Why do individuals with Williams syndrome or Down syndrome fail the Weather Prediction Task?

Williams syndrome (WS) and Down syndrome (DS) are two neurodevelopmental disorders with distinct genetic origins characterized by mild to moderate intellectual disability. Individuals with WS or DS exhibit impaired hippocampus-dependent place learning and enhanced striatum-dependent spatial response learning. Here, we used the Weather Prediction Task (WPT), which can be solved using hippocampus- or striatum-dependent learning strategies, to determine whether individuals with WS or DS exhibit similar profiles outside the spatial domain. Only 10% of individuals with WS or DS solved the WPT. We further assessed whether a concurrent memory task could promote reliance on procedural learning to solve the WPT in individuals with WS but found that the concurrent task did not improve performance. To understand how the probabilistic cue-outcome associations influences WPT performance, and whether individuals with WS or DS can ignore distractors, we assessed performance using a visual learning task with differing reward contingencies, and a modified WPT with unpredictive cues. Both probabilistic feedback and distractors negatively impacted the performance of individuals with WS or DS. These findings are consistent with deficits in hippocampus-dependent learning and executive functions, and reveal the importance of congruent feedback and the minimization of distractors to optimize learning in these two populations.

When and how do children solve the Weather Prediction Task?

The Weather Prediction Task (WPT) can be solved by adults using several strategies dependent on different memory systems. One developmental study reported that 8-12-year-old children can solve WPT-like tasks but, because of inadequate analyses, the cognitive processes involved in solving the task have not been established. The present study aimed to determine at what age children can first solve the WPT and identify the strategies used by children of different ages. We tested 3-12-year-old typically developing children and 20-30-year-old adults on a modified WPT. We performed detailed analyses of performance for each pattern of cue-outcome associations to decipher the strategies used by participants. None of the 3-5.5-year-old children solved the task. About one third of 5.5-7.5-year-old children performed above chance, relying only on the two most predictive cues. In contrast, about 80% of 7.5-12-year-old children performed above chance, relying on a conditional hierarchical strategy. Similar to 20-30-year-old adults, 7.5-12-year-old children considered the highly predictive cues primarily and the less predictive cues secondarily. These findings indicate that the learning strategies used to solve the WPT evolve from middle to late childhood and reflect an increasing ability to use a conditional strategy concomitant with the development of the hippocampus-dependent memory system.

What Is the Weather Prediction Task Good for? A New Analysis of Learning Strategies Reveals How Young Adults Solve the Task.

The Weather Prediction Task (WPT) was originally designed to assess probabilistic classification learning. Participants were believed to gradually acquire implicit knowledge about cue-outcome association probabilities and solve the task using a multicue strategy based on the combination of all cue-outcome probabilities. However, the cognitive processes engaged in the resolution of this task have not been firmly established, and despite conflicting results, the WPT is still commonly used to assess striatal or procedural learning capacities in various populations. Here, we tested young adults on a modified version of the WPT and performed novel analyses to decipher the learning strategies and cognitive processes that may support above chance performance. The majority of participants used a hierarchical strategy by assigning different weights to the different cues according to their level of predictability. They primarily based their responses on the presence or absence of highly predictive cues and considered less predictive cues secondarily. However, the influence of the less predictive cues was inconsistent with the use of a multicue strategy, since they did not affect choices when both highly predictive cues associated with opposite outcomes were present simultaneously. Our findings indicate that overall performance is inadequate to draw conclusions about the cognitive processes assessed by the WPT. Instead, detailed analyses of performance for the different patterns of cue-outcome associations are essential to determine the learning strategies used by participants to solve the task.