Analog Wave Forms Versus Digital "Information" Models of the Brain

Two recent studies reinforce my previous hypotheses regarding the underlying biophysical meta-stable soliton shockwave nature of brain/mind duality. The first study  from MIT showed that in rats the peak of oscillatory brain waves coincide with the activity of successful problem solving.

This coheres with what I have adduced from the principle embedded in Riemann's work on supersonic shockwaves. To wit: the pre-existing medium of activity is transparent for learned behaviors but must be somehow transformed to allow for new previously unknown behaviors. The wave forms associated with this new process are travelling faster than the medium can transmit. Therefore the oscillations bunch up and the medium undergoes a  transformation via induced plasticity. Once that occurs, the medium is now transparent to the newly learned behavior. (The use of a rat's brainwaves, of course only provides an extremely crude biophysical substrate for human "learning.")

The second study from UCLA, whether the said researchers are aware of it or not, provides a devastating refutation of so-called connectionist artificial intelligence brain network models.

Rather than presupposing a fatuously crude base 2 input-output, on-off "deep grammar" model for neuronal function, it proceeds from the actual physical evidence that there are harmonically tuned analog wave forms that are optimized for maximal learning.

The puerile attempt to model human thought, let alone lower forms of mammalian mental behavior, from the standpoint of a digital model is inherently fallacious because mathematics itself is not and can never be a substitute for the process of universal harmonic, and in the case of humanity, willful, ongoing self development. To coin a phrase, the very neurons and dendrites cry out this truth.