Sunday, September 14, 2008

The Dynamic Brain: From Spiking Neurons to Neural Masses and Cortical Fields

This is an excellent open access article posted a while back on the ways the brain makes consciousness from basic functions. This isn't light reading, but it's interesting.

Here is the abstract, full article is at this link.


The cortex is a complex system, characterized by its dynamics and architecture, which underlie many functions such as action, perception, learning, language, and cognition. Its structural architecture has been studied for more than a hundred years; however, its dynamics have been addressed much less thoroughly. In this paper, we review and integrate, in a unifying framework, a variety of computational approaches that have been used to characterize the dynamics of the cortex, as evidenced at different levels of measurement. Computational models at different space–time scales help us understand the fundamental mechanisms that underpin neural processes and relate these processes to neuroscience data. Modeling at the single neuron level is necessary because this is the level at which information is exchanged between the computing elements of the brain; the neurons. Mesoscopic models tell us how neural elements interact to yield emergent behavior at the level of microcolumns and cortical columns. Macroscopic models can inform us about whole brain dynamics and interactions between large-scale neural systems such as cortical regions, the thalamus, and brain stem. Each level of description relates uniquely to neuroscience data, from single-unit recordings, through local field potentials to functional magnetic resonance imaging (fMRI), electroencephalogram (EEG), and magnetoencephalogram (MEG). Models of the cortex can establish which types of large-scale neuronal networks can perform computations and characterize their emergent properties. Mean-field and related formulations of dynamics also play an essential and complementary role as forward models that can be inverted given empirical data. This makes dynamic models critical in integrating theory and experiments. We argue that elaborating principled and informed models is a prerequisite for grounding empirical neuroscience in a cogent theoretical framework, commensurate with the achievements in the physical sciences.

Geeky but cool.


gregory said...

the model is flipped. none of these physical events dictates that the events create the consciousness, nothing more can be said than that they accompany it.

to guess that they produce consciousness is a supposition or a projection.

the events could be the same if subtle shifts in consciousness resulted in changes on physical levels.

the "consciousness comes from meat" guys need to look at what the "meat comes from consciousness" guys.

and now i have to read this thing again. thanks for posting it.

gregory lent

gregory said...

it is like those guys are measuring sideways relationships between bumps and textures and pigments on the skin of an orange, unaware of the fruit within, and of the seeds within the fruit, that can actually make new oranges.

and if you analyze a seed there is no way that the life force that makes a seed make a tree can be discovered.

to me neuroscientists are not much different from religious fundamentalists. neither of those two groups would agree. :-)