Cognition seminars

Metaphor is a pervasive phenomenon in language and cognition. To date, the vast majority of psycholinguistic research on metaphor has focused on noun-noun metaphors of the form An X is a Y (e.g., My job is a jail). Yet there is evidence that verb metaphor (e.g., I sailed through my exams) is more common. Despite this, comparatively little work has examined how verb metaphors are processed. In this talk, I will propose a novel account for verb metaphor comprehension: verb metaphors are understood in the same way that analogies are—as comparisons processed via structure-mapping. I will discuss the predictions that arise from applying the analogical framework to verb metaphor and present a series of experiments showing that verb metaphoric extension is consistent with those predictions.

Why do we make decisions impulsively blinded in an emotionally rash moment? Or caught in the same repetitive suboptimal loop, avoiding fears or rushing headlong towards illusory rewards? These cognitive constructs underlying self-control and compulsive behaviours and their influence by emotion or incentives are relevant dimensionally across healthy individuals and hijacked across disorders of addiction, compulsivity and mood. My lab focuses on identifying theory-driven modifiable biomarkers focusing on these cognitive constructs with the ultimate goal to optimize and develop novel means of neuromodulation. Here I will provide a few examples of my group’s recent work to illustrate this approach. I describe a series of recent studies on intracranial physiology and acute stimulation focusing on risk taking and emotional processing. This talk highlights the subthalamic nucleus, a common target for deep brain stimulation for Parkinson’s disease and obsessive-compulsive disorder. I further describe recent translational work in non-invasive neuromodulation. Together these examples illustrate the approach of the lab highlighting modifiable biomarkers and optimizing neuromodulation.

In cognitive development, learning more than the input provides is a central challenge. This challenge is especially evident in learning the meaning of numbers. Integers – and the quantities they denote – are potentially infinite, as are the fractional values between every integer. Yet children’s experiences of numbers are necessarily finite. Analogy is a powerful learning mechanism for children to learn novel, abstract concepts from only limited input. However, retrieving proper analogy requires cognitive supports. In this talk, I seek to propose and examine number lines as a mathematical schema of the number system to facilitate both the development of rational number understanding and analogical reasoning. To examine these hypotheses, I will present a series of educational intervention studies with third-to-fifth graders. Results showed that a short, unsupervised intervention of spatial alignment between integers and fractions on number lines produced broad and durable gains in fractional magnitudes. Additionally, training on conceptual knowledge of fractions – that fractions denote magnitude and can be placed on number lines – facilitates explicit analogical reasoning. Together, these studies indicate that analogies can play an important role in rational number learning with the help of number lines as schemas. These studies shed light on helpful practices in STEM education curricula and instructions.

Cognitive science and cognitive neuroscience researchers have agreed that the replication of findings is important for establishing which ideas (or theories) are integral to the study of cognition across the lifespan. Recently, high-profile papers have called into question findings that were once thought to be unassailable. Much attention has been paid to how p-hacking, publication bias, and sample size are responsible for failed replications. However, much less attention has been paid to the fidelity by which researchers enact study protocols. Researchers conducting education or clinical trials are aware of the importance in fidelity – or the extent to which the protocols are delivered in the same way across participants. Nevertheless, this idea has not been applied to cognitive contexts. This seminar discusses factors that impact the replicability of findings alongside recent models suggesting that even small fidelity deviations have real impacts on the data collected.

Previous studies have shown that blind individuals outperform sighted controls in a variety of auditory tasks; however, only few studies have investigated blind listeners’ speaker identification abilities. In addition, existing studies in the area show conflicting results. The presented empirical investigation with 153 blind (74 of them congenitally blind) and 153 sighted listeners is the first of its kind and scale in which long-term memory effects of blind listeners’ speaker identification abilities are examined. For the empirical investigation, all listeners were evenly assigned to one of nine subgroups (3 x 3 design) in order to investigate the influence of two parameters with three levels, respectively, on blind and sighted listeners’ speaker identification performance. The parameters were a) time interval; i.e. a time interval of 1, 3 or 6 weeks between the first exposure to the voice to be recognised (familiarisation) and the speaker identification task (voice lineup); and b) signal quality; i.e. voice recordings were presented in either studio-quality, mobile phone-quality or as recordings of whispered speech. Half of the presented voice lineups were target-present lineups in which the previously heard target voice was included. The other half consisted of target-absent lineups which contained solely distractor voices. Blind individuals outperformed sighted listeners only under studio quality conditions. Furthermore, for blind and sighted listeners no significant performance differences were found with regard to the three investigated time intervals of 1, 3 and 6 weeks. Blind as well as sighted listeners were significantly better at picking the target voice from target-present lineups than at indicating that the target voice was absent in target-absent lineups. Within the blind group, no significant correlations were found between identification performance and onset or duration of blindness. Implications for the field of forensic phonetics are discussed.

In this talk, I’ll consider how new ideas emerge from old ones via the process of conceptual blending. I’ll start by considering analogical reasoning in problem solving and the role conceptual blending plays in these problem-solving contexts. Then I’ll consider blending in multi-modal contexts, including timelines, memes (viz. image macros), and, if time allows, zoom meetings. I suggest mappings analogy researchers have traditionally considered superficial are often important for the development of novel abstractions. Likewise, the analogue portion of multimodal blends anchors their generative capacity. Overall, these observations underscore the extent to which meaning is a socially distributed process whose intermediate products are stored in cognitive artifacts such as text and digital images.

Coregraph is a tool under development that allows us to collect high-density data patterns during the administration of classic neuropsychological tests such as the Trail Making Test and Clock Drawing Test. These tests are widely used to evaluate cognitive function and screen for neurodegenerative disorders, but traditional methods of data collection only yield sparse information, such as test completion time or error types. By contrast, the high-density data collected with Coregraph may contribute to a better understanding of the cognitive processes involved in executing these tests. In addition, Coregraph may potentially revolutionize the field of cognitive evaluation by aiding in the prediction of cognitive deficits and in the identification of early signs of neurodegenerative disorders such as Alzheimer's dementia. By analyzing high-density graphomotor data through techniques like manual feature engineering and machine learning, we can uncover patterns and relationships that would be otherwise hidden with traditional methods of data analysis. We are currently in the process of determining the most effective methods of feature extraction and feature analysis to develop Coregraph to its full potential.

Learning verbs is difficult and critical to learning one's native language. Children appear to benefit from seeing multiple events and comparing them to each other, and structural alignment theory provides a good theoretical framework to guide research into how preschool children may be comparing events as they learn new verbs. The talk will include 6 studies of early verb learning that make use of eye-tracking procedures as well as other behavioral (pointing) procedures, and that test key predictions from SA theory including the prediction that seeing similar examples before more varied examples helps observers learn how to compare (progressive alignment) and the prediction that when events have very low alignability with other events, that is one cue that the events should be ignored. Whether or how statistical learning may also be at work will be considered.

Memory impairment is a common cognitive deficit in temporal lobe epilepsy (TLE). The hippocampus is severely altered in TLE exhibiting multiple anatomical changes that lead to a hyperexcitable network capable of generating frequent epileptic discharges and seizures. In this study we investigated whether hippocampal involvement in epileptic activity drives working memory deficits using bilateral LFP recordings from CA1 during task performance. We discovered that epileptic mice experienced focal rhythmic discharges (FRDs) while they performed the spatial working memory task. Spatial correlation analysis revealed that FRDs were often spatially stable on the maze and were most common around reward zones (25 ‰) and delay zones (50 ‰). Memory performance was correlated with stability of FRDs, suggesting that spatially unstable FRDs interfere with working memory codes in real time.

Many animals live in complex social groups. To survive, it is essential to know who to avoid and who to interact. Although naïve mice are naturally attracted to any adult conspecifics, a single defeat experience could elicit social avoidance towards the aggressor for days. The neural mechanisms underlying the behavior switch from social approach to social avoidance remains incompletely understood. Here, we identify oxytocin neurons in the retrochiasmatic supraoptic nucleus (SOROXT) and oxytocin receptor (OXTR) expressing cells in the anterior subdivision of ventromedial hypothalamus, ventrolateral part (aVMHvlOXTR) as a key circuit motif for defeat-induced social avoidance learning. After defeat, aVMHvlOXTR cells drastically increase their responses to aggressor cues. This response change is functionally important as optogenetic activation of aVMHvlOXTR cells elicits time-locked social avoidance towards a benign social target whereas inactivating the cells suppresses defeat-induced social avoidance. Furthermore, OXTR in the aVMHvl is itself essential for the behavior change. Knocking out OXTR in the aVMHvl or antagonizing the receptor during defeat, but not during post-defeat social interaction, impairs defeat-induced social avoidance. aVMHvlOXTR receives its private supply of oxytocin from SOROXT cells. SOROXT is highly activated by the noxious somatosensory inputs associated with defeat. Oxytocin released from SOROXT depolarizes aVMHvlOXTR cells and facilitates their synaptic potentiation, and hence, increases aVMHvlOXTR cell responses to aggressor cues. Ablating SOROXT cells impairs defeat-induced social avoidance learning whereas activating the cells promotes social avoidance after a subthreshold defeat experience. Altogether, our study reveals an essential role of SOROXT-aVMHvlOXTR circuit in defeat-induced social learning and highlights the importance of hypothalamic oxytocin system in social ranking and its plasticity.

Vector-space models are used frequently to compare similarity and dimensionality among entity concepts. What happens when we apply these models to relational concepts? What is the evidence that such models do apply to relational concepts? If we use such a model, then one implication is that maximizing surface feature variation should improve relational concept learning. For example, in STEM instruction, the effectiveness of teaching by analogy is often limited by students’ focus on superficial features of the source and target exemplars. However, in contrast to the prediction of the vector-space computational model, the strategy of progressive alignment (moving from perceptually similar to different targets) has been suggested to address this issue (Gentner & Hoyos, 2017), and human behavioral evidence has shown benefits from progressive alignment. Here I will present some preliminary data that supports the computational approach. Participants were explicitly instructed to match stimuli based on relations while perceptual similarity of stimuli varied parametrically. We found that lower perceptual similarity reduced accurate relational matching. This finding demonstrates that perceptual similarity may interfere with relational judgements, but also hints at why progressive alignment maybe effective. These are preliminary, exploratory data and I to hope receive feedback on the framework and to start a discussion in a group on the utility of vector-space models for relational concepts in general.

Since Darwin, comparative research has shown that most animals share basic timing capacities, such as the ability to process temporal regularities and produce rhythmic behaviors. What seems to be more exclusive, however, are the capacities to generate temporal predictions and to display anticipatory behavior at salient time points. These abilities are associated with subcortical structures like basal ganglia (BG) and cerebellum (CE), which are more developed in humans as compared to nonhuman animals. In the first research line, we investigated the basic capacities to extract temporal regularities from the acoustic environment and produce temporal predictions. We did so by adopting a comparative and translational approach, thus making use of a unique EEG dataset including 2 macaque monkeys, 20 healthy young, 11 healthy old participants and 22 stroke patients, 11 with focal lesions in the BG and 11 in the CE. In the second research line, we holistically explore the functional relevance of body-brain physiological interactions in human behavior. Thus, a series of planned studies investigate the functional mechanisms by which body signals (e.g., respiratory and cardiac rhythms) interact with and modulate neurocognitive functions from rest and sleep states to action and perception. This project supports the effort towards individual profiling: are individuals’ timing capacities (e.g., rhythm perception and production), and general behavior (e.g., individual walking and speaking rates) influenced / shaped by body-brain interactions?