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Psychology Colloquium Series 2019
Colloquium: Lightning Talks
(Stanford University)
Lightning Talks
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Date: November 20, 2019
Description:
Outstanding students and postdocs from the Psychology Department will be presenting on a variety of topics.
Fiery Cushman
(Harvard University)
How we know what not to think
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Date: November 13, 2019
Description:
A striking feature of the real world is that there is too much to think about. This is remarkably understudied in laboratory contexts, where the study of decision-making is typically limited to small “choice sets” defined by an experimenter. In such cases an individual may devote considerable attention to each item in the choice set. But in everyday life we are often not presented with defined choice sets; rather, we must construct a viable set of alternatives to consider. I will present several recent and ongoing research projects that each aim to understand how humans spontaneously decide what actions to consider—in other words, how we construct choice sets. A common theme among these studies is a key role for cached value representations. Additionally, I will present some evidence that moral norms play a surprisingly and uniquely large role in constraining choice sets and, more broadly, in modal cognition. This suggests a new avenue for understanding how morality influences our behavior.
Jason Yeatman
(Stanford University)
Plasticity and learning: How education shapes brain development
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Date: October 30, 2019
Description:
Educational interventions offer a powerful tool to understand how changing a child’s environment shapes the development of specialized brain circuits for new cognitive functions such as literacy. I will first present a series of intervention studies that reveal a surprising capacity for rapid and widespread plasticity in the brain’s white matter connections. Next, I will ask whether there is a sensitive period for experience-dependent white matter plasticity and literacy learning. Finally, I will conclude by describing new work in pre-school children examining how learning to associate letters with sounds establishes the foundations of the brain’s reading circuitry.
Laurie Santos
(Yale University)
The Origins of Mind-Reading: Insights from Non-Human Primates
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Date: October 9, 2019
Description:
How do we come to represent the thoughts, beliefs, and intentions of other people? Over the past decade, researchers have made great strides in developing non-verbal methods for studying both the ontogenetic and phylogenetic origins of human mental state representations. This recent work has come to suggest an important divide between the representations that human infants use to think about other minds and those used by nonhuman primates: while human infants show evidence of representing others’ beliefs, to date nonhuman primates have not. However, other species do show a sophisticated ability to track others’ current and past perceptions. In my talk, I’ll explore what this pattern means for the origins of theory of mind representation more generally. I’ll argue that nonhuman primates may possess a phylogenetically-old system for tracking other individuals’ informational relations between agents and true (but not false) information. I’ll then discuss how this view accounts both for nonhuman primates’ performance in a range of theory of mind tasks as well as what it means for developmental accounts of infants’ early theory of mind representations.
Ulrike Hahn
(University of London)
How Rational Am I?
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Date: October 2, 2019
Description:
Learn about the many deficits of human rationality that have been identified over the last five decades. Hear about work in sample domains ranging from everyday informal argument, through testimony and social networks, to decision making. This work seeks not only to shed light on human behaviour in these domains but to illustrate the reasons why the often bleak picture of human rationality painted by past research is not as settled as typically assumed.
Johannes Eichstaedt
(UPENN)
Measuring Physical and Mental Health Using Social Media
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Date: June 10, 2019
Description:
The content shared on social media is among the largest data sets on human behavior in history. In my work, I seek to leverage this data to address questions in the psychological sciences. Specifically, I apply natural language processing and machine learning to characterize and measure psychological phenomena with a focus on mental and physical health. For depression, I will show that machine learning models applied to Facebook status histories can predict future depression as documented in the medical records of a sample of patients. For heart disease, the leading cause of death, I demonstrate how prediction models derived from geo-tagged Tweets can estimate county mortality rates better than gold-standard epidemiological models. I will also present preliminary findings on my emerging project to measure the subjective well-being of large populations. Across these studies, I argue that AI-based approaches to social media can augment clinical practice, guide prevention, and inform public policy.
Karin Roelofs
(Radboud University)
Neural Control of Human Defensive Reactions to Social Threat
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Date: May 15, 2019
Description:
The ability to control automatic emotional actions constitutes a critical component of emotion regulation during socially threatening situations. For instance, under acute threat, goal directed decision-making depends largely on the capacity to override automatic defensive actions such as freezing reactions or fight-or-flight actions. Distinct parts of the frontal cortex are implicated in regulating these defensive reactions. I will present a number of experimental paradigms by which we assessed neural control over these defensive reactions in humans by combining decision tasks with neural and autonomic measures. The first series of studies indicates that down-regulation of amygdala activity by the anterior prefrontal cortex (aPFC) is involved when people need to override their automatic social approach-avoidance action tendencies. I will show that the functioning of this neural circuitry is sensitive to individual differences in social anxiety and aggression, and I will discuss manipulations of this neural circuitry by steroid hormone administration (i.e. testosterone) and brain stimulation (TMS). […] Together, these series of studies show that distinct frontal regions are implicated in controlling distinct defensive reactions, and that the ability to flexibly shift between different defensive response modes is essential for adequate threat coping. It is this ability that may fail in social emotional disorders such as social anxiety and aggression-related disorders. See http://www.roelofs-epan.nl
Nour Kteily
(Northwestern University)
Darker Demons of our Nature: The Prevalence and Potency of Blatant Forms of Dehumanization
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Date: March 6, 2019
Description:
Although dehumanization research first emerged following the overt and conscious denials of humanity present during war and genocide, modern dehumanization research largely examines more subtle and implicit forms of dehumanization in more everyday settings. I argue for the need to re-orient the research agenda towards understanding when and why individuals blatantly dehumanize others. I review recent research in a range of contexts suggesting that blatant dehumanization is surprisingly prevalent and potent, uniquely predicting aggressive intergroup attitudes and behavior beyond subtle forms of dehumanization and outgroup dislike, and promoting vicious cycles of conflict. I also discuss recent intervention efforts aimed at reducing blatant dehumanization and its consequences.
Dave Rand
(MIT)
Fake news: Why we fall for it and what to do about it
Date: February 20, 2019
Description:
Why do people believe and share misinformation, including entirely fabricated news headlines (“fake news”) and biased or misleading coverage of actual events (“hyper-partisan” content)? The dominant narrative in the media and among academics is that we believe misinformation because we want to – that is, we engage in motivated reasoning, using our cognitive capacities to convince ourselves of the truth of statements that align with our political ideology rather than to undercover the truth. In a series of survey experiments using American participants, we challenge this account. […]
Further Information:
https://psychology.stanford.edu/events/colloquium-dave-rand-massachusetts-institute-technology
Terry Jernigan
(UCSD)
Developmental Population Neuroscience and the ABCD Study
Date: January 16, 2019
Description:
In the last decade, increasingly large-scale studies with a focus on the developing mind and brain have been launched in an effort to expand and update the data resources available to the research community. These high dimensional longitudinal studies aim to meet epidemiological standards for participant accrual, use a wide array of biomedical and behavioral phenotyping methods, such as genome sequencing and multimodal neuroimaging and are lately referred to as population neuroscience. One of the largest of these is the Adolescent Brain and Cognitive Development (ABCD) Study; which as the name suggests focuses on the adolescent brain, enrolling children at ages 9 and 10 for a ten-year study. I will describe this study, its rationale and aims, structure, and protocols; and will highlight its open science model. I will focus on attempts in ABCD to identify and assess relevant genetic, environmental, and experiential factors that are likely to impact health, mental health, and intellectual outcomes. Finally, I will highlight some further advances in the structure of human developmental science needed to improve models of the developing human mind and to translate this knowledge into better education, healthcare, and public policy.
Julia Leonard
(UPENN)
Social influences on children’s persistence and learning
Date: January 16, 2019
Description:
Children’s persistence in the face of challenge is central to learning. But how do young children learn when and how to deploy effort? This talk explores the various social factors that impact young children’s persistence and learning across two timescales, demonstrating that 1) social evidence influences children’s moment-to-moment effortful behavior and 2) children’s long-term social environment shapes their brain development and capacity to learn. First, I demonstrate that 15-month-olds can generalize the value of persistence from watching how hard an adult tries to reach a goal. Next, I show that young children not only integrate information about adults’ actions, but also about their outcomes (success or failure) and testimony, to decide how hard to try on a novel task. Children persist the longest when adults practice what they preach: saying they value effort in conjunction with demonstrating effortful success on their own task. In another line of work, I examine how children’s long-term social environment, specifically socioeconomic-status (SES), relates to the neural systems involved in learning. I show that SES has a selective impact on memory, relating to hippocampal-prefrontal declarative memory, but not striatal-dependent procedural memory. I also demonstrate that the neural correlates of fluid reasoning differ by SES, suggesting that positive brain development varies by early life environment. Collectively, this work elucidates both the malleable social factors that positively impact children’s persistence and the unique neural and cognitive adaptations that children develop in response to adverse environments. I will end with a discussion of future directions, including an effort to quantify and explain within and between subject day-to-day fluctuations in persistent behavior.
Elizabeth Gunderson
(Temple University)
The development of mathematical cognition and motivation
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Date: January 9, 2019
Description:
Mathematical skills are critical for academic and career success, and it is therefore vital to understand how cognitive and motivational processes work together to influence children’s developmental trajectories in math. In this talk, I will examine cognitive and motivational processes that lead to individual differences in mathematical development, using a combination of longitudinal and experimental methods in preschool and early elementary school students. […]
Psychology Colloquium Series 2018
Denise Werchan
(Brown Unversity)
The Ontogenetic Origins of Complex Knowledge: PFC Contributions to Learning in Infancy
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Date: November 28, 2018
Description:
Infants learn and grow at rates arguably unmatched during any other period in a lifespan. A key question is how the developing child acquires these rich knowledge architectures and acts on the world with increasing efficiency and complexity. To explore this question, I will present research showing that the prefrontal cortex (PFC) supports learning and contributes to complexity in thought and action as early as infancy. Specifically, I will provide evidence that (1) infants recruit the PFC to organize environmental input into flexible rule structures that allow infants to make predictions about future events and generalize learning in new contexts, (2) a rule learning account of PFC function can explain infants’ inhibitory control errors on the classic A-Not-B task, and (3) rule learning exerts top-down control over infants’ visual processing. This research demonstrates that the human brain is predisposed to organize inputs into flexible rules that help infants make sense of the cluttered and rapidly changing multisensory world. Future work will explore how these systems scaffold the emergence of increasingly complex concepts and cognitive representations, and how this in turn shapes learning and cortical organization to adapt to the changing mind, body, and environment. Together, this work offers new insights into the dynamic mechanisms that contribute to complexity in thought and action as children grow and develop.
Shige Oishi
(University of Virginia)
What is a Good Life?
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Date: October 24, 2018
Description:
In this talk, I will explore what a good life is. In Psychological Science, traditional answers to this question are either a happy life or a meaningful life. I will propose that there is another candidate: a psychologically rich life.
Mikki Hebl
(Rice University)
Gender and Race Gatekeeping
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Date: October 17, 2018
Description:
Dr. Hebl will discuss her recent research examining the biases that affect women and racial minorities. These biases are often held by gatekeepers, individuals who have access to whom is allowed to advance within an organization or society. In addition to identifying these gatekeepers and the ubiquity of these biases, she will also offer recommendations as to their reduction at the individual and organizational levels.
John Dovidio
(Yale University)
Racism among the Well-Intentioned
Date: May 9, 2018
Description:
This presentation describes research on contemporary racism and implicit bias and discusses implications for racial disparities in healthcare and, ultimately, health. It explains how explicit and implicit biases among White Americans can influence the way they evaluate Black Americans as well as affect the dynamics of interracial interactions. The presentation illustrates how these processes relate to the attitudes of physicians and shape the quality of medical care experienced by Black patients. Potential interventions to reduce the adverse effects of implicit bias are considered.
Barry Schwartz
(Swarthmore College)
Choice, Maximizing, Rationality, and Self-Expression
Date: April 25, 2018
Description:
Years ago, Herbert Simon suggested that the standard assumption of rational choice theory, that decision makers choose so as to maximize expected utility, is psychologically implausible, because maximization requires cognitive operations that exceed human capacity. Simon proposed, instead, that people “satisfice,” choosing “good enough” rather than the best options. The maximizing challenge is exacerbated when choice sets are large, as is the case with most of the decisions people face in modern, affluent societies. More recent work has identified individual differences in decision making, with some people aiming to maximize and others aiming to satisfice. Maximizers make better decisions than satisficers, but feel worse about them. In this talk, I will suggest that the goal of maximizing is not just a psychological mistake, but an epistemological one—that often it is not possible. I will also present new empirical work that shows that when choice sets are large, people view choices as self-expressive, making even seemingly trivial decisions (eg., what jeans to buy) into significant ones, and that when this happens, it enhances the tendency to maximize in making these decisions. In other words, large choice sets raise the stakes of decisions, turning people into maximizers, which results in less satisfying decisions. I will finally suggest that perhaps viewing the self as “achieved” rather than as “ascribed,” or the self as “incremental” rather than as an “entity” may be a mixed psychological blessing.
David Heeger
(NYU)
Canonical Computation in Brains and Machines
Date: April 18, 2018
Description:
Working memory is a cognitive process that is responsible for temporarily holding and manipulating information. Most of the empirical neuroscience research on working memory has focused on measuring sustained activity in prefrontal cortex (PFC) and/or parietal cortex during simple delayed-response tasks, and most of the models of working memory have been based on neural integrators. But working memory means much more than just holding a piece of information online. I will present a new theory of working memory, based on a recurrent neural circuit that I call ORGaNICs (Oscillatory Recurrent GAted Neural Integrator Circuits). ORGaNICs are a variety of LSTMs (imported from the machine learning/AI literature) that can be used to explain the complex dynamics of delay-period activity in real neural circuits during a working memory task, and that offer some computational advantages over conventional artificial recurrent neural nets. Time permitting, I’ll also say a few words about inference, exploration, prediction, and the role of feedback (top-down) in the brain.
Stanislas Dehaene
(College de France)
Language and mathematics: A close look at the mathematician’s brain
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Date: March 21, 2018
Description:
How did language and mathematics emerge in humans during the course of evolution? Scientists since Galileo have insisted that mathematics is structured as a language – but is this language similar to spoken language? Do mathematicians use classical language areas when doing mathematics? In the first part of the talk, I will present converging evidence that the left posterior superior temporal sulcus (pSTS) and inferior frontal gyrus (IFG, pars triangularis and orbitalis) play a central role in the syntax of spoken and written natural languages. In the second part, I will present fMRI studies investigating whether these brain areas also contribute to various aspects of mathematics. When professional mathematicians reflect upon high-level mathematical concepts in algebra, analysis, geometry or topology, the activation spares classical language areas. Instead, high-level mathematics involves bilateral intraparietal areas involved in elementary number sense and simple arithmetic, and bilateral infero-temporal areas involved in processing Arabic numerals. The evidence suggests that the acquisition of mathematical concepts recycles areas involved in elementary number processing. My conclusion will be that human brains are attuned to many different languages – spoken, written, mathematical, musical… – and that brain evolution may have endowed the human brain with a widespread ability to manipulate nested syntactic structures in most, if not all domains of human cognition.
Nilam Ram
(Pennsylvania State University)
Variability in Emotion at Multiple Time-Scales: Individuals Interacting with Media, Each Other, and Age
Date: March 14, 2018
Description:
Innovations in mobile computing and network infrastructure are reshaping how and when individuals engage with each other and with the world around them. These same technologies provide opportunities to observe and modify individuals’ emotional experiences as they unfold across time – second-to-second, hour-to-hour, year-to-year. Using intensive longitudinal data from survey panels, experience sampling studies, social media, and laboratory observations, I illustrate how consideration of zooms, tensions, and switches (ZOOTS) is informing our understanding of person-context transactions – in particular, how media, social relationships, and age are intertwined with the dynamics of emotional life.
Laura Lewis
(Harvard Univsersity)
Whole-brain network dynamics underlying transitions between sleep and wake
Date: February 21, 2018
Description:
Cognition and behavior vary dramatically over the course of the day, as the brain transitions between alert, inattentive, drowsy, and sleep states. How brain networks dynamically reorganize to create these diverse arousal states and modulate neural computation is not well understood. Studies of large-scale network dynamics have been limited by the fact that conventional neuroimaging methods cannot capture whole-brain activity at subsecond timescales. We developed a new approach to noninvasively measuring local dynamics throughout the whole brain simultaneously using ‘fast fMRI’, enabling direct imaging of cortical and subcortical oscillations in humans. We integrated fast fMRI with simultaneous EEG to image human subjects as they fell asleep, and identified transitory shifts in patterns of global thalamocortical dynamics that predict moment-to-moment arousal state. These results demonstrate that rapid changes in large-scale network function can be detected through new techniques for fast whole-brain neuroimaging, identify distinct neural activity patterns that signal transitions into and out of sleep, and suggest broad future potential for these approaches to identify the neural mechanisms that flexibly control brain states and cognition.
Janine Bijsterbosch
(Oxford University)
From Connectivity to Biomarker
Date: February 7, 2018
Description:
Dysfunctional brain connectivity is associated with a large variety of neurological and psychiatric disorders and therefore promises to be an important biomarker for early detection, diagnosis, and optimized treatment in key patient populations. In order to develop connectivity markers that are of predictive value in individual patients, it is critically important to address a range of challenges linked to methodology, interpretation, and translation. In this talk I will describe how my research aims to address these challenges by carefully mapping and understanding different types of variability. I will discuss results from three studies to illustrate this approach: i) connectivity markers associated with variability in trait and induced anxiety, ii) within- and between-subject variability in BOLD amplitude, and iii) the role of spatial variability in driving functional connectivity. These results show the importance of bridging between advanced analysis methods and applied clinical neuroscience to identify and interpret clinically relevant connectivity markers. I will finish my talk by briefly summarizing my future research plans.
Henry Wellman
(Northwestern University)
Children’s Understanding of (Technological) Minds
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Date: January 31, 2017
Description:
Early in life children acquire well-grounded understandings of people in terms of their mental states—a theory of mind. Later children come to think about and wrestle with extraordinary minds and mental phenomena—God, omniscience, afterlife, prayer. Recently, however, the minds children encounter has expanded to include smart technology—laptops, tablets, machines—and the minds those exhibit—Siri, Alexa, Echo, and social robots. An increasing amount of research addresses how adults approach, understand and feel about these devices. Much less is known about children and the development of their beliefs and reactions. After some background, I will focus on our own emerging research on children’s thoughts about and interactions with social robots. Social robots—those that look human-like to varying degrees—are a revealing example because they share similarities in configuration and behavior with humans but are mechanical, smart-technological devices. Every year more and more social robots are designed to befriend, teach, and care for children. They are found in malls, homes, hospitals and schools. A focus on social robots allows me to consider questions such as: To what extent do children think of these robots as having human-like minds? To what extent do the differences between robots and people prevail? What influences whether children feel positively and negatively about and accept or resist information from and learn from such minds? And, crucially I will argue, how do answers to these questions vary with children’s age and development?
Douglas Medin
(Northwestern University)
Cultural Epistemologies and Reasoning about the Natural World
Date: January 17, 2017
Description:
This talk concerns relationships between different ways of looking at the world (epistemologies) and other cognitive processes such as categorization and reasoning. The focus will be specifically on Native American relational epistemologies and biological cognition, including complex systems reasoning. The relevant data come from analyses of cultural artifacts, developmental studies and adult Native, Non-Native contrasts.
Psychology Colloquium Series 2016-17
Anna Schapiro
(Harvard University)
Learning and consolidating patterns in experience
Date: November 29, 2017
Description:
There is a fundamental tension between storing discrete traces of individual experiences, which allows recall of particular moments in our past without interference, and extracting statistics across these experiences, which supports generalization and prediction in similar situations in the future. This tension is resolved in classic memory systems theories by separating these processes anatomically: the hippocampus rapidly encodes individual episodes, while the cortex slowly extracts statistics over days, months, and years. This framework fails, however, to account for the full range of human learning and memory behavior, including: (1) how we often learn statistics quite quickly—within a few minutes or hours, and (2) how these memories transform over time and as a result of sleep. I will present evidence from fMRI and patient studies suggesting that the hippocampus, in addition to its well-established role in episodic memory, is in fact also responsible for our ability to rapidly extract statistics. I will then use computational modeling of the hippocampus to demonstrate how these two competing learning processes can coexist in one brain structure. Finally, I will present empirical and simulation work showing how these initial hippocampal memories are replayed during offline periods to help stabilize and integrate them into cortical networks. This work advocates a new comprehensive, mechanistic view of the remarkable mnemonic capabilities of the human mind and brain.
Ida Momennejad
(Princeton University)
Predictive Representations in Memory and Planning
Date: November 1, 2016
Description:
Most people around the world report wanting to be happy. Fortunately, decades of research suggest that individuals can deliberately increase their own happiness via such practices as gratitude or kindness. In this talk, I will introduce the positive activity model (Lyubomirsky & Layous, 2013), which describes when and why positive activities are more (or less) successful at boosting well-being. Then, I will propose several key moderators and mechanisms by which engaging in presumably happiness-increasing activities may actively backfire.
Sonja Lyubomirsky
(University of California, Riverside)
Whither Happiness? When, How, and Why Might Positive Activities Boost Versus Undermine Well-Being
Date: October 25, 2016
Description:
Most people around the world report wanting to be happy. Fortunately, decades of research suggest that individuals can deliberately increase their own happiness via such practices as gratitude or kindness. In this talk, I will introduce the positive activity model (Lyubomirsky & Layous, 2013), which describes when and why positive activities are more (or less) successful at boosting well-being. Then, I will propose several key moderators and mechanisms by which engaging in presumably happiness-increasing activities may actively backfire.
Bruce McNaughton
(University of California, Irvine)
'Zipping' and 'unzipping' the hippocampal index code
Date: October 18, 2016
Description:
There is a long-standing tension between the notion that the hippocampal formation is essentially a spatial mapping system, and the notion that it plays an essential role in the establishment of episodic memory and the consolidation of such memory into structured knowledge about the world. One theory that resolves this tension is the notion that the hippocampus generates rather arbitrary ‘index’ codes that serve initially to link attributes of episodic memories that are stored in widely dispersed and only weakly connected neocortical modules. I will show how an essentially ‘spatial’ coding mechanism, with some tweaks, provides an ideal indexing system and discuss the neural coding strategies that the hippocampus apparently uses to overcome some biological constraints affecting the possibility of shipping the index code out widely to the neocortex. Finally, I will present new data suggesting that the hippocampal index code is indeed transferred to layer II-III of the neocortex.
Joe Henrich
(Harvard University)
The Secret of our Success
Date: May 17, 2017
Description:
Humans are a highly cultural species. Unlike other animals, we are entirely dependent on a vast body of culturally-transmitted tools, techniques, skills, know-how and other cultural-psychological adaptations to survive and thrive in an immense diversity of environments. In light of this, how can we build an evolutionary approach that properly seats our species within the natural world while at the same time providing a framework for understanding our, often peculiar, behavior, psychology, anatomy and physiology? Addressing this question, I’ll begin by applying the logic of natural selection to understanding cultural learning and then consider when and where these learning abilities give rise to the process of cumulative cultural evolution. This non-genetic evolutionary process, not found in other species to any significant degree, generated increasingly rich and complex cultural products, such as cutting tools, fire, cooking, words, throwing spears and social norms (institutions), which in turn became potent selective pressures on our anatomy, brains, motivations and cognitive abilities. Having shaped our species for over a million years, these culture-gene coevolutionary processes provide a synthetic framework for understanding many aspects of our species’ psychology and lay a foundation for explaining—not merely documenting—the immense psychological variation observed around the globe today.
Wendy Berry Mendes
(UCSF)
Physiological covariation among strangers and close others
Date: April 19, 2017
Description:
Emotions, thoughts, and intentions are not simply concepts that live privately in one’s minds, but rather, affective states emanate from us via multiple channels – voice, posture, facial expressions, and behavior – and influence those around us. Affect contagion, or the spread of affective states—including stress, emotions, motivation—from one person to another, is studied in a variety of ways in the social sciences: sociologists find that happiness is contagious within social networks, social psychologists show that mimicking others’ behaviors increases liking, and neuroscientists demonstrate that observing someone experience pain may produce similar neural activation as experiencing pain. In this talk I will discuss a series of experiments exploring the antecedents and consequences of affect contagion using dynamic psychophysiological measurement. The experiments include ones focusing on mothers and children and explore how infants (12 to 14 month olds) “catch” their mothers’ stress reactivity and how touch potentiates stress contagion. Another series of experiments explore how recently acquainted individuals can catch each others’ affective state and how moderators such as racial/ethnic group, social standing, valence and empathetic tendencies moderate affect contagion.
Jessica Hamrick
(UC Berkeley)
Metareasoning and mental simulation
Date: February 22, 2017
Description:
At any given moment, how do we decide what to think about, how to think about it, and how long to think for? My research attempts to answer these questions by focusing on the phenomenon known as “mental simulation”, which is the mind’s ability to imagine seeing, interacting with, and manipulating objects and scenes, almost as if they were real. Mental simulation is an ideal domain for studying how we manage our cognitive resources, in that there are many types of meta-level decisions to be made about mental simulation that cannot always be asked of other forms of reasoning. For example, which mental simulations should be run? How many mental simulations should be run? How long should each be run for? Through a series of behavioral experiments combined with machine learning models, I show how people adaptively use their mental simulations to learn new things about the world; that they choose which simulations to run based on which they think will be more informative; and that they allocate their cognitive resources to spend less time on easy problems and more time on hard problems.
Tobias Gerstenberg
(MIT)
From counterfactual simulations to responsibility judgments
Date: February 15, 2017
Description:
We are evaluative creatures. When we see people act, we can’t help but think about why they did what they did, and whether it was a good idea. Blaming or praising others requires us to answer at least two questions: What causal role did their action play in bringing about the outcome, and what does the action reveal about the person? To answer the first question, we need a model of how the world works. To answer the second one, we need a model of how people work – an intuitive theory of decision-making that allows us to reason backward from observed actions to the underlying mental states that caused them.
In this talk, I will present a computational framework for modeling causal explanations in terms of counterfactual simulations, and several lines of experiments testing this framework in the domains of intuitive psychology and intuitive physics. In intuitive psychology, this framework explains how the causal structure of a situation influences the extent to which individuals are held responsible for group outcomes, and how expectations modulate these judgments based on what a person’s action revealed about their disposition. In the domain of intuitive physics, the model predicts people’s causal judgments about a variety of physical scenes, including dynamic collision events, complex situations that involve multiple causes, omissions as causes, and causal responsibility for a system’s stability. It also captures the cognitive processes underlying these judgments as revealed by spontaneous eye movements.
Brenden Lake
(New York University)
Three principles for understanding distinctively human learning
Date: February 2, 2017
Description:
There has been remarkable recent progress in artificial intelligence and machine learning. Computers can drive cars, defeat Go masters, and hold simple conversations, yet the best example of intelligence is clearly still natural intelligence. My research program explores the many aspects of human cognition that elude machine systems. For example, people can learn a new concept from just one or a few examples, whereas machine learning algorithms typically need tens or hundreds of examples to reach similar levels of classification performance. People can also use their learned concepts in richer and more flexible ways than current machine systems — for imagination, extrapolation, and explanation. Finally, people can learn by asking sophisticated and creative questions, whereas current algorithms pose much simpler and more stereotyped queries. My talk will present behavioral experiments and computational models that examine these uniquely human characteristics across domains such as learning handwritten characters, learning complex visual concepts (i.e., fractals), and asking questions in simple games. I identify three key cognitive principles — compositionality, causality, and learning-to-learn — that are critical ingredients of human-level intelligence. Computational models that integrate these three principles offer insight into how humans solve these impressive tasks while also suggesting new approaches to machine intelligence.
Clara Wilkins
(Wesleyan University)
Causes and consequences of perceiving bias against high-status groups
Date: January25, 2017
Description:
Historically high-status groups were seen as perpetrators and low status groups as victims of bias, but perceptions of this relationship have shifted. Whites and men increasingly see their groups as victims of discrimination. I will discuss both the causes of this shift and the consequences for intergroup relations. I demonstrate that changes to the status hierarchy make some high-status individuals particularly inclined to perceive bias against their group. I highlight how Whites who endorse the racial status hierarchy perceive more anti-White bias in response to perceiving racial progress. I also show that increasing perceptions of bias against high-status groups lead to attitudes and behaviors that ultimately perpetuate social disparities. For example, men who are motivated to maintain men’s advantage relative to women discriminate against women. I discuss the implications of this research for the current political climate and draw parallels between my experimental studies and Trump’s election.
Jasmine DeJesus
(University of Michigan)
The social significance of language: How language shapes children’s social attitudes and transmits conceptual information
Date: January 11, 2017
Description:
Language is multifaceted – not only does language facilitate learning by transmitting information between individuals, but it also marks social groups in nuanced ways. In this talk, I will review research I have conducted that examines children’s developing social attitudes about people who speak in different languages and accents (including children from diverse linguistic backgrounds), children’s beliefs about the relation between cultural groups and food, and their propensity to learn about food from messages provided by other people. My most recent work investigates children’s social reasoning in the context of food, a domain that has been understudied by developmental psychologists but has important implications for revealing the mechanisms underlying early cognitive development. This work also addresses pressing public health concerns, namely the development of obesity.
Steven Roberts
(University of Michigan)
Children's concepts of race
Date: December 14, 2016
Description:
Concepts of race play an important role in U.S. society, such that they contribute to stereotyping, prejudice, and discrimination. However, the extent to which children, learn, understand, and use these concepts is unclear. Do children use race to categorize and evaluate others? When do they show an “adult-like” representation of race? Do concepts of race vary as a function of children’s own racial group? I will present research addressing these and other questions. In one line of research I discovered that the hypodescent concept (e.g., the belief that a person with black and white ancestry is black and not white) stems from attention to perceptual features during childhood, but from ideological motives during adulthood, and that the extent to which this concept develops varies between Black and White children. In a second line of research, I found that the concept of racial stability (e.g., that a Black child will grow up to be a Black adult) develops between the ages of 5 and 10, at different rates across racial groups, and as a function of language input. In a third line of research, I found that children use concepts of descriptive group regularities (i.e., characteristics shared by individuals within a group) to make prescriptive judgments (i.e., characteristics that should be shared by individuals within a group). Together, these studies highlight the complex roles of development and social experiences in the acquisition, understanding, and use of concepts of race. Implications for stereotyping and norm enforcement will be discussed.
Ione Fine
(University of Washington)
Do you hear what I see? How blind individuals understand the auditory world.
Date: December 7, 2016
Description:
Individuals who become blind early in life show superior performance on a wide range of auditory tasks. However, the neural basis of this improved performance is still not well understood. Using a combination of BOLD neuroimaging, behavioral testing and computational modeling, I will describe current research in my laboratory trying to understand the relationship between altered brain responses and the extraordinary ability of blind people to make sense of the auditory world.
Psychology Colloquium Series
(Stanford University)
Lightning Talks 2
Date: November 2, 2016
Gregory Samanez-Larkin
(Yale University)
Motivation and decision making in the aging brain
Date: October 19, 2016
Description:
As baby boomers continue to age into retirement, there is increasing interest in how to apply knowledge from psychological and neuroscientific research to promote wise decision making in old age. This talk will review recent laboratory research on age differences in intertemporal and risky decision making. This work has identified interesting divergent patterns of time and risk preferences across adulthood in different contexts. New research from our lab and others suggests that previous cognitive and neurobiological theories of the aging brain may need to be revised to account for these context-dependent motivational effects. Specifically, the findings of a recent meta-analysis point to one dopaminergic mechanism that might be spared or even enhanced with age that may partially explain these effects. The talk will conclude with the implications of this work for decision making in the real world.
Psychology Colloquium Series
(Stanford University)
Lightning Talks
Date: October 5, 2016
Frank Tong
(Vanderbuilt)
Visual orientation and its contributions to perception, attention and working memory
Date: May 4, 2016
Description:
Orientation is a fundamental feature that underlies how we see, make sense of, and imagine the visual world. In this talk, I will describe behavioral, computational, and neuroimaging research that demonstrates how the study of orientation processing can provide a window into mechanisms of perception, attentional selection and visual working memory. In recent fMRI work, we find that the earliest site of orientation processing takes place in the human lateral geniculate nucleus, where modest but reliable orientation responses can be found (Ling, Pratte & Tong, Nat Neurosci, 2015). Attentional feedback, presumably from cortical sources, can modify the strength of orientation-selective responses in the LGN. Activity patterns in cortical visual areas also reveal strong correspondences with perception, including the well-known tilt illusion and the oblique effect. Our behavioral and neuroimaging investigations further demonstrate how orientations are represented in visual working memory, and how the precision and capacity of working memory is highly dependent upon the nature of these stimuli. By incorporating orientation processes into computational models of visual working memory, we go on to show how stimulus-specific representations are important for discerning between discrete-item and continuous-resource models of working memory.
Amanda Woodward
(University of Chicago)
Acting and thinking in infancy
Date: April 20, 2016
Description:
In the study of early cognitive development there is considerable debate not only as to what infants understand, but also how best to characterize the nature of their knowledge. In this talk, I will engage this broad question in considering infants’ knowledge about others’ intentional actions. Drawing on recent findings from our laboratory, I will make two claims (1) Young infants’ analysis of meaningful structure in others’ actions is grounded, to some significant extent, in information derived from their own actions; and (2) This fact does not mean that infants’ understanding of others’ action analysis is concrete, low-level, or cognitively uninteresting. In fact, infants’ action knowledge is cognitively generative. I will review research that illustrates this generativity in the context of infants’ intelligent social behavior, their generalization of learning to new instances, and their memory for events. In each case, our findings suggest not only that infants’ action knowledge provides a foundation for adaptive responding and learning, but also that infants’ engagement in action fuels their thinking.
Yaoda Xu
(Harvard University)
Multi-level and dynamic visual information representation in the human brain
Date: March 2, 2016
Description:
The human vision is fundamentally a construction process. As reflected in the hierarchical structure of the human ventral visual system, complex visual inputs are broken down into simple features and then reassembled to form increasingly complex representations. Through this process, we gain access to visual information at multiple distinctive levels, such as lines, edges, parts, and objects. Yet at any given moment, we are able to navigate through these different levels of visual representations and extract information at the appropriate level for the task at hand. This highlights two important issues that are critical to understanding visual information processing in the human brain: (1) how are simple features combined to give rise to increasingly complex representations at multiple distinctive levels? And (2) how is the moment-to-moment goal-driven visual information processing accomplished? Using fMRI and multi-voxel pattern analysis, our research attempts to address these two questions by examining how parts, objects and ensembles are represented in the human ventral visual cortex and the role of the human parietal cortex in dynamic visual information representation.
Rebecca Saxe
(MIT)
It’s the thought that counts: progress in understanding the neural basis of thinking about thought
Date: February 10, 2016
Description:
Perhaps one of the most surprising discoveries of early functional neuroimaging studies in humans was that a group of cortical regions, including bilateral temporal parietal junction (right and left TPJ) and medial prefrontal cortex (MPFC), show preferential activity while people are thinking about other people’s thoughts. We now have extensive evidence concerning when, how much, and how selectively these regions are recruited in healthy adults. By contrast, not much is known about the representations and computations supported by the populations of neurons in these regions, or about how development in these neural populations supports the dramatic changes in social cognition that occur in childhood. I will describe some new directions of research in my lab aimed at characterizing the feature-space of mental state inferences, and using this feature-space as a window on social cognitive development.
Nick Turk-Browne
(Princeton)
Interactions of statistical learning with perception, attention, and memory
Description:
The environment is highly stable over time. Not only do we repeatedly encounter the same people, places, and objects, but they also tend to appear in regular sequences and configurations. These regularities are extracted rapidly and often without effort or awareness, resulting in higher-order knowledge of words, events, and scenes. Based on behavioral studies, I will suggest that this kind of statistical learning has widespread consequences for the mind, including showing that it distorts the perception of ensemble features such as numerosity, and that it commands attention to locations and features with structure. Based on neuroimaging, patient, and computational studies, I will then suggest that the medial temporal lobe memory system helps implement this kind of statistical learning in the brain, including showing that the hippocampus learns structure by shaping the representational space for objects to mirror both simple and complex regularities. These studies reveal the deep and broad ways in which statistical learning interacts with other aspects of cognition.
Psychology Colloquium Series 2012-2015
J. David Creswell
(Carnegie Mellon University)
The Mindful Mindset: Stress-Health Pathways
Date: December 2, 2015
Description:
Over the last decade there has been significant interest in mindfulness and mindfulness training interventions for health. But little is known about how this mindset of being open and receptive to present moment experience (‘mindfulness’) might affect health over time. In this talk I will describe current theory on mindfulness, and a series of studies we have conducted that depict potential brain and physiological stress reduction pathways linking mindfulness with a broad range of health outcomes. Discussion will focus on a consideration of the underlying psychological mechanisms of these mindfulness-stress reduction-health links.
Craig Fox
(UCLA)
Two Dimensions of Subjective Uncertainty
Date: October 14, 2015
Description:
In my talk I will argue that people maintain dual intuitions about the nature of uncertainty, and these intuitions can have a critical impact on judgments and choices. In some cases people attribute uncertainty to deficiencies in their knowledge, information, and/or mental model of relevant events (knowable or “epistemic” uncertainty); in other cases people attribute uncertainty to causal systems in the world whose behavior is largely stochastic (random or “aleatory” uncertainty). I will briefly review evidence of this distinction from prior literature and then present a series of novel empirical studies. First, I will show that epistemic (knowable) uncertainty is marked in natural language by statements such as “I am 80% sure that…” or “I am reasonably confident that…” whereas aleatory (random) uncertainty is marked by statements such as “I think there is an 80% chance that…” or “I believe there is a high probability that…”. Second, I will show that people reliably distinguish between epistemic and aleatory uncertainty in their rating of events, and forecasters are assigned more credit/blame for correct/incorrect predictions when events are seen as more epistemic (knowable) whereas they are seen as more lucky/unlucky when events are seen as more aleatory (random). Moreover, people sometimes make self-serving attributions concerning the nature of uncertainty. Third, I’ll show that people tend to make more extreme probability judgments (and therefore exhibit greater overconfidence) when assessing events that they see as more epistemic (knowable) or less aleatory (random). Finally, I’ll show that investing behaviors (e.g., time horizon, diversification, advice-seeking) are associated with individual differences in perceptions of market uncertainty. I’ll conclude with a brief discussion of further implications and directions for future research.
Wei Ja Ma
(NYU)
Decision-making in combinatorial games
Date: June 3, 2015
Description:
Decision-making tasks such as navigation, negotiation, writing a paper, career planning, playing board games and military strategy involve long sequences of decisions with multiple options at each step, leading to a combinatorial explosion of the decision tree. To make such decisions tractable, people must prune the tree. To investigate how people do this, we use a set of experimental paradigms involving a new variant of tic-tac-toe: people playing against each other, against computers of different strengths, solving puzzles, choosing between two moves, and evaluating positions. We model the data using AI-inspired models.
Jean Twenge
(San Diego State University)
Modern culture and individualism: Has self-focus made us better or worse?
Date: May 20, 2015
Description:
Cultures change, and generations change with them. Just as in cross-cultural comparisons, individuals and cultures mutually constitute on another. But how can cultural change be concisely understood? There is no one answer, but this talk explores four possible models of cultural change in the U.S. over the last few decades: Everything is getting better, everything is getting worse, rising individualism, and rising collectivism. Evidence includes cultural and generational change in self-views (including self-esteem, thinking one is above average, narcissism, uniqueness in given names, and individualistic language) and changes in views of others (including tolerance, gender equality, concern for others, and civic engagement). The evidence primarily fits the view that individualism has increased in American culture. The talk concludes with data on whether this is a beneficial or detrimental trend.
Phil Cowan & Carolyn Cowan
(UC Berkeley)
Interventions for parents to strengthen family relationships and benefit children: 40 years of research in 40 minutes
Date: April 29, 2015
Description:
Couples groups, father involvement interventions, and parenting classes have all been promoted as programs that will improve the lives of children. Each of these approaches ignores at least one key feature of the other two. In this talk we describe a new intervention approach that invites couples to work in small groups with clinically trained co-leaders, involves fathers, helps to increase couple satisfaction and parenting effectiveness and lower parenting stress – and has positive effects on children from 18 months to 10 years after the intervention ends. We describe a 5-domain model of risk and protective factors that affect fathers’ involvement, both parents’ satisfaction, and children’s development. We present data from three longitudinal studies that include 4 randomized trials and a replication, with an intervention model that addresses each of these aspects of family life. In each intervention trial we find support for the model: Improving couple and co-parenting relationships and preventing the normative decline in relationship satisfaction over time in parents of young children affects father involvement, parenting quality, and positive outcomes for children. We conclude with a brief discussion of some policy issues raised by current controversies about the effectiveness of couples group interventions.
Elizabeth Spelke
(Harvard University)
Core Knowledge and Conceptual Change: Persons
Date: February 11, 2015
Description:
Mature human cognition is complex and variable, both across contemporary cultures and over human history, but human cognitive development proceeds in a more predictable pattern, especially in infants and young children. Studies of infants’ cognitive abilities in non-social domains (including object cognition, numerical cognition and spatial cognition) shed light on the starting points for human cognitive development. Together with studies of these cognitive abilities in other animals, at other ages, and in different cultures, this research suggests deep properties of physical and mathematical reasoning in older children and adults. Here I ask whether studies of infants can bring similar insights into human social cognition. Do the complex social inferences and intuitions of adults develop from, and build on, simpler systems that are functional in infancy? If so, what are the properties of these systems, and what roles do they play in the richer social reasoning that emerges later in development? Recent studies of human infants, using simple behavioral methods, suggest that the answers to these questions may lie within reach. I describe some new findings and call for a multi-species, multi-leveled search for the core mechanisms by which humans navigate the social world.
Daniel Yamins
(MIT)
Using Behaviorally-Driven Computational Models to Uncover Principles of Cortical Representation
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Date: February 4, 2015
Description:
Human behavior is founded on the ability to identify meaningful entities in complex noisy data streams that constantly bombard the senses. For example, in vision, retinal input is transformed into rich object-based scenes; in audition, sound waves are transformed into words and sentences. In this talk, I will describe my work using computational models to help uncover how sensory cortex accomplishes these enormous computational feats.
The core observation underlying my work is that optimizing neural networks to solve challenging real-world tasks can yield predictive models of the cortical neurons that support these tasks. I will first describe how we leveraged recent advances in high-performance computing to train a neural network that approaches human-level performance on a challenging visual object recognition task. Critically, even though this network was not explicitly fit to neural data, it is nonetheless predictive of neural response patterns of neurons in multiple areas of the ventral visual pathway, including higher cortical areas that have long resisted modeling attempts. This model also makes two counterintuitive but testable predictions. One is that inferior temporal (IT) cortex, an area generally thought to specialize in ‘high-level’ categorization of objects, also represents ‘low-level’ visual properties (e.g., position, size, pose, etc.) — and in fact, represents better than low-level visual areas. The other is that face selectivity, a property of some high-level neurons commonly believed to require extensive experience with faces to achieve, can emerge just from the model architecture itself.
Intriguingly, some of these same ideas turn out be helpful for studying audition. We have recently found that neural networks optimized for word recognition and speaker identification tasks naturally exhibit high predictivity for fMRI BOLD responses in human auditory cortex to a wide spectrum of natural sound stimuli, and help differentiate poorly understood non-primary auditory cortical regions. I’ll discuss the similarities and differences between these models and those that perform well on visual tasks, assessing the extent to which they provide the beginnings of a general approach to understanding sensory cortex.
Roger Levy
(UC San Diego)
Expectation-based language comprehension and production
Date: January 28, 2015
Description:
Using language to communicate is central to what makes us human. Elucidating the knowledge, expectations, and cognitive resources that allow us to communicate so effectively is one of the most fundamental problems in the study of mind. For much of the contemporary history of psychology and linguistics, motivated by the ideas of figures including Chomsky, Miller, and Fodor, work on this problem has conceptualized language processing as centrally about modular structure-building operations and the memory resources required to carry them out. Here I describe an alternative approach that conceptualizes language processing as centrally about rational, goal-driven inference and action. First, I outline a state-of-the-art theory of expectation-based incremental language understanding, in which comprehenders integrate diverse information sources from preceding context to guide interpretation of current input. This theory unifies three key, seemingly disparate topics in the domain of language understanding — ambiguity resolution, prediction, and syntactic complexity effects — and finds broad empirical support in data from both controlled experiments and naturalistic language understanding. Second, I describe several apparent empirical puzzles for this theory that ultimately lead us to revisit one of the implicit foundational assumptions in all theories of language understanding: that of modularity between the processes of word recognition and of inter-word, utterance-level comprehension. I generalize the expectation-based theory to a fully bidirectional, interactive theory of word recognition and utterance comprehension, and show how this generalized theory solves the apparent puzzles and leads to a range of new, empirically verified predictions. Finally, I touch briefly on the consequences of this view for language production: why do speakers choose to structure their utterances the way they do? The expectation-based theory novelly predicts that speakers use the options afforded them by their native language to come as close as possible to a uniform distribution of information content throughout their utterance. We confirm this prediction through statistical analysis of speaker choices regarding optional word omission in naturalistic speech.
Anne Collins
(Brown University)
The hidden players in human reinforcement learning
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Date: January 21, 2015
Description:
Classic models of reinforcement learning use a single computational principle to describe how we learn values and decision policies for well-defined states and actions. They account for a host of behavioral and neural data from the basal ganglia-dopamine system. However, additional mechanisms make human reinforcement learning efficient and flexible: they help us organize states and actions, and control how, what, and when to learn. I study the neuro-cognitive processes that contribute to human learning, and their interactions. In this talk, I will present one theme from this research program.
In a series of behavioral experiments, I show that when learning stimulus-action mappings through reinforcement, adult human subjects tend to structure their policy into abstract rules, even when this does not afford any immediate advantage. Algorithmic and neural-network-level computational models predict that creating such abstract rule structure enables later generalization of new information and transfer of known rules to new contexts. Results from behavioral and EEG experiments support model predictions, with EEG evidence for hidden structure predicting individual differences in transfer.
Throughout my research, computational models play a crucial role to identify the latent processes that jointly contribute to learning behavior, and to relate them to their neural substrates. I will show examples of combining computational modeling with genetic studies, functional imaging, and patient and developmental studies to understand interactive processes in learning.
George Alvarez
(Harvard University )
How representing multiple objects (and features) as an ensemble enhances higher-level visual cognition
Duration: 1h 6m 50s
Date: January 15, 2015
Description:
The human visual system has a massively parallel architecture, and yet it can only accurately represent a handful of objects at once. A vast literature has focused on ways to explain these severe capacity limitations (slots, resources, central bottlenecks, brain juice, neural competition), but today I will focus on understanding how the visual system copes with these limitations. Specifically, I will focus on the possibility that the visual system does what we (scientists) would do with a bunch of noisy measurements: it averages them and combines them to represent a statistical summary, or ensemble representation. I will describe recent experiments which show that ensemble representations can be extracted at early processing stages (prior to object or scene recognition) and that these statistical representations enhance downstream processes, including attentional guidance, object recognition, and perhaps categorization as well. Combined, these results suggest that ensemble representations are efficiently computed and useful for many stages of visual processing, making ensemble coding a crucial mechanism for coping with the severe capacity limits on higher-level visual cognition.
Talia Konkle
(Harvard University )
The large-scale organization of object representation
Duration: 1h 15m 6s
Date: January 14, 2015
Description:
How are representational spaces of the mind mapped onto the surface of the brain? In the domain of visual object representation, there is no widely accepted model of the coding dimensions of objects: the representational space of objects is so high-dimensional that its neural organization is assumed to have only a few category-selective regions with remaining heterogenous structure only at a fine-grained scale.
In contrast to this view, I will present results showing there is a large-scale organization of object responses spanning the entire ventral and lateral occipito-temporal cortex, based on two major cognitive dimensions of objects: animacy and real-world size. Regions selective for faces, bodies, and scenes fit within this organization at a meso-scale. These results demonstrate that object cortex, just like early visual cortex, has structure that can be explained at multiple spatial scales, where the large-scale neural organization reflects core factors in the representational space.
Motivated by these findings, I will present a theoretical framework in which we can leverage the spatial topography of neural responses to help infer and test the structure of the underlying cognitive architecture. While developed in the context of explaining object representation, this framework is broadly applicable to understanding the organization of many forms of knowledge on the cortical surface.
Wendy Suzuki
(New York University)
Plasticity Two Ways
Date: December 3, 2014
Description:
In my lab, we have examined two distinct forms of plasticity in the primate brain. In the first part of my talk I will summarize our most recent work from behavioral neurophysiological studies describing striking incremental timing signals in the hippocampus of non-human primates. We have focused on timing because it plays such a critical role in episodic memory, or memory for the events in our lives, a function known to be dependent on the hippocampus. In the second part of my talk, I’ll summarize findings from studies in humans examining the effects of aerobic exercise on learning, memory, cognition and mood. I will also describe our efforts to expand these studies to examine the effects of aerobic exercise on academic performance in schools.
Tor Wager
(University of Colorado, Boulder)
Neuroimaging of pain and distress: The path from blobs to biomarkers to brain representation
Date: November 5, 2014
Description:
Pain and emotional distress are realities that affect us all. Preventing, resolving, and sometimes accepting pain and distress motivates many human endeavors, ranging from spiritual practices to medical interventions. Understanding the brain representations that underlie pain and suffering could transform how we understand and treat them; but currently, there are no human brain measures adequate for determining whether one is angry or sad, whether pain is physical or emotional, or whether one is feeling pain that is intense or mild.
In this talk, I describe a series of studies aimed at beginning to address these questions. Combining functional neuroimaging with machine learning techniques, we have developed brain markers capable of indicating the intensity of pain and negative emotion in individual participants with > 90% accuracy, with no prior knowledge of an individual’s experience. In addition to their use as markers, such maps can provide insight into the structure of the neurophysiological representations underlying pain and distress. Our findings to date suggest that specific types of aversive experiences are encoded in separate, population-based patterns that are co-localized in similar gross anatomical circuits.
These studies are part of a transformational shift in how neuroimaging data is being used, from early ‘blob-based’ brain-mapping studies to the development of predictive maps with tangible translational potential. They show that as the field progresses, we may be able to map specific types of subjective experience to specific brain circuits. This endeavor enables cross-species mapping of mechanisms, translational work on treatment development, and new ways of understanding and relieving human suffering.
Psychology Colloquium Series
(Stanford University)
Lightning Talks
Date: October 1, 2014
Description:
1. Are Emotions Always Contagious?: Amit Goldenberg, Tamar Saguy, Eran Halperin, James Gross
2. Learning From Actions and Outcomes: Daniel Hawthorne and Noah Goodman
3. Physician Health Behavior As a Cue of Potential Judgment In Doctor-Patient Interactions: Lauren Howe & Benoît Monin
4. The Length of Words Reflects their Conceptual Complexity: Molly L. Lewis and Michael C. Frank
5. Relational Barriers: A Field Experiment to Improve Perspectives On School Discipline: Jason Okonofua, David Paunesku, & Gregory Walton
6. Dynamic Norms: Impacts of Learning About Others’ Behavioral Changes: Gregg Sparkman, Greg Walton
7. Prior State Effects on Instrumental Behavior: Rav Suri, Gal Sheppes, James Gross
8. Three Dimensions Shape Neural and Psychological Representations of Others’ Mental States: Diana Tamir, Mark Thornton, Juan Manuel Contreras, Jason Mitchell
9. Adaptive Engagement of Cognitive Control Reflects a Predictive Model of Task Context: Michael L. Waskom, Michael C. Frank, Anthony D. Wagner
Ehud Zohary
(Hebrew University)
Representations of space for action in the human motor system: A revision to the classical view
Date: 10/24/2012
Description:
Our understanding how target-directed actions are represented in the brain, is quite limited. Probably, the best cases in which some insight has been gained over the years, are (1) the representation of simple directional limb movement in primary motor cortex (termed M1), and (2) the encoding of saccades in the occulomotor system. In this talk I will suggest that even these classics should be somewhat revised.
Further Information:
Richard J. Davidson
(University of Wisconsin-Madison)
Order and Disorder in the Emotional Brain
Date: 10/03/2012
Description:
Emotions are at the core of human personality, they define each person’s uniqueness and they shape resilience and vulnerability to adversity. Perhaps the single most salient characteristic of emotion is the variability across individuals in how each responds to emotional cues and challenges. This variability is termed “affective style.” Different parameters of affective style can be objectively measured and are instantiated in different underlying neural circuits. Activation patterns assessed with neuroimaging are related to different parameters of affective style and are consistent over time within individuals. Specific patterns of brain activity are related to vulnerability to particular types of disorders. Moreover, patterns of central brain function are related to peripheral biological systems that play a role in physical health and illness. Despite their consistency over time within individuals, these patterns of neural activity are not immutable to change but rather can be transformed through systematic mental training such as meditation. The literature on neuroplasticity provides a framework for understanding these changes. This latter body of evidence supports the view that happiness, well-being and emotional balance are best regarded as the product of trainable skills.
Further Information: