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Investigating Cognitive Flexibility Training

No phase Interventional Healthy

For patients and families

In plain language

An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.

What is being studied
The protocol lists: Experimental (Implicit Training): Structure Learning Training, Active Control (Explicit Training): 'All You Can E.T.'.
Who it may be relevant to
Registry conditions: Healthy. Basic parameters: 18 years — 29 years · All.
What needs checking
Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
Where it takes place
Singapore
Next step
Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →

Overview

The investigators' previous research identified two distinct subtypes of Cognitive Flexibility (CF), termed CF1 (shifting flexibility) and CF2 (strategy flexibility). The present study aims to determine whether these forms of CF can be trained, how they differ, and the extent to which improvements transfer to broader learning and cognitive skills. In addition, social functioning outcomes and the extent to which social factors moderate the effects of cognitive flexibility training are assessed. The investigators will employ a multi-modal approach combining cognitive-behavioural and neuroimaging methods to examine how brain mechanisms and cognitive performance change following CF-targeted training intervention (Structure learning) compared with active control and a no-training paradigm (passive control).

Detailed description

Cognitive flexibility (CF) is critical for humans to perform complex tasks and ensures that humans exhibit appropriate behaviour in response to changing environments. The ability to shift thinking, adapt behaviour, and apply knowledge in new contexts is a core executive function that supports problem solving, self-regulation and lifelong learning. It is especially crucial during key developmental periods where the brain is rapidly changing, and later in adulthood to help maintain cognitive health. In a fast-evolving world. CF is essential for navigating uncertainty, developing new skills and thriving in dynamic work and social environments. Yet, current education and training systems often do not adequately support the development of flexible thinking, highlighting the need for more evidence-based interventions that can strengthen CF across the lifespan.

Successful implementation of cognitive flexibility involves several sub-domains within executive functions. Prior research on cognitive flexibility has portrayed it as various aspects of human cognition ranging from a cognitive skill related to set-shifting, or a by-product of cognitive processes, to part of the cognitive system. In previous work, the investigators clarified the structure of cognitive flexibility through a large behavioural study, resulting in a dual-factor model comprising distinct but complementary dimensions that show unique associations with critical outcome variables. The first factor, CF1 (shifting type flexibility) refers to the ability to switch efficiently between rules and tasks. The second factor, CF2 (strategy type flexibility) reflects the capacity to adapt problem-solving strategies based on contextual cues. Notably, previous work shows that these two forms of CF relate to different learning outcomes. Shifting flexibility predicts reading ability, while strategy flexibility is associated with mathematical proficiency, problem-solving, academic skills and creativity. These findings suggest that different forms of CF may support distinct aspects of learning and raise the possibility that training-related gains in CF may generalise beyond the trained tasks to other cognitive and behavioural domains. Improvements may emerge on tasks that closely overlap with the trained processes, for example those that use similar task structures (near transfer) or extend to more dissimilar tasks (far transfer).

Current flexibility interventions and neuroimaging studies examining CF commonly utilise tasks that tap on to executive functions such as task-set switching or the Dimensional Change Card Sort (DCCS) task. These tasks primarily target CF1 shifting type flexibility. Although effective, one concern related to using these tasks is that it does not tap merely into cognitive flexibility but also activate other executive functions such as inhibition and working memory. Hence, this reduces the precision and specificity of these tasks as training tools. The present project proposed structure learning as a more fundamental and apt training approach. It involves seeking patterns in the stochastic presentations of stimuli, without the need for explicit feedback and is in itself a basic building block for cognitive flexibility, particularly CF2 strategy flexibility.

In the educational context, structure learning is analogous to patterning, a crucial cognitive ability that underpins mathematical and reading skills. Prior research has demonstrated a close relationship between pattern understanding and cognitive flexibility. Hence, structure learning training could potentially be beneficial in improving one's cognitive flexibility. Furthermore, emerging evidence has demonstrated that domain-general training of structure learning skills produced learning that transfer well beyond the learning task (far transfer). However, there is also a paucity in studies that examined whether structure learning training per se could produce generalisable improvements in cognitive flexibility.

The present study aims to address this gap by examining whether cognitive flexibility can be trained using a structure learning intervention, compared with an active control condition (shifting related training) and a passive no-training control. This study will assess whether these interventions produce changes in neural markers and behavioural performance associated with potential gains in CF. Behavioural changes will be examined in terms of their generalisation beyond the trained tasks, specifically whether they show near and far transfer across cognitive and learning-related outcomes, and whether these effects differ for shifting and strategy related training.

Outcome variables are defined a priori and organised into prespecified cognitive domains. Corrections for multiple comparisons will be applied within each domain.

Interventions

  • Behavioral Experimental (Implicit Training): Structure Learning Training
    Participants will undergo 6-12 sessions of Structure Learning or set-shifting training in the active control training group lasting up to 30 minutes each. Each session will be conducted in a remote-guided manner with an approximate 1-day gap in between sessions. The entire training will span a maximum of 12 days. Across the task, difficulty will progressively increase through changes in probabilistic contingencies. For example, following each symbol, one subsequent symbol may occur with 75% pro
  • Behavioral Active Control (Explicit Training): 'All You Can E.T.'
    The protocol for the active control condition will mirror that of the experimental arm. Participants will complete an equivalent number of training sessions, and total task time will be matched between the experimental and control groups.

Primary outcome measures

  • Structure Learning Outcome 1 - Performance Index (PI) Relative [Time frame: Through training completion (adaptive, up to 12 days)]
  • Structure Learning Outcome 2 - Strategy choice [Time frame: Through training completion (adaptive, up to 12 days)]
  • Structure Learning Outcome 3 - Strategy ICD index (measured by the integral curve difference) [Time frame: Through training completion (adaptive, up to 12 days)]
  • Structure Learning Outcome 4 - Learning rate [Time frame: Through training completion (adaptive, up to 12 days)]
  • Structure Learning Outcome 5 - Strategy shifting rate [Time frame: Through training completion (adaptive, up to 12 days)]
  • 'All You Can E.T.' (AYCET) Outcome 1 - Accuracy [Time frame: Through training completion (adaptive, up to 12 days)]
  • 'All You Can E.T.' (AYCET) Outcome 2 - Response Time (RT) [Time frame: Through training completion (adaptive, up to 12 days)]
  • Cognitive Flexibility (Strategy) Outcome 1 - Wisconsin Card Sorting Test (WCST): Proportion of perseverative errors [Time frame: Post-intervention (within one week after post-MRI scan)]
  • Cognitive Flexibility (Strategy) Outcome 2 - Wisconsin Card Sorting Test (WCST): Learning rate [Time frame: Post-intervention (within one week after post-MRI scan)]
  • Cognitive Flexibility (Strategy) Outcome 3 - Wisconsin Card Sorting Test (WCST): Decision consistency [Time frame: Post-intervention (within one week after post-MRI scan)]
Secondary outcome measures (12)
  • Stress Outcome 1 - Perceived Stress Scale (PSS): Perceived Stress Scale Score [Time frame: Baseline (pre-intervention and within two weeks prior to pre-MRI scan) and Post-intervention (within two weeks after post-MRI scan)]
  • Sleep Quality Outcome 1 - Pittsburgh Sleep Quality Index (PSQI): Global PSQI Score [Time frame: Post-intervention (within two weeks after post-MRI scan)]
  • Literacy and Numeracy Outcome 1 - Wide Range Achievement Test-5 [Time frame: Pre-intervention (within one week before pre-MRI) and Post-intervention (within one week after post-MRI scan)]
  • Decision Making Outcome 1 - Social Value Orientation: Social Preference Score [Time frame: Baseline (pre-intervention and within two weeks prior to pre-MRI scan) and Post-intervention (within two weeks after post-MRI scan)]
  • Decision Making Outcome 2 - Prisoner's Dilemma: Proportion of cooperative choices [Time frame: Baseline (pre-intervention and within two weeks prior to pre-MRI scan) and Post-intervention (within two weeks after post-MRI scan)]
  • Decision Making Outcome 3 - Risk Preference: Risk Preference (Positive Domain) [Time frame: Baseline (pre-intervention and within two weeks prior to pre-MRI scan) and Post-intervention (within two weeks after post-MRI scan)]
  • Decision Making Outcome 4 - Ambiguity Aversion: Ambiguity preference [Time frame: Baseline (pre-intervention and within two weeks prior to pre-MRI scan) and Post-intervention (within two weeks after post-MRI scan)]
  • Decision Making Outcome 5 - Temporal Discounting [Time frame: Baseline (pre-intervention and within two weeks prior to pre-MRI scan) and Post-intervention (within two weeks after post-MRI scan)]
  • Social Orientation Outcome 1 - Personal Relative Deprivation Scale: Total personal relative deprivation score [Time frame: Post-intervention (within two weeks after post-MRI scan)]
  • Social Orientation Outcome 2 - Cooperativeness and Competitiveness Personality Scale: Score for Cooperativeness dimension [Time frame: Baseline (pre-intervention and within two weeks prior to pre-MRI scan) and Post-intervention (within two weeks after post-MRI scan)]
  • Social Orientation Outcome 3 - Cooperativeness and Competitiveness Personality Scale: Score for Competitiveness dimension [Time frame: Baseline (pre-intervention and within two weeks prior to pre-MRI scan) and Post-intervention (within two weeks after post-MRI scan)]
  • Tolerance of Uncertainty Outcome 1 - Receptiveness to Opposing Views: Score from Questionnaire [Time frame: Baseline (pre-intervention and within two weeks prior to pre-MRI scan) and Post-intervention (within two weeks after post-MRI scan)]

Eligibility criteria

Inclusion criteria

  • Healthy volunteer (male of female) between 18 and 29 years who gave written informed consent to participate

Exclusion criteria

  • Current and/or prior history of learning disabilities
  • Current and/or prior history of neurological disorder
  • Current and/or prior history of psychiatric disorder
  • Current and/or prior history of cardiovascular disorder
  • Predominantly left-handed
  • Contraindications for MRI (e.g., pacemakers, implanted pumps, metal objects in the body)
  • Claustrophobic
  • Pregnancy (females)
  • Lactation (females)
  • Pronounced visual or auditory impairments

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: Yes

Study design

Allocation
Randomized
Model
Parallel assignment
Masking
Open label
Primary purpose
Basic science

Study locations

Singapore · 1 center
  • Centre for Lifelong Learning and Individualised Cognition (CLIC), Nanyang Technological Un — Singapore

Publications

  • Parong, J., Wells, A., & Mayer, R. E. (2020). Replicated evidence towards a cognitive theory of game-based training. Journal of Educational Psychology, 112(5), 922-937.
  • Tong, K., Uchiyama, R., Fischer, N. L., Langley, C., Cheng, X., Kalaivanan, K., Melia, N., Feng, S., Fu, X., Marzuki, A. A., Talwar, A., Chan, Y. N., Fauziana, R., Hoo, N., Lee, K. M., Lee, L. L., Lee, T., Melani, I., Pei, J. Y., ... Leong, V. Cognitive flexibility: Separate shifting and strategy factors [Manuscript under review]
  • Tong K, Chan YN, Cheng X, Cheon B, Ellefson M, Fauziana R, Feng S, Fischer N, Gulyas B, Hoo N, Hung D, Kalaivanan K, Langley C, Lee KM, Lee LL, Lee T, Melani I, Melia N, Pei JY, Raghani L, Sam YL, Seow P, Suckling J, Tan YF, Teo CL, Uchiyama R, Yap HS, Christopoulos G, Hendriks H, Chen A, Robbins T, Sahakian B, Kourtzi Z, Leong V; CLIC Phase 1 Consortium. Study protocol: How does cognitive flexibi PMID 37471399
  • Parong, J., Mayer, R. E., Fiorella, L., MacNamara, A., Homer, B. D., & Plass, J. L. (2017). Learning executive function skills by playing focused video games. Contemporary Educational Psychology, 51, 141-151.
  • Mayer, R. E., Parong, J., & Bainbridge, K. (2019). Young adults learning executive function skills by playing focused video games. Cognitive Development, 49, 43-50.
  • Lee, L. Y., Healy, M. P., Fischer, N. L., Tong, K., Chen, A. S. H., Sahakian, B. J., & Kourtzi, Z. (2024). Cognitive flexibility training for impact in real-world settings. Current Opinion in Behavioural Sciences, 59(101413), 101413.
  • Holland, J.L., Daiger, D.C., & Power, P.G. (1980). My Vocational Situation. Palo Alto, CA: Consulting Psychologists Press.
  • Gupta, A., Chong, S., & Leong, F. T. L. (2015). Development and validation of the Vocational Identity Measure. Journal of Career Assessment, 23(1), 79-90.

Identifiers

NCT: NCT07556250 · IRB-2025-1325

Primary sources (government registries)

View this study on ClinicalTrials.gov ↗