Adaptations of temporal dynamics

The human mind rapidly parses high-dimensional dynamic input into useful representations. Identifying the source of relevant sensory information in time is critical to the formation of informative perceptions. One source of information to aid perceptual processing is the temporal regularity of sensory input. Knowledge of what regularities are utilized and how they are utilized is critical to understanding how perception functions in a dynamic world. The objective of this dissertation is to explore the adaptations of perception to temporal regularities in the environment. Chapters 1 and 2 use short term priming paradigms to examine the temporal segregation of perceptual information. Chapter 1 shows that inverted versus upright faces have different time courses of priming, suggesting that familiarity plays a role in temporal segregation. Furthermore, for faces, there are individual differences in priming dynamics related to perceptual identification ability. Chapter 2 examines the influence of occurrence and co-occurrence statistics in the same task. Several incremental reductions of stimulus frequency at different levels of representation all slow priming compared to higher occurring word stimuli. Word associations as a measure of co-occurrence, produce waxing and waning priming effects, with a small effect of the order of the associative relationship. Priming based on direct measures of linguistic co-occurrence produces priming dynamics that are similar to associative priming. Words which are expected to repeat provide a small increase in priming compared to priming by repeating a word. These priming effects are interpreted as the result of habituation. The findings in Chapters 1 and 2 generalize the habituation account of priming effects to faces, demonstrate its dependence on the occurrence rates of stimuli, and show that temporal co-occurrence regularities for particular items only result in small changes to the basic dynamics. Chapter 3 uses a spatial cueing paradigm to test if we adapt to diagnostic spatial-temporal relationships. Participants implicitly learn and generalize diagnostic cue-target relationships with long delays between cues and target. Diagnostic relationships are also learned for short cue-target delays when no shift of expectation is required. As a whole, these experiments find that temporal regularities pertaining to familiarity and general occurrence relationships are strongly reflected in the dynamics of perception, and that directional associations or expectations between individual stimuli deviate only slightly from general dynamic

Using a neural network model with synaptic depression to assess the dynamics of feature-based versus configural processing in face identification

Accounting for the finding that brief prime durations facilitate perception of immediate word repetitions whereas long prime durations are detrimental, Huber and O’Reilly (2003) proposed a neural network model in which the unwanted effects of perceptual persistence are counteracted through activity dependent synaptic depression. Rieth and Huber (in prep) found similar results with immediate face repetitions, manipulating featural versus configural processing by means of face inversion. We extend the neural network model to face perception and account for individual differences by assuming some participants perform the task on the basis of feature identification, corresponding to the second layer of the 3-layer network, whereas other participants perform the task on the basis of configural identification, corresponding to the top layer. Under these assumptions, the model is used to describe the dynamics for each type of processing, with the resultant parameters revealing that configural identification integrates information at a faster rate than feature identification

Turn, Turn, Turn: Perceiving Global and Local, Clockwise and Counterclockwise Rotations

The processing of Navon figures (Navon, 1977), i.e., hierarchical letter stimuli, has been studied in experimental settings for many years. In particular, they have been studied in the context of visual hemifield studies and yielded an interaction between hemifield and whether a target is at the local or global level, with a right hemisphere advantage for the global level, and a left hemisphere advantage for the targets at the local level (Sergent, 1982). This is a ventral stream process, however, and we were interested in whether there might be a similar interaction for hierarchical motion stimuli, presumably a dorsal stream process. Hence we developed a series of dynamic geometric Navon figures in order to study global/local rotation processing. These figures consist of a global figure (a triangle or a square) made up of local figures (also triangles or squares). Both global and local figures can rotate in either clockwise or counterclockwise directions independently. We found that there is no right or left visual field perceptual advantage for either the global or local levels of these figures. However, curiously enough, we found that there is a significant processing advantage for clockwise motion compared to counterclockwise motion. We also found a highly significant interaction between the detection of a particular rotational motion and the presence or absence of that motion in the figure being examined. Finally, our data strongly support the Global Precedence Hypothesis which says that people generally tend to focus on the global properties of an object before local properties and that processing proceeds in a global-to-local direction

Turn, turn, turn : perceiving global and local, clockwise and counterclockwise rotations

International audienceWe developed a series of dynamic geometric Navon figures in order to study global/local rotation processing. These figures consist of a global figure (a triangle or a square) made up of local figures (also triangles or squares). Both global and local figures can rotate in either clockwise or counterclockwise directions independently. We found that there is no right or left visual field perceptual advantage for either the global or local levels of these figures, as in Sergent (1982). We did, however, find a significant processing advantage for clockwise motion compared to counterclockwise motion. We also found a highly significant interaction between the detection of a particular rotational motion and the presence or absence of that motion in the figure being examined. Our data also strongly support the Global Precedence Hypothesis which says that people generally tend to focus on the global properties of an object before local properties

Additional Tennessee Eastman Process Simulation Data for Anomaly Detection Evaluation

User Agreement, Public Domain Dedication, and Disclaimer of Liability. By accessing or downloading the data or work provided here, you, the User, agree that you have read this agreement in full and agree to its terms. The person who owns, created, or contributed a work to the data or work provided here dedicated the work to the public domain and has waived his or her rights to the work worldwide under copyright law. You can copy, modify, distribute, and perform the work, for any lawful purpose, without asking permission. In no way are the patent or trademark rights of any person affected by this agreement, nor are the rights that any other person may have in the work or in how the work is used, such as publicity or privacy rights. Pacific Science & Engineering Group, Inc., its agents and assigns, make no warranties about the work and disclaim all liability for all uses of the work, to the fullest extent permitted by law. When you use or cite the work, you shall not imply endorsement by Pacific Science & Engineering Group, Inc., its agents or assigns, or by another author or affirmer of the work. This Agreement may be amended, and the use of the data or work shall be governed by the terms of the Agreement at the time that you access or download the data or work from this Website. Description This dataverse contains the data referenced in Rieth et al. (2017). Issues and Advances in Anomaly Detection Evaluation for Joint Human-Automated Systems. To be presented at Applied Human Factors and Ergonomics 2017. Each .RData file is an external representation of an R dataframe that can be read into an R environment with the 'load' function. The variables loaded are named ‘fault_free_training’, ‘fault_free_testing’, ‘faulty_testing’, and ‘faulty_training’, corresponding to the RData files. Each dataframe contains 55 columns: Column 1 ('faultNumber') ranges from 1 to 20 in the “Faulty” datasets and represents the fault type in the TEP. The “FaultFree” datasets only contain fault 0 (i.e. normal operating conditions). Column 2 ('simulationRun') ranges from 1 to 500 and represents a different random number generator state from which a full TEP dataset was generated (Note: the actual seeds used to generate training and testing datasets were non-overlapping). Column 3 ('sample') ranges either from 1 to 500 (“Training” datasets) or 1 to 960 (“Testing” datasets). The TEP variables (columns 4 to 55) were sampled every 3 minutes for a total duration of 25 hours and 48 hours respectively. Note that the faults were introduced 1 and 8 hours into the Faulty Training and Faulty Testing datasets, respectively. Columns 4 to 55 contain the process variables; the column names retain the original variable names. Acknowledgments. This work was sponsored by the Office of Naval Research, Human & Bioengineered Systems (ONR 341), program officer Dr. Jeffrey G. Morrison under contract N00014-15-C-5003. The views expressed are those of the authors and do not reflect the official policy or position of the Office of Naval Research, Department of Defense, or US Government