@phdthesis{Schwetlick2023,
  author    = {Schwetlick, Lisa},
  title     = {Data assimilation for neurocognitive models of eye movement},
  doi       = {10.25932/publishup-59828},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-598280},
  school      = {Universit{\"a}t Potsdam},
  pages     = {x, 209},
  year      = {2023},
  abstract  = {Visual perception is a complex and dynamic process that plays a crucial role in how we perceive and interact with the world. The eyes move in a sequence of saccades and fixations, actively modulating perception by moving different parts of the visual world into focus. Eye movement behavior can therefore offer rich insights into the underlying cognitive mechanisms and decision processes. Computational models in combination with a rigorous statistical framework are critical for advancing our understanding in this field, facilitating the testing of theory-driven predictions and accounting for observed data. In this thesis, I investigate eye movement behavior through the development of two mechanistic, generative, and theory-driven models. The first model is based on experimental research regarding the distribution of attention, particularly around the time of a saccade, and explains statistical characteristics of scan paths. The second model implements a self-avoiding random walk within a confining potential to represent the microscopic fixational drift, which is present even while the eye is at rest, and investigates the relationship to microsaccades. Both models are implemented in a likelihood-based framework, which supports the use of data assimilation methods to perform Bayesian parameter inference at the level of individual participants, analyses of the marginal posteriors of the interpretable parameters, model comparisons, and posterior predictive checks. The application of these methods enables a thorough investigation of individual variability in the space of parameters. Results show that dynamical modeling and the data assimilation framework are highly suitable for eye movement research and, more generally, for cognitive modeling.},
  language  = {en}
}
@phdthesis{Chandra2020,
  author    = {Chandra, Johan},
  title     = {The role of the oculomotor control in eye movements during reading},
  doi       = {10.25932/publishup-47593},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-475930},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xiii, 115},
  year      = {2020},
  abstract  = {Most reading theories assume that readers aim at word centers for optimal information processing. During reading, saccade targeting turns out to be imprecise: Saccades' initial landing positions often miss the word centers and have high variance, with an additional systematic error that is modulated by the distance from the launch site to the center of the target word. The performance of the oculomotor system, as reflected in the statistics of within-word landing positions, turns out to be very robust and mostly affected by the spatial information during reading. Hence, it is assumed that the saccade generation is highly automated. The main goal of this thesis is to explore the performance of the oculomotor system under various reading conditions where orthographic information and the reading direction were manipulated. Additionally, the challenges in understanding the eye movement data to represent the oculomotor process during reading are addressed. Two experimental studies and one simulation study were conducted for this thesis, which resulted in the following main findings: (i) Reading texts with orthographic manipulations leads to specific changes in the eye movement patterns, both in temporal and spatial measures. The findings indicate that the oculomotor control of eye movements during reading is dependent on reading conditions (Chapter 2 \& 3). (ii) Saccades' accuracy and precision can be simultaneously modulated under reversed reading condition, supporting the assumption that the random and systematic oculomotor errors are not independent. By assuming that readers increase the precision of sensory observation while maintaining the learned prior knowledge when reading direction was reversed, a process-oriented Bayesian model for saccade targeting can account for the simultaneous reduction of oculomotor errors (Chapter 2). (iii) Plausible parameter values serving as proxies for the intended within-word landing positions can be estimated by using the maximum a posteriori estimator from Bayesian inference. Using the mean value of all observations as proxies is insufficient for studies focusing on the launch-site effect because the method exhibits the strongest bias when estimating the size of the effect. Mislocated fixations remain a challenge for the currently known estimation methods, especially when the systematic oculomotor error is large (Chapter 4). The results reported in this thesis highlight the role of the oculomotor system, together with underlying cognitive processes, in eye movements during reading. The modulation of oculomotor control can be captured through a precise analysis of landing positions.},
  language  = {en}
}
@phdthesis{Seelig2021,
  author    = {Seelig, Stefan},
  title     = {Parafoveal processing of lexical information during reading},
  doi       = {10.25932/publishup-50874},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-508743},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xi, 113},
  year      = {2021},
  abstract  = {During sentence reading the eyes quickly jump from word to word to sample visual information with the high acuity of the fovea. Lexical properties of the currently fixated word are known to affect the duration of the fixation, reflecting an interaction of word processing with oculomotor planning. While low level properties of words in the parafovea can likewise affect the current fixation duration, results concerning the influence of lexical properties have been ambiguous (Drieghe, Rayner, \& Pollatsek, 2008; Kliegl, Nuthmann, \& Engbert, 2006). Experimental investigations of such lexical parafoveal-on-foveal effects using the boundary paradigm have instead shown, that lexical properties of parafoveal previews affect fixation durations on the upcoming target words (Risse \& Kliegl, 2014). However, the results were potentially confounded with effects of preview validity. The notion of parafoveal processing of lexical information challenges extant models of eye movements during reading. Models containing serial word processing assumptions have trouble explaining such effects, as they usually couple successful word processing to saccade planning, resulting in skipping of the parafoveal word. Although models with parallel word processing are less restricted, in the SWIFT model (Engbert, Longtin, \& Kliegl, 2002) only processing of the foveal word can directly influence the saccade latency. Here we combine the results of a boundary experiment (Chapter 2) with a predictive modeling approach using the SWIFT model, where we explore mechanisms of parafoveal inhibition in a simulation study (Chapter 4). We construct a likelihood function for the SWIFT model (Chapter 3) and utilize the experimental data in a Bayesian approach to parameter estimation (Chapter 3 \& 4). The experimental results show a substantial effect of parafoveal preview frequency on fixation durations on the target word, which can be clearly distinguished from the effect of preview validity. Using the eye movement data from the participants, we demonstrate the feasibility of the Bayesian approach even for a small set of estimated parameters, by comparing summary statistics of experimental and simulated data. Finally, we can show that the SWIFT model can account for the lexical preview effects, when a mechanism for parafoveal inhibition is added. The effects of preview validity were modeled best, when processing dependent saccade cancellation was added for invalid trials. In the simulation study only the control condition of the experiment was used for parameter estimation, allowing for cross validation. Simultaneously the number of free parameters was increased. High correlations of summary statistics demonstrate the capabilities of the parameter estimation approach. Taken together, the results advocate for a better integration of experimental data into computational modeling via parameter estimation.},
  language  = {en}
}
@misc{Blum2021,
  type      = {Master Thesis},
  author    = {Blum, Franziska},
  title     = {I see you smile, you must be happy! Social-emotional gains and usability evaluation of the new training tool E.V.A.: A pilot study},
  doi       = {10.25932/publishup-50550},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-505509},
  school      = {Universit{\"a}t Potsdam},
  pages     = {XIX, 80},
  year      = {2021},
  abstract  = {Emotions are a complex concept and they are present in our everyday life. Persons on the autism spectrum are said to have difficulties in social interactions, showing deficits in emotion recognition in comparison to neurotypically developed persons. But social-emotional skills are believed to be positively augmented by training. A new adaptive social cognition training tool "E.V.A." is introduced which teaches emotion recognition from face, voice and body language. One cross-sectional and one longitudinal study with adult neurotypical and autistic participants were conducted. The aim of the cross-sectional study was to characterize the two groups and see if differences in their social-emotional skills exist. The longitudinal study, on the other hand, aimed for detecting possible training effects following training with the new training tool. In addition, in both studies usability assessments were conducted to investigate the perceived usability of the new tool for neurotypical as well as autistic participants. Differences were found between autistic and neurotypical participants in their social-emotional and emotion recognition abilities. Training effects for neurotypical participants in an emotion recognition task were found after two weeks of home training. Similar perceived usability was found for the neurotypical and autistic participants. The current findings suggest that persons with ASC do not have a general deficit in emotion recognition, but are in need for more time to correctly recognize emotions. In addition, findings suggest that training emotion recognition abilities is possible. Further studies are needed to verify if the training effects found for neurotypical participants also manifest in a larger ASC sample.},
  language  = {en}
}
@misc{Galetzka2018,
  type      = {Master Thesis},
  author    = {Galetzka, Cedric},
  title     = {Reward and prediction errors in Bayesian sensorimotor control},
  doi       = {10.25932/publishup-50350},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-503507},
  school      = {Universit{\"a}t Potsdam},
  pages     = {53},
  year      = {2018},
  abstract  = {Midbrain dopamine neurons invigorate responses by signaling opportunity costs (tonic dopamine) and promote associative learning by encoding a reward prediction error signal (phasic dopamine). Recent studies on Bayesian sensorimotor control have implicated midbrain dopamine concentration in the integration of prior knowledge and current sensory information. The present behavioral study addressed the contributions of tonic and phasic dopamine in a Bayesian decision-making task by alternating reward magnitude and inferring reward prediction errors. Twenty-four participants were asked to indicate the position of a hidden target stimulus under varying prior and likelihood uncertainty. Trial-by-trial rewards were allocated based on performance and two different reward maxima. Overall, participants' behavior agreed with Bayesian decision theory, but indicated excessive reliance on likelihood information. These results thus oppose accounts of statistically optimal integration in sensorimotor control, and suggest that the sensorimotor system is subject to additional decision heuristics. Moreover, higher reward magnitude was not observed to induce enhanced response vigor, and was associated with less Bayes-like integration. In addition, the weighting of prior knowledge and current sensory information proceeded independently of reward prediction errors. Taken together, these findings suggest that the process of combining prior and likelihood uncertainties in sensorimotor control is largely robust to variations in reward.},
  language  = {en}
}
@phdthesis{Rabe2024,
  author    = {Rabe, Maximilian Michael},
  title     = {Modeling the interaction of sentence processing and eye-movement control in reading},
  doi       = {10.25932/publishup-62279},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-622792},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xiii, 171},
  year      = {2024},
  abstract  = {The evaluation of process-oriented cognitive theories through time-ordered observations is crucial for the advancement of cognitive science. The findings presented herein integrate insights from research on eye-movement control and sentence comprehension during reading, addressing challenges in modeling time-ordered data, statistical inference, and interindividual variability. Using kernel density estimation and a pseudo-marginal likelihood for fixation durations and locations, a likelihood implementation of the SWIFT model of eye-movement control during reading (Engbert et al., Psychological Review, 112, 2005, pp. 777-813) is proposed. Within the broader framework of data assimilation, Bayesian parameter inference with adaptive Markov Chain Monte Carlo techniques is facilitated for reliable model fitting. Across the different studies, this framework has shown to enable reliable parameter recovery from simulated data and prediction of experimental summary statistics. Despite its complexity, SWIFT can be fitted within a principled Bayesian workflow, capturing interindividual differences and modeling experimental effects on reading across different geometrical alterations of text. Based on these advancements, the integrated dynamical model SEAM is proposed, which combines eye-movement control, a traditionally psychological research area, and post-lexical language processing in the form of cue-based memory retrieval (Lewis \& Vasishth, Cognitive Science, 29, 2005, pp. 375-419), typically the purview of psycholinguistics. This proof-of-concept integration marks a significant step forward in natural language comprehension during reading and suggests that the presented methodology can be useful to develop complex cognitive dynamical models that integrate processes at levels of perception, higher cognition, and (oculo-)motor control. These findings collectively advance process-oriented cognitive modeling and highlight the importance of Bayesian inference, individual differences, and interdisciplinary integration for a holistic understanding of reading processes. Implications for theory and methodology, including proposals for model comparison and hierarchical parameter inference, are briefly discussed.},
  language  = {en}
}