GABAergic interneurons in the neocortex: From cellular properties to circuits

PV INs

The PV group includes the fast-spiking (FS) basket and chandelier cells (Figure 1, Table I). Chandelier INs, also known as axo-axonic neurons, are the most recognizable INs in terms of morphology (DeFelipe et al., 2013) due to the unique candlestick-like synaptic terminal arrays they form to specifically target the axon initial segment of pyramidal cells. In contrast, the much more numerous basket cells make perisomatic “basket” terminals on the soma and proximal dendrites of PCs and INs. By producing hyperpolarizing and/or shunting inhibition (Fishell and Rudy, 2011) close to the site of action potential generation, both types powerfully influence the output of their target neurons. A third type of PV cells not shown in Figure 1 are the “multipolar bursting cells” (Blatow et al., 2003; Caputi et al., 2009). These neurons, found mainly in upper L2, differ from FS multipolar basket cells in their morphological and electrophysiological properties. This IN type has not been studied extensively, and no further information on these cells beyond the initial description has appeared.

PV basket cell subtypes have been shown to be associated with diverse dendritic and axonal arborization territories (Freund et al., 1983; Kisvarday, 1992; Kisvarday et al., 1985; Markram et al., 2004; Martin et al., 1983; Munoz et al., 2014; Somogyi et al., 1983; Thomson and Lamy, 2007; Wang et al., 2002)(Freund et al., 1983; Kisvarday, 1992; Kisvarday et al., 1985; Markram et al., 2004; Martin et al., 1983; Munoz et al., 2014; Somogyi et al., 1983; Thomson and Lamy, 2007; Wang et al., 2002)(Freund et al., 1983; Kisvarday, 1992; Kisvarday et al., 1985; Markram et al., 2004; Martin et al., 1983; Munoz et al., 2014; Somogyi et al., 1983; Thomson and Lamy, 2007; Wang et al., 2002)(Table I). Furthermore, laminar and columnar biases in axonal and dendritic arbors and connectivity have been observed to correlate with somatic laminar location (Bortone et al., 2014; Buchanan et al., 2012; Jiang et al., 2015; Kisvarday, 1992; Markram et al., 2004; Packer and Yuste, 2011; Thomson and Lamy, 2007). Some cortical layers (L4 in S1) contain only PV basket cells with largely local axon, while others (e.g. L5) in addition to PV basket cells with largely local axon have PV basket cells with local and translaminar axons. Since basket cells make perisomatic synapses, local cells will inhibit mainly local populations, while translaminar cells provide a means for interlaminar interactions via inhibition. In addition, some PV basket cells (particularly in supragranular and infragranular layers, but not in L4) have axons that span several columns, suggesting that in addition to providing inhibition to the column where they are located, they can influence neighboring columns. This is also true for some Sst-expressing Martinotti cells, and elongated neurogliaform cells as described below.

In some cases, association between morphological subtypes, synaptic properties and in vivo activity has been reported. For example, the complexity and extent of the dendritic arbor of supragranular PV INs in visual cortex correlate with their selectivity to visual stimuli (Runyan and Sur, 2013). In infragranular layers, it has been shown that PV cells with translaminar axons had excitatory inputs exhibiting less depression than locally projecting PV basket cells. This was due to expression of presynaptic NMDA receptors of glutamatergic axons contacting translaminar, but not locally projecting PV INs (Buchanan et al., 2012), which likely participates in making them more responsive to local pyramidal cell inputs (Bortone et al., 2014). This implies that PCs differentiate these PV basket cells as different subtypes. In the hippocampus, it has recently been shown that somatic laminar position and/or dendritic fields of PV expressing bistratified, axo-axonic and basket cells further segregate each class functionally during ripple events (Varga et al., 2014). Altogether, these studies illustrate that morphologically distinct PV basket INs, even from the same cortical layer, can exhibit functional differences.

As a whole, PV FS basket cells are the largest population of INs in the neocortex (Figure 2), and until recently they were the most studied IN population due to their number and very stereotypical fast and non-adapting firing pattern. Collectively, studies of their intrinsic properties have shown that PV basket cells have a remarkable array of molecular and cellular specializations to ensure that they produce a fast, reliable, strong and temporally precise inhibition on their target cells (reviewed in (Hu et al., 2014). The speed and precision of FS basket cell signaling are impressive. The delay between the peak of an action potential in a FS basket cell soma and the start of the uIPSC in a postsynaptic pyramidal cell is on the average 0.7 ms (at ~31 °C) and the jitter between different responses 0.19 ms (Rossignol et al., 2013). On the other hand the latency of disynaptic inhibition, which will include the latency in exciting the PV cell is less than 2 ms (Miles, 1990; Pouille and Scanziani, 2001). These specializations allow FS basket cells to function as coincidence detectors and impose this function onto their postsynaptic targets (see Box 1).

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Figure 2

Laminar distribution of IN groups

GABAergic interneurons are unevenly distributed within the cortical mantle. The PV group is a major component throughout the cortex, except in L1, where it is virtually absent. Sst neurons are found in all layers, most prominently in infragranular layers. 5HT3aR INs dominate in supragranular layers, however there is a clear laminar separation between VIP-expressing INs, the largest population in L2/3 and non-VIP interneurons, which represent ~ 90% of L1 INs. These laminar distributions are from mouse somatosensory cortex, but very similar distributions have been found in frontal and visual cortices (see (Xu et al., 2010) for comparison).

Axo-axonic or chandelier cells are also considered fast spiking, although some differences in intrinsic electrophysiological properties with PV basket cells have been reported (Woodruff et al., 2009). However, much less is known about chandelier cells and it is not clear to what extent the features of speed and precision of FS basket cells described in Box 1 also apply to chandelier cells. In addition, some reports have found different excitatory input sources and in vivo responses between PV FS basket and chandelier INs (Massi et al., 2012; Xu and Callaway, 2009; Zhu et al., 2004).

The lack until now of a specific marker for chandelier cells has hampered a systematic analysis. However, alternative genetic strategies have improved the targeting of this cell type (Taniguchi et al., 2013; Woodruff et al., 2009). Chandelier cells are particularly specialized regarding their postsynaptic target. All postsynaptic boutons of chandelier INs have been reported to target exclusively the axon initial segment of pyramidal cells (Howard et al., 2005) an observation confirmed by many authors (however, this notion has recently been challenged based on paired recordings, see (Jiang et al., 2015)). This is by far the highest level of target specificity to be ever reported concerning IN type and connectivity. Chandelier cells have recently generated additional attention as a result of the discovery that in neocortex, GABAergic synapses in the axon initial segment have a depolarized reversal potential compared to those innervating the somatic domain due to a higher intracellular chloride concentration at the axon initial segment (Szabadics et al., 2006). Consequently, axo-axonic cells may excite rather than inhibit their postsynaptic pyramidal cells (Szabadics et al., 2006). However, this remains controversial (Glickfeld et al., 2009; Wang et al., 2014). It is not clear if depolarizing with a reversal potential still below threshold has predominantly an excitatory or shunting effect and will require further investigation, but it has been recently suggested that this depends on the excitatory state of the postsynaptic cell (Woodruff et al., 2011).

Sst INs

In contrast to PV INs, Sst INs are dendritic targeting (Dennison-Cavanagh et al., 1993) (de Lima and Morrison, 1989; Kawaguchi and Kubota, 1996, 1997; Wang et al., 2004), a feature that has important functional consequences (discussed in the Interneuron Circuits section). Sst INs also differ drastically from other INs in the dynamics of their excitatory inputs (Figure 1, Table I). Most INs have strongly or moderately depressing excitatory synapses. In stark contrast, excitatory inputs onto Sst INs, apparently regardless of subtypes, are strongly facilitating (Beierlein et al., 2003; Kapfer et al., 2007; Pouille and Scanziani, 2004; Silberberg and Markram, 2007; Thomson, 2003; Xu et al., 2013). This is a property determined by the postsynaptic cell, since the same excitatory axon has depressing synapses on a PV cell and facilitating onto a Sst IN (Buchanan et al., 2012; Reyes et al., 1998; Scanziani et al., 1998). Experiments in the hippocampus have shown that this unusual behavior is the result of the expression on Sst INs of the extracellular leucine-rich repeat fibronectin containing 1 (Elfn1) protein which regulates the release probability of the presynaptic terminal (Sylwestrak and Ghosh, 2012). It remains to be investigated whether the same or related proteins are responsible for the low release probability of excitatory synapses on SST cells in the neocortex.

As a result of the facilitating dynamics of their excitatory synapses, and other membrane properties of Sst INs that allow EPSP summation (Table I) excitatory inputs onto these cells produce supralinear responses. While PV INs require the synchronous firing of many presynaptic cells to fire due to their strongly depressing excitatory synapses and fast membrane time constant, the facilitation onto Sst INs enable even a single high frequency burst from one presynaptic cell to recruit Sst INs and produce feedback inhibition (Kapfer et al., 2007; Silberberg and Markram, 2007) (see Interneuron Circuits). Another feature of Sst INs is a muscarinic mediated depolarization. In response to bath applied agonists, the depolarization is strong enough that it is capable of producing prolonged spiking (Beierlein et al., 2000; Fanselow et al., 2008; Kawaguchi, 1997; Xu et al., 2013).

There is increasing evidence that Sst INs constitute a diverse group including cells that differ in morphological, electrophysiological and molecular properties (Table I). Despite these differences, all SST INs seem to have facilitating excitatory inputs and a muscarinic-mediated depolarization (Beierlein et al., 2003; Kapfer et al., 2007; Silberberg and Markram, 2007; Xu et al., 2013). Based on morphology, we can segregate Sst INs into two broad subgroups, Martinotti and non-Martinotti cells. In this review, we broadly define Martinotti cells as Sst expressing INs with a plexus of axon in L1, where it is known to target the tuft dendrites of pyramidal cells, including making synapses on spines (Chiu et al., 2013; Kawaguchi and Kubota, 1996; Wang et al., 2004). Non-Martinotti cells are here referred to as Sst INs lacking a significant axonal plexus in L1, despite sharing many of the properties of Martinotti cells (see Table I). We argue that this distinction is important since the cells we define as non-Martinotti (or non-L1-targeting) will clearly synapse onto different subcellular compartments or cell types and therefore will have a different impact on cellular and network computations than Martinotti cells (see below).

Martinotti cells are mainly present in L2/3 and L5/6 (Figure 1 and ​and2).2). In addition to arborizing in L1, a significant proportion of their axonal arbor, presumably contacting the basal dendrites of other neurons, is present in the layer where the soma is located. It seems that the vast majority of the Sst INs in supragranular layers and a significant fraction of those in infragranular layers are Martinotti cells. In contrast, the axon of most Sst INs in L4 of S1 largely remains within this layer, some of them additionally project to L2/3 (Ma et al., 2006; Xu et al., 2013). Moreover, L4 non-Martinotti Sst INs have several intrinsic electrophysological properties that differ from those of the Martinotti cells in supra and infragranular layers (see Figure 1, Table 1, (Ma et al., 2006; Xu et al., 2013)). Interestingly, L4 non-Martinotti INs also differ from Martinotti INs in terms of connectivity. While L2/3 Sst cells predominantly inhibit pyramidal neurons, L4 Sst INs predominantly target local PV INs and thus may produce disinhibition of L4 principal cells (Xu et al., 2013) (see Section on Disinhibition). However, it remains unclear whether the granular layer of other cortical areas contains Sst INs resembling those in S1. The morphological features of L4 non-Martinotti Sst INs are qualitatively very similar to L4 PV basket cells. However, synaptic dynamics, connectivity and electrophysiological properties, in addition to marker expression, clearly show that they are a functionally distinct IN subtype.

L5 of S1 seems to contain a yet undetermined but significant proportion of non-L1-targeting Sst cells (Ma et al., 2006; Munoz et al., 2014; Tan et al., 2008). The axons of infragranular non-Martinotti INs target mainly L4, but it is not known whether they also preferentially innervate PV cells, like L4 Sst INs do. In addition to these types, a few Sst cells in deep layers express nNOS (neuronal nitric oxide synthase) and are thought to have long-range projecting axons (Tamamaki and Tomioka, 2010) (see below).

It is not well established at present how other reported differences among Sst INs fit into this morphological classification. For example, L5 Sst INs have often been found to have an LTS (low-threshold spiking) firing pattern (Kawaguchi and Kubota, 1997; Ma et al., 2006). Although the term LTS has often been applied more broadly to Sst INs in general, the presence of rebound spikes from hyperpolarized potentials appears to be present more specifically in a subset of infragranular Martinotti cells, some of which are labeled with GFP in the transgenic X98 mouse line (Ma et al., 2006). Non-LTS Sst INs in L2/3 and L5 show regular spiking or burst spiking discharge patterns. On the other hand L4 and L5 non-Martinotti Sst INs typically have lower input resistance, brief spikes and fire at higher frequencies, resembling FS basket cells, but show much stronger firing frequency adaptation than these cells (Fanselow et al., 2008; Ma et al., 2006; Xu et al., 2013). The physiological significance of these differences in firing pattern is not yet clear, but they suggest a correlation between morphological subtype and electrophysiological properties.

Sst INs also display molecular heterogeneity. About 15–30% of the Sst INs in mouse neocortex express CR. Although so far only minor electrophysiological or morphological differences between CR+ and CR- Sst INs have been identified, distinct excitatory input patterns have been found (Xu and Callaway, 2009; Xu et al., 2006). Several other molecules are also expressed in subpopulations of Sst INs (see Table I). The relationship between molecular expression and morphological or electrophysiological diversity is not yet clear. However, recent transcriptional analysis of single cells suggests that Sst INs comprise genetically discreet subtypes (Tasic et al., 2016). As we discussed for PV cells, some of the molecules expressed by subpopulations of Sst INs are clearly important physiologically. For instance, a small subpopulation of Sst neurons in prefrontal cortex express oxytocin receptors, and this expression is critical to the modulation of sociosexual behavior by this hormone (Nakajima et al., 2014).

5HT3aR INs

5HT3aR INs represent ~30% of all neocortical INs and are thought to be more heterogeneous than the PV and Sst groups. However, all 5HT3aR INs express functional 5HT3a and nicotinic receptors (Lee et al., 2010). They are enriched in supragranular layers, where they represent the largest IN population (Figure 2). As mentioned previously, the 5HT3aR group can be divided in two subgroups based on the expression of the neuropeptide VIP (Figure 1). All neurons in L1 are GABAergic INs and most belong to the 5HT3aR group and are largely non-VIP-expressing. This layer contains the distal dendritic tufts of pyramidal cells, as well as intracortical axons from local PCs, long range inputs from other areas and corticopetal axons from high order thalamic nuclei and neuromodulatory centers. There is a great interest in this layer because of its presumed associative role and in top-down regulation of cortical processing as a result of the presence of projections from high order structures (Larkum, 2013). Based on their supragranular location, it has been suggested that 5HT3aR INs might be important mediators of such operations, a hypothesis supported by recent observations, as we will discuss further in this review.

Vip INs

Vip neurons represent about 40% of 5HT3aR INs in barrel cortex. They are present mainly in L2/3, but can be found in all layers (Figure 2). The large majority of Vip INs have a vertically oriented, bipolar-like dendritic morphology, the remaining being multipolar (Bayraktar et al., 2000; Pronneke et al., 2015). Dendritic trees of most bipolar Vip INs tend to be narrow and cross several layers in either direction and thus can sample translaminar inputs in several layers restricted to one column. Although the number of Vip INs in L1 is low, the dendrites of Vip INs in L2/3 extend fully through L1 reaching close to the pial surface, where they can be targeted by the many intracortical and subcortical projections to this layer. Consistent with their translaminar dendrites, L2/3 bipolar INs have been shown to receive inputs from several layers, which was less common for most other cell types studied (Xu and Callaway, 2009). Subtle differences among Vip INs with vertically oriented dendrites have been described. Some are bitufted, while others are single tufted, bipolar or tripolar (Bayraktar et al., 2000; Cauli et al., 2014). However, it is not clear that these differences in dendritic morphology are physiologically significant since they tend to sample similar intracolumnar and translaminar sectors. Here, we will use the term “bipolar” to denote all Vip INs with vertically oriented dentritic arbor. The axon of L2/3 Vip INs is also directed vertically, in a narrow columnar fashion, where their axonal projections often reach L4 and L5/6, in addition to their local axonal arbor (Bayraktar et al., 2000; Porter et al., 1998; Pronneke et al., 2015). These axonal features are reminiscent of what has been described as “horsetail” and double bouquet cells in primates (DeFelipe et al., 2006). Therefore, the direct influence of L2/3 bipolar Vip INs is likely to be vertically broad and laterally restricted. Interestingly, it has been observed that bipolar Vip INs in deeper layers follow different trends in their dendritic and axonal fields. L2/3 Vip INs had their dendrites largely restricted to supragranular layers and their axon extending to both supra- and infragranular layers. In contrast, Vip INs in deeper layers had dendrites spanning both supra- and infragranular layers, but had their axons restricted to L5/6 (Kawaguchi and Kubota, 1996; Pronneke et al., 2015). Multipolar VIP INs include VIP INs expressing CCK (see below) and a group of L6 multipolar VIP cells with an intralaminar axon spanning laterally (Bayraktar et al., 2000; Pronneke et al., 2015).

Subpopulations of Vip neurons express molecular markers that may help in subdividing this group of INs (see table I) (Cauli et al., 2014; Ferezou et al., 2007; Taki et al., 2000). About 10–30 % of Vip INs express Cck and about 50–70% of Vip INs express CR. In addition, CR and Cck are largely non-overlapping on Vip cells. Vip CR+ INs behave differently than Vip CR- neurons in terms of the role of activity in their migration and maturation during development (De Marco Garcia et al., 2011), suggesting that CR could be a useful marker to differentiate between Vip IN subpopulations. In fact, using intersectional Vip flp x CR cre mice, He et al., (He et al., 2016) found that VIP/CR cells were significantly enriched in irregular spiking bipolar neurons. Some Vip INs also express the ACh synthetizing enzyme choline acetyl transferase (ChAT). ChAT-expressing INs appear to be irregular spiking, CR+, and have “bipolar” dendritic morphology (Cauli et al., 2014; Porter et al., 1998). However, the cholinergic nature of these neurons is not clear. In fact in mouse and humans the vesicular acetylcholine transporter is not expressed in ChAT INs (Cauli et al., 2014). It is therefore unclear whether ChAT expression in VIP neurons is of functional significance. In contrast to Vip CR INs, Cck-expressing Vip INs tend to exhibit multipolar or bitufted dendrites, although bipolar cells can also be found (Freund et al., 1986; Kubota and Kawaguchi, 1997)(He et al., 2016). These neurons have small soma and are largely found in L2, although they are also present in other layers. These INs likely correspond to what has been referred to as small CCK basket cells, which, in contrast to the typical vertically oriented translaminar axonal arbor of the Vip bipolar cells, have a rather local axonal arbor (Freund et al., 1986; Kawaguchi and Kubota, 1996; Kubota, 2014; Wang et al., 2002).. At least a portion of Vip INs seems to form perisomatic basket terminals on their postsynaptic targets. Vip containing boutons have been found on both PCs and INs (David et al., 2007; Freund et al., 1986; Hioki et al., 2013; Kawaguchi and Kubota, 1996; Peters, 1990; Staiger et al., 2004). However, it is not clear if small basket cells expressing both Vip and Cck are the only source of these boutons. As we will discuss in the disinhibition section, Vip neurons, as a population, preferentially form synapses onto Sst neurons. This seems to be particularly true for the Vip bipolar (CR+) cells (Caputi et al., 2009; Jiang et al., 2015), which are the majority of the Vip cells. It is doubtful that Cck-expressing Vip INs exhibit the same connectivity pattern.

Perhaps, the most salient intrinsic electrophysiological feature of Vip INs is their relatively high input resistance, higher than most cortical neurons (Table I), a property that makes Vip neurons particularly sensitive to excitatory inputs. For instance, although thalamic stimulation in thalamocortical slices produces weak excitatory synaptic currents on Vip INs in L4 and deep L3, these can produce substantial depolarization due to their high input resistance (Lee et al., 2010).

Vip INs have often been described as having an irregular spiking (IS) firing pattern in response to depolarizing steps (Cauli et al., 2000; Lee et al., 2010; Porter et al., 1998). IS INs are characterized by an initial burst of action potentials followed by intermittent action potentials at an irregular frequency. The IS property is seen mainly at near threshold depolarizations, and is replaced by a regular adapting firing pattern during larger depolarizations. Porter et al., 1998, found that low concentrations of 4-AP, as well as DTX-I and DTX-K convert the IS firing pattern to a more regular discharge pattern, suggesting that a Kv1-mediated I_D-like K⁺ current contributes to irregular spiking. Irregular spiking might be seen often in Vip cells as a result of their high input resistance, which increases the possibility that noise, an intrinsic subthreshold oscillation, or a small synaptic input will produce sufficient depolarization to reach spike threshold. The intermittent spikes observed during the train may represent spikes that escape the adaptation produced by the I_D-like K⁺ current. In addition to irregular spiking, bursting and strongly adapting Vip cells have been reported (Cauli et al., 2000; Kawaguchi and Kubota, 1996; Lee et al., 2010; Porter et al., 1998; Pronneke et al., 2015). It is not clear to what extent these differences in firing pattern are reflective of distinct Vip IN subpopulations and what their functional significance might be. Excitatory inputs to VIP cells are depressing, as is the case for the inputs from most INs (Porter et al., 1998; Rozov et al., 2001). However, Caputi et al. (Caputi et al., 2009) suggested that the output synapses of CR+ Vip cells on pyramidal cells, as well as on PV and somatostatin INs are slightly facilitating.

Like all 5HT3aR INs, Vip INs are strongly depolarized by 5HT3aR agonists (Ferezou et al., 2002; Lee et al., 2010), in addition to showing nicotinic ACh responses, suggesting that activity in neuromodulatory centers, such as raphe and basal forebrain neurons, could rapidly activate these interneurons. Anatomical, pharmacological and optogenetic evidence support this view (Acsady et al., 1993; Arroyo et al., 2012; Choi and Callaway, 2011; Ferezou et al., 2002; Lee et al., 2010). It has been reported that Vip-expressing bipolar neurons are also depolarized by muscarinic agonists (Kawaguchi, 1997), however this has not been extensively studied.

non-Vip 5HT3aR INs

Non-Vip 5HT3aR INs represent about 60% of 5HT3aR INs and about 90% of all L1 INs (Figure 2). They include the neurogliaform cells (NGFC), Cck-expressing INs (presumably non-VIP Cck basket cells) and other less clearly defined types (Table I).

Electrical connectivity in interneurons

Electrical synapses mediated by gap junctions have been used as a defining feature of different interneuron subtypes and are a major component of the connectivity between interneurons. While pyramidal cells do not show electrical coupling in mature animals, the electrical connection probability among related interneurons remains high, but apparently mainly among interneurons of the same class. For instance, as initial studies showed, PV-expressing FS cells within a distance of about 100–150 um are densely interconnected, as is the case among “LTS” SST-expressing INs, but FS cells and SST cells are not electrically connected to each other (Amitai et al., 2002; Galarreta and Hestrin, 1999; Gibson et al., 1999; Hestrin and Galarreta, 2005). Homotypic coupling has also been reported for multipolar bursting PV INs and irregular-spiking INs expressing cannabinoid receptors; presumably CCK basket cells (Blatow et al., 2003; Hestrin and Galarreta, 2005) as well as for VIP interneurons (Karnani et al., 2016). Electrical coupling between cells has therefore been interpreted as a strong indicator of INs belonging to the same subtype. However, conflicting data exists regarding the electrical connectivity of neurogliaform cells. Chu et al., (Chu et al., 2003) reported that LS INs in layer 1 are interconnected by gap-junctions but that these INs are not connected to L1 non-LS INs. On the other hand Simon et al., (Simon et al., 2005) found that NGFCs in layer 2/3 are not only densely electrically connected among themselves, but also to many other IN types including FS basket cells, suggesting that electrical coupling of NGFCs is promiscuous (Simon et al., 2005). This apparent discrepancy needs to be clarified; more generally, the rules of electrical connectivity among the different types of 5HT3aR INs need to be investigated in more detail. Furthermore, now that it is clear that the PV and SST IN groups are heterogeneous it would be of interest to determine whether there is selectivity of electrical connectivity between IN subtypes that are members of the same major group (i.e. are Martinotti and not Martinotti cells in L5 interconnected?). There are already indications that PV basket cells and chandelier cells are electrically connected (Hestrin and Galarreta, 2005; Woodruff et al., 2011).

Gap junctions are symmetrical bidirectional synapses that pass both depolarizing and hyperpolarizing signals resulting in both excitatory and inhibitory PSPs. This depends on the speed of the AP and the speed and size of the AHP and the low-pass filtering properties of electrical synapses, which result in the transmission of slow membrane potential variations but the attenuation of fast changes such as fast action potentials (Galarreta and Hestrin, 2001; Gibson et al., 2005; Hestrin and Galarreta, 2005). As extensively shown by modeling and pair recordings in slices, electrical connectivity results in the generation of IN networks that fire synchronously, however small to no effects of the knockout of connexin 36, the main connexin isoform in interneurons, have been observed on oscillations and rhythms in spite of the loss of electrical connectivity (Buhl et al., 2003), an observation that could be explained by compensatory changes.

Long-range projecting GABAergic interneurons

As reflected in the term ‘interneurons’, the majority of cortical GABAergic neurons strictly target nearby cells and control the local network activity. However, it has been known that some cortical GABAergic neurons also project to other brain areas (Alonso and Kohler, 1982). Long-range inhibitory cells have been found to reciprocally connect hippocampus and septum, hippocampus and entorihnal cortex and different neocortical areas (reviewed in (Caputi et al., 2013)) as well as corticofugal neocortical GABAergic neurons projecting to the amygdala (Lee et al., 2014b) and basal ganglia (Jinno and Kosaka, 2004; Tomioka et al., 2015). In hippocampus-related projections, long-range GABAergic neurons tend to target other GABAergic neurons in target areas (Acsady et al., 2000; Basu et al., 2016; Freund and Antal, 1988; Melzer et al., 2012; Toth et al., 1993). In addition, the types of GABAergic neurons in long-range projections in the hippocampal system seem to be heterogeneous based on their molecular markers (reviewed in (Jinno, 2009)). In neocortex, long-range projecting GABAerginc INs have been generally assumed to be nNOS-expressing Sst INs (reviewed in (Tamamaki and Tomioka, 2010)). However, long-range projecting GABAergic neurons belonging to other molecular groups, such as PV and Vip, have also been found (Jinno and Kosaka, 2004; Lee et al., 2014b; Tomioka et al., 2015)(Table 1).

GABAergic INs as sources of neuropeptides

Neuropeptides such as Sst, Vip, Cck and NPY in specific IN subtypes have been useful markers to classify and characterize IN subtypes. However, these are neuromodulators that are known to have a powerful impact on the function of neurons and the INs that express them are the main source of these peptides in the cortex. It is thought that neuropeptide release requires high-frequency firing (Baraban and Tallent, 2004; van den Pol, 2012; Zupanc, 1996), but virtually nothing is known about the conditions in which they are released from INs. Differential regulation of release between neurotransmitters and neuropeptides is possible because they are stored separately in small synaptic vesicles (SSVs) and large dense-core vesicles (LDCVs) respectively. While SSVs are densely clustered in axon terminals, LDCVs are detected in axon, soma and dendrites (Morris and Pow, 1991; Pow and Morris, 1989). Release of neuropeptides from dendrites has been reported (Castel et al., 1996; Landry et al., 2003; Simmons et al., 1995). Some of neuropetidergic neurons express autoreceptors (Freund-Mercier et al., 1994; Hurbin et al., 2002). Thus, activation of peptide receptors on the dendrites or soma provides positive feedback to dendritic peptide release, thus dendritic neuropeptide release can be self-sustaining and long- lasting (Ludwig et al., 2005; Ludwig et al., 2002). The mechanisms by which cortical INs regulate the release of neuropeptides still needs to be addressed. It has been shown however, that Vip INs release Vip, a potent vasodilator, and that single cell stimulation of Vip+ bipolar neurons is sufficient to elicit vasodilatation of nearby arterioles (Cauli et al., 2004). Interestingly, acetylcholine produces vasodilatation of cerebral arterioles (Fergus and Lee, 1997), perhaps via the nicotinic activation of Vip INs. Molnar et al., (Molnar et al., 2014) recently reported that NGFCs strongly express insulin and that local application of glucose or glibenclamide to NGFCs mimics the excitation suppressing effect of applied insulin on local microcircuits.

A. Feedforward inhibition

Feedorward inhibition (FFI) is the process by which an afferent excitatory input source, in addition to contacting principal neurons, also synapses onto local inhibitory neurons, which in turn provide disynaptic inhibition to the principal cells receiving the excitatory input (Figure 4, ​,5).5). Conceptually, a FFI motif in its pure form is inherently a circuit mechanism regulating local integration by tracking the activity of incoming inputs, independently of the local network activity (Buzsaki, 1984). However, in reality this should not be taken literally, since the coexistence of other circuit and cellular mechanisms can effectively modulate the ability of FFI circuits to accomplish this task. Virtually any external excitatory input source to a neocortical area has been observed to also trigger short latency disynaptic inhibition (Toyama et al., 1974) and FFI seems ubiquitous in the central nervous system. In most, but not all, reported cases in neocortex, FFI is mediated by PV FS basket cells. The involvement of perisomatic targeting PV neurons, in combination with their intrinsic properties enabling high speed and temporal fidelity, provides unique high pass filtering properties to these feedforward inhibitory circuits, imposing coincidence detection onto postsynaptic neurons.

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Figure 5

Thalamocortical FFI by PV neurons imposes coincidence detection

A. Thalamocortical neurons synapse onto both excitatory principal cells (PC) and PV neurons. Thalamocortical connections are stronger onto PV than PC neurons. B. FFI by PV INs curtails TC mediated EPSPs on PCs leaving a narrow temporal window of opportunity for excitatory inputs to summate. Consequently, near synchronous inputs are required for efficient summation of EPSPs and to drive action potential firing on the PC. C. Weakening of PV INs FFI by short-term depression of TC synaptic inputs onto PV cells and PV INs outputs to PC (Gabernet et al., 2005). These two steps of adaptation weaken FFI more than direct feed-forward excitation of PC neurons. D. Weakening of FFI by modulation of PV IN output synapses. Both GABAB receptor-activation by NGFCs (Chittajallu et al., 2013) and muscarinic receptor-activation by acetylcholine (Kruglikov and Rudy, 2008) reduce inhibitory outputs to PCs. E. Relationship between the summation of EPSPs on PCs and their temporal difference for different strengths of FFI. As FFI is weakened, asynchronous inputs can summate more effectively (Pouille and Scanziani, 2001). F. FFI regulates the gain of PC populations. As excitatory drive increases, PV cells recruitment increases at a higher rate than the recruitment of excitatory cells. This will prevent PC population from saturation and will allow a wider dynamic range of the local PC population than if inhibition was absent (dotted line) (Pouille et al., 2009).

B. Feedback inhibition

In contrast to the FFI circuit motif, in which the source of excitation of INs originates from incoming external excitatory afferent axons to the local network, in feedback inhibition (FBI) the source of excitation is locally generated and interneurons synapse back to the local PC population (Figure 6). The feedback action from INs then reduces or prevents further discharges of the excitatory cells. Most IN subtypes receive inputs from multiple surrounding PCs and in turn provide inhibitory output to the excitatory cells and therefore are part of an FBI circuit motif. As was the case for FFI, the specific IN type involved in a given FBI loop will show particular recruitment patterns and provide different functional features to the local PCs. However, regardless of the IN involved, this recurrent inhibition controls the excitatory-inhibitory balance of local populations of principal cells and shapes spatial and temporal features of their activity patterns in fundamentally different ways than FFI. While the FFI is an incoming input tracking circuit mechanism and does not depend on local activity level, FBI is the opposite, i.e. a circuit mechanism tracking the local outputs that are being generated.

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Figure 6

Feedback inhibition (FBI) and differential effect of PV and Sst INs-mediated inhibition

A. FBI circuit motif encompassing both recurrent and lateral feedback inhibition. B. PV and Sst interneurons differentially summate excitatory inputs from local PCs. PV neurons (top), due to their low input resistance, fast membrane time constant and depressing excitatory inputs show a decrease in spike probability upon repetitive excitation (left) and are thus synchrony detectors, requiring the near coincident action of different cells to spike (right) (Silberberg, 2008; Silberberg and Markram, 2007). In contrast, Sst INs (bottom) have a high input resistance, slow membrane time constant and facilitating excitatory inputs and therefore show an increase in spike probability upon repetitive stimulation. This makes Sst neurons sensitive to individual excitatory cell’s firing rate and bursting (Kapfer et al., 2007; Silberberg, 2008; Silberberg and Markram, 2007). C. Assembly competition and synchronization of local PCs by PV neurons. Synchronously active PCs will recruit PV neurons that will then inhibit the local population (Silberberg, 2008).. D. Assembly competition and ‘winner takes all’ circuit mechanism with Sst INs FBI (Silberberg, 2008). By following the most active PC(s), an Sst IN will prevent the activation of other neighboring cells (except other Sst INs). E. Perisomatic inhibition by PV INs regulates the timing of action potentials (Royer et al., 2012). The speed and effectiveness at which PV INs perform this task imposes short temporal windows for excitation to generate action potentials within the local population, thus favoring their synchronization (Cobb et al., 1995). In contrast, dendritic targeting bias of Sst INs regulates input integration at the dendrite and dendritic electrogenesis such as NMDA and calcium spikes that can generate burst firing (Larkum et al., 1999).

Given the divergence of interneuron connectivity, any given IN will inhibit not only PCs from which it received excitation but also others that are part of the local population. This is due to the fact that INs generally show dense local connectivity (Fino and Yuste, 2011; Packer and Yuste, 2011) and that excitatory neuron populations in many cases show sparse activity (Barth and Poulet, 2012). In addition, some cortical INs have axons that extend beyond the local area where their soma is located, which can be in a transcolumnar and/or translaminar fashion (Helmstaedter et al., 2008; Katzel et al., 2011). Thus INs can provide inhibition to neighboring populations of principal cells located at a certain distance that may not have provided excitation to that particular interneuron population, a phenomenon more generally referred to as lateral inhibition (Figure 4,​,6).6). In lateral inhibition, as we use the term here, a population of pyramidal cells receives “feedback inhibition” from interneurons that did not received excitation from this population, regardless if the PCs are within or flanking the cells driving the INs providing feedback. These different forms that FBI encompasses have been proposed to participate in important phenomena such as surround suppression (Adesnik et al., 2012), assembly selection and competition (Roux and Buzsaki, 2015), oscillatory coupling (Buzsaki and Wang, 2012), and grid field formation (Couey et al., 2013).

While it is likely that most IN subtypes participate in local feedback loops, there are qualitative and quantitative differences in the connectivity between any IN subtype and the local PC population. Not only the presence of an excitatory-inhibitory feedback loop but also its strength are important to weight its significance. There are multiple examples of recurrent inhibitory loops in cortical circuits. Here we will focus on feedback inhibitory circuits that have been described for Sst and PV INs in the neocortex. Although impairment of PV and Sst INs have been implicated in the generation of hypersynchronous activity and epilepsy (Goldberg and Coulter, 2013; Hunt et al., 2013; Ito-Ishida et al., 2015; Paz and Huguenard, 2015), there are differences in the recruitment and functional impact of these circuits that reflect the specialized properties of these two types of interneurons.

We thank all the members of the Rudy lab for helpful discussions during the writing of the manuscript. This work was supported by NIH grants R01S30989 and P01NS074972 to B.R.