A heuristic model for working memory deficit in schizophrenia

Abstract

Background: The life of schizophrenia patients is severely affected by deficits in working memory. In various brain regions, the reciprocal interactions between excitatory glutamatergic neurons and inhibitory GABAergic neurons are crucial. Other neurotransmitters, in particular dopamine, serotonin, acetylcholine, and norepinephrine, modulate the local balance between glutamate and GABA and therefore regulate the function of brain regions. Persistent alterations in the balances between the neurotransmitters can result in working memory deficits.

Methods: Here we present a heuristic computational model that accounts for interactions among neurotransmitters across various brain regions. The model is based on the concept of a neurochemical interaction matrix at the biochemical level and combines this matrix with a mobile model representing physiological dynamic balances among neurotransmitter systems associated with working memory.

Results: The comparison of clinical and simulation results demonstrates that the model output is qualitatively very consistent with the available data. In addition, the model captured how perturbations migrated through different neurotransmitters and brain regions. Results showed that chronic administration of ketamine can cause a variety of imbalances, and application of an antagonist of the D2 receptor in PFC can also induce imbalances but in a very different manner.

Conclusions: The heuristic computational model permits a variety of assessments of genetic, biochemical, and pharmacological perturbations and serves as an intuitive tool for explaining clinical and biological observations.

General significance: The heuristic model is more intuitive than biophysically detailed models. It can serve as an important tool for interdisciplinary communication and even for psychiatric education of patients and relatives. This article is part of a Special Issue entitled "System Genetics" Guest Editor: Dr. Yudong Cai and Dr. Tao Huang.

Keywords: Interaction matrix; Mesoscopic model; Mobile; Neurotransmitter; Schizophrenia; Systems biology; Working memory deficit.

Figure 1. The neurochemical mobile is a hierarchical scale system of balanced rods

The neurochemical mobile represents a hierarchical, functional organization of neurotransmitters, along with their relative functional contributions and dynamic imbalances in human brain. It visualizes synergisms or antagonisms between neurotransmitter systems at the physiological, behavioral, and pathological levels. The lengths of the arms of each rod are in reality different and reflect corresponding relative signal intensities. The neurotransmitters, under normal, healthy condition, are perfectly balanced at all levels of the mobile. Thus, strong deviations from balances point to (temporarily) abnormal states or disease. Abbreviations: dopamine (DA), serotonin (5-HT), norepinephrine (NE), acetylcholine (ACh), glutamate (Glu), gamma-aminobutyric acid (GABA).

Figure 2. Macro-anatomy of the neurochemical interaction matrix

The interactions among the six neurotransmitter systems in multiple regions across the human brain form a complicated network, which is shown here with different arrows. An arrow pointing to a circle codes for a projection onto the specific type of neurons. By contrast, if an arrow points to a box, the projections affect either all types of neurons inside this box, if there are multiple circles, or the entire region, if the box represents a single type of neurons within this brain region. Modeled brain regions include: prefrontal cortex (PFC), striatum, global pallidus internal (GPi), global pallidus external (GPe), subthalamic nucleus (STN), thalamus, substantia nigra pars compacta (SNpc), laterodorsal tegmental nucleus (LDT), ventral tegmental area (VTA), dorsal raphe nucleus (DRN), and locus coeruleus (LC). Solid circles in different colors represent different types of neurons as shown in the legend. Note that the two green circles in striatum represent GABAergic neurons having DA receptors of D₁ or D₂ type. Arrows with solid lines represent activation, while arrows with dashed lines represent inhibition. Arrows in different colors represent different neurotransmitter projections and follow the same coloring scheme as for the circles.

Figure 3. In response to chronical ketamine administration, the overall and sub-mobiles exhibit significant imbalances

All three mobiles show imbalance in response to chronic ketamine administration, which is an NMDA receptor antagonist. The same coloring scheme as in Figure 1 is used here (red: DA; purple: 5-HT; orange: NE; black: ACh; blue: Glu; green: GABA). A: Mobile for GABAergic neurons in PFC with three nodes (5-HT, DA, and NE); B: Mobile for glutamatergic neurons in PFC with five nodes (DA, NE, ACh, Glu, and GABA); C: Overall mobile for the whole brain with six nodes for all neurotransmitter systems across whole brain. As the results show, DA/5-HT outweighs NE (A), DA/NE outweighs ACh/Glu/GABA (B), and DA/5-HT/NE (C) similarly outweighs ACh/Glu/GABA.

Figure 4. In response to application of antagonist of DA D₂ receptor in PFC, the overall and sub-mobiles exhibit significant imbalances

Two of the three mobiles show imbalances in response to application of an antagonist of DA D₂ receptor in PFC. The same coloring scheme as in Figure 1 is used here (red: DA; purple: 5-HT; orange: NE; black: ACh; blue: Glu; green: GABA). A: Mobile for GABAergic neurons in PFC with three nodes (5-HT, DA, and NE) and does not involve Glu; B: Mobile for glutamatergic neurons in PFC with five nodes (DA, NE, ACh, Glu, and GABA); C: Overall mobile for the whole brain with six nodes for all neurotransmitter systems across whole brain. As the results show, the DA D₂ antagonist does not cause imbalance on GABAergic neurons in PFC. Interestingly, projections of DA and ACh (B) to glutamatergic neurons in PFC, or overall levels of DA, 5-HT, and ACh (C), are balanced.

Figure 5. ACh agonist reduces imbalances caused by chronic ketamine administration

The mobile shows that an ACh agonist reduces imbalances caused by chronic ketamine administration. The mobile shown is for glutamatergic neurons in PFC. The same coloring scheme as in Figure 1 is used here (red: DA; purple: 5-HT; orange: NE; black: ACh; blue: Glu; green: GABA). As shown, the ACh agonist can restore the balance between DA/NE on the left side of the overall scale and ACh/Glu/GABA on the right side. The increased imbalance between Glu and GABA may be due to the action of ACh or to influences from other brain regions not included in the model.