Weber's law is the canonical scale-invariance law in psychology: when the intensities of 2 stimuli are scaled by any value k, the just-noticeable-difference between them also scales by k. A diffusion model that approximates a spike-counting process accounts for Weber's law (Link, 1992), but there exist surprising corollaries of this account that have not yet been described or tested. We show that (a) this spike-counting diffusion model predicts time-scale invariant decision time distributions in perceptual decision making, and time-scale invariant response time (RT) distributions in interval timing; (b) for 2-choice perceptual decisions, the model predicts equal accuracy but faster responding for stimulus pairs with equally scaled-up intensities; (c) the coefficient of variation (CV) of decision times should remain constant across average intensity scales, but should otherwise decrease as a specific function of stimulus discriminability and speed-accuracy trade-off; and (d) for timing tasks, RT CVs should be constant for all durations, and RT skewness should always equal 3 times the CV. We tested these predictions using visual, auditory and vibrotactile decision tasks and visual interval timing tasks in humans. The data conformed closely to the predictions in all modalities. These results support a unified theory of decision making and timing in terms of a common, underlying spike-counting process, compactly represented as a diffusion process.
Perceptual decision making has been successfully modeled as a process of evidence accumulation up to a threshold. In order to maximize the rewards earned for correct responses in tasks with response deadlines, participants should collapse decision thresholds dynamically during each trial so that a decision is reached before the deadline. This strategy ensures on-time responding, though at the cost of reduced accuracy, since slower decisions are based on lower thresholds and less net evidence later in a trial (compared to a constant threshold). Frazier and Yu (2008) showed that the normative rate of threshold reduction depends on deadline delays and on participants' uncertainty about these delays. Participants should start collapsing decision thresholds earlier when making decisions under shorter deadlines (for a given level of timing uncertainty) or when timing uncertainty is higher (for a given deadline). We tested these predictions using human participants in a random dot motion discrimination task. Each participant was tested in free-response, short deadline (800 ms), and long deadline conditions (1000 ms). Contrary to optimal-performance predictions, the resulting empirical function relating accuracy to response time (RT) in deadline conditions did not decline to chance level near the deadline; nor did the slight decline we typically observed relate to measures of endogenous timing uncertainty. Further, although this function did decline slightly with increasing RT, the decline was explainable by the best-fitting parameterization of Ratcliff's diffusion model (Ratcliff, 1978), whose parameters are constant within trials. Our findings suggest that at the very least, typical decision durations are too short for participants to adapt decision parameters within trials.
Characterizing the complexities of early cortical thickness development has been an ongoing undertaking. Longitudinal studies of Non-Human Primates (NHP) offer unique advantages to identifying cortical growth trajectories. Here, we used latent growth models to characterize the trajectories of typical cortical thickness development in Japanese macaques at each cortical surface vertex (i.e., grayordinate). Cortical thickness from 4-to-36 months showed regional-specific linear and non-linear trajectories and distinct maturation timing across the cortex. We revealed an “accumulation/ablation phenomenon” where the most profound development changes occur in zones surrounding focal points of local maxima in cortical thickness or thinness throughout the brain. We further examined maternal diet and inflammation in the context of typical brain trajectories and known network architecture. A well-controlled NHP model of a maternal “Western-style” diet was used alongside measures of inflammatory cytokine interleukin-6 in the mothers during gestation. We observed that accumulation and ablation zones might be most susceptible to environmental effects. The maternal factors, diet, and inflammation during pregnancy were distinctively associated with different aspects of offspring cortical development reflected in regions related to distinctive functional networks. Our findings characterize the intricacies of typical cortical thickness development and highlight how the maternal environment plays a role in cortical development.
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