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#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