scholarly journals Performance of normative and approximate evidence accumulation on the dynamic clicks task

2019 ◽  
Author(s):  
Adrian E. Radillo ◽  
Alan Veliz-Cuba ◽  
Krešimir Josić ◽  
Zachary P. Kilpatrick
Keyword(s):  
Model Fitting ◽  
Decision Making Process ◽  
Response Accuracy ◽  
Parameter Recovery ◽  
Ideal Observers ◽  
Log Likelihood ◽  
Left And Right ◽  
Normative Models ◽  
Task Parameters ◽  
Sensory Noise

The aim of a number of psychophysics tasks is to uncover how mammals make decisions in a world that is in flux. Here we examine the characteristics of ideal and near–ideal observers in a task of this type. We ask when and how performance depends on task parameters and design, and, in turn, what observer performance tells us about their decision-making process. In the dynamic clicks task subjects hear two streams (left and right) of Poisson clicks with different rates. Subjects are rewarded when they correctly identify the side with the higher rate, as this side switches unpredictably. We show that a reduced set of task parameters defines regions in parameter space in which optimal, but not near-optimal observers, maintain constant response accuracy. We also show that for a range of task parameters an approximate normative model must be finely tuned to reach near-optimal performance, illustrating a potential way to distinguish between normative models and their approximations. In addition, we show that using the negative log-likelihood and the 0/1-loss functions to fit these types of models is not equivalent: the 0/1-loss leads to a bias in parameter recovery that increases with sensory noise. These findings suggest ways to tease apart models that are hard to distinguish when tuned exactly, and point to general pitfalls in experimental design, model fitting, and interpretation of the resulting data.

Horizontal and Vertical Composite Effects in Novel Faces

Perception ◽  
1997 ◽  
Vol 26 (1_suppl) ◽  
pp. 118-118
Author(s):  
N P Costen ◽  
T Kato ◽  
I G Craw ◽  
S Akamatsu
Keyword(s):  
Face Recognition ◽  
Response Accuracy ◽  
Processing Strategy ◽  
Composite Construction ◽  
Composite Effect ◽  
Configural Information ◽  
The Third ◽  
Left And Right ◽  
Fourth Experiment ◽  
The Right

The composite effect, where the recognition of the upper half of a face is disrupted by a discrepant lower half relative to an isolated half-face, without a corresponding effect for vertical half-faces, provides a ready method of investigating configural information in face recognition. In previous studies purely photographic techniques have been used for composite construction. We investigated the effects of more face-like stimuli, constructed by morphing techniques. Subjects were trained to identify frontal Japanese faces, and tested on recognition on marked upper, lower, left, and right halves, both as half-faces and with distractors. While response accuracy for the upper and lower composites was lower than those for the relevant halves, there was no such effect for the right - left composites. A familiarity design was used in the second experiment to replicate this result. In the third experiment quarter-faces (top left - bottom right facial quadrants) were used to control for the information present. We found a strong composite effect for the right - left composites, and weaker ones for the top - bottom and quarter composites. In the fourth experiment we examined whether this effect was dependent on the presence of the quarter-composites by presenting them in a second block but found no effect of this manipulation. It thus appears that although there is a composite effect with faces composed in a shape-free manner, this effect is unstable. Under certain circumstances subjects may convert from a top - bottom relational processing strategy to a right - left strategy. The information used, even with a constant task, is dependent upon the variability of the images involved.

scholarly journals Modeling Conditional Dependence of Response Accuracy and Response Time with the Diffusion Item Response Theory Model

2021 ◽  
Author(s):  
Inhan Kang ◽  
Paul De Boeck ◽  
Roger Ratcliff
Keyword(s):  
Response Time ◽  
Item Difficulty ◽  
Theory Model ◽  
Cognitive Capacity ◽  
Extended Model ◽  
Response Accuracy ◽  
Parameter Recovery ◽  
Conditional Dependence ◽  
Proposed Model ◽  
Conditional Dependency

In this paper, we propose a model-based method to study conditional dependence be- tween response accuracy and response time (RT) with the diffusion IRT model. To this end, we extend the previously proposed model by introducing variability across persons and items in cognitive capacity and in the initial bias of the response processes. We show that the extended model can explain the behavioral patterns of conditional dependency found in the previous studies in psychometrics. The first variability component in cognitive capacity can predict positive and negative conditional dependency and their interaction with the item difficulty. The second variability in the initial bias can account for the early changes in the response accuracy as a function of RTs given the person and item effects, producing the curvilinear conditional accuracy functions. We also provide a simulation study to validate the parameter recovery of the proposed model and two empirical applications to describe how to implement the model to study conditional dependency underlying data response accuracy and RTs.

scholarly journals Identifying Effortful Individuals With Mixture Modeling Response Accuracy and Response Time Simultaneously to Improve Item Parameter Estimation

2020 ◽  
Vol 80 (4) ◽  
pp. 775-807
Author(s):  
Yue Liu ◽  
Ying Cheng ◽  
Hongyun Liu
Keyword(s):  
Parameter Estimation ◽  
Response Time ◽  
Mixture Model ◽  
Response Times ◽  
Latent Trait ◽  
Item Parameter ◽  
Parameter Estimates ◽  
Response Accuracy ◽  
Parameter Recovery ◽  
Item Parameter Estimation

The responses of non-effortful test-takers may have serious consequences as non-effortful responses can impair model calibration and latent trait inferences. This article introduces a mixture model, using both response accuracy and response time information, to help differentiating non-effortful and effortful individuals, and to improve item parameter estimation based on the effortful group. Two mixture approaches are compared with the traditional response time mixture model (TMM) method and the normative threshold 10 (NT10) method with response behavior effort criteria in four simulation scenarios with regard to item parameter recovery and classification accuracy. The results demonstrate that the mixture methods and the TMM method can reduce the bias of item parameter estimates caused by non-effortful individuals, with the mixture methods showing more advantages when the non-effort severity is high or the response times are not lognormally distributed. An illustrative example is also provided.

Participant skepticism: If you can't beat it, model it

2001 ◽  
Vol 24 (3) ◽  
pp. 424-425 ◽  
Author(s):  
Craig R. M. McKenzie ◽  
John T. Wixted
Keyword(s):  
Important Task ◽  
Full Belief ◽  
The Common ◽  
Normative Models ◽  
Task Parameters

For a variety of reasons, including the common use of deception in psychology experiments, participants often disbelieve experimenters' assertions about important task parameters. This can lead researchers to conclude incorrectly that participants are behaving non- normatively. The problem can be overcome by deriving and testing normative models that do not assume full belief in key task parameters. A real experimental example is discussed.

scholarly journals The Importance of Group Specification in Computational Modelling of Behaviour

2020 ◽  
Author(s):  
Vincent Valton ◽  
Toby Wise ◽  
Oliver Joe Robinson
Keyword(s):  
Model Fitting ◽  
Computational Modelling ◽  
Group Differences ◽  
Group Level ◽  
Parameter Recovery ◽  
Fitting Procedure ◽  
Computational Psychiatry ◽  
Diagnostic Labels ◽  
Data Generating Process ◽  
Parameter Values

Introduction: Hierarchical model fitting has become commonplace in cognitive neuroscience. However, these techniques require us to formalise assumptions about the data-generating process at the group level, which may not be known. In computational psychiatry, we frequently encounter situations with multiple distinct groups of subjects, which makes this specification non-trivial. Specifically, we must choose whether to assume all subjects are drawn from a common population, or to model them as deriving from separate populations. These assumptions have profound implications for computational psychiatry, as they will undoubtedly affect the resulting inference (parameter recovery) and conflate or mask true group-level differences. Methods: We used simulations to test these assumptions on synthetic multi-group behavioural data from commonly used multi-armed bandit tasks. We first demonstrate the influence of hierarchical vs non hierarchical approaches on parameter recovery. We then examine recovery of group differences in parameter values under different modelling approaches: (1) modelling groups under a common shared group-level prior (assuming all participants are generated from a common distribution, and are likely to share common characteristics); (2) modelling separate groups based on symptomatology or diagnostic labels, resulting in separate group-level priors. We evaluate the robustness of these approaches to variations in data quality and in prior specification.Results: We confirm, firstly, that hierarchical approaches lead to better parameter recovery. Secondly, we argue that fitting groups separately (Model 2) provides the most robust inference across all conditions and perturbations. Thirdly, we confirm these assumptions have less of an impact with higher numbers of trials and subjects. Finally, we show that the advice to fit groups separately can fall down when extreme assumptions are made about group variance.Conclusions: Our results suggest that when dealing with data from multiple clinical groups, researchers should use a hierarchical approach to parameter fitting, but account for hypothesised group differences in the model fitting procedure. In other words, under most normal circumstances, researchers should fit patient and control groups separately.

scholarly journals Unbiased and efficient log-likelihood estimation with inverse binomial sampling

2020 ◽  
Vol 16 (12) ◽  
pp. e1008483
Author(s):  
Bas van Opheusden ◽  
Luigi Acerbi ◽  
Wei Ji Ma
Keyword(s):  
Likelihood Function ◽  
Model Fitting ◽  
Likelihood Estimation ◽  
Minimum Variance ◽  
Data Set ◽  
Binomial Sampling ◽  
Estimated Parameters ◽  
Simulation Based ◽  
Log Likelihood ◽  
Complex Models

The fate of scientific hypotheses often relies on the ability of a computational model to explain the data, quantified in modern statistical approaches by the likelihood function. The log-likelihood is the key element for parameter estimation and model evaluation. However, the log-likelihood of complex models in fields such as computational biology and neuroscience is often intractable to compute analytically or numerically. In those cases, researchers can often only estimate the log-likelihood by comparing observed data with synthetic observations generated by model simulations. Standard techniques to approximate the likelihood via simulation either use summary statistics of the data or are at risk of producing substantial biases in the estimate. Here, we explore another method, inverse binomial sampling (IBS), which can estimate the log-likelihood of an entire data set efficiently and without bias. For each observation, IBS draws samples from the simulator model until one matches the observation. The log-likelihood estimate is then a function of the number of samples drawn. The variance of this estimator is uniformly bounded, achieves the minimum variance for an unbiased estimator, and we can compute calibrated estimates of the variance. We provide theoretical arguments in favor of IBS and an empirical assessment of the method for maximum-likelihood estimation with simulation-based models. As case studies, we take three model-fitting problems of increasing complexity from computational and cognitive neuroscience. In all problems, IBS generally produces lower error in the estimated parameters and maximum log-likelihood values than alternative sampling methods with the same average number of samples. Our results demonstrate the potential of IBS as a practical, robust, and easy to implement method for log-likelihood evaluation when exact techniques are not available.

The three-dimensional structure of frozen-hydrated left- and right-handed forms of bacterial flagellar filaments from an identical serotype

1986 ◽  
Vol 44 ◽  
pp. 298-299
Author(s):  
S. Trachtenberg ◽  
D. J. DeRosier
Keyword(s):  
Ionic Strength ◽  
Basal Body ◽  
Three Dimensional ◽  
Dimensional Structure ◽  
Protein Species ◽  
Liquid Environment ◽  
Bacterial Flagellum ◽  
Left And Right ◽  
Rotary Motor ◽  
Helical Parameters

The bacterial cell is propelled through the liquid environment by means of one or more rotating flagella. The bacterial flagellum is composed of a basal body (rotary motor), hook (universal coupler), and filament (propellor). The filament is a rigid helical assembly of only one protein species — flagellin. The filament can adopt different morphologies and change, reversibly, its helical parameters (pitch and hand) as a function of mechanical stress and chemical changes (pH, ionic strength) in the environment.

Advantages of Complementary Stereo Images as Viewed with the Low-Temperature Field-Emission SEM

1992 ◽  
Vol 50 (2) ◽  
pp. 1314-1315
Author(s):  
William P. Wergin ◽  
Eric F. Erbe
Keyword(s):  
Fold Increase ◽  
Horizontal Displacement ◽  
Three Dimensions ◽  
Stereo Image ◽  
Stereo Pair ◽  
Sem Micrograph ◽  
Left And Right ◽  
The Common ◽  
The Brain ◽  
Pair Analysis

The eye-brain complex allows those of us with normal vision to perceive and evaluate our surroundings in three-dimensions (3-D). The principle factor that makes this possible is parallax - the horizontal displacement of objects that results from the independent views that the left and right eyes detect and simultaneously transmit to the brain for superimposition. The common SEM micrograph is a 2-D representation of a 3-D specimen. Depriving the brain of the 3-D view can lead to erroneous conclusions about the relative sizes, positions and convergence of structures within a specimen. In addition, Walter has suggested that the stereo image contains information equivalent to a two-fold increase in magnification over that found in a 2-D image. Because of these factors, stereo pair analysis should be routinely employed when studying specimens.Imaging complementary faces of a fractured specimen is a second method by which the topography of a specimen can be more accurately evaluated.

Histological evaluation of cochlear hair cell damage from noise-induced hearing loss in chinchillas

1990 ◽  
Vol 48 (3) ◽  
pp. 332-333
Author(s):  
R.V. Harrison ◽  
R.J. Mount ◽  
P. White ◽  
N. Fukushima
Keyword(s):  
Hair Cell ◽  
Evoked Potential ◽  
Cell Damage ◽  
Acoustic Trauma ◽  
Histological Evaluation ◽  
Cell Integrity ◽  
Functional Changes ◽  
Cochlear Hair Cell ◽  
Left And Right ◽  
Contralateral Ear

In studies which attempt to define the influence of various factors on recovery of hair cell integrity after acoustic trauma, an experimental and a control ear which initially have equal degrees of damage are required. With in a group of animals receiving an identical level of acoustic trauma there is more symmetry between the ears of each individual, in respect to function, than between animals. Figure 1 illustrates this, left and right cochlear evoked potential (CAP) audiograms are shown for two chinchillas receiving identical trauma. For this reason the contralateral ear is used as control.To compliment such functional evaluations we have devised a scoring system, based on the condition of hair cell stereocilia as revealed by scanning electron microscopy, which permits total stereociliar damage to be expressed numerically. This quantification permits correlation of the degree of structural pathology with functional changes. In this paper wereport experiments to verify the symmetry of stereociliar integrity between two ears, both for normal (non-exposed) animals and chinchillas in which each ear has received identical noise trauma.

The crystallography characteristic of (Mn,Fe)S single crystal

1990 ◽  
Vol 48 (4) ◽  
pp. 898-899
Author(s):  
Jiang Xishan
Keyword(s):  
Single Crystal ◽  
Cast Steel ◽  
Point Group ◽  
Central Area ◽  
Hexagonal Crystal ◽  
Growth Step ◽  
Left And Right ◽  
Relationship Of ◽  
Fcc Structure ◽  
New Discovery

This paper reports the growth step pattern and morphology at equilibrium and growth states of (Mn,Fe)S single crystal on the wall of micro-voids in ZG25 cast steel by using scanning electron microscope. Seldom report was presented on the growth morphology and steppattern of (Mn,Fe)S single crystal.Fig.1 shows the front half of the polyhedron of(Mn,Fe)S single crystal,its central area being the square crystal plane,the two pairs of hexagons symmetrically located in the high and low, the left and right with a certain, angle to the square crystal plane.According to the symmetrical relationship of crystal, it was defined that the (Mn,Fe)S single crystal at equilibrium state is tetrakaidecahedron consisted of eight hexagonal crystal planes and six square crystal planes. The macroscopic symmetry elements of the tetrakaidecahedron correpond to Oh—n3m symmetry class of fcc structure,in which the hexagonal crystal planes are the { 111 } crystal planes group,square crystal plaits are the { 100 } crystal planes group. This new discovery of the (Mn,Fe)S single crystal provides a typical example of the point group of Oh—n3m.

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