Controlled variations in stimulus similarity during learning determine visual discrimination capacity in freely moving mice

The mouse is receiving growing interest as a model organism for studying visual perception. However, little is known about how discrimination and learning interact to produce visual conditioned responses. Here, we adapted a two-alternative forced-choice visual discrimination task for mice and examined how training with equiprobable stimuli of varying similarity influenced conditioned response and discrimination performance as a function of learning. Our results indicate that the slope of the gradients in similarity during training determined the learning rate, the maximum performance and the threshold for successful discrimination. Moreover, the learning process obeyed an inverse relationship between discrimination performance and discriminative resolution, implying that sensitivity within a similarity range cannot be improved without sacrificing performance in another. Our study demonstrates how the interplay between discrimination and learning controls visual discrimination capacity and introduces a new training protocol with quantitative measures to study perceptual learning and visually-guided behavior in freely moving mice

Understanding the Impact of Differentiation and Unitization on the Perceptual Features Learned During Category Training

Thesis (Ph.D.) - Indiana University, Psychological and Brain Sciences/Cognitive Sciences, 2015Perceptual representations are a foundational aspect of all cognitive processes that involve input from the external environment. Yet there is ample evidence that these perceptual representations are altered by experience in systematic ways. This work focuses on understanding how perceptual representations are modified through two perceptual learning processes, differentiation and unitization, in the context of category learning. First, we review the empirical evidence for perceptual learning with a focus on the evidence for unitization and differentiation processes in the context of category learning. This section also includes a discussion of the role of differentiation and unitization learning processes in four computational models of perceptual learning. Second, we present a series of four experiments that measure the change in perceptual representations after learning category structures designed to promote differentiation and unitization in perceptual learning. Third, we investigate the impact of these category structures on the features inferred by a model that incorporates both differentiation and unitization perceptual learning processes. Fourth, we develop a modeling framework to directly compare the fit of computational models that assume different perceptual representations to the empirical results. Finally, we conclude by considering the implications and limits of these results

Perceptual categorization

The categorization of external stimuli lies at the heart of cognitive science. Existing models of perceptual categorization assume (a) information about the absolute magnitude of a stimulus is used in the categorization decision, and (b) the representation of a stimulus does not change with experience. The three experimental programs presented here challenge these two assumptions. The experiments in Chapter 2 demonstrate that existing models of categorization are unable to predict the classification of items intermediate between two categories. Chapter 3 provides empirical evidence that categorization responses are heavily influenced by the immediately preceding context, consistent with evidence from absolute identification showing people have very poor access to absolute magnitude information. A memory and contrast model is presented where each categorization decision is based on the perceived difference between the current stimulus and immediately preceding stimuli. This model is shown to account for the data from Chapters 2 and 3. Chapter 4 explores the claim that new features may be created on experience with novel stimuli, and that these features serve to alter the representation of stimuli to facilitate new categorization tasks. An alternative account is offered for existing feature creation evidence. However, experimental work re-establishes a feature creation effect. Consideration is given as to how feature creation and memory and contrast accounts of categorization may be integrated, together with extensive suggestions for the development of these ideas

Quality-space theory in olfaction

Quality-space theory (QST) explains the nature of the mental qualities distinctive of perceptual states by appeal to their role in perceiving. QST is typically described in terms of the mental qualities that pertain to color. Here we apply QST to the olfactory modalities. Olfaction is in various respects more complex than vision, and so provides a useful test case for QST. To determine whether QST can deal with the challenges olfaction presents, we show how a quality space (QS) could be constructed relying on olfactory perceptible properties and the olfactory mental qualities then defined by appeal to that QS of olfactory perceptible properties. We also consider how to delimit the olfactory QS from other modalities. We further apply QST to the role that experience plays in refining our olfactory discriminative abilities and the occurrence of olfactory mental qualities in non-conscious olfactory states. QST is shown to be fully applicable to and useful for understanding the complex domain of olfaction

Mapping Spikes to Sensations

Single-unit recordings conducted during perceptual decision-making tasks have yielded tremendous insights into the neural coding of sensory stimuli. In such experiments, detection or discrimination behavior (the psychometric data) is observed in parallel with spike trains in sensory neurons (the neurometric data). Frequently, candidate neural codes for information read-out are pitted against each other by transforming the neurometric data in some way and asking which code’s performance most closely approximates the psychometric performance. The code that matches the psychometric performance best is retained as a viable candidate and the others are rejected. In following this strategy, psychometric data is often considered to provide an unbiased measure of perceptual sensitivity. It is rarely acknowledged that psychometric data result from a complex interplay of sensory and non-sensory processes and that neglect of these processes may result in misestimating psychophysical sensitivity. This again may lead to erroneous conclusions regarding the adequacy of candidate neural codes. In this review, we first discuss requirements on the neural data for a subsequent neurometric-psychometric comparison. We then focus on different psychophysical tasks for the assessment of detection and discrimination performance and the cognitive processes that may underlie their execution. We discuss further factors that may compromise psychometric performance and how they can be detected or avoided. We believe that these considerations point to shortcomings in our understanding of the processes underlying perceptual decisions, and therefore offer potential for future research

Decision noise: An explanation for observed violations of signal detection theory

In signal detection theory (SDT), responses are governed by perceptual noise and a flexible decision criterion. Recent criticisms of SDT (see, e.g., Balakrishnan, 1999) have identified violations of its assumptions, and researchers have suggested that SDT fundamentally misrepresents perceptual and decision processes. We hypothesize that, instead, these violations of SDT stem from decision noise: the inability to use deterministic response criteria. In order to investigate this hypothesis, we present a simple extension of SDT—the decision noise model—with which we demonstrate that shifts in a decision criterion can be masked by decision noise. In addition, we propose a new statistic that can help identify whether the violations of SDT stem from perceptual or from decision processes. The results of a stimulus classification experiment—together with model fits to past experiments—show that decision noise substantially affects performance. These findings suggest that decision noise is important across a wide range of tasks and needs to be better understood in order to accurately measure perceptual processes

Idiosyncratic biases in the perception of medical images

Funding This work was supported in part by the National Institutes of Health (grant number: R01 CA236793-01). Publication made possible in part by support from the Berkeley Research Impact Initiative (BRII) sponsored by the UC Berkeley Library. Acknowledgments Raw data from Experiment 1 and 2 were obtained from Manassi et al. (2021) and Ren et al. (2022). Parts of these datasets have been previously presented at conferences including VSS and ECVP.Peer reviewedPublisher PD

Coding Strategies Underlying Visual Processing

Acquiring and representing knowledge about our environment involves a variety of core neural computations. The coding strategies underlying visual perception highlight many of these processes, and thus reveal general design principles in perception and cognition. I will review three studies where I have used different computational frameworks and analyses to address open questions in visual coding. The first project uses factor analyses of individual differences in perception to demonstrate fundamentally different representational structures for the stimulus features of color and motion. In the second project, I have explored visual adaptation in the context of population coding to address controversies regarding which coding schemes are implicated by different patterns of adaptation aftereffects. In the third, I have explored these adaptation effects in the context of Bayesian inference. This approach accounts for the full gamut of known aftereffects within the context of physiologically plausible models and provides principled quantitative predictions for why and how much the system should adapt. Together, these projects draw on the power of formal computational approaches both for analyzing neural representations and for revealing the computations and coding principles on which they are based

Cognitive aspects of emotional expression processing

This thesis investigates the hypothesis that emotions play an influential role in cognition. Interference between facial emotional expression processing and selected tasks is measured using a variety of experimental methods. Prior to the main experimental chapters, the collection and assessment (Chapter 2, Exp. 1) of stimulus materials is described. Experiments 2-11 then concentrate on the likelihood of interference with other types of information from the face. Findings using a Garner design suggest that, although identity processing may be independent of expression variation, expression processing may be influenced by variation in identity (Exps. 2-4). Continued use of this design with sex (Exps. 6-7) and gaze direction (Exps. 9-10) information appears to support the (mutual) independence of these facial dimensions from expression. This is, however, in contrast to studies that indicate the modification of masculinity judgements by expression (Exp. 5), and the interaction of gaze direction and expression when participants rate how interesting they find a face (Exp. 8). Further to this, a search task (Exp. 11) shows that slower responses to an angry (cf. happy) face looking at us, may be due to the presence of an aversive mouth. Experiments 12-15 test for interference in the field of time perception: complex interactions between expression and encoder and decoder sex are indicated. Finally, Experiments 16-17 find that exposure to a sequence in which the majority of faces are angry depresses probability learning, and that prior exposure to varying quantities of angry and happy faces affects our later memory for them. Overall, there is evidence that exposure to emotional expressions may affect other (selected)c ognitive processesd ependingu pon which expressionsa re used and which experimental methods are chosen. It is suggested that future investigations would benefit from techniques that describe the temporal profile of an emotional response