Down syndrome is a genetic disorder caused by the presence of a third copy of chromosome 21. Affected individuals show delayed growth, characteristic facial features, altered brain development; with mild to severe intellectual disability. The exact mechanisms underlying the intellectual disability in Down syndrome are unclear, although studies in mice have provided clues. Drugs that reduce the inhibitory activity in the brain improve cognition in a mouse model of Down syndrome. This suggests that excessive inhibitory activity may contribute to the cognitive impairments.

Many different neural circuits generate inhibitory activity in the brain. These circuits contain cells called interneurons. Sub-types of interneurons act via different mechanisms to reduce the activity of neurons. Identifying the interneurons that are affected in Down syndrome would thus improve our understanding of the brain basis of the disorder.

Zorrilla de San Martin et al. compared mice with Down syndrome to unaffected control mice. The results revealed an increased activity in two types of inhibitory brain circuits in Down syndrome. The first contains interneurons called Martinotti cells. These help the brain to combine inputs from different sources. The second contains interneurons called parvalbumin-positive basket cells. These help different areas of the brain to synchronize their activity, which in turn makes it easier for those areas to exchange information.

By mapping the changes in inhibitory circuits in Down syndrome, Zorrilla de San Martin et al. have provided new insights into the biological basis of the disorder. Future studies should examine whether targeting specific circuits with pharmacological treatments could ultimately help reduce the associated impairments.

Down syndrome (DS) is a condition caused by full or partial trisomy of human chromosome 21, characterized by various physical and neurological features including mild to severe intellectual disability (Antonarakis et al., 2020). Individuals with DS present important deficits in cognitive tasks known to depend on the anatomical and functional integrity of the frontal lobe (Lee et al., 2015). Moreover, DS is also associated with other CNS-mediated phenotypes, including an ultra-high risk for developing Alzheimer’s disease and high rates of autism for which the mechanisms are unknown (DiGuiseppi et al., 2010; Wiseman et al., 2015). Interventions to ameliorate DS-mediated cognitive dysfunctions are limited. The development of interventions for this vulnerable group of individuals can be achieved through a better understanding of the mechanisms underlying a core feature of DS, such as intellectual disability.

Importantly, mouse models of DS recapitulate several cognitive deficits of this condition (Herault et al., 2017; Olmos-Serrano et al., 2016b). One of the best-characterized mouse models is the Ts65Dn mouse line (herein referred to as Ts), which carries a partial trisomy of a segment of the mouse chromosome 16 (Davisson et al., 1993). Ts mice recapitulate several dysfunctions present in DS individuals, such as reduced birthweight, male sterility, abnormal facial appearance and several cognitive impairments, including executive functions, such as working memory and cognitive flexibility (Olmos-Serrano et al., 2016b).

Recovery of behavioral and neurophysiological deficits underlying cognitive impairments using GABA_A receptor blockers led to the hypothesis that intellectual deficits in DS are produced by an excessive activity of inhibitory circuits (Fernandez et al., 2007; Zorrilla de San Martin et al., 2018). Nonetheless, direct evidence for over-inhibition in DS is lacking. Moreover, given the anatomical, molecular and functional diversity of cortical inhibitory neurons (Tremblay et al., 2016), the functional implications of this hypothesis at the network level, as well as the involvement of specific GABAergic circuits remain obscure.

Executive functions depend on the integrity of the prefrontal cortex (PFC), which plays an essential role in the synchronization of task-relevant, large-scale neuronal activity (Helfrich and Knight, 2016). An important network correlate of this synchronization is represented by neuronal oscillations: rhythmic fluctuations of the electrical activity of single neurons, local neuronal populations and multiple neuronal assemblies, distributed across different brain regions (Buzsáki and Wang, 2012). Oscillations are the result of a balanced and coordinated activity of excitatory pyramidal neurons (PNs) and a rich diversity of inhibitory neurons that use γ-aminobutiric acid (GABA) as neurotransmitter. In particular, parvalbumin (PV)-positive inhibitory interneurons form synapses onto the perisomatic region of PNs. PV cells thus tightly control PN spiking activity and drive network oscillations in the γ-frequency range (30–100 Hz) (Buzsáki and Wang, 2012). γ-Oscillations are necessary for several PFC cognitive functions, such as sustained attention (Kim et al., 2016b) and cognitive flexibility (Cho et al., 2015). Conversely, Martinotti cells (MCs) are somatostatin (SST)-positive interneurons that inhibit distal dendrites of PNs, thereby controlling the integration of distal dendritic glutamatergic synaptic inputs originating from different regions of the brain (Tremblay et al., 2016). Dendritic integration of multi-pathway inputs is necessary for working memory (Abbas et al., 2018; Kim et al., 2016a). Therefore, PV interneurons and MCs represent two major cortical inhibitory circuits, characterized by a precise division of labor during cortical activity. Both forms of inhibition were shown to be involved in the entrainment of network oscillations (Cardin et al., 2009; Chen et al., 2017; Sohal et al., 2009; Veit et al., 2017) and in the cognitive performance during medial (m)PFC-dependent tasks (Abbas et al., 2018; Cho et al., 2015; Cummings and Clem, 2020). In particular, inhibition from SST interneurons plays a crucial role in mPFC-dependent memory (Abbas et al., 2018; Cummings and Clem, 2020).

Broad-spectrum GABA_AR antagonists are not clinically viable, as they can yield undesired seizure-like activity and/or anxiety. Interestingly, however, treatment of Ts mice with selective and partial negative allosteric modulators of α5-containing GABA_ARs (α5 inverse agonist or α5IA) reverse cognitive behavioral and long-term synaptic plasticity deficits in DS mice (Braudeau et al., 2011; Duchon et al., 2020; Martínez-Cué et al., 2013; Schulz et al., 2019). Importantly, neocortical dendritic synaptic inhibition of PNs from MCs relies on α5-containing GABA_ARs (Ali and Thomson, 2008). The preference for this specific GABA_AR subunit was also recently demonstrated at the equivalent hippocampal dendritic inhibitory circuit (Schulz et al., 2019; Schulz et al., 2018), raising the question of whether dendritic inhibition is specifically altered in DS.

Here we found that the dendritic synaptic inhibitory loop formed by MCs and PNs was strongly potentiated in Ts mice, with no alteration of either cell-type excitability. Conversely, the perisomatic synaptic inhibitory loop from PV cells onto PN cell bodies was unaffected in Ts mice. Strikingly, however, PV-cell excitability was strongly altered: these interneurons did not display their typical fast-spiking behavior and exhibited enhanced excitability. At the network level in vivo, these inhibitory microcircuit-specific alterations resulted in significant reduction of putative PN firing, which in turn was more tuned to β- and low γ-oscillations (10–60 Hz). These results confirm over-inhibition in DS, and reveal unexpected functional alterations of specific GABAergic circuits in this condition.

In this study, we analyzed synaptic and intrinsic properties of two major inhibitory circuits of the prefrontal cortex in a relevant mouse model of DS. We found specific alterations of distinct GABAergic circuits. In particular, we demonstrate that the dendritic inhibitory synaptic loop involving MCs and PNs was strongly potentiated in Ts, as compared to euploid control mice. In contrast, the perisomatic synaptic inhibitory control of PNs by PV cells was not affected in Ts mice. Strikingly, however, the excitability of PV cells was profoundly altered. These GABAergic circuit-specific alterations correlate with reduced PN spiking, and enhanced coupling with network β-γ-activity in Ts mice in vivo.

We analyzed MCs, which are a subset of SST interneurons, specialized in inhibiting the distal portion of apical dendrites of PNs, by ascending their axons in L1 (Kawaguchi and Kubota, 1998), where PN dendrites integrate top-down input originating from distal brain areas. In the hippocampus, dendritic inhibition strongly regulates PN dendrite electrogenesis and supra-linearity (Lovett-Barron et al., 2012), likely modulating the emergence of burst firing (Royer et al., 2012). Interestingly, α5–mediated dendritic inhibition in the hippocampus, known to strongly control dendritic integration and action potential firing (Schulz et al., 2018), is also enhanced in Ts65Dn mice and strongly control NMDAR activation, nonlinear dendritic integration, and AP firing (Schulz et al., 2019). In the neocortex, integration of top-down information in L1 and consequent dendrite-dependent generation of burst activity was hypothesized to underlie the encoding of context-rich, salient information (Larkum, 2013). Our results indicate a specific synaptic strengthening of the dendritic inhibitory loop involving MCs in Ts mice, suggesting a major impact on PN dendritic integration and electrogenesis.

Enhanced dendritic inhibition by MCs in DS could underlie the deficits of long-term plasticity of glutamatergic synapses similar to those observed in the hippocampus of Ts mice. Indeed, these LTP deficits can be recovered by treatment of allosteric modulators of α5-GABA_ARs (Duchon et al., 2020; Martínez-Cué et al., 2013; Schulz et al., 2019). Likewise, the enhanced MC-PN inhibitory loop in Ts mice shown here can provide a mechanism for the rescue of cognitive deficits in Ts mice, operated by selective pharmacology of α5-GABA_ARs (Braudeau et al., 2011; Duchon et al., 2020; Martínez-Cué et al., 2013). This subunit of GABA_ARs, whose synaptic vs. extrasynaptic expression is still debated (Ali and Thomson, 2008; Botta et al., 2015; Glykys and Mody, 2010; Hannan et al., 2020; Hausrat et al., 2015; Schulz et al., 2018; Serwanski et al., 2006), mediate dendritic synaptic inhibition from neocortical MCs (Ali and Thomson, 2008) and their hippocampal counterparts (the oriens-lacunosum moleculare or O-LM interneurons, Schulz et al., 2018). Here, we confirmed that α5-containing GABA_ARs are majorly responsible for MC-PN dendritic synaptic inhibition, due to the overall block of α5IA, which was close to the max potency of this drug (Dawson et al., 2006).

The enhancement of the dendritic inhibitory loop involving MCs and PNs in Ts mice could not be attributed to alterations of axonal and/or dendritic arborizations in the mutant mice. On the other hand, it could be due to a combination of pre- and postsynaptic mechanisms, including alterations of release probability, number of release sites or quantal size at either GABAergic or glutamatergic synapses involved in this circuit. The strong increase of synaptic charge at MC-PN GABAergic synapses could be attributed to alterations of uIPSC waveform in Ts mice. Although the small change of uIPSC rise time can in principle account for, at least in part, an increase in synaptic charge, it is unlikely to account for the 5-fold increase of synaptic charge, with no changes in uIPSC decay.

The robust increase of synaptic charge in Ts mice is likely due to one or a combination of different non-linearities that dynamically emerge during a spike train. These include the recruitment of peri- or extrasynaptic GABA_ARs, possible alterations of release probability or quantal size during trains and differences in postsynaptic dendritic filtering in the two genotypes. These complex interplays between these factors occur at distal dendrites; therefore, they are difficult to tease out from somatic recordings as they are characterized by poor dendritic voltage control due to space-clamping constraints. The enhanced short-term depression of MC-PN uIPSCs that we report here suggests that release probability at dendritic GABAergic synapses from MCs is increased in Ts mice. This is consistent with increased short-term depression of inhibition reported in the dentate gyrus (Kleschevnikov et al., 2012), but not with unaltered short-term plasticity shown in CA1 (Mitra et al., 2012). These discrepancies could be ascribed to differences between brain regions. Moreover, they could also be a consequence of non-specific recruitment of presynaptic axons by global extracellular stimulation, in contrast to the isolation of unitary synaptic responses by dual intracellular recordings as reported here. The lack of short-term plasticity alterations at PN-MC glutamatergic synapses suggests that increased excitatory recruitment of MCs is due to alterations at postsynaptic sites. Future studies will be necessary to pinpoint the exact biophysical and anatomical alterations underlying the prominent increase of dendritic inhibition operated by MCs in DS.

Potentiation of glutamatergic synapses in Ts mice seems to be specific for PN-MC connections, as PN-PV synapses were similar in both genotypes, suggesting that presynaptic terminals of local glutamatergic synapses can undergo target-specific modulation of their strength. Intriguingly, it has been recently shown that an increase of the excitatory drive of hippocampal interneurons (due to triplication of GluR5 kainate receptor expression) could explain excess of inhibition received by pyramidal neurons in the Ts2Cje Down syndrome mouse model (Valbuena et al., 2019). Therefore, a similar gene overdose of kainate receptors can boost the recruitment of specific interneurons in the PFC of Ts mice.

The strong increase of membrane resistance of PV cells in Ts mice underlies the augmented intrinsic excitability and can produce early ectopic bouts of activity, thus contributing to network over-inhibition. Enhanced membrane resistance could result from alterations in the expression of TWIK1 and TASK1 leak channels. Indeed, these channels underlie the developmental decrease of membrane resistance in PV cells (Okaty et al., 2009). In contrast, the inability of PV cells of Ts mice to sustain high frequency firing could prevent these interneurons from generating high-frequency bursts of action potentials and therefore have a detrimental effect on the temporal coding of these interneurons.

Interestingly, however, despite the dramatic alterations of intrinsic excitability in Ts PV cells, their output synaptic perisomatic inhibition was similar in both genotypes. This, despite the widening of single PV-cell action potentials, which could, in principle change the presynaptic Ca²⁺ dynamics and thus alter release probability. Since action potentials are recorded in the soma, the lack of effect at PV-cell synapses could be due to soma-specific alterations. Alternatively, since neocortical PV-PN GABAergic synapses exhibit high release probability (Deleuze et al., 2019; Kawaguchi and Kubota, 1998), alterations of spike width might not be enough to produce additional increases. Increase of action potential width in Ts mice could be due to changes in the expression Kv3.1b potassium channels, known to underlie the fast repolarization of action potentials and fast-spiking behavior of PV cells (Erisir et al., 1999). Future experiments will be necessary to reveal the exact molecular mechanism underlying the altered firing properties of PV cells, which, in Ts mice, have lost their characteristic fast-spiking signature.

The aberrant active and passive properties of PV cells in Ts mice could be due to a delayed development of these interneurons. Indeed, during development, neocortical PV cells display marked accelerations of single action potentials and increased firing frequency, accompanied by decreased input resistance (Okaty et al., 2009). Although we cannot rule out the possibility of a delayed development of PV cells in Ts mice, these interneurons showed abnormal passive and active properties within the entire age range studied here. It will be interesting to determine whether these profound alterations of PV-cell firing are present with the same incidence and magnitude along the entire life span of Ts mice. Although previous reports have shown higher number of inhibitory interneurons in the hippocampus (Hernández-González et al., 2015) and somatosensory cortex (Aziz et al., 2018; Chakrabarti et al., 2010) we failed to detect significant differences in the density of both SST- and PV-positive interneurons in the mPFC. This could be due to differences between brain regions. A systematic comparative analysis will be required to better understand the consequences of DS neurodevelopmental alterations of the cellular composition in different brain regions.

Both potentiation of the dendritic inhibitory loop and increased PV-cell excitability are consistent with the alterations of PN spiking activity that we recorded in vivo. Indeed, reduced spike rates and increased tuning in the β-γ-frequency range are both consistent with increased activity of inhibitory neurons (Atallah et al., 2012; Cardin et al., 2009; Chen et al., 2017; Sohal et al., 2009; Veit et al., 2017). The overall LFP power spectra observed in mPFC is similar in both Ts and Eu mice, consistently with a recent report (Chang et al., 2020). However, close examination of stLFP revealed a strong increase in the power of β- and low γ-frequency bands during periods of spiking activity. This likely reflects the consequences of alterations at the level of local microcircuits.

We cannot directly link the inhibitory circuit-specific alterations that we detected in slices with the increased synchronization of β-γ-activity that we measured in vivo. However, a large body of literature indicates that oscillations in this frequency range strongly depends on the activity of PV cells (Buzsáki and Wang, 2012; Sohal et al., 2009; Cardin et al., 2009). More recently, also SST interneurons were shown to control PN phase coupling with low frequency (30 Hz) neocortical γ-oscillations (Chen et al., 2017; Veit et al., 2017). It is therefore tempting to speculate that increased dendritic inhibition from SST-expressing MCs modulates phase coupling of PNs with β- and low γ-oscillations. On the other hand, the increased phase coupling of PN spikes with high-frequency γ-activity could result from the augmented excitability of PV cells. The differential phase coupling of these two interneuron types at distinct frequencies is consistent with the peculiar fast and slower recruitment and biophysical properties of PV interneurons and MCs, respectively. Future experiments involving chemogenetic alterations of PV-interneuron excitability and/or pharmacological manipulations of MC-PN synapses in Ts mice will help decipher the role played by each inhibitory cell subtype in controlling the temporal dynamics of PN firing during different rhythmic cortical network activities. Alternatively, our results could be interpreted as differences in long-range functional connectivity in the two genotypes, possibly due to alterations in myelination and conduction velocity in Ts vs. Eu mice (Olmos-Serrano et al., 2016a). Nevertheless, a reduction of axonal conduction velocity would produce a temporal shift in spike-to-phase association, rather than increased phase locking.

The increase in β-γ-band power and enhanced neural synchronization in these frequency ranges in Ts mice is consistent with recent evidence indicating augmented hippocampal-PFC synchronization and LFP γ-band power during natural non-REM sleep in Ts65Dn mice (Alemany-González et al., 2020). This suggests that the alterations of γ-oscillations observed here could play a role in the pathophysiology of sleep disruptions reported in DS children (Fernandez et al., 2017) and adults (Giménez et al., 2018).

In sum, here we report direct evidence for over-inhibition of mPFC circuits in a mouse model of DS. However, over-inhibition was not due to a generic increase of GABAergic signaling, but emerged from highly specific synaptic and intrinsic alterations of dendritic and somatic inhibitory circuits, respectively. Future experiments are necessary to reveal whether other inhibitory neuron types are also affected in DS. Likewise, it will be fundamental to assess whether specific dysfunctions of individual GABAergic circuits underlie different aspects of cognitive deficits (e.g. impaired memory and flexibility, autistic traits), which affect individuals with DS.

Experimental procedures followed national and European (2010/63/EU) guidelines, and have been approved by the authors' institutional review boards and national authorities. All efforts were made to minimize suffering and reduce the number of animals. Experiments were performed on >4 week old and 18- to 25-day-old mice for in vivo and ex vivo recordings, respectively. We used B6EiC3Sn a/A-Ts(17 ¹⁶)65Dn/J (also known as Ts65Dn) mice (The Jackson Laboratory, Bar Harbor, Maine; stock #: 001924). For ex vivo slice experiments to label SST-positive MCs, Ts65Dn mice were crossed with Tg(Gad1-EGFP)98Agmo/J, also known as GAD67-GFP X98 or GFP-X98 (Jackson Laboratory). To label PV-INs, Ts65Dn mice were crossed with C57BL/6-Tg(Pvalb-tdTomato)15Gfng/J (Pvalb-tdTomato, Jackson Laboratory). Mice used in this study were of both sexes.

Source data files have been provided for: Figure 1, Figure 1–figure supplement 2, Figure 1–figure supplement 3, Figure 2, Figure 2–figure supplement 1, Figure 2–figure supplement 2, Figure 3, Figure 3–figure supplement 1, Figure 4, Figure 4–figure supplement 1 and Figure 5.

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Author details

1. Javier Zorrilla de San Martin

   Institut du Cerveau (ICM), CNRS UMR 7225 – Inserm U1127, Sorbonne Université, Paris, France

   Contribution

   Conceptualization, Data curation, Software, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing - original draft, Project administration, Writing - review and editing

   For correspondence

   javier.zorrilla@icm-institute.org

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-2848-7482

2. Cristina Donato

   Institut du Cerveau (ICM), CNRS UMR 7225 – Inserm U1127, Sorbonne Université, Paris, France

   Present address

   Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, Luxembourg

   Contribution

   Formal analysis, Investigation, Methodology, Project administration, Writing - review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-4078-0745

3. Jérémy Peixoto

   Institut du Cerveau (ICM), CNRS UMR 7225 – Inserm U1127, Sorbonne Université, Paris, France

   Present address

   Institut Pasteur, Paris, France

   Contribution

   Formal analysis, Investigation, Writing - review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-6814-9747

4. Andrea Aguirre

   Institut du Cerveau (ICM), CNRS UMR 7225 – Inserm U1127, Sorbonne Université, Paris, France

   Contribution

   Formal analysis, Investigation, Methodology, Writing - review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-1176-8747

5. Vikash Choudhary

   Institut du Cerveau (ICM), CNRS UMR 7225 – Inserm U1127, Sorbonne Université, Paris, France

   Contribution

   Software, Formal analysis, Methodology, Writing - review and editing

   Competing interests

   No competing interests declared

6. Angela Michela De Stasi

   Institut du Cerveau (ICM), CNRS UMR 7225 – Inserm U1127, Sorbonne Université, Paris, France

   Contribution

   Investigation, Methodology, Writing - review and editing

   Competing interests

   No competing interests declared

7. Joana Lourenço

   Institut du Cerveau (ICM), CNRS UMR 7225 – Inserm U1127, Sorbonne Université, Paris, France

   Contribution

   Investigation, Methodology, Writing - review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-5550-9291

8. Marie-Claude Potier

   Institut du Cerveau (ICM), CNRS UMR 7225 – Inserm U1127, Sorbonne Université, Paris, France

   Contribution

   Conceptualization, Resources, Supervision, Funding acquisition, Validation, Visualization, Methodology, Writing - original draft, Project administration, Writing - review and editing

   For correspondence

   marie-claude.potier@upmc.fr

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-2462-7150

9. Alberto Bacci

   Institut du Cerveau (ICM), CNRS UMR 7225 – Inserm U1127, Sorbonne Université, Paris, France

   Contribution

   Conceptualization, Resources, Software, Formal analysis, Supervision, Funding acquisition, Validation, Visualization, Writing - original draft, Project administration, Writing - review and editing

   For correspondence

   alberto.bacci@icm-institute.org

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-3355-5892

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