Ming Hsu, Professor

Closed (1) Neuroeconomics: Decision-Making and the Brain

Applications for fall 2021 are now closed for this project.

Our lab is interested in how the brain computes and represents values that allow us to make decisions. These decisions range from the mundane and everyday, such as what to have for lunch, to truly momentous ones such as deciding on where to attend college.

This project, and others in our lab, will confront participants with hypothetical and incentivized (i.e., paid!) choice problems. These behavioral experiments will be combined with neural measures (e.g. functional MRI scans, positron emission tomography, or electrocorticography) on participants to identify the brain regions and functions involved in different types of decisions. Subsequently, we will conduct followup studies to test how behavior is affected when the particular neural circuits are disrupted.

Student researchers will be exposed to cutting-edge research integrating mathematical models and biological measures of behavior. The specific role of the student will be tailored to the strengths and interests of the student, including designing experiments, engaging in data collection and data analysis, and assisting in writing research manuscripts.

Qualifications: Required: Demonstrated interest in human behavior. Desirable: sophomores or juniors, computer and programming skills

Weekly Hours: to be negotiated

Off-Campus Research Site: Due to the Covid-19 pandemic, some or all research work will be performed remotely.

Related website: http://neuroecon.berkeley.edu

Closed (2) Developing mindset metrics with big data: business and societal applications

Applications for fall 2021 are now closed for this project.

Recent advances in artificial intelligence and machine learning have made it possible to uncover subtle patterns and hidden trends in large-scale real-world data. They offer researchers and practitioners powerful tools to efficiently derive novel insights and predictions that are otherwise expensive or even impossible to obtain. Among the most exciting of these recent advances is reverse-engineering the human mind and, in parallel, engineering more humanlike machine learning systems, which has begun to help us address some of the most challenging questions about the nature and origins of human thought, knowledge, and biases.

This research project aims to develop and apply cutting-edge data science, especially natural language processing, techniques for challenging problems about human mind and behavior. Student researchers will be exposed to cutting-edge research at the intersection of natural language processing and computational social sciences, with the unique opportunity of validating data-driven insights with empirical data of human behavior. Students will explore new applications and extensions of these models, with applications spanning diverse fields and disciplines, including psychology, economics, neuroscience, and marketing.

Specifically, student researchers will be trained to (1) mine online content ranging from news media, social media, and social networks, (2) develop computational models that utilize semantic relationship embodied by real-world text corpora to capture cognitive processes, and (3) combine these models with computational social science models to predict real-world and laboratory behavior and outcomes.

Qualifications: Required: Strong computational and programming skills, interest in computational social science. Desirable, but not essential: Experience with natural language processing and text analysis

Weekly Hours: to be negotiated

Off-Campus Research Site: Due to the Covid-19 pandemic, the research work will be performed remotely.

Related website: http://neuroecon.berkeley.edu

Closed (3) Understanding effects of early-life adversity on decision-making

Applications for fall 2021 are now closed for this project.

We are looking for 1-2 student trainees who are interested in understanding the effects of early-life adversity/stress on economic and financial decision-making.  Despite the well-documented fact of the impact of early-life adversity on life-outcomes, researchers and policymakers know much less about the specific ways in which early-life adversity influences the type of behaviors (e.g., how much money to save?  What type of career options to pursue?) leading to outcomes such as wealth acquisition and education attainment.

This project will seek to improve our understanding of these processes. Results from the study can have important implications for science and policies surrounding early-life experiences.  Trainees will be jointly supervised by Prof. Ming Hsu and Prof. Ulrike Malmendier, and can expect extensive collaboration with other students throughout the week depending on the specific task involved.

The project requires that students have interest in learning and engaging with research in the following areas, as well as a good background in one or more:

- Stress: Both physiological and psychological aspects, and especially those occurring prior to adulthood.
- Systems neuroscience: Especially mechanisms underlying memory, affective, stress responses.
- Hormones and behavior
- Human behavior and economic decision-making

The ideal applicant should be interested in interdisciplinary research, collaborative work, and be excited by challenges associated with scientific research.

The specific duties include:

- Conduct literature review: This will focus on linking what is known in the biological literature on stress with the economic literature on long-term effects of past experiences.
- Participate in experimental design and developing research hypotheses: Trainees will learn to apply measures and techniques from laboratory studies on memory and stress to economic research samples and longer-run studies.
- Assist in data collection and analysis: Trainees will assist in the construction of data sets, cleaning of data, as well as basic data analysis.
- Communication and meetings: There will be a weekly meeting where trainees will report to a team of faculty and graduate students.

Qualifications: Required: Must have extensive knowledge of stress/endocrinology. Please include in your application relevant coursework (such as one or more of the following) as well as other relevant research experiences. - INTEGBI 137 Human Endocrinology - INTEGBI 138 Comparative Endocrinology - INTEGBI 139 The Neurobiology of Stress - PSYCH C116 Hormones and Behavior Desirable: Some background in human behavior/decision-making is desirable but not required. Please include in your application any relevant coursework (such as one or more of the following) as well as other relevant research experiences. - PSYCH C115C Neuroethology - ECON 101a Microeconomics (or ECON 100) - ECON 141 or other relevant statistics courses

Weekly Hours: to be negotiated

Off-Campus Research Site: Due to the Covid-19 pandemic, the research work will be performed remotely.

Related website: http://neuroecon.berkeley.edu
Related website: https://behavioral.berkeley.edu

Closed (4) How we experience music and why it matters

Applications for fall 2021 are now closed for this project.

This project will apply neuroscientific tools and insights to address a problem that has bedeviled businesses, legal scholars, and policymakers—how to more objectively determine whether a work of art is "based on plagiarism" or is "obscene". In music copyright, for example, a key question is whether two works are "substantially similar" according to some group of "ordinary listeners". However, questions of what substantially similar means, or who the ordinary listeners are, are left almost entirely to the discretion of the judge or jury.

In this project we are building on some of our past work to develop a brain-based measure of similarity between musical works. Crucially, we will compare works from historic copyright disputes involving well known artists, such as Queen, Vanilla Ice, Marvin Gaye, and Pharrell. Ultimately, this work has potentially both academic and commercial interest: it will (1) make novel contributions to the burgeoning field of Neurolaw and (2) provide legal practitioners with a new, potent form of evidence in copyright infringement litigation.

Apprentices will gain exposure and experience to cutting-edge research of human cognition and neuroscientific applications to law by assisting on multiple aspects of conducting experiments using electroencephalography (EEG).

Duties will include:
(1) Participant recruitment
(2) EEG data collection and quality assurance
(3) Analysis of behavioral and neural data

Qualifications: Must have: Interest in cognitive neuroscience, law (especially intellectual property), or the intersection of the two. Desirable: Previous experience running behavioral or neuroscientific studies with human subjects, familiarity with statistical software (eg. R or MATLAB) and analysis, knowledge of music composition or copyright law.

Weekly Hours: to be negotiated