Unravel the fascinating complexities of the human brain as we debunk the common analogy of equating it to a computer. Discover the unique intricacies that set our cognitive abilities apart, challenging the conventional understanding of neuroscience.
We are living through one of the greatest scientific endeavours – the attempt to understand the most complex object in the universe, the brain
Scientists are accumulating vast amounts of data about structure and function in a huge array of brains, from the tiniest to our own
- Tens of thousands of researchers are devoting massive amounts of time and energy to thinking about what brains do, and astonishing new technology is enabling us to both describe and manipulate that activity.
- Despite the vast number of facts being accumulated, our understanding of the brain appears to be approaching an impasse.
Different kinds of emergence
Weak emergent features, such as the movement of a shoal of tiny fish in response to a shark, can be understood in terms of the rules that govern the behaviour of their component parts.
- This kind of weak emergence cannot explain the activity of even the simplest nervous systems, never mind the working of your brain, so we fall back on strong emergence, where the phenomenon that emerges cannot be explained by the interaction of the individual components.
- Strong emergence has recently been criticised by some neuroscientists as risking “metaphysical implausibility”, because there is no evident causal mechanism, nor any single explanation, of how emergence occurs.
The Brain as a Computer
The brain-as-a-computer metaphor retains its dominance, although there is disagreement about how strong a metaphor it is.
- Some argue that the task of neuroscience is to “reverse engineer” the brain, much as one might study a computer, examining its components and their interconnections to decipher how it works
- A pair of neuroscientists decided to actually do the experiment on a real computer chip, which had a real logic and real components with clearly designed functions
- They used the full range of neuroscientific techniques they normally used to analyze the brain and applied them to the MOS 6507 processor found in computers from the late 70s and early 80s that enabled those machines to run video games such as Donkey Kong and Space Invaders
- Despite deploying this powerful analytical armoury, and despite the fact that there is a clear explanation for how the chip works, the study failed to detect the hierarchy of information processing that occurs inside the chip
Future Neuroscience
The nature of the brain – simultaneously integrated and composite – may mean that our future understanding will inevitably be fragmented and composed of different explanations for different parts.
- Churchland and Abbott spelled out the implication: “Global understanding, when it comes, will likely take the form of highly diverse panels loosely stitched together into a patchwork quilt.”
Why can’t the world’s greatest minds solve the mystery of consciousness?
Brains are made of neurons and other cells, which interact in networks, the activity of which is influenced by neuromodulators
- It is clear that brain function involves complex dynamic patterns of neuronal activity at a population level
- Finding the link between these two levels of analysis will be a challenge for much of the rest of the century
- Progress will inevitably be piecemeal and slow because there is no grand unified theory of the brain
- We will slowly piece together a theory (or theories) out of a series of separate but satisfactory explanations
The brain is not a passive organ that passively responds to inputs and processes data
It is an active organ that is intervening in the world
- The brain does not represent information: it constructs it
- Metaphors of neuroscience – computers, coding, wiring diagrams, etc – are inevitably partial
- But they allow insight and discovery
- We may be approaching the end of the computational metaphor
- Scientists often get excited when they realise how their views have been shaped by the use of metaphor
