h h chapter 1: neurons as the building blocks of behavior h h measuring behavior h h in a natural...

chapter 1: neurons as the building blocks of behavior

measuring behavior

in a natural setting

in a laboratory setting

chapter 1: neurons as the building blocks of behavior

measuring behavior

in a natural setting

in a laboratory setting

#02: BEHAVIORAL ANALYSIS

Pavlov & Thorndike

LABORATORY SETTING

learn temporal relationships value of CS changes, predicts occurrence of US

p.10 fig.1.4

food = unconditioned stimulus (US)... salivation = unconditioned response (UR) to US bell = conditioned stimulus (CS)... CS (naïve) 0 response CS + US pairing = training CS (trained) salivation = conditioned response (CR)

Pavlov: classical or Pavlovian conditioning, dogs stimulus “value” changes when paired with another

LABORATORY SETTING

cat associates own escape behavior with box features food in view outside box (motivation) levels of difficulty (e.g., pull string to excape) record time for escape

p.10 fig.1.4

Thorndike: instrumental or operant conditioning hungry cats, puzzle boxes

LABORATORY SETTING

in both, animals learn... existence of stimuli temporal relationships among stimuli

in operant only, animals learn... relationships between stimuli & their own behavior

in classical, animals receive... measured stimulus, controlled by experimenter

in operant, animals receive... stimulus determined by time to elicit behavior

learning is usually a combination of classical & operant

LABORATORY SETTING

test: previously unseen pairs able to transfer the “rule” to new situations did not simply learn pattern of cards learned that relationship between stimuli is critial

p.12 fig.1.5

train: food reward for turning right if top lighter left if top darker

what do animals associate in associative learning ? rats, radial arm maze (B)

left & right choices paired light & dark stimuli (A)

LABORATORY SETTING

other tests using the radial arm maze

p.12 fig.1.5

trained to retrieve food from each arm, no revisits remember which arms visited within each trial no need to remember info from trial to trial uses working memory

trained with food in some arms memory from trial to trial uses reference memory

LABORATORY SETTING

development physiology behavior

STRUCTURE ... ... FUNCTION

Neurobiology

LABORATORY SETTING

E1 E2

G1

G2

components of phenotypes

MEASURING BEHAVIOR – VARIATION

components of phenotypes (e.g., behavior)

P = G + E + G*E genotype (heredity) environment (experience) interaction

... for our purposes this could be ...

behavior = instinct + learning + ... ?


G1

G2

PHENOTYPE

G

ENVIRONMENT

E1

E2

E1

E2

G+E

E

E1

E2

E1

E2

G*E




where does E come from ?


GENESMESSAGESPEPTIDESPROTEINS

PROTEIN COMPLEXESORGANELLES

NEURONSASSEMBLIESSTRUCTURES

CIRCUITSNERVOUS SYSTEM

WHOLE ANIMALBEHAVIOR

EXPERIENCE

ENVIRONMENT

PLASTICITY

verticalintegration

INFORMATION FLOW

EN

VIR

ON

ME

NT



where does E come from ? what aspects of E would you try to control

in your behavior experiment ? what would you need to include ?




where does E come from ?

where does G come from ?


GENESMESSAGESPEPTIDESPROTEINS

PROTEIN COMPLEXESORGANELLES

NEURONSASSEMBLIESSTRUCTURES

CIRCUITSNERVOUS SYSTEM

WHOLE ANIMALBEHAVIOR

EXPERIENCE

ENVIRONMENT

PLASTICITY

verticalintegration

INFORMATION FLOW

how to identify natural sources: gene # / influence from F2 phenotype ratios

SOURCES OF GENETIC VARIATION

0

1

FREQUENCY

PHENOTYPE

1 gene1 allele( = 0)

GENETIC PHENOTYPIC VARIATION

0.0

0.1

0.2

0.3

0.4

0.5

FREQUENCY

PHENOTYPE

1 gene2 allelesno dominance


0.0

0.1

0.2

0.3

0.4

FREQUENCY

PHENOTYPE


2 additive genes2 alleles eachno dominance

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

FREQUENCY

PHENOTYPE

164

3 genes

14n


3 additive genes2 alleles eachno dominance


artificial selection


0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

FREQUENCY

PHENOTYPE


n additive genes2 alleles eachno dominance

xx0.05

0.10

0.15

0.20

0.25

0.30

0.35

FREQUENCY

0.00

PHENOTYPE

MEASURING BEHAVIOR – ARTIFICIAL SELECTION

ARTIFICIAL SELECTION – LEARNING IN FLIES

relaxselection

10 15

fixed

not

ARTIFICIAL SELECTION – LEARNING IN FLIES

speed things up with induced sources: chemical mutagens – “point” mutations ionizing radiation – chromosome rearrangements transposon insertions – disrupt gene activity transgene expression – block / add / change gene function

– qualitative / quantitative – spatial / temporal control


artificial selection


induced sources of genetic variation:+ : rapid gain toward understanding mechanism− : may find a subset of the genes evolution “designed” to

control behavior

natural sources of genetic variation: + : the genes evolution “designed” to control of behavior− : lots of effort, little gain toward understanding mechanism


1 GENE

POLYGENY

PLEIOTROPY

development physiology behavior

STRUCTURE ... ... FUNCTION

Neurobiology

LABORATORY SETTING

behavior significance interesting invariant

convenience cost sample size maintenance disease

research tools genetics / genomics molecular biology cell biology pharmacology physiology anatomy

ethical issues organisms research questions homology ?

A GOOD BEHAVIOR MODEL ORGANISM ?

h h chapter 1: neurons as the building blocks of behavior h h measuring behavior h h in a natural...

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