Background: The causal biology underlying schizophrenia is not well understood, but it is likely to involve a malfunction in how neurons adjust synaptic connections in response to patterns of activity in networks. We examined statistical dependencies between neural signals at the cell, local circuit, and distributed network levels in prefrontal and parietal cortices of monkeys performing a variant of the AX continuous performance task paradigm. We then quantified changes in the pattern of neural interactions across levels of scale following NMDA receptor (NMDAR) blockade and related these changes to a pattern of cognitive control errors closely matching the performance of patients with schizophrenia. Methods: We recorded the spiking activity of 1762 neurons along with local field potentials at multiple electrode sites in prefrontal and parietal cortices concurrently, and we generated binary time series indicating the presence or absence of spikes in single neurons or local field potential power above or below a threshold. We then applied causal discovery analysis to the time series to detect statistical dependencies between the signals (causal interactions) and compared the pattern of these interactions before and after NMDAR blockade. Results: Global blockade of NMDAR produced distinctive and frequently opposite changes in neural interactions at the cell, local circuit, and network levels in prefrontal and parietal cortices. Cognitive control errors were associated with decreased interactions at the cell level and with opposite changes at the network level in prefrontal and parietal cortices. Conclusions: NMDAR synaptic deficits change causal interactions between neural signals at different levels of scale that correlate with schizophrenia-like deficits in cognitive control.
|Original language||English (US)|
|Number of pages||10|
|Journal||Biological Psychiatry: Cognitive Neuroscience and Neuroimaging|
|State||Published - Jul 2020|
Bibliographical noteFunding Information:
Support for this work was provided by the National Institutes of Health (Grant No. R01MH107491 [to MVC], Grant Nos. R01MH080318 and R01MH112688 [to ADR], Grant No. NCRR 1UL1TR002494-01 [to EK and SM], Grant Nos. T32 GM008244 and T32 HD007151 [to RKB], Grant No. F31MH109238 [to ALD], and Grant Nos. R01MH081051 , R21MH110208-01A1 , and R21MH110208-01A1 [to SV]); and by the University of Minnesota Wilfred Wetzel Graduate Fellowship (to RKB). This material is the result of work supported with resources and the use of facilities at the Minneapolis Veterans Administration Health Care System.
© 2020 Society of Biological Psychiatry
- Causal modeling
- Cognitive control
- Neural dynamics
PubMed: MeSH publication types
- Journal Article
- Research Support, N.I.H., Extramural
- Research Support, Non-U.S. Gov't