Title: Healthy Aging and Quality of Life Research
Domain: Jennifer Holbein (Kinesiology)
Stats: Joe Roith
CIR Fellows: Will Brandt, Mandy Moran, Dhesel Khando
Description: With a rapidly aging global population and co-morbidities associated with social/health care costs, there is an urgent need to identify therapeutic solutions that could promote healthy aging and reduce chronic pain. The framework of human physiology research is of paramount importance: we take a person-centered focus on healthy aging and chronic pain and measure the impact of therapeutic interventions in underserved rural communities on function, social well-being, and quality of life. Our research focuses on community-dwelling adults in Northfield and other rural communities (Washington State and Montana) with the potential to empower adults to care for themselves with a maintenance or improvement of well-being by promoting strength, balance training, and chronic pain. This empowerment improves confidence, which in turn reduces long-term care costs.
On-going research will consist of analysis with our perturbation treadmill titled “Impact of the ActiveStep Perturbation Treadmill on Rural Community-Fall Prevention.” We have data from 20 individuals from last year that will need to be analyzed. In addition to this we will be: (1) recruiting and adding a control group that will then be compared to the intervention group. The control group will only be walking on the treadmill; (2) We will also be conducting a feasibility study with this intervention taking these same 20 individuals ages 65 and above and now will need to recruit and comparing them to 20 college aged individuals; (3) Lastly, there is also a spin off study where we are collaborating with the Psychology department analyzing neurological changes and cognitive sequencing. Cognitive sequencing is the brain’s ability to recognize and carry out actions in a particular order, and is the foundation of accomplishing tasks and goals. This pathway enhances a person’s ability to predict and anticipate different components associated with an action and we want to compare the sequencing taking place while on the perturbation treadmill and cognitive sequencing while using a judgment-based sequence learning task which required them to learn a full sequence by chaining together single stimulus–response associations in a step-by-step fashion. The individuals that already completed the treadmill study will be asked to come back and complete the judgment-based computer sequence learning task.
Title: Text Analysis of Political Rhetoric
Domain: Chris Chapp (Political Science)
Stats: Paul Roback
CIR Fellows: Anh Phan, Matthew Nissen, Maheen Asim
Description: CIR fellows will use a “text as data” approach to examine political polarization. Conceptually, “polarization” is typically treated as an attitudinal phenomena, however there are reasons to suspect that political polarization is also reflected in political rhetoric. We propose using a large corpus of text to measure the extent to which the parties are diverging in key policy areas. Specifically, we have scraped text from every House candidate website from 2008 — 2022. Website text is stored in separate .txt files, arranged by issue area (for example, a candidate’s position on abortion is stored separately from their position on taxes). In all, this adds up to about 55,000 unique issue statements over the years. We would like to use a combination of structural topic models and/or machine learning to measure policy divergence, policy extremity, and issue framing. The team is particularly interested in how Republicans and Democrats have changed (presumably, grown apart) over the years. Besides party, we suspect district political extremity, other district characteristics like race and income, candidate gender, candidate race, and incumbency status are all predictive of rhetorical choices. We have already collected many of these variables for 2008 – 22.
Title: Neural Activity within Magnetic Fields
Domain: Jay Demas (Physics)
Stats: Jaime Davila
CIR Fellows: Will Asinger, Rayan Elahi, Swagat Malla
Description: Many organisms have the ability to sense Earth’s magnetic field and use this sense for orientation and navigation. For example, a number of bird species have been shown to use an internal magnetic compass to navigate as they migrate long distances. However, the biophysical mechanism that detects magnetic fields and the neural circuits that process this information are a mystery. Recently, indirect evidence has accumulated to suggest that birds, including zebra finches, use a class of light sensitive proteins in their retinas called cryptochromes to “see” magnetic fields. If this hypothesis is true, then there must be output neurons from the retina that report information to the brain about the intensity and/or direction of low frequency magnetic fields.
Using multielectrode arrays, it is possible to record neural activity from tens to hundreds of neurons in the output layer of a living bird retina while also playing visual and magnetic stimuli. Armed with both the sensory inputs to a retina (spatiotemporal pattern of visual and magnetic stimuli) and recorded outputs from a retina (timestamps of neural impulses from dozens of individual neurons, also known as spike trains), CIR students will develop analyses to determine whether or not neuronal activity in any of the recorded neurons is consistently modulated by low-frequency magnetic fields. If so, they will also determine what information about magnetic fields is reliably encoded in this neural activity.
Title: Pathways, barriers and outcomes in Environmental Studies
Domain: Seth Binder (Environmental Studies)
Stats: Katie Ziegler-Graham
CIR Fellows: Katherine Musser, Paul Langois, Peter Fortier
Description: Nearly 1 in 10 members of the class of ‘23 graduated with either a major or concentration in Environmental Studies (ES). The major itself is one of the largest on campus. It serves a wide array of students with varying interests, experiences, competencies, and objectives. Majors choose one of three different areas of emphasis–arts and humanities, natural sciences, or social sciences. Each of those areas has a different set of requirements, many of which can be met in multiple ways. With many students, and many possible paths into (and ideally through) the major, it is both important and difficult to ascertain how students’ paths impact their persistence in, learning from, and experience of, the major. Key to such assessment is the ability to access and make sense of data pertaining to student pathways.
In this project, CIR fellows will work to wrangle and visualize data from IE&A on the sequences of courses that students take on their paths in/through the major. The product of that work will provide the basis for subsequent analysis. It will allow investigation into questions such as, “What fraction of pathways include coursework sufficient to meet all intended learning outcomes (ILOs) of the major and chosen emphasis?”, “Are there particular courses before or right after which students are more likely to transition out of the major or a given area of emphasis?”, “Does the timing or specific sequencing of particular sets of courses appear to drive differences in student outcomes (e.g., persistence, final GPA)?”, and more.
Title: Thermal Time Parameters for Milkweed Germination
Domain: Emily Mohl (Biology)
Stats: Laura Boehm Vock
CIR Fellows: Grace Kosieradzk, Sam Song, Mitch Ardolf
Description: Many people and organizations are planting milkweed because it is the only food source for the larvae of the declining populations of monarch butterflies. In order to make the best decisions, it’s important to know if populations of milkweed from different regions are adapted to their local environments, or if they perform about the same everywhere. Our research is designed to help us answer this question by collecting milkweed seeds from lots of different places and growing them under different conditions. We have recently conducted a germination experiment in which we took seeds from 10 different populations of milkweed and germinated them at 4 different temperatures, checking for germination daily. Our goal is to use these data to estimate thermal time parameters for germination for these different populations. Because development is temperature-dependent, thermal time refers to the number of “degree days” it takes for a developmental process, like germination, to happen. We also want to estimate the basal temperature for each population below which no germination can happen. We have observed that northern populations typically germinate faster, so we hypothesize that northern populations have lower basal temperatures or shorter degree day requirements. One of the things that is tricky about studying germination in milkweed seeds is that they are dormant, and they typically need to go through a period of cold stratification to break dormancy. We wanted to understand how dormancy affects the thermal time parameters, so we exposed all our seeds to different dormancy-breaking treatments as well. If we can estimate the thermal time parameters, then we can use them to estimate when seeds should germinate in field conditions and to predict how climate change is likely to affect germination. We have actual data from a field germination study that we can use to test our thermal time predictions.