The Wired Mind

MIND AS MACHINE

The brain is explained as a complex biological machine.

ELECTRIC MIND

Our brains are fundamentally electric and cognition occurs through “signals”.

Faster is better

We get smarter as signals move faster and more efficiently.

ITS all Connections

Intelligence is a factor of the scale and complexity of neural interconnectedness.

Mind Mapping

There is a human predilection with the mapping of theories of mind in terms of contemporary belief systems and technologies.

The myth of the wired mind Mapping Minds References

Consciousness “happens”

In our modern age we hold dearly an image of the brain as if it were a machine made of wires. The wired-mind, as it is called, is a very culturally ingrained metaphor in neuroscience, psychology, mental health, AI and even in everyday speaking when referring to the way the mind works, the way the mind heals and the way the mind breaks. The metaphor finds its origins in the scientific breakthroughs showing that the building blocks of the brain are electrically active neurons and the activity and nature of these neurons seem to reflect that of an electric wire with even its own electric insulators – the myelin sheath.

Every neuron an electrical pathway, insulated with Myelin. Through these pathways ideas somehow light up like lightbulbs. The mind is thus a circuit: signals travel, meaning arrives, thought emerges through connections, rewiring, and the sheer scale of neural network complexity.

We ‘believe’ that the mystery of consciousness lies out of our reach – beyond comprehension – due simply to the overwhelming complexity of the mind’s interconnectedness.

Science and philosophy have for quite some time been uncomfortable bedfellows. No more so than in the question of the mind and the brain. While significant progress is being made on all fronts, from the medical, the biological, the technological and computational we remain nonetheless distant from understanding the mind and the brain (Dehaene, 2014). We have mapped out the brain in astounding functional detail, like the great explorers of the new world (Geddes, 2016). Yet with our comprehensive map laid out before us, we get no closer to understanding the quandaries that have troubled us since the ancient philosophers. Chalmers (1995) presents the  hard problem facing the science of the mind and the brain in so much that we can give sophisticated descriptions of brain organisation/function while still having little understanding of the  phenomenon of subjective experience. All efforts and attention are being placed upon the perspective that cognition, memory, and consciousness are something  that just happens in due course as a product of the inordinate complexity and interplay of the neural networks in the brain (Thagard, 2012). Work across the sciences, philosophy, and now even artificial intelligence ( AI) all chase this holiest of grails, following the map laid out by the building-block  of the brain, the neuron. 

I hypothesise that maybe the reason we haven’t found what we are looking for, is because, a map is not what we need. 

Hubert Dreyfus (1992) famously asserted that computers cannot think and probably never will. Yet current dominant philosophical and scientific theories of mind and brain seem to be evolving and developing around a technological computational scaffold (Bickle, 2003). Concepts such as the free energy theorem (Friston et al., 2006) and active inference (Kirchhoff et al., 2018) taking the fore. This isn’t surprising as, over the ages, we have always tended to map our dominant belief systems as explanation for the mind and consciousness (Hofstadter & Dennett, 2010). 


Ancient Maps

In ancient times the mind and consciousness were described in terms of gods, spirits, and celestials. The age of enlightenment and organised religion opened the door to cartesian dualisms: heaven and earth, the soul and the flesh, a material extended body that coexisted with the immaterial un-extended mind, or spirit. Then came technology: in an almost synchronised burst of innovation came a flood of actual maps. The 16th century saw Mercator creating a detailed map of the world; Dürer creating the first printed celestial maps with coordinates, and Vesalius created the first detailed map of the nervous system. The discovery and exploration of electricity in the 17th and 18th centuries, mapped to Galvani’s suggestion in 1791 that electrical impulses played an important role in the nervous system. The rise of telephony mapped to the subsequent description of the brain as a complex signal exchange system. Messages travelling along nerves being routed to other nerves like the switch of a telephone standard. The wiring and neural network of the brain is still a commonly used metaphor, especially in describing learning, neuroplasticity, and the rewiring of the brain after brain trauma. Telephony was narrowly followed by the era of film where again descriptions of consciousness embraced the nomenclature of the innovation. The cinema of the mind, mental images like thought bubbles, and behavioural imprints also becoming common-sense terminology. The development of the valve and the transistor gave birth to both the electronic switch and the binary capacity for machines to make decisions, solve problems and be smart. The industrial revolution of automated factories with sensors built upon inputs and outputs then galvanised a cognitive model of the brain as an input/output system with sensory input and cognitive output. 

Modern Maps

This wave of mapped constructs continued to grow with the evolution of the transistor into the processor, the silicon chip. Now the thinking of the brain was portrayed as cognitive processing. The processor took on an architecture with a basic input output system known as ‘BIOS’ with shift registers to store and share this information. Two types of registers were developed, temporary volatile storage that requires electrical power, and non-volatile storage that doesn’t require power, referred to more commonly as short-term and long-term memory registers. At the same time cognitive science, portraying the mind as a system of sensory inputs, components, short-term and long-term memory, cognitive processing, the brain’s wetware, and cognitive operations akin to the dualistic computer hardware and software.

Digital technology overtakes analogue: quantization and discreet representation, divide and separate, ones and zeros. The internet, the world-wide computer network helped to take the wired brain into a neural network of interconnected nodes, sharing information, with massive parallel processing. Now we see the technology of digital signal processing and compression again mapping our views. The techniques developed in the 1990s used to compress sound and images that we are all familiar with, JPG, MP3 and MP4s, have leaked their error-minimisation algorithms into the 2020 models of predictive cognition. The hidden Markov models used in old fashioned signal recognition and AI with fuzzy weighted logic and trained stochastic codebooks, that learn by measuring a signal, quantifying the difference/residual to a codebook, rinse, and repeat. The fundamental binary endless loop of the computer and AI that indefatigably processes unto infinity, unaware of the meaning of its calculations. Quantum physics, has even suggested that the mathematics of quantum states lie behind the mysteries of consciousness (Hameroff, 2021).  From spirits and celestials to networked computers, AI and quantum mathematics,  Dreyfus may be safe in his assertion that computers may never think, no more than maps, wires, photographs, or valves can. The fundamental problem with the map is that it is an intellectualisation, a spatialised abstraction of reality, based on objects in locations, things in places.

Somewhere in the metaphor of a wired mind is the belief that cognition is the delivery of meaning – not its emergence. The making of wired connections is at once behind the making of meaning and yet also somehow its very delivery.  What the wired-mind erases is time through which meaning actually forms.


Selected References

Bickle, John. 2003. Philosophy and Neuroscience: A Ruthlessly Reductive Account. Dordrecht: Springer Science+Business Media.

Boycott, B. B., J. Y. Lettvin, H. R. Maturana, and P. D. Wall. 1965. ‘Octopus Optic Responses’. Experimental Neurology 12(3):247–56. doi:10.1016/0014-4886(65)90070-1.

Chalmers, D. 1995. ‘Facing up to the Problem of Consciousness’. Journal of Consciousness Studies 2(3):200–219.

Dehaene, Stanislas. 2014. Consciousness and the Brain: Deciphering How the Brain Codes Our Thoughts. Penguin Books.

Dreyfus, Hubert L. 1992. What Computers Still Can’t Do: A Critique of Artificial Reason. Cambridge, Mass: MIT Press.

Friston, Karl, James Kilner, and Lee Harrison. 2006. ‘A Free Energy Principle for the Brain’. Journal of Physiology-Paris 100(1–3):70–87. doi:10.1016/j.jphysparis.2006.10.001.

Geddes, Linda. 2016. ‘Human Brain Mapped in Unprecedented Detail’. Nature nature.2016.20285. doi:10.1038/nature.2016.20285.

Hameroff, Stuart. 2021. ‘“Orch OR” Is the Most Complete, and Most Easily Falsifiable Theory of Consciousness’. Cognitive Neuroscience 12(2):74–76. doi:10.1080/17588928.2020.1839037.

Hofstadter, Douglas R., and D. C. Dennett. 2010. The Mind’s I: Fantasies and Reflections on Self and Soul. [Nachdr.]. New York: Basic Books.

Kandel, Eric, James Schwartz, and Thomas Jessell. 2013. Principles of Neural Science. McGraw-Hill Education.

Kirchhoff, Michael, Thomas Parr, Ensor Palacios, Karl Friston, and Julian Kiverstein. 2018. ‘The Markov Blankets of Life: Autonomy, Active Inference and the Free Energy Principle’. Journal of The Royal Society Interface 15(138):20170792. doi:10.1098/rsif.2017.0792.

Reisberg, Daniel. 2021. Cognition: Exploring the Science of the Mind (Eighth Edition). 8th ed. New York, NY: WW Norton.

Rose, Steven. 2012. The Making Of Memory: From Molecules to Mind. London: Vintage Digital.

Stevens, Charles F. 1999. ‘Memory: From Mind to Molecules’. Nature Medicine 5(12):1343–44. doi:10.1038/70903.

Thagard, Paul. 2012. The Brain and the Meaning of Life. 1st pbk. ed. Princeton, N.J.: Princeton University Press.

Weidman, Nadine M. 2006. Constructing Scientific Psychology: Karl Lashley’s Mind-Brain Debates. Cambridge Studies in the History of Psychology. Cambridge ; New York: Cambridge University Press.