Brian Odegaard

Assessing similarity between objects is a fundamental cognitive process, and similarity judgments can assess many different attributes, including objective properties (color, shape) or subjective appraisals (preference, scariness). Here, we investigated how psychological similarity across eight different properties relates to neural representational geometries and artificial models. We first collected large-scale pairwise similarity ratings for 280 objects. Using representational similarity analysis (RSA) and multidimensional scaling, we identified three mental representational spaces: one defined by multiple object features and general similarity, a second by affective evaluations, and a third by color. Combining fMRI and RSA in 80 participants, we found that object feature ratings significantly correlated with representational structures in visual and prefrontal cortices. Unexpectedly, affective ratings also correlated with patterns in visual cortices. Crucially, regional variability strongly shaped these correspondences: visual cortices exhibited high noise ceilings and consistent alignment with behavior, whereas associative regions showed greater across-subjects variability and weaker correlations. Finally, algorithms and neural networks with high classification performance on specific properties strongly correlated with behavioral and fMRI RSA matrices. Together, these results demonstrate that similarity is a multidimensional construct that comprises multiple representational spaces whose neural correspondence is shaped by representational content, regional variability, and modeling methodology.

A fundamental question in psychology and neuroscience is whether expertise can generalize to improvements in basic sensory perception. Recent work suggests that musicians exhibit domain-general advantages in multisensory spatial integration, which has implications for our understanding of plasticity in sensory processing. Yet, the cause of this effect of expertise is unclear. Here, a preregistered sample of 35 musicians and 35 nonmusicians localized brief flashes and noise bursts, unimodally and bimodally, along the azimuth. Via Bayesian causal inference, we modeled participants' sensory precision and their prior tendency to perceptually integrate the stimuli (pcommon). As hypothesized, musicians exhibited less ventriloquism (audition biased toward vision) than nonmusicians, and this was captured by a reduced pcommon rather than by differences in sensory precision. Furthermore, although pcommon (and ventriloquism) was reduced after we told participants how often the stimuli were colocated, this did not eliminate the group difference in pcommon. Our results suggest that musicians have reduced susceptibility to a famous multisensory illusion, as accounted for by a Bayesian prior, and we show that such a prior (and illusory perception) can be modulated by a simple instruction. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

Psychophysics seeks to quantitatively characterize relationships between objective properties of the world and subjective properties of perception. However, traditional approaches investigate psychophysical dependencies of perception on stimulus properties on a case by case basis rather than seeking to identify quantitative relationships among these psychological processes themselves. This latter goal is particularly important when the processes in question likely depend on each other in some way, such as is the case for subjective experience and task performance: typically, stronger physical stimuli lead to better performance and stronger subjective experiences of clarity, vividness, or confidence. But is the relationship between performance and subjective experience fixed, or can it vary, e.g. by task or attentional demands? Such questions are key for better understanding psychological processes in general, and subjective experience in particular. Here, we develop and showcase a new psychophysical method designed to answer such questions: relative psychometric function (RPF) analysis, which characterizes the nonlinear psychometric relationships between psychological processes and how these relationships change under different circumstances (e.g. experimental manipulations). We demonstrate the advantages of RPF analysis using a sample dataset in which human subjects discriminated random dot kinematogram stimuli which varied in dot motion coherence and overall dot density (dots per visual degree), and rated confidence. RPF analysis revealed systematic changes in the relationship between performance and two subjective measures (confidence and metacognitive sensitivity) due to dot density and task design choices. While these empirical results are intriguing in their own right, they also show how RPF analysis can reveal changes in quantitative relationships between any two psychological measures: performance, vividness, clarity, reaction time, confidence, and more. To encourage the scientific community to use RPF analysis on their data, we also present our open-source RPF toolbox.

This study introduces an enhanced, open-source eye-tracking system integrated into an immersive VR environment. Utilizing the Tobii Pro SDK and Unity, our basic module system allows for precise gaze estimation accuracy that can be deployed in behavioral experiments. We deployed our module in two experiments: Experiment 1 involved passive observation, where participants fixated on stop signs while detecting peripheral targets. Experiment 2 added an active driving component, requiring participants to control the vehicle while performing the detection task. Results showed high fixation success and detection rates, with performance declining systematically for smaller and more eccentric targets, consistent with known peripheral vision constraints. Following these tests, we extended our module to incorporate a novel iris-based ratio method to correct pupil diameter for environmental luminance and headset-induced artifacts. This correction enables reliable, real-time assessment of cognitive load via pupillometry despite VR’s dynamic conditions. Overall, our findings demonstrate that this enhanced eye-tracking system effectively captures gaze behavior and cognitive load simultaneously in ecologically valid VR scenarios. This advancement enables detailed study of attention and workload dynamics during multitasking and offers promising applications for adaptive systems responsive to real-time user states.

Knowing when to trust and incorporate the advice from artificially intelligent (AI) systems is of increasing importance in the modern world. Research indicates that when AI provides high confidence ratings, human users often correspondingly increase their trust in such judgments, but these increases in trust can occur even when AI fails to provide accurate information on a given task. In this piece, we argue that measures of metacognitive sensitivity provided by AI systems will likely play a critical role in (1) helping individuals to calibrate their level of trust in these systems and (2) optimally incorporating advice from AI into human-AI hybrid decision making. We draw upon a seminal finding in the perceptual decision-making literature that demonstrates the importance of metacognitive ratings for optimal joint decisions and outline a framework to test how different types of information provided by AI systems can guide decision making.

More than seven decades of research provide evidence that participants miss surprisinglysalient changes to visual scenes. One of the most striking displays of change blindness is shownin the work of John Grimes (1996), which demonstrated that if items in an image are altered atthe exact moment a participant moves their eyes, changes often go unnoticed. However, little isknown about participants’ awareness of changes in this task, and surprisingly, the work itself hasnever been replicated. Here, we replicate and extend the work of John Grimes. Using a new setof stimuli, we conducted two experiments in two separate laboratories (the University of Floridaand Lingnan University in Hong Kong) to facilitate “simultaneous replication” of thisphenomenon. In our first experiment, we replicated the work of John Grimes and showed thatparticipants miss retroactively obvious changes to visual scenes on approximately half of thetrials. Additionally, on “miss” trials when an (unnoticed) change occurred, participants wereapproximately equally likely to select awareness of either the pre-change or post-change featurein the image. Fixation position played a critical role in modulating awareness in the task: failingto refixate changed items after the change occurred significantly increased the miss rate. Further,on miss trials, not looking at the changed item made it more likely to report awareness of the prechange item, but fixating the item after the change increased the likelihood of selecting the postchange attribute. In our second experiment, we ran the same task using image pairs where thechanges were meaningful or incongruent. Images with either a meaning change or scenecongruence change were noticed at higher rates than neutral changes, and the higher the degreeof meaning or congruence-related change, the more likely a change was detected. Together, theseresults replicate the work of John Grimes, reveal gaze-contingent correlates of change detectionin our tasks, and can inform current theories (e.g., Higher-Order Theory) of visual awareness.

It is well known that sensory information from one modality can automatically affect judgments from a different sensory modality. However, it remains unclear what determines the strength of the influence of an irrelevant sensory cue from one modality on a perceptual judgment for a different modality. Here we test whether the strength of multisensory impact by an irrelevant sensory cue depends on participants’ objective accuracy or subjective confidence for that cue. We created visual motion stimuli with low vs. high overall motion energy, where high-energy stimuli yielded higher confidence but lower accuracy in a visual-only task. We then tested the impact of the low- and high-energy visual stimuli on auditory motion perception in 99 participants. We found that the high-energy visual stimuli influenced the auditory motion judgments more strongly than the low-energy visual stimuli, consistent with their higher confidence but contrary to their lower accuracy. A computational model assuming common principles underlying confidence reports and multisensory integration captured these effects. Our findings show that automatic multisensory integration follows subjective confidence rather than objective performance and suggest the existence of common computations across vastly different stages of perceptual decision making.

Military personnel are often required to make perceptual decisions based on noisy and uncertain information. Over the last decade, work from experiments using simple stimuli in visual psychophysical paradigms has provided evidence that in the visual periphery, observers are often prone to false alarms and variable confidence judgments in detection tasks. To better understand whether these characteristics extend to more naturalistic paradigms, our research group has developed visual detection experiments invirtual reality, where on each trial, observers are required to first fixate on specific objects, and then make judgments about whether a target (i.e., a green soldier in uniform) is present, and rate confidence in this decision. Inevitably, extending thestudy of peripheral vision to virtual reality involves trade-offs, with tension between the degree of experimental control that is employed and the ecological validity of the task. In this piece, we focus on the challenges that emerged and the lessons we have learned in pursuit of designs that strike a balance between these factors. In our first experiment, we required participants to ride in an automatically-controlled vehicle, fixate on each red stop sign, and determine whether targets were present in the periphery while looking at the stop sign. Results indicated that observers (1) did not successfully fulfill fixation requirements in the task in all trials, and (2) requiring targets to appear and disappear based on whether a fixation requirement was metresulted in flickering that served as an unintentional, salient cue. In our second experiment, we allowed participants to navigate the vehicle themselves, while again requiring the same fixation requirement and perceptual judgments at each intersection. Initial tests of this design found that variability in how participants navigated in the vehicles sometimes resulted in stopping at locations that did not allow for viewing the stop sign and soldier at the same moment. Finally, in our third experiment, we manipulated the presence of the targets on each trial, and expanded our confidence questions to include both target-present and target-absent trials. Results revealed that confidence was similar in both target-present and target-absent conditions. Based on these preliminary findings, we outline design-related recommendations for studies of the periphery, and explain the tradeoffs that extend across several military-relevant tasks, including both target detection and visual search. Finally, we also share our code to facilitate eye tracking in the HTC Vive Pro, as well as our target detection tasks

Military personnel are often required to make perceptual decisions based on noisy and uncertain information. Over the last decade, work from experiments using simple stimuli in visual psychophysical paradigms has provided evidence that in the visual periphery, observers are often prone to false alarms and variable confidence judgments in detection tasks. To better understand whether these characteristics extend to more naturalistic paradigms, our research group has developed visual detection experiments in virtual reality, where on each trial, observers are required to first fixate on specific objects, and then make judgments about whether a target (i.e., a green soldier in uniform) is present, and rate confidence in this decision. Inevitably, extending the study of peripheral vision to virtual reality involves trade-offs, with tension between the degree of experimental control that is employed and the ecological validity of the task. In this piece, we focus on the challenges that emerged and the lessons we have learned in pursuit of designs that strike a balance between these factors. In our first experiment, we required participants to ride in an automatically-controlled vehicle, fixate on each red stop sign, and determine whether targets were present in the periphery while looking at the stop sign. Results indicated that observers (1) did not successfully fulfill fixation requirements in the task in all trials, and (2) requiring targets to appear and disappear based on whether a fixation requirement was met resulted in flickering that served as an unintentional, salient cue. In our second experiment, we allowed participants to navigate the vehicle themselves, while again requiring the same fixation requirement and perceptual judgments at each intersection. Initial tests of this design found that variability in how participants navigated in the vehicles sometimes resulted in stopping at locations that did not allow for viewing the stop sign and soldier at the same moment. Finally, in our third experiment, we manipulated the presence of the targets on each trial, and expanded our confidence questions to include both target-present and target-absent trials. Results revealed that confidence was similar in both target-present and target-absent conditions. Based on these preliminary findings, we outline design-related recommendations for studies of the periphery, and explain the tradeoffs that extend across several military-relevant tasks, including both target detection and visual search. Finally, we also share our code to facilitate eye tracking in the HTC Vive Pro, as well as our target detection tasks.