# Consciousness Studies/Neuroscience 2#Synchronisation of Neural Processes

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## Perceptual \"filling in\"

Perceptual \"filling in\" occurs when visual properties such as
textures, colours, brightness or motion are extended in the visual field
to areas where they do not have corresponding events in the world.

The filling in of the blind spot by the properties of the field in the
contralateral eye has already been discussed. The part of the visual
field represented by the blind spot is also \"filled in\" in the case of
monocular vision.

![](Constudblindill.png "Constudblindill.png")

Shut the right eye and focus on the pink cross with the left eye, if the
head is moved towards the pink cross there is a point at which the
yellow disk disappears but the white lines are still present. In this
\"filling in\" the visual field does not appear to be distorted.

Fiorani *et al.* (1992) developed a technique for probing the cortical
blind spot using vertical and horizontal bar stimuli. Matsumoto &
komatsu (2005) used this technique on macaque monkeys. In the monocular
case they found that as a bar was moved across the visual field so that
it crossed the blind spot there was a sudden change in neural activity
in the deep layers of the neurons in the blind spot area of V1. When the
bar was moved across the same part of the visual field of the
contralateral eye the neural activity in the blind spot area increased
steadily as the bar was moved. The authors found that there were neurons
in the deep layers of blind spot cortex that had elongated receptive
fields that could respond to stimuli outside the blind spot and transfer
this activation into the blind spot cortex.

Filling in of a slightly different type occurs in \"scotoma\". In
scotoma an area of the retina is damaged and unresonsive to visual
stimuli, immediately after the damage patients report an area of visual
field that is unresponsive to stimuli. After several months patients
report that the area of field represented by the scotoma contains visual
properties related to the physical world surrounding the area that would
have formed an image on the scotoma. This results in a distortion of the
visual field. (see for instance Gilbert(1993)). Direct measurements of
activity in cortical area V1 show that the neurons that represented the
area of the scotoma become sensitive to activity in the surrounding
visual field. At the cortical level the scotoma is literally \"filled
in\".

There are many stimuli that cause \"filling in\". These stimuli are
known as \"illusions\" because they produce phenomenal experience that
has no correlate in the world outside the body. In the \"neon colour
spreading illusion\" a lightly coloured circle appears where there
should be a white background. Sasaki and Watanabe (2004) used fMRI to
show that the part of the topographic map in cortical area V1
corresponding to the light coloured circle was activated.

![](Constudneon.jpg "Constudneon.jpg")

Fiorani, M., Rosa, M.G.P., Gattas, R. & Rocha-Miranda, C.E. (1992).
Dynamic surrounds of receptive fields in primate striate cortex: a
physiological basis for perceptual completion? Proc. Natl. Acad. Sci.
89, 8547-8551. <http://www.pnas.org/cgi/content/abstract/89/18/8547>

Gilbert, C.D. (1993). Circuitry, architecture and functional dynamics of
visual cortex.

Matsumoto, M & Komatsu, H. (2005). Neural responses in the macaque V1 to
bar stimuli with various lengths presented on the blind spot. J
neurophysiol. 93. 2374-2387.
<http://jn.physiology.org/cgi/content/abstract/93/5/2374>

Sasaki, Y & Watanabe, T. The primary visual cortex fills in colour.
Proc. Natl. Acad. Sci. USA 101, 18251-18256. (2004).

## Binocular Rivalry, Pattern Rivalry and Binocular Fusion

Sir Charles Wheatstone (1838) was the first scientist to systematically
investigate binocular rivalry. Binocular rivalry occurs when different
images are presented to the left and right eyes. The subject sees
successively one image, a combined image and then the other image. The
swapping of images can take a second or more. Binocular rivalry is of
interest in consciousness research because the parts of the brain that
contain the dominant image should also be those parts that are
contributing to conscious experience. Binocular rivalry involves at
least two components; the first switches from one image to a merged
image and then to the other image and the second permits the view to be
part of conscious experience.

![](Constudrival.png "Constudrival.png")

The switching of one image for another may involve selecting one of the
images as the percept or selecting one of the eyes. Blake *et al.*
(1979) performed an experiment in which subjects could change the image
at a given eye by pressing a button. When a particular image became
dominant they pressed a button to change the image at the eye receiving
the dominant image for the non-dominant image. They found that the
subjects immediately experienced the second image as the dominant image.
This suggests that binocular rivalry is selecting between eyes rather
than images. Lehky in 1988 proposed that the switching may be occurring
as a result of feedback between visual cortical area V1 and the Lateral
Geniculate Nucleus (a thalamic relay - see Carandini *et al.* 2002) and
Blake in 1989 also proposed that the switching occurred at the level of
area V1. (Visual cortical area V1 receives visual input direct from the
LGN.)

Tong (2001) has argued that, in humans, the switching of images in
binocular rivalry may occur at the earliest levels in the visual cortex.
In particular, Tong and Engel (2001) used an elegant technique measuring
the activity in the visual cortex that represents the blind spot of the
eye to show that almost complete switching to the dominant image occurs
at the level of visual cortical area V1. In support of this idea of
switching at the level of V1 or even before the cortex, Kreimann *et
al.* (2001, 2002) used direct electrode recordings in human cortex and
found that the activity of most neurons changed with the percept. Other
experiments have not shown a single locus in the brain where the
suppressed sensory information gets switched out (Blake & Logothetis
2002, Leopold & Logothetis 1996, Gail et al., 2004).

Functional MRI has also shown cortical activity outside of sensory
visual cortex related to both images in binocular rivalry. Lumer *et
al.* (1998) found that only the fronto-parietal areas of cortex switched
with the percept, Fang & He (2005) found that activity relating to both
suppressed and unsuppressed images were present in the dorsal stream of
the visual system. Wunderlich *et al.* (2005) and Haynes *et al.* (2005)
have both found suppression at the level of the lateral geniculate
nucleus using fMRI in humans.

Pasley *et al.* (2004) have shown that, even during suppression, fearful
faces can produce activity in the amygdala (see Pessoa (2005) for a
review).

Rivalry alternations seem to be the result of widespread activity
changes that cover large parts of the brain, including but not
necessarily originating at the earliest sensory stages of visual
processing. Most investigators have found that, once switching has
occurred, there are areas of the brain that contain activity that is
solely related to the percept but this varies from most of the cortex to
largely more frontal regions depending upon the study. The most likely
explanation for binocular rivalry is that the switching occurs at the
level of the LGN as a result of feedback from the cortex.

Pattern Rivalry is also of interest in consciousness research for the
same reasons as binocular rivalry. In pattern rivalry a figure may have
two or more forms that replace each other. Typical examples of such
figures are the Necker cube and Rubin\'s face-vase. The similarity of
the time course of the switching between percepts in binocular rivalry
and pattern rivalry has led many authors to suggest that these involve
the same mechanism. Logothetis *et al.* (1996) used novel dichoptic
stimuli (different images to each eyes) to produce a form of rivalry
that seems to involve switching at levels in the cerebral cortex that
are more distal to the sensory stimulus than V1. Leopold and Logothetis
(1999), on the basis of their work with monkeys, state that \"..many
neurons throughout the visual system, both monocular and binocular,
continue to respond to a stimulus even when it is perceptually
suppressed.\". Kleinschmidt *et al.* (1998) investigated pattern rivalry
with MRI and found activity in higher order visual areas during change
of dominant pattern. Pettigrew (2001) also describes effects on rivalry
due to thought and mood that may require involvement of large areas of
cortex in the switching operation and stresses the way that V1
represents different visual fields in different hemispheres of the brain
so that inter-hemispheric switching must also be considered.

It seems likely that the change of dominant pattern or percept is
associated with higher level cortical activity but once the dominant
percept is established many of the visually responsive neurons in the
cortex are switched over to the new percept. This might account for the
similarities in timing of binocular and pattern rivalry and the
disparate results found by the various groups of authors. In the words
of Kleinschmidt *et al.* (1998):

\"The transient activity fluctuations we found suggest that perceptual
metastability elicited by ambiguous stimuli is associated with rapid
redistributions of neural activity between separate specialized cortical
and subcortical structures.\"

Which permits both the idea of selecting particular eyes or percepts,
perhaps by feedback that switches a thalamic relay on the basis of
cortical processing of patterns. Once the cortex has switched the
thalamic relay most of the neurons in V1 would become exposed to the
dominant percept but there would still be a few neurons in the cortical
visual system receiving data from the non dominant image.

The investigations of binocular and pattern rivalry provide evidence
that conscious visual experience is probably distal to V1 (i.e.: cortex
or thalamus).

Perceptual rivalry may be part of complex decision making rather than
being simply a switch to blank out unwelcome input. It is clear from the
Rubin face-vase that pattern rivalry is linked to recognition and would
involve a complex delineation of forms within cortical processing. This
would suggest that many areas of cortex should be involved before a
particular percept is made dominant. Pettigrew (2001) argues that
rivalry is the result of a complex phenomenon rather than being simply a
switching event. Pettigrew\'s discovery that laughter abolishes rivalry
also points to a complex cortical system for switching percepts.
Pettigrew proposes that complex cortical processes control rivalry and
that the actual switching of percepts is performed sub-cortically in the
Ventral Tegmental Area. He concludes his review of the problem by noting
that \"Rivalry may thus reflect fundamental aspects of perceptual
decision making..\" Pettigrew (2001).

Another effect, known as \"binocular fusion\", provides further
compelling evidence for the non-conscious nature of the cerebral cortex.
In binocular fusion images from both eyes are fused together to create a
single image in experience. Moutoussis and Zeki (2002) used a form of
binocular fusion in which images of faces were flashed at 100ms
intervals to both eyes simultaneously. When both eyes received images of
the same colour the subject could see the faces but when one eye
received a green image on a red background and the other a red image on
a green background the subjects reported seeing a uniform yellow field
that contained no faces.

fMRI scans of the subject\'s brains showed that when both eyes were
exposed to images of the same colour the part of the brain that deals
with faces was active and when each eye received images of different
colours the same areas of brain showed activity. In other words the
cortex contained strong activity related to faces whether or not faces
were experienced. Moutoussis and Zeki found a similar effect when they
used images of houses instead of images of faces. The authors concluded
that: \"The present study further suggests that there are no separate
processing and perceptual areas but rather that the same cortical
regions are involved in both the processing and, when certain levels of
activation are reached and probably in combination with the activation
of other areas as well, the generation of a conscious visual percept\".

This conclusion does not seem to be supported by the data. There is no
evidence that any area of cortex contains the percept itself. The
experiment shows that the cortex contains data relating to both red and
green faces which suggests that the cortex is not the site of the
conscious percept. The percept is most likely distal to the cortex
perhaps in the thalamus or some other area that receives cortical
sensory output.

It is interesting that Fries *et al.* (1997) found that neurons that
were activated by the dominant image in binocular rivalry fired
synchronously whereas those that were activated by the non-dominant
image did not. Thalamocorticothalamic oscillations are the most likely
source for synchronising neurons over whole areas of cortex, suggesting
that the conscious percept is located in the thalamus rather than the
cortex.

## Synchronisation of Neural Processes

Our experience seems to contain entities with their attributes attached
to them at the correct places in space and time. When a dog barks we see
its jaws open at the same time as the bark and both jaws and bark are at
the same location. We take this for granted but the brain must be
engaging in some complex processing to achieve this synchronised and
appropriately positioned set of objects and events. The illustration
below shows the two basic processes that might be used to synchronise
events between the different specialised processors in the cerebral
cortex and brain in general.

![](Constudsynch.gif "Constudsynch.gif")

In the first option a complete model of sensation, dream etc. may be
created and then allowed to become part of conscious experience. In the
second model events are released into experience as fast as possible but
are synchronous when recalled, having been synchronised in a storage
buffer. There is a third option in which there is no synchronisation of
events so that the output from different processors would occur at
different times.

The \'experience buffer\' would be a volume of brain in which a
succession of events could be recorded. The buffer might either be
updated in steps, the previous content being discarded, or continuously
updated with the oldest content being lost continuously.

In the first option events from different processes would always appear
to be simultaneous unless the experience buffer were updated as a series
of steps in which case any changes at around the moment of updating
might appear in successive buffers. For instance, if change of position
were processed before change in colour a circle on a screen that changed
from green to red at the start of a motion might seem to be briefly
green during the motion and then turn red.

In the second model events from different processors might appear
asynchronous at the moment of experience but synchronous when recalled.

Colour vision and motion vision are processed in different parts of the
visual cortex and in distinct parts of visual cortical areas V1 and V2.
They are different processes and hence ideal for studying the
synchronisation of cortical activity. Moutoussis and Zeki (1997)
presented subjects with moving coloured squares on a computer screen
that changed from red to green or vice versa as they changed direction
of movement. It was found that subjects seemed to perceive changes in
colour some 70-80 msecs before they perceived a change in the direction
of motion of the squares. Further work by Arnold *et al.* (2001) and
Arnold and Clifford (2001) have confirmed that colour changes seem to be
perceived before motion. Arnold and Clifford (2001) also found a
quantitative relationship between the colour/motion asynchrony and the
direction of change of motion, complete reversals of direction giving
rise to the greatest asynchrony between the detection of colour and
motion changes.

Moutoussis and Zeki (1997) conclude by stating that the asynchrony of
neural processes shows that \"..the perception of each attribute is
solely the result of the activity in the specialised system involved in
its processing..\". It seems more likely that the experiments simply
show that slow neural processes are not synchronised before they become
percepts (the third option above). The experiments are excellent
evidence for the concept of the cortex as a set of specialised
processors that deliver their output asynchronously to some other place
where the output becomes a percept.

These experiments on colour and motion suggest that there is no
synchronisation between the processes that deal with these two aspects
of vision. Another set of experiments by Clifford *et al.* (2003)
supports this idea of processing being asynchronous. They asked subjects
to perform a variety of judgements of when visual events occurred and
found that the degree of synchrony of one visual event with another
depends on the type of judgement. Different judgements probably use
processors in different areas of cortex and the output from these
arrives asynchronously at the part of the brain that supports the
percept.

When the percept is formed there must be feedback to the cortical
processes that create its content. Otherwise it would not be possible to
report about the percept and the cortex would be unable to direct
processing to the percept in preference to other, non-conscious cortical
data.

Although slow processes (20 milliseconds to 1 second) do not seem to be
synchronised there is some evidence for very rapid synchronisation.
Andrews *et al.* (1996) revisited a problem raised by the famous
physiologist Charles Sherrington. Sherrington considered the phenomenon
of \'flicker fusion\' in which a flickering light appears to be a
continuous steady light if it flashes on and off at frequencies of about
45 Hz or higher. He reasoned that if the images from both eyes are
brought together to form a single image then the frequency at which a
flickering light appears to be steady should depend on whether one or
two eyes are used. Flicker fusion should occur if each eye receives
alternate flashes at only half the normal flicker fusion frequency. The
flicker should disappear if the left eye receives flashes at 23 pulses
per second and the right eye receives alternate flashes at 23 pulses per
second. When Sherrington performed the experiment he found that this was
not the case, using approximate figures, each eye required 46 pulses per
second for fusion to occur. Sherrington proposed that the flicker fusion
in alternate binocular presentation was occurring \"psychically\",
outside of normal physiological processes.

Andrews *et al.* duplicated Sherrington\'s result but investigated it
further. They found that when lights were flashed in each eye
alternately at low frequences (2 Hz) the experience was the same as a
light being flashed in both eyes at this rate. At frequencies of four Hz
and higher the subjects began to report that the lights being flashed
alternately in both eyes seemed to flicker at the same rate as lights
being flashed in both eyes at half the frequency. It seemed as if a
flash in one eye followed by a flash in the other eye was being
perceived as a single flash or \"conflated\" as the authors put it. The
authors explained this effect by suggesting that the brain activity
corresponding to the flashes was sampled for a short period and any
number of flashes occurring during this period became perceived as a
single flash. The maximum rate of sampling would be about 45 Hz. This
idea is similar to option (1) above, where the buffer is filled and
emptied 40 - 50 times a second.

An experience buffer that is refreshed at 40-50 times a second might
also explain the results obtained with colour and motion asynchrony
because synchronisation between processes may well happen too quickly to
affect processes that occur at very slow rates. Singer and Gray (1995),
Singer (2001) have proposed that synchronisation between neurones at
about 45 Hz is the discriminator between those neurones with activity
that contributes to conscious experience and activity in other neurones.
A rapid refresh rate in a synchronising buffer agrees with the results
found by Fries *et al.* (1997) in which visual cortical neurones that
represent a percept underwent synchronous oscillations in the gamma
frequency range (39--63 Hz). Tononi *et al.* (1998) have also found
synchronisation of neural activity in neurones that represent the
percept.

The gamma frequency oscillations are intrinsic to the cortex but are
triggered by the thalamus and are part of the \'arousal system\'.
Readers should be wary of the term \'arousal system\' because it evokes
the idea of something waking up a conscious cortex. The cortex can be
fully active during sleep and even during pathological unconsciousness
such as persistent vegetative state so it is possible that the arousal
centres themselves or nearby structures actually host phenomenal
consciousness.

## EEG and synchronisation

If electrodes are placed on the scalp varying electrical potentials of a
few tens of microvolts can be recorded between the electrodes.
Recordings of potentials from electrodes on the scalp are known as
electroencephalograms (EEGs).

The potentials recorded in the EEG are due to postsynaptic potentials in
nerve cells. The EEG is insensitive to the activity of single cells and
occurs as a result of relatively slow, **synchronised**, changes in
large areas of cells. The differences in potential between two scalp
electrodes are largely due to depolarisation and hyperpolarisation of
the dendritic trees of cortical pyramidal cells. The folding of the
cortex (gyri) is problematical for recording and interpreting EEGs
because opposing layers of cortex can cancel any net potentials.

The EEG shows rhythmic activity. This is conventionally divided into the
following frequency bands:

Delta waves 0--4 Hz

Theta waves 4--8 Hz

Alpha waves 8--12 Hz

Beta waves \>10 Hz

Gamma waves (also called fast beta) 25--100 Hz

EEGs also contain short bursts of activity called spindles and very fast
oscillations (VFOs). Spindles last for 1--2 seconds and contain rhythmic
activity at 7--14 Hz. They are associated with the onset of sleep. The
VFOs consist of short bursts at frequencies of over 80 Hz.

When the eyes are closed the amplitude of activity from most pairs of
electrodes is increased compared with when the eyes are open. When
subjects are awake the EEG consists mainly of alpha and beta activity
with considerable low amplitude gamma when the eyes are open. In stage 1
sleep the EEG consists of theta waves, in stage 2 sleep of varied
activity and spindles, in stage 4 sleep of delta and during REM sleep of
beta and theta activity. In epileptic seizures there tends to be high
amplitude activity with pronounced synchronisation between many pairs of
electrodes.

The rhythmic electrical activity is due to cortical feedback loops,
cortico-cortical synchronisation, thalamic pacemakers and
thalamo-cortical synchronisation. VFOs have been attributed to the
activity of electrical connections between cells (dendro-dendritic gap
junctions) (Traub (2003)).

The gamma activity, centred on a frequency of 40 Hz appears to be
related to activity in cortical interneurons that form electrical
connections between their dendrites (Tamas *et al.* 2000). These
oscillations can be triggered by high frequency stimulation of the
posterior intralaminar nuclei of the thalamus (Barth and MacDonald 1996,
Sukov and Barth 2001) and as a result of activation of the reticular
system (Munk *et al.* 1996). This suggests that stimulation of cortex by
thalamic sensory relays triggers gamma band activity in the cortex. A
shift from gamma to beta waves can occur in human event related
potentials after about 0.2 secs (Pantev 1995, Traub *et al.* 1999).

The alpha activity is related to thalamic pacemakers, perhaps as a
result of intrinsic oscillatory activity in thalamic sensory relays (see
Roy & Prichep 2005 for a brief review). Theta activity, which occurs
during some cognitive tasks and mental arithmetic involves a loop from
the cortex to the non-specific thalamic nuclei. Delta activity seems to
be endogenous to cortex when input is suppressed during sleep. Beta
activity is due to cortico-cortical interactions, often after a brief
period of gamma activation. It should be noted that gamma and beta
activity can be expressed as impulses in cortico-thalamic pathways and
that when cortical and thalamic activity is correlated there is a
conscious state. In other words gamma or beta waves in the cortex are
not correlates of consciousness on their own - see for instance Laureys
*et al.* (2002).

## Event related potentials

After a sudden event there are a characteristic set of changes in EEG
activity known as **event related potentials** or ERPs. The time course
of the ERP is shown in the diagram below.

![](Constudevent.png "Constudevent.png")

ERPs occur in response to novel stimuli and are also produced by brief
transcranial magnetic stimulation (TMS)(Iramina *et al.* 2002). The slow
component is known as the P3 or P300 phase of the ERP. It is due to
activation of areas of the brain that are relatively remote from the
primary sensory areas of brain.

Nieuwenhuis *et al.* (2005) have reviewed the origin of the P300 ERP:
\"To summarize, convergent evidence suggests that P3-like activity can
be recorded in several, widely separated brain areas. These include some
medial temporal and subcortical structures (e.g., the hippocampal
formation, amygdala, and thalamus), but these structures are unlikely to
contribute directly to the scalp-recorded P3.\". According to
Nieuwenhuis *et al.* (2005) the recorded P300 may be due to
temporo-parietal and prefrontal cortical activity. Linden (2005) has
also concluded that widespread, but specific, cortical activation is
correlated with the recorded P300 ERP.

The generator of the P300 is still obscure. Nieuwenhuis *et al.* (2005)
consider that the Locus coeruleus, a nucleus in the pons that regulates
task related attention and part of the sleep-wake cycle, may be
responsible. In line with this, Mashour *et al.* (2005) have discovered
that TMS induced P300 activity is reduced in unconscious states.

Whether the P300 is related to Libet\'s 0.5 second delay is still
obscure but the discovery that the P300 occurs in association with
subliminal stimuli (stimuli that do not enter awareness)(Bernat *et al.*
2001) suggests that it is associated with non-conscious cortical
processing. Williams *et al.* (2004), in an investigation of subliminal
and supraliminal fear perception, found that \"conscious fear perception
was distinguished by a more prominent N4, peaking around 400 msec\"; the
N4 component follows the P300 component in the succession of phases of
the ERP. Williams *et al.* considered that the earlier phases in the ERP
are probably related to non-conscious processing. In contrast Vogel *et
al.* (1998) found that suppression of the P300 was associated with
suppression of awareness.

## The integration delay

Psychological experiments often involve binary decisions where subjects
give one of two outputs in response to stimuli. It is found that if the
stimuli are made increasingly noisy or complex the response time tends
to increase. Psychophyicists have developed various mathematical models
to explain the increased response times due to noise such as the
Integrator and Accumulator models (cf: Luce(1986)). These models have
been fairly successful when explaining experiments such as judging the
net direction of movement of sets of dots on a screen when the dots are
given semi-random paths and different brightness etc. In these
circumstances it can take up to 2 seconds for an accurate decision.

There are many tasks however where the accuracy of decision making does
not improve after about 300 milliseconds. The accuracy of the
performance of rats when choosing between two alternatives when reacting
to odours peaks at about 300 ms (Uchida and Mainen(2003), Abraham *et
al.* (2004)). The accuracy of humans when performing vernier acuity
tasks, line detection, contrast sensitivity, motion velocity
discrimination and stereoscopic depth discrimination seems to peak at
300ms (Uchida *et al.* 2006).

Uchida, Kepecs and Mainen (2006) suggest that \"rapid and short
integration time is a sensible strategy for rapid processing of
low-level sensory information in order to form more complex sensory
images, both in vision and olfaction.\" Whether these authors regard
these derived sensory images as the content of consciousness is not
mentioned. The authors propose that the 300ms optimal integration time
may be partly due to the mechanics of sniffing (a sniff takes about
125-200ms) and the nature of optical fixation (inter-saccade intervals
are typically 200-400 ms ). The authors note that the animal or human
could, in principle, choose to integrate over longer intervals but if it
is moving this may not lead to information that is current for changed
circumstances.

An optimal processing time of about 300 ms would be consistent with the
delays observed before conscious awareness occurs in response to a
stimulus - an interval required to form \"more complex sensory images\".

## Global Workspace Theory

Global Workspace Theory is the idea that somewhere in the brain there is
a facility that integrates the processes that occur in the various
separate areas of the brain. The theory was first proposed by Descartes
as the *sensus communis*, the common sense, but the modern form of the
theory dispenses with the idea of a point soul looking at the brain. In
modern Global Workspace theory it is proposed that an area of brain
receives input from most of the cerebral cortex and broadcasts its
outputs to all of the unconscious modular information processors in the
brain.

Modern Global Workspace Theory has been championed by Baars (1983,
1988).

There is increasing evidence for a Global Workspace or Global Workspaces
in the brain. Much of this evidence comes from fMRI, single unit and
magnetoencephalography studies in which it is shown that non-conscious
or subliminal processing mainly occupies primary, sensory cortex whereas
conscious processing occupies large areas of cerebral cortex.

In binocular rivalry the stimulus that is consciously perceived is
responsible for relatively intense activation of large areas of brain
whereas the non-conscious stimulus is often suppressed (see above and
Sheinberg & Logothetis (1997), Tononi *et al.* (1998)). The suppression
is likely to occur in the Lateral Geniculate Nuclei which suggests a
role for the Thalamic Reticular Nuclei, which modulate LGN activity, in
the control of the percept.

### Masking and visual awareness

Word masking has also been used to investigate the idea of a Global
Workspace. When a word is presented on its own for a few tens of
milliseconds it remains readable but if it is immediately succeeded by,
or accompanied by, another word it becomes indistinct or invisible. This
effect is known as \"word masking\". Vogel *et al.* (1998) have
investigated a version of word masking known as the \"attentional
blink\". They found that when stimuli became invisible the P3 component
of the Event Related Potential, which peaks at around 300-500 millisecs
after a stimulus, was completely suppressed. The P3 component of the ERP
has been related to the lodging of data in working memory and also to
gamma band activity in the EEG. This strongly suggests the involvement
of a cortico-thalamic loop in the \"attentional blink\". The delay of
0.3 to 0.5 secs is typical of the time required for conscious awareness
(see above).

Word masking in conjunction with fMRI and Event Related Potential (ERP)
recordings has been used by Dehaene *et al.* (2001) to expose control by
a central mechanism. It was found that masked words activate mainly the
visual cortex and ventral stream (inferior temporal lobe) whereas
visible words also activated distant parietal, prefrontal and cingulate
sites.

Dehaene *et al.* (2003) and found that the dynamics of the loss of
visibility of words in an attentional blink experiment could be modelled
by a simulated cortico-thalamic loop. In their simulation a distributed
cortical process determined which events would receive attention and the
system used the thalamic gating systems to exclude those that did not
receive attention.

Tse *et al.* (2005) have used purely visual stimuli in masking
experiments and concluded that, in the case of purely visual stimuli,
the neural correlates of awareness were limited to the occipital cortex:

\"We suggest that there are both lower and upper bounds within the
visual hierarchy for the processing of visual masking and the
maintenance of visual awareness of simple unattended targets; the lower
bound is at least as high as the border between V2 and V3, and the upper
bound is within the occipital lobe, possibly somewhere downstream of
V4.\"

This discovery would mean that activation of large areas of cortex are
unnecessary for awareness.

Melloni *et al.* (2007) compared compared the electrophysiological
responses related to the processing of visible and invisible words in a
delayed matching to sample task. Both perceived and nonperceived words
caused a similar increase of local (gamma) oscillations in the EEG, but
only perceived words induced a transient long-distance synchronization
of gamma oscillations across widely separated regions of the brain.
After this transient period of temporal coordination, the electrographic
signatures of conscious and unconscious processes continue to diverge.
Only words reported as perceivedinduced (1) enhanced theta oscillations
over frontal regions during the maintenance interval, (2) an increase of
the P300 component of the event-related potential, and (3) an increase
in power and phase synchrony of gamma oscillationsbefore the anticipated
presentation of the test word. We propose that the critical process
mediating the access to conscious perception is the earlytransient
global increase of phase synchrony of oscillatory activity in the
gammafrequency.

Melloni L, Molina C, Pena M, Torres D, Singer W, Rodriguez E. (2007).
Synchronization of neural activity across cortical areas correlates
withconscious perception.J Neurosci. 2007 Mar 14;27(11):2858-65.

### Attention and the global workspace

Baars (2002) in his review of evidence for the Global Workspace Theory
quotes many other experiments that show activation of larger areas of
cortex in response to conscious stimuli compared with unconscious or
subliminal stimuli.The effect is also seen in change blindness, learning
and attention. Newman and Baars (1993) consider that the \"workspace\"
is fairly global in the brain:

\"This Neural Global Workspace (NGW) model views conscious processes in
terms of a globally integrative brain system. The neural circuitry
contributing to this system is not only widely distributed across the
neocortex, but includes key corticothalamic and midbrain circuits as
well. These cortico-subcortical circuits are hypothesized to be critical
to understanding the mechanisms of attentional control that provide an
essential basis for the conscious processing of information\".

However they focus particularly on the role of the thalamic Reticular
Nucleus and cortico-thalamic connectivity in the control of attention.

Other ideas for the location of the Global Workspace are the idea of
Singer et al. that gamma synchrony controls access to the content of
consciousness and Llinas et al. (1998) that the thalamus is the hub
through which communication occurs between areas of cortex.

One of the problems with Global Workspace theory is that it suggests
that attention, working memory, cognitive control and consciousness may
all be in the same area of the brain. It is likely that the mechanisms
of attention, working memory, and cognitive control may involve several,
interlinked systems perhaps co-opting the basal ganglia in the process.
In view of this Maia and Cleeremans (2005) propose that \".. attention,
working memory, cognitive control and consciousness are not distinct
functions implemented by separate brain systems. Attempting to find
separate neural correlates for each may therefore be the wrong approach.
Instead, we suggest that they should be understood in terms of the
dynamics of global competition, with biasing from PFC (prefrontal
cortex).\". The inclusion by Maia and Cleeremans of consciousness with
distributed attention, working memory and cognitive control is
reminiscent of Zeki & Bartel\'s idea of microconsciousness.

It should be noted that, in common with Libet\'s data, the percept seems
to be available to phenomenal consciousness some 0.3 to 0.5 secs after a
stimulus; this suggests that whatever determines the content of
phenomenal consciousness operates before events become part of
phenomenal consciousness. This relegates phenomenal consciousness from
being a controller of attention to being the recipient of content that
is the subject of attention. This finding is consistent with the
philosophical problem of the **apparently** epiphenomenal nature of
phenomenal consciousness.

Given the data on the timing of conscious awareness it seems that there
may be two \"workspaces\", an active workspace that models the world,
discarding and suppressing data during rivalry, and a passive workspace
that receives the final, edited product. The active workspace would
correlate with the cortical systems stressed by Dehaene *et al.* and
Maia and Cleermans although, given the results of Tse et al., the
workspace would be limited to small zones of cortex. The loading of the
passive workspace with the output of the active workspace would
correlate with thalamo-cortical activity during component P3 of the ERP
in which data is transferred from the cortex to the thalamus. This
workspace might constitute the source for reports of the content of
phenomenal consciousness.

Llinas *et al.* (1998) have proposed two parallel cortico-thalamic
attentional systems, one of which is related to the thalamic specific
nuclei and the other to the thalamic non-specific nuclei, especially the
ILN. The non-specific system would be related to consciousness itself.

## The \"cognitive map\" and the neural basis of perceptual space

Our bodies appear to be mobile within a constant space. We walk around a
room; the room does not rotate around us. The constancy of the location
of things gives us the feeling that we are directly viewing a constant
world. But how does the brain provide a constant world rather than a
world that rotates with the movement of the sense organs? Why is our
view of the world when we move our eyes so different from the disturbing
flow of images that occur when a video camera is waved around? Do our
brains contain a constant \"cognitive map\" (O\'Keefe and Nadel 1978) of
our surroundings?

Mittelstaedt & Mittelstaedt (1980, 1982) discovered that female gerbils
were able to recover their pups in darkened surroundings by searching in
a semi random fashion on the outbound journey and then proceeding
directly back to the nest on the inbound journey. The direct journey
back to the nest seemed to be due to an integration of the various
directions taken on the outward journey (**path integration**). If the
equipment being explored by the mother gerbil was rotated very slowly
the mother would make an error equivalent to the amount of rotation.
More rapid rotations that activated the vestibular system of the rat
(acceleration measurement) did not cause errors in navigation. This
demonstration that rodents could navigate accurately on the basis of
**idiothetic** cues (cues that are due to internal senses) led to
research on the neural basis of the navigation.

As early as 1971 O\'Keefe and Dostrovsky had discovered that there are
particular cells in the hippocampus that fire according to the position
of an animal in the environment. This has been complimented by research
that showed that changes in visual cues within the environment caused
changes in the firing rate of place cells in hippocampal area CA3 (.

![](Gray717.png "Gray717.png")

![](HippocampalRegions.jpg "HippocampalRegions.jpg")

!Entorhinal cortex approximately maps to areas 28 and
34{width="500"}

F. P. Battaglia and A. Treves. 1998 Attractor neural networks storing
multiple space representations: A model for hippocampal place fields.
PHYSICAL REVIEW E DECEMBER 1998 VOLUME 58, NUMBER 6
<http://www.sissa.it/~ale/Bat+98b.pdf>

Leutgeb, S., Leutgeb, J.K., Moser, M-B, and Moser, E.I. 2005. Place
cells, spatial maps and the population code for memory. Current Opinion
in Neurobiology 2005, 15:738--746.
<http://instruct1.cit.cornell.edu/courses/bionb720nejc/reprints/LeutgebEtAl2005.pdf>

Mittelstaedt, H. & Mittelstaedt, M-L. 1982. Avian Navigation. (ed. Papi,
F. & Wallraff, H.) 290-297. Springer, Berlin.

Mittelstaedt, M-L & Glasauer, S. 1991. Idiothetic Navigation in Gerbils
and Humans. Zool. Jb. Physiol. 95 (1991), 427-435
<http://web.archive.org/web/20110125132449/http://www.nefo.med.uni-muenchen.de/~sglasauer/MittelstaedtGlasauer1991.pdf>

O\'Keefe, J. & Dostrovsky, J. (1971). The hippocampus as a spatial map:
preliminary evidence from unit activity in the freely moving rat. Brain
Res. 34, 171-175.

O\'Keefe, J. & Nadel, L. (1978). The Hippocampus as a cognitive map.
(Oxford)

## Bibliography

Defining the States of Consciousness. Tassi, P., Muzet, A. (2001)
Neuroscience and Behavioural Reviews 25(2001) 175-191.

Neuroanatomy: \"Digital Slice of Life\" by Stensaas and Millhouse

<http://medlib.med.utah.edu/kw/sol/sss/subj2.html>

See also: <http://medlib.med.utah.edu/kw/sol/sss/index.html>

EEG\'s: Coles, M.G.H., Rugg, M.D. Event Related Brain Potentials: An
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<http://whalen.psych.udel.edu/667/1.What_is_ERP/ColesRugg1995chpt1.pdf>

Visual System: Tong, F. (2002). Primary Visual Cortex and Visual
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<http://www.psy.vanderbilt.edu/tonglab/publications/Tong_NRN2003.pdf>

Professor Bogen\'s Consciousness Page

<http://www.its.caltech.edu/~jbogen/text/toccons.htm>

Demonstrations of Auditory Illusions and Tricks. Yoshitaka Nakajima

<http://www.kyushu-id.ac.jp/~ynhome/ENG/Demo/illusions2nd.html>

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