Research and proof boundary

Evidence behind the
Trident G protocol

Proof-led intelligence training

IQ Mindware is built around a simple principle: train the core systems involved in general intelligence, then test progress beyond simple game completion.

The Trident G Far Transfer Protocol™ combines cognitive control and working-memory capacity training + relational reasoning under varied task demands, strategy prompts and separate progress checks. The aim is to train intelligence under changing conditions — not simply help you get better at one familiar exercise.

How to read this page

Component evidence is not programme proof

A protocol can be grounded in credible research without its complete product combination already being validated. The strongest current case for Trident G is that its main components have relevant empirical foundations and that its design responds to known limits of ordinary brain training.

Direct: evidence for the construct or closely matched training operation Emerging: promising intervention evidence, but limited replication or scope Indirect: research supports the design principle rather than IQ Pro itself
Evidence by protocol component

What the research supports

The review below is deliberately brief. Each section states the useful finding and the limit that matters for interpreting the protocol.

01 Direct construct evidence

Cognitive-control readiness and Zone Pulse

The Majority Function Task with masking estimates how much task-relevant perceptual information can be brought under cognitive control under time pressure. Wu et al. modelled this capacity as an information-processing limit, while He et al. developed an adaptive assessment method. A seven-day training study subsequently reported gains in cognitive-control capacity and selective transfer to some attention, learning, and neural processing measures, with effects varying by task similarity (Wu et al., 2016), (He et al., 2022), (Zhang et al., 2024).

Meaning for Trident G: Zone Pulse has a defensible basis as a readiness and controlled-evidence signal. It is not an IQ test, diagnosis, or proof that readiness routing improves far transfer.

02 Emerging training evidence

Relational working memory and relational n-back

Generic working-memory training reliably improves trained and structurally similar tasks, but high-quality reviews do not support broad far-transfer claims from ordinary working-memory drill alone (Melby-Lervåg et al., 2016). Trident G therefore places more weight on temporary bindings and relations. Oberauer found that increasing memory load particularly impaired memory for bindings, supporting working memory as a limited workspace for maintaining relational structure (Oberauer, 2019).

Relational integration is also closely associated with fluid reasoning. It predicts reasoning beyond other working-memory tasks, and a latent relation-processing factor has been reported as statistically equivalent to a fluid-reasoning factor in one study (Chuderski, 2014), (Jastrzębski et al., 2020). A recent randomised study trained numerical relations in 1-back and 2-back formats and found changes in frontoparietal EEG microstate dynamics associated with fluid intelligence (Wang et al., 2025).

Meaning for Trident G: relational n-back targets a more reasoning-relevant operation than item repetition because the remembered unit is a relation. Evidence is promising, but it does not establish that relational n-back reliably raises IQ or produces broad far transfer.

03 Direct and bounded evidence

Relational reasoning, abstraction, and strategy

Reasoning transfer is more plausible when learners practise identifying invariant relations and explicit strategies rather than repeating one surface form. Reviews of inductive-reasoning training support comparison, rule formation, and testing regularities across examples (Klauer & Phye, 2008). In a smaller randomised study with children, strategy-based working-memory training transferred to a novel problem-solving task, suggesting that portable strategies can matter beyond raw drill (Chan et al., 2019).

Meaning for Trident G: Reasoning Gym’s focus on relation matching, constraints, must-follow inference, and strategy reflection is research-aligned. Transfer is still expected to depend on task design, cueing, and the distance between training and outcome tasks.

04 Indirect design support

Horizontal variation and invariant recovery

Perceptual learning is often highly specific, but transfer can improve when training helps learners recover a higher-level rule or when practice is distributed across time and conditions (Zhang et al., 2010), (Larcombe et al., 2017). This supports changing wrappers while preserving the underlying relation, then checking whether performance recovers after the surface shift.

The entropy–mutual-information principle also draws formal inspiration from Zhang and Tang’s model of neural-network learning. Their analysis describes learning as a balance between maximum-entropy exploration and mutual-information constraint with the task objective (Zhang & Tang, 2025). For Trident G, the analogy is that variation should be broad enough to prevent brittle surface memorisation but constrained enough to preserve the target invariant.

Meaning for Trident G: wrapper swaps are a plausible transfer design and validation method. Zhang and Tang provide a formal analogy from machine learning, not evidence that the same mechanism causes human cognitive transfer.

05 Moderate component support

Vertical progression and real-world deployment

Vertical progression links readiness and attention control to working-memory binding, reasoning strategies, and action. Evidence for this exact chain is not yet direct, but strategy-enriched working-memory interventions are more promising than drill alone, and implementation-intention research shows that cue-linked “if–then” plans can improve goal attainment (Chan et al., 2019), (Gollwitzer & Sheeran, 2006).

Meaning for Trident G: prompts and missions are intended to connect trained control to use outside the exercise. No public IQ Pro mission-success report is currently presented; real-world outcome evidence will be added only when suitable reports exist.

06 Direct learning evidence

Spacing, consolidation, and delayed re-checks

Distributed practice is a robust route to more durable learning, while consolidation conditions can influence whether perceptual and motor learning generalises beyond the original task (Gerbier & Toppino, 2015), (Censor, 2013). A delayed check therefore carries more information than an immediate post-practice score because it asks whether the trained structure remains accessible after time and changed conditions.

Meaning for Trident G: short sessions, spacing, and later re-checks are evidence-aligned design choices. They improve the quality of a transfer test; they do not guarantee that transfer will occur.

What counts as proof

Research rationale, measures, and outcomes are different things

IQMindware does not treat a plausible mechanism, a training score, and an independent outcome as interchangeable.

Research foundation

Why each component is included

The studies above support constructs and design decisions: cognitive-control capacity, relational binding, relation processing, strategy use, variation, and consolidation.

Measure foundation

What a check can legitimately indicate

Zone Pulse is a behavioural readiness signal. Brief reasoning checks can track change, but a short internal measure is not a clinical assessment or a substitute for a professionally validated intelligence test.

Outcome proof

What would support stronger product claims

Stronger evidence would require appropriately validated pre/post outcomes, changed-task and delayed checks, suitable comparison conditions, and transparent reporting. No public IQ Pro cohort dataset is currently available.

Personal reports from earlier training

What users noticed in n-back implementations

These reports concern earlier n-back implementations in the protocol lineage, including relational variants now represented within Capacity Gym. They are not results from a current IQ Pro cohort and do not establish IQ gains or far transfer.

“I like your approach and I think you are actually putting emphasis on exactly the interventions that work.”
Yoni DonnerStanford University
“I could tell a marked improvement in my ability to block distractions and focus, which allowed me to keep more items in my workspace.”
Joshua Bridges

Individual results vary. Testimonials are personal reports, not controlled evidence or guarantees.

Claims boundary

What IQMindware does and does not claim

Supported positioning

  • Trains component capabilities involved in cognitive control, relational working memory, and reasoning.
  • Uses horizontal variation, vertical progression, and transfer-oriented re-checks by design.
  • Draws on published evidence for its component mechanisms.
  • Tests whether progress carries beyond one familiar exercise where suitable checks are available.

Not claimed

  • Guaranteed IQ gains or universal far transfer.
  • That rising game scores alone demonstrate improved intelligence.
  • Clinical outcomes, diagnosis, prevention, or treatment.
  • That component evidence proves the complete integrated programme.
Dr Mark Ashton Smith
Evidence stewardship

Protocol-led, with the limits stated

IQMindware was developed by Dr Mark Ashton Smith, a cognitive neuroscientist and former University of Cambridge psychology lecturer. The protocol grew from a long-running intervention question: how should cognitive training be designed if improvement is expected to survive changes in task, delay, reasoning demand, and practical use?

Research references

Sources used in this review

Links open the publisher or DOI record for each cited paper.

Censor, N. (2013). Generalization of perceptual and motor learning: A causal link with memory encoding and consolidation? Neuroscience, 250, 201–207. https://doi.org/10.1016/j.neuroscience.2013.06.062

Chan, S., Mueller, U., & Masson, M. E. J. (2019). Far-transfer effects of strategy-based working memory training. Frontiers in Psychology, 10, Article 1285. https://doi.org/10.3389/fpsyg.2019.01285

Chuderski, A. (2014). The relational integration task explains fluid reasoning above and beyond other working memory tasks. Memory & Cognition, 42, 448–463. https://doi.org/10.3758/s13421-013-0366-x

Gerbier, E., & Toppino, T. C. (2015). The effect of distributed practice: Neuroscience, cognition, and education. Trends in Neuroscience and Education, 4(3), 49–59. https://doi.org/10.1016/j.tine.2015.01.001

Gollwitzer, P. M., & Sheeran, P. (2006). Implementation intentions and goal achievement: A meta-analysis of effects and processes. Advances in Experimental Social Psychology, 38, 69–119. https://doi.org/10.1016/S0065-2601(06)38002-1

He, X., Qiu, B., Deng, Y., Liu, T., Chen, Y., & Zhang, W. (2022). Adaptive assessment of the capacity of cognitive control. Quarterly Journal of Experimental Psychology, 75(1), 43–52. https://doi.org/10.1177/17470218211030838

Jastrzębski, J., Ociepka, M., & Chuderski, A. (2020). Fluid reasoning is equivalent to relation processing. Intelligence, 82, Article 101489. https://doi.org/10.1016/j.intell.2020.101489

Klauer, K. J., & Phye, G. D. (2008). Inductive reasoning: A training approach. Review of Educational Research, 78(1), 85–123. https://doi.org/10.3102/0034654307313402

Larcombe, S. J., Kennard, C., & Bridge, H. (2017). Time course influences transfer of visual perceptual learning across spatial location. Vision Research, 135, 26–33. https://doi.org/10.1016/j.visres.2017.03.005

Melby-Lervåg, M., Redick, T. S., & Hulme, C. (2016). Working memory training does not improve performance on measures of intelligence or other measures of “far transfer”: Evidence from a meta-analytic review. Perspectives on Psychological Science, 11(4), 512–534. https://doi.org/10.1177/1745691616635612

Oberauer, K. (2019). Working memory capacity limits memory for bindings. Journal of Cognition, 2(1), Article 40. https://doi.org/10.5334/joc.86

Wang, Z., Sun, T., & Xiao, F. (2025). Relational integration training modulated the frontoparietal network for fluid intelligence: An EEG microstates study. Brain Topography, 38, Article 24. https://doi.org/10.1007/s10548-024-01099-3

Wu, T., Dufford, A. J., Mackie, M.-A., Egan, L. J., & Fan, J. (2016). The capacity of cognitive control estimated from a perceptual decision making task. Scientific Reports, 6, Article 34025. https://doi.org/10.1038/srep34025

Zhang, H., Fan, S., Yang, J., Yi, J., Guan, L., He, H., Zhang, X., Luo, Y., & Guan, Q. (2024). Attention control training and transfer effects on cognitive tasks. Neuropsychologia, 200, Article 108910. https://doi.org/10.1016/j.neuropsychologia.2024.108910

Zhang, J.-Y., Zhang, G.-L., Xiao, L.-Q., Klein, S. A., Levi, D. M., & Yu, C. (2010). Rule-based learning explains visual perceptual learning and its specificity and transfer. The Journal of Neuroscience, 30(37), 12323–12328. https://doi.org/10.1523/JNEUROSCI.0704-10.2010

Zhang, X.-Y., & Tang, C. (2025). Heavy-tailed update distributions arise from information-driven self-organization in nonequilibrium learning. Proceedings of the National Academy of Sciences of the United States of America, 122(51), Article e2523012122. https://doi.org/10.1073/pnas.2523012122

Current programme

Train with the full protocol

IQ Pro is the complete current IQMindware training programme built around the Trident G Far Transfer Protocol™. It includes Mission Arena and can be purchased directly.