Does science have a definition of consciousness on which all who study it can agree?
Consciousness has been defined and described specifically to one area of the brain.
whttps://www.newscientist.com/definition/consciousness/
Surprisingly, though, the human cerebellum – a sort of mini brain hanging off the back of your cortex – contains about three-quarters of the neurons in your brain but seems to have almost nothing to do with consciousness. One reason we know this is because
some people are born without a functioning cerebellum, and while they experience some problems, a lack of consciousness is not one of them.
There are, however, some bundles of neurons that do appear to be vital for consciousness. If damage occurs to specific parts of the thalamus, or to a particular region of the brain stem, the result can be permanent unconsciousness. But are these brain regions actually central to generating conscious experiences, or are they more like a power socket that simply allows whatever is plugged into it to work?
Work involving brain imaging techniques such as
electroencephalography (EEG) paints a more complex picture. Several decades ago, neuroscientists including Francis Crick and Christof Koch began to search for what they called the
neural correlates of consciousness: particular patterns of brain activity that relate to given conscious states – the experience of a painful toothache, for example.
As studies like this have progressed it has become clearer that consciousness depends on specific ways that different parts of the brain – particularly the cortex – communicate with one another. For example, by injecting a pulse of energy into the brain using
transcranial magnetic stimulation (TMS), and using electroencephalography (EEG) to monitor the response, a team of neuroscientists led by Giulio Tononi and Marcello Massimini found that
the electrical echo generated by the energy pulse will bounce all around a conscious brain, but stays very localised in an unconscious brain. In other words, the conscious brain is much more connected.
Do experiments like this bring us closer to understanding what consciousness is? Some might argue not. In the 1990s, the philosopher David Chalmers made an influential contribution to the consciousness debate by distinguishing between what he termed the easy problem, or problems, and the hard problem of consciousness.
The easy problems involve understanding how the brain and body gives rise to functions like perception, cognition, learning and behaviour. These problems are called easy not because they are trivial, but because there seems no reason why they can’t be solved in terms of physical mechanisms – albeit potentially very complex ones.
The hard problem of consciousness
The hard problem is the enigma of why and how any of this should be accompanied by conscious experience at all: why do we each have an inner universe?
To address this hard problem, we need
theories of consciousness that can bridge the gap from the world of physical processes to the world of conscious experiences: that can take us from correlation towards explanation.
There are now many theories of consciousness out there in the field of cognitive
neuroscience: higher-order theories, global workspace theories, and integrated information theories, theories that – in their strongest form – imply that consciousness is spread widely throughout universe, and that even an electron may be conscious. There are even illusionist theories which attempt to persuade us that consciousness doesn’t really exist – at least not in the way we normally think about it.
The theory I’ve been developing is
a version of predictive processing theory. When I see a chair in front of me, it’s not that the eyes are transparent windows out onto the world and my brain just reads out “chair”. Instead there are noisy sensory signals impacting my retina and my brain has to use its prior expectations about what might be out there in order to interpret this ambiguous sensory data.
In a little more detail, the idea is that the brain is constantly calibrating its perceptual predictions using data from the senses. Predictive processing theory has it that perception involves two counterflowing streams of signals. There is an “inside-out” or “top down” stream that conveys predictions about the causes of sensory inputs.
Second question next post.