The CT Institute for the Brain and Cognitive Sciences (IBaCS) offers IBACS-BIRC Research Assistantships in Neuroimaging (IBRAiN). After formal training, IBRAiN fellows provide a teaching resource to help BIRC users design and implement experimental procedures for fMRI, EEG, TMS and other methodologies, provide resources for data analysis, and oversee use of equipment by others. IBRAiN service to BIRC users is intended to be focused on educating BIRC users, rather than deliverable results. Click here for information about the scope of IBRAiN activities and associated policy. Click here for more information about applying to this program.
IBRAiN fellows hold weekly office hours to help users with their projects and provide short tutorials. Click here to request an appointment with an IBRAiN fellow.
Research Interests: The brain activates and represents meaning in complex ways. At a cognitive level, we deal with meaning using concepts which help to guide action and predict outcomes over a wide range of contexts. My research uses fMRI to examine the functional and structural connectivity underlying concept networks, representationally and as they develop in learning, as well as electrophysiology to examine activation dynamics.
Research Interests: I am interested in the cognitive and neural mechanisms underlying spoken word recognition, particularly regarding how top-down (e.g., attention, context) and bottom-up (e.g., speech signal, noise) information interact to determine speech perception. I would like to utilize simultaneous fMRI and EEG to tap into the feedback and feedforward mechanisms in speech. I’m experienced with collecting and analyzing fMRI data with various experimental designs and analysis approaches (e.g., ANOVA, functional connectivity, correlation analysis, ROI, DTI). I’m honored to be part of the IBRAIN training program to advance my neuroimaging skills and to assist IBACS in providing the technical, intellectual, and educational support to the UConn research community.
In collaboration with the BrainScope study, I aim to conjoin rs-MRI and DTI results to develop a machine learning algorithm to classify mild traumatic brain injury from no injury; this algorithm will distinguish recently concussed athletes from matched controls.
Research Interests: My research looks at how episodic and semantic memory systems interact during sentence comprehension. Specifically, I am interested in the neural underpinnings of representing object tokens in their different states. The use of simultaneous EEG + fMRI recording will allow me to track the time course of instantiating, maintaining and retrieving the representations of object token-states as the sentence unfolds, as well as identify neural pathways supporting the above mentioned processes.
Research Interests: My research focuses on how our memories, actions, and our cognitive system mutually influence our behavior, goals, and understanding of the world in the moment and across time. Successful goal directed action requires us to individuate objects we interact with and track them through time. What we remember about the objects and how we interact with them in the present moment could be shaped by our memory from previous experiences and our goals – both of which are constantly in flux as our environment and our internal states change. My research uses fMRI to investigate how these memories, goals, and perceptions influence changes in the developing cognitive system that manifest as differential patterns of task-dependent and resting state functional connectivity.
Research Interests: My research focuses on identifying the cerebellar mechanisms of essential tremor, one of the most prevalent movement disorders in the world, through computational modeling. Along this line of research, I am now exploring alternative targets of deep brain stimulation for essential tremor, and my eventual goal is to develop effective noninvasive neurostimulation protocols, such as tDCS and TMS, to treat the disease.
Research Interests: My research utilizes a variety of neuroimaging methods, including fMRI, resting state connectivity (rsfMRI), diffusion tensor imaging (DTI), and magnetic resonance spectroscopy (MRS), to examine the neural correlates of perceptual abnormalities and cognitive deficits in patients with schizophrenia. Specifically, I am interested in understanding the neurodevelopmental mechanisms by which pathophysiology in the hippocampus and prefrontal cortex confer increased risk for psychosis during adolescence/early adulthood. Through such approaches, my research aims to identify promising new targets for disease prevention and treatment.
Research Interests: I primarily study poor comprehenders, individuals who have poor reading comprehension despite intact decoding ability. In the past, I’ve used fMRI to determine that poor comprehenders show atypical activation across modalities and processing levels. My current research interest involves using fMRI to determine what may be contributing to the deficit in concept and category learning that I’ve observed in this population.