Jack Grinband, PhD
- Assistant Professor of Clinical Neurobiology in Psychiatry and Radiology
Overview
Jack Grinband, PhD, is an Assistant Professor of Clinical Neurobiology in Psychiatry and Radiology at Columbia University. His research interests include neuroimaging and psychophysics in healthy, psychiatric, and neurological populations with emphasis on decision making and emotional appraisal. Dr. Grinband received his PhD in Neuroscience from the University of Minnesota. He did his postdoctoral training at Columbia University with Vincent Ferrera where he studied the neural mechanisms of decision-making and decision uncertainty. He is currently working on developing novel methods for estimating neurovascular coupling and controlling for head movement in fMRI. In addition, he is conducting schizophrenia-related pharmacology studies and studying cognitive and emotional deficits in borderline personality disorder. Additional information can be found at http://grinbandlab.org.
Academic Appointments
- Assistant Professor of Clinical Neurobiology in Psychiatry and Radiology
Gender
- Male
Credentials & Experience
Education & Training
- BA, 1993 Psychology, University of California at Berkeley
- PhD, 2002 Neuroscience, University of Minnesota
Research
Ongoing Research:
Neural Basis of Perceptual Decision-Making. We study how sensory information is transformed into decisions in the presence of distractors. To minimize the interference caused by distractors the brain must engage attentional resources to enhance the target and/or suppress the distractor. We are using fMRI to test how the brain resolves different types of interference and measuring the degree of cognitive control necessary for shifting attention.
Ketamine pharmacoBOLD. Development of novel anti-psychotics is expensive. We have developed a model system using ketamine pharmacoBOLD for testing whether a pharmaceutical has glutamatergic activity. This model system can provide a rapid assessment of a drug's potential for treatment efficacy.
Neurovascular coupling. Structural MRI has good sensitivity for detecting the disruption of the blood brain barrier by gliomas; however, the infiltrating margins of the tumor remain invisible to standard of care structural imaging. Because glioma disrupts neurovascular coupling, functional MRI can be used to detect the infiltrative margins of the tumor, with sensitivity that is much higher than standard of care imaging. We have developed a measure called BOLD asynchrony which can be used as a whole brain metric of tumor burden.