Towards biologically constrained attractor models of schizophrenia. (October 2021)

• Record Type: Journal Article
• Authors: Stein, Heike; Barbosa, Joao; Compte, Albert
• Is Part Of: Current opinion in neurobiology. Volume 70(2021)
• Page Start: 171
• Page End: 181
• Publication Date: 2021-10
• Subjects: WM working memory -- PSZ people with schizophrenia -- NMDA N-methyl-D-aspartic acid -- NMDAR NMDA receptor -- STP short-term plasticity; Neurobiology -- Periodicals; 573.8
• DOI: 10.1016/j.conb.2021.10.013
• Languages: English
• ISSNs: 0959-4388

Abstract

Abstract: Alterations in neuromodulation or synaptic transmission in biophysical attractor network models, as proposed by the dominant dopaminergic and glutamatergic theories of schizophrenia, successfully mimic working memory (WM) deficits in people with schizophrenia (PSZ). Yet, multiple, often opposing alterations in memory circuits can lead to the same behavioral patterns in these network models. Here, we critically revise the computational and experimental literature that links NMDAR hypofunction to WM precision loss in PSZ. We show in network simulations that currently available experimental evidence cannot set apart competing biophysical accounts. Critical points to resolve are the effects of increases vs. decreases in E/I ratio (e.g. through NMDAR blockade) on firing rate tuning and shared noise modulations and possible concomitant deficits in short-term plasticity. We argue that these concerted experimental and computational efforts will lead to a better understanding of the neurobiology underlying cognitive deficits in PSZ. Highlights: WM deficits in PSZ cannot be readily mapped on the stability of continuous attractors. Different attractor models yield inconsistent behavioral predictions upon changes in E/I ratio. Grouping different perturbations under E/I ratio can be inadequate for some deficits. Insufficient experimental and computational understanding precludes model selection. We need data showing NMDAR-dependence of rate tuning and correlated noise in WM circuits.