A recent post on Mind Hacks challenged the perspective outlined in a NY Times op-ed by psychologist Gary Marcus with the title Face It, Your Brain Is a Computer. The title of Marcus’ piece may be misleading. The brain/computer analogy that he proposes is more a strategy than a theory. But the rejection of brain/computer analogies seems almost reflexive (as one can see from the comments on the Mind Hacks post). They can be quickly judged wrong, devoid of the vitality and creativity of life, and misguidedly materialistic. Information processing ideas, however, are increasingly present in the physical and life sciences and do not have the character of reductionist thinking.
Marcus describes his strategy as having two steps:
finding some way to connect the scientific language of neurons and the scientific language of computational primitives (which would be comparable in computer science to connecting the physics of electrons and the workings of microprocessors);
and finding some way to connect the scientific language of computational primitives and that of human behavior (which would be comparable to understanding how computer programs are built out of more basic microprocessor instructions).
The computational primitives of electronic systems include their instructions (like add, branch, plot) and actions related to the collection and storage of data (like fetch and store or compare and swap). An example of the application of these ideas to an analysis of brain function can be seen in some of the work of L. Andrew Coward whose recent papers can be found here. This kind of research is motivated, in part, by the needs of artificial intelligence designers. Conference proceedings from the 5th Annual International Conference on Biologically Inspired Cognitive Architectures make a number of related papers available here.
The critique of this perspective that is described on Mind Hacks points to an interesting question:
The idea that the mind and brain can be described in terms of information processing is the main contention of cognitive science but this raises a key but little asked question – is the brain a computer or is computation just a convenient way of describing its function?
Here’s an example if the distinction isn’t clear. If you throw a stone you can describe its trajectory using calculus. Here we could ask a similar question: is the stone ‘computing’ the answer to a calculus equation that describes its flight, or is calculus just a convenient way of describing its trajectory?
After a few other objections to the brain/computer analogy, the point is made that “the concept of computation is a tool.” But there is no indication that there is a growing perspective which sees ‘information’ as the fundamental aspect of everything, despite the fact that this perspective introduces a number of ideas relevant to understanding the brain, and on multiple levels.
Physicist David Deutsch, for example, is currently involved in what he has named constructor theory. I wrote about this work in a Scientific American guest blog. Constructor theory is meant to get at what Deutsch calls the “substrate independence of information,” which necessarily involves a more fundamental level of physics than particles, waves and space-time. For Deutsch, information is physical, instantiated in various forms, and transformed by various processes. And he suspects that this ‘more fundamental level’ may be shared by all physical systems.
Leibniz disassociated ‘substance’ from ‘material’ and reasoned that the world was not fundamentally built from material. He argued that fundamentals must be indivisible, and material is not. In The Lightness of Being, physicist Frank Wilczek describes the debate about fundamentals in this way:
Philosophical realists claim that matter is primary, brains (minds) are made from matter, and concepts emerge from brains. Idealists claim that concepts are primary, minds are conceptual machines and conceptual machines create matter.
It would seem from this that which ever direction one chooses, what has been learned from the development of computer hardware and software, and the ideas associated with what we call ‘computation,’ are helping to direct and inform research. And while the realist view looks reductionist, the idealist view is certainly not.
In a Closer to Truth interview, Gregory Chaitin responds to the question, “is information fundamental?” He admits that the inspiration for these ideas may be the computer, but a theory, itself, can be thought of as a computation. The theory is the input and the physical universe is the output. A theory is good when it is a compression, when what you put into the computer is simpler or smaller than what you get out. It’s then that you understand, and that understanding can be mathematical or physical.
Virginia Chaitin has written on what she calls interdisciplinary, where “the original frameworks, research methods and epistemic goals of individual disciplines are combined and recreated yielding novel and unexpected prospects for knowledge and understanding.” This kind of paradigm-shifting interdisciplinary effort involves adopting a new conceptual framework, borrowing the very way that understanding is defined within a particular discipline, as well as the way it is explored and the way it is expressed. The results, as she says, are the “migrations of entire conceptual neighborhoods that create a new vocabulary.” Perhaps the strategy that Marcus proposes can be seen in this light.
The growing interest in information-driven worlds is evident in the conference being organized in The Netherlands (October 7 – 9). It has been named ‘The Information Universe’ Conference and its welcome page says the following:
The main ambition of this conference is to explore the question “What is the role of information in the physics of our Universe?“. This intellectual pursuit may have a key role in improving our understanding of the Universe at a time when we “build technology to acquire and manage Big Data“, “discover highly organized information systems in nature“ and “attempt to solve outstanding issues on the role of information in physics“. The conference intends to address the “in vivo“ (role of information in nature) and “in vitro“ (theory and models) aspects of the Information Universe.
The discussions about the role of information will include the views and thoughts of several disciplines: astronomy, physics, computer science, mathematics, life sciences, quantum computing, and neuroscience. Different scientific communities hold various and sometimes distinct formulations of the role of information in the Universe indicating we still lack understanding of its intrinsic nature. During this conference we will try to identify the right questions, which may lead us towards an answer.
Ideas related to information and information processing are enjoying wide application. And the objections to using computational models to understand the brain are often grounded in the kind of reductionist view that, I would argue, is outdated and fading from current research efforts. It betrays a mistaken view of what mathematics can offer to theories in physics, cognitive science, consciousness studies, evolution and epistemology. The current inclination to broaden the meaning of information, and associated processes, has the potential to shed new light on what the brain might actually be doing, or what it’s place in nature might be.