Time Course and Hazard Function: A Distributional Analysis of Fixation Duration in Reading

Reading processes affect not only the mean of fixation duration but also its distribution function. This paper introduces a set of hypotheses that link the timing and strength of a reading process to the hazard function of a fixation duration distribution. Analyses based on large corpora of reading eye movements show a surprisingly robust hazard function across languages, age, individual differences, and a number of processing variables. The data suggest that eye movements are generated stochastically based on a stereotyped time course that is independent of reading variables. High-level reading processes, however, modulate eye movement programming by increasing or decreasing the momentary saccade rate during a narrow time window. Implications to theories and analyses of reading eye movement are discussed

A Theory of Reaction Time Distributions

We develop a general theory of reaction time (RT) distributions in psychological experiments, deriving from the distribution of the quotient of two normal random variables, that of the task difficulty (top-down information), and that of the external evidence that becomes available to solve it (bottom-up information). The theory provides a unied account of known changes in the shape of the distributions depending on properties of the task and of the participants, and it predicts additional changes that should be observed. A number of known properties of RT distributions are homogeneously accounted\ud for by variations in the value of two easily interpretable parameters: the coefficients of variation of the two normal variables. The predictions of the theory are compared with those of multiple families of distributions that have been proposed to account for RTs, indicating our theory provides a significantly better account of experimental data. For this purpose, we provide comparisons with four large datasets across tasks and modalitities. Finally,\ud we show how the theory links to neurobiological models of response latencies

How does rumination impact cognition? A first mechanistic model.

Rumination is a process of uncontrolled, narrowly-foused neg- ative thinking that is often self-referential, and that is a hall- mark of depression. Despite its importance, little is known about its cognitive mechanisms. Rumination can be thought of as a specific, constrained form of mind-wandering. Here, we introduce a cognitive model of rumination that we devel- oped on the basis of our existing model of mind-wandering. The rumination model implements the hypothesis that rumina- tion is caused by maladaptive habits of thought. These habits of thought are modelled by adjusting the number of memory chunks and their associative structure, which changes the se- quence of memories that are retrieved during mind-wandering, such that during rumination the same set of negative memo- ries is retrieved repeatedly. The implementation of habits of thought was guided by empirical data from an experience sam- pling study in healthy and depressed participants. On the ba- sis of this empirically-derived memory structure, our model naturally predicts the declines in cognitive task performance that are typically observed in depressed patients. This study demonstrates how we can use cognitive models to better un- derstand the cognitive mechanisms underlying rumination and depression

A computational model of focused attention meditation and its transfer to a sustained attention task

Although meditation and mindfulness practices are widely discussed and studied more and more in the scientific literature, there is little theory about the cognitive mechanisms that comprise it. Here we begin to develop such a theory by creating a computational cognitive model of a particular type of meditation: focused attention mediation. This model was created within Prims, a cognitive architecture similar to and based on ACT-R, which enables us to make predictions about the cognitive tasks that meditation experience may affect. We implemented a model based on an extensive literature review of how the meditation experience unfolds over time. We then subjected the Prims model to a session of the Sustained Reaction to Response Task, a task typically used to study sustained attention, a faculty that may be trained with meditation practice. Analyses revealed that the model was significantly more sensitive to detecting targets and non-targets after the meditation practice than before. These results agree with empirical findings of a longitudinal study conducted in 2010. These results suggest that our approach to modeling meditation and its effects of cognition is feasible

How does rumination impact cognition? A first mechanistic model.

Rumination is a process of uncontrolled, narrowly-foused neg- ative thinking that is often self-referential, and that is a hall- mark of depression. Despite its importance, little is known about its cognitive mechanisms. Rumination can be thought of as a specific, constrained form of mind-wandering. Here, we introduce a cognitive model of rumination that we devel- oped on the basis of our existing model of mind-wandering. The rumination model implements the hypothesis that rumina- tion is caused by maladaptive habits of thought. These habits of thought are modelled by adjusting the number of memory chunks and their associative structure, which changes the se- quence of memories that are retrieved during mind-wandering, such that during rumination the same set of negative memo- ries is retrieved repeatedly. The implementation of habits of thought was guided by empirical data from an experience sam- pling study in healthy and depressed participants. On the ba- sis of this empirically-derived memory structure, our model naturally predicts the declines in cognitive task performance that are typically observed in depressed patients. This study demonstrates how we can use cognitive models to better un- derstand the cognitive mechanisms underlying rumination and depression