LBCN Lab Members
Josef received his MD from the University of Oslo and PhD in neurosciences from the University of Iowa. He completed his medical internship at Mayo Clinic and Neurology Residency at BIDMC-Harvard before joining the UCLA for fellowship training in Clinical Epilepsy and Neurophysiology. He moved to Stanford University in July 2007 and started the Human Intracranial Cognitive Electrophysiology Program (SHICEP). His research is now supported by NIH, Stanford NeuroVentures Program, National Science Foundation, and Stanford School of Medicine. Josef's expertise is in functional mapping of the human brain using the three methods of electrocorticography, electrical brain stimulation, and functional imaging.
Aaron Kucyi PhD
Aaron completed a PhD in neuroscience at the University of Toronto in 2014 where he studied pain perception, attention, and spontaneous brain activity. As a postdoctoral fellow at Harvard Medical School (2014-2016), his research demonstrated how the brain's default mode network (DMN) is simultaneously engaged with both mind-wandering and with unconscious fluctuations of attention. Aaron holds a Banting Fellowship from the Canadian Institutes of Health Research for his research at the LBCN. His current work with ECoG and electrical brain stimulation focuses on the neural network dynamics of spontaneous cognition and the causal role of the DMN in experience and behavior.
Jennifer Yih PhD
Jennifer joined the lab in 2016 upon completing her PhD with Craig Smith at Vanderbilt University. In her graduate research, she used behavioral methods to understand how negative and positive emotions influence attention, motivation, and behavior. As a postdoc, she is using intracranial electrophysiological recordings in human patients and psychophysiological recordings in healthy controls to study the effects of emotional reactivity and emotion regulation on perception and behavior.
Jessica Schrouff PhD
Jessica obtained her PhD in Applied Sciences at the University of Liège – Belgium in 2013. Her thesis investigated the application of machine learning models to neuroimaging data, tackling the challenging issue of decoding spontaneous brain activity and evaluating the potential utility of multivariate methods as computer-aided diagnostic tools. More recently, she was involved in the design of PRoNTo (Pattern Recognition for Neuroimaging Toolbox), a freely available Matlab toolbox to perform machine learning modeling of neuroimaging data. She is the recipient of Belgian American Educational Foundation - Henri Benedictus Fellowship, and is studying patterns of spontaneous intracranial brain activity.
Amy Daitch PhD
Amy received her bachelor from MIT and her PhD in Biomedical Engineering from Washington University in St. Louis in 2014. As a graduate student in Maurizio Corbetta's lab, her research focused on the oscillatory dynamics of visuospatial attention in humans using ECoG. As a postdoc, she is studying the dynamics within and between two brain regions involved in numerical cognition. She also plans to use a combination of ECoG and electrical brain stimulation to study the interaction between normally opposing brain networks (e.g. those involved in externally- versus internally-oriented attention).
Kieran Fox PhD
Kieran completed his PhD in cognitive neuroscience at the University of British Columbia (Vancouver) in 2016. His research focused on investigating the neural correlates of meditation, metacognition, and mind-wandering using a mix of functional (fMRI) and morphometric (DTI) neuroimaging methods. He also spearheaded several statistical meta-analyses assessing the rigor and replicability of cognitive neuroimaging data. He joined the LBCN in 2017 to pursue these lines of research using intracranial electrophysiological recording and stimulation in humans, with a focus on the role of the hippocampus and medial temporal lobe in generating thoughts and memories.
Pedro Pinheiro-Chagas , PhD
Pedro completed his PhD in cognitive neuroscience at Sorbonne University (Paris) under the direction of Stanislas Dehaene. His work focused on characterizing the processing stages of arithmetic calculations, using continuous behavioral measures (e.g. trajtracker.com) and machine learning applied to MEG signals. As a postdoc at LBCN, Pedro will combine intracranial electrophysiological recordings and electrical brain stimulation to study the neural architecture and dynamics of the brain networks engaged in elementary mathematical reasoning.
International Visiting Scholars
Ying is a PhD student with a major in psychology at South China Normal University. During her graduate studies, she used behavioral and fMRI methods to investigate how top-down attention influence the direction of visual and auditory sensory dominance. She joined the LBCN in 2018 as a visiting student, and she is now using intracranial electrophysiological recordings in human patients to study the dynamics, the functional architecture, and connectivity of visual and auditory sensory dominance within the brain.
So Ri Baek BSc
Sori received a BSc degree in Psychology with minors in Neuroscience and Statistics from University of Minnesota: Twin Cities. During her undergraduate studies, she was simultaneously involved with research on cross-lingual visual perception using statistical modeling and on the interaction between affect and cognition using behavioral and imaging (fMRI) methods. Combining her past research interests, she is now focusing on the neural basis of visual perception and cognition using electrocorticography (ECoG) and is preparing for a career in neuroscience.
Omri Raccah BSc
Omri obtained his BSc from UCLA in Cognitive Science with a concentration in Computing in 2015. While at UCLA, he worked on using diffusion tensor imaging (DTI) to evaluate the degree to which the structural integrity of individuals’ hippocampal circuitry accounts for variance in working memory performance. After graduation, Omri spent a year working at UCSD where he researched the neural underpinning of inhibitory control through combining computational modeling and fMRI techniques. Omri is now using intracranial recordings and electrical stimulation to investigate interactions across large-scale brain networks and how perturbations in these networks affect an individual’s mental capabilities.