Mind is not an information processor

In modern science and in popular belief mind is understood as a highly sophisticated computer – a machine that calculates, computes, runs algorithms to produce thought, understand language, control behavior. From some time, alternative ideas pop up in areas of cognitive science, psychology and neuroscience. In particular, it can be seen that a perspective of complex systems and dynamical systems is employed in attempts to research, characterize and understand what mind is and how does it work.

Overview:

1. What are we talking about?
1.1. What is a mind?
1.2. What is information processing?
2. Problems with the account of mind as an information processing device
3. A list of alternative approaches to understanding the mind
4. Mind as a self-organizing, dynamical structure
4.1. What is a complex dynamical system
4.2. Mind as a complex dynamical system
4.2. Understanding is the activity of the mind

What are we talking about?

Mind – an integrated system expressing emotion, cognitive and behavioral activities (“Mind” in Wikipedia). Emotions, moods, perception, intelligence, learning and memory, attention, control of the body and interaction with the environment, thinking and decision making, imagination, adaptation, understanding, anticipation, perspective taking, awareness and control of its own functions (metacognition), the sense of self, consciousness—these are deeds that a complex, human-level mind often exhibits.

Information processing is the manipulation of symbols, computation of values. Information processor is a system that takes information as an input, manipulates it, calculates new values, then outputs new information (“Information processor” in Wikipedia).

In this way, thinking, emotion, learning, anticipation should be regarded as operations on sensory or stored (remembered) information, as computational theory of mind clearly states (“Computational theory of mind” in Wikipedia; Horst, 2011). Output of such a system can have a form of new information (or representation (“Mental representation” in Wikipedia)) or a behavior. Such a view allows for clear formalization of functions of the mind in the form of algorithms: exact, mechanistic ways of accomplishing a task using specific rules and smaller operations.

Problems of the Computational Theory of Mind

The problems with this approach are numerous:

1. What is this information that we are talking about? Clearly, the information about the number of residents of London is something entirely different than stimuli on the retina, which is different than the arrangement of elements in front of the eye. What is being processed exactly?

2. How emotions could possibly be presented as operations on any kind of information?

3. Seeing mind as an information computing device blocks any attempt of incorporating consciousness into the system. Are conscious experiences, qualia, computed by the mind?

4. Is algorithmic rule-governed operation of a system sufficient for understanding? Can a machine that operations of computational principles understand what is it doing or what does the information that it is given as an input have any sense of what it means?

5. We don’t think that cells process information, nor do we think that hands do that. It would be unintuitive to talk about bird flock behavior or immune system action or climate or forest ecosystem as information processing systems. Are reasons for regarding minds as such systems really that strong?

6. Embodied cognition (Wilson, Foglia, 2011) – the idea that cognition takes place, and is grounded in, not only in the nervous system but in the body of the animal that actively interacts with its environment – is hard to be made compatible with computationalism.

7. Inactive mind is a dead mind. Does the mind processes information constantly? If so, why? If not, what is it doing when it’s not processing it?

8. Is the creation of new information possible, or is the operation of the mind only a transformation, or translation, of information into other, known types of information? What about creativity then?

9. Meaning of words. If the meaning of a word is just another information, then what is the meaning of that information? If the meaning of a word is an external object, then can this relation be implemented, and what about the meaning of abstract (e.g. mathematical) concepts?

Alternative approaches to understanding the mind

Ecological Psychology (“Ecological psychology” in Wikipedia) states that there is no need for complicated processing of information. All that is really necessary for proper behavior in the environment is the fitting modification of behavior to the development of the situation.

Embodied Cognition framework (Wilson, Foglia, 2011) wants to get by without symbols and symbolic manipulations. Meaning (of words, actions) is grounded in perceptions, interaction with the environment. Radical embodied cognitive science, a fringe faction of research, asserts that no representations of the world are necessary at all.

Mind as a self-organizing, dynamical structure

What is a complex dynamical system

A complex system is a system of strongly connected, interacting elements, that through self-organization, give rise to novel, emergent phenomena—qualities or behaviors that no smaller element produces (“Complex systems” in Wikipedia).

A dynamical system is a system, that continuously functions, evolves (“Dynamical systems theory” in Wikipedia), and – it the case of biological systems – may be perturbed by external events, changing the system’s trajectory, that is the direction to which it evolves.

Thus, a complex dynamical system is a collection of interacting elements, that through self-organization exhibits emergent phenomena and dynamical behavior.

Mind as a complex dynamical system

Research endeavors are under way to understand mind and brain not as a collection of encapsulated computing modules, but as a system of elements, which interactions with each other give rise to complex phenomena that we can observe in ourselves and other animals (“Systems neuroscience” in Wikipedia; Khambhati, Litt, Bassett, 2014; Hotton, Yoshimi, 2011; Mcdonough, Nashiro, 2014; Papo et al., 2014; Tognoli, Kelso, 2014; Bassett et al., 2014). Mind is thus a continuously active system, which is perturbed by external events that change its dynamics (Spivey, 2007).

Understanding is the activity of the mind

Sensing of the environment means being influenced by it. A thing if sensed if it changes the mind. Perception and understanding of the thing involves specific changes of activity of the mind. The mind can perceive, recognize and understand a given thing if it can act (be influenced by the thing) in a coherent way, as to move its own dynamics (activity) towards a trajectory (a way of acting, a direction of the dynamics) that is known to the mind. A known way of acting is a way that was previously experienced and is connected with other elements of the mind.

The act of understanding of a situation should be regarded in this view as the action of connected complexes of ideas, that evolve coherently and are compatible with the situation. That is, a complex of ideas evolves in such a way that there are no breakages of this activity in the course of understanding an unfolding situation.

Understanding language should conform to this idea. Let’s take for the example the situation described in a simple sentence “A dog is running by the house”. Understanding of this sentence start by the activation of the idea of a dog, that is then modified into a running dog and finally embedded in a context, the environment (“by the house”). Understanding of the sentence is thus simulation of the concepts and events that the sentence describes (Barsalou et al., 2008). Each new word, each new term in a sentence pushes the process of understanding further, changing the direction of the process of activity of connected complexes of ideas, instantiated by connected networks of neurons in the brain.

References

Mind. (2014, September 6). In Wikipedia, The Free Encyclopedia. Retrieved 12:18, September 8, 2014, from http://en.wikipedia.org/w/index.php?title=Mind&oldid=624387571

Information processor. (2014, April 1). In Wikipedia, The Free Encyclopedia. Retrieved 12:18, September 8, 2014, from http://en.wikipedia.org/w/index.php?title=Information_processor&oldid=602275490

Computational theory of mind. (2014, March 22). In Wikipedia, The Free Encyclopedia. Retrieved 12:18, September 8, 2014, from http://en.wikipedia.org/w/index.php?title=Computational_theory_of_mind&oldid=600684485

Mental representation. (2014, August 15). In Wikipedia, The Free Encyclopedia. Retrieved 12:19, September 8, 2014, from http://en.wikipedia.org/w/index.php?title=Mental_representation&oldid=621328825

Horst, Steven, “The Computational Theory of Mind”, The Stanford Encyclopedia of Philosophy (Spring 2011 Edition), Edward N. Zalta (ed.), from http://plato.stanford.edu/archives/spr2011/entries/computational-mind/

Wilson, Robert A. and Foglia, Lucia, “Embodied Cognition”, The Stanford Encyclopedia of Philosophy (Fall 2011 Edition), Edward N. Zalta (ed.), from http://plato.stanford.edu/archives/fall2011/entries/embodied-cognition/

Ecological psychology. (2014, June 28). In Wikipedia, The Free Encyclopedia. Retrieved 12:13, September 8, 2014, from http://en.wikipedia.org/w/index.php?title=Ecological_psychology&oldid=614763498

Complex systems. (2014, September 3). In Wikipedia, The Free Encyclopedia. Retrieved 12:15, September 8, 2014, from http://en.wikipedia.org/w/index.php?title=Complex_systems&oldid=624014972

Dynamical systems theory. (2014, July 28). In Wikipedia, The Free Encyclopedia. Retrieved 12:15, September 8, 2014, from http://en.wikipedia.org/w/index.php?title=Dynamical_systems_theory&oldid=618839901

Systems neuroscience. (2013, February 28). In Wikipedia, The Free Encyclopedia. Retrieved 12:30, September 8, 2014, from http://en.wikipedia.org/w/index.php?title=Systems_neuroscience&oldid=541145954

Ankit Khambhati, Brian Litt, Danielle S. Bassett. Dynamic network drivers of seizure generation, propagation and termination in human epilepsy, http://arxiv.org/abs/1407.5105

Hotton, S. and Yoshimi, J. (2011), Extending Dynamical Systems Theory to Model Embodied Cognition. Cognitive Science, 35: 444–479. doi: 10.1111/j.1551-6709.2010.01151.x

Mcdonough, Ian M and Nashiro, Kaoru. (2014), Network complexity as a measure of information processing across resting-state networks: Evidence from the Human Connectome Project. Frontiers in Human Neuroscience. http://www.frontiersin.org/human_neuroscience/10.3389/fnhum.2014.00409/abstract

David Papo, Javier M. Buldú, Stefano Boccaletti, Edward T. Bullmore. (2014), Introduction: Complex network theory and the brain. doi:10.1098/rstb.2013.0520 1471-2970

Tognoli E and Kelso JAS (2014) Enlarging the scope: grasping brain complexity. Frontiers in Systems Neuroscience 8:122. doi: 10.3389/fnsys.2014.00122

Bassett, Danielle S. et al. (2011). Understanding complexity in the human brain. Trends in Cognitive Sciences. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3170818/

Barsalou, L., Santos, A., Simmons, W., and Wilson, C. (2008). Language and simulation in conceptual processing. In De Vega, M., Glenberg, A. M., and Graesser, A. C., editors, Symbols, embodiment, and meaning, pages 245–283. Oxford University Press.

Spivey, M. (2007). The continuity of mind, volume 40. Oxford University Press.

Further reading

Complex systems biology. (2014, July 31). In Wikipedia, The Free Encyclopedia. Retrieved 12:17, September 8, 2014, from http://en.wikipedia.org/w/index.php?title=Complex_systems_biology&oldid=619273650

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