Determining thresholds using adaptive procedures and psychometric fits: evaluating efficiency using theory, simulations, and human experiments

When measuring thresholds, careful selection of stimulus amplitude can increase efficiency by increasing the precision of psychometric fit parameters (e.g., decreasing the fit parameter error bars). To find efficient adaptive algorithms for psychometric threshold (“sigma”) estimation, we combined analytic approaches, Monte Carlo simulations, and human experiments for a one-interval, binary forced-choice, direction-recognition task. To our knowledge, this is the first time analytic results have been combined and compared with either simulation or human results. Human performance was consistent with theory and not significantly different from simulation predictions. Our analytic approach provides a bound on efficiency, which we compared against the efficiency of standard staircase algorithms, a modified staircase algorithm with asymmetric step sizes, and a maximum likelihood estimation (MLE) procedure. Simulation results suggest that optimal efficiency at determining threshold is provided by the MLE procedure targeting a fraction correct level of 0.92, an asymmetric 4-down, 1-up staircase targeting between 0.86 and 0.92 or a standard 6-down, 1-up staircase. Psychometric test efficiency, computed by comparing simulation and analytic results, was between 41 and 58 % for 50 trials for these three algorithms, reaching up to 84 % for 200 trials. These approaches were 13–21 % more efficient than the commonly used 3-down, 1-up symmetric staircase. We also applied recent advances to reduce accuracy errors using a bias-reduced fitting approach. Taken together, the results lend confidence that the assumptions underlying each approach are reasonable and that human threshold forced-choice decision making is modeled well by detection theory models and mimics simulations based on detection theory models.National Institute on Deafness and Other Communication Disorders (U.S.) (Grants R01-DC04158, R56-DC12038 and R03-DC013635

Selective Activation of Methane on Single-Atom Catalyst of Rhodium Dispersed on Zirconia for Direct Conversion

Direct methane conversion into value-added products has become increasingly important. Because of inertness of methane, cleaving the first C–H bond has been very difficult, requiring high reaction temperature on the heterogeneous catalysts. Once the first C–H bond becomes activated, the remaining C–H bonds are successively dissociated on the metal surface, hindering the direct methane conversion into chemicals. Here, a single-atom Rh catalyst dispersed on ZrO₂ surface has been synthesized and used for selective activation of methane. The Rh single atomic nature was confirmed by extended X-ray fine structure analysis, electron microscopy images, and diffuse reflectance infrared Fourier transform spectroscopy. A model of the single-atom Rh/ZrO₂ catalyst was constructed by density functional theory calculations, and it was shown that CH₃ intermediates can be energetically stabilized on the single-atom catalyst. The direct conversion of methane was performed using H₂O₂ in the aqueous solution or using O₂ in gas phase as oxidants. Whereas Rh nanoparticles produced CO₂ only, the single-atom Rh catalyst produced methanol in aqueous phase or ethane in gas phase