Hello! My name is Nicole Lalta. I'm currently a graduate student in the Behavioral and Neural science PhD program at Rutgers University-Newark.
I aspire to become a neuroscientist focused on understanding the underlying mechanisms of various mental health illnesses such as depression and addiction, and the interventions that can be used. I'm also working on an outreach initiative program focused on bias research within the science community.
Collect 30 participants with nicotine use disorder for a 3-session study. Analyze resting-state fMRI data for each participant for a personalized target to receive TMS. Compare effects of stimulation to three other fMRI targeting methods: diffusion-weighted imaging, cortical thickness, and task-based fMRI.
Comprehensive review and meta-analysis on how different categories of eye movements are dysregulated in schizophrenia patients, and the potential of using a specific category of eye movements as a diagnostic tool for schizophrenia.
Analyzed resting-state fMRI data of 30 participants using MATLAB, bash, and python scripting to create target regions for transcranial brain stimulation.
Assisted in the execution of research study about the cognitive traits that influence our behavior during the COVID-19 pandemic. Created a landing page for potential participants to read and sign up for the study. Marketed study to potential participants in the surrounding area and on online.
See projectCreated a website for informative content on science, health, technology, and research studies. Maintained and updated website periodically with new information. Created and executed a monthly newsletter.
As people learn over time, functional connectivity, or the communication between brain regions, can shift. In order to evaluate these changes in functional connectivity, our lab designed an experiment that utilized the functional magnetic resonance imaging (fMRI) and the electroencephalogram (EEG), which measure blood flow and electrical activity respectively. In this 8-hour experiment subjects gradually gain expertise in a novel multi-sensory logic task. After testing the stimuli and running a pilot study, we have run over 40 subjects. From these experiments, I studied the various components of fMRI and EEG data and how they are imperative to changes in functional connectivity. We expect the results to inform our understanding of how various brain regions interact and connections shift throughout the learning process.
See PosterThe objective of this project was to implement and validate an automated ICA approach by using a MATLAB script that correlated the IC time courses and EOG channel time courses over different thresholds. The automated approach was validated by comparing the overlap with classifications of the same ICA decomposition made manually by two humans, and by visualizing the effects of automated removal in signals of interest (event-related potentials or ERPs).
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