Cognitive Psychology seminars

Self-control is a central aspect of free will. Because self-control is often described in terms of resisting temptations, research on the cognitive neuroscience of free will often focuses on mechanisms of top-down regulation. We argue that this obscures a crucial temporal dimension of free will: now-then regulation. We distinguish now-then regulation from top-down regulation, and situate now-then regulation within a broader account of temporally extended agency. In highlighting this temporal dimension of control, we aim to provide a more nuanced account of how motivation informs action over time, different kinds of regulatory processes underlying the planning and execution of action, and the temporal components of reasons-responsiveness.

In decision-making under risk (DMR) participants' choices are based on probability values systematically different from those that are objectively correct. Similar systematic distortions are found in tasks involving relative frequency judgments (JRF). These distortions limit performance in a wide variety of tasks and an evident question is, why do we systematically fail in our use of probability and relative frequency information? We propose a Bounded Log-Odds Model (BLO) of probability and relative frequency distortion based on three assumptions: (1) log-odds: probability and relative frequency are mapped to an internal log-odds scale, (2) boundedness: the range of representations of probability and relative frequency are bounded and the bounds change dynamically with task, and (3) variance compensation: the mapping compensates in part for uncertainty in probability and relative frequency values. We compared human performance in both DMR and JRF tasks to the predictions of the BLO model as well as eleven alternative models each missing one or more of the underlying BLO assumptions (factorial model comparison). The BLO model and its assumptions proved to be superior to any of the alternatives. In a separate analysis, we found that BLO accounts for individual participants’ data better than any previous model in the DMR literature. We also found that, subject to the boundedness limitation, participants’ choice of distortion approximately maximized the mutual information between objective task-relevant values and internal values, a form of bounded rationality.

Natural behavior reveals the way that gaze serves the needs of the current task, and the complex cognitive control mechanisms that are involved. It has become increasingly clear that even the simplest actions involve complex decision processes that depend on an interaction of visual information, knowledge of the current environment, and the intrinsic costs and benefits of actions choices. I will explore these ideas in the context of walking in natural terrain, where we are able to recover the 3D structure of the visual environment. We show that subjects choose flexible paths that depend on the flatness of the terrain over the next few steps. Subjects trade off flatness with straightness of their paths towards the goal, indicating a nuanced trade-off between stability and energetic costs on both the time scale of the next step and longer-range constraints.

Working memory is the sketchpad of consciousness, the fundamental mechanism the brain uses to gain volitional control over its thoughts and actions. For the past 50 years, working memory has been thought to rely on cortical neurons that fire continuous impulses that keep thoughts “online”. However, new work from our lab has revealed more complex dynamics. The impulses fire sparsely and interact with brain rhythms of different frequencies. Higher frequency gamma (>35 Hz) rhythms help carry the contents of working memory while lower frequency alpha/beta (~8-30 Hz) rhythms act as control signals that gate access to and clear out working memory. In other words, a rhythmic dance between brain rhythms may underlie your ability to control your own thoughts.

The tight relationship between attention and conscious perception has been extensively researched in the past decades. However, whether attentional modulation extended to unconscious processes remained largely unknown, particularly when it came to abstract and high-level processing. I will talk about a recent study where we utilized the Stroop paradigm to show that task load gates unconscious semantic processing. In a series of psychophysical experiments, the unconscious word semantics influenced conscious task performance only under the low task load condition, but not the high task load condition. Intriguingly, with enough practice in the high task load condition, the unconscious effect reemerged. These findings suggest a competition of attentional resources between unconscious and conscious processes, challenging the automaticity account of unconscious processing.

The talk will give a tour of Guided Search 6.0 (GS6), the latest evolution of the Guided Search model of visual search. Part 1 describes The Mechanics of Search. Because we cannot recognize more than a few items at a time, selective attention is used to prioritize items for processing. Selective attention to an item allows its features to be bound together into a representation that can be matched to a target template in memory or rejected as a distractor. The binding and recognition of an attended object is modeled as a diffusion process taking > 150 msec/item. Since selection occurs more frequently than that, it follows that multiple items are undergoing recognition at the same time, though asynchronously, making GS6 a hybrid serial and parallel model. If a target is not found, search terminates when an accumulating quitting signal reaches a threshold. Part 2 elaborates on the five sources of Guidance that are combined into a spatial “priority map” to guide the deployment of attention (hence “guided search”). These are (1) top-down and (2) bottom-up feature guidance, (3) prior history (e.g. priming), (4) reward, and (5) scene syntax and semantics. Finally, in Part 3, we will consider the internal representation of what we are searching for; what is often called “the search template”. That search template is really two templates: a guiding template (probably in working memory) and a target template (in long term memory). Put these pieces together and you have GS6.

Many models of attention assume that attentional selection takes place at a specific moment in time which demarcates the critical transition from pre-attentive to attentive processing of sensory input. We argue that this intuitively appealing account is not only inaccurate, but has led to substantial conceptual confusion (to the point where some attention researchers offer to abandon the term ‘attention’ altogether). As an alternative, we offer a “diachronic” framework that describes attentional selectivity as a process that unfolds over time. Key to this view is the concept of attentional episodes, brief periods of intense attentional amplification of sensory representations that regulate access to working memory and response-related processes. We describe how attentional episodes are linked to earlier attentional mechanisms and to recurrent processing at the neural level. We present data showing that multiple sequential events can be involuntarily encoded in working memory when they appear during the same attentional episode, whether they are relevant or not. We also discuss the costs associated with processing multiple events within a single episode. Finally, we argue that breaking down the dichotomy between pre-attentive and attentive (as well as early vs. late selection) offers new solutions to old problems in attention research that have never been resolved. It can provide a unified and conceptually coherent account of the network of cognitive and neural processes that produce the goal-directed selectivity in perceptual processing that is commonly referred to as “attention”.

Smooth pursuit eye movements are among our most intriguing motor behaviors. They are able to keep the line of sight on smoothly moving targets with little or no overt effort or deliberate planning, and they can respond quickly and accurately to changes in the trajectory of motion of targets. Nevertheless, despite these seeming automatic characteristics, pursuit is highly sensitive to high-level factors, such as the choices made about attention, or beliefs about the direction of upcoming motion. Investigators have struggled for decades with the problem of incorporating both high- and low-level processes into a single coherent model. This talk will present an overview of the current state of efforts to incorporate high- and low-level influences, as well as new observations that add to our understanding of both types of influences. These observations (in contrast to much of the literature) focus on the directional properties of pursuit. Studies will be presented that show: (1) the direction of smooth pursuit made to pursue fields of noisy random dots depends on the relative reliability of the sensory signal and the expected motion direction; (2) smooth pursuit shows predictive responses that depend on the interpretation of cues that signal an impending collision; and (3) smooth pursuit during a change in target direction displays kinematic properties consistent with the well-known two-thirds power law. Implications for incorporating high- and low-level factors into the same framework will be discussed.

A common result is that comparison settings (i.e., several stimuli introduced simultaneously) favor conceptualization and generalization. However still little is known of the solving strategies used by children to compare and generalize novel words. Understanding the temporal dynamics of children’s solving strategies may help assess which processes underlie generalization. We tested children in noun and relational noun generalization tasks and collected eye tracking data. To analyze and interpret the data we followed predictions made by existing models of analogical reasoning and generalization. The data reveals clear patterns of exploration in which participants compare learning items before searching for a solution. Analyses of the beginning of trials show that early comparisons favor generalization and that errors may be caused by a lake of early comparison. Children then pursue their search in different ways according to the task. In this presentation I will present the generalization strategies revealed by eye tracking, compare the strategies from both tasks and confront them to existing models.

Despite the common advice “not to judge a book by its cover”, we form impressions of character within a second of seeing a stranger’s face. These impressions have widespread consequences for society and for the economy, making it vital that we have a clear theoretical understanding of which impressions are important and how they are formed. In my talk, I outline a data-driven approach to answering these questions, starting by building models of the key dimensions underlying impressions of naturalistic face images. Overall, my findings suggest deeper links between the fields of face perception and social stereotyping than have previously been recognised.

The role of attention in working memory remains controversial, but there is some agreement on the notion that the focus of attention holds mnemonic representations in a privileged state of heightened accessibility in working memory, resulting in better memory performance for items that receive focused attention during retention. Closely related, representations held in the focus of attention are often observed to be robust and protected from degradation caused by either perceptual interference (e.g., Makovski & Jiang, 2007; van Moorselaar et al., 2015) or decay (e.g., Barrouillet et al., 2007). Recent findings indicate, however, that representations held in the focus of attention are particularly vulnerable to degradation, and thus, appear to be particularly fragile rather than robust (e.g., Hitch et al., 2018; Hu et al., 2014). The present set of experiments aims at understanding the apparent paradox of information in the focus of attention having a protected vs. vulnerable status in working memory. To that end, we examined the effect of perceptual interference on memory performance for information that was held within vs. outside the focus of attention, across different ways of bringing items in the focus of attention and across different time scales.

Episodic memory performance decreases with advancing age. According to theoretical models, such memory decline might be a consequence of age-related reductions in the ability to form distinct neural representations of our past. In this talk, I want to present our new age-comparative fMRI study investigating age-related neural dedifferentiation across different representational levels. By combining univariate analyses and searchlight pattern similarity analyses, we found that older adults show reduced category selective processing in higher visual areas, less specific item representations in occipital regions and less stable item representations. Dedifferentiation on all these representational levels was related to memory performance, with item specificity being the strongest contributor. Overall, our results emphasize that age-related dedifferentiation can be observed across the entire cortical hierarchy which may selectively impair memory performance depending on the memory task.

Analogy offers a new interpretation of a common concern in ethics: whether decision making includes or excludes a consideration of moral issues. This is often discussed as the moral awareness of decision makers and considered a motivational concern. The possible new interpretation is that moral awareness is in part a matter of expertise. Some failures of moral awareness can then be understood as stemming from novicehood. Studies of analogical transfer are consistent with the possibility that moral awareness is in part a matter of expertise, that as a result motivation is less helpful than some prior theorizing would predict, and that many adults are not as expert in the domain of ethics as one might hope. The possibility of expert knowledge of ethical principles leads to new questions and opportunities.

Psychological essentialism is ubiquitous. It is one of primary bases of thoughts and behaviours throughout our entire lifetime. Human's such characteristics that find an unseen hidden entity behind observable phenomena or exemplars, however, lead us to somehow biased thinking and reasoning even in the realm of science, including psychology. For example, a latent variable extracted from various measurements is just a statistical property calculated in structural equation modeling, therefore, is not necessary to be a fundamental reality. Yet, we occasionally feel that there is the essential nature of such a psychological construct a priori. This talk will demonstrate examples of psychological essentialism in psychology and examine its resultant influences on working memory related issues, e. g., working memory training. Such demonstration, examination, and subsequent discussions on these topics will provide us an opportunity to reconsider the concept of working memory.

Natural soundscapes such as from a forest, a busy restaurant, or a busy intersection are generally composed of a cacophony of sounds that the brain needs to interpret either independently or collectively. In certain instances sounds - such as from moving cars, sirens, and people talking - are perceived in unison and are recognized collectively as single sound (e.g., city noise). In other instances, such as for the cocktail party problem, multiple sounds compete for attention so that the surrounding background noise (e.g., speech babble) interferes with the perception of a single sound source (e.g., a single talker). I will describe results from my lab on the perception and neural representation of auditory textures. Textures, such as a from a babbling brook, restaurant noise, or speech babble are stationary sounds consisting of multiple independent sound sources that can be quantitatively defined by summary statistics of an auditory model (McDermott & Simoncelli 2011). How and where in the auditory system are summary statistics represented and the neural codes that potentially contribute towards their perception, however, are largely unknown. Using high-density multi-channel recordings from the auditory midbrain of unanesthetized rabbits and complementary perceptual studies on human listeners, I will first describe neural and perceptual strategies for encoding and perceiving auditory textures. I will demonstrate how distinct statistics of sounds, including the sound spectrum and high-order statistics related to the temporal and spectral correlation structure of sounds, contribute to texture perception and are reflected in neural activity. Using decoding methods I will then demonstrate how various low and high-order neural response statistics can differentially contribute towards a variety of auditory tasks including texture recognition, discrimination, and categorization. Finally, I will show examples from our recent studies on how high-order sound statistics and accompanying neural activity underlie difficulties for recognizing speech in background noise.

Human cognitive abilities seem qualitatively different from the cognitive abilities of other primates, a difference Penn, Holyoak, and Povinelli (2008) attribute to role-based relational reasoning—inferences and generalizations based on the relational roles to which objects (and other relations) are bound, rather than just the features of the objects themselves. Role-based relational reasoning depends on the ability to dynamically bind arguments to relational roles. But dynamic binding cannot be sufficient for relational thinking: Some non-human animals solve the dynamic binding problem, at least in some domains; and many non-human species generalize affordances to completely novel objects and scenes, a kind of universal generalization that likely depends on dynamic binding. If they can solve the dynamic binding problem, then why can they not reason about relations? What are they missing? I will present simulations with the LISA model of analogical reasoning (Hummel & Holyoak, 1997, 2003) suggesting that the missing pieces are multi-role integration (the capacity to combine multiple role bindings into complete relations) and structure mapping (the capacity to map different systems of role bindings onto one another). When LISA is deprived of either of these capacities, it can still generalize affordances universally, but it cannot reason symbolically; granted both abilities, LISA enjoys the full power of relational (symbolic) thought. I speculate that one reason it may have taken relational reasoning so long to evolve is that it required evolution to solve both problems simultaneously, since neither multi-role integration nor structure mapping appears to confer any adaptive advantage over simple role binding on its own.

Analogical reasoning remains foundational to the human ability to forge meaningful patterns within the sea of information that continually inundates the senses. Yet, meaningful patterns rely not only on the recognition of attributional similarities but also dissimilarities. Just as the perception of images rests on the juxtaposition of lightness and darkness, reasoning relationally requires systematic attention to both similarities and dissimilarities. With that awareness, my colleagues and I have expanded the study of relational reasoning beyond analogous reasoning and attributional similarities to highlight forms based on the nature of core dissimilarities: anomalous, antinomous, and antithetical reasoning. In this presentation, I will delineate the character of these relational reasoning forms; summarize procedures and measures used to assess them; overview key research findings; and describe how the forms of relational reasoning work together in the performance of complex problem solving. Finally, I will share critical next steps for research which has implications for instructional practice.

Did we eat spaghetti for lunch because we saw our colleague eat spaghetti? What drives a risk decision? How can our breakfast impact our decisions throughout the day? Research from different disciplines such as economics, psychology and neuroscience have attempted to investigate the motives and modulators of human decision making. Human decisions can be flexibly modulated by the different experiences we have in our daily lives, at the same time, bodily processes, such as metabolism can also impact economic behavior. These modulations can occur through our social networks, through the impact of our own behavior on the social environment, but also simply by the food we have eaten. Here, I will present a series of recent studies from my lab in which we shed light on the psychological, neural and metabolic motives and modulators of human decision making.