The neuronal identity bias behind neocortical GABAergic plasticity

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The neuronal identity bias behind neocortical GABAergic plasticity Camille Allene, Joana Lourenc¸o, and Alberto Bacci Sorbonne Universite´s, Universite´ Pierre et Marie Curie (UPMC Paris 6), Unite´ Mixte de Recherche S 1127; Institut National de la Sante´ et de la Recherche Me´dicale (INSERM) Unite´ 1127; Centre National de la Recherche Scientifique (CNRS) Unite´ Mixte de Recherche 7225; Institut du Cerveau et de la Moelle e´pinie`re (ICM), 75013 Paris, France

In the neocortex, different types of excitatory and inhibitory neurons connect to one another following a detailed blueprint, defining functionally-distinct subnetworks, whose activity and modulation underlie complex cognitive functions. We review the cell-autonomous plasticity of perisomatic inhibition onto principal excitatory neurons. We propose that the tendency of different cortical layers to exhibit depression or potentiation of perisomatic inhibition is dictated by the specific identities of principal neurons (PNs). These are mainly defined by their projection targets and by their preference to be innervated by specific perisomatic-targeting basket cell types. Therefore, principal neurons responsible for relaying information to subcortical nuclei are differentially inhibited and show specific forms of plasticity compared to other PNs that are specialized in more associative functions. Information flow across neocortical layers Higher brain functions, such as conscious perception and cognition, result from the correct flow of information between different neuronal cortical circuits. These circuits are composed of highly interconnected neurons, about 80% of which are glutamatergic (excitatory) PNs that are functionally and anatomically organized in six radial layers [1]. Cortical layer identity is defined by the density of specific PNs as well as by their afferent and efferent projections, thereby conferring each layer a functional specialization [1] (Figure 1). Indeed, as a general scheme, in primary sensory cortical areas, sensory inputs relayed by specific thalamic nuclei mainly target layer (L) 4, although L5 and L6 also receive prominent thalamic innervation [2], whereas input from associative thalamus segregates in different cortical layers, mainly innervating L1 and superficial L5a [3–6] (Figure 1). Therefore, L4 strongly contributes to the initiation of cortical sensory information processing, which is relayed to supragranular L2/3. This is considered to be an integrative cortical layer because it combines feed-forward information from L4 with feedback input from other neocortical regions. L2/3 PNs project to infragranular L5, which, together with L6, is the main source of cortical output to subcortical structures: in Corresponding author: Bacci, A. ([email protected]). Keywords: inhibition; GABAergic plasticity; neocortex; retrograde signaling. 0166-2236/ ß 2015 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.tins.2015.07.008

particular, large L5 pyramidal cells drive subcortical structures involved in action (basal ganglia, colliculus, ventral spinal cord) whereas L6 pyramidal cells mainly innervate first-order thalamic nuclei, thus establishing the thalamocortico-thalamic loop that is believed to play a crucial feedback role in shaping cortical input and tuning thalamic receptive fields [7]. Overall, L5 is considered as the driving motor of cortical columns, whereas L6 is believed to mainly have a control feedback output [1]. Notably, however, L5 PNs do not function only as cortical drivers, and they have also been proposed to be important cellular associative elements, integrating feed-forward sensory stimuli with Glossary Associative or Hebbian plasticity: the ability to change the strength of synaptic transmission (either potentiating or depressing it) via the coordinated activity of pre- and postsynaptic neurons, based on Donald Hebb’s definition. In the case of inhibitory synapses, the application of this rule is somewhat paradoxical because increased activation of inhibitory synapses results in decreased postsynaptic excitability. Interneurons: originally described by Santiago Ramo´n y Cajal as small neurons with short dendrites and locally-projecting axons, cortical interneurons are a highly heterogeneous cell population that uses GABA as neurotransmitter. In cortical circuits, GABAergic interneurons are the major providers of inhibition and control all forms of cortical activity. In 2008, a dynamic nomenclature of the features of GABAergic cortical interneurons was proposed, called ‘Petilla terminology’. Non-associative plasticity: changes in synaptic strength can occur in response to activation of postsynaptic neurons only, without pre–post pairing of activity. Synaptic plasticity can be triggered by cell-autonomous mechanisms when specific activity patterns of a single neuron cause changes in the weight of synaptic transmission onto the same neuron. Perisomatic inhibition: the perisomatic compartment of pyramidal cells is a domain of plasma membrane which includes the cell body, the axon initial segment, and the proximal apical and basal dendrites up to a distance of 100 mm. Cortical perisomatic inhibition originates from GABAergic synapses formed by three major types of GABAergic interneurons, including parvalbumin-containing fast-spiking basket cells and axo-axonic cells, as well as cholecystokinin-expressing regular-spiking basket cells. The perisomatic compartment is primarily associated with the generation of action potentials, and thus perisomatic inhibition modulates the temporal dynamics of PN firing. Retrograde signaling: conventional chemical neurotransmission occurs anterogradely – in other words, the release of neurotransmitters, neuropeptides, and other messengers from presynaptic terminals changes postsynaptic neuron excitability. Nevertheless, neurotransmission can also act ‘backwards’ (or ‘retrogradely’) because a variety of signaling molecules released from postsynaptic neurons can affect presynaptic function. Endocannabinoids, nitric oxide, and neurotrophins are among the most common retrograde messengers. Retrograde signaling can play a crucial role in the formation, maturation, and plasticity of unitary connections. Depolarization-induced suppression of inhibition (DSI): postsynaptic depolarization or action-potential firing induces Ca2+-dependent mobilization of endogenous cannabinoids, which act retrogradely on specific presynaptic GABAergic terminals expressing cannabinoid receptor type 1 (CB1). The interaction of endocannabinoids and CB1s results in a robust, albeit short (seconds), reduction of GABA release. This phenomenon is ubiquitous to many CNS areas, including the neocortex.

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Pia L1

L2/3

L4

L5a

L5b

L6 WM

To other corcal areas

To other corcal areas From sensory thalamus

To subcorcal areas

From associave thalamus

To thalamus and other corcal areas

Figure 1. Excitatory neocortical circuits. Simplified diagram illustrating the major subtypes of cortical excitatory neurons, their localization within different lamina and the major input–output excitatory connectivity patterns. Layer L4 principal neurons (PNs) (spiny-stellate neurons, star pyramids, or small pyramidal neurons) are the major recipients of primary sensory thalamic nuclei which send collaterals to L5 and L6. Input from associative thalamus targets L1 dendritic fields and L5a. In orange are represented PNs receiving or targeting mostly subcortical areas, such as L4 PNs and deep L5 thick-tufted PNs. Neurons represented in yellow symbolize PNs mostly projecting to other cortical areas and that have a more associative function. Abbreviation: WM, white matter.

internal feedback representing contextual information originating from associative thalamic nuclei targeting L5 PN dendritic tufts in L1 (Figure 1) [6,8]. In addition, L6 was recently shown to have an unexpected role in modulating the gain of sensory responses in supragranular layers, via translaminar inhibition [9,10]. Cortical PNs have, overall, been considered to be homogenous within each cortical layer. Importantly, however, PNs can be subgrouped into different cell types according to their projection targets, gene expression, as well as dendritic and axonal morphology and functional features (Figure 1) [11–21]. Segregation of different PN subtypes and/or their preferential connectivities can define functional subnetworks or even anatomical sublayers in specific cortical areas [19,22–28]. Although information is believed to be carried by PNs, neocortical activity is strongly modulated by a rich diversity of inhibitory, locally-projecting GABAergic interneurons (see Glossary). This cell class represents a relative minority (20%), but interneurons are characterized by a dense and highly divergent synaptic meshwork. Indeed, a global ‘blanket of inhibition’ to nearby PNs was suggested as the underlying connectivity logic of interneurons [29–32]. However, whereas this logic 2

seems to apply for specific interneuron subtypes, other important cortical inhibitory circuits follow more detailed connectivity rules with PNs. Cognitive-relevant cortical activity depends on the specific properties of synapses connecting different elements of cortical microcircuits. One prominent feature of synapses is their well-known ability to undergo plasticity in response to specific stimuli. Increased or reduced synaptic transmission can be triggered and maintained by many mechanisms, and, importantly, several forms of plasticity at specific synapses (both inhibitory and excitatory) originating from different neuron types might affect distinct cortical circuit computations. We review the anatomical and functional evidence indicating that different PN subtypes can be preferentially targeted by specific GABAergic interneuron classes, thereby providing specialized inhibitory control of different PNs and defining their tendency to depress or potentiate their overall perisomatic inhibitory strength. Functional diversity of cortical inhibitory circuits and their plasticity Neocortical interneurons are highly heterogeneous and can be classified by several anatomical and functional

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Table 1. Functional classification of neocortical interneuron subtypesa Connectivity Perisomatic inhibition pattern with PNs Chandelier cells Basket cells (BCs) Name PV Parvalbumin (PV) Molecular marker

Dendritic inhibition

BCs Cholecystokinin (CCK)

Firing properties

Fast-spiking (FS)

FS

Synaptic properties

Fast, reliable, shortterm depression

Fast, reliable, shortterm depression

Peculiarity

Forms synapses with PNs only with their axon initial segment

High-degree of selfinnervation Strongly coupled to other PV BCs via chemical synapses and gap junctions

Function

Modulation of action Modulation of PN ? potential generation spike timing Generation and driving of several network oscillations Prominent role in the critical period and refinement of sensory maps Tuning of orientation selectivity NO-dependent LTPi; DSI; LTDi (?) ? spike-timingdependent plasticity (STDP)

Plasticity of synapses onto PNs

Martinotti cells Somatostatin (SST)

Regular spiking (RS) Low-threshold Irregular spiking (IS) spiking (LTS) RS Fast, reliable, shortFast, unreliable, variable short-term term depression plasticity Small and large BCs Ascending axonal Large BCs highly projections express presynaptic Form synapses with CB1 receptors distal PN dendritic apical tufts Receive facilitating glutamatergic synapses

Other

Neurogliaform cells NO synthase (NOS)

Late-spiking (LS)

Bipolar Vasoactive intestinal peptide (VIP) Burst-spiking (BS) RS

Slow, unreliable

Lack of postsynaptic specializations Volume GABA transmission Extremely slow GABAA responses Activation of dendritic GABABR

Modulation of PN Modulation of dendritic integration dendritic excitability Modulation of goaldirected behavior Providers of lateral inhibition in sensory cortices Modulation of input from motor to sensory cortex Auditory discrimination ? ?

Form synapses with other interneurons selectively (preference for SST cells) Involved in neurovascular coupling Cortical circuit disinhibition Modulation of input from motor to sensory cortex Auditory discrimination

?

a

The table lists some of the properties of some major subclasses of cortical interneurons and is by no means exhaustive. References in the main text.

features [33–37] (Table 1). Despite the great diversity, however, one relevant functional classification relies on their specialized connectivity pattern with specific domains of PNs. Indeed, basket cells (BCs) predominantly form synapses onto the perisomatic region of PNs, making them ideally suited to control PN spike timing [38–45]. In particular, BCs can be divided in two major subgroups: one expressing the calcium-binding protein parvalbumin (PV) with a fast-spiking (FS) firing behavior, and another expressing the peptide cholecystokinin (CCK) that often shows irregular or burst spiking [37]. Interestingly, although both target the PN perisomatic compartment, CCK and PV BCs possess striking firing and synaptic differences: PV BCs provide fast, strong and reliable inhibition, whereas CCK BCs (at least in the hippocampus) show more unreliable and asynchronous transmission, and are the target of several neuromodulators (Table 1) [39,46–48]. Other interneuron subtypes preferentially target dendrites, and thus they are responsible for controlling dendritic information processing and integration of excitatory inputs. Of these, two notable classes are represented by somatostatin (SST)-expressing Martinotti cells and neurogliaform cells (NGFCs), the former providing precise

dendritic inhibition [8,34,35,49,50], the latter producing nonspecific slow volume GABAergic transmission, which is nonetheless restricted to the dendritic field of the PNs (Table 1) [51–53]. This suggests that each interneuron subclass, regardless of their specific synaptic territory, may provide a differential modulation of PN output by using distinct mechanisms. In addition, specific interneuron types [such as vasoactive intestinal peptide (VIP)expressing cells] are specialized in targeting other inhibitory cells, therefore being in an ideal position to disinhibit, and thus paradoxically ultimately increase, the excitability and information flow between networks of PNs [54–56] (Table 1). Overall, this dense, powerful, and highly specialized inhibition originating from this rich interneuron diversity ends up sculpting all forms of cortical activity [57]. As mentioned above, synapses can change their strength in response to specific stimuli. Indeed, synaptic plasticity can be triggered by specific patterns of pre–post activity and/or by sensory experience, and can be maintained over different timescales (ranging from seconds to months). In particular, the plasticity of excitatory glutamatergic synapses has been extensively studied, and it has been linked to learning and memory [58,59]. Importantly, 3

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similarly to their glutamatergic counterparts, GABAergic synapses can also change their strength [60,61]. However, the function of GABAergic plasticity is still largely unknown. In the following we mainly focus on cell-autonomous, non-associative plasticity of inhibitory synapses onto neocortical PNs from perisomatic targeting BCs. This plasticity is triggered by the sole activity of postsynaptic PNs, without the requirement of coordinated pre–post activity. Activity of PNs alone potentiates or depresses the strength of impinging GABAergic transmission. We will discuss how cortical-layer specificity of this form of GABAergic plasticity could be reconciled with a model in which the specific identity of postsynaptic PNs determines the prevalence of distinct forms of plasticity of inhibitory transmission. Is there a layer-specificity of cell-autonomous cortical GABAergic plasticity? The case of CB1+ and CB1S BCs Neocortical GABAergic synapses can be potentiated or depressed in response to several conditioning protocols, such as, for example, those involving simultaneous activation of pre- and postsynaptic neurons, including spike timing-dependent plasticity (similar to associative or Hebbian plasticity; see Glossary) [62–64]. However, GABAergic synapses can undergo short (seconds)- or long (hours)term changes in their strength in a cell-autonomous, nonassociative manner; in other words, GABAergic synapses change their strength in response to postsynaptic activity only. This appears to be a prominent pattern of GABAergic plasticity in cortical structures, and, when it affects presynaptic release probability, it inevitably involves retrograde synaptic signaling. One major form of nonassociative plasticity of inhibitory synapses is that mediated by retrograde endocannabinoid (eCB) signaling. Briefly, postsynaptic Ca2+ elevations and/or activation of metabotropic glutamate or acetylcholine receptors,

(A1)

PV (A2) II-III.

CBI II-III.

(A3) Overlay (B)

induce postsynaptic mobilization of eCBs, which are released and act backwards, causing a decrease of presynaptic GABA release from specific interneuron classes [65– 75]. These interneurons are mostly [76], but not exclusively [77], large CCK BCs exerting perisomatic control of PNs [39]. eCB-mediated plasticity of GABAergic synapses can last either seconds (depolarization-induced suppression of inhibition, DSI) [71,72,74,75,78–81], or hours (long-term depression of inhibition, defined as I-LTD or LTDi) [11,60,69,82,83], and it can be purely non-associative [11,71,75,84] or rely on heterosynaptic or high-frequency presynaptic activation [85]. eCB-dependent plasticity (particularly short-term) has been extensively studied especially in the hippocampus and cerebellum [65,66] where it seems to be ubiquitously expressed. In the neocortex, this form of GABAergic plasticity is differently expressed across layers. Indeed, DSI can be reliably evoked in neocortical L2/3, while it seems to be less prominent in L5 [86–88]. In particular, large L5b PNs, presumably projecting to subcortical structures, do not display DSI, in contrast to L5b small pyramids, which presumably project to the contralateral cortex via the corpus callosum, and whose inhibitory synapses can be modulated by eCBs [86]. This layer- and sublayer-specificity of eCB-mediated plasticity correlates well with the density of GABAergic terminals expressing cannabinoid receptor type 1 (CB1): high in L2/3, L5a, and L6 (Figure 2A–C) [86,89,90,101]. Hence, retrograde eCB-dependent long-term depression of GABAergic transmission has been documented in cortical L2/3, triggered by postsynaptic depolarization only, and is associated with a persistent reduction of PN excitability by autocrine eCBs [11] (Figure 2D). Interestingly, double-immunofluorescence staining revealed that CB1- and PV-immunoreactive axons are enriched in alternate layers and sublayers in a complementary manner: L5 has stronger PV but weaker

Overlay

(D)

II-III.

(C) IV.

IV.

IV.

V.A

V.A

V.A

V.B

V.B

V.B

VI.

VI.

VI.

Baseline

LTDi

AM-251

Baseline

LTPi

L-NAME

Overlay (E)

N=O

Figure 2. Morphological and functional complementary expression of perisomatic inhibition and plasticity from PV and CCK BCs. (A) CB1 (red) and PV (green) immunostaining in the rat somatosensory cortex. The laminar density of the labeled axons is essentially complementary in the two immunostainings. (B,C) In layers L2/3, the PV- and the CB1-positive terminals are present at a similar density around the pyramidal cell somata [asterisks in (B)]. By contrast, in L5b, the density of the PV-positive boutons was high [particularly around large pyramids, see asterisk in (C)]. Panels (A–C) are reproduced with permission from [86]. (D) L2/3 PNs express cell-autonomous LTD of GABAergic transmission induced by postsynaptic depolarizations and reverted by the CB1 antagonist AM-251. (E) Large L5 PNs respond to the same protocol with NO-dependent LTPi induced at PV cell terminals (green). Panels (D) and (E), respectively, show schematic representations of results illustrated in [11] and [91]. Abbreviations: CB1, cannabinoid receptor type 1; CCK, cholecystokinin; L-NAME, N-nitro L-arginine methyl ester PN, principal neuron; PV, parvalbumin; LTDi, longterm depression of inhibition; LTPi, long-term potentiation of inhibition; NO, nitric oxide.

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Review CB1 expression than L2/3, which shows an opposite trend (Figure 2A–C) [86]. Accordingly, when large PNs in L5b are depolarized or fire bursts of action potentials, they do not exhibit eCB-dependent depression, but instead a long-term potentiation of inhibitory responses (LTPi). In addition, this cell-autonomous form of LTPi requires retrograde synaptic signaling, but in this case the messenger is nitric oxide (NO) specifically acting on CB1-negative, PV-expressing BCs [91] (Figure 2E). Importantly, other forms of plasticity of GABAergic transmission have been documented which do not require retrograde signaling, but instead rely on postsynaptic GABAAR trafficking and do not necessarily depend on distinct presynaptic interneuron subtypes [92–94]. Therefore, several forms of plasticity relying on different molecular mechanisms can coexist, depending on the specific brain state and/or distinct stimulus patterns. Importantly, other forms of GABAergic plasticity can be induced by stimulation of presynaptic afferents only [95–100], although these paradigms can activate postsynaptic metabotropic receptors (e.g., mGluRs). Even in these cases, however, it appears that L2/3 tend to express eCBdependent long-term depression of inhibition [96–100], similar to the heterosynaptic LTDi described in the hippocampus and amygdala [83–89,101–102]. Conversely, L5 PNs exhibit eCB-independent forms of long-term potentiation, relying on brain-derived neurotrophic factor (BDNF)/tyrosine receptor kinase B (TRKB) signaling pathways [95,98,99]. Overall, we can conclude that inhibitory synaptic depression is more widely expressed in L2/3, whereas potentiation is more prominent in L5. Notable exceptions of this rule are LTPi phenomena in L2/3 of auditory cortex [99] and eCB-dependent LTDi in L5 of the prefrontal cortex (PFC) [100]. Accordingly, CB1 expression in deep layers of PFC seems to correlate with this ‘unusual’ plasticity expression [89]. Differently from this tendency to express bidirectional non-associative plasticity in L2/3 and L5, L4 appears to require different mechanisms to induce plasticity of inhibition. According to anatomical data, CB1 expression is very low (if not absent) in L4, implying the absence of eCBdependent, cell-autonomous forms of GABAergic plasticity [86] although this will require functional confirmation (see e.g., [103]). Accumulating evidence indicates that PNs in L4 can produce plasticity of GABAergic synapses only if presynaptic activation is coupled to subthreshold postsynaptic depolarization because presynaptic or postsynaptic activity alone, as well as pre–post simultaneous firing, do not induce any forms of plasticity [63,64]. Interestingly, the structural plasticity underlying sensory refinement of the visual cortex during development (critical period) determines the polarity of synaptic strength at L4 inhibitory synapses, which switches from depression to potentiation at the onset of the critical period (Table 1) [63,93,104–106]. Overall, it appears that PNs can adjust the strength of inhibitory synapses impinging on their perisomatic region in a layer-specific fashion. This seems to be due to the amount of GABAergic synapses originating from either PV or CCK (CB1+) BCs. The complementary distribution of CB1+ and PV+ terminals in specific cortical layers will

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dictate the actual ratio of synapses formed by PV and CB1 cells on any given PN, and thus its tendency to depress or potentiate perisomatic inhibition. In particular, CB1+ BCs consistently depress the strength of their synapses, whereas PV+ interneurons tend to potentiate them, although depression of GABA release from PV BCs can occur in L4 [62], and in L2/3 in response to spike-timing inducing protocols [63,64]. Is cortical GABAergic plasticity determined by postsynaptic PN identity? Recent work suggests that neurons do not connect to other components of the neuronal network indiscriminately, but follow a detailed blueprint. This is true for specific connections between specific interneuron subtypes [54–56], resulting in highly defined disinhibitory circuits. Likewise, PNs prefer to connect to other PNs that share specific projection targets [107,108], a common progenitor [109,110], or a tendency to be activated by specific external stimuli [111–114]. Moreover, connections between different inhibitory and excitatory neuron types also might not necessarily result from sharing the same territory; instead, these can result from preferential innervation between specific interneuron and PN subclasses. This highly-specific synaptic connectivity diagram between distinct neuronal classes ultimately defines a specific subnetwork or even a cortical layer. The layer-specific expression of GABAergic plasticity described above could derive from the preferential axonal colonization of specific cortical lamina by distinct interneuron subclasses. Alternatively, it could result from the specific identity of postsynaptic PNs that belong to specific layers and bias the innervation from specific interneuron classes. Therefore, by receiving preferential perisomatic GABAergic innervation from specific interneuron types, could different cortical PN subtypes dictate distinct plasticity rules? Indeed, there is some precedent suggesting that this could be the case in other cortical areas. CA1 hippocampal PNs, while receiving equal amount of inhibition from CCK BCs, are differentially targeted by PV BCs according to their sublaminar location and their target preference [115]. On a similar theme, in the medial entorhinal cortex, CCK (CB1+) BCs selectively innervate L2 PNs that project to the contralateral entorhinal cortex and avoid neighboring cells which project to the ipsilateral dentate gyrus. This cell type-specific connectivity preference results in cell typespecific CB1-dependent plasticity of inhibitory synapses (DSI) [116]. In line with these results, important recent evidence has demonstrated that, in the neocortex also, specific types of PNs can be preferentially innervated by distinct interneurons: PV BCs in prefrontal cortical L5 preferentially innervate thick-tufted PNs projecting to subcortical structures, as compared to thin-tufted, callosally (i.e., contralaterally)-projecting PNs [117]. Importantly, a similar scheme has been recently reported in auditory cortex [118]. In some neocortical areas such as the somatosensory cortex, thick-tufted (also referred to as large-somata, bi-tufted) PNs tend to segregate in L5b, whereas thin-tufted (also referred to as small-somata, mono-tufted) PNs separate into L5a [119]. Remarkably, 5

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previous results indicated that large somatosensory cortex L5b PNs (presumably subcortically-projecting) receive very low level of CB1+ terminals and, accordingly, they do not display eCB-dependent plasticity, in contrast to small (presumably cortico-cortically-projecting) L5b PNs [86]. Interestingly, expression of specific molecular markers can identify different subtypes of deep (L5 and L6) neocortical PNs [19,120–123]. In particular, cortico-cortical and cortico-thalamic PNs express CCK and Purkinje cell protein 4 (PCP4) mRNA, respectively [19]. In general, corticocortical-projecting PNs represent the smaller and monotufted subtype, whereas the cortico-thalamic subclass likely belongs to the larger and bi-tufted corticofugal-projecting PNs [124]. These two PN classes also tend to segregate in distinct sublayers of L5 and L6 [19]. One can therefore hypothesize a connectivity diagram whereby CCK+, smaller, mono-tufted, and intracortically-projecting PNs are innervated by CCK+, CB1+ as well as PV BCs, in contrast to large, bi-tufted, CCK-negative PNs, which are avoided by CCK+, CB1+ BCs and are preferentially contacted by PV BCs (Figure 3) [86]. In particular, the strength of inhibition provided by PV BCs seems to be stronger in this latter PN

cell type [117], and thus represents the dominant source of inhibition onto large, corticofugal PNs. Overall, it is tempting to speculate that the polarity and the molecular mechanisms underlying specific forms of non-associative perisomatic GABAergic plasticity (e.g., depression or potentiation) in PNs will result from both the diversity of presynaptic interneurons – their tendency to depress or potentiate, as well as their sensitivity to specific modulators – and the diversity of postsynaptic PNs and their selective projection targets (Figure 3). If different PNs segregate in different cortical layers, this tendency to attract their specific inhibitory partners will ultimately confer the layer-specificity of GABAergic plasticity. Functional relevance Given the staggering diversity of synaptic properties originating from different neuronal types, identifying the function of plasticity of a specific synapse can be a daunting task and, for this reason, the functional role of plasticity at GABAergic inhibitory synapses remains poorly understood. Recently developed technologies that allow the identification and manipulation of specific subsets of neurons in the mouse brain provide an unprecedented opportunity to

Pia L1

CCK/CB1 L2/3 PV

CCK

CB1 Precursor

eCB

GABAR Ca2+

PV

L4

DSI / LTDi PV

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L5a

PV

PV

PV

L5b

sGC

L6

L-Arginine

NO

GABAR

WM

Ca2+ Other corcal areas

Subcorcal areas

LTPi

Figure 3. Postsynaptic PN identity dictates the innervation pattern from PV or CCK (CB1+) basket cells and thus the tendency to depress or potentiate their perisomatic inhibition. Large, thick-tufted layer L5 PNs (orange), projecting to subcortical brain areas, are preferentially controlled by PV BCs [117], and express cell-autonomous potentiation of perisomatic inhibition through retrograde NO signaling via soluble guanylyl cyclase (sGC) [91]. Conversely, smaller pyramidal neurons, both in L5 and L2/3, that mostly project to other cortical areas (yellow), are contacted by CCK BCs which express CB1s at their terminals and are subject to eCB-dependent short- [81–86] and long-term [11] forms of synaptic depression. The amount of innervation from PV and CCK BCs, and the ability to mobilize specific retrograde signaling molecules, will determine the polarity of perisomatic inhibitory plasticity. Abbreviations: BC, basket cell; CB1, cannabinoid receptor type 1; CCK, cholecystokinin; DSI, depolarizationinduced suppression of inhibition; eCB, endocannabinoid; PN, principal neuron; PV, parvalbumin; LTDi, long-term depression of inhibition; LTPi, long-term potentiation of inhibition. WM, white matter.

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Review probe the role of GABAergic interneurons within cortical circuits [125], and therefore to investigate specific forms of plasticity of distinct inhibitory circuits. Inhibitory plasticity has been proposed to compensate for changes of synaptic excitation to maintain a constant excitation-to-inhibition ratio (E/I). This can be achieved, for example, by concomitant weakening of feed-forward inhibition and excitation [126,127], or by persistent enhancement of inhibitory neuron excitability, in response to long-term potentiation of glutamatergic synapses [128]. Accordingly, it has been shown that perisomatic inhibition from PV BCs correlates with the amount of excitation that single L2/3 PNs receive from L4. Artificially enhancing or decreasing the excitability of PNs can lead to a fine titration of PV cell mediated inhibition [129]. Being correlated in strength with excitation, fast GABAergic inhibition constantly balances excitation and governs both spontaneous and sensory-evoked cortical activity [130,131]. Nevertheless, despite the current idea that excitation and inhibition must be maintained in proportion to one another, perturbations of the E/I ratio were shown to play a key role in sensory learning and receptive field reorganization [132,133]. Moreover, the E/I ratio is remarkably different across cortical layers, resulting in layer-specific suppression or augmentation of pyramidal neuron output in response to sustained input activation [134]. This suggests that important physiological brain functions require loosening of this highly-restrictive ‘cage’ to allow specific circuit computations underlying fundamental functions of distinct cortical networks. In principle, short- and long-term forms of synaptic plasticity of either inhibitory or excitatory neurotransmission could be responsible for dynamically altering the E/I ratio of specific cortical networks. Our recent work showed that persistent enhancement of a specific GABAergic circuit, without altering excitation, resulted in a change of perisomatic E/I lock, tuned synaptic integration, decreased spike probability, and increased the precision of firing of large L5 PNs [91]. By contrast, the tendency to induce depression of perisomatic inhibition in L2/3 PNs [11] will likely alter the E/I ratio in the opposite direction, conferring a differential sensitivity of incoming excitation in the two different cortical layers. Strengthening or diminishing perisomatic GABAergic inhibition will also exert a divisive or subtractive effect on the input–output computational properties of PNs [135]. This modulation of single PN computation will likely affect sensory feature selectivity, which was shown to be strongly modulated by perisomatic inhibition [136–138]. Notably, the connectivity preference between specific PNs and perisomatic-targeting interneurons [86,117] will differentially influence spike probability and timing of diverse PNs, thereby differently controlling cortical network oscillations. In particular, perisomatic inhibition drives oscillations in the b–g frequency range (20–80 Hz; Table 1) [38,39,43,45,139,140], which have been proposed to underlie several cognitive functions, including attention and sensory perception [43,141]. Enhancing perisomatic inhibition might therefore sharpen the temporal coordination between single PNs and global network activity, whereas depressing perisomatic inhibition could decouple

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single PNs from an active cell assembly [142]. In other words, bidirectional perisomatic plasticity can induce single neurons to ‘sing in or out of key’ during synchronous network activity. Overall, the tendency to depress or potentiate specific GABAergic synapses by distinct subtypes of PNs could homogenize and coordinate the specific temporal association of subgroups of PNs sharing common targets or input properties [142]. Interestingly, in addition to the role of specific interneuron types in microcircuit computation, several new studies indicated the specific role(s) of distinct interneuron classes in behaviorally-relevant activities, such as goal-directed behavior [143], auditory discrimination [55], experiencedependent plasticity [144,145], sensory coding [136], and sensory integration during locomotion [146] (Table 1). Importantly, whereas the role of PV BCs has been extensively studied, the other major BC subtype, the CCK BC, has received less attention, although their synapses, especially those expressing CB1 receptors, have been shown to be highly prone to synaptic depression [39,47]. Indeed, even if CB1+ terminals favor some PN subtypes, such as those in L2/3, L5a, and L6, these PNs receive also a substantial innervation by PV BCs [86]. Therefore, it is possible that a single PN can induce bidirectional plasticity (e.g., LTDi at CB1+ and LTPi at PV+ terminals) simultaneously. In this case, it will be interesting to determine what dictates the general tendency to depress or potentiate the overall perisomatic inhibition in a given PN. This could derive from specific activity patterns, ability to mobilize specific retrograde signaling molecules, the presence or absence of tonic CB1 activation [147], and the overall ratio between CB1+ and PV+ boutons. Therefore, differential plasticity of synapses originating from specific interneurons might induce persistent changes of distinct computational aspects of cortical circuits. For example, dendritic inhibition is crucial for modulating synaptic integration and dendritic supra-linearity [8,50,135–148] (Table 1). Moreover, dendritic inhibition has been shown to underlie lateral inhibition during visual [149] and olfactory [150] sensory tasks (Table 1). However little is known if dendrite-targeting GABAergic synapses are plastic and, if they are, what would the impact be on network and/or cognitive operations. Concluding remarks and future directions In this review we have attempted to find a rule underlying the layer-segregation of cell-autonomous non-associative plasticity of perisomatic GABAergic synapses originating from different populations of inhibitory neurons impinging onto different subtypes of neocortical PNs. We have highlighted layer- and cell type-specificity of preferential GABAergic innervation of PNs by distinct interneuron classes. This specialized connectivity scheme can result in finely tuned forms of GABAergic plasticity, likely having a strong impact on the computational properties of specific cortical circuits. One possible emerging pattern is that PNs serving as cortical input or output elements (e.g., L4 spiny stellate neurons, and large L5b pyramidal neurons projecting to ‘effector’ brain structures, respectively) are minimally contacted by CB1+ BCs, whereas PNs exerting 7

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Review Box 1. Outstanding questions Given the staggering diversity of cortical interneurons, and the specific properties and sensitivity to neuromodulators of distinct synapses, many questions arise, including:  Is dendritic inhibition also plastic?  Do neurons providing the ‘blanket of inhibition’ express cell typespecific forms of plasticity?  Are specific connections between interneurons also plastic? Some evidence in the hippocampus indicates that this is the case [154– 156], but do interneuron–interneuron synapses follow similar rules as synapses formed onto PNs?  Is the pattern of connectivity between specific inhibitory and excitatory neuron types similar across different cortical areas? Therefore, could plasticity and modulation of inhibition be different in specific cortical areas?  Pre- and postsynaptic forms of GABAergic plasticity likely coexist, but are they differently developmentally regulated? If so, what are the plasticity rules of different sensory cortices, which have distinct critical periods?  Does sensory deprivation and/or enrichment alter the propensity and/or the mechanisms underlying plasticity of GABAergic synapses? Does this occur also in different cortical layers (besides L4 [157]) and areas, and are inhibitory interneurons other than PV BCs also involved?  Astrocytes are emerging as important players for many forms of synaptic plasticity [158–160]. It will be therefore interesting to establish whether and how glial cells can modulate specific forms of GABAergic transmission relying on diffusion of retrograde messengers.  Alterations of cortical inhibition have been implicated in several neuropsychiatric (e.g., schizophrenia, autism, mood disorders) and neurological (e.g., epilepsy and Rett syndrome) diseases: could dysfunctional plasticity of specific inhibitory circuits be among the pathophysiological mechanisms of these devastating disorders?

a more-associative function (e.g., L2/3 or small L5a pyramidal neurons, projecting mainly intracortically) require perisomatic innervation from CB1+ inhibitory terminals (Figure 3). This connectivity logic would confer upon functionally-distinct PN populations different tendencies to change the strength of their perisomatic inhibition. Several open questions remain unanswered. Indeed, what forms of plasticity are present at dendrite-targeting GABAergic synapses? So far, we could demonstrate that SST-cells are not sensitive to activity-dependent cell-autonomous NO retrograde signaling [91], but other cellular mechanisms or specific protocols could potentiate and/or depress the inhibitory control that they exert on PN dendrites. Importantly, in contrast to the emerging detailed preferential perisomatic PN targeting by PV+ or CB1+ BCs, other interneuron subclasses with different functions within cortical circuits have been proposed to provide a nonspecific innervation pattern, also defined as a ‘blanket of inhibition’ [29,31]. These include interneurons targeting dendrites of PNs, such as SST-expressing Martinotti cells, and NGFCs [51–53,151], as well as axo-axonic chandelier cells, which provide dense and seemingly nonspecific innervation to PN axonal initial segments [152,153]. Future studies will define whether also these interneuron types might display preferential innervation and show differential synaptic strength onto specific postsynaptic PNs. Overall, it will be important to understand the role that GABAergic plasticity in nonselectively-targeting interneurons plays in cortical circuit computations. 8

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Addressing these and other issues (Box 1) will provide a better and more refined understanding of how cortical circuits can be bidirectionally modulated during normal cortical operations, and will identify new cellular and molecular players responsible for the development of neurological and psychiatric diseases. Acknowledgments We thank Vikaas Sohal, Giovanni Marsicano, Charlotte Deleuze, and Andrea Barberis for critically reading this manuscript. Our laboratory is supported by the Giovanni Armenise-Harvard Foundation: Career Development Award; European Research Council (ERC) under the European Commission 7th Framework Programmme (FP7/2007-2013)/ ERC grant 200808); ‘Investissements d’Avenir’ ANR-10-IAIHU-06; Agence Nationale de la Recherche (ANR-13-BSV4-0015-01); and a grant from the ICM (Paris).

References 1 Douglas, R. et al. (2004) Neocortex. In The Synaptic Organization of the Brain (5th edn) (Shepherd, G., ed.), pp. 499–558, Oxford University Press 2 Oberlaender, M. et al. (2012) Cell type-specific three-dimensional structure of thalamocortical circuits in a column of rat vibrissal cortex. Cereb. Cortex 22, 2375–2391 3 Jones, E.G. (2001) The thalamic matrix and thalamocortical synchrony. Trends Neurosci. 24, 595–601 4 Clasca, F. et al. (2012) Unveiling the diversity of thalamocortical neuron subtypes. Eur. J. Neurosci. 35, 1524–1532 5 Harris, K.D. and Shepherd, G.M. (2015) The neocortical circuit: themes and variations. Nat. Neurosci. 18, 170–181 6 Larkum, M. (2013) A cellular mechanism for cortical associations: an organizing principle for the cerebral cortex. Trends Neurosci. 36, 141– 151 7 Briggs, F. and Usrey, W.M. (2008) Emerging views of corticothalamic function. Curr. Opin. Neurobiol. 18, 403–407 8 Murayama, M. et al. (2009) Dendritic encoding of sensory stimuli controlled by deep cortical interneurons. Nature 457, 1137–1141 9 Bortone, D.S. et al. (2014) Translaminar inhibitory cells recruited by layer 6 corticothalamic neurons suppress visual cortex. Neuron 82, 474–485 10 Olsen, S.R. et al. (2012) Gain control by layer six in cortical circuits of vision. Nature 483, 47–52 11 Marinelli, S. et al. (2009) Self-modulation of neocortical pyramidal neurons by endocannabinoids. Nat. Neurosci. 12, 1488–1490 12 Lein, E.S. et al. (2007) Genome-wide atlas of gene expression in the adult mouse brain. Nature 445, 168–176 13 Spruston, N. (2008) Pyramidal neurons: dendritic structure and synaptic integration. Nat. Rev. Neurosci. 9, 206–221 14 Nelson, S.B. et al. (2006) The problem of neuronal cell types: a physiological genomics approach. Trends Neurosci. 29, 339–345 15 Nelson, S.B. et al. (2006) Probing the transcriptome of neuronal cell types. Curr. Opin. Neurobiol. 16, 571–576 16 Gong, S. et al. (2003) A gene expression atlas of the central nervous system based on bacterial artificial chromosomes. Nature 425, 917–925 17 Thomson, A.M. and Lamy, C. (2007) Functional maps of neocortical local circuitry. Front. Neurosci. 1, 19–42 18 Belgard, T.G. et al. (2011) A transcriptomic atlas of mouse neocortical layers. Neuron 71, 605–616 19 Watakabe, A. et al. (2012) Area-specific substratification of deep layer neurons in the rat cortex. J. Comp. Neurol. 520, 3553–3573 20 McCormick, D.A. et al. (1985) Comparative electrophysiology of pyramidal and sparsely spiny stellate neurons of the neocortex. J. Neurophysiol. 54, 782–806 21 Connors, B.W. and Gutnick, M.J. (1990) Intrinsic firing patterns of diverse neocortical neurons. Trends Neurosci. 13, 99–104 22 Lund, J.S. et al. (1975) The origin of efferent pathways from the primary visual cortex, area 17, of the macaque monkey as shown by retrograde transport of horseradish peroxidase. J. Comp Neurol. 164, 287–303

TINS-1169; No. of Pages 11

Review 23 Killackey, H.P. et al. (1989) Laminar and areal differences in the origin of the subcortical projection neurons of the rat somatosensory cortex. J. Comp. Neurol. 282, 428–445 24 Zhang, Z.W. and Deschenes, M. (1997) Intracortical axonal projections of lamina VI cells of the primary somatosensory cortex in the rat: a single-cell labeling study. J. Neurosci. 17, 6365–6379 25 Prieto, J.J. and Winer, J.A. (1999) Layer VI in cat primary auditory cortex: Golgi study and sublaminar origins of projection neurons. J. Comp. Neurol. 404, 332–358 26 Killackey, H.P. and Sherman, S.M. (2003) Corticothalamic projections from the rat primary somatosensory cortex. J. Neurosci. 23, 7381–7384 27 Anderson, C.T. et al. (2010) Sublayer-specific microcircuits of corticospinal and corticostriatal neurons in motor cortex. Nat. Neurosci. 13, 739–744 28 Mao, T. et al. (2011) Long-range neuronal circuits underlying the interaction between sensory and motor cortex. Neuron 72, 111–123 29 Fino, E. et al. (2013) The logic of inhibitory connectivity in the neocortex. Neuroscientist 19, 228–237 30 Fino, E. and Yuste, R. (2011) Dense inhibitory connectivity in neocortex. Neuron 69, 1188–1203 31 Karnani, M.M. et al. (2014) A blanket of inhibition: functional inferences from dense inhibitory connectivity. Curr. Opin. Neurobiol. 26, 96–102 32 Packer, A.M. et al. (2013) Axo-dendritic overlap and laminar projection can explain interneuron connectivity to pyramidal cells. Cereb. Cortex 23, 2790–2802 33 DeFelipe, J. et al. (2013) New insights into the classification and nomenclature of cortical GABAergic interneurons. Nat. Rev. Neurosci. 14, 202–216 34 Ascoli, G.A. et al. (2008) Petilla terminology: nomenclature of features of GABAergic interneurons of the cerebral cortex. Nat. Rev. Neurosci. 9, 557–568 35 Markram, H. et al. (2004) Interneurons of the neocortical inhibitory system. Nat. Rev. Neurosci 5, 793–807 36 Kawaguchi, Y. and Kubota, Y. (1998) Neurochemical features and synaptic connections of large physiologically-identified GABAergic cells in the rat frontal cortex. Neuroscience 85, 677–701 37 Kawaguchi, Y. and Kubota, Y. (1997) GABAergic cell subtypes and their synaptic connections in rat frontal cortex. Cereb. Cortex 7, 476–486 38 Cardin, J.A. et al. (2009) Driving fast-spiking cells induces gamma rhythm and controls sensory responses. Nature 459, 663–667 39 Freund, T.F. and Katona, I. (2007) Perisomatic inhibition. Neuron 56, 33–42 40 Freund, T.F. (2003) Interneuron diversity series: rhythm and mood in perisomatic inhibition. Trends Neurosci. 26, 489–495 41 Wang, Y. et al. (2002) Anatomical, physiological, molecular and circuit properties of nest basket cells in the developing somatosensory cortex. Cereb. Cortex 12, 395–410 42 Bartos, M. et al. (2007) Synaptic mechanisms of synchronized gamma oscillations in inhibitory interneuron networks. Nat. Rev. Neurosci. 8, 45–56 43 Buzsaki, G. and Wang, X.J. (2012) Mechanisms of gamma oscillations. Annu. Rev. Neurosci. 35, 203–225 44 Deleuze, C. et al. (2014) Autaptic self-inhibition of cortical GABAergic neurons: Synaptic narcissism or useful introspection? Curr. Opin. Neurobiol. 26C, 64–71 45 Sohal, V.S. et al. (2009) Parvalbumin neurons and gamma rhythms enhance cortical circuit performance. Nature 459, 698–702 46 Hefft, S. and Jonas, P. (2005) Asynchronous GABA release generates long-lasting inhibition at a hippocampal interneuron-principal neuron synapse. Nat. Neurosci. 8, 1319–1328 47 Armstrong, C. and Soltesz, I. (2012) Basket cell dichotomy in microcircuit function. J. Physiol. 590, 683–694 48 Daw, M.I. et al. (2009) Asynchronous transmitter release from cholecystokinin-containing inhibitory interneurons is widespread and target-cell independent. J. Neurosci. 29, 11112–11122 49 Wang, Y. et al. (2004) Anatomical, physiological and molecular properties of Martinotti cells in the somatosensory cortex of the juvenile rat. J. Physiol. 561, 65–90

Trends in Neurosciences xxx xxxx, Vol. xxx, No. x

50 Palmer, L. et al. (2012) Inhibitory regulation of dendritic activity in vivo. Front. Neural Circuits 6, 26 51 Olah, S. et al. (2007) Output of neurogliaform cells to various neuron types in the human and rat cerebral cortex. Front. Neural Circuits 1, 4 52 Szabadics, J. et al. (2007) Different transmitter transients underlie presynaptic cell type specificity of GABAA, slow and GABAA, fast. Proc. Natl. Acad. Sci. U.S.A. 104, 14831–14836 53 Tamas, G. et al. (2003) Identified sources and targets of slow inhibition in the neocortex. Science 299, 1902–1905 54 Pfeffer, C.K. et al. (2013) Inhibition of inhibition in visual cortex: the logic of connections between molecularly distinct interneurons. Nat. Neurosci. 16, 1068–1076 55 Pi, H.J. et al. (2013) Cortical interneurons that specialize in disinhibitory control. Nature 503, 521–524 56 Kuhlman, S.J. et al. (2013) A disinhibitory microcircuit initiates critical-period plasticity in the visual cortex. Nature 501, 543–546 57 Isaacson, J.S. and Scanziani, M. (2011) How inhibition shapes cortical activity. Neuron 72, 231–243 58 Malenka, R.C. and Bear, M.F. (2004) LTP and LTD: an embarrassment of riches. Neuron 44, 5–21 59 Malenka, R.C. (2003) The long-term potential of LTP. Nat. Rev. Neurosci. 4, 923–926 60 Castillo, P.E. et al. (2011) Long-term plasticity at inhibitory synapses. Curr. Opin. Neurobiol. 21, 328–338 61 Mendez, P. and Bacci, A. (2011) Assortment of GABAergic plasticity in the cortical interneuron melting pot. Neural Plast. 2011, 976856 62 Holmgren, C.D. and Zilberter, Y. (2001) Coincident spiking activity induces long-term changes in inhibition of neocortical pyramidal cells. J. Neurosci. 21, 8270–8277 63 Maffei, A. et al. (2006) Potentiation of cortical inhibition by visual deprivation. Nature 443, 81–84 64 Lefort, S. et al. (2013) Long-term inhibitory plasticity in visual cortical layer 4 switches sign at the opening of the critical period. Proc. Natl. Acad. Sci. U.S.A. 110, E4540–E4547 65 Diana, M.A. and Marty, A. (2004) Endocannabinoid-mediated shortterm synaptic plasticity: depolarization-induced suppression of inhibition (DSI) and depolarization-induced suppression of excitation (DSE). Br. J. Pharmacol. 142, 9–19 66 Chevaleyre, V. et al. (2006) Endocannabinoid-mediated synaptic plasticity in the CNS. Annu. Rev. Neurosci. 29, 37–76 67 Freund, T.F. et al. (2003) Role of endogenous cannabinoids in synaptic signaling. Physiol. Rev. 83, 1017–1066 68 Piomelli, D. (2003) The molecular logic of endocannabinoid signalling. Nat. Rev. Neurosci. 4, 873–884 69 Castillo, P.E. et al. (2012) Endocannabinoid signaling and synaptic function. Neuron 76, 70–81 70 Wilson, R.I. et al. (2001) Presynaptic specificity of endocannabinoid signaling in the hippocampus. Neuron 31, 453–462 71 Wilson, R.I. and Nicoll, R.A. (2001) Endogenous cannabinoids mediate retrograde signalling at hippocampal synapses. Nature 410, 588–592 72 Ohno-Shosaku, T. et al. (2001) Endogenous cannabinoids mediate retrograde signals from depolarized postsynaptic neurons to presynaptic terminals. Neuron 29, 729–738 73 Kreitzer, A.C. and Regehr, W.G. (2002) Retrograde signaling by endocannabinoids. Curr. Opin. Neurobiol. 12, 324–330 74 Kreitzer, A.C. and Regehr, W.G. (2001) Retrograde inhibition of presynaptic calcium influx by endogenous cannabinoids at excitatory synapses onto Purkinje cells. Neuron 29, 717–727 75 Alger, B.E. (2002) Retrograde signaling in the regulation of synaptic transmission: focus on endocannabinoids. Prog. Neurobiol. 68, 247–286 76 Marsicano, G. and Lutz, B. (1999) Expression of the cannabinoid receptor CB1 in distinct neuronal subpopulations in the adult mouse forebrain. Eur. J. Neurosci. 11, 4213–4225 77 Hill, E.L. et al. (2007) Functional CB1 receptors are broadly expressed in neocortical GABAergic and glutamatergic neurons. J. Neurophysiol. 97, 2580–2589 78 Fortin, D.A. et al. (2004) Brief trains of action potentials enhance pyramidal neuron excitability via endocannabinoid-mediated suppression of inhibition. J. Neurophysiol. 92, 2105–2112 79 Trettel, J. et al. (2004) Endocannabinoid signaling selectively targets perisomatic inhibitory inputs to pyramidal neurons in juvenile mouse neocortex. J. Physiol. 556, 95–107 9

TINS-1169; No. of Pages 11

Review 80 Trettel, J. and Levine, E.S. (2003) Endocannabinoids mediate rapid retrograde signaling at interneuron right-arrow pyramidal neuron synapses of the neocortex. J. Neurophysiol. 89, 2334–2338 81 Trettel, J. and Levine, E.S. (2002) Cannabinoids depress inhibitory synaptic inputs received by layer 2/3 pyramidal neurons of the neocortex. J. Neurophysiol. 88, 534–539 82 Heifets, B.D. and Castillo, P.E. (2009) Endocannabinoid signaling and long-term synaptic plasticity. Annu. Rev. Physiol 71, 283–306 83 Chevaleyre, V. and Castillo, P.E. (2003) Heterosynaptic LTD of hippocampal GABAergic synapses: a novel role of endocannabinoids in regulating excitability. Neuron 38, 461–472 84 Younts, T.J. et al. (2013) CA1 pyramidal cell theta-burst firing triggers endocannabinoid-mediated long-term depression at both somatic and dendritic inhibitory synapses. J. Neurosci. 33, 13743–13757 85 Younts, T.J. and Castillo, P.E. (2014) Endogenous cannabinoid signaling at inhibitory interneurons. Curr. Opin. Neurobiol. 26, 42–50 86 Bodor, A.L. et al. (2005) Endocannabinoid signaling in rat somatosensory cortex: laminar differences and involvement of specific interneuron types. J. Neurosci. 25, 6845–6856 87 Fortin, D.A. and Levine, E.S. (2007) Differential effects of endocannabinoids on glutamatergic and GABAergic inputs to layer 5 pyramidal neurons. Cereb. Cortex 17, 163–174 88 Hsieh, L.S. and Levine, E.S. (2012) Cannabinoid modulation of backpropagating action potential-induced calcium transients in layer 2/3 pyramidal neurons. Cereb. Cortex 23, 1731–1741 89 Egertova, M. et al. (2003) Comparative analysis of fatty acid amide hydrolase and CB1 cannabinoid receptor expression in the mouse brain: evidence of a widespread role for fatty acid amide hydrolase in regulation of endocannabinoid signaling. Neuroscience 119, 481–496 90 Yoneda, T. et al. (2013) Developmental and visual input-dependent regulation of the CB1 cannabinoid receptor in the mouse visual cortex. PLoS ONE 8, e53082 91 Lourenco, J. et al. (2014) Non-associative potentiation of perisomatic Inhibition alters the temporal coding of neocortical layer 5 pyramidal neurons. PLoS Biol. 12, e1001903 92 Petrini, E.M. et al. (2014) Synaptic recruitment of gephyrin regulates surface GABAA receptor dynamics for the expression of inhibitory LTP. Nat. Commun. 5, 3921 93 Kurotani, T. et al. (2008) State-dependent bidirectional modification of somatic inhibition in neocortical pyramidal cells. Neuron 57, 905–916 94 Kurotani, T. et al. (2003) Postsynaptic firing produces long-term depression at inhibitory synapses of rat visual cortex. Neurosci. Lett. 337, 1–4 95 Komatsu, Y. and Iwakiri, M. (1993) Long-term modification of inhibitory synaptic transmission in developing visual cortex. Neuroreport 4, 907–910 96 Jiang, B. et al. (2010) The maturation of GABAergic transmission in visual cortex requires endocannabinoid-mediated LTD of inhibitory inputs during a critical period. Neuron 66, 248–259 97 Moreau, A.W. et al. (2013) Serotonergic modulation of LTP at excitatory and inhibitory synapses in the developing rat visual cortex. Neuroscience 238, 148–158 98 Inagaki, T. et al. (2008) Brain-derived neurotrophic factor-mediated retrograde signaling required for the induction of long-term potentiation at inhibitory synapses of visual cortical pyramidal neurons. Neurosci. Res. 61, 192–200 99 Xu, H. et al. (2010) Normal hearing is required for the emergence of long-lasting inhibitory potentiation in cortex. J. Neurosci. 30, 331–341 100 Chiu, C.Q. et al. (2010) Dopaminergic modulation of endocannabinoidmediated plasticity at GABAergic synapses in the prefrontal cortex. J. Neurosci. 30, 7236–7248 101 Deshmukh, S. et al. (2007) Postnatal development of cannabinoid receptor type 1 expression in rodent somatosensory cortex. Neuroscience 145, 279–287 102 Marsicano, G. et al. (2002) The endogenous cannabinoid system controls extinction of aversive memories. Nature 418, 530–534 103 Garkun, Y. and Maffei, A. (2014) Cannabinoid-dependent potentiation of inhibition at eye opening in mouse V1. Front. Cell. Neurosci. 8, 46 104 Maffei, A. et al. (2010) Critical period for inhibitory plasticity in rodent binocular V1. J. Neurosci. 30, 3304–3309 10

Trends in Neurosciences xxx xxxx, Vol. xxx, No. x

105 Maffei, A. and Turrigiano, G. (2008) The age of plasticity: developmental regulation of synaptic plasticity in neocortical microcircuits. Prog. Brain Res. 169, 211–223 106 Maffei, A. et al. (2004) Selective reconfiguration of layer 4 visual cortical circuitry by visual deprivation. Nat. Neurosci. 7, 1353–1359 107 Brown, S.P. and Hestrin, S. (2009) Cell-type identity: a key to unlocking the function of neocortical circuits. Curr. Opin. Neurobiol. 19, 415–421 108 Brown, S.P. and Hestrin, S. (2009) Intracortical circuits of pyramidal neurons reflect their long-range axonal targets. Nature 457, 1133–1136 109 Yu, Y.C. et al. (2012) Preferential electrical coupling regulates neocortical lineage-dependent microcircuit assembly. Nature 486, 113–117 110 Yu, Y.C. et al. (2009) Specific synapses develop preferentially among sister excitatory neurons in the neocortex. Nature 458, 501–504 111 Cossell, L. et al. (2015) Functional organization of excitatory synaptic strength in primary visual cortex. Nature 518, 399–403 112 Harris, K.D. and Mrsic-Flogel, T.D. (2013) Cortical connectivity and sensory coding. Nature 503, 51–58 113 Hofer, S.B. et al. (2011) Differential connectivity and response dynamics of excitatory and inhibitory neurons in visual cortex. Nat. Neurosci. 14, 1045–1052 114 Ko, H. et al. (2011) Functional specificity of local synaptic connections in neocortical networks. Nature 473, 87–91 115 Lee, S.H. et al. (2014) Parvalbumin-positive basket cells differentiate among hippocampal pyramidal cells. Neuron 82, 1129–1144 116 Varga, C. et al. (2010) Target-selective GABAergic control of entorhinal cortex output. Nat. Neurosci. 13, 822–824 117 Lee, A.T. et al. (2014) Pyramidal neurons in prefrontal cortex receive subtype-specific forms of excitation and inhibition. Neuron 81, 61–68 118 Rock, C. and Apicella, A.J. (2015) Callosal projections drive neuronal-specific responses in the mouse auditory cortex. J. Neurosci. 35, 6703–6713 119 Hattox, A.M. and Nelson, S.B. (2007) Layer V neurons in mouse cortex projecting to different targets have distinct physiological properties. J. Neurophysiol. 98, 3330–3340 120 Yoneshima, H. et al. (2006) Er81 is expressed in a subpopulation of layer 5 neurons in rodent and primate neocortices. Neuroscience 137, 401–412 121 Molnar, Z. and Cheung, A.F. (2006) Towards the classification of subpopulations of layer V pyramidal projection neurons. Neurosci. Res. 55, 105–115 122 Groh, A. et al. (2010) Cell-type specific properties of pyramidal neurons in neocortex underlying a layout that is modifiable depending on the cortical area. Cereb. Cortex 20, 826–836 123 Molyneaux, B.J. et al. (2009) Novel subtype-specific genes identify distinct subpopulations of callosal projection neurons. J. Neurosci. 29, 12343–12354 124 Larsen, D.D. et al. (2007) Retrograde tracing with recombinant rabies virus reveals correlations between projection targets and dendritic architecture in layer 5 of mouse barrel cortex. Front. Neural Circuits. 1, 5 125 Taniguchi, H. et al. (2011) A resource of Cre driver lines for genetic targeting of GABAergic neurons in cerebral cortex. Neuron 71, 995–1013 126 Nataraj, K. et al. (2010) Visual deprivation suppresses L5 pyramidal neuron excitability by preventing the induction of intrinsic plasticity. Neuron 68, 750–762 127 House, D.R. et al. (2011) Parallel regulation of feedforward inhibition and excitation during whisker map plasticity. Neuron 72, 819–831 128 Campanac, E. et al. (2013) Enhanced intrinsic excitability in basket cells maintains excitatory-inhibitory balance in hippocampal circuits. Neuron 77, 712–722 129 Xue, M. et al. (2014) Equalizing excitation–inhibition ratios across visual cortical neurons. Nature 511, 596–600 130 Okun, M. and Lampl, I. (2008) Instantaneous correlation of excitation and inhibition during ongoing and sensory-evoked activities. Nat. Neurosci. 11, 535–537 131 Atallah, B.V. and Scanziani, M. (2009) Instantaneous modulation of gamma oscillation frequency by balancing excitation with inhibition. Neuron 62, 566–577

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Review 132 Gambino, F. and Holtmaat, A. (2012) Spike-timing-dependent potentiation of sensory surround in the somatosensory cortex is facilitated by deprivation-mediated disinhibition. Neuron 75, 490–502 133 Froemke, R.C. et al. (2007) A synaptic memory trace for cortical receptive field plasticity. Nature 450, 425–429 134 Adesnik, H. and Scanziani, M. (2010) Lateral competition for cortical space by layer-specific horizontal circuits. Nature 464, 1155–1160 135 Silver, R.A. (2010) Neuronal arithmetic. Nat. Rev. Neurosci. 11, 474–489 136 Atallah, B.V. et al. (2012) Parvalbumin-expressing interneurons linearly transform cortical responses to visual stimuli. Neuron 73, 159–170 137 Lee, S.H. et al. (2012) Activation of specific interneurons improves V1 feature selectivity and visual perception. Nature 488, 379–383 138 Wilson, N.R. et al. (2012) Division and subtraction by distinct cortical inhibitory networks in vivo. Nature 488, 343–348 139 Buzsaki, G. and Draguhn, A. (2004) Neuronal oscillations in cortical networks. Science 304, 1926–1929 140 Wang, X.J. (2010) Neurophysiological and computational principles of cortical rhythms in cognition. Physiol. Rev. 90, 1195–1268 141 Buzsaki, G. and Silva, F.L. (2012) High frequency oscillations in the intact brain. Prog. Neurobiol. 98, 241–249 142 Buzsaki, G. (2010) Neural syntax: cell assemblies, synapsembles, and readers. Neuron 68, 362–385 143 Pinto, L. and Dan, Y. (2015) Cell-type-specific activity in prefrontal cortex during goal-directed behavior. Neuron 87, 437–450 144 Micheva, K.D. and Beaulieu, C. (1995) An anatomical substrate for experience-dependent plasticity of the rat barrel field cortex. Proc. Natl. Acad. Sci. U.S.A. 92, 11834–11838 145 Jiao, Y. et al. (2006) Major effects of sensory experiences on the neocortical inhibitory circuits. J. Neurosci. 26, 8691–8701 146 Lee, S. et al. (2013) A disinhibitory circuit mediates motor integration in the somatosensory cortex. Nat. Neurosci. 16, 1662–1670 147 Losonczy, A. et al. (2004) Persistently active cannabinoid receptors mute a subpopulation of hippocampal interneurons. Proc. Natl. Acad. Sci. U.S.A. 101, 1362–1367

Trends in Neurosciences xxx xxxx, Vol. xxx, No. x

148 Lovett-Barron, M. et al. (2012) Regulation of neuronal input transformations by tunable dendritic inhibition. Nat. Neurosci. 15, 423 149 Adesnik, H. et al. (2012) A neural circuit for spatial summation in visual cortex. Nature 490, 226–231 150 Sturgill, J.F. and Isaacson, J.S. (2015) Somatostatin cells regulate sensory response fidelity via subtractive inhibition in olfactory cortex. Nat. Neurosci. 18, 531–535 151 Karayannis, T. et al. (2010) Slow GABA transient and receptor desensitization shape synaptic responses evoked by hippocampal neurogliaform cells. J. Neurosci. 30, 9898–9909 152 Inan, M. et al. (2013) Dense and overlapping innervation of pyramidal neurons by chandelier cells. J. Neurosci. 33, 1907–1914 153 Blazquez-Llorca, L. et al. (2014) Spatial distribution of neurons innervated by chandelier cells. Brain Struct. Funct. Published online July 24, 2014. http://dx.doi.org/10.1007/s00429-014-0828-3 154 Iball, J. and Ali, A.B. (2011) Endocannabinoid release modulates electrical coupling between CCK cells connected via chemical and electrical synapses in CA1. Front Neural Circuits. 5, 17 155 Ali, A.B. (2007) Presynaptic Inhibition of GABAA receptormediated unitary IPSPs by cannabinoid receptors at synapses between CCK-positive interneurons in rat hippocampus. J. Neurophysiol. 98, 861–869 156 Ali, A.B. and Todorova, M. (2010) Asynchronous release of GABA via tonic cannabinoid receptor activation at identified interneuron synapses in rat CA1. Eur. J. Neurosci. 31, 1196–1207 157 Maffei, A. (2011) The many forms and functions of long term plasticity at GABAergic synapses. Neural Plast. 2011, 254724 158 Kang, J. et al. (1998) Astrocyte-mediated potentiation of inhibitory synaptic transmission. Nat. Neurosci. 1, 683–692 159 Navarrete, M. and Araque, A. (2008) Endocannabinoids mediate neuron-astrocyte communication. Neuron 57, 883–893 160 Min, R. and Nevian, T. (2012) Astrocyte signaling controls spike timing-dependent depression at neocortical synapses. Nat. Neurosci. 15, 746–753

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