The overall aim of this research program is to use psychometric, psychophysical, and electrophysiological techniques to characterize visual processing deficits in schizophrenia spectrum disorders. The model motivating this project proposes that patients with schizophrenia (SZ), but not subjects with schizotypal personality disorder (SPD), will demonstrate disturbances of early stage vision and visual event related potentials (ERP) indicative of retino-geniculate or occipital cortex disturbances. Moreover, these disturbances appear to be most profound for stimuli and tasks requiring high temporal resolution or integration, suggestive of disturbed neural synchronization. Because neural synchronization at high firing frequencies may be essential for spatial and temporal binding or integration, this deficit could account for a broad range of disturbances in SZ. The model also suggests that working memory deficits are a core feature of both schizophrenia and SPD, which reflect disrupted frontal lobe function. Discrimination and delayed match-to-sample tests of short-term visual memory will be used to test these behavioral hypotheses. Event-related potential paradigms will be used to assess sensory processes, EEG synchronization to periodic stimulation, sensory gating, and attention and working memory operations. Computational modeling of neural circuits will be used to assess the role of NMDA and nicotinic dysregulation in producing these deficits. These findings may provide evidence regarding how schizophrenia and SPD differentially affect early stage vision and memory operations; implicate specific visual pathways and circuits which may be differentially sensitive to neurodevelopmental insults; and indicate visual processing deficits can identify core features across schizophrenia spectrum disorders.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
5R01MH062150-03
Application #
6630397
Study Section
Special Emphasis Panel (ZRG1-BDCN-6 (01))
Project Start
2001-07-20
Project End
2005-03-31
Budget Start
2003-07-01
Budget End
2005-03-31
Support Year
3
Fiscal Year
2003
Total Cost
$186,250
Indirect Cost
Name
Indiana University Bloomington
Department
Miscellaneous
Type
Schools of Arts and Sciences
DUNS #
006046700
City
Bloomington
State
IN
Country
United States
Zip Code
47401
Cheng, H; Skosnik, P D; Pruce, B J et al. (2014) Resting state functional magnetic resonance imaging reveals distinct brain activity in heavy cannabis users - a multi-voxel pattern analysis. J Psychopharmacol 28:1030-40
O'Bryan, Rebecca A; Brenner, Colleen A; Hetrick, William P et al. (2014) Disturbances of visual motion perception in bipolar disorder. Bipolar Disord 16:354-65
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
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
Vohs, Jenifer L; Chambers, R Andrew; O'Donnell, Brian F et al. (2012) Auditory steady state responses in a schizophrenia rat model probed by excitatory/inhibitory receptor manipulation. Int J Psychophysiol 86:136-42
Rass, Olga; Forsyth, Jennifer K; Krishnan, Giri P et al. (2012) Auditory steady state response in the schizophrenia, first-degree relatives, and schizotypal personality disorder. Schizophr Res 136:143-9
Rass, Olga; Forsyth, Jennifer K; Bolbecker, Amanda R et al. (2012) Computer-assisted cognitive remediation for schizophrenia: a randomized single-blind pilot study. Schizophr Res 139:92-8
Luck, Steven J; Mathalon, Daniel H; O'Donnell, Brian F et al. (2011) A roadmap for the development and validation of event-related potential biomarkers in schizophrenia research. Biol Psychiatry 70:28-34
Ahn, Woo-Young; Rass, Olga; Fridberg, Daniel J et al. (2011) Temporal discounting of rewards in patients with bipolar disorder and schizophrenia. J Abnorm Psychol 120:911-21
Kim, Dae-Jin; Skosnik, Patrick D; Cheng, Hu et al. (2011) Structural network topology revealed by white matter tractography in cannabis users: a graph theoretical analysis. Brain Connect 1:473-83

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