Consciousness (fMRI) have come about that we can attempt

Consciousness
is a very difficult thing to define because we still do not fully understand
where, how or why it works. Many past theories that have attempted to explain
consciousness have come across complex problems trying to explain what happens
in the brain during a conscious experience. Chalmers (1995) named one of
these the “hard problem” which states that if the brain is an object, how can
it have consciousness of itself and the rest of the world? How can a physical
process of neural activity in the brain give rise to a psychological phenomenon
such as conscious experience? Chalmers says that all theories that try and
explain consciousness by determining which physical systems are responsible for
it will run into this problem.

Theorists, philosophers, physicists,
psychologists and many others have attempted to think their way through these
problems, but it has not been until the widespread availability machines such
as functional MRIs (fMRI) have come about that we can attempt to solve these
issues in a real way. Functional MRIs measure blood-oxygen-level dependent
(BOLD) signals in different brain regions, which gives us an indication of the
spontaneous activity taking place between the areas of the brain of interest
(what we call functional connectivity; Cavanna, Vilas, Palmucci, & Tagliazucchi, 2017). When we combine
these signals with mathematical algorithms we can start to get an idea of
energy levels being used during various tasks, both in conscious participants
and in participants with disorders of consciousness (DOC; Shulman, 2013b). In this way fMRI
can be a useful diagnostic tool for determining what stage of consciousness a
patient is in. While fMRI machines are very expensive to run and can create
confusing or messy pictures due to noise and other artifacts, they provide
excellent spatial information about where in the brain a participant’s
cognitive activity is being concentrated to accomplish a specific task (Shulman, 2013b; Vanhaudenhuyse et al., 2010).

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There are several modern theories of
consciousness being used today to study consciousness: global workspace theory
proposed by Baars, Dehaene and Changeux as well as integrated information
theory proposed by Tononi and Edelman are perhaps the two most well known.
Neuroimaging tools, such as fMRI machines, have become an integral part at
attempting to provide evidence for these theories; unfortunately, there is
still a long way to go before any full explanation is found for how
consciousness works in our brains. These theories provide a framework from
which theories can begin to explore the neural underpinnings of consciousness
in the brain.

            Due to the complexity of
phenomenology (the study of consciousness), there are many overlapping and
conflicting theories and definitions of what exactly consciousness is. Cavanna
and colleagues have defined consciousness as “information processing in the
brain that is accompanied by subjective and reportable experience…” which is a
simplified way of looking at consciousness (Cavanna et al., 2017).  Dan Lloyd (2002) expands on this definition
saying that phenomenology includes three core aspects: intentionality,
non-sensory vs. sensory and that of temporality. The first is concerned with
how conscious experience presents itself; we want to know how a state is
presenting itself to a person, and how that person is experiencing it. The
second says that at any given moment we are conscious of many things that we
are not necessarily aware of. Lloyd’s final point says that consciousness is
always time sensitive because all of our experiences occur at a particular
moment in time and no two experiences are the same (Lloyd, 2002).

These aspects are both simplified and
expanded upon by Tononi and Edelman, the creators of the integrated information
theory, which suggests that consciousness is determined by its causal
properties, making it a part of all physical systems. This theory, first
introduced in 2004 has been expanded upon twice since then and was published in
its most recent form in 2014. The principle idea is that information is
perceived by the senses, and enters the brain in the form of “integrated
information” which is the smallest, functional piece of information, where it
is combined with other bits of integrated information (all known as ? or phi)
to create what we know as conscious experience (Tononi, 2008). Labelling these
units of information as phi allows for the quantification the information
coming in, from which mathematical formalization of the theory is developed and
can be applied to research using machines such as fMRI. This theory also
elegantly avoids Chalmers’ hard problem since consciousness is accepted as a
physical fact. IIT says if we can understand a conscious experience through
scientific systems, then this system must exist within the constrains of
consciousness (Biernacki, 2016; G. Tononi & Koch, 2015).  

Included in IIT Tononi has postulated five
axioms of consciousness: first, that it exists, secondly, that it is
compositional, meaning ordered and layered, it builds on itself. Third, it
includes information (also understood as differentiation), at each given moment
there are an infinite possibility of experiences and the experience that we are
aware of provides us with unique information about that state and moment (Cavanna et al., 2017; Giulio Tononi, Edelman, Tononi,
& Edelman, 2017). Fourthly, it is
integrated, it is the result of a unification of all parts of awareness and finally,
and it is exclusive-we can only consciously experience one state at a time (Biernacki, 2016; G. Tononi & Koch, 2015). The two axioms of
differentiation and integration in particular work in perfect opposition to
each other in the brain since differentiation will be at its maximum efficiency
when each unit of information entering the brain acts independently, when it is
optimally differentiated but minimally integrated; similarly, an extremely high
level of integration creates fewer and fewer possibilities and thus less
differentiation (Cavanna et al., 2017). The balance in
competition between these two aspects results in the widespread awareness of
consciousness that we experience.

From these building blocks Tononi and
colleagues hope to be able to pinpoint mathematically what systems are
responsible for the integration of phi and the creation of conscious
experience. A few assumptions about the physical aspects of IIT have been made
based on recent neuroimaging and electrophysiological techniques; the systems
that control these core concepts exist in both in binary states and in a cause
and effect scenario whereby the information coming in is the cause, and the
conscious experience is the effect (G. Tononi & Koch, 2015).

The second well-known theory in
phenomenology currently is Baars, Dehaene and Changeux’s global workspace
theory, which proposes that consciousness is a highly competitive experience in
the brain whereby there is an overwhelming amount of incoming sensory
information which compete for very limited neural areas that can be stimulated,
but once stimulated, it is available to the larger system via whole-brain
communication (Cavanna et al., 2017; Lundervold et al., 2010).

Understandably, it is difficult to
directly prove or disprove an abstract theory with neuroimaging or
electrophysiological techniques. Fortunately, these techniques have been
successful at narrowing down regions in the brain in which consciousness might
be experienced or created. Functional MRI (fMRI) have showed that a person’s
default mode network (the systems in the brain that operate while a person is
at rest), located in the posterior cingulate cortex/precuneus, medial
prefrontal cortex, and temporoparietal junctions, is critical for consciousness
and awareness (Harrison & Connolly, 2013; Shulman, 2013b). Unfortunately, consciousness
very rarely involves one sense at a time and it is more difficult to determine
where the unity of information happens (Gray, 2004).

Tononi and Edelman are attempting to
locate the area where this integration happens using their dynamic core
hypothesis. The question is whether consciousness is supported by the whole-brain,
with complex communication occurring between systems, or is it occurring in a
few groups of neurons and then being propagated outwards (i.e. global workspace
theory; Cavanna et al., 2017; Lundervold et al., 2010; Giulio
Tononi et al., 2017). Research suggests
that it is probably the former, that consciousness is created using a dynamic,
fluid system, which is hypothesized to be in the thalamocortical system
(involving connections between the thalamus, the cortex and related systems
including the sensory, motor and association systems). In other words, it
includes much of the brain working together but only the strongest, fastest
connections lead to conscious experience or action, and the more connections
occurring at once between systems, the more complex the conscious behaviour (Cavanna et al., 2017; Lundervold et al., 2010).

Using this hypothesis, we can then use
machines such as functional MRI’s to help us determine the usefulness of these
theories in general. For example, it has been shown using fMRI that when a
person loses consciousness there is less communication between sections of the
thalamocortical system. Using the integrated information theory, we can explain
this due to a lack of differentiation and integration between brain areas (Cavanna et al., 2017). It is assumed
that certain neural processes, or groups of neurons, are linked to particular
properties of consciousness, and that some brain activation patterns are
correlated with conscious experiences-known as the neural correlated of
consciousness (NCC; Tegmark, 2015). These neural
correlates are the minimum amount of neural activity needed for a single
conscious experience, each unit of phi discussed earlier corresponds to an
associated NCC (Tononi & Koch, 2015). So
using an fMRI machine we can study the change in neural activity needed for a
conscious experience to occur. Using blood-oxygenated-level dependent (BOLD)
signals allows us to measure baseline energy levels (usually looking at the
default mode network) and compare it to BOLD signals during a task, or measure
energy used in various tasks against each other (Shulman,
2013a).

Studies have shown that there is less
widespread activity throughout the brain during loss of consciousness,
especially in the thalamocortical system (Shulman,
Hyder & Rothman, 2003). This provides support for the global
workspace theory which suggests that consciousness occurs throughout the brain,
as well as the dynamic core hypothesis, which postulates that consciousness is
supported by a fluid system located in the thalamocortical regions of the
brain. One study in particular done in rats shows good evidence to support the
suggestion that consciousness is created in the thalamocortical system. In a
study by Shulman (2013a) rats’ forepaws were
stimulated while under the effects of anesthesia that either prohibited
movement (baseline) or rendered them unconscious (deep-anesthesia). In the
baseline condition the somatosensory cortex of the brain was activated along
with several other areas, which were thought to be communicating with the
somatosensory cortex. In the anaesthesia-condition the only signals found were
in the somatosensory cortex-the brain was no longer globally communicating.
These are the sorts of experiments that can only be done with state of the art
equipment such as fMRIs and which provide support for current theories of
consciousness.

Not all the evidence lends itself towards
the global workspace theory, an experiment done with fMRIs looking at the
fusiform face area (FFA) by Gauthier and Tarr (2000) show that neural
activation in parts of the thalamocortical system work in a bottom-up fashion
which provides support for the integrated information theory. Participants
learned to expertly identify greebles, which are face-like objects, in the same
way that people learn to identify faces. As learning grew stronger, activity
and neural connections in the FFA and visual cortex grew stronger as well. Results
from fMRI showed that information was starting in the retina, visual cortex and
then flowing downstream to the extrastriate visual cortex (which includes the
FFA) where the signals were much stronger as the participant showed greater
awareness and recognition of the individual greebles. In other words, small
pieces of information (integrated information) that would have otherwise been
meaningless was entering the sensory areas of the brain and were sent to
higher-order areas where they were combined and became conscious experiences that
were then mapped onto behaviour (showing recognition; Gauthier
& Tarr, 2000; Shulman, 2013b).

Tononi and Edelman’s integrated
information theory tells us that when people become unconscious there should be
a breakdown in the ability of the brain to integrate any information that it is
receiving (Tononi & Koch, 2015). Studies
have shown that there is much less connectivity in the default mode network
(DMN) and in cortico-thalamic areas in patients who have disorders of
consciousness (DOC), which might indicate that these DOCs are a result of this
lack of integration between brain systems (Harrison
& Connolly, 2013; Cauda et al., 2009). A correlation has been found
between the integrity of connections (strength and number) in the DMN of some
DOC patients under resting-state fMRI studies (Vanhaudenhuyse
et al., 2010). This might suggest that further fMRI study of the DMN
could be helpful in determining the nature and location of consciousness. It
has been suggested that the DMN consists of two layers, one layer keeps
cognitive connections active independent of level of consciousness, and another
layer which decreases in activity as more and more consciousness is lost. This
idea suggested by Vanhaudenhuyse et al. (2010) is consistent with both fMRI
findings and the global workspace theory which advocates for the necessity of
an active large-scale communication network such as the default mode network.

One of the major drawbacks of uing
functional MRI to measure consciousness is that it is necessary for researchers
to know what locations and magnitudes the BOLD signals should be, and how to
quantify the neural information into something useful and informative. This is
especially true when using Baars, Dehaene and Changeux’s theory that
consciousness occurs globally, because it is difficult to study all areas of
the brain simultaneously without being overwhelmed by statistical noise (Shulman, 2013b). It also takes a lot of effort,
cognitively speaking for a person to create a meaningful signal in the brain
that can be seen using an fMRI, especially in patients with DOC. In the average
person the brain takes up roughly 20% of the body’s given energy; in patients
with DOC or under the effects of deep anesthesia this percentage is effectively
halved (apart from patients with locked-in syndrome, in which the patient is
fully conscious but unable to visibly show awareness). While resting-state fMRI
readings help mitigate this issue, it is still possible that researchers are
not seeing the whole picture regarding conscious experience measured via BOLD
signals.

Consciousness
is a deeply complex experience that is only beginning to be understood thanks
to the advent of technology such as functional MRIs. Several theories have been
proposed to attempt to untangle and understand it, but none have provided us
with an easy, or even any, answer to what consciousness truly is, where it
takes places and how it happens. There has been some support for both the
integrated information theory and the global workspace theories of consciousness
as evidence by various fMRI studies, but neither have solved the problem. The
future of phenomenology is a wide-open door and will only continue to grow as
technology continues to advance.