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Department of Psychology

Research and Innovation

Research Communities

Our faculty are integrated within several multi-departmental research communities.

Behavioral-Biomedical Interface Program

The Behavioral-Biomedical Interface Program integrates training in multiple laboratories throughout Epidemiology, Exercise Science, and Psychology. BBIP trains the next generation of behavioral scientists with respect to biomedical conceptual frameworks and methods applied to understanding, treating, and preventing adverse health conditions/disorders and promoting optimal health outcomes. BBIP students are trained in biological sciences, anatomy, and neuroscience in addition to doctoral training.

Faculty: Rose Booze, Steven Harrod, Pete Vento, and Charlie Mactutus


Institute for Mind and Brain

The Institute for Mind and Brain is an integrated research hub for scientists interested the structural and functional bases of higher cognitive processes in the human brain. The institute has research facilities for research involving performance measures, HD-EEG/ERP recording, EMG, Eye-Tracking and computer laboratories.

Faculty: Amit Almor, Rutvik Desai, Jessica Green, Sandra Kelly, Robin Morris, John Richards, Chris Rorden, Svetlana Shinkareva, Jennifer Vendemia, Doug Wedell


McCausland Center

The McCausland Center for Brain Imaging houses the Siemens 3-Tesla Magnetic Resonance Imaging System and supports the development and implementation of various MRI-related research paradigms.

Faculty: Amit Almor, Rutvik Desai, Jessica Green, Caitlin Hudac, John Richards, Chris Rorden, Svetlana Shinkareva, Jennifer Vendemia, Doug Wedell


High-Performance Research Computing

The Research Computing Center provides the USC community with access to high-performance computing systems, remote and collaborative visualization resources, data storage, user services & software packages, assistance with HPC code development, and opportunities for computational research collaborations. These resources allow researchers within the Cognitive and Neural Sciences concentration to conduct machine learning simulations, assess quantitative methodologies, analyze Neuroimaging data, and analyze large sample data sets.

Faculty: Rutvik Desai, Jessica Green, John Richards, Chris Rorden, Svetlana Shinkareva, and Jennifer Vendemia


Methodological Expertise

Our researchers utilize a converging lines of evidence approach which combines data from behavioral, psychophysiological, and brain measures to develop theoretical models of human cognition and behavior. Thus, we have extensive overlapping expertise in multiple technologies and methodolgies.

Rose Booze, Steven Harrod, Pete Vento, and Charlie Mactutus develop animal models to study human physiological and behavioral systems.

Amit Almor, Caitlin Hudac, John Richards, and Doug Wedell use eye-tracking, which is the process of measuring either the point of gaze or the motion of an eye relative to the head

Chris Rorden, Rutvik Desai, and Svetlana Shinkareva use machine learning, mathematical models based on training data to make predictions without explicit programing instructions, to solve problems ranging from basic neurophysiology to those within the field of computational neuroscience.

Amit Almor, Jessica Green, Caitlin Hudac, John Richards and Jennifer Vendemia use high-density electroencephalography and event-related potentials in their research. Electroencephalography involves measures of the electrical activity of the brain. Event-related potentials are electroencephalographic signals that are ime-locked to complex perceptual and cognitive processing of stimuli.

Chris Rorden, Jennifer Vendemia and John Richards use Diffusion Tensor Imaging is an MRI-based neuroimaging technique which makes it possible to estimate the location, orientation, and anisotropy of the brain's white matter tracts.

John Richards, Svetlana Shinkareva and Doug Wedell emply psychophysiological measures. John Richards specializes in heart rate variability, the variation in the time interval between heartbeats, while Svetlana Shinkareva and Doug Wedell study electrodermal responses.

Rutvik Desai, Caitlin Hudac, Chris Rorden, John Richards, Svetlana Shinkareva and Jennifer Vendemia use fMRI to study brain activations and connectivity during tasks, and resting state fMRI, to evaluate regional interactions and fluctuations that occur while individuals are not performing an explicit task.

Chris Rorden and Rutvik Desai use lesion-symptom mapping and connectome-symptom mapping to study effects of brain damage. In these methods, damage to specific regions or white matter connections of the brain are mapped to changes behavioral measures.

Rutvik Desai and Chris Rorden employ transcranial magnetic stimulation, a noninvasive procedure that uses magnetic fields to stimulate neuronal activity; as well as transcranial direct current stimulation, a form of neurostimulation that uses constant, low direct current delivered via electrodes on the head.

John Richards does inverse modeling of NIRS and fNIRS data.

Amit Almor, Jessica Green, Svetlana Shinkareva, Jennifer Vendemia, and Doug Wedell specialize in applications involving performance measures such as reaction time.


Innovation

Caitlin Hudac developed innovative methods for identifying cognitive substages by incorporating single-trial approaches of dynamic learning that is integrated across methodologies (e.g., simultaneous eye tracking and  EEG/ERP).

John Richards created the Neurodevelopmental MRI database, a database of MRI average templates for individuals from 2 weeks to 89 years old and includes average MRIs and associated MRI volumes for developmental MRI work. It consists of average MRI templates, segmented partial volume estimate volumes for GM, WM, T2W-derived CSF. In addition, the database is separated into head-based and brain-based averages included with tools for cortical source analysis of EEG and ERP. These tools are based on the average MRI templates, segmenting, and atlases.

Chris Rorden has developed packages for the analysis and presentation of MRI, DTI, transcranial direct stimulation. Researchers widely employ his tools.

Jennifer Vendemia’s work includes the development and measurement of tactor devices, as well as specialized movement sensors to measure proprioceptive feedback in an MRI environment.

 

 


Challenge the conventional. Create the exceptional. No Limits.

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