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Ovarian cycle-linked plasticity of δ-GABAA receptor subunits in hippocampal interneurons affects γ oscillations in vivo.

Barth AM, Ferando I, Mody I - Front Cell Neurosci (2014)

Bottom Line: Here we show δ-GABAARs changes during the mouse ovarian cycle in hippocampal cell types, with enhanced expression during diestrus in principal cells and specific INs.Such recurring changes in γ magnitude were not observed in non-cycling wild-type (WT) females, cycling females lacking δ-GABAARs only on PV-INs (PV-Gabrd (-/-)), and in male mice during a time course equivalent to the ovarian cycle.Our findings may explain the impaired memory and cognitive performance experienced by women with premenstrual syndrome (PMS) or premenstrual dysphoric disorder (PMDD).

View Article: PubMed Central - PubMed

Affiliation: Department of Neurology, The David Geffen School of Medicine, University of California at Los Angeles Los Angeles, CA, USA.

ABSTRACT
GABAA receptors containing δ subunits (δ-GABAARs) are GABA-gated ion channels with extra- and perisynaptic localization, strong sensitivity to neurosteroids (NS), and a high degree of plasticity. In selective brain regions they are expressed on specific principal cells and interneurons (INs), and generate a tonic conductance that controls neuronal excitability and oscillations. Plasticity of δ-GABAARs in principal cells has been described during states of altered NS synthesis including acute stress, puberty, ovarian cycle, pregnancy and the postpartum period, with direct consequences on neuronal excitability and network dynamics. The defining network events implicated in cognitive function, memory formation and encoding are γ oscillations (30-120 Hz), a well-timed loop of excitation and inhibition between principal cells and PV-expressing INs (PV + INs). The δ-GABAARs of INs can modify γ oscillations, and a lower expression of δ-GABAARs on INs during pregnancy alters γ frequency recorded in vitro. The ovarian cycle is another physiological event with large fluctuations in NS levels and δ-GABAARs. Stages of the cycle are paralleled by swings in memory performance, cognitive function, and mood in both humans and rodents. Here we show δ-GABAARs changes during the mouse ovarian cycle in hippocampal cell types, with enhanced expression during diestrus in principal cells and specific INs. The plasticity of δ-GABAARs on PV-INs decreases the magnitude of γ oscillations continuously recorded in area CA1 throughout several days in vivo during diestrus and increases it during estrus. Such recurring changes in γ magnitude were not observed in non-cycling wild-type (WT) females, cycling females lacking δ-GABAARs only on PV-INs (PV-Gabrd (-/-)), and in male mice during a time course equivalent to the ovarian cycle. Our findings may explain the impaired memory and cognitive performance experienced by women with premenstrual syndrome (PMS) or premenstrual dysphoric disorder (PMDD).

No MeSH data available.


Related in: MedlinePlus

Separation of behavioral states based on synchronous video and local field potential recordings. (A) Activity values plotted against the Hilbert magnitudes in the δ frequency range (1–4 Hz) for each 1 s long epoch (total: 86,400 epochs) during a full day of synchronous video-local field potential recording. Note the appearance of three clusters in the point cloud. The red rectangle delineates the point cluster corresponding to the putative REM sleep. (B) Separation of behavioral states based on combined activity and electrographic thresholds over an ∼12 min period. Bottom: local field potential recording, above: 1 s binned Hilbert magnitude of the δ-frequency range, above: activity graph, top: step function showing behavioral states based on activity and δ magnitude values (see text for details; REM, REM-sleep; NREM, NREM-sleep; Mvmt, movement; ND, not determined). For the detailed explanation of the applied calculations please refer to the Sections “Materials and Methods,” and “Electrophysiology Data Analysis.”
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Figure 1: Separation of behavioral states based on synchronous video and local field potential recordings. (A) Activity values plotted against the Hilbert magnitudes in the δ frequency range (1–4 Hz) for each 1 s long epoch (total: 86,400 epochs) during a full day of synchronous video-local field potential recording. Note the appearance of three clusters in the point cloud. The red rectangle delineates the point cluster corresponding to the putative REM sleep. (B) Separation of behavioral states based on combined activity and electrographic thresholds over an ∼12 min period. Bottom: local field potential recording, above: 1 s binned Hilbert magnitude of the δ-frequency range, above: activity graph, top: step function showing behavioral states based on activity and δ magnitude values (see text for details; REM, REM-sleep; NREM, NREM-sleep; Mvmt, movement; ND, not determined). For the detailed explanation of the applied calculations please refer to the Sections “Materials and Methods,” and “Electrophysiology Data Analysis.”

Mentions: Video and local field potential recordings were started after 2–3 days of habituation to the recording home cage. Data were analyzed in 24 h long epochs. Local field potential recordings were filtered in the δ range (1–4 Hz) and the δ magnitude was calculated using the Hilbert transformation. Both activity values deriving from the video data and delta magnitudes were binned at 1 s bin width. The binned activity values were plotted against the binned delta magnitudes for a 24 h-long session. Based on the point clouds, 3 clusters were separated (low δ + high activity, low δ + low activity, high δ + low activity) and thresholds for δ and activity values between the clusters were determined (Figure 1A).


Ovarian cycle-linked plasticity of δ-GABAA receptor subunits in hippocampal interneurons affects γ oscillations in vivo.

Barth AM, Ferando I, Mody I - Front Cell Neurosci (2014)

Separation of behavioral states based on synchronous video and local field potential recordings. (A) Activity values plotted against the Hilbert magnitudes in the δ frequency range (1–4 Hz) for each 1 s long epoch (total: 86,400 epochs) during a full day of synchronous video-local field potential recording. Note the appearance of three clusters in the point cloud. The red rectangle delineates the point cluster corresponding to the putative REM sleep. (B) Separation of behavioral states based on combined activity and electrographic thresholds over an ∼12 min period. Bottom: local field potential recording, above: 1 s binned Hilbert magnitude of the δ-frequency range, above: activity graph, top: step function showing behavioral states based on activity and δ magnitude values (see text for details; REM, REM-sleep; NREM, NREM-sleep; Mvmt, movement; ND, not determined). For the detailed explanation of the applied calculations please refer to the Sections “Materials and Methods,” and “Electrophysiology Data Analysis.”
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4128222&req=5

Figure 1: Separation of behavioral states based on synchronous video and local field potential recordings. (A) Activity values plotted against the Hilbert magnitudes in the δ frequency range (1–4 Hz) for each 1 s long epoch (total: 86,400 epochs) during a full day of synchronous video-local field potential recording. Note the appearance of three clusters in the point cloud. The red rectangle delineates the point cluster corresponding to the putative REM sleep. (B) Separation of behavioral states based on combined activity and electrographic thresholds over an ∼12 min period. Bottom: local field potential recording, above: 1 s binned Hilbert magnitude of the δ-frequency range, above: activity graph, top: step function showing behavioral states based on activity and δ magnitude values (see text for details; REM, REM-sleep; NREM, NREM-sleep; Mvmt, movement; ND, not determined). For the detailed explanation of the applied calculations please refer to the Sections “Materials and Methods,” and “Electrophysiology Data Analysis.”
Mentions: Video and local field potential recordings were started after 2–3 days of habituation to the recording home cage. Data were analyzed in 24 h long epochs. Local field potential recordings were filtered in the δ range (1–4 Hz) and the δ magnitude was calculated using the Hilbert transformation. Both activity values deriving from the video data and delta magnitudes were binned at 1 s bin width. The binned activity values were plotted against the binned delta magnitudes for a 24 h-long session. Based on the point clouds, 3 clusters were separated (low δ + high activity, low δ + low activity, high δ + low activity) and thresholds for δ and activity values between the clusters were determined (Figure 1A).

Bottom Line: Here we show δ-GABAARs changes during the mouse ovarian cycle in hippocampal cell types, with enhanced expression during diestrus in principal cells and specific INs.Such recurring changes in γ magnitude were not observed in non-cycling wild-type (WT) females, cycling females lacking δ-GABAARs only on PV-INs (PV-Gabrd (-/-)), and in male mice during a time course equivalent to the ovarian cycle.Our findings may explain the impaired memory and cognitive performance experienced by women with premenstrual syndrome (PMS) or premenstrual dysphoric disorder (PMDD).

View Article: PubMed Central - PubMed

Affiliation: Department of Neurology, The David Geffen School of Medicine, University of California at Los Angeles Los Angeles, CA, USA.

ABSTRACT
GABAA receptors containing δ subunits (δ-GABAARs) are GABA-gated ion channels with extra- and perisynaptic localization, strong sensitivity to neurosteroids (NS), and a high degree of plasticity. In selective brain regions they are expressed on specific principal cells and interneurons (INs), and generate a tonic conductance that controls neuronal excitability and oscillations. Plasticity of δ-GABAARs in principal cells has been described during states of altered NS synthesis including acute stress, puberty, ovarian cycle, pregnancy and the postpartum period, with direct consequences on neuronal excitability and network dynamics. The defining network events implicated in cognitive function, memory formation and encoding are γ oscillations (30-120 Hz), a well-timed loop of excitation and inhibition between principal cells and PV-expressing INs (PV + INs). The δ-GABAARs of INs can modify γ oscillations, and a lower expression of δ-GABAARs on INs during pregnancy alters γ frequency recorded in vitro. The ovarian cycle is another physiological event with large fluctuations in NS levels and δ-GABAARs. Stages of the cycle are paralleled by swings in memory performance, cognitive function, and mood in both humans and rodents. Here we show δ-GABAARs changes during the mouse ovarian cycle in hippocampal cell types, with enhanced expression during diestrus in principal cells and specific INs. The plasticity of δ-GABAARs on PV-INs decreases the magnitude of γ oscillations continuously recorded in area CA1 throughout several days in vivo during diestrus and increases it during estrus. Such recurring changes in γ magnitude were not observed in non-cycling wild-type (WT) females, cycling females lacking δ-GABAARs only on PV-INs (PV-Gabrd (-/-)), and in male mice during a time course equivalent to the ovarian cycle. Our findings may explain the impaired memory and cognitive performance experienced by women with premenstrual syndrome (PMS) or premenstrual dysphoric disorder (PMDD).

No MeSH data available.


Related in: MedlinePlus