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Impaired fast-spiking interneuron function in a genetic mouse model of depression.

Sauer JF, Strüber M, Bartos M - Elife (2015)

Bottom Line: The number of FS-INs is reduced, they receive fewer excitatory inputs, and form fewer release sites on targets.Computational analysis indicates that weak excitatory input and inhibitory output of FS-INs may lead to impaired gamma oscillations.Our data link network defects with a gene mutation underlying depression in humans.

View Article: PubMed Central - PubMed

Affiliation: Physiologisches Institut I, Systemic and Cellular Neurophysiology, Albert-Ludwigs-Universität Freiburg, Freiburg, Germany.

ABSTRACT
Rhythmic neuronal activity provides a frame for information coding by co-active cell assemblies. Abnormal brain rhythms are considered as potential pathophysiological mechanisms causing mental disease, but the underlying network defects are largely unknown. We find that mice expressing truncated Disrupted-in-Schizophrenia 1 (Disc1), which mirror a high-prevalence genotype for human psychiatric illness, show depression-related behavior. Theta and low-gamma synchrony in the prelimbic cortex (PrlC) is impaired in Disc1 mice and inversely correlated with the extent of behavioural despair. While weak theta activity is driven by the hippocampus, disturbance of low-gamma oscillations is caused by local defects of parvalbumin (PV)-expressing fast-spiking interneurons (FS-INs). The number of FS-INs is reduced, they receive fewer excitatory inputs, and form fewer release sites on targets. Computational analysis indicates that weak excitatory input and inhibitory output of FS-INs may lead to impaired gamma oscillations. Our data link network defects with a gene mutation underlying depression in humans.

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Characteristics of Disc1 and control low-gamma oscillations at different excitatory drives.(A) Control (black) and Disc1 (green) network activity was quantified by means of the LFP (left) and the average discharge rate (right) at different excitation strengths. Excitatory drive was modelled as Poisson-distributed excitatory postsynaptic conductances. A variable fraction of the PC population (0–50%) received excitatory inputs at 0.6 kHz. In contrast, 80% of the FS-INs were excited at varying mean frequencies (0.4–1 kHz). Top left, during conditions of strong excitation of FS-INs and weak excitation of PCs, oscillation frequency was high (>60 Hz) because FS-INs were highly active and PCs were silent. This corresponds to a gamma rhythm mediated by a network of mutually connected FS-INs (interneuron gamma (ING)-mechanism). Shifting the excitation away from the FS-INs and recruiting more PCs reduced the oscillation frequency and established a gamma rhythm mediated by recurrent PC-IN connections (pyramidal-interneuron gamma (PING)-mechanism). Bottom left, highest power of gamma activity was observed in the PING regime, where most of the analysis was performed (see Figure 5C–E). (B) Top, schematic illustrating the PC sync measure as a quantification of PC spike timing relative to FS-IN activity (‘Materials and methods’). Bottom, in the PING regime (high PC drive, low FS-IN drive), PCs in the control network display much higher spike time fidelity than Disc1 PCs.DOI:http://dx.doi.org/10.7554/eLife.04979.024
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fig5s1: Characteristics of Disc1 and control low-gamma oscillations at different excitatory drives.(A) Control (black) and Disc1 (green) network activity was quantified by means of the LFP (left) and the average discharge rate (right) at different excitation strengths. Excitatory drive was modelled as Poisson-distributed excitatory postsynaptic conductances. A variable fraction of the PC population (0–50%) received excitatory inputs at 0.6 kHz. In contrast, 80% of the FS-INs were excited at varying mean frequencies (0.4–1 kHz). Top left, during conditions of strong excitation of FS-INs and weak excitation of PCs, oscillation frequency was high (>60 Hz) because FS-INs were highly active and PCs were silent. This corresponds to a gamma rhythm mediated by a network of mutually connected FS-INs (interneuron gamma (ING)-mechanism). Shifting the excitation away from the FS-INs and recruiting more PCs reduced the oscillation frequency and established a gamma rhythm mediated by recurrent PC-IN connections (pyramidal-interneuron gamma (PING)-mechanism). Bottom left, highest power of gamma activity was observed in the PING regime, where most of the analysis was performed (see Figure 5C–E). (B) Top, schematic illustrating the PC sync measure as a quantification of PC spike timing relative to FS-IN activity (‘Materials and methods’). Bottom, in the PING regime (high PC drive, low FS-IN drive), PCs in the control network display much higher spike time fidelity than Disc1 PCs.DOI:http://dx.doi.org/10.7554/eLife.04979.024

Mentions: In the Disc1 PrlC fewer FS-INs redistribute their weaker outputs to a higher number of PCs and receive fewer glutamatergic inputs. To address whether these alterations influence the synchrony of low-gamma oscillations, we designed computational neuronal network models with synaptically connected FS-INs and PCs and compared scenarios with experimentally-driven synaptic properties and connectivities from Disc1 and control prefrontal cortices (Wang and Buzsáki, 1996) (Figure 5, Table 1, Table 2). Both network models generated synchronous low-gamma activity patterns (Figure 5B). These oscillations were generated by a recurrent PC → FS-IN → PC network over a broad range of excitatory drives provided to both FS-INs and PCs (Figure 5C, Figure 5—figure supplement 1), in agreement with current theories on the generation of gamma rhythms in cortical networks (Tiesinga and Sejnowski, 2009). Consistent with gamma oscillations in prefrontal areas of rodents (Massi et al., 2012) and monkeys (Wilson et al., 1994), INs discharged at higher rates than PCs (mean fAP; Figure 5B). Spike histograms as well as LFP analogs demonstrated high synchrony of low-gamma activity in the control network model (Figure 5B,C; black). In contrast, reduced synchrony of low-gamma emerged in the Disc1 circuit (Figure 5B,C; green; Figure 5—figure supplement 1). Precise timing of PC activity was proposed an important requirement for information processing (Uhlhaas and Singer, 2010). Cross-correlation analysis of FS-IN and PC discharges and quantification of PC spike times in relation to FS-IN activity revealed that spike timing fidelity of PCs was high in the control but strongly reduced in the Disc 1 network model (Figure 5C; Figure 5—figure supplement 1). These findings were robust over a wide range of excitatory regimes (Figure 5—figure supplement 1).10.7554/eLife.04979.023Figure 5.Disc1-mediated circuit changes impair low-gamma power in a network model.


Impaired fast-spiking interneuron function in a genetic mouse model of depression.

Sauer JF, Strüber M, Bartos M - Elife (2015)

Characteristics of Disc1 and control low-gamma oscillations at different excitatory drives.(A) Control (black) and Disc1 (green) network activity was quantified by means of the LFP (left) and the average discharge rate (right) at different excitation strengths. Excitatory drive was modelled as Poisson-distributed excitatory postsynaptic conductances. A variable fraction of the PC population (0–50%) received excitatory inputs at 0.6 kHz. In contrast, 80% of the FS-INs were excited at varying mean frequencies (0.4–1 kHz). Top left, during conditions of strong excitation of FS-INs and weak excitation of PCs, oscillation frequency was high (>60 Hz) because FS-INs were highly active and PCs were silent. This corresponds to a gamma rhythm mediated by a network of mutually connected FS-INs (interneuron gamma (ING)-mechanism). Shifting the excitation away from the FS-INs and recruiting more PCs reduced the oscillation frequency and established a gamma rhythm mediated by recurrent PC-IN connections (pyramidal-interneuron gamma (PING)-mechanism). Bottom left, highest power of gamma activity was observed in the PING regime, where most of the analysis was performed (see Figure 5C–E). (B) Top, schematic illustrating the PC sync measure as a quantification of PC spike timing relative to FS-IN activity (‘Materials and methods’). Bottom, in the PING regime (high PC drive, low FS-IN drive), PCs in the control network display much higher spike time fidelity than Disc1 PCs.DOI:http://dx.doi.org/10.7554/eLife.04979.024
© Copyright Policy
Related In: Results  -  Collection

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Show All Figures
getmorefigures.php?uid=PMC4374525&req=5

fig5s1: Characteristics of Disc1 and control low-gamma oscillations at different excitatory drives.(A) Control (black) and Disc1 (green) network activity was quantified by means of the LFP (left) and the average discharge rate (right) at different excitation strengths. Excitatory drive was modelled as Poisson-distributed excitatory postsynaptic conductances. A variable fraction of the PC population (0–50%) received excitatory inputs at 0.6 kHz. In contrast, 80% of the FS-INs were excited at varying mean frequencies (0.4–1 kHz). Top left, during conditions of strong excitation of FS-INs and weak excitation of PCs, oscillation frequency was high (>60 Hz) because FS-INs were highly active and PCs were silent. This corresponds to a gamma rhythm mediated by a network of mutually connected FS-INs (interneuron gamma (ING)-mechanism). Shifting the excitation away from the FS-INs and recruiting more PCs reduced the oscillation frequency and established a gamma rhythm mediated by recurrent PC-IN connections (pyramidal-interneuron gamma (PING)-mechanism). Bottom left, highest power of gamma activity was observed in the PING regime, where most of the analysis was performed (see Figure 5C–E). (B) Top, schematic illustrating the PC sync measure as a quantification of PC spike timing relative to FS-IN activity (‘Materials and methods’). Bottom, in the PING regime (high PC drive, low FS-IN drive), PCs in the control network display much higher spike time fidelity than Disc1 PCs.DOI:http://dx.doi.org/10.7554/eLife.04979.024
Mentions: In the Disc1 PrlC fewer FS-INs redistribute their weaker outputs to a higher number of PCs and receive fewer glutamatergic inputs. To address whether these alterations influence the synchrony of low-gamma oscillations, we designed computational neuronal network models with synaptically connected FS-INs and PCs and compared scenarios with experimentally-driven synaptic properties and connectivities from Disc1 and control prefrontal cortices (Wang and Buzsáki, 1996) (Figure 5, Table 1, Table 2). Both network models generated synchronous low-gamma activity patterns (Figure 5B). These oscillations were generated by a recurrent PC → FS-IN → PC network over a broad range of excitatory drives provided to both FS-INs and PCs (Figure 5C, Figure 5—figure supplement 1), in agreement with current theories on the generation of gamma rhythms in cortical networks (Tiesinga and Sejnowski, 2009). Consistent with gamma oscillations in prefrontal areas of rodents (Massi et al., 2012) and monkeys (Wilson et al., 1994), INs discharged at higher rates than PCs (mean fAP; Figure 5B). Spike histograms as well as LFP analogs demonstrated high synchrony of low-gamma activity in the control network model (Figure 5B,C; black). In contrast, reduced synchrony of low-gamma emerged in the Disc1 circuit (Figure 5B,C; green; Figure 5—figure supplement 1). Precise timing of PC activity was proposed an important requirement for information processing (Uhlhaas and Singer, 2010). Cross-correlation analysis of FS-IN and PC discharges and quantification of PC spike times in relation to FS-IN activity revealed that spike timing fidelity of PCs was high in the control but strongly reduced in the Disc 1 network model (Figure 5C; Figure 5—figure supplement 1). These findings were robust over a wide range of excitatory regimes (Figure 5—figure supplement 1).10.7554/eLife.04979.023Figure 5.Disc1-mediated circuit changes impair low-gamma power in a network model.

Bottom Line: The number of FS-INs is reduced, they receive fewer excitatory inputs, and form fewer release sites on targets.Computational analysis indicates that weak excitatory input and inhibitory output of FS-INs may lead to impaired gamma oscillations.Our data link network defects with a gene mutation underlying depression in humans.

View Article: PubMed Central - PubMed

Affiliation: Physiologisches Institut I, Systemic and Cellular Neurophysiology, Albert-Ludwigs-Universität Freiburg, Freiburg, Germany.

ABSTRACT
Rhythmic neuronal activity provides a frame for information coding by co-active cell assemblies. Abnormal brain rhythms are considered as potential pathophysiological mechanisms causing mental disease, but the underlying network defects are largely unknown. We find that mice expressing truncated Disrupted-in-Schizophrenia 1 (Disc1), which mirror a high-prevalence genotype for human psychiatric illness, show depression-related behavior. Theta and low-gamma synchrony in the prelimbic cortex (PrlC) is impaired in Disc1 mice and inversely correlated with the extent of behavioural despair. While weak theta activity is driven by the hippocampus, disturbance of low-gamma oscillations is caused by local defects of parvalbumin (PV)-expressing fast-spiking interneurons (FS-INs). The number of FS-INs is reduced, they receive fewer excitatory inputs, and form fewer release sites on targets. Computational analysis indicates that weak excitatory input and inhibitory output of FS-INs may lead to impaired gamma oscillations. Our data link network defects with a gene mutation underlying depression in humans.

Show MeSH
Related in: MedlinePlus