Could you imagine that a computer program can infer the nutritional content of some food item from reading articles on related topics? How about an algorithm that can give medical diagnoses based on radiological images? Although these abilities sound like science fiction, they are becoming closer to reality thanks to the recent integration of computer science and cognitive science. In cognitive science, plenty of cognitive models have been established and developed over decades to explain and describe human cognitive processes in a computational language. However, despite their exceptional explanatory power, cognitive-process models suffer from a major limitation: almost all cognitive experiments are done in a lab setting where participants are asked to interact with visually simplified stimuli on a computer screen. For example, they could be asked to categorize a bunch of shaded squares varying in size and darkness. However, limiting cognitive research to only artificial stimuli raises the question of whether the same findings about human cognition still hold true for real-life situations. Thanks to the advancement of computer science, there is now a potential solution to this problem. (more…)
This post was written by Tongyao Zhang.
Have you – at least for a moment – ever imagined throwing your smartphone out the window, especially when you are trying to focus on your work? Now you might have a justification for your impulse. Behavioral scientists recently found that if your smartphone is merely present in your room, and even if you are not consciously thinking of it, you may still be distracted and lose access to part of your intelligence. (more…)
Conscious or not, we are faced with countless categorization decisions during our everyday lives. When organizing kids’ rooms, parents need to decide if various items are tools or toys, to know in which drawer to place them. On a visit to the pet store, visitors can take pleasure in the activity of identifying various pets they see as cats or dogs. In geometry classes, students are taught how to tell squares apart from rectangles. No matter how fast and intuitive some categorizations may feel, the process of making any classification decision involves a chain of cognitive steps. Although the exact cognitive processes are different for everyone, the decision to categorize something ultimately comes down to comparing a handful of features or characteristics of different categories to find the one in which the object fits. For example, when asked how to distinguish between cats and dogs, some people may say that cats tend to have longer, fluffy tails whereas dogs have shorter, stiff tails. Psychologists believe that features as such, whether quantitative (e.g., tail length) or qualitative (e.g., presence of dense fur on the tail), underlines how the human mind categorizes various natural objects. (more…)
The drive to reproduce has led to many of the flashiest traits observed in nature. For instance, male deer use antlers to fight one another for access to female mates, while male peacocks display their extravagant tails to impress peahens. These are examples of sexually selected traits, or traits that increase reproductive success. Sexually selected traits evolve because they increase “fitness”. In other words, specific traits cause organisms to produce more offspring in the next generation–these offspring inherit the sexually selected traits from their parents, causing the traits to continue rising in frequency with each subsequent generation. While the traits themselves are often flashy, perhaps the most extreme example of a sexually selected trait comes from an inconspicuous source. Drosophila, a class of insects colloquially referred to as fruit flies, appear unassuming on the outside, but produce the largest sperm in the animal kingdom. For context, human sperm is roughly 60 micrometers long, which is close to 1000th of a centimeter (obviously, a very small fraction of a human’s body size). Drosophila melanogaster, the fly species famous for its frequent use in biological research, has roughly 2,000 micrometer long sperm—1/5 of a centimeter, and approximately half the fly’s body size. Finally, and most incredibly, the species Drosophila bifurca produces the longest sperm cells of any known organism at nearly 6 centimeters long—over 20 times the length of their body! (more…)
Have you ever had times when you meant to provide others with constructive criticism but ended up hurting their feelings, or other times when your heart sank after hearing others’ well-intentioned remarks? As a Chinese student wading through the American waters of unfamiliar emotions and sensitivities, this happens all too often in my daily life. When I was grading a student’s writing as a teaching assistant, I thought something they had written was boring and left a comment that conveyed my thoughts about the quality of their work clearly. Later, the student complained to the instructor that I was being too harsh in my feedback. For me, honest, negative comments were a way of helping them to acknowledge the shortcomings in their knowledge and I assumed that they would naturally interpret my comment in a positive light. But based on my experience, in American culture, it is more important to spare the feelings of the student than to reveal the true feelings of the instructor. (more…)
Our brain is constantly keeping track of the experience of our body in the environment, enabling us to determine where we are, how we feel, and respond appropriately. How does this work? Let’s find out!
Researchers parse the experience of our body into three domains: exteroception, proprioception, and interoception. Are you familiar with these terms? What type of information do each of these domains contribute to the experience of the body in the image below?
In my last post, I explained the defining characteristics of cognitive models and the main steps to developing a cognitive model. In this post, I’ll discuss the advantages of cognitive modeling over alternative approaches to studying human cognition and behavior, and a precaution to be taken about interpreting modeling results. As in my last post, I will illustrate my points in the context of two competing models of human categorization mechanisms. According to the prototype model of categorization, learners abstract and memorize a single summary representation, namely the prototype for each category from all examples already learned in that category. When a new probe item is presented, the similarity of this probe to each category prototype is evaluated, and the category with the most similar prototype is chosen. For example, a prototype-based view on how people categorize a novel-looking pet as a cat or dog would be that the learner first abstracts the mental images of typical dog and cat faces by morphing all the salient features for both types of the pets. Then the learner makes the categorization decision by evaluating the relative similarity of the face of the new pet to the two typical faces. In contrast, the exemplar model of categorization specifies that learned examples from all categories were memorized, and the new probe item is classified into the category whose constituent examples are, in sum, most similar to the probe. So, in the example of dog vs. cat categorization, the exemplar-based view would be that the learner makes the categorization decision by comparing the overall similarity of the new pet face to the individual faces for both dogs and cats one has seen.
This post was written by Nathan Roden.
If you ask almost any kid today how the dinosaurs died, they’ll tell you an asteroid killed them, but this didn’t used to be the leading theory. When you look at key papers about the asteroid impact the kids are referring to, you’ll learn that it defined the transition from the Cretaceous to the Paleogene (K-Pg) boundary ~66 million years ago. Before the discovery of the asteroid, there wasn’t a single agreed upon theory on what caused the 5th global mass extinction. Not only did this mass extinction kill off the dinosaurs, but it also allowed the age of the mammals to begin. But how did scientists theorize about the 5th mass extinction before the asteroid discovery? (more…)
If you’ve ever thought about the life of a graduate student in psychology, you might have pictured someone who is asking research participants probing questions about their hidden thoughts, or perhaps someone who is discreetly observing human subjects completing some tasks while taking quick note of their behavior. In reality, we psychology students spend most of our time learning advanced statistical methods and grappling with quantitative analyses of noisy behavioral data that are difficult to interpret. People not familiar with the norms of the field often find it surprising that mathematics plays a central role in psychological research, as they tend to believe that mathematics is more useful for studying natural sciences that are objective and quantifiable, such as physics, than for studying behavioral sciences that are subjective and not amenable to measurement, such as psychology. In fact, psychology can be just as mathematically rigorous as any of the natural sciences, and the use of mathematical tools is vital to gaining a deeper, precise, and more confident understanding of the human mind as compared to – on the other extreme – armchair psychology that oftentimes leads to wishy-washy interpretations of how humans think. Over the past few decades, major theoretical journals in all subfields of psychology have seen a proliferation of research involving cognitive modeling, which is the formalization of human thinking in terms of mathematical, information-processing language. In this part of the two-part series, I’ll introduce the concept of cognitive modeling and explain the differences between cognitive, conceptual, and statistical models. (more…)
Achieving full inclusion for people with disabilities in science, technology, engineering, arts, and mathematics – STEAM – has become a global matter. People with disabilities in STEAM are underrepresented in postsecondary academic environments and the job market. The police killing of George Floyd, an unarmed Black man, in Minneapolis, Minnesota, on May 25th, 2020, was in many ways a catalyst for the global recognition of the need for greater inclusivity. Since then, universities, departments, and individual faculty members have become increasingly committed to improving diversity, inclusivity, and equity (DEI) in academia. (more…)