The challenge to simulate the brain

Michele FariscoIs it possible to create a computer simulation of the human brain? Perhaps, perhaps not. But right now, a group of scientists is trying. But it is not only finding enough computer power that makes it difficult: there are some very real philosophical challenges too.

Computer simulation of the brain is one of the most ambitious goals of the European Human Brain Project. As a philosopher, I am part of a group that looks at the philosophical and ethical issues, such as: What is the impact of neuroscience on social practice, particularly on clinical practice? What are the conceptual underpinnings of neuroscientific investigation and its impact on traditional ideas, like the human subject, free will, and moral agency? If you follow the Ethics Blog, you might have heard of our work before (“Conversations with seemingly unconscious patients”; “Where is consciousness?”).

One of the questions we ask ourselves is: What is a simulation in general and what is a brain simulation in particular? Roughly, the idea is to create an object that resembles the functional and (if possible also) the structural characteristics of the brain in order to improve our understanding and ability to predict its future development. Simulating the brain could be defined as an attempt to develop a mathematical model of the cerebral functional architecture and to load it onto a computer in order to artificially reproduce its functioning. But why should we reproduce brain functioning?

I can see three reasons: describing, explaining and predicting cerebral activities. The implications are huge. In clinical practice with neurological and psychiatric patients, simulating the damaged brain could help us understand it better and predict its future developments, and also refine current diagnostic and prognostic criteria.

Great promises, but also great challenges ahead of us! But let me now turn to challenges that I believe can be envisaged from a philosophical and conceptual perspective.

A model is in some respects simplified and arbitrary: the selection of parameters to include depends on the goals of the model to be built. This is particularly challenging when the object being simulated is characterized by a high degree of complexity.

The main method used for building models of the brain is “reverse engineering.” This is a method that includes two main steps: dissecting a functional system at the physical level into component parts or subsystems; and then reconstructing the system virtually. Yet the brain hardly seems decomposable into independent modules with linear interactions. The brain rather appears as a nonlinear complex integrated system and the relationship between the brain’s components is non-linear. That means that their relationship cannot be described as a direct proportionality and their relative change is not related to a constant multiplier. To complicate things further, the brain is not completely definable by algorithmic methods. This means that it can show unpredicted behavior. And then to make it even more complex: The relationship between the brain’s subcomponents affects the behavior of the subcomponents.

The brain is a holistic system and despite being deterministic it is still not totally predictable. Simulating it is hardly conceivable. But even if it should be possible, I am afraid that a new “artificial” brain will have limited practical utility: for instance, the prospective general simulation of the brain risks to lose the specific characteristics of the particular brain under treatment.

Furthermore, it is impossible to simulate “the brain” simply because such an entity doesn’t exist. We have billions of different brains in the world. They are not completely similar, even if they are comparable. Abstracting from such diversity is the major limitation of brain simulation. Perhaps it would be possible to overcome this limitation by using a “general” brain simulation as a template to simulate “particular” brains. But maybe this would be even harder to conceive and realize.

Brain simulation is indeed one of the most promising contemporary scientific enterprises, but it needs a specific conceptual investigation in order to clarify its inspiring philosophy and avoid misinterpretations and disproportional expectations. Even, but not only, by lay people.

If you want to know more, I recommend having a look at a report of our publications so far.

Michele Farisco

We like challenging questions - the ethics blog

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