The Swartz Program at Harvard University seeks applicants for a postdoctoral fellow in theoretical and computational neuroscience. Based on a grant from the Swartz Foundation, a Swartz postdoctoral fellowship is available at Harvard University with a start date in the summer or fall of 2024. Postdocs join a vibrant group of theoretical and experimental neuroscientists plus theorists in allied fields at Harvard’s Center for Brain Science. The Center for Brain Science includes faculty doing research on a wide variety of topics, including neural mechanisms of rodent learning, decision-making, and sex-specific and social behaviors; reinforcement learning in rodents and humans; human motor control; behavioral and fMRI studies of human cognition; circuit mechanisms of learning and behavior in worms, larval flies, and larval zebrafish; circuit mechanisms of individual differences in flies and humans; rodent and fly olfaction; inhibitory circuit development; retinal circuits; and large-scale reconstruction of detailed brain circuitry.

Emotion is defined as a rapid psychological process involving experiential, expressive and physiological responses. These emerge following an appraisal process that involves cognitive evaluations of the environment assessing its relevance, implication, coping potential, and normative significance. It has been suggested that changes in appraisal processes lead to changes in the resulting emotional nature. Simultaneously, it was demonstrated that personality can be seen as a predisposition to feel more frequently certain emotions, but the personality-appraisal-emotional response chain is rarely fully investigated. The present project thus sought to investigate the extent to which personality traits influence certain appraisals, which in turn influence the subsequent emotional reactions via a systematic analysis of the link between personality traits of different current models, specific appraisals, and emotional response patterns at the experiential, expressive, and physiological levels. Major results include the coherence of emotion components clustering, and the centrality of the pleasantness, coping potential and consequences appraisals, in context; and the differentiated mediating role of cognitive appraisal in the relation between personality and the intensity and duration of an emotional state, and autonomic arousal, such as Extraversion-pleasantness-experience, and Neuroticism-powerlessness-arousal. Elucidating these relationships deepens our understanding of individual differences in emotional reactivity and spot routes of action on appraisal processes to modify upcoming adverse emotional responses, with a broader societal impact on clinical and non-clinical populations.

Neuroimaging has greatly extended our capacity to study the workings of the human brain. Despite the wealth of knowledge this tool has generated however, there are still critical gaps in our understanding. While tremendous progress has been made in mapping areas of the brain that are specialized for particular stimuli, or cognitive processes, we still know very little about how large-scale interactions between different cortical networks facilitate the integration of information and the execution of complex tasks. Yet even the simplest behavioral tasks are complex, requiring integration over multiple cognitive domains. Our knowledge falls short not only in understanding how this integration takes place, but also in what drives the profound variation in behavior that can be observed on almost every task, even within the typically developing (TD) population. The search for the neural underpinnings of individual differences is important not only philosophically, but also in the service of precision medicine. We approach these questions using a three-pronged approach. First, we create a battery of behavioral tasks from which we can calculate objective measures for different aspects of the behaviors of interest, with sufficient variance across the TD population. Second, using these individual differences in behavior, we identify the neural variance which explains the behavioral variance at the network level. Finally, using covert neurofeedback, we perturb the networks hypothesized to correspond to each of these components, thus directly testing their casual contribution. I will discuss our overall approach, as well as a few of the new directions we are currently pursuing.

Recent insights from auditory neuroscience provide a new perspective on how the brain encodes speech. Using these recent insights, I will provide an overview of key factors underpinning individual differences in children’s development of language and phonology, providing a context for exploring atypical reading development (dyslexia). Children with dyslexia are relatively insensitive to acoustic cues related to speech rhythm patterns. This lack of rhythmic sensitivity is related to the atypical neural encoding of rhythm patterns in speech by the brain. I will describe our recent data from infants as well as children, demonstrating developmental continuity in the key neural variables.

Many psychoactive substances are used with the aim of altering experience, e.g. as analgesics, antidepressants or antipsychotics. These drugs act on specific receptor systems in the brain, including the opioid, serotonergic and dopaminergic systems. In this talk, I will summarise human drug studies targeting opioid receptors and their role for human experience, with focus on the experience of pain, stress, mood, and social connection. Opioids are only indicated for analgesia, due to their potential to cause addiction. When these regulations occurred, other known effects were relegated to side effects. This may be the cause of the prevalent myth that opioids are the most potent painkillers, despite evidence from head-to-head trials, Cochrane reviews and network meta-analyses that opioids are not superior to non-opioid analgesics in the treatment of acute or chronic non-cancer pain. However, due to the variability and diversity of opioid effects across contexts and experiences, some people under some circumstances may indeed benefit from prolonged treatment. I will present data on individual differences in opioid effects due to participant sex and stress induction. Understanding the effects of these commonly used medications on other aspects of the human experience is important to ensure correct use and to prevent unnecessary pain and addiction risk.

Over the last decade, research on curiosity – the desire to seek new information – has been rapidly growing. Several studies have shown that curiosity elicits activity within the dopaminergic circuit and thereby enhances hippocampus-dependent learning. However, given this new field of research, we do not have a good understanding yet of (i) how curiosity-based learning changes across the lifespan, (ii) why some people show better learning improvements due to curiosity than others, and (iii) whether lab-based research on curiosity translates to how curiosity affects information seeking in real life. In this talk, I will present a series of behavioural and neuroimaging studies that address these three questions about curiosity. First, I will present findings on how curiosity and interest affect learning differently in childhood and adolescence. Second, I will show data on how inter-individual differences in the magnitude of curiosity-based learning depend on the strength of resting-state functional connectivity within the cortico-mesolimbic dopaminergic circuit. Third, I will present findings on how the level of resting-state functional connectivity within this circuit is also associated with the frequency of real-life information seeking (i.e., about Covid-19-related news). Together, our findings help to refine our recently proposed framework – the Prediction, Appraisal, Curiosity, and Exploration (PACE) framework – that attempts to integrate theoretical ideas on the neurocognitive mechanisms of how curiosity is elicited, and how curiosity enhances learning and information seeking. Furthermore, our findings highlight the importance of curiosity research to better understand how curiosity can be harnessed to improve learning and information seeking in real life.

Frequency tagging based on fast periodic visual stimulation (FPVS) provides a window into ongoing visual and cognitive processing and can be leveraged to measure rule learning and high-level categorization. In this talk, I will present data demonstrating highly proficient categorization as living and non-living in preschool children, and characterize the development of this ability during infancy. In addition to associating cognitive functions with development, an intriguing question is whether frequency tagging also captures enduring individual differences, e.g. in general cognitive abilities. First studies indicate high psychometric quality of FPVS categorization responses (XU et al., Dzhelyova), providing a basis for research on individual differences. I will present results from a pilot study demonstrating high correlations between FPVS categorization responses and behavioral measures of processing speed and fluid intelligences. Drawing upon this first evidence, I will discuss the potential of frequency tagging for diagnosing cognitive functions across development.

The sense of agency refers to the subjective feeling of controlling one's own behavior and, through them, external events. Why is this subjective feeling important for humans? Is it just a by-product of our actions? Previous studies have shown that the sense of agency can affect the intensity of sensory input because we predict the input from our motor intention. However, my research has found that the sense of agency plays more roles than just predictions. It enhances perceptual processes of sensory input and potentially helps to harvest more information about the link between the external world and the self. Furthermore, our recent research found both indirect and direct evidence that the sense of agency is important for people's exploratory behaviors, and this may be linked to proximal exploitations of one's control in the environment. In this talk, I will also introduce the paradigms we use to study the sense of agency as a result of perceptual processes, and our findings of individual differences in this sense and the implications.

Following the seminal structure mapping theory by Dedre Gentner, the process of mapping the corresponding structures of relations defining two analogs has been understood as a key component of analogy making. However, not without a merit, in recent years some semantic, pragmatic, and perceptual aspects of analogy mapping attracted primary attention of analogy researchers. For almost a decade, our team have been re-focusing on relational structure mapping, investigating its potential mechanisms across various analogy tasks, both abstract (semantically-lean) and more concrete (semantically-rich), using diverse methods (behavioral, correlational, eye-tracking, EEG). I will present the overview of our main findings. They suggest that structure mapping (1) consists of an incremental construction of the ultimate mental representation, (2) which strongly depends on working memory resources and reasoning ability, (3) even if as little as a single trivial relation needs to be represented mentally. The effective mapping (4) is related to the slowest brain rhythm – the delta band (around 2-3 Hz) – suggesting its highly integrative nature. Finally, we have developed a new task – Graph Mapping – which involves pure mapping of two explicit relational structures. This task allows for precise investigation and manipulation of the mapping process in experiments, as well as is one of the best proxies of individual differences in reasoning ability. Structure mapping is as crucial to analogy as Gentner advocated, and perhaps it is crucial to cognition in general.

Information is encoded in fine-scale functional topographies that vary from brain to brain. Hyperalignment models information that is shared across brain in a high-dimensional common information space. Hyperalignment transformations project idiosyncratic individual topographies into the common model information space. These transformations contain topographic basis functions, affording estimates of how shared information in the common model space is instantiated in the idiosyncratic functional topographies of individual brains. This new model of the functional organization of cortex – as multiplexed, overlapping basis functions – captures the idiosyncratic conformations of both coarse-scale topographies, such as retinotopy and category-selectivity, and fine-scale topographies. Hyperalignment also makes it possible to investigate how information that is encoded in fine-scale topographies differs across brains. These individual differences in fine-grained cortical function were not accessible with previous methods.

SES neuroscience, using imaging and other methods, has revealed generalizations of interest for population neuroscience and the study of individual differences. But beyond its scientific interest, SES is a topic of societal importance. Does neuroscience offer any useful insights for promoting socioeconomic justice and reducing the harms of poverty? In this talk I will use research from my own lab and others’ to argue that SES neuroscience has the potential to contribute to policy in this area, although its application is premature at present. I will also attempt to forecast the ways in which practical solutions to the problems of poverty may emerge from SES neuroscience. Bio: Martha Farah has conducted groundbreaking research on face and object recognition, visual attention, mental imagery, and semantic memory and - in more recent times - has been at the forefront of interdisciplinary research into neuroscience and society. This deals with topics such as using fMRI for lie detection, ethics of cognitive enhancement, and effects of social deprivation on brain development.

Prior studies of A:B::C:D verbal analogies have identified several factors that affect performance, including the semantic similarity between source and target domains (semantic distance), the semantic association between the C-term and incorrect answers (distracter salience), and the type of relations between word pairs (e.g., categorical, compositional, and causal). However, it is unclear how these stimulus properties affect performance when utilized together. Moreover, how do these item factors interact with individual differences such as crystallized intelligence and creative thinking? Several studies reveal interactions among these item and individual difference factors impacting verbal analogy performance. For example, a three-way interaction demonstrated that the effects of semantic distance and distracter salience had a greater impact on performance for compositional and causal relations than for categorical ones (Jones, Kmiecik, Irwin, & Morrison, 2022). Implications for analogy theories and future directions are discussed.

The human brain faces a variety of computational dilemmas, including the flexibility/stability, the speed/accuracy and the labor/leisure tradeoff. I will argue that striatal dopamine is particularly well suited to dynamically regulate these computational tradeoffs depending on constantly changing task demands. This working hypothesis is grounded in evidence from recent studies on learning, motivation and cognitive control in human volunteers, using chemical PET, psychopharmacology, and/or fMRI. These studies also begin to elucidate the mechanisms underlying the huge variability in catecholaminergic drug effects across different individuals and across different task contexts. For example, I will demonstrate how effects of the most commonly used psychostimulant methylphenidate on learning, Pavlovian and effortful instrumental control depend on fluctuations in current environmental volatility, on individual differences in working memory capacity and on opportunity cost respectively.

Sex-based modulation of cognitive processes could set the stage for individual differences in vulnerability to neuropsychiatric disorders. While value-based decision making processes in particular have been proposed to be influenced by sex differences, the overall correct performance in decision making tasks often show variable or minimal differences across sexes. Computational tools allow us to uncover latent variables that define different decision making approaches, even in animals with similar correct performance. Here, we quantify sex differences in mice in the latent variables underlying behavior in a classic value-based decision making task: a restless two-armed bandit. While male and female mice had similar accuracy, they achieved this performance via different patterns of exploration. Male mice tended to make more exploratory choices overall, largely because they appeared to get ‘stuck’ in exploration once they had started. Female mice tended to explore less but learned more quickly during exploration. Together, these results suggest that sex exerts stronger influences on decision making during periods of learning and exploration than during stable choices. Exploration during decision making is altered in people diagnosed with addictions, depression, and neurodevelopmental disabilities, pinpointing the neural mechanisms of exploration as a highly translational avenue for conferring sex-modulated vulnerability to neuropsychiatric diagnoses.

The nature of facial information that is stored by humans to recognise large amounts of faces is unclear despite decades of research in the field. To complicate matters further, little is known about how representations may evolve as novel faces become familiar, and there are large individual differences in the ability to recognise faces. I will present a theory I am developing and that assumes that facial representations are cost-efficient. In that framework, individual facial representations would incorporate different diagnostic features in different faces, regardless of familiarity, and would evolve depending on the relative stability in appearance over time. Further, coarse information would be prioritised over fine details in order to decrease storage demands. This would create low-cost facial representations that refine over time if appearance changes. Individual differences could partly rest on that ability to refine representation if needed. I will present data collected in the general population and in participants with developmental prosopagnosia. In support of the proposed view, typical observers and those with developmental prosopagnosia seem to rely on coarse peripheral features when they have no reason to expect someone’s appearance will change in the future.

Identifying biomarkers that predict current and future cognition may improve estimates of Alzheimer’s disease risk among cognitively unimpaired older adults (CU). In vivo measures of amyloid and tau protein burden and task-based functional MRI measures of core memory mechanisms, such as the strength of cortical reinstatement during remembering, have each been linked to individual differences in memory in CU. This study assesses whether combining CSF biomarkers with fMRI indices of cortical reinstatement improves estimation of memory function in CU, assayed using three unique tests of hippocampal-dependent memory. Participants were 158 CU (90F, aged 60-88 years, CDR=0) enrolled in the Stanford Aging and Memory Study (SAMS). Cortical reinstatement was quantified using multivoxel pattern analysis of fMRI data collected during completion of a paired associate cued recall task. Memory was assayed by associative cued recall, a delayed recall composite, and a mnemonic discrimination task that involved discrimination between studied ‘target’ objects, novel ‘foil’ objects, and perceptually similar ‘lure’ objects. CSF Aβ42, Aβ40, and p-tau181 were measured with the automated Lumipulse G system (N=115). Regression analyses examined cross-sectional relationships between memory performance in each task and a) the strength of cortical reinstatement in the Default Network (comprised of posterior medial, medial frontal, and lateral parietal regions) during associative cued recall and b) CSF Aβ42/Aβ40 and p-tau181, controlling for age, sex, and education. For mnemonic discrimination, linear mixed effects models were used to examine the relationship between discrimination (d’) and each predictor as a function of target-lure similarity. Stronger cortical reinstatement was associated with better performance across all three memory assays. Age and higher CSF p-tau181 were each associated with poorer associative memory and a diminished improvement in mnemonic discrimination as target-lure similarity decreased. When combined in a single model, CSF p-tau181 and Default Network reinstatement strength, but not age, explained unique variance in associative memory and mnemonic discrimination performance, outperforming the single-modality models. Combining fMRI measures of core memory functions with protein biomarkers of Alzheimer’s disease significantly improved prediction of individual differences in memory performance in CU. Leveraging multimodal biomarkers may enhance future prediction of risk for cognitive decline.

Relational thinking, or the process of identifying and integrating relations between mental representations, is regularly invoked during reasoning. This mental capacity enables us to draw higher-order abstractions and generalize across situations and contexts, and we have argued that it should be included in the pantheon of executive functions. In this talk, I will briefly review our lab's work characterizing the roles of lateral prefrontal and parietal regions in relational thinking. I will then discuss structural and functional predictors of individual differences and developmental changes in reasoning.

Unfamiliar face processing (face cognition) ability varies considerably in the general population. However, the means of its assessment are not standardised, and selected laboratory tests vary between studies. It is also unclear whether 1) the most commonly employed tests are reliable, 2) participants show a degree of consistency in their performance, 3) and the face cognition tests broadly measure one underlying ability, akin to general intelligence. In this study, we asked participants to perform eight tests frequently employed in the individual differences literature. We examined the reliability of these tests, relationships between them, consistency in participants’ performance, and used data driven approaches to determine factors underpinning performance. Overall, our findings suggest that the reliability of these tests is poor to moderate, the correlations between them are weak, the consistency in participant performance across tasks is low and that performance can be broadly split into two factors: telling faces together, and telling faces apart. We recommend that future studies adjust analyses to account for stimuli (face images) and participants as random factors, routinely assess reliability, and that newly developed tests of face cognition are examined in the context of convergent validity with other commonly used measures of face cognition ability.

Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight. Here, we built an interactive resource to benchmark brain morphology, www.brainchart.io, derived from any current or future sample of magnetic resonance imaging (MRI) data. With the goal of basing these reference charts on the largest and most inclusive dataset available, we aggregated 123,984 MRI scans from 101,457 participants aged from 115 days post-conception through 100 postnatal years, across more than 100 primary research studies. Cerebrum tissue volumes and other global or regional MRI metrics were quantified by centile scores, relative to non-linear trajectories of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones; showed high stability of individual centile scores over longitudinal assessments; and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared to non-centiled MRI phenotypes, and provided a standardised measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In sum, brain charts are an essential first step towards robust quantification of individual deviations from normative trajectories in multiple, commonly-used neuroimaging phenotypes. Our collaborative study proves the principle that brain charts are achievable on a global scale over the entire lifespan, and applicable to analysis of diverse developmental and clinical effects on human brain structure.

Our ability to perceive the world around us can be affected by a number of factors including the nature of the external information, prior experience of the environment, and the integrity of the underlying perceptual system. A particular challenge for the brain is to maintain a coherent perception from information encoded by the peripheral sensory organs whose function is affected by typical, developmental changes across the lifespan. Yet, how the brain adapts to the maturation of the senses, as well as experiential changes in the multisensory environment, is poorly understood. Over the past few years, we have used a range of multisensory tasks to investigate the role of ageing on the brain’s ability to merge sensory inputs. In particular, we have embedded an audio-visual task based on the sound-induced flash illusion (SIFI) into a large-scale, longitudinal study of ageing. Our findings support the idea that the temporal binding window (TBW) is modulated by age and reveal important individual differences in this TBW that may have clinical implications. However, our investigations also suggest the TWB is experience-dependent with evidence for both long and short term behavioural plasticity. An overview of these findings, including recent evidence on how multisensory integration may be associated with higher order functions, will be discussed.

Common factors are omnipresent in everyday life, e.g., it is widely held that there is a common factor g for intelligence. In vision, however, there seems to be a multitude of specific factors rather than a strong and unique common factor. In my thesis, I first examined the multidimensionality of the structure underlying visual illusions. To this aim, the susceptibility to various visual illusions was measured. In addition, subjects were tested with variants of the same illusion, which differed in spatial features, luminance, orientation, or contextual conditions. Only weak correlations were observed between the susceptibility to different visual illusions. An individual showing a strong susceptibility to one visual illusion does not necessarily show a strong susceptibility to other visual illusions, suggesting that the structure underlying visual illusions is multifactorial. In contrast, there were strong correlations between the susceptibility to variants of the same illusion. Hence, factors seem to be illusion-specific but not feature-specific. Second, I investigated whether a strong visual factor emerges in healthy elderly and patients with schizophrenia, which may be expected from the general decline in perceptual abilities usually reported in these two populations compared to healthy young adults. Similarly, a strong visual factor may emerge in action video gamers, who often show enhanced perceptual performance compared to non-video gamers. Hence, healthy elderly, patients with schizophrenia, and action video gamers were tested with a battery of visual tasks, such as a contrast detection and orientation discrimination task. As in control groups, between-task correlations were weak in general, which argues against the emergence of a strong common factor for vision in these populations. While similar tasks are usually assumed to rely on similar neural mechanisms, the performances in different visual tasks were only weakly related to each other, i.e., performance does not generalize across visual tasks. These results highlight the relevance of an individual differences approach to unravel the multidimensionality of the visual structure.

Neuroscientists have many questions about connectomes that revolve around the ability to compare networks. For example, comparing connectomes could help explain how neural wiring is related to individual differences, genetics, disease, development, or learning. One such question is that of bilateral symmetry: are the left and right sides of a connectome the same? Here, we investigate the bilateral symmetry of a recently presented connectome of an insect brain, the Drosophila larva. We approach this question from the perspective of two-sample testing for networks. First, we show how this question of “sameness” can be framed as a variety of different statistical hypotheses, each with different assumptions. Then, we describe test procedures for each of these hypotheses. We show how these different test procedures perform on both the observed connectome as well as a suite of synthetic perturbations to the connectome. We also point out that these tests require careful attention to parameter alignment and differences in network density in order to provide biologically meaningful results. Taken together, these results provide the first statistical characterization of bilateral symmetry for an entire brain at the single-neuron level, while also giving practical recommendations for future comparisons of connectome networks.

Solutions to challenging inference problems are often subject to a fundamental trade-off between bias (being systematically wrong) that is minimized with complex inference strategies and variance (being oversensitive to uncertain observations) that is minimized with simple inference strategies. However, this trade-off is based on the assumption that the strategies being considered are optimal for their given complexity and thus has unclear relevance to the frequently suboptimal inference strategies used by humans. We examined inference problems involving rare, asymmetrically available evidence, which a large population of human subjects solved using a diverse set of strategies that were suboptimal relative to the Bayesian ideal observer. These suboptimal strategies reflected an inversion of the classic bias-variance trade-off: subjects who used more complex, but imperfect, Bayesian-like strategies tended to have lower variance but high bias because of incorrect tuning to latent task features, whereas subjects who used simpler heuristic strategies tended to have higher variance because they operated more directly on the observed samples but displayed weaker, near-normative bias. Our results yield new insights into the principles that govern individual differences in behavior that depends on rare-event inference, and, more generally, about the information-processing trade-offs that are sensitive to not just the complexity, but also the optimality of the inference process.

Previous work looking at individual differences in face identity processing (FIP) has found that most commonly used lab-based performance assessments are unfortunately not sufficiently sensitive on their own for measuring performance in both the upper and lower tails of the general population simultaneously. So more recently, researchers have begun incorporating multiple testing procedures into their assessments. Still, though, the growing consensus seems to be that at the individual level, there is quite a bit of variability between test scores. The overall consequence of this is that extreme scores will still occur simply by chance in large enough samples. To mitigate this issue, our recent work has developed measures of intra-individual FIP consistency to refine selection of those with superior abilities (i.e. from the upper tail). For starters, we assessed consistency of face matching and recognition in neurotypical controls, and compared them to a sample of SRs. In terms of face matching, we demonstrated psychophysically that SRs show significantly greater consistency than controls in exploiting spatial frequency information than controls. Meanwhile, we showed that SRs’ recognition of faces is highly related to memorability for identities, yet effectively unrelated among controls. So overall, at the high end of the FIP spectrum, consistency can be a useful tool for revealing both qualitative and quantitative individual differences. Finally, in conjunction with collaborators from the Rheinland-Pfalz Police, we developed a pair of bespoke work samples to get bias-free measures of intraindividual consistency in current law enforcement personnel. Officers with higher composite scores on a set of 3 challenging FIP tests tended to show higher consistency, and vice versa. Overall, this suggests that not only is consistency a reasonably good marker of superior FIP abilities, but could present important practical benefits for personnel selection in many other domains of expertise.

Although analogical reasoning has been assumed to involve insight and its associated “aha!” experience, the relationship between these phenomena has never been directly probed empirically. In this study we investigated the relationship between representational change and the “aha!” experience during analogical reasoning. A novel set of verbal analogy stimuli were developed for use as an insight task. Across two experiments, participants reported significantly stronger aha moments and showed greater evidence of representational change on trials with more semantically distant analogies. Further, the strength of reported aha moments was correlated with the degree to which participants’ descriptions of the analogies changed over the course of each trial. Lastly, we probed the individual differences associated with a tendency to report stronger "aha" experiences, particularly related to mood, curiosity, and reward responsiveness. The findings shed light on the affective components of analogical reasoning and suggest that measuring affective responses during such tasks may elucidate novel insights into the mechanisms of creative analogical reasoning.

The integrated conflict monitoring theory of Botvinick introduced cognitive demand into conflict monitoring research. We investigated effects of individual differences of cognitive demand and another determinant of conflict monitoring entitled reinforcement sensitivity on conflict monitoring. We showed evidence of differential variability of conflict monitoring intensity using the electroencephalogram (EEG), functional magnet resonance imaging (fMRI) and behavioral data. Our data suggest that individual differences of anxiety and reasoning ability are differentially related to the recruitment of proactive and reactive cognitive control (cf. Braver). Based on previous findings, the team of the Leue-Lab investigated new psychometric data on conflict monitoring and proactive-reactive cognitive control. Moreover, data of the Leue-Lab suggest the relevance of individual differences of conflict monitoring for the context of deception. In this respect, we plan new studies highlighting individual differences of the functioning of the Anterior Cingulate Cortex (ACC). Disentangling the role of individual differences in working memory-related cognitive demand, mental effort, and reinforcement-related processes opens new insights for cognitive-motivational approaches of information processing (Passcode to rewatch: 0R8v&m59).

In Europe, the number of people aged 65 and older is increasing dramatically, and research related to ageing is more crucial than ever. The main research dedicated to age-related changes concentrates on cognitive or sensory deficits. This is also the case in vision research. However, the majority of older adults ages without major cognitive or optical or deficits. These are foremost good news, but even in the absence of neurodegenerative or eye diseases changes in visual perception occur. It has been suggested that age-related changes are due to a general decline of cognitive, perceptual and sensory functions. However, more recent studies reveal large individual differences within the ageing population and whereas some functions show age-related deterioration, others are surprisingly unaffected. Overall, it becomes increasingly apparent that perceptual changes in healthy ageing cannot be attributed to one single underlying factor. I will present studies from various areas of visual perception that challenge the view that age-related changes are primarily related to decline. Instead, our findings suggest that age-related changes are the result of visual experience, such that the brain ages optimally given the input it receives.

Human society operates on large-scale cooperation and shared norms of fairness. However, individual differences in cooperation and incentives to free-riding on others’ cooperation make large-scale cooperation fragile and can lead to reduced social-welfare. Deciphering the neural codes representing potential rewards/costs for self and others is crucial for understanding social decision-making and cooperation. I will first talk about how we integrate computational modeling with functional magnetic resonance imaging to investigate the neural representation of social value and the modulation by oxytocin, a nine-amino acid neuropeptide, in participants evaluating monetary allocations to self and other (self-other allocations). Then I will introduce our recent studies examining the neurobiological mechanisms underlying intergroup decision-making using hyper-scanning, and share with you how we alter intergroup decisions using psychological manipulations and pharmacological challenge. Finally, I will share with you our on-going project that reveals how individual cooperation spreads through human social networks. Our results help to better understand the neurocomputational mechanism underlying interpersonal and intergroup decision-making.

Cognitive control involves the flexible allocation of mental resources during goal-directed behaviour and comprises three correlated but distinct domains—inhibition, task shifting, and working memory. Healthy ageing is characterised by reduced cognitive control. Professor Cheryl Grady and her team have been studying the influence of age differences in large-scale brain networks on the three control processes in a sample of adults from 20 to 86 years of age. In this webinar, Professor Cheryl Grady will describe three aspects of this work: 1) age-related dedifferentiation and reconfiguration of brain networks across the sub-domains 2) individual differences in the relation of task-related activity to age, structural integrity and task performance for each sub-domain 3) modulation of brain signal variability as a function of cognitive load and age during working memory. This research highlights the reduction in dynamic range of network activity that occurs with ageing and how this contributes to age differences in cognitive control. Cheryl Grady is a senior scientist at the Rotman Research Institute at Baycrest, and Professor in the departments of Psychiatry and Psychology at the University of Toronto. She held the Canada Research Chair in Neurocognitive Aging from 2005-2018 and was elected as a Fellow of the Royal Society of Canada in 2019. Her research uses MRI to determine the role of brain network connectivity in cognitive ageing.

Many flexible behaviors are thought to rely on internal representations of an animal’s spatial relationship to its environment and of the consequences of its actions in that environment. While such representations—e.g. of head direction and value—have been extensively studied, how they are combined to guide behavior is not well understood. I will discuss how we are exploring these questions using a classical visual learning paradigm for the fly. I’ll begin by describing a simple policy that, when tethered to an internal representation of heading, captures structured behavioral variability in this task. I’ll describe how ambiguities in the fly’s visual surroundings affect its perception and, when coupled to this policy, manifest in predictable changes in behavior. Informed by newly-released connectomic data, I’ll then discuss how these computations might be carried out and combined within specific circuits in the fly’s central brain, and how perception and action might interact to shape individual differences in learning performance.

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.

Mental Health problems among youth constitutes an area of significant social, educational, clinical, policy and public health concern. Understanding processes and mechanisms that underlie the development of mental health problems during childhood and adolescence requires theoretical and methodological integration across multiple scientific domains, including developmental science, neuroscience, genetics, education and prevention science. The primary focus of this presentation is to examine the relative role of genetic and family environmental influences on children’s emotional and behavioural development. Specifically, a complementary array of genetically sensitive and longitudinal research designs will be employed to examine the role of early environmental adversity (e.g. inter-parental conflict, negative parenting practices) relative to inherited factors in accounting for individual differences in children’s symptoms of psychopathology (e.g. depression, aggression, ADHD ). Examples of recent applications of this research to the development of evidence-based intervention programmes aimed at reducing psychopathology in the context of high-risk family settings will also be presented.

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.

Constraints on control-dependent processing have become a fundamental concept in general theories of cognition that explain human behavior in terms of rational adaptations to these constraints. However, theories miss a rationale for why such constraints would exist in the first place. Recent work suggests that constraints on the allocation of control facilitate flexible task switching at the expense of the stability needed to support goal-directed behavior in face of distraction. We formulate this problem in a dynamical system, in which control signals are represented as attractors and in which constraints on control allocation limit the depth of these attractors. We derive formal expressions of the stability-flexibility tradeoff, showing that constraints on control allocation improve cognitive flexibility but impair cognitive stability. We provide evidence that human participants adapt higher constraints on the allocation of control as the demand for flexibility increases but that participants deviate from optimal constraints. In continuing work, we are investigating how collaborative performance of a group of individuals can benefit from individual differences defined in terms of balance between cognitive stability and flexibility.

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.

The emergence of large-scale brain networks, and their continual refinement, represent crucial developmental processes that can drive individual differences in cognition and which are associated with multiple neurodevelopmental conditions. But how does this organization arise, and what mechanisms govern the diversity of these developmental processes? There are many existing descriptive theories, but to date none are computationally formalized. We provide a mathematical framework that specifies the growth of a brain network over developmental time. Within this framework macroscopic brain organization, complete with spatial embedding of its organization, is an emergent property of a generative wiring equation that optimizes its connectivity by renegotiating its biological costs and topological values continuously over development. The rules that govern these iterative wiring properties are controlled by a set of tightly framed parameters, with subtle differences in these parameters steering network growth towards different neurodiverse outcomes. Regional expression of genes associated with the developmental simulations converge on biological processes and cellular components predominantly involved in synaptic signaling, neuronal projection, catabolic intracellular processes and protein transport. Together, this provides a unifying computational framework for conceptualizing the mechanisms and diversity of childhood brain development, capable of integrating different levels of analysis – from genes to cognition. (Pre-print: https://www.biorxiv.org/content/10.1101/2020.08.13.249391v1)

It has long been known that when viewing a set of images, we misjudge individual elements as being closer to the mean than they are (Hollingworth, 1910) and recall seeing the (absent) set mean (Deese, 1959; Roediger & McDermott (1995). Recent studies found that viewing sets of images, simultaneously or sequentially, leads to perception of set statistics (mean, range) with poor memory for individual elements. Ensemble perception was found for sets of simple images (e.g. circles varying in size or brightness; lines of varying orientation), complex objects (e.g. faces of varying emotion), as well as for objects belonging to the same category. When the viewed set does not include its mean or prototype, nevertheless, observers report and act as if they have seen this central image or object – a form of false memory. Physiologically, detailed sensory information at cortical input levels is processed hierarchically to form an integrated scene gist at higher levels. However, we are aware of the gist before the details. We propose that images and objects belonging to a set or category are represented as their gist, mean or prototype, plus individual differences from that gist. Under constrained viewing conditions, only the gist is perceived and remembered. This theory also provides a basis for compressed neural representation. Extending this theory to scenes and episodes supplies a generalized basis for false memories. They seem right, match generalized expectations, so are believable without challenging examination. This theory could be tested by analyzing the typicality of false memories, compared to rejected alternatives.

We will start our talk with a short video of our research, illustrating methods (some old and new) and findings that have provided our current understanding of how visual capabilities develop in infancy and early childhood. However, our research poses some outstanding questions. We will briefly discuss three issues, which are linked by a common focus on the development of visual attentional processing: (1) How do recurrent cortical loops contribute to development? Cortical selectivity (e.g., to orientation, motion, and binocular disparity) develops in the early months of life. However, these systems are not purely feedforward but depend on parallel pathways, with recurrent feedback loops playing a critical role. The development of diverse networks, particularly for motion processing, may explain changes in dynamic responses and resolve developmental data obtained with different methodologies. One possible role for these loops is in top-down attentional control of visual processing. (2) Why do hyperopic infants become strabismic (cross-eyes)? Binocular interaction is a particularly sensitive area of development. Standard clinical accounts suppose that long-sighted (hyperopic) refractive errors require accommodative effort, putting stress on the accommodation-convergence link that leads to its breakdown and strabismus. Our large-scale population screening studies of 9-month infants question this: hyperopic infants are at higher risk of strabismus and impaired vision (amblyopia and impaired attention) but these hyperopic infants often under- rather than over-accommodate. This poor accommodation may reflect poor early attention processing, possibly a ‘soft sign’ of subtle cerebral dysfunction. (3) What do many neurodevelopmental disorders have in common? Despite similar cognitive demands, global motion perception is much more impaired than global static form across diverse neurodevelopmental disorders including Down and Williams Syndromes, Fragile-X, Autism, children with premature birth and infants with perinatal brain injury. These deficits in motion processing are associated with deficits in other dorsal stream functions such as visuo-motor co-ordination and attentional control, a cluster we have called ‘dorsal stream vulnerability’. However, our neuroimaging measures related to motion coherence in typically developing children suggest that the critical areas for individual differences in global motion sensitivity are not early motion-processing areas such as V5/MT, but downstream parietal and frontal areas for decision processes on motion signals. Although these brain networks may also underlie attentional and visuo-motor deficits , we still do not know when and how these deficits differ across different disorders and between individual children. Answering these questions provide necessary steps, not only increasing our scientific understanding of human visual brain development, but also in designing appropriate interventions to help each child achieve their full potential.

Learning by analogy is a powerful tool children’s developmental repertoire, as well as in educational contexts such as mathematics, where the key knowledge base involves building flexible schemas. However, noticing and learning from analogies develops over time and is cognitively resource intensive. I review studies that provide insight into the relationship between mechanisms driving children’s developing analogy skills, highlighting environmental inputs (parent talk and prior experiences priming attention to relations) and neuro-cognitive factors (Executive Functions and brain injury). I then note implications for mathematics learning, reviewing experimental findings that show analogy can improve learning, but also that both individual differences in EFs and environmental factors that reduce available EFs such as performance pressure can predict student learning.

Over the past decade, the domain of face identity processing has seen a surging interest in inter-individual differences, with a focus on individuals with superior skills, so-called Super-Recognizers (SRs; Ramon et al., 2019; Russell et al., 2009). Their study can provide valuable insights into brain-behavior relationships and advance our understanding of neural functioning. Despite a decade of research, and similarly to the field of developmental prosopagnosia, a consensus on diagnostic criteria for SR identification is lacking. Consequently, SRs are currently identified either inconsistently, via suboptimal individual tests, or via undocumented collections of tests. This state of the field has two major implications. Firstly, our scientific understanding of SRs will remain at best limited. Secondly, the needs of government agencies interested in deploying SRs for real-life identity verification (e.g., policing) are unlikely to be met. To counteract these issues, I suggest the following action points. Firstly, based on our and others’ work suggesting novel and challenging tests of face cognition (Bobak et al., 2019; Fysh et al., in press; Stacchi et al., 2019), and my collaborations with international security agencies, I recommend novel diagnostic criteria for SR identification. These are currently being used to screen the Berlin State Police’s >25K employees before identifying SRs via bespoke testing procedures we have collaboratively developed over the past years. Secondly, I introduce a cohort of SRs identified using these criteria, which is being studied in-depth using behavioral methods, psychophysics, eye-tracking, and neuroimaging. Finally, I suggest data acquired for these individuals should be curated to develop and share best practices with researchers and practitioners, and to gain an accurate and transparent description of SR cases to exploit their informative value.