The conceptual chasm between neuroscience and psychology

The New York Times has a nice op-ed piece The Trouble with Brain Science by Gary Marcus, a psychologist. It is worth reading for several reasons. First, it is a nice accessible discussion of the status and challenges of neuroscience. Second, it illustrates the scientific challenges of understanding emergent phenomena. Third, it highlights some funding/political/stategic issues that are relevant to other fields.

The piece is stimulated by controversy concerning the Human Brain Project, "an approximately $1.6 billion effort that aims to build a complete computer simulation of the human brain", funded by the European Commission. The US has also funded a massive project, The Brain Initiative, focussed on developing new measurement techniques.

The controversy serves as a reminder that we scientists are not only far from a comprehensive explanation of how the brain works; we’re also not even in agreement about the best way to study it, or what questions we should be asking.
.... a critical question that is too often ignored in the field: What would a good theory of the brain actually look like?
..... biological complexity is only part of the challenge in figuring out what kind of theory of the brain we’re seeking. What we are really looking for is a bridge, some way of connecting two separate scientific languages — those of neuroscience and psychology....
We know that there must be some lawful relation between assemblies of neurons and the elements of thought, but we are currently at a loss to describe those laws.......  

The problem with both of the big brain projects is that too few of the hundreds of millions of dollars being spent are devoted to spanning this conceptual chasm.

Some of the scientific and political issues here are also relevant to other areas of science. In most fields involving complex systems advances require a combination of advances in instrumentation, materials preparation, computational models, analytical model development, and concepts. All are necessary and interdependent. At any one time a challenge for setting priorities and allocating resources is to have an appropriate balance between all of these approaches and areas.

Unfortunately, currently it seems funding agencies think it easier to convince politicians to fund big projects involving large scale instrumentation and/or computation. Smaller single-investigator grants, and particularly those focusing on conceptual issues and simple models, are getting squeezed out.