Standard experimental paradigm designs and data exclusion practices in cognitive psychology can inadvertently introduce systematic "shadow" biases in participant samples.

Standard cognitive psychology research practices can introduce inadvertent sampling biases that reduce the reliability and generalizability of the findings. Researchers commonly acknowledge and understand that any given study sample is not perfectly generalizable, especially when implementing typical experimental constraints (e.g., limiting recruitment to specific age ranges or to individuals with normal color vision). However, less obvious systematic sampling constraints, referred to here as "shadow" biases, can be unintentionally introduced and can easily go unnoticed. For example, many standard cognitive psychology study designs involve lengthy and tedious experiments with simple, repetitive stimuli. Such testing environments may 1) be aversive to some would-be participants (e.g., those high in certain neurodivergent symptoms) who may self-select not to enroll in such studies, or 2) contribute to participant attrition, both of which reduce the sample's representativeness. Likewise, standard performance-based data exclusion efforts (e.g., minimum accuracy or response time) or attention checks can systematically remove data from participants from subsets of the population (e.g., those low in conscientiousness). This commentary focuses on the theoretical and practical issues behind these non-obvious and often unacknowledged "shadow" biases, offers a simple illustration with real data as a proof of concept of how applying attention checks can systematically skew latent/hidden variables in the included population, and then discusses the broader implications with suggestions for how to manage and reduce, or at a minimum acknowledge, the problem.

Evidence for a Spoken Word Lexicon in the Auditory Ventral Stream.

The existence of a neural representation for whole words (i.e., a lexicon) is a common feature of many models of speech processing. Prior studies have provided evidence for a visual lexicon containing representations of whole written words in an area of the ventral visual stream known as the visual word form area. Similar experimental support for an auditory lexicon containing representations of spoken words has yet to be shown. Using functional magnetic resonance imaging rapid adaptation techniques, we provide evidence for an auditory lexicon in the auditory word form area in the human left anterior superior temporal gyrus that contains representations highly selective for individual spoken words. Furthermore, we show that familiarization with novel auditory words sharpens the selectivity of their representations in the auditory word form area. These findings reveal strong parallels in how the brain represents written and spoken words, showing convergent processing strategies across modalities in the visual and auditory ventral streams.

Increases in symptoms associated with obsessive-compulsive disorder among university students during the COVID-19 pandemic.

OBJECTIVE: The long-term consequences of the COVID-19 pandemic on college students' mental health remains unknown. The current study explored self-reported Obsessive-Compulsive symptomatology among college student cohorts from pre-, peak-, and later-pandemic time points. PARTICIPANTS: Undergraduate college students (N = 524) who volunteered for course credit. METHODS: Self-report responses on the Dimensional Obsessive-Compulsive Scale (DOCS), which includes subscales for contamination, unacceptable thoughts, harm responsibility, and symmetry, were collected from November 29, 2016 through April 27, 2021 and assessed for differences between the pre-, peak-, and later-pandemic cohorts. RESULTS: Peak-pandemic responders reported higher symptomatology for contamination and unacceptable thoughts compared to pre-pandemic responders (and for pre- vs. later-pandemic for contamination), with no significant effects for symmetry or harm responsibility. CONCLUSIONS: Although the longer-term consequences of the COVID-19 pandemic on students remains unknown, a greater shift in college mental health services from prevention to assessing and addressing more immediate challenges may be necessary.

Conscientiousness protects visual search performance from the impact of fatigue.

Visual search-looking for targets among distractors-underlies many critical professions (e.g., radiology, aviation security) that demand optimal performance. As such, it is important to identify, understand, and ameliorate negative factors such as fatigue-mental and/or physical tiredness that leads to diminished function. One way to reduce the detrimental effects is to minimize fatigue itself (e.g., scheduled breaks, adjusting pre-shift behaviors), but this is not always possible or sufficient. The current study explored whether some individuals are less susceptible to the impact of fatigue than others; specifically, if conscientiousness, the ability to control impulses and plan, moderates fatigue's impact. Participants (N = 374) self-reported their energy (i.e., the inverse of fatigue) and conscientiousness levels and completed a search task. Self-report measures were gathered prior to completing the search task as part of a large set of surveys so that participants could not anticipate any particular research question. Preregistered linear mixed-effect analyses revealed main effects of energy level (lower state energy related to lower accuracy) and conscientiousness (more trait conscientiousness related to higher accuracy), and, critically, a significant interaction between energy level and conscientiousness. A follow-up analysis, that was designed to illustrate the nature of the primary result, divided participants into above- vs. below-median conscientiousness groups and revealed a significant negative relationship between energy level and accuracy for the below median, but not above-median, group. The results raise intriguing operational possibilities for visual search professions, with the most direct implication being the incorporation of conscientiousness measures to personnel selection processes.

A precise quantification of how prior experience informs current behavior.

Human behavior does not exist in a bubble-it is influenced by countless forces, including each individual's current goals, preexisting cognitive biases, and prior experience. The current project leveraged a massive behavioral data set to provide a data-driven quantification of the relationship between prior experience and current behavior. Data from two different behavioral tasks (a categorization task and a visual search task) demonstrated that prior history had a precise, systematic, and meaningful influence on subsequent performance. Specifically, the greater the evidence for (or against) all aspects of the current trial, the more (or less) efficient behavior was on that trial. The robust influence of prior experience was present for even distracting and likely unattended information. The ubiquity and consistency of the effect for features both related and unrelated to stimulus presence suggests a domain-general mechanism that increases the efficiency of behavior in contexts that match prior experience. These findings are theoretically important for understanding behavioral adaptation, experimentally powerful for directly addressing effects of previous trials when designing and analyzing research projects, and potentially useful for optimizing behavior in various applied contexts. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Moving Beyond the Keypress: As Technology Advances, so Should Psychology Response Time Measurements.

Decades of research in cognitive psychology have largely relied on simple key or button presses to quantify human behavior. While many valuable discoveries have been made, a richer response modality may reveal more information regarding the different processes that underlie complex human behavior. This study provides a proof of concept for using a touch-and-swipe response method to separate response time into two components to extract more meaningful behavioral insights. Across several analyses, the two components were consistently shown to be separable, independent measurements of behavior. Furthermore, evaluating these isolated response time components improved inferential power and clarity of behavioral patterns. The touch-and-swipe response method is simple and easy-to-use, and it shows promise for more accurately targeting mechanisms of interest.

Great expectations: minor differences in initial instructions have a major impact on visual search in the absence of feedback.

Professions such as radiology and aviation security screening that rely on visual search-the act of looking for targets among distractors-often cannot provide operators immediate feedback, which can create situations where performance may be largely driven by the searchers' own expectations. For example, if searchers do not expect relatively hard-to-spot targets to be present in a given search, they may find easy-to-spot targets but systematically quit searching before finding more difficult ones. Without feedback, searchers can create self-fulfilling prophecies where they incorrectly reinforce initial biases (e.g., first assuming and then, perhaps wrongly, concluding hard-to-spot targets are rare). In the current study, two groups of searchers completed an identical visual search task but with just a single difference in their initial task instructions before the experiment started; those in the "high-expectation" condition were told that each trial could have one or two targets present (i.e., correctly implying no target-absent trials) and those in the "low-expectation" condition were told that each trial would have up to two targets (i.e., incorrectly implying there could be target-absent trials). Compared to the high-expectation group, the low-expectation group had a lower hit rate, lower false alarm rate and quit trials more quickly, consistent with a lower quitting threshold (i.e., performing less exhaustive searches) and a potentially higher target-present decision criterion. The expectation effect was present from the start and remained across the experiment-despite exposure to the same true distribution of targets, the groups' performances remained divergent, primarily driven by the different subjective experiences caused by each groups' self-fulfilling prophecies. The effects were limited to the single-targets trials, which provides insights into the mechanisms affected by the initial expectations set by the instructions. In sum, initial expectations can have dramatic influences-searchers who do not expect to find a target, are less likely to find a target as they are more likely to quit searching earlier.

A crash in visual processing: Interference between feedforward and feedback of successive targets limits detection and categorization.

The human visual system can detect objects in streams of rapidly presented images at presentation rates of 70 Hz and beyond. Yet, target detection is often impaired when multiple targets are presented in quick temporal succession. Here, we provide evidence for the hypothesis that such impairments can arise from interference between "top-down" feedback signals and the initial "bottom-up" feedforward processing of the second target. Although it is has been recently shown that feedback signals are important for visual detection, this "crash" in neural processing affected both the detection and categorization of both targets. Moreover, experimentally reducing such interference between the feedforward and feedback portions of the two targets substantially improved participants' performance. The results indicate a key role of top-down re-entrant feedback signals and show how their interference with a successive target's feedforward process determine human behavior. These results are not just relevant for our understanding of how, when, and where capacity limits in the brain's processing abilities can arise, but also have ramifications spanning topics from consciousness to learning and attention.

Correction to: How to correctly put the "subsequent" in subsequent search miss errors.

The following formatting changes to the figures and table need to be made in order to enhance readability.

How to correctly put the "subsequent" in subsequent search miss errors.

Visual search, finding targets among distractors, is theoretically interesting and practically important as it involves many cognitive abilities and is vital for several critical industries (e.g., radiology, baggage screening). Unfortunately, search is especially error prone when more than one target is present in a display (a phenomenon termed the satisfaction of search effect or the subsequent search miss effect). The general effect is that observers are more likely to miss a second target if a first was already detected. Unpacking the underlying mechanisms requires two key aspects in analysis and design. First, to speak to the "subsequent" nature of the effect, the analyses must compare performance on single-target trials to performance for a second target in dual-target displays after a first has been found. Second, the design must include single-target displays that are matched in difficulty to each dual-target display to enable fair comparisons. However, it is not clear that prior research has met these two standards simultaneously. Work from academic radiology has primarily used designs with well-matched single- and dual-target trials, but most employed analyses that do not focus solely on performance after a first target has been detected. Work from cognitive psychology has generally performed the correct analyses, but relied on unmatched single- and dual-target trials, introducing a confound that could distort the results. In the current paper, we demonstrate the impact of this confound in empirical data and provide a roadmap for proper study design and analyses.

There Is a "U" in Clutter: Evidence for Robust Sparse Codes Underlying Clutter Tolerance in Human Vision.

The ability to recognize objects in clutter is crucial for human vision, yet the underlying neural computations remain poorly understood. Previous single-unit electrophysiology recordings in inferotemporal cortex in monkeys and fMRI studies of object-selective cortex in humans have shown that the responses to pairs of objects can sometimes be well described as a weighted average of the responses to the constituent objects. Yet, from a computational standpoint, it is not clear how the challenge of object recognition in clutter can be solved if downstream areas must disentangle the identity of an unknown number of individual objects from the confounded average neuronal responses. An alternative idea is that recognition is based on a subpopulation of neurons that are robust to clutter, i.e., that do not show response averaging, but rather robust object-selective responses in the presence of clutter. Here we show that simulations using the HMAX model of object recognition in cortex can fit the aforementioned single-unit and fMRI data, showing that the averaging-like responses can be understood as the result of responses of object-selective neurons to suboptimal stimuli. Moreover, the model shows how object recognition can be achieved by a sparse readout of neurons whose selectivity is robust to clutter. Finally, the model provides a novel prediction about human object recognition performance, namely, that target recognition ability should show a U-shaped dependency on the similarity of simultaneously presented clutter objects. This prediction is confirmed experimentally, supporting a simple, unifying model of how the brain performs object recognition in clutter. SIGNIFICANCE STATEMENT: The neural mechanisms underlying object recognition in cluttered scenes (i.e., containing more than one object) remain poorly understood. Studies have suggested that neural responses to multiple objects correspond to an average of the responses to the constituent objects. Yet, it is unclear how the identities of an unknown number of objects could be disentangled from a confounded average response. Here, we use a popular computational biological vision model to show that averaging-like responses can result from responses of clutter-tolerant neurons to suboptimal stimuli. The model also provides a novel prediction, that human detection ability should show a U-shaped dependency on target-clutter similarity, which is confirmed experimentally, supporting a simple, unifying account of how the brain performs object recognition in clutter.