Computing Architectures The human brain as computing system Based on presentation from and

transcript

Computing Architectures

The human brain

as computing system

Based on presentation from http://www.stanford.edu/class/symbsys100/ andhttp://www.willamette.edu/~gorr/classes/cs449/brain.html

From symbols to meatMeet the brainBrains vs. digital computersBio-inspired computers

Reasoning module: concluding discussion

Human cognition is based on a very specific computing system, with specific limits, inherent trade-offs, etc. that are not necessarily the same as for digital computers

It is therefore worth looking at the "mind's implementation" in order to learn more about the limits of our mind/cognition

From symbols to meatMeet the brainBrains vs. digital computersBio-inspired computersReasoning module: concluding

discussion

The brain – just 2 pounds of meat?

The cortex1.3-1.4kg (2% of the body weight) … [13,14]2,500 cm2 (rat: 6 cm2, elephant: 6,300 cm2) [14]1,300-1,500 cm3

2 hemispheres connected by corpus callossum (250 mill. nerve fibers)

Inputs: spinal cordoptic nerve (1.2 mill.)cranial nerves (12)auditory system, …

The lobes

4 lobes: occipital, parietal, temporal, frontalOccipital: visionParietal: touch, pressure, temperature, painTemporal: auditory information, long term

memoryFrontal: short term memory, planning,

emotion, movement…Biggest difference from our closest evolutionary

ancestors

Taken fromhttp://www.sciencebob.com/lab/bodyzone/brain.html

Neurons [14]

100 billion neurons (children)300 million – octapus; 18,000 – sea slug Aplysia; 350 - leech

Diameter: 4 – 100 microns Weight: 10-6 grams Length: <1 mm – 4 feet (in the leg) [15]

Length of Giraffe primary afferent axon: 15 feet

Loss of neurons: ~1/sec 31 million/year an octapus/10 years

~5,400 at the end of this lecture (sorry!)

How do we know?

Non-invasive (1mm3 ~ 6-7*104 neurons)EEG (Electroencephalogram), ERP (Early receptor potential)fMRI (blood flow; ~1mm; secs-mins)MEG (Magnetoencephalogram with ERP: ~1.5mm; msecs-secs)PET (imaging technique blood flow; 1mm; >mins)

Invasive methods: electrodes (1 neuron; msecs)Lesions

Permanent: injury, diseaseTemporary: specific drugs, TMS (<1mm; <secs)

All methods have trade-offs (spatial, temporal resolution)

The brain as a computational system

The brain isbiologicalde-central (plasticity)non-digitalhighly parallel

What does this mean?

The brain: a biological CS

not manufactured from scratch with a certain intention in mind, but subject to evolution

Co-adaptation; its parts must have been of use

Not made out of copper or light-conduction cables .... slowSignal speed: MAX=120m/s, AV.=6.5m/sec

(1.2 - 250mph) [14]Signal frequency: up to 1000Hz (activ./sec)

Non-digital

At least to some degree, the brain is non-digitalOn the lowest level (i.e. within the neuron):

quasi-digitalthis creates an analog signal travelling

along the neuronat the synapses this is converted into a

chemical signal, which in turn triggers an elecrical signal.

The brain: a highly parallel CSSome neurons have up to 150,000 connections

(others as low as 2) average: 1,000-10,000 [14]

different brain regions are highly interconnected

human can manage many tasks at the same time (sitting, listening to the lecture, doodling)

however, there are also parts of the brain which are involved in a lot of tasks "narrow passages" for computation

Storage capacity of the brain - I

100 billion neurons1011! hypothetically possible connectionsupto 150,000 connections between each

neuron (180,000km of myelinated nerves)during the first year of life, the child

generates ~ 15,000 connections for each neuron (during growth: 250,000 per minute!)

“… this program will support more than 130,000 [i.e. 1.3 * 105] neural connections…”

Storage capacity of the brain - II

# bits = # of neurons * # of connections1 * 1011 * 1.5 * 105 = 1.5 * 1016 bits

The entire Enc. Britannica contains 109 bits of information (Turing 1950)

In 1987, Hideaki Tomoyori memorized the first 40,000 digits of π

Information processing speed of the Brain

# bits/sec = # ops/sec* # bits/op10 ops/sec per synapse (connection) [3,4]~1.5 * 1017 bits/sec information transfer

Estimates of the brain's computing power range from 1011 to 1020 bits/secConverging evidence for ~ 1015 [2,3,5,9,14]~100 teraflops (8 bit words); ~ 8 teraflops

(128 bits words)

Brain vs. digital Computers

Fastest computer atm:40 terra flops (5,000 processors; NEC)

Planned360 terra flops (130,000 processors; IBM)

~ 3-4 times faster than the human brain (8 bit words); 40 times faster otherwise.

Bio-inspired models of computation

This gives us a motivation to investigate bio-inspired models of computationLearn about the brain by modeling itTake advantage of billions of years of

evolutionary designDevelop robust computational systems

Neural networks

So what?

“It is true that a discrete-state machine must be different from a continuous machine. But if we adhere to the conditions of the imitation game, the interrogator will not be able to take any advantage of this difference.” Turing (1950:451)

References1. Gazzaniga, Ivry & Mangun (1998): Cognitive Neuroscience. The Biology of the

Mind. Norton.2. Merkle, Ralph C. (1988): How many bytes in human memory? at

http://www.merkle.com/humanMemory.html3. Merkle, Ralph C. (1989): Energy Limits to the Computational Power of the

Human Brain; at http://www.merkle.com/brainLimits.html 4. Principles of Neural Science, by Eric R. Kandel and James H. Schwartz, 2nd

edition, Elsevier, 19855. http://www.coping.org/earlyin/ruleout/reason.htm6. http://www.jsmf.org/zarticles&pap/John/neural_connections.htm7. http://ifcsun1.ifisiol.unam.mx/Brain/neuron.htm 8. http://ifcsun1.ifisiol.unam.mx/Brain/neuron2.htm 9. http://www.rfreitas.com/Nano/DeusExDigita.htm 10. http://www.cheshireeng.com/Neuralyst/nrlnds.htm 11. http://www.top500.org/ 12. http://www.consciousness.arizona.edu/hameroff/ 13. http://www.neurologicalalliance.org.uk/pages/network/answers.asp 14. http://faculty.washington.edu/chudler/facts.html15. http://www.uncc.edu/sspauldi/LECNote/ch02.html

Computing Architectures The human brain as computing system Based on presentation from and

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