Cognitive Psychology seminars

Margaret Livingstone of Harvard Medical School presents in Princeton Neuroscience Institute's public seminar series. Livingstone's laboratory studies how visual recognition occurs in the primate brain using behavior, brain imaging, and electrophysiology.

In this talk, I will explore how social affective biases arise even in the absence of motivational factors as an emergent outcome of the basic structure of social learning. In several studies, we found that initial negative interactions with some members of a group can cause subsequent avoidance of the entire group, and that this avoidance perpetuates stereotypes. Additional cognitive modeling discovered that approach and avoidance behavior based on biased beliefs not only influences the evaluative (positive or negative) impressions of group members, but also shapes the depth of the cognitive representations available to learn about individuals. In other words, people have richer cognitive representations of members of groups that are not avoided, akin to individualized vs group level categories. I will end presenting a series of multi-agent reinforcement learning simulations that demonstrate the emergence of these social-structural feedback loops in the development and maintenance of affective biases.

Many situations rely on the accurate identification of people with whom we are unfamiliar. For example, security at airports or in police investigations require the identification of individuals from photo-ID. Yet, the identification of unfamiliar faces is error prone, even for practitioners who routinely perform this task. Indeed, even training protocols often yield no discernible improvement. The challenge of unfamiliar face identification is often thought of as a perceptual problem; however, this assumption ignores the potential role of decision-making and its contributing factors (e.g., criterion placement). In this talk, I am going to present a series of experiments that investigate the role of decision-making in face identification.

Within the last decade, Deep Artificial Neural Networks (DNNs) have emerged as powerful computer vision systems that match or exceed human performance on many benchmark tasks such as image classification. But whether current DNNs are suitable computational models of the human visual system remains an open question: While DNNs have proven to be capable of predicting neural activations in primate visual cortex, psychophysical experiments have shown behavioral differences between DNNs and human subjects, as quantified by error consistency. Error consistency is typically measured by briefly presenting natural or corrupted images to human subjects and asking them to perform an n-way classification task under time pressure. But for how long should stimuli ideally be presented to guarantee a fair comparison with DNNs? Here we investigate the influence of presentation time on error consistency, to test the hypothesis that higher-level processing drives behavioral differences. We systematically vary presentation times of backward-masked stimuli from 8.3ms to 266ms and measure human performance and reaction times on natural, lowpass-filtered and noisy images. Our experiment constitutes a fine-grained analysis of human image classification under both image corruptions and time pressure, showing that even drastically time-constrained humans who are exposed to the stimuli for only two frames, i.e. 16.6ms, can still solve our 8-way classification task with success rates way above chance. We also find that human-to-human error consistency is already stable at 16.6ms.

I my talk I will give an overview of recent research on deception and concealed information detection. I will start with a short introduction on the problems and shortcomings of traditional deception detection tools and why those still prevail in many recent approaches (e.g., in AI-based deception detection). I want to argue for the importance of more fundamental deception research and give some examples for insights gained therefrom. In the second part of the talk, I will introduce the Concealed Information Test (CIT), a promising paradigm for research and applied contexts to investigate whether someone actually recognizes information that they do not want to reveal. The CIT is based on solid scientific theory and produces large effects sizes in laboratory studies with a number of different measures (e.g., behavioral, psychophysiological, and neural measures). I will highlight some challenges a forensic application of the CIT still faces and how scientific research could assist in overcoming those.

In 2014, the US National Research Council called for the development of new lineup technologies to increase eyewitness identification accuracy (National Research Council, 2014). In a police lineup, a suspect is presented alongside multiple individuals known to be innocent who resemble the suspect in physical appearance know as fillers. A correct identification decision by an eyewitness can lead to a guilty suspect being convicted or an innocent suspect being exonerated from suspicion. An incorrect decision can result in the perpetrator remaining at large, or even a wrongful conviction of a mistakenly identified person. Incorrect decisions carry considerable human and financial costs, so it is essential to develop and enact lineup procedures that maximise discrimination accuracy, or the witness’ ability to distinguish guilty from innocent suspects. This talk focuses on new technology and innovation in the field of eyewitness identification. We will focus on the interactive lineup, which is a procedure that we developed based on research and theory from the basic science literature on face perception and recognition. The interactive lineup enables witnesses to actively explore and dynamically view the lineup members. The procedure has been shown to maximize discrimination accuracy, which is the witness’ ability to discriminate guilty from innocent suspects. The talk will conclude by reflecting on emerging technological frontiers and research opportunities.

Filmmakers and editors have empirically developed techniques to ensure the spatiotemporal continuity of a film's narration. In terms of time, editing techniques (e.g., elliptical, overlapping, or cut minimization) allow for the manipulation of the perceived duration of events as they unfold on screen. More specifically, a scene can be edited to be time compressed, expanded, or real-time in terms of its perceived duration. Despite the consistent application of these techniques in filmmaking, their perceptual outcomes have not been experimentally validated. Given that viewing a film is experienced as a precise simulation of the physical world, the use of cinematic material to examine aspects of time perception allows for experimentation with high ecological validity, while filmmakers gain more insight on how empirically developed techniques influence viewers' time percept. Here, we investigated how such time manipulation techniques of an action affect a scene's perceived duration. Specifically, we presented videos depicting different actions (e.g., a woman talking on the phone), edited according to the techniques applied for temporal manipulation and asked participants to make verbal estimations of the presented scenes' perceived durations. Analysis of data revealed that the duration of expanded scenes was significantly overestimated as compared to that of compressed and real-time scenes, as was the duration of real-time scenes as compared to that of compressed scenes. Therefore, our results validate the empirical techniques applied for the modulation of a scene's perceived duration. We also found interactions on time estimates of scene type and editing technique as a function of the characteristics and the action of the scene presented. Thus, these findings add to the discussion that the content and characteristics of a scene, along with the editing technique applied, can also modulate perceived duration. Our findings are discussed by considering current timing frameworks, as well as attentional saliency algorithms measuring the visual saliency of the presented stimuli.

Rhythmic flashing light, or “Ganzflicker”, can elicit altered states of consciousness and hallucinations, bringing your mind’s eye out into the real world. What do you experience if you have a super mind’s eye, or none at all? In this talk, I will discuss how Ganzflicker has been used to simulate psychedelic experiences, how it can help us predict symptoms of psychosis, and even tap into the neural basis of hallucinations.

How central were psychological features deriving from our visual systems to the early evolution of human visual culture? Art making emerged deep in our evolutionary history, with the earliest art appearing over 100,000 years ago as geometric patterns etched on fragments of ochre and shell, and figurative representations of prey animals flourishing in the Upper Palaeolithic (c. 40,000 – 15,000 years ago). The latter reflects a complex visual process; the ability to represent something that exists in the real world as a flat, two-dimensional image. In this presentation, I argue that pareidolia – the psychological phenomenon of seeing meaningful forms in random patterns, such as perceiving faces in clouds – was a fundamental process that facilitated the emergence of figurative representation. The influence of pareidolia has often been anecdotally observed in Upper Palaeolithic art examples, particularly cave art where the topographic features of cave wall were incorporated into animal depictions. Using novel virtual reality (VR) light simulations, I tested three hypotheses relating to pareidolia in the caves of Upper Palaeolithic cave art in the caves of Las Monedas and La Pasiega (Cantabria, Spain). To evaluate this further, I also developed an interdisciplinary VR eye-tracking experiment, where participants were immersed in virtual caves based on the cave of El Castillo (Cantabria, Spain). Together, these case studies suggest that pareidolia was an intrinsic part of artist-cave interactions (‘conversations’) that influenced the form and placement of figurative depictions in the cave. This has broader implications for conceiving of the role of visual psychological phenomena in the emergence and development of figurative art in the Palaeolithic.

Using videos from the Deepfake Detection Challenge (cf. Groh et al., 2021), we investigated human deepfake detection performance (DDP) in two unique observer groups: Super-Recognizers (SRs) and "normal" officers from within the 18K members of the Berlin Police. SRs were identified either via previously proposed lab-based procedures (Ramon, 2021) or the only existing tool for SR identification involving increasingly challenging, authentic forensic material: beSure® (Berlin Test For Super-Recognizer Identification; Ramon & Rjosk, 2022). Across two experiments we examined deepfake detection performance (DDP) in participants who judged single videos and pairs of videos in a 2AFC decision setting. We explored speed-accuracy trade-offs in DDP, compared DDP between lab-identified SRs and non-SRs, and police officers whose face identity processing skills had been extensively tested using challenging. In this talk I will discuss our surprising findings and argue that further work is needed too determine whether face identity processing is related to DDP or not.

In the real world, object arrangement follows a number of rules. Some of the rules pertain to the spatial relations between objects and scenes (i.e., syntactic rules) and others about the contextual relations (i.e., semantic rules). Research has shown that violation of semantic rules influences interval timing with the duration of scenes containing such violations to be overestimated as compared to scenes with no violations. However, no study has yet investigated whether both semantic and syntactic violations can affect timing in the same way. Furthermore, it is unclear whether the effect of scene violations on timing is due to attentional or other cognitive accounts. Using an oddball paradigm and real-world scenes with or without semantic and syntactic violations, we conducted two experiments on whether time dilation will be obtained in the presence of any type of scene violation and the role of attention in any such effect. Our results from Experiment 1 showed that time dilation indeed occurred in the presence of syntactic violations, while time compression was observed for semantic violations. In Experiment 2, we further investigated whether these estimations were driven by attentional accounts, by utilizing a contrast manipulation of the target objects. The results showed that an increased contrast led to duration overestimation for both semantic and syntactic oddballs. Together, our results indicate that scene violations differentially affect timing due to violation processing differences and, moreover, their effect on timing seems to be sensitive to attentional manipulations such as target contrast.

First, a new measure of MI for reaction times is proposed that takes the entire RT distribution into account. Second, we present some recent developments in TWIN modeling, including a new proposal for the sound-induced flash illusion (SIFI).

The defining characteristic of development prosopagnosia is severe difficulty recognising familiar faces in everyday life. Numerous studies have reported that the condition is highly heterogeneous in terms of both presentation and severity with many mixed findings in the literature. I will present behavioural data from a large face processing test battery (n = 24 DPs) as well as some early findings from a larger survey of the lived experience of individuals with DP and discuss how insights from individuals' real-world experience can help to understand and interpret lab-based data.

In our daily lives, we perceive things as possessing a mind (e.g., people) or lacking one (e.g., shoes). Intriguingly, how much mind we attribute to people can vary, with real people perceived to have more mind than depictions of individuals, such as photographs. Drawing from a range of research methodologies, including naturalistic observation, mobile eye tracking, and surreptitious behavior monitoring, I discuss how various shades of mind influence human attention and behaviour. The findings suggest the novel concept that overt attention (where one looks) in real-life is fundamentally supported by covert attention (attending to someone out of the corner of one's eye).

People largely differ with respect to how well they can learn, memorize, and perceive faces. In this talk, I address two potential sources of variation. One factor might be people’s ability to adapt their perception to the kind of faces they are currently exposed to. For instance, some studies report that those who show larger adaptation effects are also better at performing face learning and memory tasks. Another factor might be people’s sensitivity to perceive fine differences between similar-looking faces. In fact, one study shows that the brain of good performers in a face memory task shows larger neural differences between similar-looking faces. Capitalizing on this body of evidence, I present a behavioural study where I explore the relationship between people’s perceptual adaptability and sensitivity and their individual face processing performance.

Working memory is about the past but for the future. Adopting such a future-focused perspective shifts the narrative of working memory as a limited-capacity storage system to working memory as an anticipatory buffer that helps us prepare for potential and sequential upcoming behaviour. In my talk, I will present a series of our recent studies that have started to reveal emerging principles of a working memory that looks forward – highlighting, amongst others, how selective attention plays a vital role in prioritising internal contents for behaviour, and the bi-directional links between visual working memory and action. These studies show how studying the dynamics of working memory, selective attention, and action together paves way for an integrated understanding of how mind serves behaviour.