Psychology 196B: Research in Cognitive Science
Probabilistic Model of Social Commonsense
Faculty Sponsor: Gao, Tao
Department: Statistics; Communication; Psychology
Contact Name: Tao Gao
E-mail: tao.gao@stat.ucla.edu
Website: http://www.stat.ucla.edu/~taogao/
Description of Research Project:
My lab explores human social perception and cognition, with a special focus on aspects of human mind that can inspire the development of artificial intelligence that is communicative and trustworthy. Research in my lab is highly inter-disciplinary, drawing tools from cognitive science, statistics, artificial intelligence, and robotics. The goals of my lab are to (a) reveal the nature of human social commonsense through cognitive modeling and psychophysical experiments; (b) implement human-like social commonsense in artificial intelligence, so that it can seamlessly communicate to and collaborate with humans in safe and trustworthy ways.
Description of Student Responsibilities:
Students should be motivated to build computational models of human minds. Specific responsibilities include: (1) reading cognitive modeling papers and book chapters under my guidance; (2) implementing cognitive models with python; (3) designing and running human psychophysics experiments.
Dissection of nucleus accumbens and prefrontal cortex neural dynamics underlying social interactions
Faculty Sponsor: Peyman Golshani
Department: Neurology
Contact Name: Pingping Zhao
E-mail: ppzhaoion@gmail.com
Room Number: CHS-77100B
Description of Research Project:
This project is about circuit mechanism of social behavior. We're working on neural dynamics of nucleus accumbens (NAc) and its connected brain regions during social interaction (test mice interacting with conspecifics). Combined with different virus expressing calcium indicator GCaMP6f, we are using V3 miniscopes (UCLA Miniscope) to record neural activity in different brain regions when imaged mice are doing freely moving behavior test. Then we would process calcium images and extract neuronal activity. Behavioral movies will be analyzed using custom-written deep-learning based algorithms (DeepBehavior) that can track the position and orientation of each animal and quantitate interaction time, velocity and any other information we need. With the imaging data we collect, we are able to use decoder to predict animal behavior with high performance.
Description of Student Responsibilities:
We're looking for students to join the project. The main responsibilities include: 1 Image processing using Matlab or Python. 2 Use DeepBehavior to analyze behavior data. 3 Help writing/modifying code for different data analysis (ROC, PCA, TCA). 4 Work on decoder to predict animal behavior Qualification: Strong background in Matlab or Python programming Experience in data analysis Creative problem-solving skills A desire to apply for graduate school (not required) Have interest in Neuroscience.
Perceptual Learning: Teaching with Computers
Faculty Sponsor: Kellman, Philip
Department: Psychology - Cognitive Science
Contact Name: Everett Mettler
E-mail: mettler@ucla.edu
Room Number: 7574 and 2349
Phone: (310) 825-4202
Website: http://kellmanlab.psych.ucla.edu/
Description of Research Project:
How do learners get better at searching, organizing and interpreting their visual world? Do the same processes that underlie perception of movement in sport, discovery in art, facility with puzzles and other forms of visual expertise also underly such practical skills as fluency in mathematics or proficiency in medical diagnosis? The current study is concerned with basic research in perceptual learning and object recognition. In addition we attempt to isolate and train visual skills using computer software that dynamically adapts to a learner's mental state.
Description of Student Responsibilities:
Research assistants would help in the collection of data by running subjects at least 7 hours per week. Opportunities would be provided for assistants to collaborate in the generation of new experiments, analysis of data, and independent research. Experience with programming is a plus, but not required. Psych 120A or B are highly recommended.
Cognitive processes in language comprehension
Faculty Sponsor: Harris, Jesse
Department: Linguistics
Contact Name: Jesse Harris
E-mail: jharris@humnet.ucla.edu
Room Number: Campbell Hall 2226
Phone: https://jesseharris.netlify.com/
Description of Research Project:
Research in the Language Processing Lab addresses how adults interpret sentences using a variety of information sources during online sentence comprehension, using methods such as eye-tracking, pupillometry, self-paced reading, memory probe tasks, and other response time methods.
Description of Student Responsibilities:
Research assistants will help administer experiments to subjects using a wide range of methods, and should feel comfortable explaining experimental directions. They may also be asked to help create or review test stimuli, or annotate corpus materials, depending on experience. Depending on background and interest, assistants may also assist in data analysis. Students should have completed prior coursework in linguistics, and cognitive science or psychology.
Research in Behavioral Science, Behavioral Economics, and Judgment & Decision Making
Faculty Sponsor: Fox, Craig
Department: Psychology & Business (Anderson)
Contact Name: Megan Weber
E-mail: meweber13@gmail.com
Description of Research Project:
In our lab, we are investigating several different projects related to judgment, decision making, and human behavior. We take on political psychology (e.g., how people think about inequality), persuasion (e.g., tactics to convince people to adopt new behaviors), basic psychology (e.g., perceptions of uncertainty), and response to incentives (e.g., pay-for-performance in the context of non-profit organizations). We use a variety of methods in our work, including online and in-lab survey-based experiments, field studies, natural language processing, and eye-tracking devices.
Description of Student Responsibilities:
Students will be doing a variety of research-related tasks, from literature reviews to study design to study administration. Students should be extremely reliable, fast, and clear communicators, eager to take on challenges and solve them independently. We want RAs who are not only talented and fastidious but also passionate and intrigued by the cognitive process underneath human decision making. Students who are exceptionally hard working, organized, detail-oriented, curious, and thoughtful should apply. Those with extensive coding skills (especially in JavaScript) will be given preference.
Neural mechanisms of decision making
Faculty Sponsor: Wikenheiser, Andrew
Department: Psychology
Contact Name: Wikenheiser, Andrew
E-mail: amwikenheiser@psych.ucla.edu
Room Number: LSB 5833
Website: https://wikenheiserlab.psych.ucla.edu/
Description of Research Project:
Our lab is interested in understanding how the brain controls behavior. We approach this question by recording the electrical activity of neurons as subjects perform carefully-designed behavioral tasks, and electrophysiological techniques are augmented with optogenetics and computational analyses. Specifically, much of our work focuses on decision making tasks inspired by a wide-ranging set of models from psychology, neuroscience, economics, and ethology. Our primary focus is on how interactions between the hippocampus and cortical regions mediate these behaviors.
Description of Student Responsibilities:
Research assistants can contribute to a variety of projects currently underway in the lab. We have a several projects that revolve around designing, fabricating, and testing custom behavioral equipment that allow us to ask new experimental questions. This work involves learning to use CAD software to design and fabricate behavioral devices using in-house 3D printers. These projects will give students hands on experience with 3D printing and electronic sensor design for data collection in experimental settings. Completed behavioral devices will be validated experimentally, and then incorporated into new experiments that research assistants will help design and execute. We also interested in applying novel computational analyses to previously-collected data. This work will give students experience with state of the art deep neural network methods for analyzing behavioral and neural data. The results of these analyses will serve as preliminary data to aid the design of new experiments. Research assistants can help in the design and execution of new experiments that result from these exploratory data analysis projects.
Motor cortex network dynamics during skilled motor behavior
Faculty Sponsor: Arac, Ahmet
Department: Neurology
Contact Name: Ahmet Arac
E-mail: aarac@mednet.ucla.edu
Description of Research Project:
The primary goal of this research is to understand the relationship between learned behaviors and neuron activity in the M1 region of the cerebral cortex. We are interested in capturing the changes in neuron activity as the mouse increases skill in the learned motor behavior. The lab measures learned behaviors and neuron activity simultaneously using two separate observations. The learned behavior is observed through deep learning computer vision applications and is used to calculate kinematic movements of paws of the mice. Neuronal activity is recorded in-vivo using two-photon calcium imaging.
Description of Student Responsibilities:
The student research assistance will be responsible in conducting experiments, handling the mice, and fine-tuning deep learning neural networks for optimized computer vision applications. The assistance will aid in the process of training subjects for the experiments. The assistance must be comfortable or be willing to learn how to handle rodents as well as gone through the necessary animal and safety training mandated by UCLA. It is preferred that the assistant is familiar with machine learning methods as well as python programming to aid in the behavioral analysis.
Quantitative Research Collaboratory
Faculty Sponsor: Montoya, Amanda
Department: Psychology
Contact Name: Amanda Montoya
E-mail: qrclab@psych.ucla.edu
Room Number: LSB 5324
Phone: 3107945069
Website: http://akmontoya.com/QRClab
Description of Research Project:
The QRClab focuses on developing and evaluating statistical methods and research practices used to answer psychological research questions. We develop new statistical analyses to be used for testing questions of mediation, moderation, or moderated mediation with complex data structures. We review published research to understand current practices and develop new guidelines for research practice. We conduct qualitative and quantitative research to understand new publishing mechanisms, such as registered reports. We develop tools (e.g., R packages, SPSS and SAS macros) to help researchers implement new statistical methods.
Description of Student Responsibilities:
Students may contribute to these projects in multiple ways. For example, finding research articles with specific data structures or from specific domains. Conducting data analysis to demonstrate novel statistical methods or using specific tools. Quality testing of newly developed statistical tools in SPSS, SAS, or R. Literature searches and coding of academic papers to describe how they use certain statistical methods. Searching for useful or interesting datasets to be used in analysis. Students often come to the lab from a wide range of backgrounds, but the most important qualifications are an eagerness to learn, interest in quantitative psychology, and confidence in your analytical and mathematical skills. Students particularly interested in statistics and research methods are highly encouraged to apply.
To apply to the lab go to akmontoya.com/QRClab, download and complete the lab application, and email it to qrclab@psych.ucla.edu.
Adaptive Learning: Teaching with Computers
Faculty Sponsor: Kellman, Philip
Department: Psychology
Contact Name: Everett Mettler
E-mail: mettler@ucla.edu
Room Number: 7574 and 2349
Phone: (310) 825-4202
Website: http://kellmanlab.psych.ucla.edu
Description of Research Project:
Computer-based learning activities offer great potential to adapt the flow of learning events to optimize progress for each individual. Can adaptive learning algorithms that dynamically sequence learning items result in improved efficiency for factual learning and pattern recognition? The current study is concerned with basic research in adaptive learning and will examine if adaptive sequencing based on accuracy, speed, and retirement criteria, produce learning outcomes superior to traditional classroom methods.
Description of Student Responsibilities:
Research assistants would help in the collection of data by grading assessments, data entry, and general office work for at least 7 hours per week and will have the opportunity to participate in all aspects of research, including literature search, study design, experimental design, and data analysis. Experience with programming is a plus, but not required. Psych 120A&B are highly recommended.
Human action perception
Faculty Sponsor: Lu, Hongjing
Department: Psychology
Contact Name: Lu, Hongjing
E-mail: hongjing@ucla.edu
Room Number: 6552 Franz Hall
Phone: (310) 206-2587
Description of Research Project:
We are interested in how the visual system represents and identifies human action in a motion sequence. It is crucial to perceive and interpret human body movements to be able to interact with other people well. This research explores the underlying information use of visual input in a series of psychophysical experiments.
Description of Student Responsibilities:
Students will be involved in conducting experiments, data collection and organization. Students also have the opportunity to aid in the design of new experiments and the development of computational modeling. Students are encouraged to be involved in the new experiments for the preparation for the Psychology Undergraduate Research Conference (PURC) at UCLA.
Prior knowledge in high-level cognition
Faculty Sponsor: Lu, Hongjing
Department: Psychology
Contact Name: Lu, Hongjing
E-mail: hongjing@ucla.edu
Room Number: 6552 Franz Hall
Phone: (310) 2062587
Description of Research Project:
We study predictive, diagnostic and analogical reasoning from a computational perspective. We are especially interested in what prior knowledge humans assume in making an inference from few examples. Our research aims to develop computational models for a range of reasoning experiments, and assess the validity of computational models by comparing their predictions with human performance in controlled experiments.
Description of Student Responsibilities:
Students will be involved in conducting experiments, data collection and organization. Students also have the opportunity to aid in the design of new experiments and the development of computational modeling. Students are encouraged to be involved in the new experiments for the preparation for the Psychology Undergraduate Research Conference (PURC) at UCLA.
Visual Object Recognition
Faculty Sponsor: Liu, Zili
Department: Psychology-Cognitive
Contact Name: Dr. Zili Liu
E-mail: zili@psych.ucla.edu
Room Number: 7619 Franz
Phone: 310-267-4683
Description of Research Project:
This National Science Foundation sponsored research investigates how the brain encodes into memory visually perceived scenes and objects (e.g., faces). Counter-intuitive predictions, with promising pilot data, will be tested.
Description of Student Responsibilities:
Responsibilities include scheduling experiments on experimentrix, conducting the experiments, and debriefing the participant after each experiment.