Learning decouples accuracy and reaction time for rapid decisions in a transitive inference task
Abstract
Transitive inference (TI) is a cognitive process in which decisions are guided by internal representations of abstract relationships. While the mechanisms underlying transitive learning have been well studied, the dynamics of the decision-making process during learning and inference remain less clearly understood. In this study, we investigated whether a modeling framework traditionally applied to perceptual decision-making-the drift diffusion model (DDM)-can account for performance in a TI transfer task involving rapid decisions that deviate from standard accuracy and response time (RT) patterns. We trained three macaque monkeys on a TI transfer task, in which they learned the implied order of a novel list of seven images in each behavioral session. Monkeys indicated their decisions with saccadic eye movements. Consistent learning of the list structure was achieved within 200-300 trials per session, with asymptotic accuracies reaching approximately 80-90%. Behavioral performance exhibited a symbolic distance effect, with accuracy increasing as the ordinal distance between items grew. Notably, RTs remained relatively stable across learning, despite improvements in accuracy. We applied a generalized DDM implementation (PyDDM; Shinn et al., 2020) to jointly fit accuracy and RT data. Model fits were achieved by incorporating both an increasing evidence accumulation rate and a collapsing decision bound, successfully capturing the RT distribution shapes observed during learning.…
How strong is the evidence?
Evidence Hub reads this as a preprint, done in animal, not in people. Its evidence level is 5 of 5 (Very low · case / narrative / animal / in vitro / in silico). Case reports, narrative reviews, and animal, cell or computer-model studies give the weakest evidence for human health.
Read the paper
Related studies
- Learning from First-Generation Qualitative Approaches in the IS Discipline: An Evolutionary View and Some Implications for Authors and Evaluators (PART 1/2)
- Commentary on the clinical and preclinical dosage limits of interstitially administered magnetic fluids for therapeutic hyperthermia based on current practice and efficacy models
- Prosthesis: New Technological Opportunities and Innovative Biomedical Devices
- The history and future of neural modeling for cochlear implants
- Ryanodine receptors: waking up from refractoriness
- Novel Transgenic Rabbit Model Sheds Light on the Puzzling Role of Matrix Metalloproteinase-12 in Atherosclerosis
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.