Distinguishing the contributions of implicit and explicit processes to performance of the weather prediction task

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.

The Visual Advantage Effect in Comparing Uni-Modal and Cross-Modal Probabilistic Category Learning

People rely on multiple learning systems to complete weather prediction (WP) tasks with visual cues. However, how people perform in audio and audiovisual modalities remains elusive. The present research investigated how the cue modality influences performance in probabilistic category learning and conscious awareness about the category knowledge acquired. A modified weather prediction task was adopted, in which the cues included two dimensions from visual, auditory, or audiovisual modalities. The results of all three experiments revealed better performances in the visual modality relative to the audio and audiovisual modalities. Moreover, participants primarily acquired unconscious knowledge in the audio and audiovisual modalities, while conscious knowledge was acquired in the visual modality. Interestingly, factors such as the amount of training, the complexity of visual stimuli, and the number of objects to which the two cues belonged influenced the amount of conscious knowledge acquired but did not change the visual advantage effect. These findings suggest that individuals can learn probabilistic cues and category associations across different modalities, but a robust visual advantage persists. Specifically, visual associations can be learned more effectively, and are more likely to become conscious. The possible causes and implications of these effects are discussed.

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.

Intact capacity for implicit learning in obsessive-compulsive disorder

BACKGROUND AND OBJECTIVES

Individuals with OCD tend to rely on explicit processing when performing implicit learning tasks. However, it is unclear whether this tendency reflects impaired capacity for implicit processing or a preference toward explicit processing. We sought to use a psychometrically valid task to examine the hypothesis that individuals with OCD have intact capacity for implicit learning.

METHODS

Twenty-four participants with OCD and 24 non-psychiatric controls completed a modified artificial grammar learning task where acquisition and retrieval of the underlying grammatical rules are considered strictly implicit. In an exploratory condition designed to examine the effect of nudging participants toward controlled processing, 12 participants in each group were told that the stimuli presented at acquisition were composed according to grammatical rules and were encouraged to identify these rules.

RESULTS

As predicted, participants with OCD acquired and expressed knowledge of the grammatical rule, demonstrating intact capacity for implicit learning, with no differences found between the OCD and controls on the extent of implicit learning. The exploratory intentional learning instructions had no effect, as participants in this condition were unable to adhere to the instructions, supporting the robust implicit nature of the artificial grammar learning task.

LIMITATIONS

The relatively small sample size did not allow comparisons between OCD symptom subtypes.

CONCLUSIONS

Our results provide evidence for intact implicit learning in OCD, and challenge previous studies suggesting a general deficiency in implicit learning in OCD.

Strategy use in probabilistic categorization by rhesus macaques (Macaca mulatta) and capuchin monkeys (Cebus [Sapajus] apella)

Probabilistic categorization tasks present the learner with a set of possible responses and imperfect cue evidence of which response will be rewarded. A single, optimal integration of all available cues into an optimal response is possible given any set of evidence. In contrast, there are many possible uses of the cues that offer the learner suboptimal (but better than chance) responding. We presented a classic probabilistic categorization task to 3 rhesus macaques (Macaca mulatta) and 13 capuchin monkeys (Cebus [Sapajus] apella) to explore what strategies for integration of imperfectly predictive stimulus information would be used by the animals. Using the strategy analysis models that have been previously used to describe human strategy use in probabilistic categorization tasks, we fit each of thousands of blocks of responses to 25 types of response strategies ranging from complex cognitive strategies (e.g., optimal integration of all evidence) to heuristic strategies (e.g., identify a highly predictive cue and respond based only on its presence or absence) to rote behavior (e.g., choosing the same response every trial). Inferences about strategy use were highly stable within animals and were heterogeneous across animals, with some animals never using cue information and others using it fruitfully. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Impaired sequential and partially compensated probabilistic skill learning in Parkinson's disease

The striatal dopaminergic dysfunction in Parkinson's disease (PD) has been associated with deficits in skill learning in numerous studies, but some of the findings remain controversial. Our aim was to explore the generality of the learning deficit using two widely reported skill learning tasks in the same group of Parkinson's patients. Thirty-four patients with PD (mean age: 62.83 years, SD: 7.67) were compared to age-matched healthy adults. Two tasks were employed: the Serial Reaction Time Task (SRT), testing the learning of motor sequences, and the Weather Prediction (WP) task, testing non-sequential probabilistic category learning. On the SRT task, patients with PD showed no significant evidence for sequence learning. These results support and also extend previous findings, suggesting that motor skill learning is vulnerable in PD. On the WP task, the PD group showed the same amount of learning as controls, but they exploited qualitatively different strategies in predicting the target categories. While controls typically combined probabilities from multiple predicting cues, patients with PD instead focused on individual cues. We also found moderate to high correlations between the different measures of skill learning. These findings support our hypothesis that skill learning is generally impaired in PD, and can in some cases be compensated by relying on alternative learning strategies.

Explicit instructions facilitate performance of OCD participants but impair performance of non-OCD participants on a serial reaction time task

Previous studies have shown that individuals diagnosed with OCD tend to rely on explicit processing while performing implicit learning tasks. We sought to investigate whether individuals with OCD are capable of implicit learning, but would demonstrate improved performance when explicit processing strategies are enhanced. Twenty-four participants with OCD and 24 non-psychiatric control (NPC) participants performed an implicit learning task in which they responded to a single target stimulus that successively appears at one of four locations according to an underlying sequence. We manipulated the learning strategy by informing half of the participants that the target stimulus location was determined by an underlying sequence, which they should identify (intentional learning). The other half of the participants was not informed of the existence of the underlying sequence, and was expected to learn the sequence implicitly (standard learning). We predicted that OCD participants will exhibit inferior performance compared to NPC participants in the standard learning condition, and that intentional learning instructions would impair the performance of NPC participants, but enhance the performance of OCD participants. The results supported these predictions and suggest that individuals with OCD prefer controlled to automatic processing. We discuss the implications of this conclusion to our understanding of OCD.

Media multitasking and implicit learning

Media multitasking refers to the simultaneous use of different forms of media. Previous research comparing heavy media multitaskers and light media multitaskers suggests that heavy media multitaskers have a broader scope of attention. The present study explored whether these differences in attentional scope would lead to a greater degree of implicit learning for heavy media multitaskers. The study also examined whether media multitasking behaviour is associated with differences in visual working memory, and whether visual working memory differentially affects the ability to process contextual information. In addition to comparing extreme groups (heavy and light media multitaskers) the study included analysis of people who media multitask in moderation (intermediate media multitaskers). Ninety-four participants were divided into groups based on responses to the media use questionnaire, and completed the contextual cueing and n-back tasks. Results indicated that the speed at which implicit learning occurred was slower in heavy media multitaskers relative to both light and intermediate media multitaskers. There was no relationship between working memory performance and media multitasking group, and no relationship between working memory and implicit learning. There was also no evidence for superior performance of intermediate media multitaskers. A deficit in implicit learning observed in heavy media multitaskers is consistent with previous literature, which suggests that heavy media multitaskers perform more poorly than light media multitaskers in attentional tasks due to their wider attentional scope.

Paired-Associate and Feedback-Based Weather Prediction Tasks Support Multiple Category Learning Systems

It remains unclear whether probabilistic category learning in the feedback-based weather prediction task (FB-WPT) can be mediated by a non-declarative or procedural learning system. To address this issue, we compared the effects of training time and verbal working memory, which influence the declarative learning system but not the non-declarative learning system, in the FB and paired-associate (PA) WPTs, as the PA task recruits a declarative learning system. The results of Experiment 1 showed that the optimal accuracy in the PA condition was significantly decreased when the training time was reduced from 7 to 3 s, but this did not occur in the FB condition, although shortened training time impaired the acquisition of explicit knowledge in both conditions. The results of Experiment 2 showed that the concurrent working memory task impaired the optimal accuracy and the acquisition of explicit knowledge in the PA condition but did not influence the optimal accuracy or the acquisition of self-insight knowledge in the FB condition. The apparent dissociation results between the FB and PA conditions suggested that a non-declarative or procedural learning system is involved in the FB-WPT and provided new evidence for the multiple-systems theory of human category learning.

Probing Implicit Learning in Obsessive-Compulsive Disorder: Moderating Role of Medication on the Weather Prediction Task

Deficits in implicit learning, a process by which knowledge is acquired accretively through practice independent of conscious awareness, have been implicated in Obsessive-Compulsive Disorder (OCD). The weather-prediction task (WPT) was used to assess implicit learning in 26 unmedicated patients with OCD and 23 healthy controls. An additional analysis compared these two groups with 25 medicated patients with OCD. In the comparison of unmedicated patients with healthy controls there was a subtle but statistically significant group-by-block interaction. Patients with OCD showed slower improvement in performance during the middle phase of learning. In a three-group comparison, there was no main effect of group; in post-hoc tests, medicated patients with OCD differed from unmedicated patients and were not different from healthy controls. Unmedicated patients with OCD have a subtle deficit in implicit learning in the WPT. This may be mitigated by pharmacotherapy, although prospective studies would be required to confirm this conclusion.

Reinforcement learning in multidimensional environments relies on attention mechanisms

In recent years, ideas from the computational field of reinforcement learning have revolutionized the study of learning in the brain, famously providing new, precise theories of how dopamine affects learning in the basal ganglia. However, reinforcement learning algorithms are notorious for not scaling well to multidimensional environments, as is required for real-world learning. We hypothesized that the brain naturally reduces the dimensionality of real-world problems to only those dimensions that are relevant to predicting reward, and conducted an experiment to assess by what algorithms and with what neural mechanisms this "representation learning" process is realized in humans. Our results suggest that a bilateral attentional control network comprising the intraparietal sulcus, precuneus, and dorsolateral prefrontal cortex is involved in selecting what dimensions are relevant to the task at hand, effectively updating the task representation through trial and error. In this way, cortical attention mechanisms interact with learning in the basal ganglia to solve the "curse of dimensionality" in reinforcement learning.

Self-insight in probabilistic category learning

The Weather Prediction (WP) task is one of the most extensively used Probabilistic Category Learning tasks. Although it has been usually treated as an implicit task, its implicit nature has been questioned with focus on the structural knowledge of the acquired information. The goal of the current studies is to test if participants acquire explicit knowledge on the WP task. Experiment 1 addresses this question directly with the help of a subjective measure on self-insight in two groups: an experimental group facing the WP task and a control group with a task lacking predictive structure. Participants in the experimental group produced more explicit reports than the control group, and only on trials with explicit knowledge was their performance higher. Experiment 2 provided further evidence against the implicitness of the task by showing that decreasing stimulus presentation times extends the learning process, but does not result in more implicit processes.

Evidence of compensatory processing in adults with developmental language impairment: testing the predictions of the procedural deficit hypothesis

BACKGROUND

The Procedural Deficit Hypothesis (PDH) proposes that individuals with primary developmental language impairment (DLI) have a deficient procedural memory, compromising their syntactic abilities. Individuals with DLI may compensate for procedural memory deficits by engaging declarative memory for syntactic tasks. Arguments are part of the lexicon whereas adjuncts rely on syntactic processing. As a result, individuals with DLI may have unusual difficulty processing adjuncts. Alternatively, processing for adjuncts may be typical for individuals with DLI but show frequency effects, indicating compensatory use of declarative memory.

AIMS

Our goal was to test the predictions of the PDH by comparing argument and adjunct processing times for adults with and without DLI, and to seek evidence of compensatory use of declarative memory for adjunct processing. We further evaluated group performance on measures of visual procedural and declarative memory.

METHODS AND PROCEDURES

Forty-four adults, 21 with DLI, completed a self-paced listening task, a procedural memory task, and a declarative memory task. The self-paced listening task tracked the word-by-word processing time for sentences that included prepositional phrases acting as arguments or adjuncts. We used regression analysis to determine effects of group membership and argument or adjunct status on processing times. Correlation analyses evaluated relationships between argument and adjunct frequency on processing times by group.

RESULTS AND OUTCOMES

We found no effect of group membership on the processing time for arguments and adjuncts in the self-paced listening task. Argument phrases were processed more easily by both groups. There were frequency effects for adjunct processing for the group with DLI, but not the group with typical language. We did not find the expected frequency effects for argument processing. The group with DLI also performed more poorly in both the procedural and declarative memory tasks. Secondary analyses found that non-verbal intelligence was related to outcomes on the declarative memory but not the procedural memory task.

CONCLUSIONS AND IMPLICATIONS

We found mixed evidence on the predictions of the PDH. Adults with DLI may compensate for procedural memory deficits but it is unclear whether this depends on declarative memory or language processing experience. Compensatory processing is an important element of the language profile for adults with DLI.

LEARNING OUTCOMES

The readers will be able to describe how processing arguments and adjuncts in sentences may depend on different memory systems, and how adults with developmental language impairment may compensate for syntactic processing deficits.

The subthalamic nucleus modulates the early phase of probabilistic classification learning

Previous models proposed that the subthalamic nucleus (STN) is critical in the early phase of skill acquisition. We hypothesized that subthalamic deep brain stimulation modulates the learning curve in early classification learning. Thirteen idiopathic Parkinson's disease patients (iPD) with subthalamic deep brain stimulation (STN-DBS), 9 medically treated iPD, and 21 age-matched healthy controls were tested with a probabilistic classification task. STN-DBS patients were tested with stimulation OFF and ON, and medically treated patients with medication OFF and ON, respectively. Performance and reaction time were analyzed on the first 100 consecutive trials as early learning phase. Moreover, data were separated for low and high-probability patterns, and more differentiated strategy analyses were used. The major finding was a significant modulation of the learning curve in DBS patients with stimulation ON: although overall learning was similar to healthy controls, only the stimulation ON group showed a transient significant performance dip from trials '41-60' that rapidly recovered. Further analysis indicated that this might be paralleled by a modulation of the learning strategy, particularly on the high-probability patterns. The reaction time was unchanged during the dip. Our study supports that the STN serves as a relay in early classification learning and directs attention toward unacquainted content. The STN might play a role in balancing the short-term success against strategy optimization for improved long-term outcome.

Adult age differences in subjective and objective measures of strategy use on a sequentially cued prediction task

Differences in strategy use are thought to underlie age-related performance deficits on many learning and decision-making tasks. Recently, age-related differences in learning to make predictions were reported on the Triplets Prediction Task (TPT). Notably, deficits appeared early in training and continued with experience. To assess if age differences were due to early strategy use, neural networks were used to objectively assess the strategies implemented by participants during Session 1. Then, the relationship between these strategies and performance was examined. Results revealed that older adults were more likely to implement a disadvantageous strategy early in learning, and this led to poorer task performance. Importantly, the relationship between age and task performance was partially mediated by early strategy use, suggesting that early strategy selection played a role in the lower quality of predictions in older adults.

Prediction and control in a dynamic environment

The present study compared the accuracy of cue-outcome knowledge gained during prediction-based and control-based learning in stable and unstable dynamic environments. Participants either learnt to make cue-interventions in order to control an outcome, or learnt to predict the outcome from observing changes to the cue values. Study 1 (N = 60) revealed that in tests of control, after a short period of familiarization, performance of Predictors was equivalent to Controllers. Study 2 (N = 28) showed that Controllers showed equivalent task knowledge when to compared to Predictors. Though both Controllers and Predictors showed good performance at test, overall Controllers showed an advantage. The cue-outcome knowledge acquired during learning was sufficiently flexible to enable successful transfer to tests of control and prediction.