1. Neuroscience & Behavior Program Robert J. Polewan & John W. Moore* University of Massachusetts Amherst COMPOUND CONDITIONING UNDER TEMPORAL UNCERTAINTY

2. 2 Neuroscience & Behavior Program Compound Conditioning Under Temporal Uncertainty  Eyeblink conditioning has long been a model for understanding behavioral and physiological processes of learning, memory, and performance.  The present research extends our previous studies of rabbit eyeblink conditioning under temporal uncertainty to compound conditioning.

3. 3 Neuroscience & Behavior Program Temporal Uncertainty Training  Rabbits were trained to make eyeblink conditioned responses (CRs) to a compound conditioned stimulus (CS) consisting of a tone (T) and a light (L) presented simultaneously an reinforced with an unconditioned stimulus (US).  This training involved a mixture of two CS-US intervals. On some trials, the US occurred 300 ms after CS onset; on other trials, the US occurred 700 ms after CS onset.

4. 4 Neuroscience & Behavior Program Temporal Uncertainty Training  Randomly mixing trials with these CS-US intervals produced bimodal CR waveforms with amplitude peaks located at the two temporal loci of the US, temporal windows centered at 300 and 700 ms.

5. 5 Neuroscience & Behavior Program TD (CSC) model  Sutton and Barto’s (1990) TD (CSC) model is a representational system capable of describing the complex conditioned response waveforms instilled through training under temporal uncertainty.  The model assumes a delay-line timing structure.

6. 6 Neuroscience & Behavior Program Delay-line Timing Structure  Basic tapped delay-line. Injection of CS input begins sequential propagation of signal through a delay-line. Each synapse (—<) introduces a delay; the total delay from activation of the first element in the delay-line to the last element is a direct function of the number of sequential synapses. Taps from the delay-line units send timing information to higher-order processing units.

7. 7 Neuroscience & Behavior Program Compound Conditioning Under Temporal Uncertainty  Like the Rescorla-Wagner model, the TD (CSC) model assumes that CR performance to a compound stimulus is the sum of the “associative strengths” of the components.  In order to test this assumption, it is necessary to specify how the theoretical indices of CR associative strength map onto real measures of performance such as CR amplitude.

8. 8 Neuroscience & Behavior Program Compound Conditioning Under Temporal Uncertainty  Summation of CR amplitudes to component stimuli should reconstitute the CR waveforms obtained under compound conditioning.  Deviations from a “simple summation” rule should indicate shortcomings and point the way to improving the model.

9. 9 Neuroscience & Behavior Program Compound Conditioning Under Temporal Uncertainty  Factors that could challenge a simple summation rule for reconstituting a compound CR waveform from its components include Configuring/patterning Overshadowing Transfer from prior training.  In addition, floor effects (thresholds) and ceiling effects (saturation) could complicate assessment of the model in terms of CR amplitudes.

10. 10 Neuroscience & Behavior Program Pretraining  Prior to compound conditioning training half of the 24 rabbits were pretrained to one CS (predominantly a light) at one of the two CS-US intervals.  Pretrained rabbits were run concurrently with yoked control rabbits.

11. 11 Neuroscience & Behavior Program Averaged Topographical CR Waveforms

12. 12 Neuroscience & Behavior Program Averaged Topographical CR Waveforms

13. 13 Neuroscience & Behavior Program Peak Amplitudes in Decomposition  Mean peak amplitudes (+SE) to TL-, L-, and T- for the 12 pretrained (PRE) and 12 control rabbits (CONT) at both peak locations in the fourth session-block of training.

14. 14 Neuroscience & Behavior Program Decomposition Peak Latencies Shifts  Mean peak latencies (+SE) to TL-, L-, and T- for 12 pretrained (PRE) and 12 control rabbits (CONT) at both peak locations in the fourth session-block of training.

15. 15 Neuroscience & Behavior Program Proportional Contribution  Mean proportional contribution of T- to the compound waveform for both pretrained subjects (PRE) and control subjects (CONT).

16. 16 Neuroscience & Behavior Program Gain Factors  Mean gain factors of T- and L- for pretrained subjects (PRE) and control subjects (CONT).

17. 17 Neuroscience & Behavior Program Sum of Squared Deviations  Mean (+SE) Sum of Squared Deviations (SSDs) for pretrained (n = 12) and control rabbits (n = 12) for nine combination rules in the last block of sessions.

18. 18 Neuroscience & Behavior Program Summary of Findings  Decomposition slowed the initiation of the motor program representing CR waveforms.  The latency of initiation was greater for the light than the tone, consistent with the tone’s greater salience, as indexed by the tones greater proportional contribution to the compound.  Decomposition did not affect other features of component CR waveforms, as inter-peak intervals remained unchanged.

19. 19 Neuroscience & Behavior Program Summary of Findings  The slower initiation of the motor program did not result in a later “catching up” such that the second amplitude peak appeared within the 700- ms temporal window. Nor did the slower initiation result a greater temporal separation of amplitude peaks.  In terms of the spreading activation account of CR topography proposed by the TD (CSC) model, the speed of propagation remained the unchanged.

20. 20 Neuroscience & Behavior Program Discussion  The slower initiation of component CR waveforms following compound conditioning may reflect a “processing cost.”  Pearce has suggested that compound CSs are gestalts, and that changes in performance to component stimuli are “generalization decrements.”  If so, the costs of decomposition did not extend to CR amplitudes, as amplitudes adhered to a summation combination rule.

21. 21 Neuroscience & Behavior Program Acknowledgments Moore Lab Vanessa Castagna Jamy Gaynor Jordan Marks Tony Rauhut June-Seek Choi Marcy Rosenfield  Thank You

22. 22 Neuroscience & Behavior Program

23. 23 Neuroscience & Behavior Program Summation Experiment  Rabbits were trained with individual CSs, with each CS trained at a different CS-US interval (light at 300 ms and tone at 700 ms).  The two CSs were only presented together on probe trials.

24. 24 Neuroscience & Behavior Program Averaged Summation CR Waveforms

25. 25 Neuroscience & Behavior Program Pretrained & Control Summation Rabbits

26. 26 Neuroscience & Behavior Program Summation Results  Waveforms to compound CS showed a unimodal peak that was between the component peaks in both amplitude and latency.  The peak amplitude favored the more salient tone CS resulting in a “Performance Overshadowing Effect.”

27. 27 Neuroscience & Behavior Program Performance Overshadowing/ Summated Generalization  The characteristic waveform for one stimulus (tone) is dominated the characteristic waveform for the other stimulus (light) because of the tone’s higher salience, even though the light stimulus is pretrained.  One possible explanation for the intermediate temporal position of the peak is summated generalization, similar to summated generalization along dimensions such as auditory frequency (Moore, 1972).

28. 28 Neuroscience & Behavior Program

29. 29 Neuroscience & Behavior Program Effects of Pretraining  Mean peak amplitudes (+SE) to TL-, L-, and T- for the 6 rabbits pretrained to light at the 300-ms ISI (PRE) and their 6 yoked controls (CONT) at both peak locations in the fourth session-block of training.