mGluR1,5 activation improves network asynchrony and GABAergic synapse attenuation in the amygdala: implication for anxiety-like behavior in DBA/2 mice
© Zhang et al.; licensee BioMed Central Ltd. 2012
Received: 27 January 2012
Accepted: 9 May 2012
Published: 9 June 2012
Anxiety is a prevalent psychological disorder, in which the atypical expression of certain genes and the abnormality of amygdala are involved. Intermediate processes between genetic defects and anxiety, pathophysiological characteristics of neural network, remain unclear. Using behavioral task, two-photon cellular imaging and electrophysiology, we studied the characteristics of neural networks in basolateral amygdala and the influences of metabotropic glutamate receptor (mGluR) on their dynamics in DBA/2 mice showing anxiety-related genetic defects. Amygdala neurons in DBA/2 high anxiety mice express asynchronous activity and diverse excitability, and their GABAergic synapses demonstrate weak transmission, compared to those in low anxiety FVB/N mice. mGluR1,5 activation improves the anxiety-like behaviors of DBA/2 mice, synchronizes the activity of amygdala neurons and strengthens the transmission of GABAergic synapses. The activity asynchrony of amygdala neurons and the weakness of GABA synaptic transmission are associated with anxiety-like behavior.
KeywordsAnxiety Amygdala GABA Neuron Synapse and neural network
Anxiety, characterized as unstable mood, elevated attention, negative interpretation and social phobia under the conditions of potential threatening signs, is one of prevalent psychological disorders [1–3]. The studies by neural imaging indicate the hyperactivity of amygdala in anxiety disorder [4, 5]. A stimulus to amygdala induces anxiogenic somatic and autonomic responses . The grafts of GABAergic-rich neural tissue into amygdala improve anxiety-like signs . The abnormality of amygdala is presumably a major origin of anxiety pathogenesis [1, 4, 8–24]. However, anxiety-related pathological characteristics and mechanisms in amygdala remain to be elusive.
In terms of molecular mechanisms, the defects of certain genes are presumably associated with anxiety disorder [25–34]. At the cellular level, the abnormalities of amygdala neurons [1, 15, 22, 35–37] and GABAergic synapses [38–40] are likely related to anxiety. It remains unclear how these genetic deficits lead to the impairment of amygdala neural microcircuits in anxiety disorders. In DBA/2 mice that are anxiety-like phenotype and gene variances in amygdala , we investigated the pathophysiological characteristics and pharmacological improvement of neuronal networks and GABAergic synapses in basolateral amygdala by two-photon cellular imaging, electrophysiology and pharmacology.
In order to study how genetic deficits impair neuronal networks in amygdala and lead to anxiety disorder, we have to select an appropriate model of animals that show anxiety-related phenotype and genotype. Compared to FVB/N mice, DBA/2 mice show anxiety-like behavior and anxiety-associated genetic variance, such as the abnormal expressions of glyoxalase-1 and glutathione reductase-1 genes in amygdala . These two strains of mice were used to study the correlation among anxiety, genes and amygdala neuron networks.
The activity asynchrony of network neurons in the amygdala of DBA/2 anxiety-like mice
The abnormality of amygdala is presumably one of major mechanisms associated with anxiety [1, 15, 22, 38–40]. However, the pathological dynamics of its neuronal networks has not been characterized , which we examined in basolateral amygdala of DBA/2 high anxiety mice by two-photon cellular imaging and electrophysiology. Control experiments were conducted in FVB/N low anxiety mice. The temporal and spatial patterns in the activity of amygdala network neurons were evaluated by detecting the changes of intracellular Ca2+, since neuronal spikes raise its levels [43, 44]. Oregon-green BAPTA-AM was loaded into the cells of brain slices including amygdala from DBA/2 and FVB/N mice to monitor intracellular Ca2+ levels. Sulforhodanmine-101 (SR-101) was used to label the astrocytes . Fluorescents in amygdala were excited and detected by a two-photon laser scanning microscopy.
The temporal activity of amygdala neurons is evaluated by cross-correlations in the time phase of activities between neighboring neurons [46–48]; Methods). Chip patterns in Figure 3A-B show the cross-correlations of cell temporal activity from two strains of mice. The colors from red to blue denote their correlation coefficients from high (synchronous activity) to low (asynchronous). Amygdala neurons in DBA/2 high anxiety mice (3A) show lower cross-correlations than those in FVB/N low anxiety mice (3B). Figure 3C demonstrates correlation coefficients averaged from amygdala neurons in a FVB/N mouse (red line) and a DBA/2 (black, p < 0.01). Figure 3D illustrates the correlation coefficients averaged from all FVB/N mice (red line, n = 11) and DBA/2 mice (black; p < 0.01, n = 12). It is noteworthy that cross-correlations from all astrocytes in FVB/N mice (red line) and DBA/2 ones (black) are not statistically different (p = 0.56, Figure 3E). These data from analyzing cross-correlation indicate that the activities of amygdala neurons are less synchronous in DBA/2 high anxiety mice than FVB/N low anxiety mice.
Diversified neuronal excitability and weak GABAergic synapses in amygdala of DBA/2 anxiety-like mice
The activity asynchrony of amygdala neurons in DBA/2 anxiety-like mice may be caused by their functional diversity and GABAergic synapse weakness, since the activities of cerebral neurons are presumably coordinated by inhibitory interneurons [49–55]. We examined neuronal intrinsic properties and GABAergic synapses in the amygdala.
The results above indicate that the activity asynchrony of neuronal activity, the diversity of their excitability and the weakness of GABAergic synapses in the amygdala are associated with anxiety pathophysiology. We subsequently seek the approach to improve anxiety-like behaviors and cellular pathophysiology. Temporal activities of cortical neurons are hypothetically regulated by metabotropic glutamate receptors (mGluR, . We examined the influences of mGluR activation on neuronal network activity, GABAergic synaptic transmission and anxiety-like behaviors.
mGluR activation improves anxiety, network asynchrony and GABA synaptic transmission
In addition, the influences of mGluR1,5 activation on the activity strength of amygdala neurons in DAB/2 anxiety-like mice are showed in Figure 8E-F. Figure 8E illustrates the comparison in the number of cells vs. their fluorescence intensity in DBA/2 mice before (gray bars/fitting curve) and after (white bars/black curve) using 3,5-DHPG, in which the average values are 773 ± 488 for control and 825 ± 512 for DHPG (p = 0.3, n = 193). Figure 8F shows the number of spontaneous events versus their relative fluorescence intensity in DBA/2 mice before (gray bars/fitting curve) and after (white bars/black curve) 3,5-DHPG, in which the average values are 0.512 ± 0.26 for control and 0.38 ± 0.23 for 3,5-DHPG. Thus, mGluR1,5 activation does not affect the activity strength of amygdala network neurons in DBA/2 anxiety-like mice.
We studied cellular mechanisms underlying anxiety-like behavior in DBA/2 mice by using two-photon cellular imaging, electrophysiology and behavioral analysis. The temporal asynchrony of neuronal activity and the weakness of GABAergic synaptic transmission in amygdala are associated with anxiety-like behavior (Figures 2, 3, 4, 5 and 6). mGluR1,5 activation improves anxiety-like behavior, synchronizes neuronal activities and enhances GABAergic synaptic transmission in the amygdala (Figures 7, 8 and 9). These results indicate mGluR1,5 agonists may be potentially useful as anxiety therapies. Our studies bring insights into the pathological mechanisms between genetic deficits and anxiety-like behavior, and the potential medications for anxiety disorders.
Previous studies imply that the abnormality of certain genes is associated with anxiety disorders, such as CRHR1, FKBP5, CREB, Egr-1, Glo1, Gsr, AC8, CaMKIV, dystrophin, HTTLPR and COMT Met158 [25–34, 59]. The amygdala dysfunction is presumably one of anxiety pathogeneses [1, 10, 14–16, 20, 22, 24]. The cellular processes linking genes’ defects and functional impairment in amygdala remain unclear. We used DBA/2 mice that are genetic variances (glyoxalase-1/glutathione reductase-1 genes) and anxiety-like phenotype  to study the cellular pathophysiology of anxiety. Our studies will be extended to address the relationships between other genes and anxiety-related cellular pathophysiology.
Neural hyperactivity in amygdala may be associated with anxiety disorders [5, 6, 60, 61], and its networks are hypothetically abnormal [1, 15, 22, 35]. Compared to these studies by brain imaging [5, 6, 60, 61], two-photon imaging in our studies has cellular resolution, which enables the temporal and spatial activity natures of individual cells be analyzed. Here, we reveal that the amygdala neurons in DBA/2 anxiety-like mice appear a temporal asynchrony in their activities (Figures 3 and 4). As GABAergic inhibitory system coordinates the activities of network neurons [49, 53–55], the dysfunction of GABAergic synapses in amygdala (Figure 6) leads to the asynchrony of neuronal network. Our studies by imaging cell dynamics provide a direct evidence for this hypothesis, and address its mechanisms.
Previous studies indicate that dysfunctional interactions in ligands and receptors, e.g., serotonin, norepinephrine, GABA, glutamate and hormones, are associated with anxiety [62–65]. The reagents strengthening the efficacy of their interactions were applied for the psychotropic medication of anxiety disorders, such as selective serotonin reuptake inhibitors, tricyclic antidepressants, monoamine oxidase inhibitors and benzodiazepine . Despite notable advances, numerous patients suffering from anxiety disorders fail to adequately respond to these pharmacologic reagents. In addition, the objects to strengthen ligand-receptor interactions may be realized by mGluR-mediated activations of cellular signals. Figures 7, 8 and 9 indicate that mGluR1,5 activation improves anxiety-like behavior, synchronizes neuronal activity and enhances GABA synaptic transmission in the amygdala of DBA/2 mice, indicating a potential use of mGluR agonists for the therapy of anxiety disorders. This supports an early-stage effort to understand the role of mGluR reagents in anxiety disorders [67–69].
It is noteworthy that the values measured in behavioral tasks from DBA mice are variable in Figure 1 vs. Figure 7. As all of the treatments to mice were identical, only difference between these two groups was intraperitoneal injections. In addition, the injections of 3,5-DHPG and PBS saline increased the duration in closed arms/total (Figure 7), compared with no injection (Figure 1). Therefore, our explanation for such discrepancies would be that the injections may influence anxiety-like behaviors. This explanation is supported by a reference in behavioral study .
In conclusion, mGluR1,5 activation improves anxiety-like behavior by up-regulating GABAergic synapse-mediated synchrony of amygdala network neurons (Figure 10). Our findings are adding the knowledge for the pathological mechanisms and medications of anxiety disorders.
Methods and materials
The selection of mice with anxiety-like behavior
According to the study in mouse behavior , we selected two strains of mice DBA/2 and FVB/N, which demonstrate high anxiety and low anxiety, respectively (also see Figure 1). Mice in postnatal day (PND) 20 ~ 30 were used to conduct the experiments of behavioral tasks as well as of two-photon cellular imaging and electrophysiology in amygdala of brain slices. The elevated plus-maze was used to evaluate anxiety-like behaviors. Patch-clamp was used to record the transmission of GABAergic synapses and the intrinsic property of amygdala neurons. A two-photon laser scanning microscopy was applied to image the activities of neural networks in the amygdala. The entire procedures are approved by the Institutional Animal Care Unit Committee in the Administration Office of Laboratory Animals Beijing China (B10831).
Anxiety-like behaviors in DBA/2 and FVB/N mice were evaluated by an elevated plus-maze (EPM), which is described as a validated and classic method to assess the level of anxiety in the rodents [41, 42]. The EPM consists of two open arms (30 × 5 cm) opposite to two closed arms (30 × 5 × 15.25 cm). The arms extended from a central platform (5 × 5 cm). The EPM was located 40 cm above the floor (Figure 1A). FBV/n and DBA/2 mice were housed in plastic cages with food/water availability ad libitum and a schedule of alternative light and dark (12 hours for each condition), in which the light was on 17:00. All experiments were performed between 8:00 to 14:00. Mice were at the age about one month when the tests were conducted.
Mice naturally avoid the open field. On the other hand, they intend to explore a new environment for food. In this regard, the measurement for mice avoiding the open field was the duration when mice stayed in the closed arms, i.e., the duration in the closed arms vs. total experimental time, whereas the measurement for mice exploring the new environment was exploration times toward the open arms (Figure 1B). Therefore, exploration times and the duration in the closed arms were used to evaluate the level of anxiety, which were recorded by an automatic video-tracking system for 5 min. Mice were placed at the open field of an elevated plus-maze with facing to a closed arm at the beginning of experiments. High anxiety-like behaviors are described as mice spending more time in the closed arms as well as having lower exploration times toward the open arms. Behavioral data were presented as means ± SE and statistically analyzed by one-way ANOVA (Origin Lab).
Brain slices in coronal section including cortex, amygdala, hippocampus and thalamus (350 μm) were prepared from DBA/2 and FVB/N mice. These mice were anesthetized by injecting chloral hydrate (300 mg/kg) and decapitated by a guillotine. The slices were sectioned by a Vibratome in the modified and oxygenized (95% O2 and 5% CO2) artificial cerebrospinal fluid (mM: 124 NaCl, 3 KCl, 1.2 NaH2PO4, 26 NaHCO3, 0.5 CaCl2, 5 MgSO4, 10 dextrose and 5 HEPES; pH 7.35) at 4 °C, and then were held in the normal oxygenated ACSF (mM: 124 NaCl, 3 KCl, 1.2 NaH2PO4, 26 NaHCO3, 2.4 CaCl2, 1.3 MgSO4, 10 dextrose and 5 HEPES; pH 7.35) 25 °C for 1–2 hours. A slice was transferred into a submersion chamber (Warner RC-26 G) that was perfused with normal ACSF at 31°C for electrophysiological experiments [71–73].
Neurons in basolateral amygdala were recorded by whole-cell clamp under a visualized condition (DIC/FN-E600, Nikon, Japan). Spontaneous inhibitory postsynaptic currents (sIPSC) from GABAergic synapses were recorded by voltage-clamp model (MultiClamp 700B and pClamp 10, Axon Instrument, Foster CA, USA) on amygdala neurons. Standard pipette solution contained (mM) 135 K-gluconate, 20 KCl, 4 NaCl, 10 HEPES, 0.5 EGTA, 4 Mg-ATP, and 0.5 Tris–GTP. The osmolarity of pipette solutions was 295–310 mOsmol, and the resistance of filled pipettes was 5 ~ 7 MΩ. Based on Nernst equation, the concentration of chloride ions in this pipette solution makes reversal potential approximately −43 mV, which is consistent with values in our measurements. When we held the membrane potential at −70 mV, GABAergic sIPSCs were inward (down-fluctuation). Series and input resistances for all of the neurons were monitored by injecting hyperpolarization pulses (5 mV/50 ms) throughout each experiment, and calculated by voltage pulses versus instantaneous and steady-state currents. 6-Cyano-7-nitroquinoxaline −2,3-(1 H,4 H)-dione (10 μM) and D-amino-5-phosphonovanolenic acid (40 μM) were added into ACSF to block ionotropic receptor-channels in the glutamatergic synapses [74, 75]. These procedures isolate GABAergic IPSCs out. At the end of experiments, bicuculline (10 μM) was washed onto the slices to test whether synaptic responses were purely mediated by GABAAR. Bicuculline did block synaptic currents recorded in our experiments.
Action potentials were recorded by MultiClamp-700B amplifier and inputted into pClamp10 with 100 Hz sampling rate (Axon Instrument Inc., Foster CA, USA). Transient capacitance was compensated, and output bandwidth filter was 3 kHz. Standard pipette solution contained (mM) 150 K-gluconate, 5 NaCl, 0.4 EGTA, 4 Mg-ATP, 4 Na-phosphocreatine, 0.5 Tris-GTP and 10 HEPES (pH 7.4 adjusted by 2 M KOH). Pipette solution osmolarity was 295–305 mOsmol, and pipette resistance was 6 ~ 8 MΩ. The threshold potentials (Vts) of sequential spikes, which were the voltages of firing sequential spikes, were measured [76–80].
Data were analyzed if the recorded neurons had resting membrane potentials negatively more than 60 mV. The criteria for the acceptation of each experiment also included less than 5% changes in the resting membrane potential, spike magnitudes, and input/seal resistance. The values of sIPSCs and Vts are presented as mean ± SE. The comparisons of the data from behavior tasks, electrophysiology and cellular imaging between groups are statistically done by one-way ANOVA.
Ca2+ indicative dye was AM esters of its dye (Oregongreen BAPTA-1-AM) and astrocyte indicator was sulforhodanmine 101-AM (SR101; , in which AM element facilitated the dyes to be loaded into brain cells in slices. OGB1-AM was dissolved in DMSO and 20% Pluronic F-127 (2 g Pluronic F-127 in 10 ml DMSO) to have their stock solutions at 1 mM, and then were diluted in the oxygenated ACSF to yield its final concentration at 10 μM. SR-101 was dissolved in distilled water at 1 mM for stock solution and then dissolved in ACSF to 1 μM for the final concentration. These dyes in such solutions were loaded into the neurons and astrocytes in amygdala slices were based on a modified method . A slice was placed in an incubation chamber (1 cm in diameter) containing 2 ml of the loading solution at 35 °C for 45 min, and the loading solution was then washed out with the oxygenated ACSF. A slice was transferred to a submersion chamber (Warner RC-26 G) and perfused by the oxygenated ACSF at 2 ml/min for cellular imaging experiments.
The images of OGB-1 for Ca2+ in amygdala neurons and astrocytes and SR-101 for astrocytes were taken by using a two-photon laser scanning microscope (Olympus FV-1000, Olympus, Tokyo Japan). The 2PLSM was equipped by a two-photon laser-beam generator (Mai Tai, Physical Spectrum, USA) and a scanning system mounted onto an upright microscope (Olympus BX61WI) with water immersion objectives (40X, 0.8NA). A laser beam (810 nm) was given to excite OGB-1-AM and SR-101. The emission wave spectra were 523 nm for Ca2+-binding OGB-1 and 603 nm for SR-101, respectively. Average power delivered to the brain slices was <10 mW. The parameters set for the laser beam and photomultiplier tube were locked for two groups of slices throughout the experiments in order to have consistent condition in the comparisons of the results between DBA/2 and FVB/N mice. Images were viewed and analyzed with Fluoviewer. Data are presented as the changes in fluorescence intensity .
Both frame scanning and line scanning were applied for the imaging. The pixels crossed with a manually drawn line in the interested cells were scanned under the line scanning, in which the scanning rate reached as high as 50–200 Hz. In line scan, these areas were scanned 512 × 512 pixels. In the frame scan, 400 × 400 μm areas in amygdala slices were scanned by 320 × 320 pixels, and the rates were 5–10 frames/s. It is noteworthy that in consistence with the duration of a single spike and sequential spikes, Ca2+ signals can be classified into two phases, fast and slow phases. Based on the temporal resolution in our experiments, Ca2+ signals were activated neuronal sequential spikes. All of the frames in an independent and complete scanning acquired by a software fluoview were exported as a single movie file which was then analyzed with ImageJ software (National Institute of Health) or custom-made codes in Matlab (MathWorks).
All fluorescence signals were acquired by using Fluoviewer-10 software (Olympus Inc. Japan) and analyzed from the cell bodies in amygdala. Signals are presented as relative fluorescence change [ΔF/F = (F-Fbasal)/Fbasal] after subtracting background noise from unstained blood vessels. F is the fluorescence intensity at any time point, and Fbasal the baseline fluorescence averaged across appointed time course or the whole movie for each cell.
mx and my are the means of the corresponding series. Based on these calculations, the correlation matrices were plotted using MATLAB 7.0. All of the data are presented as mean ± SD. Student’s t tests (two-tailed, paired, or unpaired assuming unequal variances) were done in R software package, version 2.10.1 (http://www.r-project.org/), to make the statistical evaluation. A p value ≤ 0.05 was defined as a statistical significance.
This study is supported by National Award for Outstanding Young Scientist (30325021), National Basic Research Program (2011CB504405) and Natural Science Foundation China (30990261 and 81171033) to JHW.
- Bishop SJ: Neurocongnitive mechanisms of anxiety: an integrative account. Trends Cogn Sci. 2007, 11 (7): 307-316. 10.1016/j.tics.2007.05.008.PubMedGoogle Scholar
- Cameron OG: The differential diagnosis of anxiety. Psychiatric and medical disorders. Psychiatr Clin North Am. 1985, 8 (1): 3-23.PubMedGoogle Scholar
- Rickeles K, Rynn M: Overview and clinical presentation of generalized anxiety disorder. Psychiatr Clin North Am. 2001, 24 (1): 1-17. 10.1016/S0193-953X(05)70203-3.Google Scholar
- Rauch SL, Shin LM, Wright CI: Neuroimaging studies of amygdala function in anxiety disorders. Annu NY Acad Sc. 2003, 985: 389-410.Google Scholar
- Stein MB, Stein DJ: Social anxiety disorders. Lancet. 2008, 371 (9618): 1115-1125. 10.1016/S0140-6736(08)60488-2.PubMedGoogle Scholar
- Davis M: The role of the amygdala in fear and anxiety. Annu Rev Neurosci. 1992, 15: 353-375. 10.1146/annurev.ne.15.030192.002033.PubMedGoogle Scholar
- Cunnigham MG, et al: Amygdala GABAergic-rich neural grafts attenuate anxiety-like behavior in rats. Behav Brain Res. 2009, 205 (1): 146-153. 10.1016/j.bbr.2009.06.015.Google Scholar
- Anand A, Shekhar A: Brain imaging studies in mood and anxiety disorders: special emphasis on the amygdala. Annu NY Acad Sci. 2003, 985: 370-388.Google Scholar
- Bremner JD: Brain imaging in anxiety disorders. Expert Rev Neurotherapy. 2004, 4 (2): 275-284. 10.1586/1473722.214.171.1245.Google Scholar
- Craske MG, et al: What is an anxiety disorder?. Depress Anxiety. 2009, 26 (12): 1066-1085. 10.1002/da.20633.PubMedGoogle Scholar
- Damsa C, Kosel M, Moussally J: Current status of brain imaging in anxiety disorders. Curr Opin Psychiatry. 2009, 22 (1): 96-110. 10.1097/YCO.0b013e328319bd10.PubMedGoogle Scholar
- Davidson RJ: Anxiety and affective style: one of prefrontal cortex and amygdala. Biol Psychiatry. 2002, 51 (1): 68-80. 10.1016/S0006-3223(01)01328-2.PubMedGoogle Scholar
- Davis M, Rainnie D, Cassell M: Neurotransmission in the rat amygdala related to fear and anxiety. Trends Neurosci. 1994, 17 (5): 208-214. 10.1016/0166-2236(94)90106-6.PubMedGoogle Scholar
- Davis M, et al: Phasic vs. sustained fear in rats and humans: role of the extended amygdala in fear vs. anxiety. Neuropsychopharmacology. 2010, 35 (1): 105-135. 10.1038/npp.2009.109.PubMed CentralPubMedGoogle Scholar
- Delgado MR, Olsson A, Phelps EA: Extending animal models of fear conditioning to humans. Biol Psychol. 2006, 73: 39-48. 10.1016/j.biopsycho.2006.01.006.PubMedGoogle Scholar
- Freitas-Feerrari MC, et al: Neuroimaging in social anxiety disorder: A systematic review of the literature. Prog Neuropyschopharmacology Biol Psychiatry. 2010, 34 (4): 565-580. 10.1016/j.pnpbp.2010.02.028.Google Scholar
- Gallagher M, Chiba AA: The amygdala and emotion. Curr Opin Neurobiol. 1996, 6 (2): 221-227. 10.1016/S0959-4388(96)80076-6.PubMedGoogle Scholar
- Gross C, Hen R: The developmental origins of anxiety. Nat Rev Neurosci. 2004, 5: 545-552.PubMedGoogle Scholar
- Garrett A, Chang K: The role of the amygdala in bipolar disorder development. Dev Psychopathol. 2008, 20 (4): 1285-1296. 10.1017/S0954579408000618.PubMedGoogle Scholar
- LeDoux J: Emotion circuits in the brain. Annu Rev Neurosci. 2000, 23: 155-184. 10.1146/annurev.neuro.23.1.155.PubMedGoogle Scholar
- LeDoux J: The emotional brain, fear and the amygdala. Cell Mol Neurosci. 2003, 23 (4–5): 727-738.Google Scholar
- Pape HC, Pare D: Plastic synaptic networks of the amygdala for the acquisition, expression and extinction of conditioned fear. Physiological review. 2010, 90 (2): 419-463. 10.1152/physrev.00037.2009.Google Scholar
- Neugebauer V, et al: The amygdala and persistent pain. Neuroscientist. 2004, 10 (3): 221-234. 10.1177/1073858403261077.PubMedGoogle Scholar
- Roozendaal B, McEwen BS, Chattarji S: Stress, memory and amygdala. Nat Rev Neurosci. 2009, 10 (6): 423-433.PubMedGoogle Scholar
- Dent GW, O'Dell DM, Eberwine JH: Gene expression profiling in the amygdala: an approach to examine the molecular substrates of mammalian behavior. Physiological Behavior. 2001, 73 (5): 841-847. 10.1016/S0031-9384(01)00521-2.Google Scholar
- Gillespie CF, et al: Risk and resillience: genetic and environmental influences on development of the stress response. Depress Anxiety. 2009, 26 (11): 984-992. 10.1002/da.20605.PubMed CentralPubMedGoogle Scholar
- Gonda X: The serotonin transporter gene and personality: association of the 5-HTTLPR s allele, anxiety, depression and affective temperaments. Orv Hetil. 2008, 149 (33): 1569-1573. 10.1556/OH.2008.28406.PubMedGoogle Scholar
- Gross C, Hen R: Genetic and environmental factors interact to influence anxiety. Neurotoxin Research. 2004, 6 (6): 493-501. 10.1007/BF03033286.Google Scholar
- Hovatta I, et al: Glyoxalase 1 and glutathione reductase 1 regulate anxiety in ice. Nature. 2005, 438: 662-666. 10.1038/nature04250.PubMedGoogle Scholar
- McNaughton N: A gene promotes anxiety in mice-and also in scientists. Nat Med. 1999, 5 (10): 1131-1132. 10.1038/13455.PubMedGoogle Scholar
- Poulton R, Andrews G, Millichamp J: Gene-environment interaction and the anxiety disorders. Eur Arch Psychiatry Clin Neurosci. 2008, 258 (2): 65-68. 10.1007/s00406-007-0784-5.PubMedGoogle Scholar
- Sekiguchi M, et al: A deficit of brain dystrophin impairs specific amygdala GABAergic transmission and enhances defensive behaviour in mice. Brain. 2009, 132 (Pt1): 124-135.PubMedGoogle Scholar
- Wu L-J, Kim SS, Zhuo M: Molecular targets of anxiety: from membrane to nucleus. Neurochem Res. 2008, 33: 1925-1932. 10.1007/s11064-008-9679-8.PubMedGoogle Scholar
- Xu K, Emst M, Goldman D: Imaging genetics applied to anxiety, stress response and resilliency. Neuroinformatics. 2006, 4 (1): 51-64. 10.1385/NI:4:1:51.PubMedGoogle Scholar
- Shin LM, Liberzon I: The neurocircuitry of fear, stress and anxiety disorders. Neuropsychopharmacology. 2010, 35 (1): 169-191. 10.1038/npp.2009.83.PubMed CentralPubMedGoogle Scholar
- Shumyatsky GP, et al: Identification of a signaling network in lateral nucleus of amygdala important for inhibiting memory specifically related to learned fear. Cell. 2002, 111 (6): 905-918. 10.1016/S0092-8674(02)01116-9.PubMedGoogle Scholar
- Wu LJ, et al: Increased anxiety-like behavior and enhanced synaptic efficacy in the amygdala of GluR5 knockout mice. PLoS One. 2007, 2 (1): e167-10.1371/journal.pone.0000167.PubMed CentralPubMedGoogle Scholar
- Amano T, Unal CT, Pare D: Synaptic correlates of fear extinction in the amygdala. Nat Neurosci. 2010, 13 (4): 489-495. 10.1038/nn.2499.PubMed CentralPubMedGoogle Scholar
- DuBios DW, et al: Distinct functional characteristics of the lateral/basolateral amygdala GABAergic system in C57BL/6J and DBA/2J mice. J Pharmacol Exp Ther. 2006, 318 (2): 629-640. 10.1124/jpet.105.100552.Google Scholar
- Ehrlich I, et al: Amygdala inhibitory circuits and the control of fear memory. Neuron. 2009, 62: 757-771. 10.1016/j.neuron.2009.05.026.PubMedGoogle Scholar
- Pellow S, Chopin P: Validation of open:closed arm entries in an elevated plus-maze as a measure of anxiety in the rats. J Neurosci Methods. 1985, 14 (3): 149-167. 10.1016/0165-0270(85)90031-7.PubMedGoogle Scholar
- Walf AA, Frye CA: The use of elevated plus maze as an assay of anxiety-related behavior in rodents. Nat Protoc. 2007, 2 (2): 322-328. 10.1038/nprot.2007.44.PubMed CentralPubMedGoogle Scholar
- Tsien RW, et al: Multiple types of calcium channel in excitable cells. Soc Gen Physiol Ser. 1987, 41: 167-187.PubMedGoogle Scholar
- Tsien RW, Tsien RY: Calcium channels, stores, and oscillations. Annu Rev Cell Biol. 1990, 6: 715-760. 10.1146/annurev.cb.06.110190.003435.PubMedGoogle Scholar
- Zhao J, Wang D, Wang JH: Barrel cortical neurons and astrocytes coordinately respond to an increased whisker stimulus frequency. Mol Brain. 2012, 5 (12): 1-10.Google Scholar
- Golshani P, et al: Internally mediated developmental desynchronization of neocortical network activity. J Neurosci. 2009, 29 (35): 10890-10899. 10.1523/JNEUROSCI.2012-09.2009.PubMed CentralPubMedGoogle Scholar
- Hirase H, et al: Calcium dynamics of cortical astrocytic networks in vivo. PLoS Biol. 2004, 2 (4): E96-10.1371/journal.pbio.0020096.PubMed CentralPubMedGoogle Scholar
- Takata N, Hirase H: Cortical layer 1 and layer 2/3 astrocytes exhibit distinct calcium dynamics in vivo. PLoS One. 2008, 3 (6): e2525-10.1371/journal.pone.0002525.PubMed CentralPubMedGoogle Scholar
- Beierlein M, Gibson JR, Connors BW: A network of electrical coupled interneurons drives synchronized inhibition in neocortex. Nat Neurosci. 2000, 3 (9): 904-910. 10.1038/78809.PubMedGoogle Scholar
- Long MA, et al: Electrical synapses coordinate activity in the suprachiasmatic nucleus. Nat Neurosci. 2005, 8 (1): 61-66. 10.1038/nn1361.PubMedGoogle Scholar
- Fanselow EE, Richardson KA, Connors BW: Selective, state-dependent activation of somatostain-expressing inhibitory interneurons in mouse neocortex. J Neurophysiol. 2008, 100 (5): 2640-2652. 10.1152/jn.90691.2008.PubMed CentralPubMedGoogle Scholar
- Klausberger T, Somogyi P: Neuronal diversity and temporal dynamics: the unity of hippocampal circuit operations. Science. 2008, 321: 53-57. 10.1126/science.1149381.PubMed CentralPubMedGoogle Scholar
- McBain CJ, Fisahn A: Interneurons unbound. Nat Rev Neurosci. 2001, 2: 11-23.PubMedGoogle Scholar
- Somogyi P, Klausberger T: Defined types of cortical interneurone structure space and spike timing in the hippocampus. Journal of Physiology (London). 2005, 562 (1): 9-29.Google Scholar
- Wehr M, Zador AM: Balanced inhibition underlies tuning and sharpens spike timing in auditory cortex. Nature. 2003, 426: 442-446. 10.1038/nature02116.PubMedGoogle Scholar
- Chen N, et al: After-hyperpolarization improves spike programming through lowering threshold potentials and refractory periods mediated by voltage-gated sodium channels. Biochem Biophys Res Commun. 2006, 346: 938-945. 10.1016/j.bbrc.2006.06.003.PubMedGoogle Scholar
- Chen N, et al: Sodium channel-mediated intrinsic mechanisms underlying the differences of spike programming among GABAergic neurons. Biochem Biophys Res Commun. 2006, 346: 281-287. 10.1016/j.bbrc.2006.05.120.PubMedGoogle Scholar
- Salah A, Perkins KL: Effects of subtype-selective group I mGluR antagonists on synchronous activity induced by 4-aminopyridine/CGP 55845 in adult guinea pig hippocampal slices. Neuropharmacology. 2008, 55 (1): 47-54. 10.1016/j.neuropharm.2008.04.010.PubMed CentralPubMedGoogle Scholar
- Kim SS, et al: Neurabin in the anterior cingulate cortex regulates anxiety-like behavior in adult mice. Mol Brain. 2011, 4: 6-10.1186/1756-6606-4-6.PubMed CentralPubMedGoogle Scholar
- Barot SK, et al: Functional imaging of stimulus convergence in amygdalar neurons during Pavlovian fear conditioning. PLoS One. 2009, 4 (7): e6156-10.1371/journal.pone.0006156.PubMed CentralPubMedGoogle Scholar
- Oler JA, et al: Amygdalar and hippocampal substrates of anxious temperament differ in their heritability. Nature. 2010, 466 (7308): 864-868. 10.1038/nature09282.PubMed CentralPubMedGoogle Scholar
- Charney DS: Neuroanatomical circuits modulating fear and anxiety behavior. Acta Psychiatry Scand. Suppl. 2003, 417: 38-50.Google Scholar
- Dell'Osso B, et al: Serotonin norepinephrine reuptake inhibitors (SNRIs) in anxiety disorders: a comprehensive review of their clinical efficacy. Hum Psychopharmacol. 2010, 25 (1): 17-29. 10.1002/hup.1074.PubMedGoogle Scholar
- Mathew SJ, Price RB, Charney DS: Recent advances in the neurobiology of anxiety disorders: implications for novel therapeutics. Am J Med Genet C Semin Med Genet. 2008, 148C (2): 89-98. 10.1002/ajmg.c.30172.PubMedGoogle Scholar
- Siever LJ, Weinstein LN: The neurobiology of personality disorders: implications for psychoanalysis. J Am Psychoanal Assoc. 2009, 57 (2): 361-398. 10.1177/0003065109333502.PubMedGoogle Scholar
- Ravindran LN, Stein MB: The pharmacologic treatment of anxiety disorders: a review of progress. J Clin Psychiatry. 2010, 71 (7): 839-854. 10.4088/JCP.10r06218blu.PubMedGoogle Scholar
- Krystal JH, et al: Potential psychiatric applications of metabotropic glutamate receptor agonists and antagonists. CNS Drugs. 2010, 24 (8): 669-693. 10.2165/11533230-000000000-00000.PubMedGoogle Scholar
- Lima VC, et al: Modulation of defensive responses and anxiety-like behaviors by group I metabotropic glutamate receptors located in the dorsolateral periaqueductal gray. Prog Neuropsychopharmacol Biol Psychiatry. 2008, 32 (1): 178-185. 10.1016/j.pnpbp.2007.08.006.PubMedGoogle Scholar
- Muly EC, et al: Group II metabotropic glutamate receptors in anxiety circuitry: correspondence of physiological response and subcellular distribution. J Comp Neurol. 2007, 505 (6): 682-700. 10.1002/cne.21525.PubMedGoogle Scholar
- Lapin IP: Only controls: Effect of handling, sham injection and intraperitoneal injection of saline on behavior of mice in an elevated plus-maze. J Pharmacol Toxicol Methods. 1995, 34 (1): 73-77.PubMedGoogle Scholar
- Ge R, Qian H, Wang JH: Physiological synaptic signals initiate sequential spikes at soma of cortical pyramidal neurons. Mol Brain. 2011, 4 (1): 19-10.1186/1756-6606-4-19.PubMed CentralPubMedGoogle Scholar
- Wang J-H: Short-term cerebral ischemia causes the dysfunction of interneurons and more excitation of pyramidal neurons. Brain Res Bull. 2003, 60 (1–2): 53-58.PubMedGoogle Scholar
- Yu J, et al: Quantal glutamate release is essential for reliable neuronal encodings in cerebral networks. PLoS One. 2011, 6 (9): e25219-10.1371/journal.pone.0025219.PubMed CentralPubMedGoogle Scholar
- Wang J-H, Stelzer A: Shared calcium signaling pathways in the induction of long-term potentiation and synaptic disinhibition in CA1 pyramidal cell dendrites. J Neurophysiol. 1996, 75: 1687-1702.PubMedGoogle Scholar
- Wei J, et al: Ca2 + −calmodulin signalling pathway upregulates GABA synaptic transmission through cytoskeleton-mediated mechanisms. Neurosci. 2004, 127: 637-647. 10.1016/j.neuroscience.2004.05.056.Google Scholar
- Chen N, et al: The refractory periods and threshold potentials of sequential spikes measured by whole-cell recordings. Biochem Biophys Res Commun. 2006, 340: 151-157. 10.1016/j.bbrc.2005.11.170.PubMedGoogle Scholar
- Chen N, Chen X, Wang J-H: Homeostasis established by coordination of subcellular compartment plasticity improves spike encoding. J Cell Sci. 2008, 121 (17): 2961-2971. 10.1242/jcs.022368.PubMedGoogle Scholar
- Chen N, et al: Axons amplify somatic incomplete spikes into uniform amplitudes in mouse cortical pyramidal neurons. PLoS One. 2010, 5 (7): e11868-10.1371/journal.pone.0011868.PubMed CentralPubMedGoogle Scholar
- Ni H, et al: Upregulation of barrel GABAergic neurons is associated with cross-modal plasticity in olfactory deficit. PLoS One. 2010, 5 (10): e13736-10.1371/journal.pone.0013736.PubMed CentralPubMedGoogle Scholar
- Wang JH, et al: The gain and fidelity of transmission patterns at cortical excitatory unitary synapses improve spike encoding. J Cell Sci. 2008, 121 (17): 2951-2960. 10.1242/jcs.025684.PubMedGoogle Scholar
- Ikegaya Y, Le Bon-Jego M, Yuste R: Large-scale imaging of cortical network activity with calcium indicators. Neurosci Res. 2005, 52 (2): 132-138. 10.1016/j.neures.2005.02.004.PubMedGoogle Scholar
- Huang L, et al: Ca2+ and acidosis synergistically lead to the dysfunction of cortical GABAergic neurons during ischemia. Biochem Biophys Res Commun. 2010, 394: 709-714. 10.1016/j.bbrc.2010.03.056.PubMedGoogle Scholar
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