While researchers have learned vast amounts about brain function at a cellular and molecular level over the past several years, we still have a poor understanding of the manner in which these phenomena give rise to behavior, and the way that neurobiological dysfunction creates psychiatric symptoms. This is particularly true for schizophrenia: while a large number of research studies have implicated hippocampus in the etiology of schizophrenia, and several possible neuroanatomic and biochemical abnormalities have been identified in this region, we still do not know how these findings, alone or in combination, lead to the clinical syndrome. Computational modeling is a research tool that allows one to make links between cellular phenomena and clinical behaviors by offering insights at the level of cells or cell ensembles as to how emergent properties arise. We have developed a computer simulation of a subsection of hippocampus CA1 incorporating 452 cells. Each cell is a biologically realistic model of a neuron, featuring an extensive dendritic arborization and Na+, Ca++, K+DR, K*AHp, K+c, and K+A channels, as well as AMPA, NMDA, and GABA synapses. We will use an elaborated version of this computational model as a tool to examine particular hypothesis regarding the hippocampal neuropathology of schizophrenia. Specifically, we will """"""""lesion"""""""" the model in a schizophrenogenic way by separately and in combination (a) altering aspects of the GABA system, (b) disrupting the glutamatergic system, and (c) increasing dopaminergic tone. We will examine two outcome measures: oscillatory activity and performance on context-dependent memory tasks;both of these have clinical correlations with schizophrenia. Finally, we will apply a number medications, including typical and atypical antipsychotics, and examine their effects on system functioning. We expect these studies to 1) offer mechanistic and system-level insights into the neuropathological basis of the illness;2) generate hypotheses that can subsequently be tested experimentally;and 3) identify potentially effective antipsychotic medications. Also, we hope that this study can make a contribution from a methodological point of view: though it involves only one brain area performing a discrete psychological task for a particular psychiatric illness, it is an approach that potentially can be applied to other brain regions and neuropsychiatric diseases.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Clinical Investigator Award (CIA) (K08)
Project #
5K08MH072771-03
Application #
7609102
Study Section
Neural Basis of Psychopathology, Addictions and Sleep Disorders Study Section (NPAS)
Program Officer
Wynne, Debra K
Project Start
2007-08-21
Project End
2012-04-30
Budget Start
2009-05-01
Budget End
2010-04-30
Support Year
3
Fiscal Year
2009
Total Cost
$175,500
Indirect Cost
Name
Mclean Hospital
Department
Type
DUNS #
046514535
City
Belmont
State
MA
Country
United States
Zip Code
02478
Siekmeier, Peter J (2015) Computational modeling of psychiatric illnesses via well-defined neurophysiological and neurocognitive biomarkers. Neurosci Biobehav Rev 57:365-80
Siekmeier, Peter J; vanMaanen, David P (2014) Dopaminergic contributions to hippocampal pathophysiology in schizophrenia: a computational study. Neuropsychopharmacology 39:1713-21
Siekmeier, Peter J; vanMaanen, David P (2013) Development of antipsychotic medications with novel mechanisms of action based on computational modeling of hippocampal neuropathology. PLoS One 8:e58607
Siekmeier, Peter J; Stufflebeam, Steven M (2010) Patterns of spontaneous magnetoencephalographic activity in patients with schizophrenia. J Clin Neurophysiol 27:179-90
Siekmeier, Peter J (2009) Evidence of multistability in a realistic computer simulation of hippocampus subfield CA1. Behav Brain Res 200:220-31
Vierling-Claassen, Dorea; Siekmeier, Peter; Stufflebeam, Steven et al. (2008) Modeling GABA alterations in schizophrenia: a link between impaired inhibition and altered gamma and beta range auditory entrainment. J Neurophysiol 99:2656-71