19 research outputs found
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
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Expectations About the Temporal Structure of the World Result in the Attentional Blink and Repetition Blindnsess
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 OâReilly (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
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Individual Differences in Face Processing as Revealed with Priming
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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
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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 âfault_free_trainingâ, âfault_free_testingâ, âfaulty_testingâ, and âfaulty_trainingâ, corresponding to the RData files.
Each dataframe contains 55 columns:
Column 1 ('faultNumber') ranges from 1 to 20 in the âFaultyâ datasets and represents the fault type in the TEP. The âFaultFreeâ 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 (âTrainingâ datasets) or 1 to 960 (âTestingâ 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