Linking signal detection theory and encoding models to reveal independent neural representations from neuroimaging data (original) (raw)
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Frontiers in Psychology, 2017
Determining whether perceptual properties are processed independently is an important goal in perceptual science, and tools to test independence should be widely available to experimental researchers. The best analytical tools to test for perceptual independence are provided by General Recognition Theory (GRT), a multidimensional extension of signal detection theory. Unfortunately, there is currently a lack of software implementing GRT analyses that is ready-to-use by experimental psychologists and neuroscientists with little training in computational modeling. This paper presents grtools, an R package developed with the explicit aim of providing experimentalists with the ability to perform full GRT analyses using only a couple of command lines. We describe the software and provide a practical tutorial on how to perform each of the analyses available in grtools. We also provide advice to researchers on best practices for experimental design and interpretation of results.
Frontiers in Psychology, 2015
The processing of facial identity and facial expression have traditionally been seen as independent-a hypothesis that has largely been informed by a key double dissociation between neurological patients with a deficit in facial identity recognition but not facial expression recognition, and those with the reverse pattern of impairment. The independence hypothesis is also reflected in more recent anatomical models of faceprocessing, although these theories permit some interaction between the two processes. Given that much of the traditional patient-based evidence has been criticized, a review of more recent case reports that are accompanied by neuroimaging data is timely. Further, the performance of individuals with developmental face-processing deficits has recently been considered with regard to the independence debate. This paper reviews evidence from both acquired and developmental disorders, identifying methodological and theoretical strengths and caveats in these reports, and highlighting pertinent avenues for future research.
Psychonomic Bulletin & Review, 2014
A common question in perceptual science is to what extent different stimulus dimensions are processed independently. General recognition theory (GRT) offers a formal framework via which different notions of independence can be defined and tested rigorously, while also dissociating perceptual from decisional factors. This article presents a new GRT model that overcomes several shortcomings with previous approaches, including a clearer separation between perceptual and decisional processes and a more complete description of such processes. The model assumes that different individuals share similar perceptual representations, but vary in their attention to dimensions and in the decisional strategies they use. We apply the model to the analysis of interactions between identity and emotional expression during face recognition. The results of previous research aimed at this problem have been disparate. Participants identified four faces, which resulted from the combination of two identities and two expressions. An analysis using the new GRT model showed a complex pattern of dimensional interactions. The perception of emotional expression was not affected by changes in identity, but the perception of identity was affected by changes in emotional expression. There were violations of decisional separability of expression from identity and of identity from expression, with the former being more consistent across participants than the latter. One explanation for the disparate results in the literature is that decisional strategies may have varied across studies and influenced the results of tests of perceptual interactions, as previous studies lacked the ability to dissociate between perceptual and decisional interactions.
Vision Research, 2009
Major cognitive and neural models of face perception view that the mechanisms underlying the extraction of facial expression and facial identity information involve separable visual systems. Using the visual adaptation paradigm, we explored the sensitivity of happy, sad, angry, disgusted and fearful facial expressions to changes in identity. Contrary to what would be predicted by traditional face perception models, larger expression aftereffects were produced when the identity of the adapting and test stimuli was the same compared to when the identity differed, suggesting the involvement of identity-dependent neurons in processing these expressions. Furthermore, for all five expressions, the aftereffects remained significant when the adapting and test stimuli differed in identity, suggesting the involvement of identity-independent neural populations. The extent to which the aftereffect transferred across changes in identity was the same for all emotional expressions. Consequently, there is no evidence that the processing of individual facial expressions depend on facial identity differentially. Implications of these findings are discussed.
Varieties of perceptual independence
Psychological Review, 1986
Several varieties of perceptual independence are investigated. These include sampling independence, dimensional orthogonality, stimulus separability and integrality, and performance parity. A general multivariate perceptual theory is developed, and a precise definition of perceptual independence is offered. Each of these related concepts is then examined within the framework of this theory, and their theoretical interrelationships are explicated. It is shown that none of the concepts are equivalent to perceptual independence but that if separability holds, then sampling independence is equivalent to perceptual independence. Several simple tests of separability are suggested that can be applied to the same data as sampling independence. Dimensional orthogonality is shown to test for independence only if some strong distributional assumptions are made about the perceptual effects of stimuli. Reaction time and information-based performance parity criteria are examined. The potential for empirically testing each of these concepts is discussed. The stimuli of perception are many dimensional. Tones may vary in frequency, intensity, and duration. Individual characters in text may vary in size, orientation, shape, and the number of line segments they contain (among other things). Even the fruit that we eat may vary in size, shape, texture, sugar content, and the wavelength of light it reflects. A fundamentally important problem is to determine how these dimensions are combined in perceptual processing. Because of this, a notion central to almost all theories of perception, whether they are aimed at the visual, the auditory, or some other modality, is that of perceptual independence. At a macroscopic verbal level, there is agreement among most theoreticians about the meaning of this term. The components A and B of the two-dimensional stimulus AB are said to be independently perceived if the perception of each is in no way contingent on or interacts with the perception of the other, or somewhat more rigorously, if the probability of simultaneously perceiving both components A and B is equal to the probability of perceiving component A times the probability of perceiving component B (e.g., Garner & Morton, 1969; Green & Birdsall, 1978; Wandmacher, 1976). Unfortunately, perceptions are not usually directly observable; instead they first pass through some decision process that uses the perceptions to select a response appropriate to the general experimental milieu. Decision or judgment processes therefore fundamentally alter direct perceptions (i.e., the early stages of perception), thereby making the above definition of perceptual independence difficult to test.
Unmixing fMRI with independent component analysis
IEEE Engineering in Medicine and Biology Magazine, 2006
Independent component analysis (ICA) is a statistical method used to discover hidden factors (sources or features) from a set of measurements or observed data such that the sources are maximally independent. Typically, it assumes a generative model where observations are assumed to be linear mixtures of independent sources and works with higher-order statistics to achieve independence. ICA has recently demonstrated considerable promise in characterizing functional magnetic resonance imaging (fMRI) data, primarily due to its intuitive nature and ability for flexible characterization of the brain function. In this article, ICA is introduced and its application to fMRI data analysis is reviewed.
Estimation of Separable Representations In Psychophysical Experiments
cogsci.rpiscrews.us
Studying how individuals compare two given quantita-tive stimuli, say d1 and d2, is a fundamental problem. One very common way to address it is through ratio magnitude estimation, that is to ask individuals not to give values to d1 and d2 but rather to give their es-timates of the ...