Our brain contains over a 100 billion nerve cells or neurons, and each of them is thought to connect to over 1,000 other neurons. Together, these cells form a complex network to convey information from our surroundings or transmit messages to designated destinations. This circuitry forms the basis of our unique cognitive abilities.

In the cerebral cortex – the largest region of the brain – two main types of neurons can be found: projection neurons, which transfer information to other regions in the brain, and interneurons, which connect locally to different neurons and harmonize this information by inhibiting specific messages. The over 20 different types of known interneurons come in different shapes and properties and are thought to play a key role in powerful computations such as learning and memory.

Since interneurons are hard to track, it is still unclear when and how they start to form and mature as the brain of an embryo develops. For example, one type of interneurons called the neurogliaform cells, have a very distinct shape and properties. But, until now, the origin of this cell type had been unknown.

To find out how neurogliaform cells develop, Niquille, Limoni, Markopoulos et al. used a specific gene called Hmx3 to track these cells over time. With this strategy, the shapes and properties of the cells could be analyzed. The results showed that neurogliaform cells originate from a region outside of the cerebral cortex called the preoptic area, and later travel over long distances to reach their final location. The cells reach the cortex a few days after their birth and take several weeks to mature.

These results suggest that the traits of a specific type of neuron is determined very early in life. By labeling this unique subset of interneurons, researchers will now be able to identify the specific molecular mechanisms that help the neurogliaform cells to develop. Furthermore, it will provide a new strategy to fully understand what role these cells play in processing information and guiding behavior.

Cortical microcircuit function relies on the coordinated activity of a variety of GABAergic interneuron subtypes, which play critical roles in controlling the firing rate of glutamatergic pyramidal neurons, synchronizing network rhythms and regulating behavioral states (Cardin et al., 2009; Fu et al., 2014; Kepecs and Fishell, 2014; Pfeffer et al., 2013; Pi et al., 2013; Pinto and Dan, 2015; Sohal et al., 2009; Zhang et al., 2014). Different subtypes of cortical interneurons (INs) emerge during development and their specification arises through the complex interaction of cell-intrinsic mechanisms and cell-extrinsic cues (Bartolini et al., 2013; Fishell and Rudy, 2011; Huang, 2014; Kessaris et al., 2014). Cortical INs are generated in a variety of subpallial regions and the combinatorial expression of transcription factors (TFs) in these domains is believed to play a critical role in their fate specification (Kessaris et al., 2014; Anastasiades and Butt, 2011; Flames et al., 2007; Wonders and Anderson, 2006). The largest fraction (about 60–70%) of cortical INs is generated from NKX2.1-expressing progenitors located in the medial ganglionic eminence (MGE) (Butt et al., 2008; Xu et al., 2008) and their specification is under the control of the TFs LHX6 (Du et al., 2008; Liodis et al., 2007) and SOX6 (Azim et al., 2009; Batista-Brito et al., 2009). MGE-derived INs develop into fast-spiking parvalbumin (PV)+ basket and chandelier cells, as well as into Martinotti and multipolar somatostatin (SST)+ INs (Butt et al., 2008; Xu et al., 2008; Du et al., 2008; Butt et al., 2005; Fogarty et al., 2007; Taniguchi et al., 2013). The second largest fraction of cortical INs arises from the caudal ganglionic eminence (CGE) (Miyoshi et al., 2010; Nery et al., 2002) and expresses TFs such as PROX1, SP8 and NR2F2 (Cai et al., 2013; Ma et al., 2012; Miyoshi et al., 2015; Rubin and Kessaris, 2013). CGE-derived INs also express the ionotropic serotonin receptor 3A (5-HT_3AR) and give rise to a large diversity of INs, including reelin+ cells, vasointestinal peptide (VIP)+/calretinin+ bipolar cells and VIP+/cholecystokinin+ basket cells (Miyoshi et al., 2010; Armstrong and Soltesz, 2012; Prönneke et al., 2015; Lee et al., 2010; Murthy et al., 2014; Vucurovic et al., 2010). Finally, lineage-tracing experiments using Hmx3 (Nkx5.1)-Cre (Gelman et al., 2009) and Dbx1-Cre driver lines (Gelman et al., 2011) have shown that a small fraction (about 10%) of cortical INs originate from the preoptic area (POA) (Gelman et al., 2009; Gelman et al., 2011).

Among cortical INs, neurogliaform cells (NGCs) display unique characteristics. They represent the main source of ‘slow’ cortical inhibition by acting on metabotropic GABA_B receptors (Tamás et al., 2003), and are thought to be key effectors of a powerful inhibitory circuit recruited by long-range connections such as interhemispheric and thalamic projections (Craig and McBain, 2014; Palmer et al., 2012; De Marco García et al., 2015). Whether the current description of NGCs captures an IN subtype related to a distinct developmental specification process is unclear. Here we used in vivo genetic lineage-tracing to follow the developmental origin and trajectory of NGCs. We found that they originate from a distinct pool of 5-HT_3AR-expressing Hmx3+ cells located in the rostral POA region, ventrally to the anterior commissure. In the embryonic POA, Htr3a-GFP+ INs in the Hmx3+ domain expressed CGE-enriched TFs such as PROX1 and NR2F2, but only rarely, if not, MGE-related TFs such as NKX2.1 or LHX6. In the cortex, Hmx3-derived Htr3a-GFP+ INs expressed markers of CGE-derived INs such as NPY and/or reelin, as well as CGE-enriched TFs such as SP8, NR2F2 and PROX1, but neither MGE-specific markers such as PV or SST nor TFs such as LHX6 or SOX6. Finally, single-molecule in situ hybridization and electrophysiological recordings followed by post hoc reconstructions indicated that Hmx3-derived Htr3a-GFP+ cells exhibited the molecular, electrophysiological and morphological profile of NGCs. Taken together, these results demonstrate that cortical NGCs have a precise developmental trajectory that is linked to the expression of the transcription factor (TF) Hmx3 in a discrete embryonic subpallial region.

To determine whether the POA could contribute to Htr3a-GFP INs, we crossed Htr3a-GFP; R26R-tdTOM^fl/fl mice with Hmx3-Cre mice, a reporter line previously shown to fate map a population of cortical INs derived from cells located in the POA (Gelman et al., 2009). Examination of brains from Hmx3-Cre::Htr3a-GFP; R26R-tdTOM^fl/fl matings at embryonic age 14.5 (E14.5) revealed a large fraction of Hmx3; tdTOM+ cells co-labelled with Htr3a-GFP (85.2 ± 0.9%; 1675/1986 cells in the overlap zone) in a restricted region of the POA, located ventrally to the anterior commissure (Figure 1A,C, Figure 1—source data 1). Individual co-labelled Hmx3; tdTOM+/Htr3a-GFP+ cells displaying migratory profiles were observed at more caudal levels entering the CGE (Figure 1B), suggesting that a fraction of Hmx3; tdTOM+/Htr3a-GFP+ cells migrate from the POA into the CGE. In situ hybridization indicated that the vast majority (95.8 ± 0.9%; 115/120 cells) of Hmx3; tdTOM+/Htr3a-GFP+ cells located in the POA expressed the endogenous Htr3a mRNA, in contrast to Hmx3; tdTOM+cells negative for Htr3a-GFP (0.5 ± 0.5%; 1/158 cells) (Figure 1D, Figure 1—source data 1). In addition, a large fraction of Hmx3; tdTOM+/Htr3a-GFP+ cells in the POA expressed the TFs PROX1 (54.0 ± 2.2%; 249/463 cells) and NR2F2 (65.9 ± 1.3%; 795/1212 cells), which have previously been shown to be enriched in CGE-derived INs (Cai et al., 2013; Ma et al., 2012; Miyoshi et al., 2015; Rubin and Kessaris, 2013), but more rarely the TF NKX2.1 (15.3 ± 1%; 175/1146 cells) (Figure 1E,F, Figure 1—source data 1). Collectively, these results indicate that a fraction of Hmx3+ cells located in the POA express the 5-HT_3AR and a pattern of TFs related to CGE-derived INs.

Figure 1

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Figure 1—source data 1

Detailed counts of cells quantified in Figure 1 in the different experimental conditions.

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To determine whether Hmx3; tdTOM+/Htr3a-GFP+ cells in the POA eventually give rise to a specific subpopulation of cortical INs, we examined brains at various postnatal ages. From P5 to P21, Hmx3; tdTOM+/Htr3a-GFP+ INs were found distributed preferentially in superficial cortical layers and in a variety of other brain regions including in the hippocampus (Figure 2A, Figure 2—figure supplement 1). Hmx3; tdTOM+/Htr3a-GFP+ cells were rarely observed at postnatal ages in the subpallial brain regions corresponding to the embryonic POA (i.e., the preoptic nuclei) (Figure 2—figure supplement 2). In situ hybridization for Htr3a mRNA indicated that Hmx3; tdTOM+/Htr3a-GFP+ cells expressed the Htr3a transcript, similarly to Htr3a-GFP+ cells negative for Hmx3; tdTOM (Figure 2C). About half (51.9 ± 2.1%; 863/1653 cells) of Hmx3-derived cells in the cortex were co-labelled with Htr3a-GFP+ and virtually all Hmx3; tdTOM+/Htr3a-GFP+ (96.1 ± 0.5%; 357/372 cells) were positive for the neuronal marker NeuN (Figure 2D,E, Figure 2—source data 1). In contrast, the fraction of Hmx3; tdTOM+ cells negative for Htr3a-GFP mostly did not express NeuN (3.4 ± 1.3%; 28/758 cells) (Figure 2D,E, Figure 2—source data 1), and remained relatively constant across postnatal ages (Figure 2—figure supplement 3A, Figure 2—figure Supplement 3—source data 1). These cells displayed the morphology of glial cells and expressed the astrocytic markers GFAP and S100β as well as the oligodendrocytic marker SOX10 (Figure 2—figure supplement 3B–D). Overall, these findings indicate that the cortical Hmx3-derived lineage observed in the POA differentiate into INs that are Htr3a-GFP+, glial cells that are Htr3a-GFP negative and, for a small fraction, to NeuN+ neurons negative for Htr3a-GFP.

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Detailed counts of cells quantified in Figure 2 in the different experimental conditions.

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A second distinct region in the POA expressing Dbx1 was previously reported to give rise to subsets of cortical INs (Gelman et al., 2011). To determine whether a fraction of Htr3a-GFP+ INs also originate from Dbx1-expressing cells, we examined Dbx1-Cre::Htr3a-GFP; R26R-tdTOM^fl/fl brains at postnatal periods. While the overall contribution of Hmx3-derived cells to the Htr3a-GFP IN population in the cortex increased with postnatal maturation from P5 (6.8 ± 0.2%; 77/1118 cells) to P21 (16.0 ± 0.3%; 863/5405 cells) (Figure 3A,C), only minimal fractions (1.44 ± 0.2%; 81/5741 cells at P5; 0.8 ± 0.2%; 20/2551 cells at P21) of Htr3a-GFP+ INs were fate-mapped with Dbx1; tdTOM (Figure 3B,C, Figure 3—source data 1). Moreover, Dbx1; tdTOM+ cells were preferentially found in deep cortical layers and expressed the MGE-enriched TF SOX6 (30.4 ± 2.2%; 82/266 cells), while PROX1 was found only in a very small fraction of Dbx1; tdTOM+ cells expressing also the Htr3a-GFP (2.2 ± 0.7%; 6/266 cells) (Figure 3D, Figure 3—source data 1). In addition, Dbx1; tdTOM+ INs expressed Lhx6 mRNA (Figure 3E), and the MGE-related markers SST and PV (Figure 3—figure supplement 1), and only very rarely the Htr3a mRNA (Figure 3F). Overall, these results indicate that Hmx3-derived 5-HT_3AR+ cortical INs largely originate from Hmx3-expressing cells but not from the Dbx1+ domain, which gives rise to INs expressing MGE-related markers.

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Detailed counts of cells quantified in Figure 3 in the different experimental conditions.

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We next examined whether Hmx3; tdTOM+/Htr3a-GFP+ cells expressed distinct patterns of TFs involved in cortical IN subtype specification. At P21, we found that, similarly to Htr3a-GFP+ INs, a large fraction (65.8 ± 3.4%; 202/308 cells) of Hmx3; tdTOM+/Htr3a-GFP+ INs expressed the CGE-enriched but not the MGE-related TFs. Indeed, a large fraction of them (65.8 ± 3.4%; 202/308 cells) expressed PROX1 but not SOX6 (Figure 4A,B, Figure 4—source data 1), as well as NR2F2 (32.7 ± 5.9%; 71/218 cells), SP8 (9.8 ± 2.6%; 22/218 cells), and both SP8 and NR2F2 (8.8 ± 2.0%; 18/218 cells) (Figure 4C,D, Figure 4—source data 1). The fraction of Hmx3; tdTOM+/Htr3a-GFP+ expressing at least one of these two latter TFs was smaller and biased toward NR2F2 expression, when compared to Htr3a-GFP+ INs (Figure 4D, Figure 4—figure supplement 1, Figure 4—source data 1). These findings indicate that Hmx3; tdTOM+/Htr3a-GFP+ cortical INs express a repertoire of TFs related to CGE but not to MGE-derived INs.

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Detailed counts of cells quantified in Figure 4 in the different experimental conditions.

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We next examined whether Hmx3; tdTOM+/Htr3a-GFP+ INs expressed classical CGE markers such as reelin, NPY and VIP (Lee et al., 2010; Murthy et al., 2014; Vucurovic et al., 2010). Quantification across layers revealed that a large fraction of Hmx3; tdTOM+/Htr3a-GFP+ INs expressed reelin or NPY. This was particularly striking in layer 1 (L1) for reelin (Figure 5A,C) and in L2–6 for NPY (Figure 5B,E), respectively (Figure 5—source data 1). Overall, Hmx3; tdTOM+/Htr3a-GFP+ INs accounted for approximately a third of all reelin+/Htr3a-GFP+ INs (34.5 ± 2.3%; 267/797 cells) and of all NPY+/Htr3a-GFP+ INs (27.7 ± 2.3%; 149/571 cells) (Figure 5D,F, Figure 5—source data 1). Given that INs expressing reelin have been shown to co-express NPY (Lee et al., 2010), we assessed reelin and NPY co-expression in Hmx3; tdTOM+/Htr3a-GFP+ cells. At P21, only a small fraction (8.0 ± 0.9%; 17/232 cells) of these cells expressed NPY without reelin, thus indicating that reelin labels the largest fraction (66.1 ± 8.6%; 267/398 cells) of Hmx3-derived Htr3a-GFP+ INs (Figure 5G,H, Figure 5—source data 1). In contrast, Hmx3; tdTOM+/Htr3a-GFP+ INs did not co-label nor with the CGE-specific marker VIP (Figure 5I) neither with the MGE-enriched markers SST and PV (Figure 5—figure supplement 1). These results indicate that Hmx3-derived Htr3a-GFP+ INs mainly belong to the reelin but not to the VIP subtypes and account for an important fraction of all reelin+/Htr3a-GFP+ INs.

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Detailed counts of cells quantified in Figure 5 in the different experimental conditions.

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Two distinct profiles of reelin-expressing INs have been identified in L1 of the neocortex, namely neurogliaform (NGCs) and single bouquet-like cells (SBCs) (Cadwell et al., 2016; Jiang et al., 2015). At a molecular level, NGCs are strongly enriched in the carbonic anhydrase 4 (Car4) transcript in contrast to SBCs (Cadwell et al., 2016). Using single-molecule fluorescent in situ hybridization experiments (Wang et al., 2012), we found that Hmx3; tdTOM+/Htr3a-GFP+ INs in L1 exhibited significantly higher levels of Car4 transcripts in contrast to Htr3a-GFP+ INs (Figure 6A, Figure 6—source data 1), thus indicating that Hmx3-derived Htr3a-GFP+ INs share the molecular profile of NGC. To further verify whether their morphological and electrophysiological features could fit with NGCs, we performed whole-cell recordings (Figure 6B) and reconstructions (Figure 6C,D; Figure 6—figure supplement 1) of Hmx3-derived versus non Hmx3-derived Htr3a-GFP+ INs in L1 of the barrel cortex. There, Hmx3; tdTOM+/Htr3a-GFP+ INs displayed the characteristic morphology of elongated NGCs with dense axonal ramifications mostly restricted to L1 (Figure 6C, Figure 6—figure supplement 1), whereas Htr3a-GFP+ INs negative for tdTOM had the morphology of SBCs with less developed axonal processes that extended deeper in cortical layers (Figure 6D). With regard to their first action potential (AP) at rheobase, NGCs are reported to display a type 1 profile with only an after-hyperpolarization potential (AHP), whereas SBCs show a type 2 profile consisting of an AHP followed by an after-depolarization potential (ADP) (Cadwell et al., 2016; Jiang et al., 2015). Strikingly, all (29 out of 29) recorded Hmx3; tdTOM+/Htr3a-GFP+ INs were of type 1, thus confirming their NGC identity. Moreover, the vast majority of them (23 out of 29) were of type 1A with a deep and wide AHP and only a few (6 out of 29) were of type 1B with a shallow and narrow AHP (Figure 6E, left, Figure 6—source data 2). Htr3a-GFP+ INs negative for Hmx3; tdTOM had more variable profiles, but the majority of them (24 out of 28) were displaying a type two profile with an average ADP amplitude of 2.30 ± 0.51 mV, suggesting that they were SBCs. Most of them (20 out of 28) were of type 2B with a small ADP below the spike threshold, a few others (4 out of 28) were of type 2A with a big ADP above the spike threshold (Figure 6E, right, Figure 6—source data 2) and another few of them (4 out of 28) had not measurable ADP (not shown). Hmx3; tdTOM+/Htr3a-GFP+ INs showed also a higher tendency to late-spiking when compared to Htr3a-GFP+ INs (Figure 6F, Figure 6—source data 2). Hmx3; tdTOM+/Htr3a-GFP+ INs had bigger AP delay average, but not significantly different from Htr3a-GFP+ INs negative for Hmx3; tdTOM (Figure 6—figure supplement 2C, Figure 6—source data 2). However, the variability of individual cell values was higher for Hmx3; tdTOM+/Htr3a-GFP+ INs, indicating that these cells tend to be more late-spiking, a characteristic of NGCs (Cadwell et al., 2016; Jiang et al., 2015). Alignement of the first APs at rheobase revealed other putative differences between the two groups (Figure 6G, Figure 6—source data 2). After quantification, Hmx3; tdTOM+/Htr3a-GFP+ INs significantly differed from Htr3a-GFP+ INs negative for Hmx3; tdTOM in the first AP amplitude (Peak), AHP amplitude (AHP), membrane resistance (Rm) (Figure 6H, Figure 6—source data 2) and threshold potential (Vthr) (Figure 6—figure supplement 2C). We next aimed to determine whether Hmx3 and non Hmx3-derived Htr3a-GFP+ INs classes in L1 could be predicted from single-cell electrophysiological properties. Using an automatic cell type classifier based on combined electrophysiological measures, we were able to predict the Hmx3-derived class with 80.7% accuracy, with highest weights found on ADP, Peak and AHP but not Vthr (Figure 6I,J; Figure 6—figure supplement 2A,B, Figure 6—source data 2). Finally, we analysed Hmx3; tdTOM+/Htr3a-GFP+ INs in other cortical layers to determine whether they displayed the same NGC characteristics. Similarly to L1 cells, Car4 expression in L2-6 was significantly higher in Hmx3; tdTOM+/Htr3a-GFP+ INs as compared to Htr3a-GFP+ INs negative for tdTOM (Figure 6—figure supplement 3A,B, Figure 6—source data 1). Morphological recovery of Hmx3; tdTOM+/Htr3a-GFP+ INs located in L2–6 revealed that all cells (7 out of 7) had also the characteristic morphology of NGCs (Figure 6—figure supplement 4). Furthermore, characteristic properties of NGC like the tendency to late spiking, the depth of AHP, and the level of Vthr were significantly more pronounced in these cells compared to L1 cells (Figure 6—figure supplement 3C,E). Overall, these data indicate that Htr3a-GFP+ INs displaying the molecular, morphological and electrophysiological properties of NGC INs originate from Hmx3-expressing cells in the embryonic POA (Figure 7, orange), whereas SBCs in layer 1, as well as VIP +INs, are more likely to originate from the CGE (Figure 7, green).

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Detailed counts of cells expressing Car4 quantified in Figure 6 in the different experimental conditions.

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Figure 6—source data 2

Electrophysiological properties of cells quantified in Figure 6.

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Figure 7

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Distinct subtypes of local GABAergic INs are required to regulate microcircuit function (Cardin et al., 2009; Fu et al., 2014; Kepecs and Fishell, 2014; Pfeffer et al., 2013; Pi et al., 2013; Pinto and Dan, 2015; Sohal et al., 2009; Zhang et al., 2014). Whether current classifications of cortical IN subtypes relate to intrinsic biological processes such as their developmental specification is a key question in the field (Huang, 2014; Taniguchi et al., 2013). Among cortical INs, NGCs are considered as belonging to a distinct subtype acting as a main effector of a powerful inhibitory motif recruited by long-range connections (Tamás et al., 2003; Craig and McBain, 2014; Palmer et al., 2012). Here we aimed to track the developmental trajectory of NGCs using genetic fate mapping strategies. We find that NGCs derive from Htr3a-GFP+/Hmx3+ cells located in the embryonic POA, but not from Dbx1+ cells. Strikingly, L1 Hmx3-derived Htr3a-GFP+ INs display the distinct molecular, morphological and electrophysiological properties of NGCs, whereas Htr3a-GFP+ INs negative for Hmx3 have the profile of SBCs (Cadwell et al., 2016). Hmx3-derived Htr3a-GFP+ NGCs represent about a third of reelin-expressing Htr3a-GFP+ INs. At a molecular level, Hmx3; tdTOM+/Htr3a-GFP+ NGCs express CGE-related TFs such as NR2F2 and PROX1, indicating that they share common features with CGE-derived INs. Overall, these results indicate that cortical NGCs derive from a discrete embryonic area located in the subpallial POA and that their specification is linked to the expression of the TF Hmx3.

1. 1. Anastasiades PG
   2. Butt SJ

   (2011) Decoding the transcriptional basis for GABAergic interneuron diversity in the mouse neocortex

   European Journal of Neuroscience 34:1542–1552.

   https://doi.org/10.1111/j.1460-9568.2011.07904.x

   • PubMed
   • Google Scholar
2. 1. Armstrong C
   2. Soltesz I

   (2012) Basket cell dichotomy in microcircuit function

   The Journal of Physiology 590:683–694.

   https://doi.org/10.1113/jphysiol.2011.223669

   • PubMed
   • Google Scholar
3. 1. Azim E
   2. Jabaudon D
   3. Fame RM
   4. Macklis JD

   (2009) SOX6 controls dorsal progenitor identity and interneuron diversity during neocortical development

   Nature Neuroscience 12:1238–1247.

   https://doi.org/10.1038/nn.2387

   • PubMed
   • Google Scholar
4. 1. Bartolini G
   2. Ciceri G
   3. Marín O

   (2013) Integration of GABAergic interneurons into cortical cell assemblies: lessons from embryos and adults

   Neuron 79:849–864.

   https://doi.org/10.1016/j.neuron.2013.08.014

   • PubMed
   • Google Scholar
5. 1. Batista-Brito R
   2. Rossignol E
   3. Hjerling-Leffler J
   4. Denaxa M
   5. Wegner M
   6. Lefebvre V
   7. Pachnis V
   8. Fishell G

   (2009) The cell-intrinsic requirement of Sox6 for cortical interneuron development

   Neuron 63:466–481.

   https://doi.org/10.1016/j.neuron.2009.08.005

   • PubMed
   • Google Scholar
6. 1. Butt SJ
   2. Fuccillo M
   3. Nery S
   4. Noctor S
   5. Kriegstein A
   6. Corbin JG
   7. Fishell G

   (2005) The temporal and spatial origins of cortical interneurons predict their physiological subtype

   Neuron 48:591–604.

   https://doi.org/10.1016/j.neuron.2005.09.034

   • PubMed
   • Google Scholar
7. 1. Butt SJ
   2. Sousa VH
   3. Fuccillo MV
   4. Hjerling-Leffler J
   5. Miyoshi G
   6. Kimura S
   7. Fishell G

   (2008) The requirement of Nkx2-1 in the temporal specification of cortical interneuron subtypes

   Neuron 59:722–732.

   https://doi.org/10.1016/j.neuron.2008.07.031

   • PubMed
   • Google Scholar
8. 1. Cadwell CR
   2. Palasantza A
   3. Jiang X
   4. Berens P
   5. Deng Q
   6. Yilmaz M
   7. Reimer J
   8. Shen S
   9. Bethge M
   10. Tolias KF
   11. Sandberg R
   12. Tolias AS

   (2016) Electrophysiological, transcriptomic and morphologic profiling of single neurons using Patch-seq

   Nature Biotechnology 34:199–203.

   https://doi.org/10.1038/nbt.3445

   • PubMed
   • Google Scholar
9. 1. Cai Y
   2. Zhang Q
   3. Wang C
   4. Zhang Y
   5. Ma T
   6. Zhou X
   7. Tian M
   8. Rubenstein JL
   9. Yang Z

   (2013) Nuclear receptor COUP-TFII-expressing neocortical interneurons are derived from the medial and lateral/caudal ganglionic eminence and define specific subsets of mature interneurons

   Journal of Comparative Neurology 521:479–497.

   https://doi.org/10.1002/cne.23186

   • PubMed
   • Google Scholar
10. 1. Cardin JA
    2. Carlén M
    3. Meletis K
    4. Knoblich U
    5. Zhang F
    6. Deisseroth K
    7. Tsai LH
    8. Moore CI

    (2009) Driving fast-spiking cells induces gamma rhythm and controls sensory responses

    Nature 459:663–667.

    https://doi.org/10.1038/nature08002

    • PubMed
    • Google Scholar
11. 1. Craig MT
    2. McBain CJ

    (2014) The emerging role of GABAB receptors as regulators of network dynamics: fast actions from a 'slow' receptor?

    Current Opinion in Neurobiology 26:15–21.

    https://doi.org/10.1016/j.conb.2013.10.002

    • PubMed
    • Google Scholar
12. 1. De Marco García NV
    2. Priya R
    3. Tuncdemir SN
    4. Fishell G
    5. Karayannis T

    (2015) Sensory inputs control the integration of neurogliaform interneurons into cortical circuits

    Nature Neuroscience 18:393–401.

    https://doi.org/10.1038/nn.3946

    • PubMed
    • Google Scholar
13. 1. Du T
    2. Xu Q
    3. Ocbina PJ
    4. Anderson SA

    (2008) NKX2.1 specifies cortical interneuron fate by activating Lhx6

    Development 135:1559–1567.

    https://doi.org/10.1242/dev.015123

    • PubMed
    • Google Scholar
14. 1. Fishell G
    2. Rudy B

    (2011) Mechanisms of inhibition within the telencephalon: "where the wild things are"

    Annual Review of Neuroscience 34:535–567.

    https://doi.org/10.1146/annurev-neuro-061010-113717

    • PubMed
    • Google Scholar
15. 1. Flames N
    2. Pla R
    3. Gelman DM
    4. Rubenstein JL
    5. Puelles L
    6. Marín O

    (2007) Delineation of multiple subpallial progenitor domains by the combinatorial expression of transcriptional codes

    Journal of Neuroscience 27:9682–9695.

    https://doi.org/10.1523/JNEUROSCI.2750-07.2007

    • PubMed
    • Google Scholar
16. 1. Fogarty M
    2. Grist M
    3. Gelman D
    4. Marín O
    5. Pachnis V
    6. Kessaris N

    (2007) Spatial genetic patterning of the embryonic neuroepithelium generates GABAergic interneuron diversity in the adult cortex

    Journal of Neuroscience 27:10935–10946.

    https://doi.org/10.1523/JNEUROSCI.1629-07.2007

    • PubMed
    • Google Scholar
17. 1. Fu Y
    2. Tucciarone JM
    3. Espinosa JS
    4. Sheng N
    5. Darcy DP
    6. Nicoll RA
    7. Huang ZJ
    8. Stryker MP

    (2014) A cortical circuit for gain control by behavioral state

    Cell 156:1139–1152.

    https://doi.org/10.1016/j.cell.2014.01.050

    • PubMed
    • Google Scholar
18. 1. Gelman D
    2. Griveau A
    3. Dehorter N
    4. Teissier A
    5. Varela C
    6. Pla R
    7. Pierani A
    8. Marín O

    (2011) A wide diversity of cortical GABAergic interneurons derives from the embryonic preoptic area

    Journal of Neuroscience 31:16570–16580.

    https://doi.org/10.1523/JNEUROSCI.4068-11.2011

    • PubMed
    • Google Scholar
19. 1. Gelman DM
    2. Martini FJ
    3. Nóbrega-Pereira S
    4. Pierani A
    5. Kessaris N
    6. Marín O

    (2009) The embryonic preoptic area is a novel source of cortical GABAergic interneurons

    Journal of Neuroscience 29:9380–9389.

    https://doi.org/10.1523/JNEUROSCI.0604-09.2009

    • PubMed
    • Google Scholar
20. 1. He M
    2. Tucciarone J
    3. Lee S
    4. Nigro MJ
    5. Kim Y
    6. Levine JM
    7. Kelly SM
    8. Krugikov I
    9. Wu P
    10. Chen Y
    11. Gong L
    12. Hou Y
    13. Osten P
    14. Rudy B
    15. Huang ZJ

    (2016) Strategies and tools for combinatorial targeting of gabaergic neurons in mouse cerebral cortex

    Neuron 91:1228–1243.

    https://doi.org/10.1016/j.neuron.2016.08.021

    • PubMed
    • Google Scholar
21. 1. Huang ZJ

    (2014) Toward a genetic dissection of cortical circuits in the mouse

    Neuron 83:1284–1302.

    https://doi.org/10.1016/j.neuron.2014.08.041

    • PubMed
    • Google Scholar
22. 1. Jiang X
    2. Shen S
    3. Cadwell CR
    4. Berens P
    5. Sinz F
    6. Ecker AS
    7. Patel S
    8. Tolias AS

    (2015) Principles of connectivity among morphologically defined cell types in adult neocortex

    Science 350:aac9462.

    https://doi.org/10.1126/science.aac9462

    • PubMed
    • Google Scholar
23. 1. Jiang X
    2. Wang G
    3. Lee AJ
    4. Stornetta RL
    5. Zhu JJ

    (2013) The organization of two new cortical interneuronal circuits

    Nature Neuroscience 16:210–218.

    https://doi.org/10.1038/nn.3305

    • PubMed
    • Google Scholar
24. 1. Kanatani S
    2. Yozu M
    3. Tabata H
    4. Nakajima K

    (2008) COUP-TFII is preferentially expressed in the caudal ganglionic eminence and is involved in the caudal migratory stream

    Journal of Neuroscience 28:13582–13591.

    https://doi.org/10.1523/JNEUROSCI.2132-08.2008

    • PubMed
    • Google Scholar
25. 1. Kepecs A
    2. Fishell G

    (2014) Interneuron cell types are fit to function

    Nature 505:318–326.

    https://doi.org/10.1038/nature12983

    • PubMed
    • Google Scholar
26. 1. Kessaris N
    2. Magno L
    3. Rubin AN
    4. Oliveira MG

    (2014) Genetic programs controlling cortical interneuron fate

    Current Opinion in Neurobiology 26:79–87.

    https://doi.org/10.1016/j.conb.2013.12.012

    • PubMed
    • Google Scholar
27. 1. Lee S
    2. Hjerling-Leffler J
    3. Zagha E
    4. Fishell G
    5. Rudy B

    (2010) The largest group of superficial neocortical GABAergic interneurons expresses ionotropic serotonin receptors

    Journal of Neuroscience 30:16796–16808.

    https://doi.org/10.1523/JNEUROSCI.1869-10.2010

    • PubMed
    • Google Scholar
28. 1. Liodis P
    2. Denaxa M
    3. Grigoriou M
    4. Akufo-Addo C
    5. Yanagawa Y
    6. Pachnis V

    (2007) Lhx6 activity is required for the normal migration and specification of cortical interneuron subtypes

    Journal of Neuroscience 27:3078–3089.

    https://doi.org/10.1523/JNEUROSCI.3055-06.2007

    • PubMed
    • Google Scholar
29. 1. Ma T
    2. Zhang Q
    3. Cai Y
    4. You Y
    5. Rubenstein JL
    6. Yang Z

    (2012) A subpopulation of dorsal lateral/caudal ganglionic eminence-derived neocortical interneurons expresses the transcription factor Sp8

    Cerebral Cortex 22:2120–2130.

    https://doi.org/10.1093/cercor/bhr296

    • PubMed
    • Google Scholar
30. 1. Miyoshi G
    2. Hjerling-Leffler J
    3. Karayannis T
    4. Sousa VH
    5. Butt SJ
    6. Battiste J
    7. Johnson JE
    8. Machold RP
    9. Fishell G

    (2010) Genetic fate mapping reveals that the caudal ganglionic eminence produces a large and diverse population of superficial cortical interneurons

    Journal of Neuroscience 30:1582–1594.

    https://doi.org/10.1523/JNEUROSCI.4515-09.2010

    • PubMed
    • Google Scholar
31. 1. Miyoshi G
    2. Young A
    3. Petros T
    4. Karayannis T
    5. McKenzie Chang M
    6. Lavado A
    7. Iwano T
    8. Nakajima M
    9. Taniguchi H
    10. Huang ZJ
    11. Heintz N
    12. Oliver G
    13. Matsuzaki F
    14. Machold RP
    15. Fishell G

    (2015) Prox1 regulates the subtype-specific development of caudal ganglionic eminence-derived GABAergic cortical interneurons

    Journal of Neuroscience 35:12869–12889.

    https://doi.org/10.1523/JNEUROSCI.1164-15.2015

    • PubMed
    • Google Scholar
32. 1. Murthy S
    2. Niquille M
    3. Hurni N
    4. Limoni G
    5. Frazer S
    6. Chameau P
    7. van Hooft JA
    8. Vitalis T
    9. Dayer A

    (2014) Serotonin receptor 3A controls interneuron migration into the neocortex

    Nature Communications 5:5524.

    https://doi.org/10.1038/ncomms6524

    • PubMed
    • Google Scholar
33. 1. Nery S
    2. Fishell G
    3. Corbin JG

    (2002) The caudal ganglionic eminence is a source of distinct cortical and subcortical cell populations

    Nature Neuroscience 5:1279–1287.

    https://doi.org/10.1038/nn971

    • PubMed
    • Google Scholar
34. 1. Nóbrega-Pereira S
    2. Kessaris N
    3. Du T
    4. Kimura S
    5. Anderson SA
    6. Marín O

    (2008) Postmitotic Nkx2-1 controls the migration of telencephalic interneurons by direct repression of guidance receptors

    Neuron 59:733–745.

    https://doi.org/10.1016/j.neuron.2008.07.024

    • PubMed
    • Google Scholar
35. 1. Palmer LM
    2. Schulz JM
    3. Murphy SC
    4. Ledergerber D
    5. Murayama M
    6. Larkum ME

    (2012) The cellular basis of GABA(B)-mediated interhemispheric inhibition

    Science 335:989–993.

    https://doi.org/10.1126/science.1217276

    • PubMed
    • Google Scholar
36. 1. Pfeffer CK
    2. Xue M
    3. He M
    4. Huang ZJ
    5. Scanziani M

    (2013) Inhibition of inhibition in visual cortex: the logic of connections between molecularly distinct interneurons

    Nature Neuroscience 16:1068–1076.

    https://doi.org/10.1038/nn.3446

    • PubMed
    • Google Scholar
37. 1. Pi HJ
    2. Hangya B
    3. Kvitsiani D
    4. Sanders JI
    5. Huang ZJ
    6. Kepecs A

    (2013) Cortical interneurons that specialize in disinhibitory control

    Nature 503:521–524.

    https://doi.org/10.1038/nature12676

    • PubMed
    • Google Scholar
38. 1. Pinto L
    2. Dan Y

    (2015) Cell-Type-specific activity in prefrontal cortex during goal-directed behavior

    Neuron 87:437–450.

    https://doi.org/10.1016/j.neuron.2015.06.021

    • PubMed
    • Google Scholar
39. 1. Prönneke A
    2. Scheuer B
    3. Wagener RJ
    4. Möck M
    5. Witte M
    6. Staiger JF

    (2015) Characterizing VIP neurons in the barrel cortex of vipcre/tdtomato mice reveals layer-specific differences

    Cerebral Cortex 25:4854–4868.

    https://doi.org/10.1093/cercor/bhv202

    • PubMed
    • Google Scholar
40. 1. Rubin AN
    2. Kessaris N

    (2013) PROX1: a lineage tracer for cortical interneurons originating in the lateral/caudal ganglionic eminence and preoptic area

    PLoS One 8:e77339.

    https://doi.org/10.1371/journal.pone.0077339

    • PubMed
    • Google Scholar
41. 1. Rudy B
    2. Fishell G
    3. Lee S
    4. Hjerling-Leffler J

    (2011) Three groups of interneurons account for nearly 100% of neocortical GABAergic neurons

    Developmental Neurobiology 71:45–61.

    https://doi.org/10.1002/dneu.20853

    • PubMed
    • Google Scholar
42. 1. Sohal VS
    2. Zhang F
    3. Yizhar O
    4. Deisseroth K

    (2009) Parvalbumin neurons and gamma rhythms enhance cortical circuit performance

    Nature 459:698–702.

    https://doi.org/10.1038/nature07991

    • PubMed
    • Google Scholar
43. 1. Southwell DG
    2. Paredes MF
    3. Galvao RP
    4. Jones DL
    5. Froemke RC
    6. Sebe JY
    7. Alfaro-Cervello C
    8. Tang Y
    9. Garcia-Verdugo JM
    10. Rubenstein JL
    11. Baraban SC
    12. Alvarez-Buylla A

    (2012) Intrinsically determined cell death of developing cortical interneurons

    Nature 491:109–113.

    https://doi.org/10.1038/nature11523

    • PubMed
    • Google Scholar
44. 1. Tamás G
    2. Lorincz A
    3. Simon A
    4. Szabadics J

    (2003) Identified sources and targets of slow inhibition in the neocortex

    Science 299:1902–1905.

    https://doi.org/10.1126/science.1082053

    • PubMed
    • Google Scholar
45. 1. Taniguchi H
    2. Lu J
    3. Huang ZJ

    (2013) The spatial and temporal origin of chandelier cells in mouse neocortex

    Science 339:70–74.

    https://doi.org/10.1126/science.1227622

    • PubMed
    • Google Scholar
46. 1. Vucurovic K
    2. Gallopin T
    3. Ferezou I
    4. Rancillac A
    5. Chameau P
    6. van Hooft JA
    7. Geoffroy H
    8. Monyer H
    9. Rossier J
    10. Vitalis T

    (2010) Serotonin 3A receptor subtype as an early and protracted marker of cortical interneuron subpopulations

    Cerebral Cortex 20:2333–2347.

    https://doi.org/10.1093/cercor/bhp310

    • PubMed
    • Google Scholar
47. 1. Wang F
    2. Flanagan J
    3. Su N
    4. Wang LC
    5. Bui S
    6. Nielson A
    7. Wu X
    8. Vo HT
    9. Ma XJ
    10. Luo Y

    (2012) RNAscope: a novel in situ RNA analysis platform for formalin-fixed, paraffin-embedded tissues

    The Journal of Molecular Diagnostics : JMD 14:22–29.

    https://doi.org/10.1016/j.jmoldx.2011.08.002

    • PubMed
    • Google Scholar
48. 1. Wonders CP
    2. Anderson SA

    (2006) The origin and specification of cortical interneurons

    Nature Reviews Neuroscience 7:687–696.

    https://doi.org/10.1038/nrn1954

    • PubMed
    • Google Scholar
49. 1. Xu Q
    2. Tam M
    3. Anderson SA

    (2008) Fate mapping Nkx2.1-lineage cells in the mouse telencephalon

    The Journal of Comparative Neurology 506:16–29.

    https://doi.org/10.1002/cne.21529

    • PubMed
    • Google Scholar
50. 1. Zhang S
    2. Xu M
    3. Kamigaki T
    4. Hoang Do JP
    5. Chang WC
    6. Jenvay S
    7. Miyamichi K
    8. Luo L
    9. Dan Y

    (2014) Selective attention. Long-range and local circuits for top-down modulation of visual cortex processing

    Science 345:660–665.

    https://doi.org/10.1126/science.1254126

    • PubMed
    • Google Scholar

Author details

1. Mathieu Niquille

   1. Department of Psychiatry, University of Geneva, Geneva, Switzerland
   2. Department of Basic Neuroscience, University of Geneva, Geneva, Switzerland

   Contribution

   Data curation, Formal analysis, Investigation, Writing—review and editing

   Contributed equally with

   Greta Limoni and Foivos Markopoulos

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-2860-3861

2. Greta Limoni

   1. Department of Psychiatry, University of Geneva, Geneva, Switzerland
   2. Department of Basic Neuroscience, University of Geneva, Geneva, Switzerland

   Contribution

   Data curation, Formal analysis, Investigation, Writing—review and editing

   Contributed equally with

   Mathieu Niquille and Foivos Markopoulos

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-6808-9510

3. Foivos Markopoulos

   Department of Basic Neuroscience, University of Geneva, Geneva, Switzerland

   Contribution

   Data curation, Formal analysis, Investigation, Writing—review and editing

   Contributed equally with

   Mathieu Niquille and Greta Limoni

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-5501-9249

4. Christelle Cadilhac

   1. Department of Psychiatry, University of Geneva, Geneva, Switzerland
   2. Department of Basic Neuroscience, University of Geneva, Geneva, Switzerland

   Contribution

   Formal analysis, Investigation, Writing—review and editing

   Competing interests

   No competing interests declared

5. Julien Prados

   1. Department of Psychiatry, University of Geneva, Geneva, Switzerland
   2. Department of Basic Neuroscience, University of Geneva, Geneva, Switzerland

   Contribution

   Data curation, Formal analysis, Writing—review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-8546-241X

6. Anthony Holtmaat

   Department of Basic Neuroscience, University of Geneva, Geneva, Switzerland

   Contribution

   Supervision, Funding acquisition, Validation, Methodology, Writing—review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-7577-0769

7. Alexandre Dayer

   1. Department of Psychiatry, University of Geneva, Geneva, Switzerland
   2. Department of Basic Neuroscience, University of Geneva, Geneva, Switzerland

   Contribution

   Conceptualization, Supervision, Funding acquisition, Validation, Investigation, Methodology, Writing—original draft, Administration, Writing—review and editing

   For correspondence

   alexandre.dayer@unige.ch

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-4490-9780

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