The journal of neuroscience : the official journal of the Society for Neuroscience.

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Social class and mental illness: a community study

In the social sciences it is common practice to test specific theoretically motivated research hypotheses using formal statistical procedures. Typically, students in these disciplines are trained in such methods starting at an early stage in their academic tenure. On the other hand, in psychophysical research, where parameter estimates are generally obtained using a maximum-likelihood (ML) criterion and data do not lend themselves well to the least-squares methods taught in introductory courses, it is relatively uncommon to see formal model comparisons performed. Rather, it is common practice to estimate the parameters of interest (e.g., detection thresholds) and their standard errors individually across the different experimental conditions and to 'eyeball' whether the observed pattern of parameter estimates supports or contradicts some proposed hypothesis. We believe that this is at least in part due to a lack of training in the proper methodology as well as a lack of available software to perform such model comparisons when ML estimators are used. We introduce here a relatively new toolbox of Matlab routines called Palamedes which allows users to perform sophisticated model comparisons. In Palamedes, we implement the model-comparison approach to hypothesis testing. This approach allows researchers considerable flexibility in targeting specific research hypotheses. We discuss in a non-technical manner how this method can be used to perform statistical model comparisons when ML estimators are used. With Palamedes we hope to make sophisticated statistical model comparisons available to researchers who may not have the statistical background or the programming skills to perform such model comparisons from scratch. Note that while Palamedes is specifically geared toward psychophysical data, the core ideas behind the model-comparison approach that our paper discusses generalize to any field in which statistical hypotheses are tested.

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Applying the Model-Comparison Approach to Test Specific Research Hypotheses in Psychophysical Research Using the Palamedes Toolbox.

Analysis of Local and Wide-Field Movements in the Superior Temporal Visual Areas of the Macaque Monkey

Time is a universal psychological dimension, but time perception has often been studied and discussed in relative isolation. Increasingly, researchers are searching for unifying principles and integrated models that link time perception to other domains. In this review, we survey the links between temporal cognition and other psychological processes. Specifically, we describe how subjective duration is affected by nontemporal stimulus properties (perception), the allocation of processing resources (attention), and past experience with the stimulus (memory). We show that many of these connections instantiate a "processing principle," according to which perceived time is positively related to perceptual vividity and the ease of extracting information from the stimulus. This empirical generalization generates testable predictions and provides a starting-point for integrated theoretical frameworks. By outlining some of the links between temporal cognition and other domains, and by providing a unifying principle for understanding these effects, we hope to encourage time-perception researchers to situate their work within broader theoretical frameworks, and that researchers from other fields will be inspired to apply their insights, techniques, and theorizing to improve our understanding of the representation and judgment of time. (PsycINFO Database Record

/pdf/temporal-cognition-connecting-subjective-time-to-perception-48ogorryc7.pdf

Temporal cognition: Connecting subjective time to perception, attention, and memory.

quickpsy is a package to parametrically fit psychometric functions. In comparison with previous R packages, quickpsy was build to easily fit and plot data for multiple groups. Here, we describe the standard parametric model used to fit psychometric functions and the standard estimation of its parameters using maximum likelihood. We also provide examples of usage of quickpsy, including how allowing the lapse rate to vary can sometimes eliminate the bias in parameter estimation, but not in general. Finally, we describe some implementation details, such as how to avoid the problems associated to round-off errors in the maximisation of the likelihood or the use of closures and non-standard evaluation functions.

/pdf/quickpsy-an-r-package-to-fit-psychometric-functions-for-3a0eyw6zgl.pdf

quickpsy: An R Package to Fit Psychometric Functions for Multiple Groups

When a ﬂash is presented in spatial alignment with a moving stimulus, the ﬂash appears to lag behind (the ﬂash-lag effect).The motion of the object can inﬂuence the position of the ﬂash, but there may also be a reciprocal effect of the ﬂash on themoving object. Here, we demonstrate that this is the case. We show that when a ﬂash is presented near the moving object,the ﬂash-lag effect does not depend greatly on the duration of the preﬂash trajectory. However, when the ﬂash is presentedsufﬁciently far from the moving object, the ﬂash-lag effect increases with the duration of the preﬂash trajectory, until itreaches an asymptotic level. We also show that the interaction of the near ﬂash can occur when it is task irrelevant. Finally,using the motion aftereffect, we demonstrate that motion signals are involved in the time evolution of the ﬂash-lag effect.Keywords: ﬂash-lag effect, temporal mechanisms, spatial mechanisms, motion aftereffectCitation: Linares, D., Lopez-Moliner, J., & Johnston, A. (2007). Motion signal and the perceived positions of moving objects.Journal of Vision, 7(7):1, 1

/pdf/motion-signal-and-the-perceived-positions-of-moving-objects-cldpf99ub3.pdf

Motion signal and the perceived positions of moving objects.

The flash-lag effect is reduced when the flash is perceived as a sensory consequence of our action.

When a stimulus repeatedly and rapidly changes color (e.g., between red and green) and motion direction (e.g., upwards and downwards) with the same frequency, it was found that observers were most likely to pair colors and motion directions when the direction changes lead the color changes by approximately 80 ms. This is the color-motion asynchrony illusion. According to the differential processing time model, the illusion is explained because the neural activity leading to the perceptual experience of motion requires more time than that of color. Alternatively, the time marker model attributes the misbinding to a failure in matching different sorts of changes at rapid alternations. Here, running counter to the time marker model, we demonstrate that the illusion can arise with a single direction change. Using this simplified version of the illusion we also show that, although some form of visual masking takes place between colors, the measured asynchrony genuinely reflects processing time differences.

Perceptual asynchrony between color and motion with a single direction change

Humans can precisely judge relative location between two objects moving with the same speed and direction, as numerous studies have shown. However, the precision for localizing a single moving object relative to stationary references remains a neglected topic. Here, subjects reported the perceived location of a moving object at the time of a cue. The variability of the reported positions increased steeply with the speed of the object, such that the distribution of responses corresponds to the distance that the object traveled in 70 ms. This surprisingly large temporal imprecision depends little on the characteristics of the trajectory of the moving object or of the cue that indicates when to judge the position. We propose that the imprecision reflects a difficulty in identifying which position of the moving object occurs at the same time as the cue. This high-level process may involve the same low temporal resolution binding mechanism that, in other situations, pairs simultaneous features such as color and motion.

Daniel Linares

Papers

quickpsy: An R Package to Fit Psychometric Functions for Multiple Groups

Motion signal and the perceived positions of moving objects.

The flash-lag effect is reduced when the flash is perceived as a sensory consequence of our action.

Perceptual asynchrony between color and motion with a single direction change

Where is the moving object now? Judgments of instantaneous position show poor temporal precision (SD = 70 ms)