Cognitive Psychology Part 2: (Behavioral) Learning

I. Learning -- Classical Conditioning II. Neural Basis of Classical Conditioning

I. Learning -- Classical Conditioning

1. What is learning?

2. Classical Conditioning

1. What is learning?

Learning is a permanent change in the nervous system of an organism that changes the way it responds to its environment, usually as a result of an experience that the organism went through.

(Note: By learning here we do not mean the acquisition of knowledge like in school but the acquisition of behavioral and emotional responses.)

1. Learning is a memory phenomenon. Without memory, no learning can occur.

2. Learning must be associative in nature. That is, learning occurs when an association is formed between two stimuli or between a stimulus and a response.

Associative Learning

Associative Learning via Bi-directional Projections from/to Hippocampus

2. Classical Conditioning

A type of learning in which an artificial stimulus evokes a response that was originally associated with a natural stimulus (Ivan Pavlov, 1900?).

(e.g.) A hungry dog

1. Before learning

Food -----> Salivation (natural stimulus) (response)

That is,

Unconditioned Stimulus ------> Unconditioned Response (UCS) (UCR)

(‘Unconditioned’ means automatic or without-learning.)

2. During training

Food with bell -----> Salivation (natural stimulus with (response)

artificial stimulus)

UCS + CS ------> UCR

Note that the Salivation (UCR) is evoked by food (UCS), not by the bell (CS).

3. After learning

Bell -----> Salivation (artificial stimulus only) (response)

CS ------> CR (not UCR)

An association that has been formed between the CS (bell) and UCR (salivation) during training evokes the same salivation response (now termed as CR), without the participation of the UCS (food) .

What association and how?

Everyday Examples of Classical Conditioning

1. Advertising

During training Man in cowboy hat (UCS) and cigarette (CS) -------> Favorable feeling (UCR)

After training Cigarette (CS) in supermarket ------> ???

(also, woman in bikini + beer; wealthy looking business man + car, etc.)

2. Emotion

Robbery at gun point (UCS) in dark alley (CS) ----> Frightening experience (UCR)

Dark alley (CS) ------> Get frightened (CR)

Also, Demanding ill-tempered supervisor with red mustache ----> bad experience and eventually got fired

3. Physiological response

Harmless Turkish food (CS) contaminated with a poisonous chemical of unknown origin (UCS)

----> Severe stomach ache (UCR)

Turkish food (CS) ------> Stomach ache (CR)

Un-awared self-curing capacity (or simply disease gone through its course of action) + tooth paste

---> disease cured (“placebo effects”)

Instead of tooth paste, how about simple meditation, bible reading or even reciting of incomprehensible code words?

II. Neural Basis of Classical Conditioning

All that is needed to explain the classical conditioning phenomenon is the associative Hebbian learning rule.

1. Before learning

Wucs >> 0; Wcs = 0,

UCS alone evokes the salivation (UCR)

2. During training

UCS CS R (present) (present) (present)

Hebbian learning then implies that

Wcs > 0

on every training trial.

3. After learning

At the end of training,

Wcs >> 0 (sufficiently large)

which means that

CS alone can now evoke the salivation (CR)!

Neurophysiology of Conditioning

More sophisticated models of conditioning

Discussion of the Paper “Is the Brain a Digital Computer” by J. Searl

Cognitivism as DCTM (Digital Computational Theory of Mind)(excepts from R M Harnish (2002, chap. 8)

Point #1 (Cognition as Symbol Manipulation): Cognition, in essence, is digital computation that involves manipulating

(creating, transforming and deleting) symbols which we call mental representations of the world around us.

Point #2 (Symbol Manipulation Defines Computation):According to Turing, computation is defined syntactically in terms of symbol

manipulation.

Point #3 (Brain as a UTM)Cognition, or thinking for that matter, really is a species of digital computation,

then the Church-Turing thesis tells us that these can be carried out by Turing machines or just one Universal Turing machine. In other words, the brain is somewhat equivalent to a Universal Turing machine, say a von Neumann machine or a production system or the like.

Point #4 (Cognitivist Scientific Research Paradigm):So, the reasoning goes, therefore, the job of cognitive science, neuroscience,

and artificial intelligence is to discover the actual algorithms of the mind.

Q1: Is this a Strong or Weak AI view?

Q2: Do you think Searl endorses the DCTM?

Q3: What’s Searl answer to the question “Is the brain a digital computer?” What are the arguments he puts forward to defend his position?

- Chinese Room Argument (NP-hard problem??)

- Syntax is not the same as semantics;

Semantics is not intrinsic to syntax

- Homunculus fallacy

Q4???