The cortical brain is an evolutionary marvel which interacts with the outside world via self-regulation, based on its resting or ground state. The resting state, which is disturbed during the stimulus and sensory processing, is recovered by automatic operations. A new research article, THE THERMODYNAMIC ANALYSIS OF NEURAL
COMPUTATION, examines the brain's sensory processing as an energy-information cycle. The work also has relevance for artificial
intelligence, such as deep learning.
The brain’s energy need multiplies in
warm-blooded animals. Although the human brain represents only 2% of the body
weight, it receives 15% of the cardiac output, 20% of total body oxygen
consumption, and 25% of overall body glucose utilization. The baseline energy
consumption might be entirely dedicated
to neuronal signaling. This constant and massive energy use maintains
the brain’s alertness, even during sleep, by a dynamic balance between
inhibitory and excitatory neurons.
The slightest variation in excitation
determines whether a spike is generated.
Such a delicate balance of excitatory and inhibitory neurons turns the resting
state into a highly energy-requiring state. Even in the absence of stimulus,
the delicate balancing of excitatory and inhibitory neurons produces seemingly
arbitrary activations. Like the tennis player's anticipation of the opponent's serve, the brain’s dynamic balance ensures its ability for a rapid, targeted response. For example, changes in inhibitory neurons increase frequencies and
their energetic needs. The brain partakes in the energy
information exchange with the environment via the sensory system.
Read the whole article in the Journal of Neuroscience &
Clinical Research
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