Brain as Metaphor for Organization

Since Kurt Lewin’s founding work, organizational behaviorists have viewed the organization as an “organism” which exists in an interacting system. “Open systems theory,” in turn, looks at the organization as an organism with permeable boundaries between its internal capabilities and competencies and the external environment, from which it draws sustenance (customers, investors, suppliers), restrictions (regulators, industry structures) and hostility (competitors).

In their textbook Organizational Development , French & Bell, C. provide the following characteristics of open systems:

• Open systems are input–throughput–output mechanisms. They take inputs (e.g. people, resources, information), change them in some way, and then return the processed input to the environment as an output.
  
• Open systems have permeable boundaries, which separate the organization from the environment.
  
• Open systems have goals and exist for a purpose. These purposes must be compatible with environmental needs otherwise the system will cease to exist.
  
• Open systems are homeostatic—they seek to achieve a state of equilibrium and minimize the impact of disruptive forces, whether internal or external.
  
• Open systems are predisposed to becoming increasingly differentiated, getting more elaborated, complex and specialized over time. Thus increased co-ordination and integration are needed to manage systems as they develop.

Organization as organism, of course, is an excellent example of the power of metaphor. By examining the properties and characteristics of one concept, such as a living, breathing animal, we seek to understanding that we can apply to another concept, such as the complex nature of today’s organizations. Literature falling out of the open systems tradition of organizational development have generally depicted the organization as a one-celled organism interacting with its rather primordial environment.

Linguists and literary critics tell us that metaphor consists of two parts: the tenor and vehicle. The tenor is the subject to which attributes are ascribed. The vehicle is the subject from which the attributes are borrowed. (I.A. Richards in The Philosophy of Rhetoric, 1936). Thus, open systems theorists in the domain of organization behavior typically deem the one-celled organism as the vehicle, and seek to extract learning about the organization as tenor. While the analogy has yielded considerable and useful insight about organizations, the simplicity and limitations of the vehicle - the simple-minded organism - diminish the potential utility of the metaphor.

Fortunately, the field of Neuroscience offers a much richer vehicle for understanding living systems: the brain. Like the tenor of our metaphor, the organization, the brain is composed of constituent systems that decide upon purpose and strategy (the frontal lobe of the cerebrum), motivate action (the amygdala), manage the flow of key information (the hippocampus), and enable communication from one sub-system to another (the corpus callosum).

This blog will exploit the metaphor of organization as brain. Its purpose is to extract information about the exquisitely formed human brain in order to gain insight into the design and redesign of modern organizations.

Motivation and the Sense of Urgency

Two brain parts appear to work in tandem for purposeful behavior to occur... The frontal cortex, part of the cerebral area, and the basal ganglia, which is part of the limbic system. In this article from Scientific American, a man sinks to the bottom of a pool, and cannot seem to muster the motivation to swim back to the top. He is content to drown, and after being saved from dewoning by his daughter, reports remembering being aware he was in grave danger, but he was simply unable to will himself to do anything about it.

http://www.sciam.com/article.cfm?id=drowning-mr-m

The Universe Large and Small

“How many particles are there in the known universe?,” you ask. Particles… protons, neutrons, electrons… that make up the atoms that make up the molecules in the uh, known universe. Billions of galaxies holding billions of stars and, evidently, planetary systems.

Well, there are apparently about 10 to the 87th particles out there. Ten to the 87th power. Ten multiplied by itself 87 times. That doesn’t seem like such a large number at all, does it? Yes, if I used a small typeface I could type the number onto one line of this page. Check me on this if you’d like. Google it. Subject the question to Wikipedia. Ask a smart friend. I know it’s quite a thought to think.

"Oh the thinks you can think!
Think and wonder and dream
Far and wide as you dare.
When your thinks have run dry,
In the blink of an eye
There's another think there!
If you open your mind
Oh, the thinks you will find
Lining up to get loose

Oh, the thinks you can think.... "

.

--Dr. Seuss

.

Thoughts, by the way, are now observable to the naked eye using a new machine called the fMRI. We can watch as circuits of neurons in the brain to fire in an instant corresponding to a cognition, image, smell or feeling. Since we have a billion neurons in our brains, with each neuron capable of connecting via little connectors called dendrites to a thousand or so other neurons at a time, there is a large number of possible “Hebbian nets” -- neural circuits – that a person might experience. How large a number? A recent estimate indicates the number of possible neural circuits in one person’s brain to be, listen to this now, ten to the millionth power. That’s a 1 followed by a million zeros. Now, just imagine the number of possible thinks that can be thunk when people multiply themselves as members of groups, teams, and organizations!

Yes, in a way of thinking, our brains are larger than the known universe. But we as individuals , as you know, are quite small. Here is a picture of a portion of the universe measuring roughly 2 billion light years in the shape of a cube.

The points of light are galaxies. Scientists could not find anyone willing to stand back far enough to snap this picture, so they roughed it out using a computer model. This is about what it would look like, though, as I understand it.

Now look at the picture below. What do you guess this is?

No, this is not the known universe looking from the other side. This is a picture of a neuron making connections to other neurons in a human brain. Remember, neurons are tiny. Each of our brains contains a hundred billion of these.

Both the big and small slices of the universe shown above are examples of systems, or networks. Obviously, the universe of galaxies and stars bears more than a passing likeness to the inner world we all carry around with us. We have only just begun understanding how these marvelous Hebbian nets work. A few axioms have become clear, though. Here are a few attributes of neurons and neural networks:

A neuron is built for connectivity. The interesting things that happen in the brain are characterized by vast webs of neurons firing simultaneously or in sequence. As noted, each neuron has numerous dendrites capable of hooking up with other neurons. A neuron working on its own could behave something like a light switch or a thermostat, but would otherwise seem fairly unintelligent and unimpressive to us. A network of neurons, though, provides us with the magic of our human experience. The depiction to the left shows the way neurons reach out to one another.

Individual neurons serve as hubs. Thousands of neighboring neurons may connect through a neuron as a means of reaching thousands more.

The picture to the left is familiar to us a hubbing system. This, of course, is the air traffic system of the North American continent. Bright sections in the picture, analogous to neurons, are the “hub cities” through which people may connect as they travel from their originating city to their airport of destination.

Neural networks are constantly being updated and renewed. Neural connections show plasticity. New connections are constantly being forged. Much of this reorganization and renewal is accomplished by the active brain while our bodies sleep.

Redundancy is a natural characteristic of Hebbian nets. An impulse may travel through a myriad of possible routes or pathways in order to connect one area of the brain with another. This avoids the bottle-necking that is observed in more limited systems. For example, there is really only one road I can take to reach the airport from my house. If there is a traffic tie-up, I’m sunk. A more natural network of roads, by which I might reach the airport from a variety of routes, would allow me to leave my house later when I travel. I could rest assured that if there is blockage somewhere in the system, I can get through some other way.

The internet works this way, by the way. As I send you an email, small packets of digital information leave my computer, depart from my house and travel separately through a variety web of connections, and are recombined at your house.

The image just above, by the way, is a depiction of the system, or network, that we know as the internet. You can see form this that there are indeed a lot of pathways that might connect my house with yours.

Any given neuron may become a part of any number of “networks” or “webs” that we experience of mental events. Typically neurons that fire together (in close temporal proximity), wire together. It's thought that networks (representing memories, beliefs, mental events) are represented by such "Hebbian nets" as they're called. Of course, that's just the current thinking and people are still debating it all the time.

The graphic to the left shows four fMRI views of a single mental event. A brainstorm of sorts.

The flavor of a given mental experiece appears to be determeinnted by the parts of the brian through which the Hebbian maps itself. For example, neuroscientist Jessica Payne confirms that "most lasting memories probably do have limbic connections that give them emotional flavor." (We'll examine the nature of the limbic system in a futur post.)

Use it or lose it. We'll make this the final principle, for the moment. My initial hypotesis was that if a neuron doesn’t get much “action,” its effectiveness diminishes and will not be available for future networks. Dr. Payne writes, though, that it is "not the neuron itself necessarily, but any given concept probably. If you've learned some bit of obscure knowledge and never think about it, it's availability will become diminished and will be unable to be woven into other networks (i.e. you won't be able to build on the knowledge)."

* * * * *
Remember, the purpose of this blog is to examine the workings of the brain as a vehicle for understanding, in an anological or metaphorical sense, the workings of complex orgaizations. Future posts will flesh this out. As a preview, though, I'll leave you with the following graphic showing a human network.

.

Why Do We Have Left and Right Brains?

Mark: Can you think of a reason why the evolutionary development process would leave us with these two brains?

John Batson, Furman University: I think the key is just as you suggest, evolution.

Ancient ancestors that were the first vertebrates displayed bilateral symmetry -- the right side is more or less the mirror image of the left. And that held and holds true for most internal organs, including brain.

So long before there was anything resembling a primate (much less a human), our ancestors were selected for a bilaterally symmetrical body plan. By the time the first primate-like creatures evolved, the bilateral brain was almost certainly symmetrical in function as well. But with recent evolution (the last few million years or so), some functions became lateralized (right brain better at some tasks, left brain better at others). So the present human brain is a relic of ancient selection that has adapted to more current selection pressures, including especially language and bipedalism.

Why do we have two brains? Certainly, if we designed an efficient brain today from scratch, we probably would not end up with the existing brain... it is not completely intelligently designed. We simply inherited what worked long ago, and what got modified along the way.

And by the way, the corpus callosum is not the only fiber system connecting left and right brains. There are several other smaller "commissures" (connecting pathways) joining various parts of left and right.

A Brain in the State of Reverie

Mark: Aware of the treasures of the intellect just before sleep, artists and intellectuals alike have found ways to tap into their theta state in manners both benign and dangerous. Not so long ago, people like Timothy Leary were touting hallucinogenic drugs as windows into the subconscious. On a healthier track, the artist Salvador Dali—he of the melting clocks and strangely shaped human figures—used to sit in a comfortable armchair holding a serving spoon in his hand. As he would begin to drift through the theta state toward sleep, the spoon would fall to the floor with a clang. Alarmed back to a wakeful state, Dali would immediately grab a pencil or brush and sketch the things he had just “seen” during his theta state.

Question: What does science, and in particular the study of different "brain waves" as tell us about the creative process?

Jess: Alpha waves do correspond to relaxed states, but they are usually observed with eyes closed. Mostly they correspond to the reduction of sensory input, as they appear immediately in most people upon closing the eyes with instructions to relax (8-12 Hz). Beta waves are higher frequency waves (> 12 Hz) and characterize active wakefullness, theta is between 4-8Hz and is still in the process of being understood.

It's a characteristic wave of REM sleep, and is not typically seen in healthy awake adults (except in the case of meditation! See Aftanas L, Golosheykin S (2005) Impact of regular meditation practice on EEG activity at rest and during evoked negative emotions. Int J Neurosci. 2005 Jun;115(6):893-909) - so we really could think of it, organizationally speaking, as a quiet, reflective, creative brain wave. But of course, it has a zillion other proposed roles as well, from sensori-motor integration, to short-term memory function, etc, etc. Delta waves are very slow (1-4Hz) and characterize the deepest stage of sleep (stages 3-4). So, what you learned wasn't entirely inaccurate, but it's not quite that simple, since all of these waves are seen in sleep except for beta.