TY  - JOUR
A1  - Schütt, Heiko Herbert
A1  - Rothkegel, Lars Oliver Martin
A1  - Trukenbrod, Hans Arne
A1  - Reich, Sebastian
A1  - Wichmann, Felix A.
A1  - Engbert, Ralf
T1  - Likelihood-based parameter estimation and comparison of dynamical cognitive models
JF  - Psychological Review
N2  - Dynamical models of cognition play an increasingly important role in driving theoretical and experimental research in psychology. Therefore, parameter estimation, model analysis and comparison of dynamical models are of essential importance. In this article, we propose a maximum likelihood approach for model analysis in a fully dynamical framework that includes time-ordered experimental data. Our methods can be applied to dynamical models for the prediction of discrete behavior (e.g., movement onsets); in particular, we use a dynamical model of saccade generation in scene viewing as a case study for our approach. For this model, the likelihood function can be computed directly by numerical simulation, which enables more efficient parameter estimation including Bayesian inference to obtain reliable estimates and corresponding credible intervals. Using hierarchical models inference is even possible for individual observers. Furthermore, our likelihood approach can be used to compare different models. In our example, the dynamical framework is shown to outperform nondynamical statistical models. Additionally, the likelihood based evaluation differentiates model variants, which produced indistinguishable predictions on hitherto used statistics. Our results indicate that the likelihood approach is a promising framework for dynamical cognitive models.
KW  - likelihood
KW  - model fitting
KW  - dynamical model
KW  - eye movements
KW  - model comparison
Y1  - 2017
U6  - https://doi.org/10.1037/rev0000068
SN  - 0033-295X
SN  - 1939-1471
VL  - 124
IS  - 4
SP  - 505
EP  - 524
PB  - American Psychological Association
CY  - Washington
ER  - 
TY  - JOUR
A1  - Rothkegel, Lars Oliver Martin
A1  - Trukenbrod, Hans Arne
A1  - Schütt, Heiko Herbert
A1  - Wichmann, Felix A.
A1  - Engbert, Ralf
T1  - Temporal evolution of the central fixation bias in scene viewing
JF  - Journal of vision
N2  - When watching the image of a natural scene on a computer screen, observers initially move their eyes toward the center of the image—a reliable experimental finding termed central fixation bias. This systematic tendency in eye guidance likely masks attentional selection driven by image properties and top-down cognitive processes. Here, we show that the central fixation bias can be reduced by delaying the initial saccade relative to image onset. In four scene-viewing experiments we manipulated observers' initial gaze position and delayed their first saccade by a specific time interval relative to the onset of an image. We analyzed the distance to image center over time and show that the central fixation bias of initial fixations was significantly reduced after delayed saccade onsets. We additionally show that selection of the initial saccade target strongly depended on the first saccade latency. A previously published model of saccade generation was extended with a central activation map on the initial fixation whose influence declined with increasing saccade latency. This extension was sufficient to replicate the central fixation bias from our experiments. Our results suggest that the central fixation bias is generated by default activation as a response to the sudden image onset and that this default activation pattern decreases over time. Thus, it may often be preferable to use a modified version of the scene viewing paradigm that decouples image onset from the start signal for scene exploration to explicitly reduce the central fixation bias.
KW  - eye movements
KW  - dynamic models
KW  - visual scanpath
KW  - visual attention
Y1  - 2017
U6  - https://doi.org/10.1167/17.13.3
SN  - 1534-7362
VL  - 17
SP  - 1626
EP  - 1638
PB  - Association for Research in Vision and Opthalmology
CY  - Rockville
ER  -