Unless otherwise noted, all talks are Wednesdays 12:30–2:30 and via Zoom. Prior to each talk, the Zoom link will be emailed to all students and faculty from Cognitive Science and Philosophy. If you're affiliated with York but not in one of those groups, and want to receive the Zoom links, email firstname.lastname@example.org from your York email address.
Sarah Robins, Philosophy, University of Kansas
The Memory Trace in Philosophy and Neuroscience
Memory traces are a persistent yet puzzling feature of our thinking about memory. They have been a part of theorizing about memory for as long as there has been theorizing about memory. But they’re also mysterious. The primary way of ‘making sense’ of them is via metaphors—traces are likened birds in aviaries, impressions in wax, items in a warehouse, or grooves in a record. As philosophy of memory has grown recently into an active subfield, many working in this area consider traces an unnecessary and outdated idea. Meanwhile, memory researchers in neurobiology proclaim that we are in the midst of “engram renaissance” (Josselyn, Köhler, & Frankland, 2017). Engram is a new word for an old idea, the current scientific term for the memory trace. New tools like optogenetics have produced a number of discoveries, exciting not only for what they reveal about the basic mechanisms of memory, but for the opportunities they provide to connect with broader areas of memory science. What are memory traces, and do we need them? The memory trace (or engram) remains woefully undertheorized—a neglect that persists even as the philosophy of memory expands. In this talk, I sketch a way to address this, developing a theory of the engram/trace that captures work in contemporary neurobiology and conveys its significance for our theorizing about memory more broadly. The account also serves to appropriately situate the neurobiology of memory as a central contributor in the interdisciplinary inquiry into memory, and as an area of memory science worth the attention of philosophers of memory.
Joel Zylberberg, Physics, York University
Learning from Unexpected Events in Hierarchical Cortical Circuits
Scientists have long conjectured that the cortex learns the structure of the environment in a predictive, hierarchical manner. According to this conjecture, expected, predictable features are differentiated from unexpected ones by comparing bottom-up and top-down streams of information. It is theorized that the cortex then changes the representation of incoming stimuli, guided by differences in the responses to expected and unexpected events. To test these ideas, we compared neural activity recorded at the somata and distal apical dendrites of cortical pyramidal cells: these neuronal compartments tend to receive bottom-up and top-down information, respectively. While previous work showed different responses to expected and unexpected sensory features at the somata (bottom-up information), the top-down signals (apical dendrites) had not previously been measured, leaving the nature of this hierarchical computation largely untested. Leveraged recent improvements in in vivo microscopy, and in image processing, we were able to track the responses of individual somata and apical dendritic branches of layer 2/3 and layer 5 pyramidal neurons over multiple days in awake, behaving mice using two-photon calcium imaging, while the mice were exposed to stimuli that were initially unexpected. Our main finding was that both somata and distal apical dendrites of cortical pyramidal neurons exhibit distinct unexpected event signals that systematically change over days, as the animals learn about these stimuli. Interestingly, these top-down vs bottom-up responses evolved in opposite directions in the somata and distal apical dendrites as a result of learning, supporting the hierarchical predictive coding model of sensory cognition.
Joey T. Cheng, Psychology, York University
Force and Persuasion: How Do We Humans Climb the Social Hierarchy?
This talk will explore how two fundamental strategies to social rank—dominance (i.e., relying on intimidation to induce compliance) and prestige (i.e., earning respect via competence to increase persuasion)—influence individual and group outcomes. In both field and lab groups, individuals who use a dominance or a prestige strategy exercise greater behavioral impact and receive more visual attention. Prestige, however, appears to offer a more stable form of influence over time. Highlighting the distinction between these strategies, individuals signal their dominance by deepening their voice pitch—a unique vocal pattern that is absent among those who adopt a prestige strategy. In the biological domain, individuals who gain high prestige in their community show a subsequent increase in testosterone, which may function to motivate future rank-seeking behavior in an adaptive manner. In terms of collective outcomes, when these strategies are deployed by leaders, dominant leaders lead to group-wide negative affect. By contrast, prestigious leaders boost team creativity, follower loyalty, and positive affect. Together, these findings indicate that although both dominance and prestige strategies reward individuals with higher rank and social success, they are underpinned by distinct nonverbal signals and biological substrates, and confer distinct benefits and costs on self, other, and teams. Other current and future research will be highlighted.
Tania Lombrozo, Department of Psychology, Princeton University
Explanation: The Good, the Bad, and the Beautiful
Like scientists, children and adults are often motivated to explain the world around them, including why people behave in particular ways, why objects have some properties rather than others, and why events unfold as they do. Moreover, people have strong and systematic intuitions about what makes something a good (or beautiful) explanation. Why are we so driven to explain? And what accounts for our explanatory preferences? In this talk I’ll present evidence that both children and adults prefer explanations that are simple and have broad scope, consistent with many accounts of explanation from philosophy of science. The good news is that a preference for simple and broad explanations can sometimes improve learning and support effective inferences. The bad news is that under some conditions, these preferences can systematically lead children and adults astray.
Lisa Miracchi, Department of Philosophy, University of Pennsylvania
Real intelligence: Avoiding Substitution Bias, Echo Chambers, and Philosophical Laundering
I argue for what I call a stance of practical emergence towards intelligence and related kinds such as perception, knowledge, and action. Practical emergence is a commitment in explanatory practice to treating higher-level kinds as distinct from lower-level kinds, such that they cannot be reductively identified in lower-level terms, and to assuming that explanations of them in terms of lower-level kinds may be substantive, in that behavior of higher-level kinds cannot be logically or mathematically deduced from lower-level behavior. I’ll flesh out this stance using the Generative Framework for explaining how higher-level kinds obtain in virtue of lower-level kinds. Then I’ll show how this stance of practical emergence, bolstered by the Generative Framework, saves us from three main pitfalls affecting much contemporary cognitive science, AI, and robotics research. First, it helps us better understand our explananda by avoiding substitution bias — the phenomenon of accidentally trading the problem we want to solve for an easier one. Second, it helps us avoid creating echo chambers where the reductive hypotheses about intelligence kinds are amplified, not because they are empirically supported but because they allow for more simple interdisciplinary communication. Third, it helps us empirically examine our commitments about the nature and key features of intelligence kinds by avoiding philosophical laundering, a phenomenon where support for a philosophical view is illegitimately strengthened because it is adopted as a working hypothesis in empirical research but is not itself an object of empirical scrutiny. In each case, I’ll use examples from contemporary cognitive science and engineering to demonstrate the payoff of retaining higher-level vocabulary in intelligence research. Lastly, I’ll discuss some important ethical implications of adopting this approach.
Amanda Seed, School of Psychology and Neuroscience, University of St. Andrews
Thinking in the Abstract: Evolutionary Origins
Abstract concepts allow wide-ranging predictions in new situations based on sparse data. Whereas some looking-time studies point towards an early emergence of this ability during the first year of life (e.g. Dewar & Xu, 2010, Yin & Csibra2015), others show failure to use abstract concepts like same and different until 4-5 years of age, and suggest a relationship with linguistic ability (Hochmann et al., 2017). Similarly, the evolutionary emergence of the ability to form abstract concepts remains highly debated, both because of mixed results from non-human primates, and different interpretations of positive results following long training regimens. I will present data from two recent lines of work, aiming to shed new light on this old question.
The first is a series of experiments designed to test a computational model of abstract knowledge formation (Kemp et al. (2007)). We developed an ecologically valid method for testing chimpanzees, capuchin monkeys and 3-5-year-old human children, and compared their performance to the model predictions. The second is a series of experiments examining the ability to imagine an unseen physical cause to infer the location of food rewards. We developed paradigms which required little verbal framing, exploring participants’ ability to find rewards when they could benefit from applying prior physical knowledge to make sense of the information given.
Our results show some areas of overlap in performance. We also find some differences in ability between preschoolers and non-human primates, though interestingly, in these cases we also find, in the children, a relationship between performance and age, and the ability to provide verbal explanations. I will suggest an account whereby non-human primates are able to make use of some kinds of abstract information when the testing situation does not overwhelm other cognitive abilities, and discuss what might develop in the later part of the pre-school years to allow children to outperform their nearest primate relatives.
Charles Yang, Departments of Linguistics, Computer Science, and Psychology, University of Pennsylvania
Good Enough is Better than Best
What is the past participle of the verb “stride”?
I stride down the street, you strode down the street, and they have __ down the street???
The thought is perfectly natural but the linguistic form is not available for speakers of (North) American English. Why not “they have strode down the street”? After all, the vast majority of verbs have the same form for past tense and participle: “walk-walked-walked”, “jump-jumped-jumped”, “think-thought-thought”, “sleep-slept-slept” …
Language is famous for being infinitely productive: when “google” became a verb in English, no one hesitated to add “-ed” (“googled”), despite the rule (“add -ed”) has quite a few exceptions, namely, the irregular verbs. But language also has a soft underbelly where rules break down: we are bound by experience and refuse to generalize—as in the case of “stride".
It turns out that rule learning in language requires a delicate calibration of evidence: We form generalizations when the supporting evidence is sufficient, or good enough, even though some residual exceptions may remain. This enables children in a linguistic community to learn essentially the same rules, even though their individual experience with language (e.g., vocabulary) can vary significantly. I will offer a very precise theory of how good is good enough.
Good enough learning protects the learner from over-fitting, a problem that plagues modern machine learning systems, which are invariably predicated on some optimization principle: maximize the probability of the training data, minimize the error term for the learning function, etc. Insights from how biological systems learn may prove necessary for the development of robust learning and AI systems.
Thibaud Gruber, Swiss Institute for Affective Sciences, University of Geneva
A Cognitive Approach to Wild Cultures
Environment and genetics have played a central part in the debate on the existence of the question of animal—particularly chimpanzee—culture, often as a way to dismiss the possibility of their existence. Today, the debate is no longer on whether chimpanzees have culture or not. Rather, empirical researchers and theorists now attempt to decipher how much chimpanzee cultures compare to human cultures, and the evolutionary relatedness between the two phenomena. In particular, the interaction between social and ecological mechanisms appears crucial. Here, I will use the results of my own research on tool use with the Sonso community of Budongo Forest, Uganda (Pan troglodytes schweinfurthii) to provide novel insights on chimpanzee culture and how it compares to human culture. Critically, the Sonso chimpanzees, a community with a leaf-based culture, have proven surprisingly reluctant to learn stick use, a behaviour long classified as a universal in chimpanzees. The once particularly favourable environment of the Budongo Forest may have both led to the disappearance of the stick use behaviour in the community, but also provided a buffer against the re-invention of the behaviour. More recent results on the development of a novel tool use behaviour, moss-sponging, suggest that chimpanzees expand their cultural repertoire in the vicinity of what they know already rather than through brand new innovations. The emerging picture is that ecological reasons, particularly through their impact on energy balance, can trigger the appearance of novel cultural behaviour, which will then be transmitted through social learning processes. At the cognitive level, my work supports the idea that apes are limited in their ability to represent their cultural knowledge, a determining feature of modern human cultures, a hypothesis named the Jourdain Hypothesis, after Molière's character. I will also connect this research with my work in child development, to evaluate what features may have changed in our cognitive evolution to make our cultures so different from those of our closest relatives. In particular I will argue that emotions have to be part of the debate to fully understand the differences between humans' and other animals' cultures.
Cecilia Heyes, All Souls College and Department of Experimental Psychology, University of Oxford
Cultural Evolutionary Psychology
The character and effectiveness of cognitive mechanisms has traditionally been explained by nature and nurture. In the last decade, evidence has emerged that distinctively human cognitive mechanisms, like physical technology, are shaped by culture. At the individual level, these “cognitive gadgets” are inherited via social interaction. At the population level, they have been made fit for purpose by cultural selection. In the first part of the talk I will introduce these ideas using the example of imitation. In the second, focussing on metacognition, I will discuss the prospects for a cultural evolutionary psychology.
Natalie Brito, Department of Applied Psychology, New York University
Early Bilingual Experience and Neurocognitive Development
It is well known that early experiences play a critical role in shaping trajectories of brain development and behavior. Research that examines how children learn from their caregivers and environments are needed, but more importantly, studies that incorporate culturally and linguistically diverse families are imperative to gain a fuller understanding of how basic learning mechanisms may vary across children’s experiences.Understanding the wider effects of the sociocultural context on development can potentially help to disentangle the many pathways through which adaptations to the environment impact brain and behavior. This talk will highlight two experiences common to many children, social inequality and multilingualism, and will examine associations between these experiences and neurocognitive development.
Gary Lupyan, Department of Psychology, University of Wisconsin, Madison
How Words Structure Our Concepts
Does language reflect the categories of our mind or does it help create them? On one widespread view learning a language involves mapping words onto pre-existing categories, leaving little room for language to affect the conceptual landscape. Alternatively, many of our concepts — including some that seem very basic — may derive from our experience with and use of language. I will argue in favor of this second view and present evidence for the causal role of language in categorization and reasoning.
Maria Gendron, Department of Psychology, Yale University
Sources of Diversity in Emotion Perception
Unpacking the nature of emotions is critical to a scientific understanding of the human condition. Recent evidence reveals that emotion categories contain considerable neural, physiological and behavioural variation, challenging long-held views of emotion in psychology and neuroscience. Consistent with these broad patterns, I will present research highlighting diversity in perceptions of emotion across societies and individuals. I will suggest that the functioning of the conceptual system (what we "know" about emotions) serves as a source of both variation and consistency across levels. This research is informed by the constructionist proposal that culturally learned knowledge may account for the discrete and functional nature of emotions.
Oliver Scott Curry, Institute for Cognitive and Evolutionary Anthropology, Oxford University
Morality as Cooperation: Past, Present, and Future
What is morality, where does it come from, how does it work? According to the theory of morality-as-cooperation, morality is a collection of biological and cultural solutions to the problems of cooperation recurrent in social life. As evolutionary game theory has shown, there are many types of cooperation, hence the theory explains many types of morality, including: family values, group loyalty, reciprocity, hawkish heroism, dovish deference, fairness and property rights. Previous research has shown that, as predicted, these seven types of morality are psychologically distinct, and cross-culturally universal. Current research is investigating their genetic, neuroanatomical, and cultural-phylogenetic bases. Future research will explore the implications of morality as a ‘combinatorial system’, and show how cooperation explains sexual morality. Continuing to test the many implications of the theory will help to put the study of morality on a firm scientific foundation.
Gabrielle Johnson, Department of Philosophy, Claremont McKenna College
Proxies Aren’t Intentional, They’re Intentional
This talk concerns 'The Proxy Problem': often machine learning programs utilize seemingly innocuous features as proxies for social sensitive attributes, posing various challenges for the creation of ethical algorithms. I argue that to address this problem, we must first settle a prior question of what it means for an algorithm that only has access to seemingly neutral features to be using those features as ‘proxies’ for, and so to be making decisions on the basis of, protected class features. I argue against theories of proxy discrimination in law and political theory that rely on overly intellectual views of the intentions of the agents involved or on overly deflationary views that reduce proxy use to mere statistical correlation. Instead, using insights from philosophy of language and mind, I adopt an anti-individualist account of representational content to argue for a constitutive account of ‘contentful proxy use’. On this view, proxies represent socially sensitive features when and only when they constitutively depend on discriminatory practices against
Myrto Mylopoulos, Philosophy & Cognitive Science, Carleton University
On Skepticism about Unconscious Perception
While there seems to be much evidence that perceptual states can occur without being conscious, some theorists recently express skepticism about unconscious perception. Drawing on joint work with Jacob Berger, I explore here two kinds of such skepticism: Megan Peters and Hakwan Lau’s experimental work regarding the well-known problem of the criterion—which seems to show that many purported instances of unconscious perception go unreported but are weakly conscious—and Ian Phillips’ theoretical consideration, which he calls the ‘problem of attribution’—the worry that many purported examples of unconscious perception are not perceptual, but rather merely informational and subpersonal. I argue that these concerns do not undermine the evidence for unconscious perception and that this skeptical approach results in a dilemma for the skeptic, who must either deny that there is unconscious mentality generally or explain why perceptual states are unique in the mind such that they cannot occur unconsciously. Both options, I argue, are problematic.
Josh Plotnik , Psychology, Hunter College, City University of New York
Can Comparative Cognition Play a Role in Endangered Species Conservation?
The study of convergent cognitive evolution is an exciting research area aimed at understanding how similarities in cognition emerge in evolutionarily distant taxa, like primates, elephants and corvids. One significant concern in the field is that fair comparisons require careful attention to species’ unique sensory perspectives. Here, I'll discuss some of our research over the past decade on elephant cognition, and will detail studies focused on the elephant's use of olfaction in the decision-making process. I’ll also discuss how we are applying our growing understanding of elephant behavior to the mitigation of human-elephant conflict in Thailand. Comparative cognition and animal behavior research have important roles to play in the conservation of endangered species.
Michael L. Anderson, Philosophy, University of Western Ontario
Neural Reuse, Dynamics, and Constraints: Getting Beyond Componential Mechanistic Explanation of Neural Function
This talk will review some of the evidence that structure-function relationships in the brain are complex, dynamic, and--most importantly--not adequately captured by the leading form of explanation in the neurosciences, componential mechanistic explanation (CME). In CME one identifies the spatial subparts of a system, discerns their functions, and determines how the parts are organized and interact to give rise to system-level function. However, in the brain neural sub-systems are not stable, function-determining interactions can be bottom up and also top-down, and function-relevant parts are not always spatial sub-parts of the system in question. In light of this, I will suggest that it would be more fruitful to look for the ways that function emerges from interacting structures via the imposition of enabling constraints, that temporary stabilize the system's configuration (i.e. enact a synergy) to achieve the cognitive or behavioural task at hand.
Parisa Moosavi, Philosophy, York University
On the Moral Psychology of Intelligent Machines
This talk examines the suitability of intelligent machines for learning to replicate moral judgment and behaviour in light of the objection that morality is uncodifiable. I appeal to the distinction between symbolic and connectionist representation to evaluate this objection. I argue that although the uncodifiability of morality would raise a problem for encoding morality by symbolic AI, it leaves room for the possibility of a connectionist representation. However, I also argue that even if connectionist AI can in principle replicate moral judgment, the problem of explainability in connectionist AI raises important challenges for replicating moral justification.
David Barner, Linguistics and Psychology, UC San Diego
Humans Create Abstract Symbols to Explain the Perceptual World
How do words and other symbolic forms get their meaning? One popular and intuitive solution to this problem appeals to simple associative learning: A word like "chair" gets its meaning from patterns of association between the word form and perceptual experiences with chairs in the world. A natural challenge to this idea, however, is that many symbols that humans use, whether linguistic or otherwise, are not only abstract, but also make distinctions that simply don't exist in the perceptual signal. For example, perceptual representations can't easily explain the nature of human representations of mental states, time, and number, inter alia. In my lab, we study this problem and how humans use symbolic representations to represent and explain a noisy perceptual world. In this talk, I will discuss one example of this work by focusing on numerical cognition. In particular, I will argue that only the very smallest number words (i.e., one, two, three) are learned by associating words with perceptual representations of number, and that the meanings of all larger numbers - which are infinite - are constructed via processes of inference that are defined over the structure of number words themselves, not perceptual representations of number. I provide evidence for this hypothesis using data from seven different languages, as well as from French-English and Spanish-English bilinguals.
Rami Gabriel Psychology, Columbia College Chicago
The Emotional Brain: The Affective Roots of Culture and Cognition
An affective approach to culture and cognition may hold the key to uniting findings across experimental psychology and, eventually, the Human Sciences. Many accounts of the human mind concentrate on the brain’s computational power yet for nearly 200 million years before humans developed a capacity to reason the emotional centers of the brain were running the show. To attain a clearer picture of the evolution of mind, we challenge the cognitivist and behaviorist paradigms in psychology by exploring how the emotional capacities that we share with other animals saturate every thought and perception. Many of the distinctive social and cultural behaviors of our species, including: bonding, social learning, hierarchy, decision-making, self-identity can be integrated if we use an affective approach. Even the roots of so much that makes us uniquely human—art, mythology, religion—can be traced to feelings of caring, longing, fear, loneliness, awe, rage, lust, and playfulness. An affective framework is developed through elaborations upon biological intentionality, an ecological model of social intelligence, and biocultural loops in the ontogeny of affective systems. Furthermore, we explain the evolution of imagination through its early manifestations in body grammar, dreams, and spatial cognition. Drawing from research in anthropology, we describe how affect is domesticated through social and cultural technologies like norms, ceremonies, and goods. Finally, we explore the spiritual emotions in how art, religion, and mythology create ecological niches for belief, commitment, and solidarity.
E.J. Green Philosophy, MIT
What Is Perceptual Constancy?
Perceptual constancy involves a type of sensory stability across change in the proximal stimulus for perception. Constancy has played a significant role in recent philosophy of perception. The phenomenon figures centrally in debates over direct realism, color ontology, and the minimal conditions for perceptual representation. Despite this, the philosophical literature lacks a systematic account of what constancy is. In this talk, I argue that an adequate account of perceptual constancy must distinguish it from three superficially similar but fundamentally distinct phenomena: mere sensory stability through change, stability through irrelevant change, and perceptual categorization of a distal dimension. Standard characterizations of constancy fall short in one or more of these respects. I develop an account of constancy that meets these challenges. The account has two parts: a theory of constancy mechanisms, and a theory of the conditions under which a constancy capacity is exercised. Finally, I exhibit some consequences of this account for the debate over whether constancy is a necessary condition for perceptual representation of the external world.
Kristin Andrews, Philosophy, York University
Can Animals Be Moral?
Recent research challenges the idea that adult humans are the only actors whose behavior is evaluable by other members of their group. Very young children, great apes, dolphins, and monkeys may also find some actions to be acceptable, and others not. Normative thinking, that is, seeing actions as right or wrong, is the foundation of morality, and the current science suggests these roots may run deep in the animal kingdom. To investigate normative thinking in other animals I present an account of animal social norms and show that there are four cognitive capacities involved in normative thinking: identification of agents; sensitivity to in-group/out-group differences, social learning of group traditions, and the conscious awareness of appropriateness. Drawing on comparative cognition and developmental psychology research, I show that these capacities of naïve normativity are part of typical human social cognitive practices and they are seen in other species; therefore, they are likely an ancient human cognitive endowment. Finally, I show that these capacities they are necessary for moral cognition from the framework of standard ethical theories.
Sep 12—Laura Niemi (Munk School, University of Toronto), Tracing the Process of Moral Judgment in Language and Cognition
When things go wrong, people ask questions like: “Who made it happen?” “Who was responsible?” and “Who is to blame?” In other words, they engage in a process of moral judgment that involves causal cognition. To what extent is this process permeated by people’s diverse values and ideological commitments; and, to what extent is it influenced by the language used to describe the event? This talk will cover findings from several studies combining individual differences measures with vignette-based experiments and psycholinguistics tasks. Collectively, the research demonstrates that values systematically map onto different patterns of causal attribution and language use. Studying morality through the lens of language brings precision to our understanding of the psychological underpinnings of diverse values, and also indicates that our understanding of language is incomplete without consideration of moral psychology.
Oct 3—Dale Stevens (Psychology, York University), Are Object Concepts Hardwired in the Brain?
Discrete parts of the human brain respond preferentially to very particular categories of objects. Moreover, the general organization of these “category-specialized” brain regions is remarkably similar across individuals. This is one of the most robust and oft replicated findings in the field of cognitive neuroscience, and it has sparked much controversy and debate regarding the fundamental nature of object concepts in the brain. Is this category-related organization innate/hardwired in the brain, or driven solely by external perceptual characteristics of objects, or something else? In this talk, I present recent evidence from my neuroimaging research demonstrating that while stable anatomical connectivity constrains the spatial topography of this category-related organization, malleable experience-driven "functional connectivity" among brain regions gives rise to category-specilazation.
Oct 24—Adam Pautz (Philosophy, Brown University), How Does Experience Represent the World?
Like many others, I think we should accept a representational theory of sensory consciousness: being conscious of the world is a matter of representing the world. Thus the hard problem of consciousness becomes the hard problem of representation. For example, how do electrical events in soggy grey matter enable us to represent bright orange pumpkins? The most popular answer (Armstrong, Dretske, Tye, Byrne and Hilbert, Hill) is that the sensible qualities (colors, smells, tastes, etc.) are "in the world" and the brain represents them by undergoing states that have the biological function of indicating them. In this talk, my primary aim is to develop some empirical arguments against this view. At the end, I will briefly motivate a radically different approach: a kind of internalist, non-reductive form representationalism.
NB: Pautz will be giving a companion talk the next day at the University of Toronto in which he will develop some quite different, more a priori arguments for a non-reductive, internalist theory of consciousness. The arguments will be founded on a series of novel thought-experiments.
Nov 7—Hayley Clatterbuck (Philosophy, University of Rochester), How Does Language Create New Concepts?
Compared to other species, humans seem to have an exceptional capacity for representing and learning abstract concepts. According to the “language-first hypothesis”, language – and not some antecedent change in our representational abilities – explains how we first gained these abilities and how individuals today learn new concepts. To test this hypothesis, I consider whether and how language can play this role, drawing on Carey’s bootstrapping account and several techniques from machine learning. Finally, I investigate whether associative mechanisms found in other species suffice for the kind of word learning that creates new abstract concepts.
CHAZ FIRESTONE (Psychology, Johns Hopkins University)
TAKING A MACHINE'S PERSPECTIVE
Friday, January 25, 2pm, BSB 163 (this is a joint talk with the Centre for Vision Research)
How similar is the human mind to the sophisticated machine-learning systems that mirror its performance? Convolutional Neural Networks (CNNs) have taken our field by storm, achieving human-level benchmarks in recognizing novel images and objects. These advances support transformative technologies such as autonomous vehicles and machine diagnosis, but beyond this they also serve as candidate models for the human mind itself -- not only in their output but perhaps even in their underlying mechanisms and principles. However, unlike humans, CNNs can be "fooled" by adversarial examples -- carefully crafted images that appear as nonsense patterns to humans but are recognized as familiar objects by machines, or that appear as one object to humans and a different object to machines. This seemingly extreme divergence between human and machine classification challenges the promise of these new advances, both as applied image-recognition systems and also as models of the human mind. Surprisingly, however, little work has empirically investigated human classification of such stimuli: Does human and machine performance fundamentally diverge? Or could humans engage in some “machine theory of mind” and predict the CNN’s preferred labels? Here, I’ll show how human and machine classification of adversarial stimuli are surprisingly related: I will present data showing that, across many prominent and diverse adversarial imagesets, human subjects can reliably identify the machine's preferred label over relevant foils, even for images described in the literature as "totally unrecognizable to human eyes". I suggest that human intuition may be a more reliable guide to machine (mis)classification than has typically been imagined, and explore the consequences of this result for minds and machines alike.
MAGGIE TOPLAK (Psychology, York University)
ASSESSING THE DEVELOPMENT OF COGNITIVE ABILITIES AND COGNITIVE BIASES
Wednesday, February 6, 12:30pm, Ross S421
Many cognitive abilities show a steady increase throughout childhood and adolescence. However, previous research has found that performance on some cognitive biases (such as heuristics and biases tasks) show improvement with age, but others do not. The developmental course of cognitive biases remains largely unknown. It is particularly challenging to identify suitable stimuli for the assessment of cognitive biases in developmental samples, given that these paradigms were originally developed using adult samples. In addition to the developmental suitability of these items, an additional challenge of using developmental samples is the rapid, parallel development of general cognitive abilities such as intellectual abilities and executive functions. In order to advance our understanding of the development of cognitive biases, we have examined their association with different indicators of cognitive sophistication. In our program of research, we have examined performance on cognitive abilities and cognitive biases cross-sectionally across different periods of development. We have also examined whether cognitive abilities and dispositional tendencies that support rational thinking are correlated with resistance to cognitive biases. Our work has demonstrated that children and youth who display resistance to cognitive biases tend to display higher cognitive abilities and tendencies toward actively open-minded thinking. Most recently, we have conducted a longitudinal follow-up of our original developmental sample to examine developmental trajectories of these measures. I will also report on the findings from a cohort-sequential longitudinal design of typically developing children and youth. Our sample spans the range from 8 to 20 years of age based on testing at three time points, each separated by three years. We estimated latent growth curve models to examine the developmental trajectories of resistance to cognitive biases, based on a composite measure including baserate sensitivity, ratio bias, belief bias syllogisms, resistance to framing and temporal discounting. We also estimated these models for intellectual abilities (verbal and nonverbal), executive functions (interference control and mental flexibility), and actively open-minded thinking (AOT). Together, our results provide further evidence for the development of resistance to cognitive biases and convergence with other indicators of cognitive sophistication. These results also highlight the role of individual differences for understanding how children and youth improve or fail to show improvement on resisting cognitive biases.
MUHAMMAD ALI KHALIDI (Philosophy, York University)
NEURAL CORRELATES WITHOUT REDUCTION: THE CASE OF THE CRITICAL PERIOD
Wednesday, February 27, 12:30pm, Ross S421
Researchers in the cognitive sciences often seek neural correlates of psychological constructs. In this talk, I argue that even when these correlates are discovered, they do not always lead to reductive outcomes. To this end, I examine the psychological construct of a critical period and briefly describe research identifying its neural correlates. Although the critical period is correlated with certain neural mechanisms, this does not imply that there is a reductionist relationship between this psychological construct and its neural correlates. Instead, this case study suggests that there may be many-to-many psychological-neural mappings, not just one-to-one or even one-to-many relations between psychological kinds and types of neural mechanisms.
STEVEN PIANTADOSI (Psychology, University of California Berkeley)
ALGORITHMIC INFERENCE AS THE BASIS OF HUMAN LEARNING
Wednesday, March 27, 12:30pm, Ross S421
I'll present an overview of my research that is aimed at understanding how human learners solve complex, structured learning problems. Recent theories of human learning have hypothesized that people can infer the algorithm or computation giving rise to the data they can observe. This approach shows promise in explaining human behavior across a variety of domains, including language learning, number acquisition, and conceptual development generally. It also allows the field to address even more basic questions about what types of knowledge might be "built in" for humans, and how children develop the rich systems of knowledge found in adults. I'll describe a series of studies on mathematical learning and cognitive development in children, US adults, and indigenous Amazonians, and describe families of computational models that we can use to capture the remarkable statistical inferences carried out by human learners.
Nov 03, 2017, at 3.30 pm
Geoffrey MacDonald (Psychology, University of Toronto)
Love is the Drug: Social Reward and Interpersonal Behaviour Regulation
Abstract: Although a general principle is that animals regulate behaviour based on avoiding punishments and approaching rewards, relationship science has largely focused on safety rather than reward motives. In this talk, I argue for the importance of reward in the regulation of interpersonal behaviour. The studies I will discuss show that people regret missing opportunities for social reward and pursue relationships that promise reward. My data suggest that social reward is mediated by the release of endogenous opioids reflecting its addictive qualities. Finally, I explore boundary conditions to the pursuit of reward such that individuals high in the fear of being single or attachment avoidance are less motivated by social rewards.
Time and location: 3.30-5.30 pm (Friday), Ross S 421
Oct 14 (Fri) with Philosophy: Sharon Street (NYU, Philosophy)
Meditation, Metaethics, and the View from Everywhere
Oct 19: Daphna Buchsbaum (UofT, Developmental Psychology)
How do you know that? Integrating Causal Knowledge and Learning from Others
We live in a causally complex world, where we must learn not only to predict the consequences of events (“the wind blowing could make that branch fall on me”), but also to act causally on the world ourselves (“pressing the remote control button turns on the TV”). How do children learn causal relationships, especially when the world presents them with sparse, ambiguous data or with multiple, conflicting sources of evidence? Social learning may be especially beneficial —with little expertise and few life experiences, children can quickly acquire large amounts of new information from other people without spending the time and effort to learn through trial-and-error. However, not all information from others is equally dependable. People can be ignorant, make mistakes, or give conflicting information. I will first present work suggesting that children are able to rationally combine multiple sources of information about which actions are causally necessary when deciding what to imitate, interpreting the same statistical evidence differently when it comes from a knowledgeable teacher versus a naïve demonstrator. I will next present research looking at how children and adults combine direct observation of probabilistic data with causal predictions provided by a social informant, and how this influences their future trust in that informant. Finally, I will present research looking at how people reconcile differences in opinion amongst multiple demonstrators, including how they balance the opinion of a majority against the quality of informants’ information. Throughout this work, I use computational probabilistic models to evaluate what learners with differing social assumptions should rationally infer from the social and statistical evidence they receive.
Oct 26: Chris Westbury, Cognitive Psychology, Linguistics
Beyond ‘takete’ and ‘maluma’: Using big data to understand sound symbolism
Sound symbolism is the phenomenon of extracting semantics from formal (orthographic and/or phonological) elements of a string. Köhler (1929/1947) famously showed that people were much more likely to associate the nonword ‘takete’ with a spiky shape and the nonword ‘maluma’ with a round shape than the other way around. Sapir (1929) showed that people were more likely to associated the string ‘mal’ than the string ‘mil' with large things. These findings have been much replicated: indeed, a large proportion of the sound symbolism literature (40% in a review of 99 studies) consists of follow-up studies to Köhler and Sapir. I will point out several limitations in the sound symbolism literature and present results from three recent studies that try to overcome these limitations by using ‘big data’ (experiments that use thousands of randomly-generated stimuli). The first two studies address an unusual question that turns out to have a surprisingly clear and simple answer: Why do people consistently find some nonword strings humourous? The third study characterizes sound symbolic effects in nearly two dozen semantic categories, including several for which no sound symbolism effects have ever been suggested. I will end by discussing several plausible reasons why sound symbolic effects exist, and what their existence suggests about human cognitive processing.
Paul Katsafanas (Boston, Philosophy): "Fanaticism and Sacred Values"
Luke Roelofs (Philosophy, Australian National University)
'Octopuses, split-brains, and the universe: how unified does consciousness have to be?'
Short abstract: Normal human consciousness is in many ways remarkably well-integrated; plausibly this is part of what leads us to think of each person as a single conscious subject. By contrast, the conscious goings-on in the universe as a whole are not similarly well-integrated; plausibly this is part of what leads us to think of them as not belonging to a single conscious subject. But what should we think about systems that seem to fall somewhere in between, displaying too much integration to be called simply many and too little to be called simply one? With an eye to two particular examples of such cases (cephalopods and callosotomy patients) I review some rival ways of thinking about this question, and consider how far we can retain the simplicity of the common-sense outlook.
Jacob Beck (Philosophy, York University)
‘Is sensory experience analog?’
Abstract: Back in the 1980s several philosophers argued, on broadly introspective and a priori grounds, that sensory experience is analog. In the ensuing years, these arguments have been forcefully criticized, leaving the thesis that sensory experience is analog in doubt. My talk will have two aims: to diagnose a common flaw in these past arguments that traces to their armchair methodology; and to begin to develop a new, and more empirically informed, argument for the same conclusion.
Lunch and refreshments will be provided at the talks.
Wednesday, November 18
Jennifer Steele (Psychology, York)
“How and When Do Children's Implicit Racial Biases Develop?”
Wednesday, December 02
Tim Bayne (Philosophy, University of Manchester and Western University)
"Can we Build a Consciousness Meter?
September 10, 2014
Otavio Bueno (Philosophy, University of Miami)
“What Does a Mathematical Proof Really Prove?” *
September 24, 2014
Joni Sasaki (Psychology, York University)
“The Cultural and Biological Shaping of Religion's Effects”
October 8, 2014
Tina Malti (Psychology, University of Toronto, Mississauga)
“Mind, Emotions, and Morality”
October 22, 2014
Serife Tekin (Philosophy, Daemen College)
“Against Grief Erosion: Incompatible Research and Clinical Interests in Psychiatric Taxonomy”
November 19, 2014
Laurence Harris (Psychology and CVR, York University)
“The Vestibular System and the Sense of Self”
Wednesday, January 28
Frank Russo (Psychology, Ryerson)
"Oscillatory Brain Dynamics Underlying the Perception of Pitch, Rhythm,
and Emotion in Music and Speech"
Friday, February 6*
Ernie Lepore (Philosophy and Cognitive Science, Rutgers)
"On the Perspective-Taking and Open-Endedness of Slurring"
Wednesday, February 25
Robert Foley (Philosophy, Western)
"Flexible Interaction as a Criterion for Consciousness"
The speaker series is held on Weds at 3:30 pm in Ross S 421, unless otherwise indicated.
* = Joint session with Philosophy Department Colloquium
September 18, 2013
Keith Schneider (Biology and Centre for Vision Research, York University)
"Visual Attention Affects our Decisions but not Perceptions"
October 16, 2013
Wayne Wu (Philosophy and Center for Neural Basis of Cognition, Carnegie Mellon University)
"What is Attention?"
January 31, 2014*
Robert McCauley (Philosophy, Emory University)
"The Cognitive Foundations of Science and Religion"
February 26, 2014
Steven Sloman (Psychology, Brown University)
"Explanation Fiends and Foes: Different Modes of Causal Reasoning"
March 12, 2014
Tina Malti (Psychology, University of Toronto - Mississauga)
"Mind, Emotions, and Morality" -- (Postponed due to weather)
* Joint with Philosophy Department Colloquium, scheduled for Friday instead of Wednesday.
September 19, 2012
John Heil (Philosophy, Washington University St Louis)
October 17, 2012
Adam Cohen (Psychology, Western)
“Theory of mind as a cognitive reflex”
November 7, 2012
Louise Barrett (Anthropology, Lethbridge)
“A little less representation, a little more action, please”
January 30, 2013
Rebecca Saxe (Neuroscience, MIT)
"The Happiness of Fish: Neural Mechanisms for Understanding Minds Unlike Your Own"
March 6, 2013
Hakob Barseghyan (Institute for History and Philosophy of Science, University of Toronto)
"A Descriptive Theory of Scientific Change"
April 5, 2013
Tyler Burge (Philosophy, UCLA)
"Perception: Origins of Mind"
January 11, 2013
Interdisciplinary Workshop - Animal Pain and Consciousness
Colin Allen (Department of Philosophy, University of Indiana)
Kristin Andrews (Department of Philosophy, York University)
Verena Gottschling (Department of Philosophy, York University)
Suzanne McDonald (Department of Psychology, York University)
Anne Russon (Department of Psychology, York University, Glendon)
Adam Shriver (The Rotman Institute of Philosophy, University of Western Ontario)