AFC Lab & CARLA Talk Series

A striking range of individual differences has been reported in a variety of visual search tasks, which naturally leads to the idea that some people are better at finding things than others. However, this conclusion appears to be premature. We carried out a replication of three recent visual search experiments and found that each task showed a wide range of individual differences as predicted, and observed good test-retest reliability in all three. However, performance on any one task was not correlated with the performance in the others: participants who naturally adopt efficient search strategies in one paradigm may perform at chance in another! Furthermore, we also show that behaviour in different versions of the same paradigm can be radically different: When simple line segments are used for search items, a large range of search strategies are found. If we instead use more complex search items, all our participants effortlessly adopt an optimal strategy. These results suggest search strategies are stable over time, but context-specific. To understand visual search we, therefore, need to account not only for differences between individuals but also how individuals interact with the search task and context.

The human visual system enables us to recognize objects (e.g., this is a cup) and act upon them (e.g., grasp the cup) with astonishing ease and accuracy. For decades, it was widely accepted that these different functions rely on two separated cortical pathways. The ventral occipitotemporal pathway subserves object recognition, while the dorsal occipitoparietal pathway promotes visually guided actions. In my talk, I will discuss recent evidence from a series of neuropsychological, developmental and neuroimaging studies that were aimed to explore the nature of object representations in the dorsal pathway. The results from these studies highlight the plausible role of the dorsal pathway in object perception and reveal an interplay between shape representations derived by the two pathways. Together, these findings challenge the binary distinction between the two pathways and are consistent with the view that object recognition is not the sole product of ventral pathway computations, but instead relies on a distributed network of regions.

Visual attention refers to a set of processes allowing selection of relevant and filtering out of irrelevant information in the visual environment. A large amount of research on visual attention has involved visual search paradigms, where observers are asked to report whether a single target is present or absent. However, recent studies have revealed that these classic single-target visual search tasks only provide a snapshot of how attention is allocated in the visual environment, and that multitarget visual foraging tasks may capture the dynamics visual attention more accurately. In visual foraging, observers are asked to select multiple instances of multiple target types, as fast as they can. A critical question in foraging research concerns the factors driving the next target selection. Most likely, this would require two steps: (1) identifying a set of candidates for the next selection, and (2) selecting the best option among these candidates. After having briefly described the advantage of visual foraging over visual search, I will review recent visual foraging studies testing the influence of several manipulations (e.g., target crypticity, number of items, selection modality) on foraging behaviour. Overall, these studies revealed that the next target selection during visual foraging is determined by the competition between three factors: target value, target proximity, and priming of features. I will explain how the analysis of individual differences in foraging behaviour can provide important information, with the idea that individuals show by-default internal biases toward value, proximity and priming that determine their search strategy and behaviour.

In recent years, more and more evidence has accumulated showing that many studies in psychological research cannot be replicated, effects are often overestimated, and little is publicly known about unsuccessful studies. What are the mechanisms behind this crisis? In this talk, I will explain how we got there and why it is still difficult to break free from the current system. I will further explain which role Open Science plays within the replication crisis and how it can help to improve science. This might sound like a pessimistic, negative talk, but I will end it on a positive note, I promise!

Case-control comparisons are a gold standard method for diagnosing and researching neuropsychological deficits and dissociations at the single-case level. These statistical tests, developed by John Crawford and collaborators, provide quantitative criteria for the classical concepts of deficit, dissociation and double-dissociation. Much attention has been given to the control of Type I (false positive) errors for these tests, but far less to the avoidance of Type II (false negative) errors; that is, to statistical power. I will describe the origins and limits of statistical power for case-control comparisons, showing that there are hard upper limits on power, which have important implications for the design and interpretation of single-case studies. My aim is to stimulate discussion of the inferential status of single-case neuropsychological evidence, particularly with respect to contemporary ideals of open science and study preregistration.

State-of-the-art machine vision models can predict human recognition memory for complex scenes with astonishing accuracy. In this talk I present work that investigated how memorable scenes are actually remembered and experienced by human observers. We found that memorable scenes were recognized largely based on recollection of specific episodic details but also based on familiarity for an entire scene. I thus highlight current limitations in machine vision models emulating human recognition memory, with promising opportunities for future research. Moreover, we were interested in what observers specifically remember about complex scenes. We thus considered the functional role of eye-movements as a window into the content of memories, particularly when observers recollected specific information about a scene. We found that when observers formed a memory representation that they later recollected (compared to scenes that only felt familiar), the overall extent of exploration was broader, with a specific subset of fixations clustered around later to-be-recollected scene content, irrespective of the memorability of a scene. I discuss the critical role that our viewing behavior plays in visual memory formation and retrieval and point to potential implications for machine vision models predicting the content of human memories.

Deciding whether two different face photographs or voice samples are from the same person represent fundamental challenges within applied settings. To date, most research has focussed on average performance in these tests, failing to consider individual differences and within-person consistency in responses. In the current studies, participants completed the same face or voice matching test on two separate occasions, allowing comparison of overall accuracy across the two timepoints as well as consistency in trial-level responses. In both experiments, participants were highly consistent in their performances. In addition, we demonstrated a large association between consistency and accuracy, with the most accurate participants also tending to be the most consistent. This is an important result for applied settings in which organisational groups of super-matchers are deployed in real-world contexts. Being able to reliably identify these high performers based upon only a single test informs regarding recruitment for law enforcement agencies worldwide.

Progress in psychology has been frustrated by challenges concerning replicability, generalizability, strategy selection, inferential reproducibility, and computational reproducibility. Although often discussed separately, I argue that these five challenges share a common cause: insufficient investment of resources into the typical psychology study. I further suggest that big team science can help address these challenges by allowing researchers to pool their resources to efficiently and drastically increase the amount of resources available for a single study. However, the current incentives, infrastructure, and institutions in academic science have all developed under the assumption that science is conducted by solo Principal Investigators and their dependent trainees. These barriers must be overcome if big team science is to be sustainable. Big team science likely also carries unique risks, such as the potential for big team science institutions to monopolize power, become overly conservative, make mistakes at a grand scale, or fail entirely due to mismanagement and a lack of financial sustainability. I illustrate the promise, barriers, and risks of big team science with the experiences of the Psychological Science Accelerator, a global research network of over 1400 members from 70+ countries.

The human brain is a heavily interconnected structure giving rise to complex functions. While brain functionality is mostly revealed during wakefulness, the sleeping brain might offer another view into physiological and pathological brain connectivity. Furthermore, there is a large body of evidence supporting that sleep mediates plastic changes in brain connectivity. Although brain plasticity depends on environmental input which is provided in the waking state, disconnection during sleep might be necessary for integrating new into existing information and at the same time restoring brain efficiency. In this talk, I will present structural, molecular, and electrophysiological markers of brain connectivity and sleep-dependent restoration that we have evaluated using Magnetic Resonance Imaging and electroencephalography in a healthy population. In a second step, I will show how we translated the gained findings into two clinical populations in which alterations in brain connectivity have been described, the neuropsychiatric disorder attention-deficit/hyperactivity disorder (ADHD) and the neurologic disorder thalamic ischemic stroke.

Face matching tests have traditionally been developed to assess human face perception in the neurotypical range, but methods that underlie their development often make it difficult for these measures to be applied in atypical populations (developmental prosopagnosics, super recognizers) due to unadjusted difficulty. We have recently presented the development of the Oxford Face Matching Test, a measure that bases individual item-difficulty on algorithmically derived similarity of presented stimuli. The measure seems useful as it can be given online or in-laboratory, has good discriminability and high test-retest reliability in the neurotypical groups. In addition, it has good validity in separating atypical groups at either of the spectrum ends. In this talk, I examine the stability of the OFMT and other traditionally used measures in atypical groups. On top of the theoretical significance of determining whether reliability of tests is equivalent in atypical population, this is an important question because of the practical concerns of retesting the same participants across different lab groups. Theoretical and practical implications for further test development and data sharing are discussed.