siclari et al., 2017). Post hoc analysis also located the areas most predictive for dreaming consciousness within temporo-parieto-occipital cortices (Siclari et al., 2017). Anesthesia studies have shown that frontal activity is a poor predictor of consciousness (Avidan et al., 2011; Gaskell et al., 2017), but there are no data so far for posterior cortex.

Figure 5.
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 5.

Neuroimaging, Predictive approaches. Full NCC, Machine learning approaches applied to fMRI resting state show that temporo-parieto-occipital connectivity best differentiates patients in MCS versus VS (Demertzi et al., 2015). Content-specific NCC, The contents of a working memory task can best be decoded from the back of the brain (posterior green ROI, activated during sample period), but not from the front of the brain (red fronto-parietal ROI, activated during delay period) (Emrich et al., 2013). Right side panel, Classification accuracy to identify conscious contents is much higher for posterior Sample ROI than for fronto-parietal Delay ROI (left part of panel, before dashed line). Classification accuracy is also higher in occipital areas compared with parietal cortex (right part of panel, after dashed line). IPS, Intraparietal sulcus; IOS, intraoccipital sulcus; MT, area MT; V1, primary visual cortex; V2, secondary visual cortex; ROI, region of interest.

As for content-specific NCC, numerous studies in both awake and dreaming subjects could decode the occurrence of specific experiential contents from the activity of specific regions of posterior cortex (Nishimoto et al., 2011; Horikawa et al., 2013; Siclari et al., 2017). Working memory contents can also be decoded more reliably from the back than from the front of the cortex (Emrich et al., 2013) (Fig. 5, bottom). Finally, multivariate patterns predictive of differences in subjective experiences both within (Kriegeskorte, 2011) and between subjects (Charest et al., 2014) are most consistently found in posterior cortex.

Conclusion and future directions

In this Perspective, we have reviewed evidence across lesion, stimulation, and recording studies that consistently point to regions in the “back” of the cortex, including temporal, parietal, and occipital areas, as a “posterior hot zone” that seems to play a direct role in specifying the contents of consciousness. By contrast, evidence for a direct, content-specific involvement of the “front” of the cortex, including most prefrontal regions, is missing or unclear. At a minimum, reports of conscious patients after bilateral frontal lobectomy demonstrate that the prefrontal cortex is not necessary for consciousness. Although most prefrontal regions may be “mute” as regards to consciousness, not unlike basal ganglia and cerebellum, it remains possible that some prefrontal regions, such as ventromedial areas (Koenigs et al., 2007) or premotor areas, may contribute specific conscious contents, such as feelings of reflection, valuation, and affect (Koch et al., 2016b). Below we discuss some promising future research directions.

Lesion studies

Lesion studies would benefit from a systematic assessment of loss of specific conscious contents after frontal cortex damage, sampling both task-related experiences as well as dream contents (as in Solms, 2014). Future experiments should also investigate possible dissociations between consciousness and cognitive functions, such as attention and working memory after frontal damage, detail the precise 3D location (as in Mah et al., 2014) and laminar profile (Koch et al., 2016a) of the lesions, and control for network effects (Fischer et al., 2016).

Stimulation studies

Stimulation studies should explore the effects of local perturbations on both task performance (as in Winawer and Parvizi, 2016) and subjective experience, for example, using structured questionnaires. Direct electrical stimulation combined with intracranial recordings at the stimulation site and at distant sites (as in Keller et al., 2014; Pigorini et al., 2015) should help to identify specific patterns of functional connectivity involved in consciousness.

Neuroimaging studies

Neuroimaging studies should further exploit within-state, no-task paradigms to differentiate between the full NCC and neural correlates of responsiveness (Koch et al., 2016a). With respect to conscious content, pooling across an exhaustive set of different experiments (as in Axelrod et al., 2015), including a formal comparison between them (Rutiku et al., 2016) and a combination of report and no-report paradigms (Tsuchiya et al., 2016), should help to identify content-specific NCC as the brain regions most consistently activated in the presence of specific conscious percepts. Systematic meta-analyses using reverse inference will be useful to assess the reliability of NCC candidates while avoiding cherry-picking (Moran and Zaki, 2013). Meta-analytic frameworks, such as Neurosynth, should be modified by explicitly incorporating the dissociation between consciousness and cognitive functions, such as attention, working memory, and task execution. Prospective studies should confirm that the full NCC identified through forward and reverse inferences remains the best predictor for the presence of consciousness across different physiological or pathological states, at the level of single trials, or even online, in real time (as in Siclari et al., 2017). Decoding studies should also explicitly compare the predictive value of different neural activity patterns for specific conscious contents (as in Emrich et al., 2013). Finally, prospective studies should be used to assess the clinical utility of different NCC candidates for detecting consciousness in brain-damaged patients (as in Demertzi et al., 2015; Stender et al., 2016).

Footnotes

  • This work was supported by National Institutes of Health Grant 1R03NS096379 to M.B., the James S. McDonnell Scholar Award 2013 and the H2020-FETOPEN-2014-2015-RIA under agreement No. 686764 (Luminous Project) to M.M., the Templeton World Charity Foundation to N.T., National Institutes of Health Grant MH095984 to B.R.P., and the Tiny Blue Dot Foundation and the Distinguished Chair in Consciousness Science (University of Wisconsin) to G.T.

  • The authors declare no competing financial interests.

  • Correspondence should be addressed to either Dr. Melanie Boly or Dr. Giulio Tononi, 6001 Research Park Boulevard, Madison WI 53719. boly{at}wisc.edu or gtononi{at}wisc.edu

References

  1. ↵
    1. Andersen LM,
    2. Pedersen MN,
    3. Sandberg K,
    4. Overgaard M
    (2016) Occipital MEG activity in the early time range (<300 ms) predicts graded changes in perceptual consciousness. Cereb Cortex 26:2677–2688. doi:10.1093/cercor/bhv108 pmid:26009612
    OpenUrlCrossRefPubMed
  2. ↵
    1. Aru J,
    2. Bachmann T,
    3. Singer W,
    4. Melloni L
    (2012) Distilling the neural correlates of consciousness. Neurosci Biobehav Rev 36:737–746. doi:10.1016/j.neubiorev.2011.12.003 pmid:22192881
    OpenUrlCrossRefPubMed
  3. ↵
    1. Avidan MS,
    2. Jacobsohn E,
    3. Glick D,
    4. Burnside BA,
    5. Zhang L,
    6. Villafranca A,
    7. Karl L,
    8. Kamal S,
    9. Torres B,
    10. O'Connor M,
    11. Evers AS,
    12. Gradwohl S,
    13. Lin N,
    14. Palanca BJ,
    15. Mashour GA
    (2011) Prevention of intraoperative awareness in a high-risk surgical population. N Engl J Med 365:591–600. doi:10.1056/NEJMoa1100403 pmid:21848460
    OpenUrlCrossRefPubMed
  4. ↵
    1. Axelrod V,
    2. Bar M,
    3. Rees G
    (2015) Exploring the unconscious using faces. Trends Cogn Sci 19:35–45. doi:10.1016/j.tics.2014.11.003 pmid:25481216
    OpenUrlCrossRefPubMed
  5. ↵
    1. Barton JJ
    (2011) Disorders of higher visual processing. Handb Clin Neurol 102:223–261. doi:10.1016/B978-0-444-52903-9.00015-7 pmid:21601069
    OpenUrlCrossRefPubMed
  6. ↵
    1. Barton JJ,
    2. Cherkasova M
    (2003) Face imagery and its relation to perception and covert recognition in prosopagnosia. Neurology 61:220–225. doi:10.1212/01.WNL.0000071229.11658.F8 pmid:12874402
    OpenUrlCrossRefPubMed
  7. ↵
    1. Beauchamp MS,
    2. Sun P,
    3. Baum SH,
    4. Tolias AS,
    5. Yoshor D
    (2012) Electrocorticography links human temporoparietal junction to visual perception. Nat Neurosci 15:957–959. doi:10.1038/nn.3131 pmid:22660480
    OpenUrlCrossRefPubMed
  8. ↵
    1. Bianchi MT,
    2. Sims JR
    (2008) Restricted diffusion in the splenium of the corpus callosum after cardiac arrest. Open Neuroimag J 2:1–4. doi:10.2174/1874440000802010001 pmid:19018311
    OpenUrlCrossRefPubMed
  9. ↵
    1. Blanke O,
    2. Landis T,
    3. Seeck M
    (2000) Electrical cortical stimulation of the human prefrontal cortex evokes complex visual hallucinations. Epilepsy Behav 1:356–361. doi:10.1006/ebeh.2000.0109 pmid:12609167
    OpenUrlCrossRefPubMed
  10. ↵
    1. Blanke O,
    2. Ortigue S,
    3. Landis T,
    4. Seeck M
    (2002) Stimulating illusory own-body perceptions. Nature 419:269–270. doi:10.1038/419269a pmid:12239558
    OpenUrlCrossRefPubMed
  11. ↵
    1. Blumenfeld H
    (2011) Neuroanatomy through clinical cases, Ed 2. Sunderland, MA: Sinauer.
  12. ↵
    1. Boly M,
    2. Seth AK
    (2012) Modes and models in disorders of consciousness science. Arch Ital Biol 150:172–184. doi:10.4449/aib.v150i2.1372 pmid:23165877
    OpenUrlCrossRefPubMed
  13. ↵
    1. Boly M,
    2. Seth AK,
    3. Wilke M,
    4. Ingmundson P,
    5. Baars B,
    6. Laureys S,
    7. Edelman DB,
    8. Tsuchiya N
    (2013) Consciousness in humans and non-human animals: recent advances and future directions. Front Psychol 4:625. doi:10.3389/fpsyg.2013.00625 pmid:24198791
    OpenUrlCrossRefPubMed
  14. ↵
    1. Bor D,
    2. Seth AK
    (2012) Consciousness and the prefrontal parietal network: insights from attention, working memory, and chunking. Front Psychol 3:63. doi:10.3389/fpsyg.2012.00063 pmid:22416238
    OpenUrlCrossRefPubMed
  15. ↵
    1. Borchers S,
    2. Himmelbach M,
    3. Logothetis N,
    4. Karnath HO
    (2011) Direct electrical stimulation of human cortex, the gold standard for mapping brain functions? Nat Rev Neurosci 13:63–70. doi:10.1038/nrn3140 pmid:22127300
    OpenUrlCrossRefPubMed
  16. ↵
    1. Brickner RM
    (1936) The intellectual functions of the frontal lobes. New York: MacMillan.
  17. ↵
    1. Brickner RM
    (1952) Brain of Patient A after bilateral frontal lobectomy: status of frontal-lobe problem. AMA Arch Neurol Psychiatry 68:293–313. doi:10.1001/archneurpsyc.1952.02320210003001 pmid:14952067
    OpenUrlCrossRefPubMed
  18. ↵
    1. Brown EN,
    2. Lydic R,
    3. Schiff ND
    (2010) General anesthesia, sleep, and coma. N Engl J Med 363:2638–2650. doi:10.1056/NEJMra0808281 pmid:21190458
    OpenUrlCrossRefPubMed
  19. ↵
    1. Cairns H,
    2. Oldfield RC,
    3. Pennybacker JB,
    4. Whitteridge D
    (1941) Akinetic mutism with an epidermoid cyst of the 3rd ventricle. Brain 64:273–290. doi:10.1093/brain/64.4.273
    OpenUrlCrossRef
  20. ↵
    1. Casarotto S,
    2. Comanducci A,
    3. Rosanova M,
    4. Sarasso S,
    5. Fecchio M,
    6. Napolitani M,
    7. Pigorini A,
    8. Casali A,
    9. Trimarchi PD,
    10. Boly M,
    11. Gosseries O,
    12. Bodart O,
    13. Curto F,
    14. Landi C,
    15. Mariotti M,
    16. Devalle G,
    17. Laureys S,
    18. Tononi G,
    19. Massimini M
    (2016) Stratification of unresponsive patients by a validated index of brain complexity. Ann Neurol 80:718–729. doi:10.1002/ana.24779 pmid:27717082
    OpenUrlCrossRefPubMed
  21. ↵
    1. Cavanna AE,
    2. Trimble MR
    (2006) The precuneus: a review of its functional anatomy and behavioural correlates. Brain 129:564–583. doi:10.1093/brain/awl004 pmid:16399806
    OpenUrlCrossRefPubMed
  22. ↵
    1. Charest I,
    2. Kievit RA,
    3. Schmitz TW,
    4. Deca D,
    5. Kriegeskorte N
    (2014) Unique semantic space in the brain of each beholder predicts perceived similarity. Proc Natl Acad Sci U S A 111:14565–14570. doi:10.1073/pnas.1402594111 pmid:25246586
    OpenUrlAbstract/FREE Full Text
  23. ↵
    1. Corbetta M,
    2. Shulman GL
    (2011) Spatial neglect and attention networks. Annu Rev Neurosci 34:569–599. doi:10.1146/annurev-neuro-061010-113731 pmid:21692662
    OpenUrlCrossRefPubMed
  24. ↵
    1. Corkin S
    (2002) What's new with the amnesic patient H.M.? Nat Rev Neurosci 3:153–160. doi:10.1038/nrn726 pmid:11836523
    OpenUrlCrossRefPubMed
  25. ↵
    1. Craig AD
    (2010) The sentient self. Brain Struct Funct 214:563–577. doi:10.1007/s00429-010-0248-y pmid:20512381
    OpenUrlCrossRefPubMed
  26. ↵
    1. Crick F,
    2. Koch C
    (1990) Towards a neurobiological theory of consciousness. Semin Neurosci 2:263–275.
    OpenUrl
  27. ↵
    1. Damasio A,
    2. Van Hoesen G
    (1983) Focal lesions of the limbic lobe. In: Neuropsychology of human emotion (Hellman K, Satz P, eds). New York: Guilford.
  28. ↵
    1. Damasio A,
    2. Damasio H,
    3. Tranel D
    (2013) Persistence of feelings and sentience after bilateral damage of the insula. Cereb Cortex 23:833–846. doi:10.1093/cercor/bhs077 pmid:22473895
    OpenUrlCrossRefPubMed
  29. ↵
    1. de Graaf TA,
    2. Sack AT
    (2014) Using brain stimulation to disentangle neural correlates of conscious vision. Front Psychol 5:1019. doi:10.3389/fpsyg.2014.01019 pmid:25295015
    OpenUrlCrossRefPubMed
  30. ↵
    1. de Graaf TA,
    2. Hsieh PJ,
    3. Sack AT
    (2012) The ‘correlates’ in neural correlates of consciousness. Neurosci Biobehav Rev 36:191–197. doi:10.1016/j.neubiorev.2011.05.012 pmid:21651927
    OpenUrlCrossRefPubMed
  31. ↵
    1. Dehaene S,
    2. Changeux JP
    (2011) Experimental and theoretical approaches to conscious processing. Neuron 70:200–227. doi:10.1016/j.neuron.2011.03.018 pmid:21521609
    OpenUrlCrossRefPubMed
  32. ↵
    1. Dehaene S,
    2. Naccache L,
    3. Cohen L,
    4. Bihan DL,
    5. Mangin JF,
    6. Poline JB,
    7. Rivière D
    (2001) Cerebral mechanisms of word masking and unconscious repetition priming. Nat Neurosci 4:752–758. doi:10.1038/89551 pmid:11426233
    OpenUrlCrossRefPubMed
  33. ↵
    1. Del Cul A,
    2. Dehaene S,
    3. Reyes P,
    4. Bravo E,
    5. Slachevsky A
    (2009) Causal role of prefrontal cortex in the threshold for access to consciousness. Brain 132:2531–2540. doi:10.1093/brain/awp111 pmid:19433438
    OpenUrlCrossRefPubMed
  34. ↵
    1. Demertzi A,
    2. Antonopoulos G,
    3. Heine L,
    4. Voss HU,
    5. Crone JS,
    6. de Los Angeles C,
    7. Bahri MA,
    8. Di Perri C,
    9. Vanhaudenhuyse A,
    10. Charland-Verville V,
    11. Kronbichler M,
    12. Trinka E,
    13. Phillips C,
    14. Gomez F,
    15. Tshibanda L,
    16. Soddu A,
    17. Schiff ND,
    18. Whitfield-Gabrieli S,
    19. Laureys S
    (2015) Intrinsic functional connectivity differentiates minimally conscious from unresponsive patients. Brain 138:2619–2631. doi:10.1093/brain/awv169 pmid:26117367
    OpenUrlCrossRefPubMed
  35. ↵
    1. Desmurget M,
    2. Reilly KT,
    3. Richard N,
    4. Szathmari A,
    5. Mottolese C,
    6. Sirigu A
    (2009) Movement intention after parietal cortex stimulation in humans. Science 324:811–813. doi:10.1126/science.1169896 pmid:19423830
    OpenUrlAbstract/FREE Full Text
  36. ↵
    1. Desmurget M,
    2. Song Z,
    3. Mottolese C,
    4. Sirigu A
    (2013) Re-establishing the merits of electrical brain stimulation. Trends Cogn Sci 17:442–449. doi:10.1016/j.tics.2013.07.002 pmid:23932195
    OpenUrlCrossRefPubMed
  37. ↵
    1. Eickhoff SB,
    2. Bzdok D,
    3. Laird AR,
    4. Roski C,
    5. Caspers S,
    6. Zilles K,
    7. Fox PT
    (2011) Co-activation patterns distinguish cortical modules, their connectivity and functional differentiation. Neuroimage 57:938–949. doi:10.1016/j.neuroimage.2011.05.021 pmid:21609770
    OpenUrlCrossRefPubMed
  38. ↵
    1. Emrich SM,
    2. Riggall AC,
    3. Larocque JJ,
    4. Postle BR
    (2013) Distributed patterns of activity in sensory cortex reflect the precision of multiple items maintained in visual short-term memory. J Neurosci 33:6516–6523. doi:10.1523/JNEUROSCI.5732-12.2013 pmid:23575849
    OpenUrlAbstract/FREE Full Text
  39. ↵
    1. Farah M
    (2004) Visual agnosia. Cambridge, MA: Massachusetts Institute of Technology.
  40. ↵
    1. Fischer DB,
    2. Boes AD,
    3. Demertzi A,
    4. Evrard HC,
    5. Laureys S,
    6. Edlow BL,
    7. Liu H,
    8. Saper CB,
    9. Pascual-Leone A,
    10. Fox MD,
    11. Geerling JC
    (2016) A human brain network derived from coma-causing brainstem lesions. Neurology 87:2427–2434. doi:10.1212/WNL.0000000000003404 pmid:27815400
    OpenUrlAbstract/FREE Full Text
  41. ↵
    1. Foster BL,
    2. Parvizi J
    (2017) Direct cortical stimulation of human posteromedial cortex. Neurology 88:685–691. doi:10.1212/WNL.0000000000003607 pmid:28100728
    OpenUrlAbstract/FREE Full Text
  42. ↵
    1. Frässle S,
    2. Sommer J,
    3. Jansen A,
    4. Naber M,
    5. Einhäuser W
    (2014) Binocular rivalry: frontal activity relates to introspection and action but not to perception. J Neurosci 34:1738–1747. doi:10.1523/JNEUROSCI.4403-13.2014 pmid:24478356
    OpenUrlAbstract/FREE Full Text
  43. ↵
    1. Gaskell AL,
    2. Hight DF,
    3. Winders J,
    4. Tran G,
    5. Defresne A,
    6. Bonhomme V,
    7. Raz A,
    8. Sleigh JW,
    9. Sanders RD
    (2017) Frontal alpha-δ EEG does not preclude volitional response during anaesthesia: EEG findings from a prospective cohort study using the isolated forearm technique. Br J Anaesth, in press.
  44. ↵
    1. George MS,
    2. Parekh PI,
    3. Rosinsky N,
    4. Ketter TA,
    5. Kimbrell TA,
    6. Heilman KM,
    7. Herscovitch P,
    8. Post RM
    (1996) Understanding emotional prosody activates right hemisphere regions. Arch Neurol 53:665–670. doi:10.1001/archneur.1996.00550070103017 pmid:8929174
    OpenUrlCrossRefPubMed
  45. ↵
    1. Gorgolewski KJ,
    2. Varoquaux G,
    3. Rivera G,
    4. Schwartz Y,
    5. Sochat VV,
    6. Ghosh SS,
    7. Maumet C,
    8. Nichols TE,
    9. Poline JB,
    10. Yarkoni T,
    11. Margulies DS,
    12. Poldrack RA
    (2016) NeuroVault.org: a repository for sharing unthresholded statistical maps, parcellations, and atlases of the human brain. Neuroimage 124:1242–1244. doi:10.1016/j.neuroimage.2015.04.016 pmid:25869863
    OpenUrlCrossRefPubMed
  46. ↵
    1. Gosseries O,
    2. Di H,
    3. Laureys S,
    4. Boly M
    (2014) Measuring consciousness in severely damaged brains. Annu Rev Neurosci 37:457–478. doi:10.1146/annurev-neuro-062012-170339 pmid:25002279
    OpenUrlCrossRefPubMed
  47. ↵
    1. Haynes JD
    (2009) Decoding visual consciousness from human brain signals. Trends Cogn Sci 13:194–202. doi:10.1016/j.tics.2009.02.004 pmid:19375378
    OpenUrlCrossRefPubMed
  48. ↵
    1. Hebb DO,
    2. Penfield W
    (1940) Human behavior after extensive bilateral removal from the frontal lobes. Arch Neurol Psychol 44:421–438. doi:10.1001/archneurpsyc.1940.02280080181011
    OpenUrlCrossRef
  49. ↵
    1. Henson R
    (2006) Forward inference using functional neuroimaging: dissociations versus associations. Trends Cogn Sci 10:64–69. doi:10.1016/j.tics.2005.12.005 pmid:16406759
    OpenUrlCrossRefPubMed
  50. ↵
    1. Horikawa T,
    2. Tamaki M,
    3. Miyawaki Y,
    4. Kamitani Y
    (2013) Neural decoding of visual imagery during sleep. Science 340:639–642. doi:10.1126/science.1234330 pmid:23558170
    OpenUrlAbstract/FREE Full Text
  51. ↵
    1. Johanson M,
    2. Revonsuo A,
    3. Chaplin J,
    4. Wedlund JE
    (2003) Level and contents of consciousness in connection with partial epileptic seizures. Epilepsy Behav 4:279–285. doi:10.1016/S1525-5050(03)00106-9 pmid:12791329
    OpenUrlCrossRefPubMed
  52. ↵
    1. Kajimura N,
    2. Uchiyama M,
    3. Takayama Y,
    4. Uchida S,
    5. Uema T,
    6. Kato M,
    7. Sekimoto M,
    8. Watanabe T,
    9. Nakajima T,
    10. Horikoshi S,
    11. Ogawa K,
    12. Nishikawa M,
    13. Hiroki M,
    14. Kudo Y,
    15. Matsuda H,
    16. Okawa M,
    17. Takahashi K
    (1999) Activity of midbrain reticular formation and neocortex during the progression of human non-rapid eye movement sleep. J Neurosci 19:10065–10073. pmid:10559414
    OpenUrlAbstract/FREE Full Text
  53. ↵
    1. Kampfl A,
    2. Schmutzhard E,
    3. Franz G,
    4. Pfausler B,
    5. Haring HP,
    6. Ulmer H,
    7. Felber S,
    8. Golaszewski S,
    9. Aichner F
    (1998) Prediction of recovery from post-traumatic vegetative state with cerebral magnetic-resonance imaging. Lancet 351:1763–1767. doi:10.1016/S0140-6736(97)10301-4 pmid:9635948
    OpenUrlCrossRefPubMed
  54. ↵
    1. Keller CJ,
    2. Honey CJ,
    3. Mégevand P,
    4. Entz L,
    5. Ulbert I,
    6. Mehta AD
    (2014) Mapping human brain networks with cortico-cortical evoked potentials. Philos Trans R Soc Lond B Biol Sci 369:20130528. doi:10.1098/rstb.2013.0528 pmid:25180306
    OpenUrlAbstract/FREE Full Text
  55. ↵
    1. King JR,
    2. Sitt JD,
    3. Faugeras F,
    4. Rohaut B,
    5. El Karoui I,
    6. Cohen L,
    7. Naccache L,
    8. Dehaene S
    (2013) Information sharing in the brain indexes consciousness in noncommunicative patients. Curr Biol 23:1914–1919. doi:10.1016/j.cub.2013.07.075 pmid:24076243
    OpenUrlCrossRefPubMed
  56. ↵
    1. King JR,
    2. Pescetelli N,
    3. Dehaene S
    (2016) Brain mechanisms underlying the brief maintenance of seen and unseen sensory information. Neuron 92:1122–1134. doi:10.1016/j.neuron.2016.10.051 pmid:27930903
    OpenUrlCrossRefPubMed
  57. ↵
    1. Koch C,
    2. Tsuchiya N
    (2012) Attention and consciousness: related yet different. Trends Cogn Sci 16:103–105. doi:10.1016/j.tics.2011.11.012 pmid:22154091
    OpenUrlCrossRefPubMed
  58. ↵
    1. Koch C,
    2. Massimini M,
    3. Boly M,
    4. Tononi G
    (2016a) Neural correlates of consciousness: progress and problems. Nat Rev Neurosci 17:307–321. doi:10.1038/nrn.2016.22 pmid:27094080
    OpenUrlCrossRefPubMed
  59. ↵
    1. Koch C,
    2. Massimini M,
    3. Boly M,
    4. Tononi G
    (2016b) Posterior and anterior cortex, where is the difference that makes the difference? Nat Rev Neurosci. Advance online publication. doi: 10.1038/nrn.2016.105. doi:10.1038/nrn.2016.105 pmid:27466141
    OpenUrlCrossRefPubMed
  60. ↵
    1. Koenigs M,
    2. Young L,
    3. Adolphs R,
    4. Tranel D,
    5. Cushman F,
    6. Hauser M,
    7. Damasio A
    (2007) Damage to the prefrontal cortex increases utilitarian moral judgements. Nature 446:908–911. doi:10.1038/nature05631 pmid:17377536
    OpenUrlCrossRefPubMed
  61. ↵
    1. Koivisto M,
    2. Revonsuo A
    (2010) Event-related brain potential correlates of visual awareness. Neurosci Biobehav Rev 34:922–934. doi:10.1016/j.neubiorev.2009.12.002 pmid:20005249
    OpenUrlCrossRefPubMed
  62. ↵
    1. Kozuch B
    (2014) Prefrontal lesion evidence against higher-order theories of consciousness. Philos Stud. 167:721–746. doi:10.1007/s11098-013-0123-9
    OpenUrlCrossRef
  63. ↵
    1. Kriegeskorte N
    (2011) Pattern-information analysis: from stimulus decoding to computational-model testing. Neuroimage 56:411–421. doi:10.1016/j.neuroimage.2011.01.061 pmid:21281719
    OpenUrlCrossRefPubMed
  64. ↵
    1. Kundishora AJ,
    2. Gummadavelli A,
    3. Ma C,
    4. Liu M,
    5. McCafferty C,
    6. Schiff ND,
    7. Willie JT,
    8. Gross RE,
    9. Gerrard J,
    10. Blumenfeld H
    (2017) Restoring conscious arousal during focal limbic seizures with deep brain stimulation. Cereb Cortex 27:1964–1975. doi:10.1093/cercor/bhw035 pmid:26941379
    OpenUrlCrossRefPubMed
  65. ↵
    1. Lamme VA
    (2006) Towards a true neural stance on consciousness. Trends Cogn Sci 10:494–501. doi:10.1016/j.tics.2006.09.001 pmid:16997611
    OpenUrlCrossRefPubMed
  66. ↵
    1. Lau H,
    2. Rosenthal D
    (2011) Empirical support for higher-order theories of conscious awareness. Trends Cogn Sci 15:365–373. doi:10.1016/j.tics.2011.05.009 pmid:21737339
    OpenUrlCrossRefPubMed
  67. ↵
    1. Laureys S,
    2. Schiff ND
    (2012) Coma and consciousness: paradigms (re)framed by neuroimaging. Neuroimage 61:478–491. doi:10.1016/j.neuroimage.2011.12.041 pmid:22227888
    OpenUrlCrossRefPubMed
  68. ↵
    1. Laureys S,
    2. Owen AM,
    3. Schiff ND
    (2004) Brain function in coma, vegetative state, and related disorders. Lancet Neurol 3:537–546. doi:10.1016/S1474-4422(04)00852-X pmid:15324722
    OpenUrlCrossRefPubMed
  69. ↵
    1. Lou HC,
    2. Kjaer TW,
    3. Friberg L,
    4. Wildschiodtz G,
    5. Holm S,
    6. Nowak M
    (1999) A 15O-H2O PET study of meditation and the resting state of normal consciousness. Hum Brain Mapp 7:98–105. doi:10.1002/(SICI)1097-0193(1999)7:2%3C98::AID-HBM3%3E3.3.CO%3B2-D pmid:9950067
    OpenUrlCrossRefPubMed
  70. ↵
    1. Lumer ED,
    2. Friston KJ,
    3. Rees G
    (1998) Neural correlates of perceptual rivalry in the human brain. Science 280:1930–1934. doi:10.1126/science.280.5371.1930 pmid:9632390
    OpenUrlAbstract/FREE Full Text
  71. ↵
    1. Mah YH,
    2. Husain M,
    3. Rees G,
    4. Nachev P
    (2014) Human brain lesion-deficit inference remapped. Brain 137:2522–2531. doi:10.1093/brain/awu164 pmid:24974384
    OpenUrlCrossRefPubMed
  72. ↵
    1. Markowitsch HJ,
    2. Kessler J
    (2000) Massive impairment in executive functions with partial preservation of other cognitive functions: the case of a young patient with severe degeneration of the prefrontal cortex. Exp Brain Res 133:94–102. doi:10.1007/s002210000404 pmid:10933214
    OpenUrlCrossRefPubMed
  73. ↵
    1. Mataró M,
    2. Jurado MA,
    3. García-Sánchez C,
    4. Barraquer L,
    5. Costa-Jussà FR,
    6. Junqué C
    (2001) Long-term effects of bilateral frontal brain lesion: 60 years after injury with an iron bar. Arch Neurol 58:1139–1142. doi:10.1001/archneur.58.7.1139 pmid:11448304
    OpenUrlCrossRefPubMed
  74. ↵
    1. Meador KJ,
    2. Revill KP,
    3. Epstein CM,
    4. Sathian K,
    5. Loring DW,
    6. Rorden C
    (2017) Neuroimaging somatosensory perception and masking. Neuropsychologia 94:44–51. doi:10.1016/j.neuropsychologia.2016.11.017 pmid:27894900
    OpenUrlCrossRefPubMed
  75. ↵
    1. Mégevand P,
    2. Groppe DM,
    3. Goldfinger MS,
    4. Hwang ST,
    5. Kingsley PB,
    6. Davidesco I,
    7. Mehta AD
    (2014) Seeing scenes: topographic visual hallucinations evoked by direct electrical stimulation of the parahippocampal place area. J Neurosci 34:5399–5405. doi:10.1523/JNEUROSCI.5202-13.2014 pmid:24741031
    OpenUrlAbstract/FREE Full Text
  76. ↵
    1. Melloni L,
    2. Schwiedrzik CM,
    3. Müller N,
    4. Rodriguez E,
    5. Singer W
    (2011) Expectations change the signatures and timing of electrophysiological correlates of perceptual awareness. J Neurosci 31:1386–1396. doi:10.1523/JNEUROSCI.4570-10.2011 pmid:21273423
    OpenUrlAbstract/FREE Full Text
  77. ↵
    1. Mettler FA
    (1949) Selective partial ablation of the frontal cortex, a correlative study of its effects on human psychotic subjects. New York: Hoebar.
  78. ↵
    1. Miller SM
    (2007) On the correlation/constitution distinction problem (and other hard problems) in the scientific study of consciousness. Acta Neuropsychiatr 19:159–176. doi:10.1111/j.1601-5215.2007.00207.x pmid:26952854
    OpenUrlCrossRefPubMed
  79. ↵
    1. Moran JM,
    2. Zaki J
    (2013) Functional neuroimaging and psychology: what have you done for me lately? J Cogn Neurosci 25:834–842. doi:10.1162/jocn_a_00380 pmid:23469884
    OpenUrlCrossRefPubMed
  80. ↵
    1. Moruzzi G,
    2. Magoun HW
    (1949) Brain stem reticular formation and activation of the EEG. Electroencephalogr Clin Neurophysiol 1:455–473. doi:10.1016/0013-4694(49)90219-9 pmid:18421835
    OpenUrlCrossRefPubMed
  81. ↵
    1. Nishimoto S,
    2. Vu AT,
    3. Naselaris T,
    4. Benjamini Y,
    5. Yu B,
    6. Gallant JL
    (2011) Reconstructing visual experiences from brain activity evoked by natural movies. Curr Biol 21:1641–1646. doi:10.1016/j.cub.2011.08.031 pmid:21945275
    OpenUrlCrossRefPubMed
  82. ↵
    1. Noy N,
    2. Bickel S,
    3. Zion-Golumbic E,
    4. Harel M,
    5. Golan T,
    6. Davidesco I,
    7. Schevon CA,
    8. McKhann GM,
    9. Goodman RR,
    10. Schroeder CE,
    11. Mehta AD,
    12. Malach R
    (2015) Ignition's glow: ultra-fast spread of global cortical activity accompanying local “ignitions” in visual cortex during conscious visual perception. Conscious Cogn 35:206–224. doi:10.1016/j.concog.2015.03.006 pmid:25824626
    OpenUrlCrossRefPubMed
  83. ↵
    1. Parvizi J,
    2. Rangarajan V,
    3. Shirer WR,
    4. Desai N,
    5. Greicius MD
    (2013) The will to persevere induced by electrical stimulation of the human cingulate gyrus. Neuron 80:1359–1367. doi:10.1016/j.neuron.2013.10.057 pmid:24316296
    OpenUrlCrossRefPubMed
  84. ↵
    1. Pascual-Leone A,
    2. Gates JR,
    3. Dhuna A
    (1991) Induction of speech arrest and counting errors with rapid-rate transcranial magnetic stimulation. Neurology 41:697–702. doi:10.1212/WNL.41.5.697 pmid:2027485
    OpenUrlAbstract/FREE Full Text
  85. ↵
    1. Penfield W
    (1959) The interpretive cortex; the stream of consciousness in the human brain can be electrically reactivated. Science 129:1719–1725. doi:10.1126/science.129.3365.1719 pmid:13668523
    OpenUrlAbstract/FREE Full Text
  86. ↵
    1. Penfield W,
    2. Jasper HH
    (1954) Epilepsy and the functional anatomy of the brain. Boston: Little Brown.
  87. ↵
    1. Perogamvros L,
    2. Baird B,
    3. Seibold M,
    4. Riedner B,
    5. Boly M,
    6. Tononi G
    (2017) The phenomenal contents and neural correlates of spontaneous thoughts across wakefulness, NREM sleep and REM sleep. J Cogn Neurosci. Advance online publication. doi: 10.1162/jocn_a_01155. doi:10.1162/jocn_a_01155 pmid:28562209
    OpenUrlCrossRefPubMed
  88. ↵
    1. Pigorini A,
    2. Sarasso S,
    3. Proserpio P,
    4. Szymanski C,
    5. Arnulfo G,
    6. Casarotto S,
    7. Fecchio M,
    8. Rosanova M,
    9. Mariotti M,
    10. Lo Russo G,
    11. Palva JM,
    12. Nobili L,
    13. Massimini M
    (2015) Bistability breaks-off deterministic responses to intracortical stimulation during non-REM sleep. Neuroimage 112:105–113. doi:10.1016/j.neuroimage.2015.02.056 pmid:25747918
    OpenUrlCrossRefPubMed
  89. ↵
    1. Pitts MA,
    2. Martínez A,
    3. Hillyard SA
    (2012) Visual processing of contour patterns under conditions of inattentional blindness. J Cogn Neurosci 24:287–303. doi:10.1162/jocn_a_00111 pmid:21812561
    OpenUrlCrossRefPubMed
  90. ↵
    1. Pitts MA,
    2. Metzler S,
    3. Hillyard SA
    (2014) Isolating neural correlates of conscious perception from neural correlates of reporting one's perception. Front Psychol 5:1078. doi:10.3389/fpsyg.2014.01078 pmid:25339922
    OpenUrlCrossRefPubMed
  91. ↵
    1. Poldrack RA
    (2006) Can cognitive processes be inferred from neuroimaging data? Trends Cogn Sci 10:59–63. doi:10.1016/j.tics.2005.12.004 pmid:16406760
    OpenUrlCrossRefPubMed
  92. ↵
    1. Poldrack RA,
    2. Farah MJ
    (2015) Progress and challenges in probing the human brain. Nature 526:371–379. doi:10.1038/nature15692 pmid:26469048
    OpenUrlCrossRefPubMed
  93. ↵
    1. Poldrack RA,
    2. Yarkoni T
    (2016) From brain maps to cognitive ontologies: informatics and the search for mental structure. Annu Rev Psychol 67:587–612. doi:10.1146/annurev-psych-122414-033729 pmid:26393866
    OpenUrlCrossRefPubMed
  94. ↵
    1. Popa I,
    2. Donos C,
    3. Barborica A,
    4. Opris I,
    5. Mălîia MD,
    6. Ene M,
    7. Ciurea J,
    8. Mîndruţă I
    (2016) Intrusive thoughts elicited by direct electrical stimulation during stereo-electroencephalography. Front Neurol 7:114. doi:10.3389/fneur.2016.00114 pmid:27486431
    OpenUrlCrossRefPubMed
  95. ↵
    1. Postle BR
    (2015) The cognitive neuroscience of visual short-term memory. Curr Opin Behav Sci 1:40–46. doi:10.1016/j.cobeha.2014.08.004 pmid:26516631
    OpenUrlCrossRefPubMed
  96. ↵
    1. Quiroga RQ
    (2012) Concept cells: the building blocks of declarative memory functions. Nat Rev Neurosci 13:587–597. doi:10.1038/nrn3251 pmid:22760181
    OpenUrlCrossRefPubMed
  97. ↵
    1. Rangarajan V,
    2. Hermes D,
    3. Foster BL,
    4. Weiner KS,
    5. Jacques C,
    6. Grill-Spector K,
    7. Parvizi J
    (2014) Electrical stimulation of the left and right human fusiform gyrus causes different effects in conscious face perception. J Neurosci 34:12828–12836. doi:10.1523/JNEUROSCI.0527-14.2014 pmid:25232118
    OpenUrlAbstract/FREE Full Text
  98. ↵
    1. Rauschecker AM,
    2. Dastjerdi M,
    3. Weiner KS,
    4. Witthoft N,
    5. Chen J,
    6. Selimbeyoglu A,
    7. Parvizi J
    (2011) Illusions of visual motion elicited by electrical stimulation of human MT complex. PLoS One 6:e21798. doi:10.1371/journal.pone.0021798 pmid:21765915
    OpenUrlCrossRefPubMed
  99. ↵
    1. Rutiku R,
    2. Aru J,
    3. Bachmann T
    (2016) General markers of conscious visual perception and their timing. Front Hum Neurosci 10:23. doi:10.3389/fnhum.2016.00023 pmid:26869905
    OpenUrlCrossRefPubMed
  100. ↵
    1. Samaha J,
    2. Gosseries O,
    3. Postle BR
    (2017) Distinct oscillatory frequencies underlie excitability of human occipital and parietal cortex. J Neurosci 37:2824–2833. doi:10.1523/JNEUROSCI.3413-16.2017 pmid:28179556
    OpenUrlAbstract/FREE Full Text
  101. ↵
    1. Sandberg K,
    2. Andersen LM,
    3. Overgaard M
    (2014) Using multivariate decoding to go beyond contrastive analyses in consciousness research. Front Psychol 5:1250. doi:10.3389/fpsyg.2014.01250 pmid:25400616
    OpenUrlCrossRefPubMed
  102. ↵
    1. Sanders RD,
    2. Tononi G,
    3. Laureys S,
    4. Sleigh JW
    (2012) Unresponsiveness not equal unconsciousness. Anesthesiology 116:946–959. doi:10.1097/ALN.0b013e318249d0a7 pmid:22314293
    OpenUrlCrossRefPubMed
  103. ↵
    1. Schiff ND
    (2010) Recovery of consciousness after brain injury: a mesocircuit hypothesis. Trends Neurosci 33:1–9. doi:10.1016/j.tins.2009.11.002 pmid:19954851
    OpenUrlCrossRefPubMed
  104. ↵
    1. Schiff ND,
    2. Giacino JT,
    3. Kalmar K,
    4. Victor JD,
    5. Baker K,
    6. Gerber M,
    7. Fritz B,
    8. Eisenberg B,
    9. Biondi T,
    10. O'Connor J,
    11. Kobylarz EJ,
    12. Farris S,
    13. Machado A,
    14. McCagg C,
    15. Plum F,
    16. Fins JJ,
    17. Rezai AR
    (2007) Behavioural improvements with thalamic stimulation after severe traumatic brain injury. Nature 448:600–603. doi:10.1038/nature06041 pmid:17671503
    OpenUrlCrossRefPubMed
  105. ↵
    1. Selimbeyoglu A,
    2. Parvizi J
    (2010) Electrical stimulation of the human brain: perceptual and behavioral phenomena reported in the old and new literature. Front Hum Neurosci 4:46. doi:10.3389/fnhum.2010.00046 pmid:20577584
    OpenUrlCrossRefPubMed
  106. ↵
    1. Seth AK,
    2. Suzuki K,
    3. Critchley HD
    (2011) An interoceptive predictive coding model of conscious presence. Front Psychol 2:395. doi:10.3389/fpsyg.2011.00395 pmid:22291673
    OpenUrlCrossRefPubMed
  107. ↵
    1. Siclari F,
    2. LaRocque JJ,
    3. Bernardi G,
    4. Postle BR,
    5. Tononi G
    (2014) The neural correlates of consciousness in sleep: a no-task, within-state paradigm. BioRXiv. Available at: http://www.biorxiv.org/content/early/2014/12/30/012443.
  108. ↵
    1. Siclari F,
    2. Baird B,
    3. Perogamvros L,
    4. Bernardi G,
    5. LaRocque JJ,
    6. Riedner B,
    7. Boly M,
    8. Postle BR,
    9. Tononi G
    (2017) The neural correlates of dreaming. Nat Neurosci 20:872–878. doi:10.1038/nn.4545 pmid:28394322
    OpenUrlCrossRefPubMed
  109. ↵
    1. Silvanto J,
    2. Pascual-Leone A
    (2012) Why the assessment of causality in brain-behavior relations requires brain stimulation. J Cogn Neurosci 24:775–777. doi:10.1162/jocn_a_00193 pmid:22264196
    OpenUrlCrossRefPubMed
  110. ↵
    1. Sirigu A,
    2. Daprati E,
    3. Ciancia S,
    4. Giraux P,
    5. Nighoghossian N,
    6. Posada A,
    7. Haggard P
    (2004) Altered awareness of voluntary action after damage to the parietal cortex. Nat Neurosci 7:80–84. doi:10.1038/nn1160 pmid:14647290
    OpenUrlCrossRefPubMed
  111. ↵
    1. Solms M
    (2014) The neuropsychology of dreams: a clinico-anatomical study. New York: Psychology.
  112. ↵
    1. Stender J,
    2. Mortensen KN,
    3. Thibaut A,
    4. Darkner S,
    5. Laureys S,
    6. Gjedde A,
    7. Kupers R
    (2016) The minimal energetic requirement of sustained awareness after brain injury. Curr Biol 26:1494–1499. doi:10.1016/j.cub.2016.04.024 pmid:27238279
    OpenUrlCrossRefPubMed
  113. ↵
    1. Tononi G,
    2. Boly M,
    3. Massimini M,
    4. Koch C
    (2016a) Integrated information theory: from consciousness to its physical substrate. Nat Rev Neurosci 17:450–461. doi:10.1038/nrn.2016.44 pmid:27225071
    OpenUrlCrossRefPubMed
  114. ↵
    1. Tononi G,
    2. Boly M,
    3. Gosseries O,
    4. Laureys S
    (2016b) The neurology of consciousness: an overview. In: The neurology of consciousness, Ed 2 (Laureys S, Tononi G, eds), pp 463–471. Amsterdam: Elsevier.
  115. ↵
    1. Tsuchiya N,
    2. Koch C
    (2016) The relationship between consciousness and top-down attention. In: The neurology of consciousness, Ed 2 (Tononi G, Gosseries O, Laureys S, eds), pp 69–89. Amsterdam: Elsevier.
  116. ↵
    1. Tsuchiya N,
    2. Wilke M,
    3. Frässle S,
    4. Lamme VA
    (2015) No-report paradigms: extracting the true neural correlates of consciousness. Trends Cogn Sci 19:757–770. doi:10.1016/j.tics.2015.10.002 pmid:26585549
    OpenUrlCrossRefPubMed
  117. ↵
    1. Tsuchiya N,
    2. Frässle S,
    3. Wilke M,
    4. Lamme V
    (2016) No-report and report-based paradigms jointly unravel the NCC: response to Overgaard and Fazekas. Trends Cogn Sci 20:242–243. doi:10.1016/j.tics.2016.01.006 pmid:26899261
    OpenUrlCrossRefPubMed
  118. ↵
    1. Vanhaudenhuyse A,
    2. Noirhomme Q,
    3. Tshibanda LJ,
    4. Bruno MA,
    5. Boveroux P,
    6. Schnakers C,
    7. Soddu A,
    8. Perlbarg V,
    9. Ledoux D,
    10. Brichant JF,
    11. Moonen G,
    12. Maquet P,
    13. Greicius MD,
    14. Laureys S,
    15. Boly M
    (2010) Default network connectivity reflects the level of consciousness in non-communicative brain-damaged patients. Brain 133:161–171. doi:10.1093/brain/awp313 pmid:20034928
    OpenUrlCrossRefPubMed
  119. ↵
    1. von Arx SW,
    2. Müri RM,
    3. Heinemann D,
    4. Hess CW,
    5. Nyffeler T
    (2010) Anosognosia for cerebral achromatopsia: a longitudinal case study. Neuropsychologia 48:970–977. doi:10.1016/j.neuropsychologia.2009.11.018 pmid:19944708
    OpenUrlCrossRefPubMed
  120. ↵
    1. Winawer J,
    2. Parvizi J
    (2016) Linking electrical stimulation of human primary visual cortex, size of affected cortical area, neuronal responses, and subjective experience. Neuron 92:1213–1219. doi:10.1016/j.neuron.2016.11.008 pmid:27939584
    OpenUrlCrossRefPubMed
  121. ↵
    1. Wu X,
    2. Zou Q,
    3. Hu J,
    4. Tang W,
    5. Mao Y,
    6. Gao L,
    7. Zhu J,
    8. Jin Y,
    9. Wu X,
    10. Lu L,
    11. Zhang Y,
    12. Zhang Y,
    13. Dai Z,
    14. Gao JH,
    15. Weng X,
    16. Zhou L,
    17. Northoff G,
    18. Giacino JT,
    19. He Y,
    20. Yang Y
    (2015) Intrinsic functional connectivity patterns predict consciousness level and recovery outcome in acquired brain injury. J Neurosci 35:12932–12946. doi:10.1523/JNEUROSCI.0415-15.2015 pmid:26377477
    OpenUrlAbstract/FREE Full Text
  122. ↵
    1. Yarkoni T,
    2. Poldrack RA,
    3. Van Essen DC,
    4. Wager TD
    (2010) Cognitive neuroscience 2.0: building a cumulative science of human brain function. Trends Cogn Sci 14:489–496. doi:10.1016/j.tics.2010.08.004 pmid:20884276
    OpenUrlCrossRefPubMed
  123. ↵
    1. Yarkoni T,
    2. Poldrack RA,
    3. Nichols TE,
    4. Van Essen DC,
    5. Wager TD
    (2011) Large-scale automated synthesis of human functional neuroimaging data. Nat Methods 8:665–670. doi:10.1038/nmeth.1635 pmid:21706013
    OpenUrlCrossRefPubMed

Response from Dual Perspectives Companion Authors–Brian Odegaard, Robert T. Knight, and Hakwan Lau

We welcome the opportunity to address the issues raised by Boly et al. Much of the basis of our disagreement with their views has already been covered in our article. In essence, we think it is misguided to downplay the role of the PFC in conscious perception based on their selective review of the literature.

One useful point Boly et al. raised is that we should carefully distinguish between different aspects of consciousness. In the case of patients with large bilateral prefrontal lesions, we argued that they lack consciousness in the sense of not displaying goal-directed, meaningful interaction with objects in the external world. But one may ask: do they specifically have normal subjective perceptual experiences? Arguably, the most challenging and conceptually important questions about consciousness concern subjective experiences.

To clarify the issue, we included a video of such a patient. Our point is that this question is difficult to address in a decisive manner, given the inability of these lateral frontal lesioned patients to provide meaningful responses to queries. Notice also the striking difference compared with another patient with extensive damage to the orbitofrontal cortex, highlighting the regional differences in prefrontal damage and conscious behavior.

Despite this difficulty, other evidence based on transcranial magnetic stimulation (Rounis et al., 2010) and frontal lesions (Fleming et al., 2014) shows that such patients are impaired in subjective perceptual experience.

We also want to reemphasize that patients with extensive bilateral parieto-occipital damage with visual agnosias are also conscious by the criteria of showing goal-directed actions toward the external world. This is not to say that these regions are not critical for aspects of sensory perception, as noted by Boly et al.

We think that this exchange is an important reminder that data interpretation often depends on details. As such, we are unsure about their suggestion that we can make use of meta-analytic databases, such as Neurosynth, to definitively settle these issues. In some areas of research, meta-analysis is no doubt useful. But consciousness is an emerging field, where discussion regarding, for example, what counts as an appropriate experimental design, what existing measures are valid, and how to control for confounds, is important.

A case in point is perhaps a recent study by some of the same authors as Boly et al. on EEG correlates of dreams (Siclari et al., 2017). As pointed out in our article, a significant finding emerged in PFC but was not emphasized, similar to other examples in recent literature. A meta-analytic study may well miss the positive prefrontal results because they were not reported and highlighted as main findings by the authors. Such meta-analytic approaches may also overemphasize neuroimaging methods with limited sensitivity.

Instead, we advocate the importance of continuing the present kind of conversation in depth. Traditionally, much discussion on human consciousness takes the form of authoritative scholars advocating intriguing theories and ideas, but placing relatively little emphasis on conflicting data. To make true progress as a rigorous scientific field, we need open and legitimate platforms, on which theoretical viewpoints are critically scrutinized and evaluated from multiple angles. The meetings for the Association for the Scientific Studies of Consciousness provide excellent opportunities for us to continue these kind of debates, as well as the opportunity to keep up to date with this burgeoning and exciting literature.

Finally, Boly et al. cite 2 articles in their response (Schoenemann et al, 2005; Kennedy et al, 1998). Boly et al.'s conclusion is that the non area 4 and 6 PFC is only 13% of the cortical mantle. They fail to notice that the criteria for PFC was tissue anterior to the genu of the corpus callosum. Simple inspection of Fig 1a in Schoenemann et al (2005) reveals that this method severely underestimates PFC (note the location of the central sulcus on the right of Fig 1a.) The true percentage of non area 4 and 6 PFC is closer to 20–25% of the cortical mantle.

References

  1. ↵
    1. Fleming SM,
    2. Ryu J,
    3. Golfinos JG,
    4. Blackmon KE
    (2014) Domain-specific impairment in metacognitive accuracy following anterior prefrontal lesions. Brain 137:2811–2822. doi:10.1093/brain/awu221 pmid:25100039
    OpenUrlCrossRefPubMed
  2. ↵
    1. Rounis E,
    2. Maniscalco B,
    3. Rothwell JC,
    4. Passingham RE,
    5. Lau H
    (2010) Theta-burst transcranial magnetic stimulation to the prefrontal cortex impairs metacognitive visual awareness. Cogn Neurosci 1:165–175. doi:10.1080/17588921003632529 pmid:24168333
    OpenUrlCrossRefPubMed
  3. ↵
    1. Siclari F,
    2. Baird B,
    3. Perogamvros L,
    4. Bernardi G,
    5. LaRocque JJ,
    6. Riedner B,
    7. Boly M,
    8. Postle BR,
    9. Tononi G
    (2017) The neural correlates of dreaming. Nat Neurosci 20:872–878. doi:10.1038/nn.4545 pmid:28394322
    OpenUrlCrossRefPubMed
View Abstract
Back to top

In this issue

The Journal of Neuroscience: 37 (40)
Journal of Neuroscience
Vol. 37, Issue 40
4 Oct 2017
  • Table of Contents
  • Table of Contents (PDF)
  • About the Cover
  • Index by author
  • Advertising (PDF)
  • Ed Board (PDF)
Email

Thank you for sharing this Journal of Neuroscience article.

NOTE: We request your email address only to inform the recipient that it was you who recommended this article, and that it is not junk mail. We do not retain these email addresses.

Enter multiple addresses on separate lines or separate them with commas.
Are the Neural Correlates of Consciousness in the Front or in the Back of the Cerebral Cortex? Clinical and Neuroimaging Evidence
(Your Name) has forwarded a page to you from Journal of Neuroscience
(Your Name) thought you would be interested in this article in Journal of Neuroscience.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Print
View Full Page PDF
Citation Tools
Are the Neural Correlates of Consciousness in the Front or in the Back of the Cerebral Cortex? Clinical and Neuroimaging Evidence
Melanie Boly, Marcello Massimini, Naotsugu Tsuchiya, Bradley R. Postle, Christof Koch, Giulio Tononi
Journal of Neuroscience 4 October 2017, 37 (40) 9603-9613; DOI: 10.1523/JNEUROSCI.3218-16.2017

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Respond to this article
Request Permissions
Share
Are the Neural Correlates of Consciousness in the Front or in the Back of the Cerebral Cortex? Clinical and Neuroimaging Evidence
Melanie Boly, Marcello Massimini, Naotsugu Tsuchiya, Bradley R. Postle, Christof Koch, Giulio Tononi
Journal of Neuroscience 4 October 2017, 37 (40) 9603-9613; DOI: 10.1523/JNEUROSCI.3218-16.2017
del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Jump to section

  • Article
    • Abstract
    • Introduction
    • Distinguishing between the neural correlates of consciousness and other neural processes
    • Footnotes
    • References
    • Response from Dual Perspectives Companion Authors–Brian Odegaard, Robert T. Knight, and Hakwan Lau
    • References
  • Figures & Data
  • Info & Metrics
  • eLetters
  • PDF

Keywords

  • consciousness
  • frontal cortex
  • lesion studies
  • neuroimaging
  • stimulation studies

Responses to this article

Respond to this article

Jump to comment:

No eLetters have been published for this article.

Related Articles

Cited By...

More in this TOC Section

  • Studying Human Neurodevelopment and Diseases Using 3D Brain Organoids
  • Integrating CRISPR Engineering and hiPSC-Derived 2D Disease Modeling Systems
  • Forebrain Cholinergic Signaling: Wired and Phasic, Not Tonic, and Causing Behavior
Show more Dual Perspectives
  • Home
  • Alerts
  • Visit Society for Neuroscience on Facebook
  • Follow Society for Neuroscience on Twitter
  • Follow Society for Neuroscience on LinkedIn
  • Visit Society for Neuroscience on Youtube
  • Follow our RSS feeds

Content

  • Early Release
  • Current Issue
  • Issue Archive
  • Collections

Information

  • For Authors
  • For Advertisers
  • For the Media
  • For Subscribers

About

  • About the Journal
  • Editorial Board
  • Privacy Policy
  • Contact
  • Feedback
(JNeurosci logo)
(SfN logo)

Copyright © 2021 by the Society for Neuroscience.
JNeurosci Online ISSN: 1529-2401

The ideas and opinions expressed in JNeurosci do not necessarily reflect those of SfN or the JNeurosci Editorial Board. Publication of an advertisement or other product mention in JNeurosci should not be construed as an endorsement of the manufacturer’s claims. SfN does not assume any responsibility for any injury and/or damage to persons or property arising from or related to any use of any material contained in JNeurosci.