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Temporal learning in animals: Empirical tests of two mathematical models of timing * Armando Machado University of Minho, Portugal Université Charles-de-Gaulle,

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Presentation on theme: "Temporal learning in animals: Empirical tests of two mathematical models of timing * Armando Machado University of Minho, Portugal Université Charles-de-Gaulle,"— Presentation transcript:

1 Temporal learning in animals: Empirical tests of two mathematical models of timing * Armando Machado University of Minho, Portugal Université Charles-de-Gaulle, Lille 3

2 The Skinner box The microscope of learning psychologist

3 Two models of timing Scalar Expectancy Theory (SET) Learning to Time (LeT) Critical tests: SET vs LeT Temporal Bisection Double Bisection Successes and Failures: what have we learned? The role of context Errorless learning and mediating behavior

4 The pigeon’s sense of time

5 The scalar property

6 Retrospective Timing The Bisection Experiment Red

7 Retrospective Timing The Bisection Experiment Green

8 Retrospective Timing The Bisection Experiment TRAININGTESTING

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10 Scalar Expectancy Theory (SET)

11 SET and temporal bisection

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14 Learning to Time (LeT) Behavioral States X(t,n) Response Strengths R(t), G(t) Signal Associative Connections W n

15 Behavioral States Deterministic interpretation Stochastic interpretation

16 Behavioral States 0 1 2

17 Associative Connections

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19 Response Strength

20 Learning to Time (LeT)

21 LeT and temporal bisection

22 For the bisection task, SET and LeT make similar predictions. We need a new procedure to contrast the two models The Double Bisection task

23 Double Bisection Experiment 1

24 SET LeT 1 s  Red 4 s  Green 4 s  Blue 16 s  Violet

25 Predictions A context effect? 1 s  Red 4 s  Green 4 s  Blue 16 s  Violet

26 Data Yes, a context effect! 1 s  Red 4 s  Green 4 s  Blue 16 s  Violet

27 Double Bisection Experiment 2 Group 8 1 s  Red 4 s  Green 4 s  Blue 8 s  Violet 1 s  Red 4 s  Green 4 s  Blue 16 s  Violet Group 16

28 Double Bisection Experiment 2 SETLeT Group 8: 1-4 and 4-8 Group 16: 1-4 and 4-16

29 SET vs LeT vs Data Group 8Group 16

30 LeT: Predictions vs Data

31 Double Bisection Experiment 3 1 s  Red 4 s  Green 4 s  Blue 16 s  Violet 1 s  Green 16 s  Blue 1 s  Blue 16 s  Green Group “Consistent” Group “Inconsistent” How fast will the new discrimination be learned?

32 LeT: Predictions vs data Group “Consistent” 1 s  Red 4 s  Green 4 s  Blue 16 s  Violet 1 s  Blue 16 s  Green

33 LeT: Predictions vs data Group “Inconsistent” 1 s  Red 4 s  Green 4 s  Blue 16 s  Violet 1 s  Green 16 s  Blue

34 Double Bisection Experiment 3 1 s  Red 4 s  Green 4 s  Blue 16 s  Violet 1 s  Green 16 s  Blue 1 s  Blue 16 s  Green 1 s  Red 4 s  Green 4 s  Blue 16 s  Violet Group “Consistent” Group “Inconsistent” Which discrimination(s) will be disrupted?

35 LeT: Predictions vs data Group “Consistent” 1 s  Red 4 s  Green 4 s  Blue 16 s  Violet 1 s  Blue 16 s  Green

36 LeT: Predictions vs data Group “Inconsistent” 1 s  Red 4 s  Green 4 s  Blue 16 s  Violet 1 s  Green 16 s  Blue

37 Conclusions SET and its memories –Failure of independence from alternatives LeT and the role of context –Which key to peck after a signal –Which key not to peck after a signal

38 Current work LeT and the role of context –Errorless (temporal) learning? Behavioral patterns –Structuring and restructuring of patterns during the time signal. –Some videos of mediational(?), collateral(?) behavior.

39 Behavioral patterns P689 –1s: approaching keys –4s R-G and 4s B-Y: pecking –16 s: approaching keys, pecking, pausing, pecking P65 –16sf: pecking and wing flapping; –16s: pecking and wing flapping  ERROR; –38: pecking and wing flapping; P68 –34 & 54: wall pecking and head-in-the-feeder

40 Collaborators Paulo Rodrigues Marco Vasconcelos Paulo Pata Joana Arantes Antonio Fidalgo Ana Paula Leite Paula Magalhães Richard Keen Ozlem Cevik Paulo Guilhardi

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42 The full picture 1 s  Red 4 s  Green 4 s  Blue 16 s  Violet


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