Cognitive deficits in schizophrenia: from pharmacology to neurocognitive models

Journal of Translational Neuroscience ›› 2018, Vol. 3 ›› Issue (1) : 1 -11.

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Journal of Translational Neuroscience ›› 2018, Vol. 3 ›› Issue (1) :1 -11. DOI: 10.3868/j.issn.2096-0689.2018.01.001
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Cognitive deficits in schizophrenia: from pharmacology to neurocognitive models

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Abstract

Schizophrenia is a typical mental disorder characterized by cognitive, social, and emotional impairments and by psychotic symptoms. For nearly a century, there have been ongoing discussions on the anatomical-functional connections between brain abnormalities and symptoms in patients with schizophrenia. Neuroimaging studies in such patients show abnormalities in the prefrontal cortex (PFC), a brain region that acts as an executive center in cognition processing. The disrupted brain connectivity between PFC and other brain structures (such as the limbic system, basal ganglia and thalamus) results in faulty information processing and cognition deficits. Dopamine receptors, which have his torically acted as vital targets in schizophrenia therapies, have complex roles in cognition. Here we reviewed dopamine’s role as a widespread neurotransmitter mediating the PFC-cognitive system. The imbalance of braindopamine level, especially the abnormal D1/D2receptors ratio, leads to dysfunctions in brain connectivity in patients with schizophrenia. Recent neurocognitive modeling studies suggest the imbalance of dopamine receptors affects the internal noise within brain networks, which may lead to reduced signal-to-noise ratio in the PFC neuron populations. Going forward, more researches focusing on the relationship between pharmacology and neurocognitive models are needed, in an effort to identify more effective and efficient ways to treat cognitive impairment in patients with schizophrenia.

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dopamine / internal noise model / schizophrenia / cognitive deficits

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Zhemeng Wu, Qian Wang. Cognitive deficits in schizophrenia: from pharmacology to neurocognitive models. Journal of Translational Neuroscience, 2018, 3(1): 1-11 DOI:10.3868/j.issn.2096-0689.2018.01.001

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