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Articles 1 - 4 of 4
Full-Text Articles in Quantitative Psychology
Finding The Ghost With The Machine: Breaking Through The Assessment Center Validity Ceiling By Exploring Decisional Processes Using New Sources Of Behavioral Data Within Virtual Assessments, Brett W. Guidry
Open Access Dissertations
Decades of assessment center (AC) research has resulted in an inevitable “validity ceiling” whereby increasing the validity of the AC method is becoming increasingly difficult. To overcome this challenge, new avenues for collecting and evaluating AC participant behaviors must be explored, with a particular focus on overcoming the inherent limitations of human observation—a hallmark of the AC method. This study examines detailed logs of AC participant behaviors captured automatically and unobtrusively during a computer-based simulation assessment. Using a decision making framework, basic characteristics of the new behavioral data are tested against existing theories of decisional efficacy. The construct-related validity of …
Parametrically Constrained Lightness Model Incorporating Edge Classification And Increment-Decrement Neural Response Asymmetries, Michael E. Rudd
Parametrically Constrained Lightness Model Incorporating Edge Classification And Increment-Decrement Neural Response Asymmetries, Michael E. Rudd
MODVIS Workshop
Lightness matching data from disk-annulus experiments has the form of a parabolic (2nd-order polynomial) function when matches are plotted against annulus luminance on log-log axes. Rudd (2010) has proposed a computational cortical model to account for this fact and has subsequently (Rudd, 2013, 2014, 2015) extended the model to explain data from other lightness paradigms, including staircase-Gelb and luminance gradient illusions (Galmonte, Soranzo, Rudd, & Agostini, 2015). Here, I re-analyze parametric lightness matching data from disk-annulus experiments by Rudd and Zemach (2007) and Rudd (2010) for the purpose of further testing the model and to try to constrain …
An Image-Based Model For Early Visual Processing, Heiko H. Schütt, Felix A. Wichmann
An Image-Based Model For Early Visual Processing, Heiko H. Schütt, Felix A. Wichmann
MODVIS Workshop
No abstract provided.
A Learning Model For L/M Specificity In Ganglion Cells, Albert Ahumada
A Learning Model For L/M Specificity In Ganglion Cells, Albert Ahumada
MODVIS Workshop
An unsupervised learning model for developing L/M specific wiring at the ganglion cell level would support the research indicating L/M specific wiring at the ganglion cell level (Reid and Shapley, 2002). Removing the contributions to the surround from cells of the same cone type improves the signal-to-noise ratio of the chromatic signals. The unsupervised learning model used is Hebbian associative learning, which strengthens the surround input connections according to the correlation of the output with the input. Since the surround units of the same cone type as the center are redundant with the center, their weights end up disappearing. This …