PSYCH 112 Chapter 4: Chapter 4 Malley Text Notes

145 views2 pages
21 Oct 2015
School
Department
Course
Professor
Chapter 4 Malley Text Notes
- Fetal-Alcohol-Syndrome shows us that simply having neurons present does not make a
brain functional: the neurons must be properly arranged
- Claude Shannon proposed a theory of analyzing electrical circuits using formal logic
oWire with current was considered a true proposition
oWire without a current was considered a false proposition
oIf either of the wires were active, corresponds to the logical connective “or”, and
if both wires were active, corresponds to the logical connective “and”
oImplied that electrical engineers could design circuits more simply using logical
reasoning
- McCulloch and Pitts further elaborated on Shannon’s work
oShowed that simple neural activity could implement a kind of logical reasoning
using the “and,” “or,” and “not” functions
Based on the idea of the all-or-none principle
- Parallel distributed processing
oOpposite from serial processing, which occurs in a computer processor, for
example, and which processes calculations one at a time
oComputational processes are distributed across the neural network and executed
simultaneously
oThe network as a whole carries out a variety of operations
oAdvantages
With many processes happening at the same time, the brain can make
calculations quickly
Computers are better at math problems than humans because they math
requires a serial fashion to execute calculations
Humans are good at doing many calculations at once (all the calculations
it takes to catch a fly ball)
- Graceful degradation is the resilience of parallel distributed processing in the face of
damage
oNeurons are susceptible to a failure to respond, injury/death, and occasional
random firing
Because processes are spread out, one failure is not catastrophic
Serial processes tend to be brittle
- Computers only know what they are told
oInput of the desired information
oInput of a formula to compute the information
- Humans can learn like computers, but we usually learn by generalizing about examples
oBeing shown what an “orange” is, we can identify other oranges without being
explicitly told what it is
oChildren and humans intuitively generalize
- Artificial neural networks, like the brain, can learn from examples and adjust their
connection weights:
Unlock document

This preview shows half of the first page of the document.
Unlock all 2 pages and 3 million more documents.

Already have an account? Log in

Get OneClass Notes+

Unlimited access to class notes and textbook notes.

YearlyBest Value
75% OFF
$8 USD/m
Monthly
$30 USD/m
You will be charged $96 USD upfront and auto renewed at the end of each cycle. You may cancel anytime under Payment Settings. For more information, see our Terms and Privacy.
Payments are encrypted using 256-bit SSL. Powered by Stripe.