Electrophysiological (EEG) measures of neural synchronization and oscillations are abnormal in schizophrenia and may contribute to deficits in perceptual and cognitive processing. It has been hypothesized that these oscillatory deficits may be produced by disturbances in GABA and glutamatergic interactions within cortical and thalamocortical circuits. While oscillatory measures could provide a neurophysiological probe into a putative mechanism for schizophrenia, the neural basis for these disturbances and their relation to risk factors for the disorder, are little understood. This translational investigation will use complementary studies of patients with schizophrenia spectrum disorders and a ketamine rodent model of schizophrenia to investigate oscillatory disturbances as a potential biomarker for schizophrenia. Three types of responses will be analyzed in the frequency domain: a) oscillatory activity entrained to periodic stimuli (auditory steady state response or ASSR);2) gamma activity induced by tones;and 3) frequency domain analysis of sensory gating. In the human study, four groups will be compared: 1) Patients with schizophrenia, 2) subjects with schizotypal personality, a phenotype which shares symptoms with schizophrenia, 3) siblings of patients with schizophrenia, and 4) healthy control subjects. This human data will test whether these deficits in synchronization meet key criteria for an endophenotype in the disorder, or are state indicators for clinical psychosis. In the ketamine rodent model, we will test the sensitivity of these measures to acute and chronic administration of ketamine, a potent NMDA antagonist, and determine whether these are reversed by treatment with an atypical antipsychotic medication, olanzapine, or a glycine transporter 1 (GlyT1)-inhibitor N[3-(4'-flurophenyl)-3-(4'-phenylphenoxy) propyl]sarcosine (NFPS). The animal studies will therefore yield in-vivo evidence of the sensitivity of time-frequency measures to a well-validated rodent model of schizophrenia, and whether these measures are affected by anti-psychotic medications. These results may help identify neurophysiological biomarkers which index disturbances of synchronization and oscillations in schizophrenia, test the validity of these biomarkers in a rodent model, and evaluate the potential of these measures to evaluate treatment effects.

Public Health Relevance

Recordings of EEG activity (brainwaves) in schizophrenia show that responses to stimulation often show disturbed synchronization or oscillations. This project will study EEG oscillations in humans and in a rat model of schizophrenia. These results could help in understanding the neural mechanisms responsible for the disorder, and identify biomarkers in studies of genetic factors and treatment response.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21MH091774-02
Application #
8116476
Study Section
Special Emphasis Panel (ZRG1-BDCN-N (03))
Program Officer
Meinecke, Douglas L
Project Start
2010-07-23
Project End
2013-06-30
Budget Start
2011-07-01
Budget End
2013-06-30
Support Year
2
Fiscal Year
2011
Total Cost
$228,690
Indirect Cost
Name
Indiana University Bloomington
Department
Psychology
Type
Schools of Arts and Sciences
DUNS #
006046700
City
Bloomington
State
IN
Country
United States
Zip Code
47401
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O'Donnell, Brian F; Vohs, Jenifer L; Krishnan, Giri P et al. (2013) The auditory steady-state response (ASSR): a translational biomarker for schizophrenia. Suppl Clin Neurophysiol 62:101-12
Kent, Jerillyn S; Michael Bailey, D; Vollmer, Jennifer M et al. (2013) A magnetic resonance imaging-safe method for the study of human eyeblink conditioning. J Neurosci Methods 216:16-21
Fridberg, Daniel J; Skosnik, Patrick D; Hetrick, William P et al. (2013) Neural correlates of performance monitoring in chronic cannabis users and cannabis-naive controls. J Psychopharmacol 27:515-25
Kim, Dae-Jin; Bolbecker, Amanda R; Howell, Josselyn et al. (2013) Disturbed resting state EEG synchronization in bipolar disorder: A graph-theoretic analysis. Neuroimage Clin 2:414-23
Kam, Julia W Y; Bolbecker, Amanda R; O'Donnell, Brian F et al. (2013) Resting state EEG power and coherence abnormalities in bipolar disorder and schizophrenia. J Psychiatr Res 47:1893-901

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