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Wednesday, May 4, 2011

What's the Code (2.0) - Got Rhythm? [Full link to blog for email clients.][FT:C44]

As promised in the last blog, this time we're going to talk about a less obvious form of neural code - oscillation.

Believe it or not, most people have heard of this type of encoding, they just don't realize what it is - some neurons in the brain seem to not have a specific encoding function, rather they fire at a continuous steady rate.  Like a pacemaker, these neurons vary their firing rates only within very highly constrained circumstances, thus the neuron forms a sort of clock or pacemaker rhythm as a background to other types of encoding.

Such a rhythm is not a single fixed frequency, nor does any one neuron provide the entirety of the frequency - that is, not every neuron necessarily fires on each "peak" of the wave.  Instead, many different neurons fire "entrained" to the rhythm, and the frequency is thus a product of many neurons firing, going silent, then firing over and over again.  Most of the brain's intrinsic rhythms are derived from small bundles of neurons that "oscillate" at the basic frequency.  For example, the first electroencephalographic (EEG) recording by Hans Berger in 1924 revealed a basic rhythm that he called "Alpha wave" (Top of figure at right).  This rhythm was eventually found to originate in thalamic neurons.

Neuroscientists consider two oscillations to be "basic" to rhythms to the EEG - even though only one is a true "rhythm" - and these are termed the Alpha and Beta rhythm.  Alpha is dominant at rest, when the eyes are closed, or the subject is in a restful, meditative state.  Beta dominates when the eyes are open and the brain is actively involved in attention, and conscious thought.  Beta is not a true rhythm in that it does not adhere to a strict oscillator, but is instead reflects the natural rate(s) at which neurons can fire when active.  The Mu rhythm is essentially an Alpha-like rhythm that is recorded from motor cortex when the muscles are at rest, however it originates in motor cortex and is modulated more by cerebellum than thalamus.

Delta is the frequency most indicative of sleep and drowsiness.  A subject with eyes closed but awake and thinking or meditating will show very little Delta.  However, an awake but sleepy person will show intermittent bouts of large amplitude Delta waves in their EEG which represent "microsleep" episodes responsible for the "head nod" well-known to students in lectures!  The "Power Spectrum" plot in the figure above represents analysis of EEG according to the underlying frequencies of the waveform (aka Fourier Analysis).  In the sleep state (red), Delta dominates, and the faster frequencies (Beta and Gamma) are nonexistent (until REM sleep starts, that is).  The awake subject shows more of the fast rhythms, and less of the slow rhythms. 

Theta and Gamma are interesting rhythms in that these actually are oscillator rhythms that are essential to information encoding in the brain.  Theta is a slow rhythm associated with movement, and found mostly in the deep nuclei, particularly the limbic system.  Hippocampal Place Cells tend to fire in phase with Theta, and the *difference* in time between neuron firing and the peak of the Theta rhythm can be used to determine distance, speed and direction of movement.  Theta appears to be essential to *sequences* of neural activity that form a map of the environment and track navigation through that environment.  There is also some indication that it assists in timing and coordinating muscle movement.

Gamma rhythm is associated with the cortical regions of the brain.  Neurons that are active at the same time in separate brain areas, but representing the same or related information, tend to fire with the same relationship to fast oscillations of typically 40 Hz.  Local regions may exhibit a rhythm up to 100 Hz, but the common factor is that the Gamma rhythm ensures that neurons within a circuit are active at the same time.  Neuroscientists feel that the Gamma rhythms serve as the "binding" or connection between neurons within a region, and between associated regions, in order to allow them to work on the same information - whether that is a cognitive (thought) process or planning and carrying out a motor movement.

So, in addition to the examples of Neural Coding presented in the last blog, we now see that each can exist in relationship to oscillations created by collections of neurons that fire with the same rhythm.  The presence or absence of such rhythms, not to mention the timing relationships within the rhythm, form a powerful additional modulator of the information that a neural code can represent. To this we then add the topographical connections between neurons, the specificity of neurotransmitter and receptor combinations, and the thousands of connections that each neuron can make...

The net result is a "device" that is capable of representing so much more than "one's" and "zero's" and make the brain so much more than merely a collection of simple processing units!

Thus, despite the technological advance of putting more and more processors into a computer, we have *so* far to go before being able to model a mammalian brain with a computer. 

Until next time - use your brain!  That's what it's there for!

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