Information Processing in Human Body

Posted on May 3rd, 2010 Admin
Gene Circuit Based on final project for MIT Class MAS 862 (1998) by Vadim Gerasimov
Corrected and updated in 2000-2006.

Human Body

Total number of cells 6*1013
Genetic code 6*109 base pairs or 1.5GByte (only 3% or 45 MBytes of that is active)
Summated length of chromosome DNA chains in all cells 1.2*1014m (4.6 light days)
Chromosome copy operations (prenatal + 1st year) >40 TBytes/s or 1,000,000 Ultra Wide SCSIs
Power consumption (adult) 90-100 Watts (2,000 kilocalories/day) 1.6 pW/cell

We can think about the human body as a self-organized collective of clones of a single fertilized egg cell. Each cell of the human body is an elaborate bio-chemical computer. It has its own power management and information processing structures. It communicates with its neighbors and the environment. Each cell is an individual organism. Under certain conditions it may live outside of the collective. Most cells have a complete copy of the genetic information and theoretically are capable of recreating the whole human body.

The magnitude of information processing activity inside the human body is amazing. The cell reproduction processes require terabytes of chromosome DNA information to be copied every second within the body. Besides, the protein formation and other functions in cells can be several orders of magnitude more information-intensive.

Power consumption of a single cell corresponds to about 107 chemical reactions per second.

Human Brain

Number of neurons (adult)* 20,000,000,000 – 50,000,000,000
Number of neurons in cerebral cortex (adult)* about 20,000,000,000 (some sources have incorrect number 8,000,000)
Number of synapses (adult) 1014 (2,000-5,000 per neuron)
Weight Birth 0.3 kg, 1 y/o 1 kg, puberty 1.3 kg, adult 1.5 kg
Power consumption (adult) 20-40 Watts (0.5-4 nW/neuron)
Percentage of body 2% weight, 0.04-0.07% cells, 20-44% power consumption
Genetic code influence 1 bit per 10,000-1,000,000 synapses
Atrophy/death of neurons 50,000 per day (between ages 20 and 75)
Sleep requirement (adult) average 7.5 hours/day or 31%
Normal operating temperature 37±2°C
Maximum firing frequency of neuron 250-2,000 Hz (0.5-4 ms intervals)
Signal propagation speed inside axon 90 m/s sheathed, <0.1 m/s unsheathed
Processing of complex stimuli 0.5s or 100-1,000  firings

*The main source of these numbers is the article [1] by Pakkenberg & Gundersen. The authors estimate that an average human brain has 21.5 billion neocortical neurons with a 95% tolerance limit of + or -38%. They have a more precise estimate with sex, age, neocortical surface and volume taken into account. According to other sources there are more neocortical neurons than other neurons in the human brain. That gives us a very rough top estimate of 40-50 billion. Unfortunately, I could not find a more accurate and believable estimate of the total number of neurons. 100 billion is a nice round number used in most sources…

The brain consists of interconnected neurons which exchange signals with each other and with the rest of the body cells. There are at least three different signaling mechanisms. Two of the mechanisms are based on ion-flow (electronic) pulses sent along axons. Those signals can either be received directly as ion current arriving to a receiving neuron’s dendrite or through a more complicated neurotransmitter mechanism. Some neurons can also produce or receive special chemical tags transported though the blood flow.

The total information processing activity of the brain is hard to estimate because the current knowledge in this area is fragmentary. However, it is possible to get a general picture of the electronic pulse exchange activity within a couple of orders of magnitude. The activity of the brain is equivalent to that of 1000 kHz processor with 40 Gbits of states. The corresponding processing power (channel capacity) is C=4*1013 bit/s. The minimum necessary power to perform the computations is P=C k T log e, where k is Boltzmann constant and T is the temperature (310 K). So P=1.2*10-7 W. If we assume that brain only needs the energy to perform the computations, the efficiency is about 10-8 of the physical limit.

The neurons require several orders of magnitude more power than the other cells. Therefore, we can assume that most of the power goes to the information processing activity. 0.4-4 nW corresponds to roughly 1010 chemical reactions per second or to at least 107 chemical reactions per firing.

Neuron2.gif (11006 bytes)Neuron.gif (5510 bytes)

Fig.1 Human cortical neuron

An electronic equivalent of the cortical neuron would have 2,500+ pins. The dendrite inputs are connected to axon inputs of other neurons. All pins must be able to change their length and move around. The behavior of the neuron itself is more complicated than sending an axon pulse after receiving signal at a dendrite.

Intel Pentium 4 1.5GHz

Number of transistors 4.2*107
Power consumption up to 55 Watts
Weight 0.1 kg cartridge w/o fans, 0.3 kg with fan/heatsink
Maximum firing frequency 1.5 GHz
Normal operating temperature 15-85°C
Sleep requirement 0 (if not overheated/overclocked)
Processing of complex stimuli if can be done, takes a long time

The power consumption of the Pentium 4 may exceed that of the human brain. That explains why Pentium cooling systems are getting close in size to the human head.

The number of transistors in 500 Pentiums is roughly the same as the number of neurons in cerebral cortex. The firing frequency is 1,000,000 times higher in the Pentium. Transistors are less sophisticated than neurons. For example, transistors cannot move and change connections.


  1. Neocortical neuron number in humans: Effect of sex and age / B. Pakkenberg, H. Gundersen 1997
  2. An introduction to genetic analysis. / Anthony Griffiths [et al.] 1993
  3. Molecular evolutionary genetics. / Masatoshi Nei 1987
  4. Role of excessive genetic information in evolution. / Vadim Gerasimov 1995
  5. Wisconsin’s Biotechnology and Food Handbook / Tom Zinnen and Jane Voichick
  6. Human Molecular Genetics / Weber, W. and Wong, C. 1993
  7. Molecular Evolution: Computer Analysis of Protein and Nucleic Acid Sequences. / R. F. Doolittle 1990
  8. Controlling Computers with Neural Signals/ Hugh S. Lusted and R. Benjamin Knapp, Scientific American October 1996
  9. Signal entropy and the thermodynamics of computation / Neil Gershenfeld 1996
  10. Encyclopedia Britannica –
  11. Various WWW sources…
  12. Generalized electromechanical modeling of bioenergetic systems. / S.V.Gandilyan [et al.] 1997
  13. Efficiency function of human and monkey brain applicable to robotic pattern recognition. / Z. Shen, J. Hua 1997
  14. Orchestrated reduction of quantum coherence in brain microtubules: a model for consciousness. / S. Hameroff, R. Penrose 1997
  15. Intelligent machines. / Hans P. Moravec 1977
  16. The mind and the brain. / Jeffrey M. Schwartz 2002
  17. Neuroscience: exploring the brain. / Mark F Bear, Barry Connors, and Michael Paradiso 2006

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