Steven Crane Compiled Section Handouts. Human Behavioral Biology 2012

Reductionism and Chaos

What are the historical origins of our modern reductionist science?

1. 
   Dark Ages: a whole lot of tremendous knowledge was lost.
   
2. 
   Somewhere along the way (Enlightenment), a lot was re-discovered and invented, like reductionist thinking. What are the big ideas of reductionism?
   
   1. 
      You can break things down into component parts, understand the parts, and therefore understand the complex whole.
      
   2. 
      Putting the component parts back together in a linear, additive manner will produce the complex whole.
      
   3. 
      Know the starting state, and you know the ending state. Further, a simple, small change in the starting state leads to a simple, small change in the end state.
      
   4. 
      Complex reductive systems need plans/blueprints (and a master planner to make those blueprints).
      
   5. 
      Variability is just noise/signal error/instrument error. The ideal solution is out there; all you need is more powerful tools to find it.
      

Of course, this reductionist view runs into issues in some areas of science. Like what?

1. 
   Problem: insufficient numbers of component parts
   
   1. 
      Not enough neurons for a reductive brain based on simple dot/line/shape recognition building up to
      

grandmother neurons. Solutions?

1. Instead we see sparse coding in some neurons that respond to relatively few complex stimuli (like Jennifer Anniston and the Sydney Opera House). Almost like grandmother neurons. That's not the majority of cases though.

2. Instead, we have networks of neurons (or different nodes in the networks) representing many different things. (more to come on this below)

1. 
   Not enough genes
   
   1. 
      For the bifurcations of the circulatory system, pulmonary system, or dendritic trees on neurons.
      
      1. 
         These systems bifurcate at the level of single dendrites, at the level of dozens of cells in a capillary wall, at the level of thousands of cells in lung bronchi bifurcations.
         
      2. 
         But there just aren't enough genes for this style of genetic bifurcation!
         
2. 
   You also can't have a purely reductive system of deterministic predictability when there is so much chance.
   
   1.