Transcript measuring behavior – variation

#02: BEHAVIORAL ANALYSIS
 chapter 1:
neurons as the building blocks of behavior
 measuring behavior
 in a natural setting
 in a laboratory setting
LABORATORY SETTING
 Pavlov & Thorndike
LABORATORY SETTING
 Pavlov: classical or Pavlovian conditioning, dogs
 stimulus “value” changes when paired with another
 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 =
p.10 fig.1.4
conditioned response (CR)
 learn temporal relationships
 value of CS changes, predicts occurrence of US
LABORATORY SETTING
 Thorndike: instrumental or operant conditioning
 hungry cats, puzzle boxes
 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
LABORATORY SETTING
 learning is usually a combination of classical & operant
 in classical, animals receive...
 measured stimulus, controlled by experimenter
 in operant, animals receive...
 stimulus determined by time to elicit behavior
 in both, animals learn...
 existence of stimuli
 temporal relationships among stimuli
 in operant only, animals learn...
 relationships between stimuli & their own behavior
LABORATORY SETTING
 what do animals associate in associative learning ?
 rats, radial arm maze (B)
 left & right choices
 paired light & dark stimuli (A)
 train: food reward for turning
 right if top lighter
 left if top darker
 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
LABORATORY SETTING
 other tests using the radial arm maze
 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
p.12 fig.1.5
LABORATORY SETTING
development  physiology  behavior
Neurobiology
STRUCTURE ...
... FUNCTION
MEASURING BEHAVIOR – VARIATION
 components of phenotypes
E1
G1
G2
E2
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 + ... ?
MEASURING BEHAVIOR – VARIATION
PHENOTYPE
G
G+E
G
1
EE1
E2
E1
G*E
E2
E1
E2
E1
E2
ENVIRONMENT
G
2
MEASURING BEHAVIOR – VARIATION
 components of phenotypes (e.g., behavior)
 P = G + E + G*E
 genotype (heredity)
 environment (experience)
 interaction
 where does E come from ?
INFORMATION FLOW
ENVIRONMENT
GENES
MESSAGES
PEPTIDES
PROTEINS
PROTEIN COMPLEXES
ORGANELLES
NEURONS
ASSEMBLIES
STRUCTURES
CIRCUITS
NERVOUS SYSTEM
WHOLE ANIMAL
BEHAVIOR
PLASTICITY
EXPERIENCE
ENVIRONMENT
vertical
integration
MEASURING BEHAVIOR – VARIATION
 components of phenotypes (e.g., behavior)
 P = G + E + G*E
 genotype (heredity)
 environment (experience)
 interaction
 where does E come from ?
 what aspects of E would you try to control
in your behavior experiment ?
 what would you need to include ?
MEASURING BEHAVIOR – VARIATION
 components of phenotypes (e.g., behavior)
 P = G + E + G*E
 genotype (heredity)
 environment (experience)
 interaction
 where does E come from ?
 where does G come from ?
INFORMATION FLOW
GENES
MESSAGES
PEPTIDES
PROTEINS
PROTEIN COMPLEXES
ORGANELLES
NEURONS
ASSEMBLIES
STRUCTURES
CIRCUITS
NERVOUS SYSTEM
WHOLE ANIMAL
BEHAVIOR
PLASTICITY
EXPERIENCE
ENVIRONMENT
vertical
integration
INFORMATION FLOW
GENES
MESSAGES
PEPTIDES
PROTEINS
PROTEIN COMPLEXES
ORGANELLES
NEURONS
ASSEMBLIES
STRUCTURES
CIRCUITS
NERVOUS SYSTEM
WHOLE ANIMAL
BEHAVIOR
PLASTICITY
EXPERIENCE
ENVIRONMENT
vertical
integration
SOURCES OF GENETIC VARIATION
 how to identify natural sources:
 gene # / influence from F2 phenotype ratios
GENETIC  PHENOTYPIC VARIATION
1
FREQUENCY
1 gene
1 allele
( = 0)
0
PHENOTYPE
GENETIC  PHENOTYPIC VARIATION
FREQUENCY
0.5
1 gene
2 alleles
no dominance
0.4
0.3
0.2
0.1
0.0
PHENOTYPE
GENETIC  PHENOTYPIC VARIATION
FREQUENCY
0.4
2 additive genes
2 alleles each
no dominance
0.3
0.2
0.1
0.0
PHENOTYPE
GENETIC  PHENOTYPIC VARIATION
0.35
3 genes
3 additive genes
2 alleles each
no dominance
FREQUENCY
0.30
0.25
0.20
1
4n
0.15
0.10
0.05
1
64
0.00
PHENOTYPE
SOURCES OF GENETIC VARIATION
 how to identify natural sources:
 gene # / influence from F2 phenotype ratios
 artificial selection
GENETIC  PHENOTYPIC VARIATION
0.35
n additive genes
2 alleles each
no dominance
FREQUENCY
0.30
0.25
0.20
0.15
0.10
0.05
0.00
PHENOTYPE
MEASURING BEHAVIOR – ARTIFICIAL SELECTION
0.35
FREQUENCY
0.30
0.25
0.20
0.15
0.10
0.05
0.00
 x
 x
PHENOTYPE
ARTIFICIAL SELECTION – LEARNING IN FLIES
ARTIFICIAL SELECTION – LEARNING IN FLIES
fixed
not
relax
selection
10
15
SOURCES OF GENETIC VARIATION
 how to identify natural sources:
 gene # / influence from F2 phenotype ratios
 artificial selection
 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
SOURCES OF GENETIC VARIATION
 natural sources of genetic variation:
+ : the genes evolution “designed” to control of behavior
− : lots of effort, little gain toward understanding mechanism
 induced sources of genetic variation:
+ : rapid gain toward understanding mechanism
− : may find a subset of the genes evolution “designed” to
control behavior
1 GENE
POLYGENY
PLEIOTROPY
LABORATORY SETTING
development  physiology  behavior
Neurobiology
STRUCTURE ...
... FUNCTION
A GOOD BEHAVIOR MODEL ORGANISM ?
 behavior
 significance
 interesting
 invariant
 convenience
 cost
 sample size
 maintenance
 disease
 homology ?
 research tools
 genetics / genomics
 molecular biology
 cell biology
 pharmacology
 physiology
 anatomy
 ethical issues
 organisms
 research questions