Leslie S. Prichep

Biosketch / Results /

Leslie Prichep

Adjunct Professor, Department of Psychiatry
Psychiatry

Contact Info

Address
462 First Avenue
New York, NY 10016

212/263-6296
Leslie.Prichep@nyumc.org

Research Summary

Using quantitative EEG (QEEG) methodology developed in this laboratory over the past 20 years, we study the profiles of abnormal QEEG features in large populations of psychiatric patients and the relationship of these profiles to treatment outcome. Results to date from our current National Institute of Drug Abuse-funded study of the pathophysiology of crack cocaine dependence reveal the existence of a characteristic profile of QEEG changes associated with cocaine dependence and demonstrate that this profile persists during 1, 6, and 9 mo of abstinence. Such findings may reflect lasting alterations in neurotransmission as a consequence of cocaine exposure. Our published pilot work, demonstrating a markedly similar pattern of QEEG abnormalities in children with histories of in utero exposure to cocaine lend further evidence for such hypotheses. In addition, subtypes with distinctive QEEG profiles have been identified at baseline within the cocaine-dependent population. Significant interactions have been found between subtype membership, gender, comorbidity, and treatment retention. Another series of studies are focused specifically on the electrophysiological heterogeneity observed in clinically homogeneous patient populations. Cluster analysis of the baseline QEEG evaluations in DSM III-R obsessive-compulsive patients revealed two subtypes. Following a 3-mo clinical trial with specific serotonin reuptake inhibitors, it was found that treatment response could be accurately predicted in over 80% of the cases, determined on baseline QEEG subtype membership. Similarly, in schizophrenic patient populations and children with attention deficit disorder, the relationship between QEEG subtype and treatment response has been shown.

Research Interests

QEEG Characteristics and Subtyping Of Neuropsychiatric Disorders

Identification of acute stroke using quantified brain electrical activity
Michelson, Edward A; Hanley, Daniel; Chabot, Robert; Prichep, Leslie S
2015-01-11; 1069-6563,Academic emergency medicine - id: 1429042, year: 2015 Journal Article

Response to letter to the Editor regarding 'Classification algorithms for the identification of structural injury in TBI using brain electrical activity'
Prichep, Leslie S; Ghosh Dastidar, Samanwoy; Jacquin, Arnaud; Koppes, William; Miller, Jonathan; ONeil, Brian; Naunheim, Roseanne; Stephen Huff, J
2015-07-05; 1879-0534,Computers in biology & medicine - id: 1649702, year: 2015 LETTER

Identification of hematomas in mild traumatic brain injury using an index of quantitative brain electrical activity
Prichep, Leslie S; Naunheim, Rosanne; Bazarian, Jeffrey; Mould, W Andrew; Hanley, Daniel
2015-02-03; 0897-7151,Journal of neurotrauma - id: 1449122, year: 2015 Journal Article

Comparison of quantitative electroencephalogram to current clinical decision rules for head computed tomography use in acute mild traumatic brain injury in the ED
Ayaz, Syed Imran; Thomas, Craig; Kulek, Andrew; Tolomello, Rosa; Mika, Valerie; Robinson, Duane; Medado, Patrick; Pearson, Claire; Prichep, Leslie S; O'Neil, Brian J
2015-03-08; 0735-6757,American journal of emergency medicine - id: 1480282, year: 2014 JOURNAL ARTICLE

Classification algorithms for the identification of structural injury in TBI using brain electrical activity
Prichep, Leslie S; Ghosh Dastidar, Samanwoy; Jacquin, Arnaud; Koppes, William; Miller, Jonathan; Radman, Thomas; ONeil, Brian; Naunheim, Rosanne; Huff, J Stephen
2014-08-26; 0010-4825,Computers in biology & medicine - id: 1142372, year: 2014 JOURNAL ARTICLE