Understanding Human Cognition through Experimental and Computational Methods

Jay McClellandSymbolic Systems 100

Spring, 2011

Early History of the Study of Human Mental Processes

• Introspectionism (Wundt, Titchener)– Thought as conscious content, but two problems:

• Suggestibility• Gaps

• Freud suggests that mental processes are not all conscious

• Behaviorists (Watson, Skinner) eschew talk of mental processes altogether

Can Experiments Teach Us About the Contents of the Mind?

• Conrad: Verbal coding in short-term memory

• Sachs: Representation of meaning in long-term memory

Conrad’s Experiment

• You will see a series of letters.

• Try to remember them so that, when you see the word recall, you can write them down in the correct order.

• There will be six letters, followed by a brief delay, then the word ‘Recall’ will appear.

• After you see the word recall, write down the letters in order, starting with the first letter and then proceeding through the list.

.

B

M

S

F

X

T

V

N

.

.

.

Recall

B M S F X T V N

Sachs’ Experiment

• Participants heard a story containing a sentence such as:– He sent Galileo, the great Italian Scientist, a letter about it.

• Either immediately, or after reading a few more sentences, the participants were asked which of the following sentences they had heard:– He sent Galileo, the great Italian Scientist, a letter about it.– He sent a letter about it to Galileo, the great Italian Scientist.– Galileo, the great Italian Scientist, sent him a letter about it.

• When tested immediately, nearly all participants chose the correct sentence.

• After a delay, many participants chose the second sentence, but no one chose the third.

A Question:

• What sort of a mechanism should we use to capture the processes that underlie human thought?– A mechanism like the brain?– Or a mechanism like a computer?

The McCulloch-Pitts Neuron

Neuron i

Output fromneuron j

wij

Input

ThresholdOut

put

McCulloch-Pitts neurons can be used to compute logical functions,such as A-AND-B, A-OR-B, A-AND-NOT-B, etc

0

1

The Perceptron

1 if ; else 0i ii

w

; i iw

Problems for the Perceptron

• Depends crucially on the φi

• Some functions require an exponential number of φi

• No one figured out how to train the weights coming in to the φi

– all the possible φi that might ever be needed had to be provided in advance

The Rise of Symbolic Computation

• Mathematics and logic grew up around the use of symbols:– Marks on paper that stand for things.

• Computer programs that do math and logic make use of symbols too.

• Rules of mathematics and logic can be expressed in terms of statements about symbols.– ‘If p then q’ and ‘p’ implies ‘q’

• So symbolic models seemed like they might be effective ways of using computers to model human reasoning.

But AI Didn’t Live Up to It’s Promise Either

• Computers could do math and logic, but they couldn’t:– Recognize objects– Recognize speech– Understand sentences– Retrieve relevant information from memory

• Was there something wrong with the specific models or languages people were using or was there something wrong with the whole approach?

Ubiquity of the Constraint SatisfactionProblem

• In sentence processing– I saw the grand canyon flying to New York– I saw the sheep grazing in the field

• In comprehension– Margie was sitting on the front steps when she heard the

familiar jingle of the “Good Humor” truck. She remembered her birthday money and ran into the house.

• In reaching, grasping, typing…

Graded and variable nature of neuronal responses

Lateral Inhibition in Eye of Limulus

(Horseshoe Crab)

Neural Network Models of Cognition: The Interactive

Activation Model

Newer Directions

• Cognitive Neuroscience:– Using measurements of human brain activity to learn more

about mental processing

• Reasoning with uncertain information:– Probabilistic models of cognition

• Cognition as an embodied process, tied to experience and action.