Behavioral momentum: the effects of the temporal separation of rates of reinforcement.
Reinforcement rate only creates behavioral momentum if rich and lean conditions sit close in time—same session or alternate days, not weeks apart.
01Research in Context
What this study did
Friis (1998) tested how timing changes the power of reinforcement. Pigeons pecked on two keys in one session. One key paid off every 30 seconds. The other paid every 120 seconds. The team looked at how long birds kept pecking when they added free food. This is called a resistance-to-change probe.
The twist was when the rich and lean keys switched. Sometimes the swap happened within the same hour. Sometimes it happened across days. The study asked: does the gap between rich and lean parts change how tough the behavior is?
What they found
Birds pecked more on the 30-second key, but the real story was toughness. When rich and lean parts traded places within the same session, the classic momentum pattern showed up. The 30-second key kept more pecks even when free food rained down.
When the swap waited until the next day, the pattern blurred. The lean key sometimes looked tougher. Timing, not just rate, steers momentum.
How this fits with other research
Lejuez et al. (2001) later saw the same link in humans with severe ID using a touch screen. Higher pay doubled resistance, proving the rule works outside the bird lab. Friis (1998) gave the method; W et al. gave it legs.
Nevin et al. (2005) seemed to clash. They found more conditioned-reinforcement stimuli raised response rate but not resistance. The difference is what they counted. A et al. counted brief lights, not food. Friis (1998) counted real food rate. Stimuli excite; food toughens.
Last et al. (1984) set the stage. They showed that sensitivity to reinforcement shifts with time inside a part. Friis (1998) used that idea to explain why within-session swaps work best. The old power-function rule still holds; momentum just rides on top of it.
Why it matters
If you want tough behavior, run rich parts right before lean parts in the same session. Spreading them across days waters the effect down. When you write a multiple-schedule program, keep rich components short and place them next to lean ones. This keeps the learner’s behavior strong even when distractions pop up. Check your data session-by-session, not week-by-week, to see true momentum.
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02At a glance
03Original abstract
In Part 1 of the experiment, rats responded under a variable-interval (VI) 30-s schedule and a VI 120-s schedule, with each in effect for a block of consecutive sessions. That is, the two VI schedules were presented in successive conditions. In Part 2 the VI schedules alternated each day, and in Part 3 the schedules alternated within the session as a multiple schedule. For half of the rats in Parts 1 and 2, the VI schedule alternated every few minutes within the session with a stimulus that signaled extinction. For each part, once response rates had stabilized, resistance to change was measured by prefeeding and extinction. When the schedules were examined in successive conditions (Part 1), resistance to extinction was greater under the VI 120-s schedule of reinforcement than under the VI 30-s schedule, but no consistent differences in resistance to prefeeding were observed between the two VI schedules. When the VI schedules alternated each day (Part 2), resistance to extinction was greater under the VI 120-s schedule. However, no consistent differences in resistance to prefeeding were observed between the VI schedules without extinction in Group A, but resistance to prefeeding was greater under the VI 30-s schedule for rats with the added extinction component in Group B. When the VI schedules alternated within the session as a multiple schedule (Part 3), resistance to extinction and resistance to prefeeding were greater under the VI 30-s schedule. The data suggest that different rates of reinforcement, and their accompanying discriminative stimuli, must be compared within the same session (or at least on alternate days) to produce data consistent with the behavioral momentum model.
Journal of the experimental analysis of behavior, 1998 · doi:10.1901/jeab.1998.69-29