Over the past year, the neuropsychology group has attempted to characterize more completely the cognitive disturbances in schizophrenia. In particular we have begun work on the mechanisms accounting for failures in memory in schizophrenia. Patients' difficulties do not appear to be due to qualitative abnormalities in susceptibility to interference, encoding, or so called false memory problems. We have begun to computationally model the episodic memory impairments in schizophrenia in order to determine if they are due to general noise or a single stage in memory processing. We found that one possible explanation of our results involves defective encoding of context information (a function assigned to the parahippocampal gyrus in our model). Most recently, one of our studies shows evidence of increased variability of noise being associated with genetic risk for schizophrenia, specifically based on COMT genotype. Findings in our study of response inhibition and interference monitoring and suppression, indicate regional functional specialization within a cortical network supporting cognitive control. We have examined disorganized speech in schizophrenia using various semantic processing paradigms. In general, patients have difficulties not with the size of their vocabulary but rather how they access it automatically, as evidenced in priming paradigms. Thus, we have devised a battery of novel experimental tasks to assess whether schizophrenic patients show dissociation between vocabulary integrity and semantic abnormality. We have completed work on a study which compares the integrity of the internal representation itself to the integrity of activation among representations using various types of number priming and quantity processing. This technique circumvents problems in judging the relatedness of words. We have also begun to use a computationally rich technique called """"""""latent semantic analysis"""""""" which judges the coherence of schizophrenic discourse using reliable computer controlled methods. We have found odd associations and diminished coherence over various discourse lengths. Importantly the technique is highly reliable; because it was highly correlated with clinical ratings from interviews we also think that it is valid. Additionally, we are assessing working memory and attention processing in a large sample of schizophrenic patients, their well siblings, and healthy control subjects using the N-Back task to engage the working memory system. This study suggests that cognitive deficits associated with increased genetic risk for schizophrenia involve subprocesses related to target selection and memory manipulation and not load, delay, or speed of processing attention. We have now completed a study examining cognitive deficits such as, working memory, time estimation, and absolute identification of stimuli in patients with schizophrenia. The tasks are designed to be structurally similar and yield rich error data. Our findings do not support the global consensus of impairment in absolute identification, but instead impairment on a duration identification task and probed-recall memory task were observed in patients with schizophrenia. In a study using healthy controls, we examined neurological correlates of age-related reductions in working memory. We determined that normal aging is associated with a reduction in neural efficiency and that the elderly recruit more units of resources even at lower task complexity to maintain performance. This study is further evidence of a dynamic relationship between cortical activation observed with neuroimaging and performance on a cognitive task. When probabilistic category learning is invoked in a similar cohort, there is differential activation within the neural network suggesting that some brain regions may provide compensatory mechanisms for inefficiency or functionally compromised areas. Finally, a genetic study of schizophrenia with an emphasis on intermediate phenotypes is ongoing. We are using a large battery of neurocognitive measures to characterize this """"""""intermediate"""""""" phenotype. We base this on the rationale that patients do not inherit schizophrenia per se but a variety of susceptibilities to cognitive impairments and their attendant neurophysiologic abnormalities. We have already found that some cognitive measures yield high relative risks that are not redundant with diagnosis. Moreover, we have identified a gene COMT (Catechol-O-Methyltransferase) that has an impact on the N-Back through dopamine signaling. Another study was further evidence of this effect in that COMT Val/Met genotype may influence the cognitive response to antipsychotic treatment in patients with schizophrenia, with the met allele predicting the greatest improvement on medication. We have also identified a gene BDNF brain-derived necrotrophic factor) that has significant impact on human hippocampal function, including episodic memory. We have examined a third gene, called G72 that demonstrates epistasis such that its effect on cognition was amplified in a group of schizophrenia patients (in contrast to controls and siblings). Most recently, our study of G72 extended our data in that cognitive memory functions worsen with increased risk allele load. This is the first such report in the literature. We will continue to acquire new cognitive datasets related to other potential brain deficits associated with schizophrenia in an effort to further characterize the cognitive neuroscience of some of these phenotypes and to examine mental processing through other brain systems.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Intramural Research (Z01)
Project #
1Z01MH002712-12
Application #
7312858
Study Section
(CBDB)
Project Start
Project End
Budget Start
Budget End
Support Year
12
Fiscal Year
2006
Total Cost
Indirect Cost
Name
U.S. National Institute of Mental Health
Department
Type
DUNS #
City
State
Country
United States
Zip Code
Rosenstein, Mark; Diaz-Asper, Catherine; Foltz, Peter W et al. (2014) A computational language approach to modeling prose recall in schizophrenia. Cortex 55:148-66
Voorspoels, Wouter; Storms, Gert; Longenecker, Julia et al. (2014) Deriving semantic structure from category fluency: clustering techniques and their pitfalls. Cortex 55:130-47
ElvevÄg, Brita; Wynn, Rolf; Covington, Michael A (2011) Meaningful confusions and confusing meanings in communication in schizophrenia. Psychiatry Res 186:461-4
Walenski, Matthew; Weickert, Thomas W; Maloof, Christopher J et al. (2010) Grammatical processing in schizophrenia: evidence from morphology. Neuropsychologia 48:262-9
Elvevag, Brita; Weinberger, Daniel R (2009) Introduction: genes, cognition and neuropsychiatry. Cogn Neuropsychiatry 14:261-76
Weickert, Thomas W; Goldberg, Terry E; Callicott, Joseph H et al. (2009) Neural correlates of probabilistic category learning in patients with schizophrenia. J Neurosci 29:1244-54
Honea, Robyn A; Meyer-Lindenberg, Andreas; Hobbs, Katherine B et al. (2008) Is gray matter volume an intermediate phenotype for schizophrenia? A voxel-based morphometry study of patients with schizophrenia and their healthy siblings. Biol Psychiatry 63:465-74
Elvevag, Brita; Foltz, Peter W; Weinberger, Daniel R et al. (2007) Quantifying incoherence in speech: an automated methodology and novel application to schizophrenia. Schizophr Res 93:304-16
Talamini, Lucia M; Meeter, Martijn; Elvevag, Brita et al. (2005) Reduced parahippocampal connectivity produces schizophrenia-like memory deficits in simulated neural circuits with reduced parahippocampal connectivity. Arch Gen Psychiatry 62:485-93
Paul, Brianna M; Elvevag, Brita; Bokat, Christina E et al. (2005) Levels of processing effects on recognition memory in patients with schizophrenia. Schizophr Res 74:101-10

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