Titrating decision processes in the mental rotation task.
DOI: 10.1037/a0039706
archive: archived pipeline: cataloged verified
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Summary
This paper presents the first comprehensive quantitative model of behavior in the Shepard and Metzler (1971) mental rotation task, addressing the need to simultaneously account for error rates and the full distribution of response times (RTs). While previous research has extensively examined spatial cognition using this task, existing models often focused only on mean RTs or failed to distinguish between mental rotation processes and decision-making stages. The authors aim to provide a finer-grained decomposition of the task by separating the latent mental rotation stage from the response-selection process, thereby offering a more complete account of cognitive performance than traditional regression approaches. To achieve this, the authors employed the linear ballistic accumulator (LBA) model, a cognitive model of choice processing, to "titrate" out the effects of the decision stage. They applied this framework to data from Provost et al. (2013), specifically the final session of their second experiment. This dataset was selected because converging evidence from event-related potentials and transfer testing indicated that participants relied on a general-purpose mental rotation skill rather than stimulus-specific strategies or alternative shortcuts. The stimuli were modified block figures with a long major axis, ensuring that rotation angles were well-defined for both matching and mismatching (mirror) stimuli. The authors tested three specific models of the rotation stage: a multiple-rotation model (gamma distribution), a single-rotation model (lognormal distribution), and a deterministic-rotation model. The results supported a mental rotation stage consistent with Larsen’s (2014) model, where rotation time is variable, with both mean and variance increasing linearly with the rotation angle. The analysis revealed that differences in response thresholds, rather than rotation speed, were largely responsible for the slowing of mirror responses compared to normal responses. Additionally, these threshold differences accounted for the increase in errors with rotation angle observed in some participants. The study replicated previous findings that mismatch judgments are slower than match judgments and that the slope of the rotation function is steeper for mismatches. The model successfully accounted for the full distribution of RTs and error rates for both match and mismatch conditions, providing a robust fit to the behavioral data. The significance of this work lies in its ability to disentangle the cognitive processes underlying mental rotation. By using the LBA to isolate decision processes, the authors demonstrated that the traditional interpretation of RT slopes as purely reflecting rotation speed is incomplete; decision thresholds play a critical role in performance differences between normal and mirror judgments. This approach offers a more precise understanding of spatial cognition, validating the view that mental imagery involves simulated perception with variable processing times. The findings also clarify the mechanisms behind the linear RT-angle relationship and the specific costs associated with mirror-image judgments, advancing the theoretical modeling of spatial tasks.
Key finding
Mental rotation performance is best explained by a process where rotation time mean and variance increase linearly with angle, while decision threshold differences account for slower mirror-image responses.
Methodology
modeling
Sample size: 11
Provenance
The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed. Discovered via author_sweep_intake on 2026-05-28.
| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | author_sweep | — | — | 2 | 2026-05-28 |
| archive | success | canonical_url | — | — | 5 | 2026-06-06 |
| extract | success | cached | — | — | 3 | 2026-06-10 |
| clean | success | clean | — | — | 1 | 2026-06-04 |
| chunk | success | chunk | — | — | 1 | 2026-06-04 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-04 |
| enrich | success | — | — | — | 1 | 2026-05-28 |
| promote | success | — | — | — | 1 | 2026-06-04 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 2 | 2026-06-10 |
| tag | success | vector_similarity | — | — | 15 | 2026-06-11 |
| verify | success | — | — | — | 2 | 2026-06-10 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.
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