Cerebral Cortex Advance Access originally published online on May 12, 2006
Cerebral Cortex 2007 17(4):760-765; doi:10.1093/cercor/bhk029
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Similar Frontal and Distinct Posterior Cortical Regions Mediate Visual and Auditory Perceptual Awareness
1 Department of Psychology, 2 Department of Radiation Science, Radiation Physics, Umeå University, S-901 87 Umeå, Sweden, 3 Umeå Centre for Functional Brain Imaging (UFBI), Umeå, Sweden, 4 Department of Radiation Sciences, Diagnostic Radiology, 5 Department of Integrative Medical Biology, Physiology Section, Umeå University, S-901 87 Umeå, Sweden
Address correspondence to Johan Eriksson, Department of Psychology, Umeå University, S-901 87 Umeå, Sweden. Email: johan.eriksson{at}psy.umu.se.
 |
Abstract |
|---|
 Top Abstract IntroductionMethodsResultsDiscussionSupplementary MaterialReferences |
|---|
Activity in ventral visual cortex is a consistent neural correlate of visual consciousness. However, activity in this area seems insufficient to produce awareness without additional involvement of frontoparietal regions. To test the generality of the frontoparietal response, neural correlates of auditory awareness were investigated in a paradigm that previously has revealed frontoparietal activity during conscious visual perception. A within-experiment comparison showed that frontal regions were related to both visual and auditory awareness, whereas parietal activity was correlated with visual awareness and superior temporal activity with auditory awareness. These results indicate that frontal regions interact with specific posterior regions to produce awareness in different sensory modalities.
Key Words: auditory awareness • fMRI • parietal cortex • prefrontal cortex • visual awareness
|
Introduction |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionSupplementary MaterialReferences |
|---|
Consciousness is a central concept in the history of psychology (Leahey 2000
) but has only more recently become a topic of study in the neurosciences. How the brain implements consciousness has been labeled "the deepest of biological mysteries" (Kandel and others 2000). Searching for the neural correlates of consciousness, defined as neuronal events that give rise to a specific aspect of a conscious percept, has been proposed as a framework for consciousness (Crick and Koch 2003). Several previous studies have found that activity in regions in ventral visual cortex is correlated with visual conscious perception (Sheinberg and Logothetis 1997; Tong and others 1998; Grill-Spector and others 2000). However, such activity has been suggested to be necessary but not sufficient for conscious visual experience in the sense that additional contribution from parietal and prefrontal loci is required (Rees and others 2002). This suggestion is supported by the functional magnetic resonance imaging (fMRI) studies that show transient changes in frontoparietal brain activity related to visual conscious experience (Kleinschmidt and others 1998; Lumer and others 1998; Portas and others 2000; Eriksson and others 2004), as well as other studies that have implicated frontoparietal regions with conscious awareness (McIntosh and others 1999; Beck and others 2001; Dehaene and others 2001; Kjaer and others 2001; Ehrsson and others 2004). Moreover, frontoparietal activity has consistently been observed in relation to visual attention (Kanwisher and Wojciulik 2000) and visual working memory (Baddeley 2003), and similarities in frontoparietal activity for awareness, attention, and working memory have been noted (Lumer and others 1998).
Most previous studies on conscious perception have involved visual stimuli (Rees and others 2002). In the present study, we tested the generality of frontoparietal activity by examining conscious perception in the visual and auditory modalities with a fMRI paradigm that previously has revealed frontoparietal activity during visual conscious perception (Portas and others 2000; Eriksson and others 2004). This paradigm makes it possible to isolate transient brain activity related to conscious awareness (Fig. 1a). We found that similar frontal regions were related to conscious perception in both the visual and auditory domains. By contrast, posterior brain activity was domain selective with occipitotemporal and parietal activation for visual stimuli and superior temporal activation for auditory stimuli.
|
|
Methods |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionSupplementary MaterialReferences |
|---|
Experiment 1
Participants
Sixteen neurologically healthy subjects participated in the study, 24–37 years old (8 women). All participants were right handed by self-report, had normal or corrected to normal vision, and no hearing impairments. Participants gave their informed consent, and the study was approved by the ethics committee at the University Hospital of Northern Sweden.
Stimulus Material
The stimuli consisted of sounds of objects (animals) rather than tones because this is more perceptually and conceptually comparable with visual object recognition (Bregman 1990). The stimulus consisted of 24 animal sounds deemed commonly known, such as pig, dog, lion, etc. A background noise (consisting of a conglomerate of all animal sounds used) was custom made for each animal sound. Specifically, the noise was made louder on some sections and quieter on others. This was to make melodic and pitch clues less pronounced and thereby making the different animal sounds more comparable in terms of recognizability. The animal sounds were made either 1 x 4 or 2 x 4 s long to match the timing of the noise reduction steps (4 s, see Procedures) and were looped during playback to create a continuous sound image. The choice between 1 x 4 and 2 x 4 s was based on whether the animal had a characteristically repetitive sound or not. For example, a cricket would get 1 x 4 s, whereas the howling of a wolf would get 2 x 4 s.
Procedure
Each animal sound remained constant throughout the trial with a loop of 4.0 or 8.0 s (see Stimulus Material) and a stimulus onset asynchrony of 60.0 s. The participants were required to fixate on a black crosshair centered on a white screen throughout the experiment. Every 4.0 s, the noise level was reduced one step (one step is –120, where 0 is no reduction and –10 000 is complete silence, see E-Prime manual, Psychology Software Tools, Inc. [Pittsburgh, PA], for further detail) until the subject pressed a button with their left hand, thereby indicating animal identification. This motor response was accompanied by a change in background screen color from white to green. After identification, the subject was required to continue attending to the animal sound during the remainder of the trial (sustained perception).
During the period of sustained perception, a second change of background color, from green to white, prompted the subject to press the button once again. This subsequent motor response served as control for any brain activation in the first response that was due to the response itself and not to perceptual identification because it also consisted of seeing a color change and performing the same motor act (Fig. 1a). This second response occurred 8.0–12.0 s after identification. Following the second response, the stimulus presentation continued for 12.0 s. The described procedure with 1 target identification, 2 motor responses, and an unbroken period of sustained perception enables a comparison of the 3 conditions and identification of brain activity specifically associated with each effect.
If identification did not occur within 28 s, the sound and trial were terminated because there would not be enough time left of the remaining trial to reliably separate each effect of interest. Although each stimulus was constructed with the aim of an identification time of 8–28 s, no lower boundary was set. This was based on the argument that if a larger proportion of the identifications occurred after 8 s, occasional early responses would still provide useful information as in a jittered design (Donaldson and Buckner 2001) and not be confounded by stimulus onset.
The participants were asked to identify each animal as fast as possible. To avoid false-positive responses, trials with only noise and no animal sound were intermixed with the other trials, and the participants were explicitly told not to respond unless they could identify the animal. Despite these precautions, one false positive occurred which, combined with low task performance, lead to the exclusion of the (male) participant from the statistical analysis. After magnetic resonance (MR) scanning, a debriefing was performed with each participant, making sure that they had heard the correct animal in each trial. All trials were deemed successful.
MR Procedures
Data collection was made on a 1.5-T Philips Intera scanner (Philips Medical Systems, The Netherlands). Functional T2*-weighted images were obtained with a single-shot gradient echo planar imaging sequence used for blood oxygen level–dependent imaging. The sequence had the following parameters: echo time 50 ms, repetition time 3000 ms (33 slices acquired), flip angle 90°, field of view 22 x 22 cm, 64 x 64 matrix, and 4.4-mm slice thickness. To eliminate signals arising from progressive saturation, 5 dummy scans were performed prior to the image acquisition. The stimuli were presented through MR-compatible headphones (Silent Scan SS-3000 Audio System, Avotech, Stuart FL), and the color background and crosshair were projected on a semitransparent screen, which the participants viewed through a tilted mirror attached to the head coil. Presentation and reaction time data were handled by a PC running E-Prime 1.1 (Psychology Software Tools, Inc.,). Before the functional imaging, high-resolution T1- and T2-weighted structural images were acquired.
Data Analysis
The data were analyzed with statistical parametric mapping (SPM2) (Wellcome Department of Cognitive Neurology, London, UK) on Matlab 6.5.1 (Mathworks Inc., Sherborn, MA). All images were corrected for slice timing, realigned to the first image volume in the series, normalized to standard anatomical space defined by the Montreal Neurological Institute (MNI) atlas (SPM2), and smoothed using an 8.0-mm full width half maximum Gaussian filter kernel. The effects of interest were modeled using 3 regressors: identification, sustained perception, and sensorimotor integration (Fig. 1a). Because onset for the regressors varied in every trial depending on the participants' identification time, each regressor parameter was based on reaction time data for that specific trial. All regressors were convolved with a hemodynamic response function. Model estimations of main effects from each individual were taken into a second level random-effects model to account for interindividual variability. The statistical threshold was set to P < 0.05 (familywise error—corrected for multiple comparisons).
Experiment 2
Participants
Twelve healthy volunteers (6 women) aged 20–42 years participated (no one from Experiment 1 participated in Experiment 2). All participants were right handed by self-report, had normal or corrected to normal vision, and no hearing impairment. All gave informed consent, and the study was approved by the ethics committee at the University Hospital of Northern Sweden.
Stimulus Material
Twenty of the 24 sounds from Experiment 1 were reused for the auditory condition. For the visual condition, 20 pictures developed for an earlier experiment were used. These are fragmented pictures where an object is made out of a subset of colored fragments and is therefore difficult to identify. However, once the object is identified, there is no ambiguity in the picture and sustained perception can occur (Fig. 1b; for further detail, see Eriksson and others 2004).
Procedure
Each trial was randomly selected without replacement from 1 of 2 lists, consisting of auditory and visual trials, respectively. The procedure for auditory trials was similar as in Experiment 1 except that trial duration was interactive (i.e., no fixed stimulus onset asynchrony). The visual trials proceeded as follows: The picture was projected on the semitransparent screen and remained unchanged throughout the trial. When identification occurred, the participant pressed a button and continued looking at the identified object. As a consequence of the button press, a short beep appeared in the headphones. After 8.0–12.0 s, the beep reappeared prompting a second button press. Following the second response, the stimulus presentation continued for 12.0 s. All trials (auditory and visual) were separated by a 9.0-s presentation of a crosshair on a gray background.
MR Procedures and Data Analysis
The MR procedures for Experiment 2 were the same as in Experiment 1. Data analysis was similar to Experiment 1 except that 6 regressors were used to model the effects of interest (3 for auditory and 3 for visual trials). One participant did not show the expected activation pattern for sensorimotor integration and was therefore excluded from the group analysis. The statistical threshold was set to P < 0.01 corrected for false discovery rate (Genovese and others 2002). This more liberal threshold compared with Experiment 1 was chosen because of the power difference between the 2 experiments (14 vs. 10 degrees of freedom). The random-effects conjunction analysis was implemented in in-house software on the relevant main effects contrasts (testing the conjunction null hypothesis, Nichols and others 2005).
Data Extraction for Selected Regions
Regions of interest (Fig. 3) were defined from the random-effects analysis, where the superior temporal region was selected as the regional peak voxel for auditory identification, the parietal region as the regional peak voxel for visual identification, and the anterior cingulate and dorsolateral (DL) prefrontal regions as regional peak voxels for the conjunction analysis on identification. Data (effect size) were extracted using the Marsbar software (Brett and others 2002) from a spherical region with a radius of 6 mm.
|
|
Results |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionSupplementary MaterialReferences |
|---|
Sensorimotor Processes
In Experiment 1, the motor responses activated primary motor cortex (x, y, z = 30, –20, 64, z-score = 7.29) and color-related regions in the fusiform gyrus (26, –74, –14, z-score = 6.88; –20, –68, –10, z-score = 6.50). This result was replicated in Experiment 2 for auditory stimuli (motor cortex: 48, –14, 62, z-score = 5.77; fusiform gyrus: –16, –54, –16, z-score = 5.71). For visual stimuli, sensorimotor activity was observed in primary motor cortex (28, –26, 58, z-score = 6.10) and auditory cortex (–52, –32, 14, z-score = 5.33). These results confirm that the analytic strategy of separating effects of interest within trials was successful.
Conscious Awareness
In Experiment 1, identification of target sounds activated lateral prefrontal cortex (PFC), anterior cingulate cortex (ACC), superior temporal cortex, and cerebellum (Fig. 2 and Table 1). However, in contrast to previous research on visual awareness (Portas and others 2000; Eriksson and others 2004), no parietal activity increase was observed. To consider possible parietal activity at a lower statistical threshold, we reexamined the results at a threshold of P < 0.001 uncorrected for multiple comparisons. At this more liberal threshold, some parietal activity was seen (x, y, z = –6, –74, 40; –30, –58, 42), but frontotemporal activity continued to be the most salient response.
|
|
In Experiment 2, a similar pattern of results was observed as in Experiment 1. Identification of sounds activated lateral PFC, ACC, superior temporal cortex, and cerebellum. Again, no parietal activity increase was found (Fig. 3), and this was true even at a threshold of P < 0.001 uncorrected. In contrast, identification of visual stimuli did activate regions in the parietal cortex. In addition, increased activity was observed in inferior occipitotemporal cortex, lateral PFC, and ACC (Fig. 3 and Table 2).
|
The results of Experiment 2 showed overlapping frontal activity for visual and auditory perception. To formally characterize similarities in activation patterns associated with awareness in different sensory modalities, a conjunction analysis was performed. This analysis revealed exclusively frontal (lateral PFC and ACC) activity across modalities, mainly in the right hemisphere (Fig. 3). These results suggest that activity in the same frontal regions is related to awareness regardless of sensory modality.
Sustained Perception
For both visual and auditory stimuli, sustained perception activated extensive brain networks (Supplementary Table 1 online; Table 1 for results from Experiment 1). Critically, in both modalities, the networks included frontal and parietal regions, and a conjunction analysis revealed overlapping frontal and parietal activity during visual and auditory sustained perception (Table 3).
|
Control Analysis of Experiment 1 and 2
A difference between the auditory and visual stimuli is that in the auditory version, the stimuli change in a systematic way, whereas the visual stimuli remain unchanged throughout each trial. To control for possible confounding effects from this on the results of Experiment 1 and 2, we reanalyzed both data sets with the addition of a fourth (for Experiment 1, seventh for Experiment 2) regressor modeling the noise levels parametrically (assuming linearity among levels). This analysis revealed activity in auditory cortex related to noise level for both experiments. Importantly, the activation pattern for all previous contrasts remained unchanged, although statistical power was reduced (Supplementary Fig. 1).
|
Discussion |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionSupplementary MaterialReferences |
|---|
A consistent finding in neuroimaging research on visual awareness is that activity in both visual sensory regions and frontoparietal regions is correlated with the subjective experience of seeing a particular percept (Rees and others 2002
). Frontoparietal activity correlates with awareness of a number of different visual stimuli (words, Kjaer and others 2001; motion, Williams and others 2003; objects, Portas and others 2000) and may thus reflect general stimulus-independent cognitive processes. The aim of Experiment 1 was to test the apparent generality of frontoparietal regions in relation to perceptual awareness by using auditory stimuli in a paradigm that previously has revealed frontoparietal activity during visual conscious perception (Portas and others 2000; Eriksson and others 2004). Whereas both auditory sensory regions and frontal regions were activated for auditory awareness, only weak parietal activity was found. This result was replicated in Experiment 2 where visual and auditory awareness were directly compared. In this experiment, parietal activity correlated exclusively with visual awareness.
Parietal cortex is reciprocally connected with visual areas, and activity in secondary visual cortex during visual perceptual rivalry has been found to correlate with parietal and prefrontal activity (Lumer and Rees 1999). These previous observations converge with the present findings of frontoparietal activity during visual awareness, and they provide support for neural theories that visual awareness depends on interactions between visual cortex and PFC (Crick and Koch 1995). Our finding that frontal and temporal regions showed increased activity during auditory perceptual awareness extends this theory by suggesting that auditory awareness depends on frontotemporal interactions. In support of this interpretation, auditory object identification has been associated with a region in temporal cortex (Binder and others 2004), and anatomical connections between PFC and auditory association areas have been demonstrated (Romanski and others 1999).
Our experiments on auditory and visual awareness thus suggest that frontal regions interact with posterior regions in a modality-specific manner to create perceptual awareness in different sensory modalities. Several frontal regions were identified here in relation to perceptual awareness. Ventrolateral PFC activation may be related to making decisions about sensory stimuli (Bar and others 2001; Binder and others 2004). ACC has been associated with conflict monitoring (Dehaene and others 2003), and interactions among ACC and regions in lateral PFC have been related to the ability to decide whether a response is correct (Gehring and Knight 2000). A region in right DLPFC was also engaged. This prefrontal region has consistently been observed in previous studies of conscious perception (Rees and others 2002; Naghavi and Nyberg 2005), and it is also consistent with the model by Frith and Dolan (1996) that advocate a principal role for PFC in establishing conscious states. Frith and Dolan suggested that posterior regions define the specific content of consciousness, whereas frontal regions are needed to become aware of this content. DLPFC has also been linked to a variety of cognitive functions, such as attention (Kanwisher and Wojciulik 2000), working memory (Baddeley 2003), and cognitive control (Miller and Cohen 2001). Furthermore, DLPFC and also ACC are important regions in a recent version of global workspace theory (Dehaene and Naccache 2001). In relation to this theory, Dehaene and Naccache notice several empirical findings that connects the mentioned cognitive functions with consciousness 1) that attention may be a requirement for conscious awareness, 2) that consciousness seems to require durable and explicit information maintenance (implicating working memory), and 3) that some functions seem impossible without consciousness, for example, intentional behavior and novel combinations of operations. These latter functions are related to cognitive control because they tend to involve some form of conflict resolution. The exact relation between attention, working memory, cognitive control, and consciousness is not yet clear, but recent theories suggest that they may share underlying information-processing mechanisms (Courtney 2004; Maia and Cleeremans 2005; Naghavi and Nyberg 2005), thus explaining the common activation of PFC across functions.
Our results further indicated that once modality-specific frontoposterior interactions had defined a percept, an amodal brain system contributed to actively holding this percept in mind. That is, for both visual and auditory stimuli, a network including frontoparietal regions was activated during sustained perception. Conceivably, representation maintenance during sustained perception involves working memory processes and/or selective attentional enhancement due to the relative difficulty of the perceptual task. In previous studies, working memory and also selective attention have been found to engage a similar frontoparietal network for many different kinds of stimuli (Cabeza and Nyberg 2000), and a recent fMRI study found considerable overlap in frontal and parietal activity for visual and auditory working memory (Crottas-Herbette and others 2004). Critically, the fMRI protocol allowed us to isolate transient brain activity related to perceptual awareness from brain activity during sustained perception, which made possible the demonstration that parietal cortex was differentially involved in auditory and visual awareness and commonly involved in auditory and visual sustained perception.
In conclusion, this study demonstrates that the role of frontoparietal regions in perceptual awareness may not be as general as previously thought. Instead, common frontal regions seem to interact with specific posterior regions to produce awareness in different sensory modalities.
|
Supplementary Material |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionSupplementary MaterialReferences |
|---|
Supplementary material can be found at: http://www.cercor.oxfordjournals.org/.
|
Acknowledgments |
|---|
This research was supported by an infrastructure fMRI grant from Umeå University to LN and Roland Johansson. We thank the staff at the MR centre, University Hospital of Northern Sweden, for assisting us during MR imaging. Conflict of Interest: None declared.
|
References |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionSupplementary MaterialReferences |
|---|
Baddeley A. (2003) Working memory: looking back and looking forward. Nat Rev Neurosci 4:829–839.[CrossRef][Web of Science][Medline]
Bar M, Tootel RBH, Schacter DL, Greve DN, Fischl B, Mendola JD, Rosen BR, Dale AM. (2001) Cortical mechanisms specific to explicit visual object recognition. Neuron 29:529–535.[CrossRef][Web of Science][Medline]
Beck DM, Rees G, Frith CD, Lavie N. (2001) Neural correlates of change detection and change blindness. Nat Neurosci 4:645–650.[CrossRef][Web of Science][Medline]
Binder JR, Liebenthal E, Possing ET, Medler DA, Ward DB. (2004) Neural correlates of sensory and decision processes in auditory object identification. Nat Neurosci 7:295–301.[CrossRef][Web of Science][Medline]
Bregman AS. (1990) Auditory scene analysis(MIT Press, Cambridge, MA).
Brett M, Anton J-L, Valabregue R, Poline J-B. (2002) Region of interest analysis using an SPM toolbox. 8th International Conference on Functional Mapping of the Human Brain; June 2–6; Sendai, Japan. Available on CD-ROM in Neuroimage 16:2 Abstract.
Cabeza R and Nyberg L. (2000) Imaging cognition II: an empirical review of 275 PET and fMRI studies. J Cogn Neurosci 12:1–47.[Web of Science][Medline]
Courtney S. (2004) Attention and cognitive control as emergent properties of information representation in working memory. Cogn Affect Behav Neurosci 4:501–516.[Medline]
Crick F and Koch C. (1995) Are we aware of neural activity in primary visual cortex? Nature 375:121–123.[CrossRef][Medline]
Crick F and Koch C. (2003) A framework for consciousness. Nat Neurosci 6:119–126.[CrossRef][Web of Science][Medline]
Crottaz-Herbette S, Anagnoson RT, Menon V. (2004) Modality effects in verbal working memory: differential prefrontal and parietal responses to auditory and visual stimuli. Neuroimage 21:340–351.[CrossRef][Web of Science][Medline]
Dehaene S and Naccache L. (2001) Towards a cognitive neuroscience of consciousness: basic evidence and a workspace framework. Cognition 79:1–37.[CrossRef][Web of Science][Medline]
Dehaene S, Naccache L, Cohen L, Le Bihan D, Mangin J-F, Poline J-B, Rivière D. (2001) Cerebral mechanisms of word masking and unconscious repetition priming. Nat Neurosci 4:752–758.[CrossRef][Web of Science][Medline]
Dehaene S, Artiges E, Naccache L, Martelli C, Viard A, Schürhoff F, Recasens C, Martinot MRP, Leboyer M, Martinot J-L. (2003) Conscious and subliminal conflicts in normal subjects and patients with schizophrenia: the role of the anterior cingulate. Proc Natl Acad Sci USA 100:13722–13727.
Donaldson DI and Buckner RL. (2001) Effective paradigm design. In Jezzard P, Matthews PM, Smith SM (Eds.). Functional MRI: an introduction to methods(Oxford University Press, Oxford) pp. 177–195.
Ehrsson HH, Spence C, Passingham RE. (2004) That's my hand! Activity in premotor cortex reflects feeling of ownership of a limb. Science 305:874–877.
Eriksson J, Larsson A, Riklund-Åhlström K, Nyberg L. (2004) Visual consciousness: dissociating the neural correlates of perceptual transitions from sustained perception with fMRI. Conscious Cogn 13:61–72.[CrossRef][Web of Science][Medline]
Frith C and Dolan R. (1996) The role of the prefrontal cortex in higher cognitive functions. Cogn Brain Res 5:175–181.[CrossRef][Medline]
Gehring WJ and Knight RT. (2000) Prefrontal–cingulate interaction in action monitoring. Nat Neurosci 3:516–520.[CrossRef][Web of Science][Medline]
Genovese CR, Lazar NA, Nichols T. (2002) Thresholding of statistical maps in functional neuroimaging using the false discovery rate. Neuroimage 15:870–878.[CrossRef][Web of Science][Medline]
Grill-Spector K, Kushnir T, Hendler T, Malach R. (2000) The dynamics of object-selective activation correlate with recognition performance in humans. Nat Neurosci 3:837–843.[CrossRef][Web of Science][Medline]
Kandel ER, Schwartz JH, Jessell TM. (2000) Principles of neural science(McGraw-Hill, New York, NY) pp. xxxvi.
Kanwisher N and Wojciulik E. (2000) Visual attention: insights from brain imaging. Nat Rev Neurosci 1:91–100.[Web of Science][Medline]
Kjaer TW, Nowak M, Kjaer KW, Lou AR, Lou HC. (2001) Precuneus-prefrontal activity during awareness of visual verbal stimuli. Conscious Cogn 10:356–365.[CrossRef][Web of Science][Medline]
Kleinschmidt A, Büchel C, Zeki S, Franckowiak RSJ. (1998) Human brain activity during spontaneously reversing perception of ambiguous figures. Proc R Soc Lond Ser B Biol Sci 265:2427–2433.[Medline]
Leahey TH. (2000) A history of psychology. (Prentice Hall, New Jersey).
Lumer ED, Friston KJ, Rees G. (1998) Neural correlates of perceptual rivalry in the human brain. Science 280:1930–1934.
Lumer ED and Rees G. (1999) Covariation of activity in visual and prefrontal cortex associated with subjective visual perception. Proc Natl Acad Sci USA 96:1669–1673.
Maia TV and Cleeremans A. (2005) Consciousness: converging insights from connectionist modelling and neuroscience. Trends Cogn Sci 9:397–404.[CrossRef][Web of Science][Medline]
McIntosh RA, Rajah NM, Lobaugh NJ. (1999) Interactions of prefrontal cortex in relation to awareness in sensory learning. Science 284:1531–1533.
Miller EK and Cohen JD. (2001) An integrative theory of prefrontal cortex function. Annu Rev Neurosci 24:167–202.[CrossRef][Web of Science][Medline]
Naghavi RH and Nyberg L. (2005) Common fronto-parietal activity in attention, memory, and consciousness: shared demands on integration? Conscious Cogn 14:390–425.[CrossRef][Web of Science][Medline]
Nichols T, Brett M, Andersson J, Wagner T, Poline J-B. (2005) Valid conjunction inference with the minimum statistic. Neuroimage 25:653–660.[CrossRef][Web of Science][Medline]
Portas CM, Strange BA, Friston KJ, Dolan RJ, Frith CD. (2000) How does the brain sustain a visual percept? Proc R Soc Lond Ser B Biol Sci 267:845–850.[Medline]
Rees G, Kreiman G, Koch C. (2002) Neural correlates of consciousness in humans. Nat Rev Neurosci 3:261–270.[CrossRef][Web of Science][Medline]
Romanski LM, Tian B, Fritz J, Mishkin M, Goldman-Rakic PS, Rauschecker JP. (1999) Dual streams of auditory afferents target multiple domains in the primate prefrontal cortex. Nat Neurosci 2:1131–1136.[CrossRef][Web of Science][Medline]
Sheinberg DL and Logothetis NK. (1997) The role of temporal cortical areas in perceptual organization. Proc Natl Acad Sci USA 94:3408–3413.
Tong F, Nakayama K, Vaughan TJ, Kanwisher N. (1998) Binocular rivalry and visual awareness in human extrastriate cortex. Neuron 21:753–759.[CrossRef][Web of Science][Medline]
Van Essen DC, Dickson J, Harwell J, Hanlon D, Anderson CH, Drury HA. (2001) An integrated software system for surface-based analyses of cerebral cortex. J Am Med Inform Assoc 41:1359–1378.
Williams ZM, Elfar JC, Eskandar EN, Toth LJ, Assad JA. (2003) Parietal activity and the perceived direction of ambiguous apparent motion. Nat Neurosci 6:616–623.[CrossRef][Web of Science][Medline]
CiteULike 
Connotea 
Del.icio.us What's this?
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||