Neuroscience Projects

Classification: Dry lab

Project Description: Previously the lab has developed a paradigm to look at the effect of positive and negative feedback on timing behaviors. Previous results implicated the dmPFC and insula in encoding these feedback effects in a mixed manner, but in looking at the mesoscale LFP. In some cases, we had microwires, enabling us to get the activity of single neurons in this task in various brain regions (Orbitofrontal Cortex, Hippocampus, Anterior Cingulate, Amygdala). This project will look at the single neuron responses during this task and compare this to the LFP responses on the micro and mesoscale, focusing on mPFC to investigate the presence of task-relevant information at various spatial scales. 

REP Student Main Contribution: 

The student will be using a semi-automatic spike sorter to recover single unit spike trains from individual runs of the experiment for different patients. In addition, the student will implement some basic regression models to look for single neuron coding to positive feedback, negative feedback, and RPE and see if different trends hold for different brain regions. If time allows, the student will use population decoding methods to see if these task variables are more easily recovered on the global scale than on a single neuron scale. 

Skills that you will learn:

1. Matlab (for spike sorting)

2. Statistics (Poisson GLMs, multiple comparison corrections)

3. Python coding (Handling Pandas dataframe and big numpy arrays using a server)

4. Neurobiology (Some neuroanatomy and basic understanding of how neurons transmit information)

Classification: Dry lab

Project Description: Our lab combines tools from neuroscience, psychology, and economics to better understand how people make decisions. This project will investigate behavioral, emotional, and neural responses to social evaluation. We are also interested in how these responses may be altered by social anxiety. This project will use fMRI, as well as computational models of emotional well-being.  

REP Student Main Contribution: Data Collection and Analysis

1. Main duties will include collecting human behavioral data during a social decision-making task. If there is interest from the student, they may also learn about analysis and modeling of the data.

Classification: Dry lab

Project Description: Can large language models (LLMs) like ChatGPT demonstrate human-like intelligence? Can we systematically and robustly evaluate the intelligence of LLMs like neuroscientists have done on humans and animals? Using a set of behavioral tasks that target broad cognitive abilities, we will evaluate LLMs to characterize their intelligence, providing a benchmark for future Al models and a deeper understanding of how artificial intelligence measures up to humans. 

REP Student Main Contribution: The student will participate in data collection, which includes generating prompts, querying LLMs, parsing outputs, and streamlining the process. Depending on the student’s background and interests, they may also help with data analysis, visualization, and computational cognitive modeling of LLM and human behavioral data. No prior experience is necessary. 

Classification: Wet lab

Project Description: In this project, we are going to study sleep disorders in a Parkinson's disease (PD) mouse model. Specifically, we will characterize specific sleep deficits and investigate alterations in substantia nigra pars reticulata (SNr) physiology, function and coupling to sleep circuits across different stages of PD. 

REP Student Main Contribution: Data Collection and Analysis

Student will be responsible for:

1. sleep data analysis

2. mouse brain dissection

3. immunohistochemistry 

4. fluorescence microscope imaging 

Classification: Wet lab

Project Description: Neural computations in sensory cortex occur rapidly within specific subnetworks and interact with cognitive signals in ways that remain unclear. Traditional neural imaging methods, lack the temporal resolution to capture fast neural activity changes. Genetically encoded voltage indicators (GEVIs) offer better resolution and can detect spiking activity and subthreshold potentials. This project has two main goals: First, to improve high-speed imaging of GEVIs using advanced optical and analysis methods. Second, to apply this method to study how sensory and cognitive signals interact in specific neural subtypes. 

REP Student Main Contribution: Data Collection and Analysis

The primary responsibilities of this project involve behavioral training of mice to study how deviant or unexpected stimuli are processed in different contexts. This involves operant conditioning training and adjustment of behavioral parameters to ensure mice achieve expert level performance on the task. Additionally, a critical part of these experiments is related to determining the anatomical location of the neurons that were imaged during the behavior. This involves performing histological staining on ex vivo brain tissue. There are also opportunities to learn analysis of behavioral and neural data. 

Classification: Wet lab

Project Description: Vision is not a passive process. Instead, visual areas at different levels dynamically communicate with each other to produce a coherent perception of the world. In this project, we leverage high-throughput NHP Neuropixels probes to record from multiple regions of the Inferior Temporal cortex simultaneously, capturing spiking data from hundreds of neurons at once. Our goal is to understand the feedforward and feedback computations among these brain areas while the animals perform specific visual tasks. Uncovering the principles governing these complex computations will offer exciting new insights into the mechanisms of robust object recognition. 

REP Student Main Contribution: Data Analysis (Old Data)

Student will be responsible for:

1 Fully understand the motivation of the project and the data structure.

2 Conduct analysis (using Python or Matlab) to explore the feedforward and feedback communication between the brain areas.

3 Develop ideas on any other analysis techniques to gain deeper insights from the data.

4 Organize and clean up the data for analysis.

5 Ensure that all code is well-organized and easily readable. 

Classification: Dry lab

Project Description: The key focus of our lab's research is exploring how the brain integrates somatosensory information to facilitate dexterous motor learning and motor execution. Our lab is developing novel behavioral tasks to delve into this complex process. This project involves testing these tasks in human participants to examine how somatosensory feedback is integrated into motor output during learning and execution of an object manipulation task. 

REP Student Main Contribution: Data Collection and Analysis

The student will participate in collecting human behavioral data during a somatosensory motor learning task. They will analyze behavioral data to assess for hallmarks of somatosensory-motor integration by developing and testing code in Python. Other responsibilities include attending lab meetings and journal clubs, and presenting their work to lab members 

Classification: Wet lab

Project Description: The project aims to elucidate mechanisms underlying psychedelic effects on stress-induced compulsivity. Stress disorders like PTSD are associated with compulsive behaviors, but the brain mechanisms linking stress exposure to compulsive behaviors, and the effects of psychedelics on them, are not well understood. I pursue the hypotheses that myelin plays a role in psychedelic effects on stress-induced behavior. This work illuminates myelin plasticity’s role in psychedelic effects on stress-induced behaviors, and provides insights on future therapeutic targets focusing on the reversibility of posttraumatic structural brain changes. 

REP Student Main Contribution: Data collection and analysis. 

Major student responsibilities include, slicing and cryo-preserving brain slices, immunohistochemistry and subsequent analysis of scanned images for fluorescence intensity. Other responsibilities include, assisting in collection of animal behavioral measures, assisting in brain collections, and assisting with statistical analyses of collected data. Students are expected to be proactive in their position, learn and perform techniques as taught, work with a team, and provide consistent communication with their supervisor. 

Classification: Wet lab

Project Description: This project aims to study the effect of stress on reproductive functions. Stress is known to negatively affect reproductive system. However, the central mechanisms on how stress interacts with reproductive system is not fully understood yet. This work will study how kisspeptin neurons, the major regulator of reproductive functions, respond to stress induction and possible connections between kisspeptin neurons and stress-related brain areas. 

REP Student Main Contribution: Data Collection and Analysis

Student will be responsible for assisting in transgenic mouse colony management, genotyping using PCR, mouse brain slicing using cryostat, immunohistochemistry, and analysis of scanned images to determine expression of proteins of interest. Students are expected to be involved in journal club to discuss scientific literatures related to the study. 

Classification: Wet lab

Project Description: Given some evidence that blood brain barrier dysfunction (BBBd) is involved in aging and Alzheimer’s disease, this project aims to elucidate the relationship BBBd and accumulation of amyloid-beta (Aβ) and tau, the hallmark proteins of AD. I will use two transgenic mouse models with either Aβ or tau mutations to individually examine how BBBd interacts with each protein to induce neuropathological changes. Behavioral assays and immunohistochemistry will be performed at multiple time points across the lifespan of the transgenic mice to determine whether BBBd is accelerated in the presence of Aβ or tau compared to wild-type mice. 

REP Student Main Contribution: Data collection and analysis. 

The student will help with running behavior experiments and immunohistochemistry assays (perfusion, tissue collection, tissue slicing, staining, mounting, and imaging). The student will also help with maintaining the mouse colony, including checking on breeding pairs and genotyping new pups. All of these tasks will be performed with a team that currently includes myself, a post-bac researcher, an incoming associate staff scientist, and an undergraduate volunteer. 

Classification: Wet lab

Project Description: Synaptic plasticity enables neural circuits to adjust the strength of synaptic connections between cells, refining circuit communication and behavior in response to changing inputs. Psychedelics induce plasticity in both humans and mice, and are currently in clinical trials to treat mood disorders like depression and anxiety. Our lab wants to understand the long-term effects of psychedelics on cellular biology and synaptic communication. We are looking for someone to investigate the effect of psychedelics on cellular mechanisms that can regulate synaptic plasticity.

REP Student Main Contribution: Data Collection and Analysis

The student's project will likely involve learning to independently perform immunohistochemistry and microscopy experiments (wet lab). Since the lab uses a mouse model, the student will be responsible for handling and maintaining mouse colonies (colony check ups, genotyping, etc). While the student is not expected to have prior experience working with mice, the student must be comfortable learning to work with mice in order to be successful in the lab. In addition to lab work, the student will be expected to attend lab meetings and learn to read primary literature on their research topic. The goal is to train the student to become independent in the lab, both experimentally and intellectually. 

Classification: Wet lab

Project Description: Magnetogenetics is a neuromodulatory technique that employs magnetic fields for noninvasive control of cellular activity. The lab has developed a method that employs endogenous ferritin, an iron storage protein found in most cells, to convert the applied magnetic fields into biochemical signals that can activate cells. This project will investigate how application of magnetic fields to cultured cells can alter their activity through calcium imaging experiments. 

REP Student Main Contribution: Data Collection and Analysis

Major student responsibilities include performing calcium imaging recordings and data analysis. Students are expected to maintain open communication with their mentor/supervisor, develop critical thinking skills, and gain a proficient understanding of the field and experimental motivations.

Classification: Wet Lab

Project Description: Optimization of the light-sensitive membrane protein channelrhodopsin for use as an optogenetic tool. We will utilize structures of these proteins to design mutants that will display optimal properties for use in optical in-vivo neuroscience experiments. 

REP Student Main Contribution: Model Development

Students will utilize knowledge from the literature and insights from protein structures to undertake selected mutagenesis of channelrhodopsins. Students will regularly utilize the techniques of cloning, transfections, and electrophysiology patch-clamp, as well as the fundamentals of data analysis and presentation. 

Classification: Dry lab

Project Description: In this project, we investigate the neural basis of cognition using intracranial recordings in humans while they perform tasks related to language, music, imagination and reward. We try to identify the features of the data that underlie these abilities, including neural oscillations and communication between brain regions.

REP Student Main Contribution: Data analysis. The student will analyze human intracranial EEG data recorded when people performed tasks related to music, language, memory and reward. Analyses include data cleaning, signal processing, statistics. The student will present the results in a lab meeting at the end of the internship.

Classification: Dry lab

Project Description: Lateral parietal cortex in mammalian brains has been strongly linked with domains of higher order cognition, including executive function, planning, and language. This project will investigate the structural evolution of lateral parietal cortex by examining MRI images of chimpanzees, macaques, and humans. Students will learn to reconstruct cortical surfaces from MRI images, extract and label features on the cortex, and then analyze their structure.

REP Student Main Contribution: Data collection and analysis. Students will be expected to work 10 hours per week with their mentor. The beginning of the project will including training in relevant domains of computing, including MRI post-processing, labeling surfaces, and using pre-written scripts to extract metrics for the cortices. After this, students will have a chance to complete their own analysis of the data they collect, and then learn to present the data for the poster session.

Classification: Dry lab

Project Description: We are interested in developing a notion of single biological neuron I/O transformation complexity. A developed notion of transformation complexity would allow us to classify neurons in a way that would further our understanding of the role of specific neuronal biophysical properties in cognition, as well as aid the development of neuromorphic technology.

REP Student Main Contribution: Model development. Your role would be to aid in the development and running of detailed neuron simulations. This work would mostly be done in Python. For those who have a strong background in math and statistical physics, there is room for aid in theory development. 

Classification: Dry lab

Project Description: Students will help in the development of a data analysis method to identify the presence of state feedback dynamics between co-recorded activity in multiple brain areas.

REP Student Main Contribution: Data analysis. Students will be developing and testing code in python. Responsibilities may include application of the method to neural datasets (macaque motor/somatosensory corticies and rodent hippocampus, mPFC) and testing correctness of methods in synthetically generated data.

Classification: Dry lab

Project Description: Developing and training a biologically-realistic spiking neural network that learns spatial-temporal receptive fields, on top of typical V1 simple cell receptive fields, from dynamic visual stimuli.

REP Student Main Contribution: Model development. The student will use existing Python code to replicate existing results and generate training data, write additional code to train different variants of networks, and develop metrics of analyses for probing these networks.

Classification: Dry lab

Project Description: Our laboratory studies vocal communication in animals and would like to develop an advanced machine learning-based automatic classifier for bird calls. This project seeks to implement supervised classification algorithms that will decode call type and caller id for vocalizations produced by zebra finches and canaries. The project will require a literature review of current methods of supervised classification of auditory stimuli, and implementation of the chosen algorithm, and evaluation of its effectiveness. This project will contribute to a better understanding into what acoustic features are important to decode semantic categories, as well as provide a useful tool for the field.

REP Student Main Contribution: Data analysis. This project will be largely led and executed by the REP student, with guidance from us. We expect the student to, in broad terms, (1) do a literature review on the different classification algorithms that could be implemented. (2) Justify a decision on one classification algorithm. (3) implement the classification algorithm on our recorded databank of calls. (4) evaluate the success of the algorithm on held out data. (5,optional) implement this algorithm into our lab’s sound analysis software.

Classification: Wet lab

Project Description: Our sensory perception is shaped by the integration of inputs from multiple points of the surrounding space. In the mouse model, we will probe the neural activity evoked by multi-whisker inputs within the primary (S1) and secondary (S2) somatosensory regions of the cerebral cortex during a tactile target detection task. Throughout task performance, responses to sensory stimulations will be recorded using a dense electrocorticography (ECOG) array, which offers a readout of individual and multiple whiskers’ cortical representation. Our objective is to relate electrophysiological characteristics of multi-whisker integration to the animal's performance in detecting these stimuli.

REP Student Main Contribution: Data Collection & Analysis. Student's primary responsibility will involve imaging brain slices using a microscope and processing these images to align electrophysiological signals with the anatomical boundaries of whisker-related structures in S1 (no prior experience required). Additionally, we offer the opportunity for the student to assist in electrophysiological recording sessions and analyze electrophysiological and behavioral data under supervision (prior coding experience is preferred but not required). The student is expected to actively engage in critical thinking about the experiments by reading scientific articles, attending meetings with the supervisor and other students, and demonstrating an interest and/or curiosity in the topic.

Classification: Dry lab

Project Description: All organisms have an internal sense of direction, called head direction, which is computed within neural circuits using information about body movement and external cues. Head direction in Drosophila is represented within the compass network, where Ring neurons represent visual features in the fly’s environment and directly shape head direction representation. Whole-cell patch clamp recordings (electrophysiology) have found that Ring neurons exhibit distinct firing patterns that include massive depolarizations referred to as bursts. The molecular and cellular mechanisms underlying Ring neuron bursts and how this unique firing property modulates information processing are unknown. Burst firing in mammalian neurons has been found to have various functions, including expanding stimuli encoding and facilitating synaptic plasticity. To begin to understand the functional significance of ring neuron bursts, work needs to be done to parameterize burst properties such as magnitude and duration. Developing a quantitative framework to analyze and categorize bursts will set the foundation for perturbation experiments to understand the molecular and cellular mechanisms underlying Ring neuron bursts.

REP Student Main Contribution: A student working on this project will be developing computational tools in Python to analyze electrophysiological data (i.e. voltage recordings). In addition to coding, students will meet regularly with the mentor to check-in with the progress of the project and conduct literature reviews to understand the project background. If interested, the student may also assist or shadow during aspects of the data collection process (patch clamp electrophysiology).

Classification: Wet lab

Project Description: All organisms have an internal sense of direction, called head direction, which is computed within neural circuits using information about body movement and external cues. Head direction in Drosophila is represented within the compass network, where visual information is relayed from the retina through a multi-synaptic pathway. Previously, activation of the TuBu neurons in the pathway have been shown to result in an excitatory response in the downstream Ring neurons when using calcium imaging. The electrophysiological response of Ring neurons to TuBu activation is unknown, but nevertheless important in understanding visual information processing relevant for spatial navigation. The expression patterns of the genetic tools needed for this experiment are not well characterized. Immunohistochemical analysis of the driver lines used for this experiment is needed to understand the precise connectivity between neurons.

REP Student Main Contribution: A student working on this project will perform immunohistochemistry on Drosophila brains. This entails maintaining fly stocks, making fly crosses, dissecting fly brains, processing fly brains with immunohistochemistry (fixing, staining), and finally imaging the brains using a confocal microscope. In addition to wet lab work, students will meet regularly with the mentor to check-in with the project and conduct literature reviews to understand the project background.