By the number of related disciplines, you may appreciate that this is a multidisciplinary problem of significant interest.
I will start with the bottom line and then provide brief background.
The Fundamental Problem: To Construct a 3-D Model of the 3 mm shell of the Human Cerebral Cortex so that microscopic neuroanatomic data specific to the six layers of 50 different cortical areas can be mapped onto it to show how the human cortex develops during the first six years of life.
The Background: We have the largest, quantitative database available on the microscopic, neuroanatomic features of the developing human cerebral cortex. In 1998, these data led to the overturning of the 100 year old dogma of no new neuron formation after birth, and ushered in the era of stem cell research. The data were described by the NY Times as the most important scientific finding of the last decade of the 20th century. Specifically, there are 8 age points of children who died of normal causes, at 0, 1, 3, 6, 15, 24, 48 and 72 months after birth. At each age point, for each layer of 50 cortical areas, there are measures of the numbers of neurons, their size, the numbers of inputs (large dendrites) and outputs (axons), the thickness of each cortical layer, the surface area of each cortical area. We have published that the signal-noise ratio of these data is extremely high, and that there is a common (undiscovered yet) pattern that characterizes the development of each cortical area.
The Challenge: To build a 3-D model that can take the values of these microscopic, neuroanatomic features at each age point, layer, and cortical locus, so that these changes can be visualized and analyzed with more complex mathematical methods to discover the underlying rules governing the development of the human cerebral cortex. These rules are likely to govern the structure of development of the cortex of other mammals.
An Additional Challenge: We also have camera lucida drawings of the cortical columns of each of these 50 cortical areas for each of the 8 age points. These camera lucida drawings are tracings of representative neurons in each layer of each cortical area. By quantifying these 2-D images and making some assumptions about their 3-D representation, one could incorporate these data into the above model to learn even more. Such research and development should lead to programs and algorithms of extraordinary power that will have use in many different disciplines. I can see how different disciplines would approach this problem in different ways, which is why I posted so many fields of interest.
If anyone would like to know more, or has suggestions for developing this project, I have the database, am a statistician and cognitive scientist by training and experience, and am one of the clinical authorities on Alzheimer's disease and other dementing disorders, which is essentially the reverse of development.
I would appreciate input from anyone with a creative streak and a taste for a challenging problem.
Thanks very much
Rod Shankle, MS MD FACP
PS: I have attached a PNAS article giving a nice brief summary of the data.