Laboratoire de Neurosciences Cognitives et Computationnelles, Département d'Études Cognitives, École Normale Supérieure, INSERM U960, PSL University, Paris, France.
Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.
Curr Opin Neurobiol. 2021 Oct;70:171-181. doi: 10.1016/j.conb.2021.10.013. Epub 2021 Nov 26.
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.
生物物理吸引子网络模型中神经调节或突触传递的改变，如精神分裂症的主导多巴胺能和谷氨酸能理论所提出的，成功地模拟了精神分裂症患者的工作记忆（WM）缺陷。然而，记忆回路中经常出现的多种、相互矛盾的改变，可能导致这些网络模型中出现相同的行为模式。在这里，我们批判性地审查了将 NMDAR 功能低下与 PSZ 中的 WM 精度损失联系起来的计算和实验文献。我们在网络模拟中表明，目前可用的实验证据无法区分竞争的生物物理解释。需要解决的关键点是 E/I 比增加与减少（例如通过 NMDA 受体阻断）对放电率调谐和共享噪声调制的影响，以及短期可塑性可能同时出现的缺陷。我们认为，这些协同的实验和计算努力将导致更好地理解 PSZ 中认知缺陷的神经生物学基础。
