Potsdam Cognitive Science Series, ISSN 2190-4553
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Proceedings of KogWis 2010 : 10th Biannual Meeting of the German Society for Cognitive Science
(2010)
As the latest biannual meeting of the German Society for Cognitive Science (Gesellschaft für Kognitionswissenschaft, GK), KogWis 2010 at Potsdam University reflects the current trends in a fascinating domain of research concerned with human and artificial cognition and the interaction of mind and brain. The Plenary talks provide a venue for questions of the numerical capacities and human arithmetic (Brian Butterworth), of the theoretical development of cognitive architectures and intelligent virtual agents (Pat Langley), of categorizations induced by linguistic constructions (Claudia Maienborn), and of a cross-level account of the “Self as a complex system“ (Paul Thagard). KogWis 2010 integrates a wealth of experimental research, cognitive modelling, and conceptual analysis in 5 invited symposia, over 150 individual talks, 6 symposia, and more than 40 poster contributions. Some of the invited symposia reflect local and regional strenghts of research in the Berlin-Brandenburg area: the two largests research fields of the university Cognitive Sciences Area of Excellence in Potsdam are represented by an invited symposium on “Information Structure” by the Special Research Area 632 (“Sonderforschungsbereich”, SFB) of the same name, of Potsdam University and Humboldt-University Berlin, and by a satellite conference of the research group “Mind and Brain Dynamics”. The Berlin School of Mind and Brain at Humboldt-University Berlin takes part with an invited symposium on “Decision Making” from a perspective of cognitive neuroscience and philosophy and the DFG Cluster of Excellence “Languages of Emotion” of Free University presents interdisciplinary research results in an invited symposium on “Symbolising Emotions”.
Experimental and quantitative research in the field of human language processing and production strongly depends on the quality of the underlying language material: beside its size, representativeness, variety and balance have been discussed as important factors which influence design, analysis and interpretation of experiments and their results. This volume brings together creators and users of both general purpose and specialized lexical resources which are used in psychology, psycholinguistics, neurolinguistics and cognitive research. It aims to be a forum to report experiences and results, review problems and discuss perspectives of any linguistic data used in the field.
Microsaccades
(2015)
The first thing we do upon waking is open our eyes. Rotating them in our eye sockets, we scan our surroundings and collect the information into a picture in our head. Eye movements can be split into saccades and fixational eye movements, which occur when we attempt to fixate our gaze. The latter consists of microsaccades, drift and tremor. Before we even lift our eye lids, eye movements – such as saccades and microsaccades that let the eyes jump from one to another position – have partially been prepared in the brain stem. Saccades and microsaccades are often assumed to be generated by the same mechanisms. But how saccades and microsaccades can be classified according to shape has not yet been reported in a statistical manner. Research has put more effort into the investigations of microsaccades’ properties and generation only since the last decade. Consequently, we are only beginning to understand the dynamic processes governing microsaccadic eye movements. Within this thesis, the dynamics governing the generation of microsaccades is assessed and the development of a model for the underlying processes. Eye movement trajectories from different experiments are used, recorded with a video-based eye tracking technique, and a novel method is proposed for the scale-invariant detection of saccades (events of large amplitude) and microsaccades (events of small amplitude). Using a time-frequency approach, the method is examined with different experiments and validated against simulated data. A shape model is suggested that allows for a simple estimation of saccade- and microsaccade related properties. For sequences of microsaccades, in this thesis a time-dynamic Markov model is proposed, with a memory horizon that changes over time and which can best describe sequences of microsaccades.
In reading, word frequency is commonly regarded as the major bottom-up determinant for the speed of lexical access. Moreover, language processing depends on top-down information, such as the predictability of a word from a previous context. Yet, however, the exact role of top-down predictions in visual word recognition is poorly understood: They may rapidly affect lexical processes, or alternatively, influence only late post-lexical stages. To add evidence about the nature of top-down processes and their relation to bottom-up information in the timeline of word recognition, we examined influences of frequency and predictability on event-related potentials (ERPs) in several sentence reading studies. The results were related to eye movements from natural reading as well as to models of word recognition. As a first and major finding, interactions of frequency and predictability on ERP amplitudes consistently revealed top-down influences on lexical levels of word processing (Chapters 2 and 4). Second, frequency and predictability mediated relations between N400 amplitudes and fixation durations, pointing to their sensitivity to a common stage of word recognition; further, larger N400 amplitudes entailed longer fixation durations on the next word, a result providing evidence for ongoing processing beyond a fixation (Chapter 3). Third, influences of presentation rate on ERP frequency and predictability effects demonstrated that the time available for word processing critically co-determines the course of bottom-up and top-down influences (Chapter 4). Fourth, at a near-normal reading speed, an early predictability effect suggested the rapid comparison of top-down hypotheses with the actual visual input (Chapter 5). The present results are compatible with interactive models of word recognition assuming that early lexical processes depend on the concerted impact of bottom-up and top-down information. We offered a framework that reconciles the findings on a timeline of word recognition taking into account influences of frequency, predictability, and presentation rate (Chapter 4).
This dissertation addresses the question of how linguistic structures can be represented in working memory. We propose a memory-based computational model that derives offline and online complexity profiles in terms of a top-down parser for minimalist grammars (Stabler, 2011). The complexity metric reflects the amount of time an item is stored in memory. The presented architecture links grammatical representations stored in memory directly to the cognitive behavior by deriving predictions about sentence processing difficulty.
Results from five different sentence comprehension experiments were used to evaluate the model's assumptions about memory limitations. The predictions of the complexity metric were compared to the locality (integration and storage) cost metric of Dependency Locality Theory (Gibson, 2000). Both metrics make comparable offline and online predictions for four of the five phenomena. The key difference between the two metrics is that the proposed complexity metric accounts for the structural complexity of intervening material. In contrast, DLT's integration cost metric considers the number of discourse referents, not the syntactic structural complexity.
We conclude that the syntactic analysis plays a significant role in memory requirements of parsing. An incremental top-down parser based on a grammar formalism easily computes offline and online complexity profiles, which can be used to derive predictions about sentence processing difficulty.
This dissertation uses a common grammatical phenomenon, light verb constructions (LVCs) in English and German, to investigate how syntax-semantics mapping defaults influence the relationships between language processing, representation and conceptualization. LVCs are analyzed as a phenomenon of mismatch in the argument structure. The processing implication of this mismatch are experimentally investigated, using ERPs and a dual task. Data from these experiments point to an increase in working memory. Representational questions are investigated using structural priming. Data from this study suggest that while the syntax of LVCs is not different from other structures’, the semantics and mapping are represented differently. This hypothesis is tested with a new categorization paradigm, which reveals that the conceptual structure that LVC evoke differ in interesting, and predictable, ways from non-mismatching structures’.