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Inhibitory microcircuit modules in hippocampal learning
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ScienceDirect Inhibitory microcircuit modules in hippocampal learning Pico Caroni It has recently become possible to investigate connectivities and roles of identified hippocampal GABAergic interneurons (INs) in behaving rodents. INs targeting distinct pyramidal neuron subcompartments are recruited dynamically at defined phases of behavior and learning. They include Parvalbumin Axo-axonic and perisomatic Basket cells, and Somatostatin radiatum-oriens and oriens-lacunosum moleculare cells. Each IN is in turn either activated or inhibited upon specific behavioral and network state requirements through specific inputs and neuromodulators. Subpopulations of these principal neurons and INs interconnect selectively, suggesting selective processing and routing of alternate information streams. First canonical functional modules have emerged, which will have to be further defined and linked to identified afferents and efferents towards a circuit understanding of how hippocampal networks support behavior. Address Friedrich Miescher Institut, Maulbeerstrasse 66, CH-4058 Basel, Switzerland Corresponding author: Caroni, Pico ([email protected])
Current Opinion in Neurobiology 2015, 35:66–73 This review comes from a themed issue on Circuit plasticity and memory Edited by Tom Mrsic-Flogel and Alessandro Treves
system-specific properties. The latter include GABAergic principal neurons such as cerebellar cortex Purkinje cells or striatal medium spiny neurons, as well as long-distance GABAergic neurons thought to have key roles in coordinating network activity through multiple brain regions. Investigations of local inhibitory neuron functions have recently undergone what can safely be considered a quantum leap due to key advances in technologies and tools [3–7]. Head-fixed preparations have become available that can combine behavioral paradigms with twophoton microscopy-supported monitoring and manipulation of identified neurons in awake mice. This key advance overcame limitations of anaesthetized preparations and allowed investigation of neuronal functions during behavior and in learning. Genetically modified mice have provided tools for specific genetic control of identified interneuron subpopulations during development and in the adult. This advance opened the door to functional investigations and manipulation of interneuron subpopulations in slices and in behaving mice. Finally, opto-genetic and pharmacogenetic tools in combination with viral tools for intersectional targeting of neurons based on their identities and/or connectivities have provided powerful means for causal investigations of neuronal and circuit functions in situ. Together, and in combination with electrophysiology and neuroanatomical techniques, these developments have led to a refocusing of the major questions in circuit neuroscience.
http://dx.doi.org/10.1016/j.conb.2015.06.010 0959-4388/# 2015 Elsevier Ltd. All rights reserved.
Introduction Local microcircuits involving inhibitory GABAergic interneurons (INs) organize the activities of excitatory principal neurons, shaping information processing and orchestrating network activity flows that underlie animal behavior [1,2]. The local inhibitory IN subtypes at the focus of this review recur with closely comparable molecular, connectivity and functional properties in cortical and hippocampal circuits [3]. They are generated in a few specialized ganglionic eminences through the activity of subtype-specific transcriptional networks, and are further specified during their migration and insertion within principal neuron circuits through local signals and activity-dependent mechanisms [3]. These widely distributed building blocks of local networks differ fundamentally from other inhibitory GABAergic neurons with more Current Opinion in Neurobiology 2015, 35:66–73
Application of these technological advances uncovered a key distinction between the firing patterns of principal neurons and local inhibitory INs within cortical and hippocampal areas. Thus, while principal neurons fire sparsely and usually in patterns that differ temporally among individual principal neurons, inhibitory INs of one subtype tend to fire as a group and in predictable patterns [8]. This observation supported the notion that local INs organize network activity, and revealed how subpopulations of INs exhibit distinct and characteristic recruitment and firing properties as a function of brain state and behavior. This, in turn, led to formulation of an influential new conceptual framework in which local IN subtypes are tentatively classified according to their function [3]. This recent development complements previous classifications based on specific connectivity and intrinsic properties of cortical INs [1]. This review focuses on possible functions of local hippocampal inhibitory IN subpopulations in learning, and in particular on how IN connectivity might relate to function. Specifically, I discuss three interrelated issues with broad implications beyond hippocampal function. These www.sciencedirect.com
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include emerging evidence for selective connectivity between subpopulations of INs and principal neurons, evidence of recurring functional microcircuit modules involving identified INs and principal neurons with specific roles in learning, and how the orderly recruitment of IN subpopulations targeting distinct principal neuron subdomains might also mediate how brain states and network oscillations impact on behavior. For more comprehensive treatments of IN subpopulations, hippocampal connectivity and the roles of hippocampal INs in network oscillations the reader is referred to excellent in depth reviews [1,2,9].
Selective connectivity by GABAergic IN subpopulations and information routing Whether anatomical and functional connectivity between IN subtypes and principal neurons is random (i.e. largely predicted by physical proximity), or whether subpopulations of INs and principal neurons might be connected selectively has profound implications for information flow through neuronal circuits. When considering these possibilities it is important to distinguish between selective connectivity based on neuronal subpopulations versus that based on learning rules. That synapses between individual interconnected neurons can vary in strengths as a result of synaptic plasticity and homeostasis processes is well established and not controversial. By contrast, influential studies of subpopulation connectivity have reached the conclusion that GABAergic INs establish local functional synapses in a random process [9,10]. This notion has recently been challenged by careful studies of hippocampal CA1 connectivity. The main reason for the very different conclusions likely lies in the fact that subpopulations of INs and principal neurons need to first be identified before questions about their connectivity can be addressed properly. Pyramidal neurons within cortical or hippocampal layers have predominantly been treated as homogeneous populations of neurons. This presumption tended to imply that any individual pyramidal neuron, for example, within cortical layer 5b or hippocampal CA1, projecting to distinct target areas would be conveying the same information. That individual CA1 pyramidal neurons, for example, cells positioned within the half of the pyramidal layer facing stratum oriens (deep) or facing stratum radiatum (superficial), can indeed project to distinct target areas could be established recently through anatomical and functional studies [11,12,13,14]. Deep cells in CA1 are generated before superficial cells, and they express distinct molecular markers (e.g. Calbindin versus Zinc), consistent with the notion that they might reflect distinct neuronal subpopulations [11]. In parallel, physiological studies in vivo provided evidence that CA1 deep and superficial cells have distinct roles in hippocampal information processing [12]. Although the initial axonal branching patterns were undistinguishable, ventral hippocampus deep cells projected to www.sciencedirect.com
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a much larger number of distant targets (including basolateral amygdala (BLA), medial prefrontal cortex (mPFC), nucleus accumbens) than superficial cells, whose projections were mainly confined to the extended hippocampal system [14]. Furthermore, some deep cells preferentially projected to BLA but not mPFC, whereas other deep cells targeted mPFC but not BLA [13]. A separate study provided evidence for the existence of at least four principal neuron subpopulations in hippocampal dentate gyrus, CA3 and CA1 with distinct and matched time windows of neurogenesis and synaptogenesis, and distinct and partially matched patterns of gene expression [15]. The two earliest born subpopulations accumulate in the deep layers of CA1 and CA3. Notably, the principal neuron subpopulations exhibited a substantial degree of selective connectivity within temporally matched subpopulations (less than 10% mismatch in CA3 and CA1), suggesting that they might provide parallel sub-circuits of information routing through the hippocampus [15] (Figure 1).
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Parallel microcircuits of principal neuron and local IN subpopulations in hippocampal CA1. The schematic indicates CA1 superficial cells (SUP, light blue) preferentially inhibited by late-born PV BCs (PVlate, light brown) and CA1 deep cells (Deep, dark blue) preferentially inhibited by early-born PV BCs (PVearly, dark brown). Deep and superficial cells differ in their projection targets, in their afferents from CA3, in the strength of perisomatic inhibition they receive from PV BCs, and in the strength of excitation they deliver to PV BCs. Whether feedback excitation is selective to early-PV or late-PV BCs is not known. Late-born PV BCs exhibit low ratios of E/I synaptic boutons onto their dendrites (black inhibitory symbol), and their plasticity is regulated through changes in inhibition. Early-born PV BCs exhibit high ratios of E/I synaptic boutons (black excitatory symbol) and their plasticity is regulated through changes in excitation. Whether earlyborn and late-born PV BCs are interconnected as local PV network, and whether these CA1 modules include selective connectivity from SOM and/or VIP INs remains to be determined (indicated by pale tones). Current Opinion in Neurobiology 2015, 35:66–73
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The discovery of principal neuron subpopulations with distinct connectivity properties raised the issue of whether these might be controlled indiscriminately or differentially by GABAergic INs. Because of their relatively greater abundance and better known functional properties, the focus has so far been on fast-spiking Parvalbumin-positive (PV) Basket cells (BCs) and axo-axonic cells (AACs). A key study by Soltesz, Losonczy and colleagues provided evidence that deep cells receive stronger and more abundant inhibitory connections from PV BCs than superficial cells, and that conversely, deep cells provide weaker excitatory connectivity to PV BCs than superficial cells [13] (Figure 1). Furthermore, deep cells projecting to BLA received stronger inhibition from PV BCs than deep cells projecting to mPFC, which in turn provided stronger excitatory inputs to PV BCs than those projecting to BLA [13]. These selective connectivity schemes predict that information from CA1 to distant targets might be conveyed in alternate streams, with activation of one output channel (e.g. deep cells vs superficial cells or deepBLA vs deep-mPFC cells) tending at the same time to minimize output through the other channel(s) [13]. In conceptually related findings, Cholecystokinin (CCK) positive BCs in medial entorhinal cortex (MEC) layer 2 selectively contact Calbindin-positive principal neurons projecting to contralateral EC but not Reelin-positive principal neurons projecting to hippocampal dentate gyrus (see references in [13]). Likewise, AACs in primary visual cortex target cortico-cortical neurons eight times more frequently than cortico-thalamic neurons [16]. Furthermore, Somogyi and colleagues provided evidence that PV-positive septal GABAergic neurons inhibit CA3 PV AACs during sharp-wave ripples (SWRs), and that these might represent a different subpopulation from septal PV neurons projecting to hippocampal BCs [17]. Finally, a recent study provided evidence that CA1 PV BCs selectively targeting principal neuron subpopulations themselves represent distinct subpopulations. Thus, PV BCs were shown to consist of two distinct subpopulations specified through their distinct time schedules of neurogenesis (early-born and late-born PV neurons) [18]. In the adult, early-born PV neurons exhibited higher ratios of excitatory-to-inhibitory synaptic puncta densities onto their dendrites, and expressed higher levels of PV and the GABA synthesizing enzyme GAD67 [18,19]. By contrast, late-born PV neurons exhibited higher dendritic inhibitory-to-excitatory synaptic puncta ratios and lower levels of PV and GAD67. Early-born and late-born PV BCs exhibited plasticity upon distinct learning requirements: late-born PV BC plasticity was induced when mice acquired information about a new task (e.g. in water maze or in rotarod learning, or in environmental enrichment), and led to further accentuation of late-born PV neuron features (further reduction in PV/GAD67 and E/I ratios) [18]. By contrast, early-born PV BC plasticity was induced upon consolidation of validated rules (e.g. in fear conditioning, Current Opinion in Neurobiology 2015, 35:66–73
or at the end of water maze or rotarod learning), and led to further accentuation of early-born PV BC features (further enhancement of PV/GAD67 and E/I ratios). Lateborn PV BC plasticity was specifically induced upon changes in inhibition, whereas early-born PV BC plasticity was specifically induced upon changes in excitation [18]. Notably, early-born PV BC boutons preferentially targeted deep pyramidal neurons in CA1, whereas lateborn PV BCs preferentially targeted superficial cells [18]. Taken together, these findings suggest that subpopulations of PV BCs are embedded into specific local microcircuits with distinct roles in learning and hippocampal information flow (Figure 1). This circuit level organization can provide the basis for specific and possibly alternative routing of information flows as a function of learning and behavioral requirements. How these modules are embedded into more extended local and afferent hippocampal circuits, as well as their behavioral significance remains to be determined (Figure 1).
IN microcircuit modules and their specific roles in learning It is well established that subtypes of cortical and hippocampal local INs innervate distinct subcompartments of principal neurons, that they express distinct neuromodulatory receptors, and that the INs also provide inhibitory inputs to other GABAergic INs [1]. In addition, distinct subtypes of INs fire in characteristic temporal patterns with respect to behaviorally relevant oscillations such as hippocampal theta and SWRs [1]. These detailed neuroanatomical and physiologically studies had, however, left unaddressed the question of whether there might be any consistent connectivity logics relating IN wiring schemes to local regulation of network activity in behavior and during learning. This has changed following a string of recent studies relating what appears to be canonical IN connectivity modules to specific roles in behavior and learning. A study from Kepecs and colleagues related the activities of Somatostatin-positive (SOM) and PV INs to distinct behavioral phases [8]. The study focused on foraging behavior and anterior cingulate cortex, a brain structure thought to determine when to stay and when to leave a foraging site. A subset of SOM neurons fired at the approach of reward, consistent with the notion that they encoded future stay, whereas a subset of PV neurons fired when the mouse left. SOM neurons gated inputs onto pyramidal neurons, whereas PV neurons appeared to control their outputs [8]. In an important study in vitro, Losonczy and colleagues provided evidence that the firing rates of principal neurons in hippocampal CA1 are determined by signal integration at the level of their dendritic compartments in stratum radiatum and oriens, which in turn is under strong and specific negative control www.sciencedirect.com
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by inhibitory inputs from bistratified SOM INs [20]. While somatic inhibition determined at what time pyramidal neurons fired, it was SOM inhibition that determined whether and to what extent they fired [20]. Suppressing somatic inhibition through PV BCs had only a modest impact on principal neuron firing because PV BCs not only inhibited principal neurons but also SOM neurons, leading to potent disinhibition [20]. These findings were consistent with those of a previous report that pairing increasing dendritic excitation to increasing perisomatic inhibition reproduced important features of navigation related theta activity in CA1 pyramidal neurons [21]. A key study of fear learning from Lu¨thi and colleagues focusing on the activity of BLA neurons provided evidence that inhibition of SOM neurons by PV neurons during tone presentation (CS) was required for learning about the conditioning stimulus [22]. Consistent with these findings, studies relating activity in somatosensory cortex to whisking provided evidence that inhibition of SOM neurons through VIP neurons recruited by vibrissae motor cortex might facilitate perception and plasticity during stimulus presentation [23,24,25,7]. Taken together, these studies provided evidence for the existence of a recurrent functional microcircuit module involving disinhibition of pyramidal neuron dendrites through activation of PV neurons leading to inhibition of SOM neurons by the PV neurons (Figure 2). In several distinct behavioral settings involving cortical
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and hippocampal circuits the module appears to be critically important for sensation and encoding of sensory stimuli [26–29]. This recurring microcircuit motif of interconnected dendrite-targeting SOM neurons and soma targeting PV BCs might, however, not always function in the same direction. Thus, studies from the Scanziani and Ha¨usser laboratories highlighted inhibition of PV neurons by SOM INs in primary visual cortex [30,31]. How the opposite directions of PV-SOM-PV inhibition might relate to learning and behavior remains to be determined. In addition to activated PV neurons inhibiting SOM neurons, a second key disinhibition motif was shown to link aversive and neuromodulatory signals to SOM IN suppression in learning. An earlier study of fear conditioning by Lu¨thi, Letzkus and colleagues provided evidence that presentation of an aversive stimulus is associated with widespread ACh release from locus coeruleus neurons to cortical layer 1, to activate GABAergic interneurons that in turn promote learning by suppressing the activity of downstream PV INs, disinhibiting principal neurons [32]. In their more recent study Lu¨thi and colleagues show that a similar IN microcircuit module is important in BLA to learn sensory-aversive associations in fear conditioning [22]. Presentation of the aversive stimulus led to inhibition of both SOM and PV INs, to disinhibit pyramidal neurons at the level of dendrite and soma. The identity of the GABAergic neurons that inhibit
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Dynamic recruitment of distinct local microcircuit modules in learning. Left panel: schematic indicating local IN connectivity as discussed in the main text of this review. IN subtypes provide inhibitory inputs to distinct subcompartments of pyramidal neurons in hippocampal CA1 (dark blue). Central panel: learning sensory associations is promoted by excitation of PV BCs (black arrow), leading to inhibition of bistratified SOM INs and of pyramidal neuron somatic compartments (black inhibitory symbols). This leads to disinhibition of the dendritic compartment (dark blue) but inhibition of the somatic compartment (pale blue) of principal neurons, facilitating dendritic plasticity. Right panel: association of the sensory information to reinforcement signals (here ACh) involves recruitment of VIP and SOM OLM INs, leading to inhibition of bistratified SOM INs and PV BCs (disinhibition of pyramidal neuron dendritic and somatic compartment), as well as inhibition of distal dendritic tufts, suppressing cueassociated sensory signals from EC, and supporting learning of context-reinforcement associations in the hippocampus. www.sciencedirect.com
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SOM and PV neurons upon foot shock remained unclear but independent studies suggest that VIP-positive INs are one candidate for the IN subtype sensitive to neuromodulation in learning [25,33,34,35,36] (Figure 2). Kepecs and colleagues provided evidence that positive and negative reinforcement signals produce disinhibition of sensory cortex through inhibition of SOM and PV neurons by recruited VIP neurons [33]. Likewise, signals from primary motor cortex activated VIP neurons in somatosensory cortex to inhibit SOM and PV neurons, possibly coupling sensory perception to motor output in whisking [25]. Furthermore, VIP bouton numbers onto PV BCs increased upon water maze and rotarod learning, and VIP provided inhibition of PV BCs required for learning [19]. In partial agreement with these findings, the slice study by Scanziani and colleagues in primary visual cortex highlighted prominent inhibition of SOM INs by VIP INs, although it did not detect inhibition of PV neurons by VIP INs [30]. VIP neurons specifically express high levels of ionotropic ACh and serotonin receptors, providing possible fast mechanisms for reinforcement-mediated disinhibition through VIP IN recruitment [3,33,34,35]. In a further example of how disinhibition can gate behavior through PV inhibition, phasic inhibition of mPFC PV INs mediated re-expression of fear upon extinction [37,38]. Interestingly, in addition to a neuromodulatory VIP-SOM/ PV disinhibitory module involving bistratified SOM INs targeting dendritic domains in CA1 stratum radiatum and oriens, a second neuromodulation-gated inhibitory pathway involving OLM SOM INs suppresses sensory input to distal CA1 dendrites in stratum lacunosum moleculare during fear learning [39] (Figure 2). Thus, contextual fear learning further depended on suppression of sensory inputs associated with the unconditioned stimulus in the hippocampus, possibly to allow association of context information from the hippocampus with aversive sensory information from thalamus and/or cortex at BLA. This was achieved through an aversive ACh signal from septum, to activate OLM SOM neurons and suppress excitation of distal dendritic domains by signals from EC [39]. In parallel, island cells in EC layer 2 targeted INs in distal CA1, to inhibit their distal CA1 principal neuron dendrites, and suppress the impact of excitatory input from MEC layer 3, thereby controlling strength and duration of temporal associations in fear learning [40].
theta oscillations related to spatial navigation [41,42], gamma oscillations related to information binding and transmission [43], and SWR related to compressed replay of neuronal sequences during quiet wakefulness and slow-wave sleep [44]. A so-called hippocampal chronocycle has been suggested to orchestrate alternate functions of encoding and retrieval [45] through segregation at the ascending and peak phase of theta (acquisition) and at the descending and trough of theta (retrieval) [42,44]. In parallel, the EC input to CA1 is most active near the peak of theta, whereas the trough is characterized by waning EC input, rising CA3 input, and strongest LTP induction. Buszaki and colleagues investigated the role of CA1 PV and SOM neurons during theta in head-fixed awake mice running on a one-dimensional treadmill [41]. PV neurons had strongest impact on pyramidal neuron firing during the rising phase of theta (somatic inhibition), whereas SOM INs mostly affected firing during the descending phase (dendritic inhibition). Furthermore, SOM neurons controlled pyramidal neuron bursting activity but not theta phase locking, whereas PV neuron silencing did not affect firing rates but shifted firing towards the trough of theta [41,46]. A study from Somogyi et al. investigated how inhibition is recruited during theta and sleep-related SWR activities [44]. For each theta cycle inhibition shifted from axon initial segment to soma, on to proximal dendrites (bistratified SOM) and finally distal dendrites (OLM SOM) of pyramidal neurons in CA1. This pattern of shifting inhibition might reflect organization of encoding (highest at raising phase) and retrieval (highest at descending phase and trough) [44,45]. Furthermore, recruitment of OLM SOM neurons was strongest during free movement and reduced during SWRs, whereas recruitment of bistratified SOM neurons was highest during slow-wave sleep. The authors proposed that higher activity at distal dendrites during the rise of theta might contribute to selecting active neurons over inactive ones at the through of theta [44].
INs targeting principal neuron subdomains and information flow shaping
A study from Klausberger and colleagues investigated how inhibition to distinct pyramidal neuron compartments relates to gamma oscillations in CA1 [43]. Two distinct gamma activities were generated near the soma and at distal dendritic tufts. Distal gamma was generated at the top of theta and was modulated by local INs driven by layer 3 MEC inputs, whereas somatic gamma was generated at the trough of theta and involved PV BCs. These coordinated activities might again reflect temporal segregation of hippocampal encoding (tuft gamma) and transfer of information to downstream targets (somatic gamma).
The theme of IN subpopulations specifically targeting distinct principal neuron dendritic domains and being recruited in an orchestrated manner during learning is found again in how specific IN/principal neuron connectivity organizes hippocampal information flow as a function of behavior and brain states. These studies have focused on hippocampal network activity patterns such as
Taken together, these studies describe how sequential IN recruitment shifts inhibition along the somato-dendritic compartments of principal neurons during each oscillation cycle coupled to behavior and brain state. The results provide further strong support to the emerging concept that distinct subtypes of INs are recruited in
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characteristic and temporally defined patterns to orchestrate network function, behavior and learning. The precise ways in which these inhibition-subcompartmentoscillation studies at the level of individual pyramidal neurons will be linked to learning-related and behaviorrelated orchestration of IN module recruitment remain to be determined.
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at the circuit level might have to embed functional microcircuit models into a broader context of brain state and network oscillations.
Conflict of interest statement Nothing declared.
Acknowledgments Conclusions and outlook Recent findings discussed in this review provide exciting advances on how IN connectivity and recruitment relate to function, and at the same time make it abundantly clear that much remains to be done in order to obtain a circuitlevel understanding of how the hippocampus might support behavior and learning. Research on subpopulation-specific connectivity has uncovered first elements of potential parallel circuits through which hippocampal information might be routed as a function of behavior, brain state and learning (Figure 1). Those circuit elements are far from complete at the anatomical level. For example, we need to know how are the elements embedded into broader schemes of hippocampal circuitry, and whether there is also selective connectivity involving the other subtypes of local GABAergic INs. Then, we need to know how the putative parallel circuits are recruited in hippocampal functions. For example, early-born PV BCs, which are most readily excited, might be well suited for being part of a local module to effectively inhibit SOM bistratified cells and pyramidal neurons and couple sensation to action, whereas late-born PV BCs mainly controlled by inhibition might be suited for inhibitory control through VIP neurons during learning of new associations. Furthermore, if other main subtypes of local INs also include subpopulations, it will be important to determine how they are recruited during learning and behavior. Research on microcircuit modules involving local GABAergic INs in learning has uncovered what might be canonical motives (Figure 2). The motives need to be completed with information concerning afferent inputs and how these are recruited selectively during learning and in behavior. It will be important to determine how behavior-related recruitment of modules interfaces with mechanisms that balance excitation and inhibition at the level of individual pyramidal neurons [47]. In addition, it will be interesting to determine how alternative connectivity involving IN subtypes is recruited during behavior and learning. For example, under what conditions does inhibition of PV neurons by (presumably bistratified) SOM neurons predominate? Finally, as mentioned above, it will be particularly important to link the studies on control of principal neuron subcompartments during oscillations to those relating modules of IN and principal neuron connectivity to behavior and learning. A mechanistic understanding of hippocampal and cortical function www.sciencedirect.com
This work was supported in part by a Swiss National Fund grant. The Friedrich Miescher Institut is part of the Novartis Research Foundation.
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32. Letzkus JJ, Wolff SB, Meyer EM, Tovote P, Courtin J, Herry C, Lu¨thi A: A disinhibitory microcircuit for associative fear learning in the auditory cortex. Nature 2011, 480:331-335.
20. Lovett-Barron M, Turi GF, Kaifosh P, Lee PH, Bolze F, Sun XH, Nicoud JF, Zemelman BV, Sternson SM, Losonczy A: Regulation of neuronal input transformations by tunable dendritic inhibition. Nat Neurosci 2012, 15:423-430. An important study in vitro, showing that the firing rates of principal neurons in hippocampal CA1 are determined by signal integration at the level of their dendritic compartments in stratum radiatum and oriens, which in turn is under strong and specific negative control by inhibitory inputs from bistratified SOM INs. Suppressing somatic inhibition through PV BCs has only a modest impact on principal neuron firing because PV BCs not only inhibit principal neurons but also SOM neurons. The study implies dynamic regulation of principal neuron soma and dendrite processing through specific PV and SOM INs
33. Pi HJ, Hangya B, Kvitsiani D, Sanders JI, Huang ZJ, Kepecs A:: Cortical interneurons that specialize in disinhibitory control. Nature 2013, 503:521-524. A key study showing that positive and negative reinforcement signals produce disinhibition of sensory and medial prefrontal cortex principal neurons through inhibition of SOM and PV neurons by recruited VIP neurons. During an auditory discrimination task reinforcement signals strongly recruit VIP neurons, to enhance the gain of a functional subpopulation of principal neurons.
21. Losonczy A, Zemelman BV, Vaziri A, Magee JC: Network mechanisms of theta related neuronal activity in hippocampal CA1 pyramidal neurons. Nat Neurosci 2010, 13:967-972. 22. Wolff SB, Gru¨ndemann J, Tovote P, Krabbe S, Jacobson GA, Mu¨ller C, Herry C, Ehrlich I, Friedrich RW, Letzkus JJ, Lu¨thi A: Amygdala interneuron subtypes control fear learning through disinhibition. Nature 2014, 509:453-458. Key study focusing on the activity and function of BLA INs neurons in fear learning. Provides evidence that inhibition of SOM neurons by PV neurons during tone presentation is required for learning about conditioning stimulus. Subsequent learning about the association of tone and aversive stimulus involves inhibition of both SOM and PV INs, to disinhibit pyramidal neurons at the level of dendrite and soma. 23. Gentet LJ, Kremer Y, Taniguchi H, Huang ZJ, Staiger JF, Petersen CC: Unique functional properties of somatostatin expressing GABAergic neurons in mouse barrel cortex. Nat Neurosci 2012, 15:607-612. This study and the study in [25] relate activity in somatosensory cortex to whisking, and show that inhibition of SOM neurons might facilitate perception and plasticity during stimulus presentation. 24. Eggermann E, Kremer Y, Crochet S, Petersen CC: Cholinergic signals in mouse barrel cortex during active whisker sensing. Cell Rep 2014, 9:1654-1660. Current Opinion in Neurobiology 2015, 35:66–73
34. Zhang S, Xu M, Kamigaki T, Hoang Do JP, Chang WC, Jenvay S, Miyamichi K, Luo L, Dan Y: Selective attention. Long-range and local circuits for top-down modulation of visual cortex processing. Science 2014, 345:660-665. This study uncovers an attentional signal provided by anterior cingulate cortex onto primary visual cortex through recruitment of VIP INs and local disinhibition to produce center facilitation. In addition, the cingulate input induces surround inhibition through SOM INs. 35. Fu Y, Tucciarone JM, Espinosa JS, Sheng N, Darcy DP, Nicoll RA, Huang ZJ, Stryker MP: A cortical circuit for gain control by behavioral state. Cell 2014, 156:1139-1152. This study reveals that locomotion recruits VIP neurons in primary visual cortex independent of vision through nicotinic ACh signaling from basal forebrain. The VIP IN recruitment and associated disinhibition account for enhanced responses of primary visual cortex during motion. 36. Tyan L, Chamberland S, Magnin E, Camire´ O, Francavilla R, David LS, Deisseroth K, Topolnik L: Dendritic inhibition provided by interneuron-specific cells controls the firing rate and timing of the hippocampal feedback inhibitory circuitry. J Neurosci 2014, 34:4534-4547. 37. Courtin J, Chaudun F, Rozeske RR, Karalis N, Gonzalez-Campo C, Wurtz H, Abdi A, Baufreton J, Bienvenu TC, Herry C: Prefrontal parvalbumin interneurons shape neuronal activity to drive fear expression. Nature 2014, 505:92-96. This study reveals how promotion of a fear response in BLA involves an activation signal by prefrontal cortex upon inhibition of local prefrontal PV neurons, leading to activation of projection neurons. www.sciencedirect.com
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38. Sparta DR, Hovelsø N, Mason AO, Kantak PA, Ung RL, Decot HK, Stuber GD: Activation of prefrontal cortical parvalbumin interneurons facilitates extinction of reward-seeking behavior. J Neurosci 2014, 34:3699-3705.
42. Lapray D, Lasztoczi B, Lagler M, Viney TJ, Katona L, Valenti O, Hartwich K, Borhegyi Z, Somogyi P, Klausberger T: Behaviordependent specialization of identified hippocampal interneurons. Nat Neurosci 2012, 15:1265-1271.
39. Lovett-Barron M, Kaifosh P, Kheirbek MA, Danielson N, Zaremba JD, Reardon TR, Turi GF, Hen R, Zemelman BV, Losonczy A: Dendritic inhibition in the hippocampus supports fear learning. Science 2014, 343:857-863. This study reveals a specific circuit through which an aversive cholinergic input from medial septum activates SOM OLM neurons to suppress the impact of sensory cue inputs from EC to distal dendrites of CA1 pyramidal neurons during fear conditioning. Absence of sensory suppression at the time of acquisition prevents contextual fear conditioning.
43. Laszto´czi B, Klausberger T: Layer-specific GABAergic control of distinct gamma oscillations in the CA1 hippocampus. Neuron 2014, 81:1126-1139. This study shows how in CA1 pyramidal neurons distal dendrite gamma is generated independently from somatic gamma. Distal tuft gamma is generated at the top of theta, and is modulated through lacunosum moleculare INs and inputs from MEC layer 3, whereas somatic gamma is generated at the trough of gamma and is modulated by perisomatic PV BCs.
40. Kitamura T, Pignatelli M, Suh J, Kohara K, Yoshiki A, Abe K, Tonegawa S: Island cells control temporal association memory. Science 2014, 343:896-901. 41. Royer S, Zemelman BV, Losonczy A, Kim J, Chance F, Magee JC, Buzsa´ki G: Control of timing, rate and bursts of hippocampal place cells by dendritic and somatic inhibition. Nat Neurosci 2012, 15:769-775. A study of PV and SOM IN recruitment during one-dimensional treadmill running in head-fixed mice. Somatic inhibition through PV neurons has strongest impact during the rising phase of theta, whereas dendritic inhibition through SOM INs mostly affects firing during the descending phase of theta. SOM neurons control pyramidal neuron bursting activity but not theta phase locking, whereas PV neurons affect theta phase timing but not firing rates.
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44. Katona L, Lapray D, Viney TJ, Oulhaj A, Borhegyi Z, Micklem BR, Klausberger T, Somogyi P: Sleep and movement differentiates actions of two types of somatostatin-expressing GABAergic interneuron in rat hippocampus. Neuron 2014, 82:872-886. 45. Hasselmo ME, Bodelo´n C, Wyble BP: A proposed function for hippocampal theta rhythm: separate phases of encoding and retrieval enhance reversal of prior learning. Neural Comput 2002, 14:793-817. 46. Losonczy A1, Zemelman BV, Vaziri A, Magee JC: Network mechanisms of theta related neuronal activity in hippocampal CA1 pyramidal neurons. Nat Neurosci 2010, 13:967-972. 47. Xue M, Atallah BV, Scanziani M: Equalizing excitation-inhibition ratios across visual cortical neurons. Nature 2014, 511: 596-600.
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ScienceDirect Inhibitory microcircuit modules in hippocampal learning Pico Caroni It has recently become possible to investigate connectivities and roles of identified hippocampal GABAergic interneurons (INs) in behaving rodents. INs targeting distinct pyramidal neuron subcompartments are recruited dynamically at defined phases of behavior and learning. They include Parvalbumin Axo-axonic and perisomatic Basket cells, and Somatostatin radiatum-oriens and oriens-lacunosum moleculare cells. Each IN is in turn either activated or inhibited upon specific behavioral and network state requirements through specific inputs and neuromodulators. Subpopulations of these principal neurons and INs interconnect selectively, suggesting selective processing and routing of alternate information streams. First canonical functional modules have emerged, which will have to be further defined and linked to identified afferents and efferents towards a circuit understanding of how hippocampal networks support behavior. Address Friedrich Miescher Institut, Maulbeerstrasse 66, CH-4058 Basel, Switzerland Corresponding author: Caroni, Pico ([email protected])
Current Opinion in Neurobiology 2015, 35:66–73 This review comes from a themed issue on Circuit plasticity and memory Edited by Tom Mrsic-Flogel and Alessandro Treves
system-specific properties. The latter include GABAergic principal neurons such as cerebellar cortex Purkinje cells or striatal medium spiny neurons, as well as long-distance GABAergic neurons thought to have key roles in coordinating network activity through multiple brain regions. Investigations of local inhibitory neuron functions have recently undergone what can safely be considered a quantum leap due to key advances in technologies and tools [3–7]. Head-fixed preparations have become available that can combine behavioral paradigms with twophoton microscopy-supported monitoring and manipulation of identified neurons in awake mice. This key advance overcame limitations of anaesthetized preparations and allowed investigation of neuronal functions during behavior and in learning. Genetically modified mice have provided tools for specific genetic control of identified interneuron subpopulations during development and in the adult. This advance opened the door to functional investigations and manipulation of interneuron subpopulations in slices and in behaving mice. Finally, opto-genetic and pharmacogenetic tools in combination with viral tools for intersectional targeting of neurons based on their identities and/or connectivities have provided powerful means for causal investigations of neuronal and circuit functions in situ. Together, and in combination with electrophysiology and neuroanatomical techniques, these developments have led to a refocusing of the major questions in circuit neuroscience.
http://dx.doi.org/10.1016/j.conb.2015.06.010 0959-4388/# 2015 Elsevier Ltd. All rights reserved.
Introduction Local microcircuits involving inhibitory GABAergic interneurons (INs) organize the activities of excitatory principal neurons, shaping information processing and orchestrating network activity flows that underlie animal behavior [1,2]. The local inhibitory IN subtypes at the focus of this review recur with closely comparable molecular, connectivity and functional properties in cortical and hippocampal circuits [3]. They are generated in a few specialized ganglionic eminences through the activity of subtype-specific transcriptional networks, and are further specified during their migration and insertion within principal neuron circuits through local signals and activity-dependent mechanisms [3]. These widely distributed building blocks of local networks differ fundamentally from other inhibitory GABAergic neurons with more Current Opinion in Neurobiology 2015, 35:66–73
Application of these technological advances uncovered a key distinction between the firing patterns of principal neurons and local inhibitory INs within cortical and hippocampal areas. Thus, while principal neurons fire sparsely and usually in patterns that differ temporally among individual principal neurons, inhibitory INs of one subtype tend to fire as a group and in predictable patterns [8]. This observation supported the notion that local INs organize network activity, and revealed how subpopulations of INs exhibit distinct and characteristic recruitment and firing properties as a function of brain state and behavior. This, in turn, led to formulation of an influential new conceptual framework in which local IN subtypes are tentatively classified according to their function [3]. This recent development complements previous classifications based on specific connectivity and intrinsic properties of cortical INs [1]. This review focuses on possible functions of local hippocampal inhibitory IN subpopulations in learning, and in particular on how IN connectivity might relate to function. Specifically, I discuss three interrelated issues with broad implications beyond hippocampal function. These www.sciencedirect.com
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include emerging evidence for selective connectivity between subpopulations of INs and principal neurons, evidence of recurring functional microcircuit modules involving identified INs and principal neurons with specific roles in learning, and how the orderly recruitment of IN subpopulations targeting distinct principal neuron subdomains might also mediate how brain states and network oscillations impact on behavior. For more comprehensive treatments of IN subpopulations, hippocampal connectivity and the roles of hippocampal INs in network oscillations the reader is referred to excellent in depth reviews [1,2,9].
Selective connectivity by GABAergic IN subpopulations and information routing Whether anatomical and functional connectivity between IN subtypes and principal neurons is random (i.e. largely predicted by physical proximity), or whether subpopulations of INs and principal neurons might be connected selectively has profound implications for information flow through neuronal circuits. When considering these possibilities it is important to distinguish between selective connectivity based on neuronal subpopulations versus that based on learning rules. That synapses between individual interconnected neurons can vary in strengths as a result of synaptic plasticity and homeostasis processes is well established and not controversial. By contrast, influential studies of subpopulation connectivity have reached the conclusion that GABAergic INs establish local functional synapses in a random process [9,10]. This notion has recently been challenged by careful studies of hippocampal CA1 connectivity. The main reason for the very different conclusions likely lies in the fact that subpopulations of INs and principal neurons need to first be identified before questions about their connectivity can be addressed properly. Pyramidal neurons within cortical or hippocampal layers have predominantly been treated as homogeneous populations of neurons. This presumption tended to imply that any individual pyramidal neuron, for example, within cortical layer 5b or hippocampal CA1, projecting to distinct target areas would be conveying the same information. That individual CA1 pyramidal neurons, for example, cells positioned within the half of the pyramidal layer facing stratum oriens (deep) or facing stratum radiatum (superficial), can indeed project to distinct target areas could be established recently through anatomical and functional studies [11,12,13,14]. Deep cells in CA1 are generated before superficial cells, and they express distinct molecular markers (e.g. Calbindin versus Zinc), consistent with the notion that they might reflect distinct neuronal subpopulations [11]. In parallel, physiological studies in vivo provided evidence that CA1 deep and superficial cells have distinct roles in hippocampal information processing [12]. Although the initial axonal branching patterns were undistinguishable, ventral hippocampus deep cells projected to www.sciencedirect.com
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a much larger number of distant targets (including basolateral amygdala (BLA), medial prefrontal cortex (mPFC), nucleus accumbens) than superficial cells, whose projections were mainly confined to the extended hippocampal system [14]. Furthermore, some deep cells preferentially projected to BLA but not mPFC, whereas other deep cells targeted mPFC but not BLA [13]. A separate study provided evidence for the existence of at least four principal neuron subpopulations in hippocampal dentate gyrus, CA3 and CA1 with distinct and matched time windows of neurogenesis and synaptogenesis, and distinct and partially matched patterns of gene expression [15]. The two earliest born subpopulations accumulate in the deep layers of CA1 and CA3. Notably, the principal neuron subpopulations exhibited a substantial degree of selective connectivity within temporally matched subpopulations (less than 10% mismatch in CA3 and CA1), suggesting that they might provide parallel sub-circuits of information routing through the hippocampus [15] (Figure 1).
Figure 1
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Parallel microcircuits of principal neuron and local IN subpopulations in hippocampal CA1. The schematic indicates CA1 superficial cells (SUP, light blue) preferentially inhibited by late-born PV BCs (PVlate, light brown) and CA1 deep cells (Deep, dark blue) preferentially inhibited by early-born PV BCs (PVearly, dark brown). Deep and superficial cells differ in their projection targets, in their afferents from CA3, in the strength of perisomatic inhibition they receive from PV BCs, and in the strength of excitation they deliver to PV BCs. Whether feedback excitation is selective to early-PV or late-PV BCs is not known. Late-born PV BCs exhibit low ratios of E/I synaptic boutons onto their dendrites (black inhibitory symbol), and their plasticity is regulated through changes in inhibition. Early-born PV BCs exhibit high ratios of E/I synaptic boutons (black excitatory symbol) and their plasticity is regulated through changes in excitation. Whether earlyborn and late-born PV BCs are interconnected as local PV network, and whether these CA1 modules include selective connectivity from SOM and/or VIP INs remains to be determined (indicated by pale tones). Current Opinion in Neurobiology 2015, 35:66–73
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The discovery of principal neuron subpopulations with distinct connectivity properties raised the issue of whether these might be controlled indiscriminately or differentially by GABAergic INs. Because of their relatively greater abundance and better known functional properties, the focus has so far been on fast-spiking Parvalbumin-positive (PV) Basket cells (BCs) and axo-axonic cells (AACs). A key study by Soltesz, Losonczy and colleagues provided evidence that deep cells receive stronger and more abundant inhibitory connections from PV BCs than superficial cells, and that conversely, deep cells provide weaker excitatory connectivity to PV BCs than superficial cells [13] (Figure 1). Furthermore, deep cells projecting to BLA received stronger inhibition from PV BCs than deep cells projecting to mPFC, which in turn provided stronger excitatory inputs to PV BCs than those projecting to BLA [13]. These selective connectivity schemes predict that information from CA1 to distant targets might be conveyed in alternate streams, with activation of one output channel (e.g. deep cells vs superficial cells or deepBLA vs deep-mPFC cells) tending at the same time to minimize output through the other channel(s) [13]. In conceptually related findings, Cholecystokinin (CCK) positive BCs in medial entorhinal cortex (MEC) layer 2 selectively contact Calbindin-positive principal neurons projecting to contralateral EC but not Reelin-positive principal neurons projecting to hippocampal dentate gyrus (see references in [13]). Likewise, AACs in primary visual cortex target cortico-cortical neurons eight times more frequently than cortico-thalamic neurons [16]. Furthermore, Somogyi and colleagues provided evidence that PV-positive septal GABAergic neurons inhibit CA3 PV AACs during sharp-wave ripples (SWRs), and that these might represent a different subpopulation from septal PV neurons projecting to hippocampal BCs [17]. Finally, a recent study provided evidence that CA1 PV BCs selectively targeting principal neuron subpopulations themselves represent distinct subpopulations. Thus, PV BCs were shown to consist of two distinct subpopulations specified through their distinct time schedules of neurogenesis (early-born and late-born PV neurons) [18]. In the adult, early-born PV neurons exhibited higher ratios of excitatory-to-inhibitory synaptic puncta densities onto their dendrites, and expressed higher levels of PV and the GABA synthesizing enzyme GAD67 [18,19]. By contrast, late-born PV neurons exhibited higher dendritic inhibitory-to-excitatory synaptic puncta ratios and lower levels of PV and GAD67. Early-born and late-born PV BCs exhibited plasticity upon distinct learning requirements: late-born PV BC plasticity was induced when mice acquired information about a new task (e.g. in water maze or in rotarod learning, or in environmental enrichment), and led to further accentuation of late-born PV neuron features (further reduction in PV/GAD67 and E/I ratios) [18]. By contrast, early-born PV BC plasticity was induced upon consolidation of validated rules (e.g. in fear conditioning, Current Opinion in Neurobiology 2015, 35:66–73
or at the end of water maze or rotarod learning), and led to further accentuation of early-born PV BC features (further enhancement of PV/GAD67 and E/I ratios). Lateborn PV BC plasticity was specifically induced upon changes in inhibition, whereas early-born PV BC plasticity was specifically induced upon changes in excitation [18]. Notably, early-born PV BC boutons preferentially targeted deep pyramidal neurons in CA1, whereas lateborn PV BCs preferentially targeted superficial cells [18]. Taken together, these findings suggest that subpopulations of PV BCs are embedded into specific local microcircuits with distinct roles in learning and hippocampal information flow (Figure 1). This circuit level organization can provide the basis for specific and possibly alternative routing of information flows as a function of learning and behavioral requirements. How these modules are embedded into more extended local and afferent hippocampal circuits, as well as their behavioral significance remains to be determined (Figure 1).
IN microcircuit modules and their specific roles in learning It is well established that subtypes of cortical and hippocampal local INs innervate distinct subcompartments of principal neurons, that they express distinct neuromodulatory receptors, and that the INs also provide inhibitory inputs to other GABAergic INs [1]. In addition, distinct subtypes of INs fire in characteristic temporal patterns with respect to behaviorally relevant oscillations such as hippocampal theta and SWRs [1]. These detailed neuroanatomical and physiologically studies had, however, left unaddressed the question of whether there might be any consistent connectivity logics relating IN wiring schemes to local regulation of network activity in behavior and during learning. This has changed following a string of recent studies relating what appears to be canonical IN connectivity modules to specific roles in behavior and learning. A study from Kepecs and colleagues related the activities of Somatostatin-positive (SOM) and PV INs to distinct behavioral phases [8]. The study focused on foraging behavior and anterior cingulate cortex, a brain structure thought to determine when to stay and when to leave a foraging site. A subset of SOM neurons fired at the approach of reward, consistent with the notion that they encoded future stay, whereas a subset of PV neurons fired when the mouse left. SOM neurons gated inputs onto pyramidal neurons, whereas PV neurons appeared to control their outputs [8]. In an important study in vitro, Losonczy and colleagues provided evidence that the firing rates of principal neurons in hippocampal CA1 are determined by signal integration at the level of their dendritic compartments in stratum radiatum and oriens, which in turn is under strong and specific negative control www.sciencedirect.com
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by inhibitory inputs from bistratified SOM INs [20]. While somatic inhibition determined at what time pyramidal neurons fired, it was SOM inhibition that determined whether and to what extent they fired [20]. Suppressing somatic inhibition through PV BCs had only a modest impact on principal neuron firing because PV BCs not only inhibited principal neurons but also SOM neurons, leading to potent disinhibition [20]. These findings were consistent with those of a previous report that pairing increasing dendritic excitation to increasing perisomatic inhibition reproduced important features of navigation related theta activity in CA1 pyramidal neurons [21]. A key study of fear learning from Lu¨thi and colleagues focusing on the activity of BLA neurons provided evidence that inhibition of SOM neurons by PV neurons during tone presentation (CS) was required for learning about the conditioning stimulus [22]. Consistent with these findings, studies relating activity in somatosensory cortex to whisking provided evidence that inhibition of SOM neurons through VIP neurons recruited by vibrissae motor cortex might facilitate perception and plasticity during stimulus presentation [23,24,25,7]. Taken together, these studies provided evidence for the existence of a recurrent functional microcircuit module involving disinhibition of pyramidal neuron dendrites through activation of PV neurons leading to inhibition of SOM neurons by the PV neurons (Figure 2). In several distinct behavioral settings involving cortical
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and hippocampal circuits the module appears to be critically important for sensation and encoding of sensory stimuli [26–29]. This recurring microcircuit motif of interconnected dendrite-targeting SOM neurons and soma targeting PV BCs might, however, not always function in the same direction. Thus, studies from the Scanziani and Ha¨usser laboratories highlighted inhibition of PV neurons by SOM INs in primary visual cortex [30,31]. How the opposite directions of PV-SOM-PV inhibition might relate to learning and behavior remains to be determined. In addition to activated PV neurons inhibiting SOM neurons, a second key disinhibition motif was shown to link aversive and neuromodulatory signals to SOM IN suppression in learning. An earlier study of fear conditioning by Lu¨thi, Letzkus and colleagues provided evidence that presentation of an aversive stimulus is associated with widespread ACh release from locus coeruleus neurons to cortical layer 1, to activate GABAergic interneurons that in turn promote learning by suppressing the activity of downstream PV INs, disinhibiting principal neurons [32]. In their more recent study Lu¨thi and colleagues show that a similar IN microcircuit module is important in BLA to learn sensory-aversive associations in fear conditioning [22]. Presentation of the aversive stimulus led to inhibition of both SOM and PV INs, to disinhibit pyramidal neurons at the level of dendrite and soma. The identity of the GABAergic neurons that inhibit
Figure 2
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Dynamic recruitment of distinct local microcircuit modules in learning. Left panel: schematic indicating local IN connectivity as discussed in the main text of this review. IN subtypes provide inhibitory inputs to distinct subcompartments of pyramidal neurons in hippocampal CA1 (dark blue). Central panel: learning sensory associations is promoted by excitation of PV BCs (black arrow), leading to inhibition of bistratified SOM INs and of pyramidal neuron somatic compartments (black inhibitory symbols). This leads to disinhibition of the dendritic compartment (dark blue) but inhibition of the somatic compartment (pale blue) of principal neurons, facilitating dendritic plasticity. Right panel: association of the sensory information to reinforcement signals (here ACh) involves recruitment of VIP and SOM OLM INs, leading to inhibition of bistratified SOM INs and PV BCs (disinhibition of pyramidal neuron dendritic and somatic compartment), as well as inhibition of distal dendritic tufts, suppressing cueassociated sensory signals from EC, and supporting learning of context-reinforcement associations in the hippocampus. www.sciencedirect.com
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SOM and PV neurons upon foot shock remained unclear but independent studies suggest that VIP-positive INs are one candidate for the IN subtype sensitive to neuromodulation in learning [25,33,34,35,36] (Figure 2). Kepecs and colleagues provided evidence that positive and negative reinforcement signals produce disinhibition of sensory cortex through inhibition of SOM and PV neurons by recruited VIP neurons [33]. Likewise, signals from primary motor cortex activated VIP neurons in somatosensory cortex to inhibit SOM and PV neurons, possibly coupling sensory perception to motor output in whisking [25]. Furthermore, VIP bouton numbers onto PV BCs increased upon water maze and rotarod learning, and VIP provided inhibition of PV BCs required for learning [19]. In partial agreement with these findings, the slice study by Scanziani and colleagues in primary visual cortex highlighted prominent inhibition of SOM INs by VIP INs, although it did not detect inhibition of PV neurons by VIP INs [30]. VIP neurons specifically express high levels of ionotropic ACh and serotonin receptors, providing possible fast mechanisms for reinforcement-mediated disinhibition through VIP IN recruitment [3,33,34,35]. In a further example of how disinhibition can gate behavior through PV inhibition, phasic inhibition of mPFC PV INs mediated re-expression of fear upon extinction [37,38]. Interestingly, in addition to a neuromodulatory VIP-SOM/ PV disinhibitory module involving bistratified SOM INs targeting dendritic domains in CA1 stratum radiatum and oriens, a second neuromodulation-gated inhibitory pathway involving OLM SOM INs suppresses sensory input to distal CA1 dendrites in stratum lacunosum moleculare during fear learning [39] (Figure 2). Thus, contextual fear learning further depended on suppression of sensory inputs associated with the unconditioned stimulus in the hippocampus, possibly to allow association of context information from the hippocampus with aversive sensory information from thalamus and/or cortex at BLA. This was achieved through an aversive ACh signal from septum, to activate OLM SOM neurons and suppress excitation of distal dendritic domains by signals from EC [39]. In parallel, island cells in EC layer 2 targeted INs in distal CA1, to inhibit their distal CA1 principal neuron dendrites, and suppress the impact of excitatory input from MEC layer 3, thereby controlling strength and duration of temporal associations in fear learning [40].
theta oscillations related to spatial navigation [41,42], gamma oscillations related to information binding and transmission [43], and SWR related to compressed replay of neuronal sequences during quiet wakefulness and slow-wave sleep [44]. A so-called hippocampal chronocycle has been suggested to orchestrate alternate functions of encoding and retrieval [45] through segregation at the ascending and peak phase of theta (acquisition) and at the descending and trough of theta (retrieval) [42,44]. In parallel, the EC input to CA1 is most active near the peak of theta, whereas the trough is characterized by waning EC input, rising CA3 input, and strongest LTP induction. Buszaki and colleagues investigated the role of CA1 PV and SOM neurons during theta in head-fixed awake mice running on a one-dimensional treadmill [41]. PV neurons had strongest impact on pyramidal neuron firing during the rising phase of theta (somatic inhibition), whereas SOM INs mostly affected firing during the descending phase (dendritic inhibition). Furthermore, SOM neurons controlled pyramidal neuron bursting activity but not theta phase locking, whereas PV neuron silencing did not affect firing rates but shifted firing towards the trough of theta [41,46]. A study from Somogyi et al. investigated how inhibition is recruited during theta and sleep-related SWR activities [44]. For each theta cycle inhibition shifted from axon initial segment to soma, on to proximal dendrites (bistratified SOM) and finally distal dendrites (OLM SOM) of pyramidal neurons in CA1. This pattern of shifting inhibition might reflect organization of encoding (highest at raising phase) and retrieval (highest at descending phase and trough) [44,45]. Furthermore, recruitment of OLM SOM neurons was strongest during free movement and reduced during SWRs, whereas recruitment of bistratified SOM neurons was highest during slow-wave sleep. The authors proposed that higher activity at distal dendrites during the rise of theta might contribute to selecting active neurons over inactive ones at the through of theta [44].
INs targeting principal neuron subdomains and information flow shaping
A study from Klausberger and colleagues investigated how inhibition to distinct pyramidal neuron compartments relates to gamma oscillations in CA1 [43]. Two distinct gamma activities were generated near the soma and at distal dendritic tufts. Distal gamma was generated at the top of theta and was modulated by local INs driven by layer 3 MEC inputs, whereas somatic gamma was generated at the trough of theta and involved PV BCs. These coordinated activities might again reflect temporal segregation of hippocampal encoding (tuft gamma) and transfer of information to downstream targets (somatic gamma).
The theme of IN subpopulations specifically targeting distinct principal neuron dendritic domains and being recruited in an orchestrated manner during learning is found again in how specific IN/principal neuron connectivity organizes hippocampal information flow as a function of behavior and brain states. These studies have focused on hippocampal network activity patterns such as
Taken together, these studies describe how sequential IN recruitment shifts inhibition along the somato-dendritic compartments of principal neurons during each oscillation cycle coupled to behavior and brain state. The results provide further strong support to the emerging concept that distinct subtypes of INs are recruited in
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characteristic and temporally defined patterns to orchestrate network function, behavior and learning. The precise ways in which these inhibition-subcompartmentoscillation studies at the level of individual pyramidal neurons will be linked to learning-related and behaviorrelated orchestration of IN module recruitment remain to be determined.
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at the circuit level might have to embed functional microcircuit models into a broader context of brain state and network oscillations.
Conflict of interest statement Nothing declared.
Acknowledgments Conclusions and outlook Recent findings discussed in this review provide exciting advances on how IN connectivity and recruitment relate to function, and at the same time make it abundantly clear that much remains to be done in order to obtain a circuitlevel understanding of how the hippocampus might support behavior and learning. Research on subpopulation-specific connectivity has uncovered first elements of potential parallel circuits through which hippocampal information might be routed as a function of behavior, brain state and learning (Figure 1). Those circuit elements are far from complete at the anatomical level. For example, we need to know how are the elements embedded into broader schemes of hippocampal circuitry, and whether there is also selective connectivity involving the other subtypes of local GABAergic INs. Then, we need to know how the putative parallel circuits are recruited in hippocampal functions. For example, early-born PV BCs, which are most readily excited, might be well suited for being part of a local module to effectively inhibit SOM bistratified cells and pyramidal neurons and couple sensation to action, whereas late-born PV BCs mainly controlled by inhibition might be suited for inhibitory control through VIP neurons during learning of new associations. Furthermore, if other main subtypes of local INs also include subpopulations, it will be important to determine how they are recruited during learning and behavior. Research on microcircuit modules involving local GABAergic INs in learning has uncovered what might be canonical motives (Figure 2). The motives need to be completed with information concerning afferent inputs and how these are recruited selectively during learning and in behavior. It will be important to determine how behavior-related recruitment of modules interfaces with mechanisms that balance excitation and inhibition at the level of individual pyramidal neurons [47]. In addition, it will be interesting to determine how alternative connectivity involving IN subtypes is recruited during behavior and learning. For example, under what conditions does inhibition of PV neurons by (presumably bistratified) SOM neurons predominate? Finally, as mentioned above, it will be particularly important to link the studies on control of principal neuron subcompartments during oscillations to those relating modules of IN and principal neuron connectivity to behavior and learning. A mechanistic understanding of hippocampal and cortical function www.sciencedirect.com
This work was supported in part by a Swiss National Fund grant. The Friedrich Miescher Institut is part of the Novartis Research Foundation.
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A key study showing that deep cells in CA1 receive stronger and more abundant inhibitory connections from PV BCs than superficial cells, and that they provide weaker excitatory connectivity to PV BCs than superficial cells. Furthermore, deep cells projecting to BLA receive stronger inhibition from PV BCs than deep cells projecting to mPFC. Therefore, information from CA1 to distant targets might be conveyed in alternate streams, with activation of one output channel tending at the same time to minimize output through the other channel(s). 14. Arszovszki A, Borhegyi Z, Klausberger T: Three axonal projection routes of individual pyramidal cells in the ventral CA1 hippocampus. Front Neuroanat 2014, 8:53. 15. Deguchi Y, Donato F, Galimberti I, Cabuy E, Caroni P: Temporally matched subpopulations of selectively interconnected principal neurons in the hippocampus. Nat Neurosci 2011, 14:495-504. 16. Farinas I, DeFelipe J: Patterns of synaptic input on corticocortical and corticothalamic cells in the cat visual cortex. II. The axon initial segment. J Comp Neurol 1991, 304:70-77. 17. Viney TJ, Lasztoczi B, Katona L, Crump MG, Tukker JJ, Klausberger T, Somogyi P: Network state-dependent inhibition of identified hippocampal CA3 axo-axonic cells in vivo. Nat Neurosci 2013, 16:1802-1811. 18. Donato F, Chowdhury A, Lahr M, Caroni P: Early- and late-born parvalbumin basket cell subpopulations exhibiting distinct regulation and roles in learning. Neuron 2015, 85:770-786. This study shows that PV BCs consist of two distinct subpopulations specified through their distinct time schedules of neurogenesis (earlyborn and late-born PV neurons). Late-born PV BC plasticity is specifically induced through changes in inhibition when mice acquire information about a new task, whereas early-born PV BC plasticity is specifically induced through changes in excitation upon consolidation of validated rules. Early-born PV BC boutons preferentially target deep pyramidal neurons in CA1, whereas late-born PV BCs preferentially target superficial cells.
25. Lee S, Kruglikov I, Huang ZJ, Fishell G, Rudy B: A disinhibitory circuit mediates motor integration in the somatosensory cortex. Nat Neurosci 2013, 16:1662-1670. This important study and the study in [23] relate activity in somatosensory cortex to whisking. Here the authors show that long-range projections from vibrissae motor cortex recruit VIP neurons in somatosensory cortex, to inhibit SOM neurons during whisking. 26. Wang XJ, Tegne´r J, Constantinidis C, Goldman-Rakic PS: Division of labor among distinct subtypes of inhibitory neurons in a cortical microcircuit of working memory. Proc Natl Acad Sci U S A 2004, 101:1368-1373. 27. Wilson NR, Runyan CA, Wang FL, Sur M: Division and subtraction by distinct cortical inhibitory networks in vivo. Nature 2012, 488:343-348. 28. Xu H, Jeong HY, Tremblay R, Rudy B: Neocortical somatostatinexpressing GABAergic interneurons disinhibit the thalamorecipient layer 4. Neuron 2013, 77:155-167. 29. Nakajima M, Go¨rlich A, Heintz N: Oxytocin modulates female sociosexual behavior through a specific class of prefrontal cortical interneurons. Cell 2014, 159:295-305. 30. Pfeffer CK, Xue M, He M, Huang ZJ, Scanziani M: Inhibition of inhibition in visual cortex: the logic of connections between molecularly distinct interneurons. Nat Neurosci 2013, 16:10681076. Important study in slices combining optogenetics and electrophysiology of identified INs, and providing a quantitative analysis of inhibitory drives by identified GABAergic INs onto primary visual cortex INs. 31. Cottam JC, Smith SL, Ha¨usser M: Target-specific effects of somatostatin-expressing interneurons on neocortical visual processing. J Neurosci 2013, 33:19567-19578. This in vivo study, and the study in [30] provide evidence for strong inhibitory inputs by SOM INs onto PV INs in visual cortex. The inhibition of PV INs by SOM INs enhances orientation tuning of pyramidal neurons in primary visual cortex.
19. Donato F, Rompani SB, Caroni P: Parvalbumin-expressing basket-cell network plasticity induced by experience regulates adult learning. Nature 2013, 504:272-276.
32. Letzkus JJ, Wolff SB, Meyer EM, Tovote P, Courtin J, Herry C, Lu¨thi A: A disinhibitory microcircuit for associative fear learning in the auditory cortex. Nature 2011, 480:331-335.
20. Lovett-Barron M, Turi GF, Kaifosh P, Lee PH, Bolze F, Sun XH, Nicoud JF, Zemelman BV, Sternson SM, Losonczy A: Regulation of neuronal input transformations by tunable dendritic inhibition. Nat Neurosci 2012, 15:423-430. An important study in vitro, showing that the firing rates of principal neurons in hippocampal CA1 are determined by signal integration at the level of their dendritic compartments in stratum radiatum and oriens, which in turn is under strong and specific negative control by inhibitory inputs from bistratified SOM INs. Suppressing somatic inhibition through PV BCs has only a modest impact on principal neuron firing because PV BCs not only inhibit principal neurons but also SOM neurons. The study implies dynamic regulation of principal neuron soma and dendrite processing through specific PV and SOM INs
33. Pi HJ, Hangya B, Kvitsiani D, Sanders JI, Huang ZJ, Kepecs A:: Cortical interneurons that specialize in disinhibitory control. Nature 2013, 503:521-524. A key study showing that positive and negative reinforcement signals produce disinhibition of sensory and medial prefrontal cortex principal neurons through inhibition of SOM and PV neurons by recruited VIP neurons. During an auditory discrimination task reinforcement signals strongly recruit VIP neurons, to enhance the gain of a functional subpopulation of principal neurons.
21. Losonczy A, Zemelman BV, Vaziri A, Magee JC: Network mechanisms of theta related neuronal activity in hippocampal CA1 pyramidal neurons. Nat Neurosci 2010, 13:967-972. 22. Wolff SB, Gru¨ndemann J, Tovote P, Krabbe S, Jacobson GA, Mu¨ller C, Herry C, Ehrlich I, Friedrich RW, Letzkus JJ, Lu¨thi A: Amygdala interneuron subtypes control fear learning through disinhibition. Nature 2014, 509:453-458. Key study focusing on the activity and function of BLA INs neurons in fear learning. Provides evidence that inhibition of SOM neurons by PV neurons during tone presentation is required for learning about conditioning stimulus. Subsequent learning about the association of tone and aversive stimulus involves inhibition of both SOM and PV INs, to disinhibit pyramidal neurons at the level of dendrite and soma. 23. Gentet LJ, Kremer Y, Taniguchi H, Huang ZJ, Staiger JF, Petersen CC: Unique functional properties of somatostatin expressing GABAergic neurons in mouse barrel cortex. Nat Neurosci 2012, 15:607-612. This study and the study in [25] relate activity in somatosensory cortex to whisking, and show that inhibition of SOM neurons might facilitate perception and plasticity during stimulus presentation. 24. Eggermann E, Kremer Y, Crochet S, Petersen CC: Cholinergic signals in mouse barrel cortex during active whisker sensing. Cell Rep 2014, 9:1654-1660. Current Opinion in Neurobiology 2015, 35:66–73
34. Zhang S, Xu M, Kamigaki T, Hoang Do JP, Chang WC, Jenvay S, Miyamichi K, Luo L, Dan Y: Selective attention. Long-range and local circuits for top-down modulation of visual cortex processing. Science 2014, 345:660-665. This study uncovers an attentional signal provided by anterior cingulate cortex onto primary visual cortex through recruitment of VIP INs and local disinhibition to produce center facilitation. In addition, the cingulate input induces surround inhibition through SOM INs. 35. Fu Y, Tucciarone JM, Espinosa JS, Sheng N, Darcy DP, Nicoll RA, Huang ZJ, Stryker MP: A cortical circuit for gain control by behavioral state. Cell 2014, 156:1139-1152. This study reveals that locomotion recruits VIP neurons in primary visual cortex independent of vision through nicotinic ACh signaling from basal forebrain. The VIP IN recruitment and associated disinhibition account for enhanced responses of primary visual cortex during motion. 36. Tyan L, Chamberland S, Magnin E, Camire´ O, Francavilla R, David LS, Deisseroth K, Topolnik L: Dendritic inhibition provided by interneuron-specific cells controls the firing rate and timing of the hippocampal feedback inhibitory circuitry. J Neurosci 2014, 34:4534-4547. 37. Courtin J, Chaudun F, Rozeske RR, Karalis N, Gonzalez-Campo C, Wurtz H, Abdi A, Baufreton J, Bienvenu TC, Herry C: Prefrontal parvalbumin interneurons shape neuronal activity to drive fear expression. Nature 2014, 505:92-96. This study reveals how promotion of a fear response in BLA involves an activation signal by prefrontal cortex upon inhibition of local prefrontal PV neurons, leading to activation of projection neurons. www.sciencedirect.com
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38. Sparta DR, Hovelsø N, Mason AO, Kantak PA, Ung RL, Decot HK, Stuber GD: Activation of prefrontal cortical parvalbumin interneurons facilitates extinction of reward-seeking behavior. J Neurosci 2014, 34:3699-3705.
42. Lapray D, Lasztoczi B, Lagler M, Viney TJ, Katona L, Valenti O, Hartwich K, Borhegyi Z, Somogyi P, Klausberger T: Behaviordependent specialization of identified hippocampal interneurons. Nat Neurosci 2012, 15:1265-1271.
39. Lovett-Barron M, Kaifosh P, Kheirbek MA, Danielson N, Zaremba JD, Reardon TR, Turi GF, Hen R, Zemelman BV, Losonczy A: Dendritic inhibition in the hippocampus supports fear learning. Science 2014, 343:857-863. This study reveals a specific circuit through which an aversive cholinergic input from medial septum activates SOM OLM neurons to suppress the impact of sensory cue inputs from EC to distal dendrites of CA1 pyramidal neurons during fear conditioning. Absence of sensory suppression at the time of acquisition prevents contextual fear conditioning.
43. Laszto´czi B, Klausberger T: Layer-specific GABAergic control of distinct gamma oscillations in the CA1 hippocampus. Neuron 2014, 81:1126-1139. This study shows how in CA1 pyramidal neurons distal dendrite gamma is generated independently from somatic gamma. Distal tuft gamma is generated at the top of theta, and is modulated through lacunosum moleculare INs and inputs from MEC layer 3, whereas somatic gamma is generated at the trough of gamma and is modulated by perisomatic PV BCs.
40. Kitamura T, Pignatelli M, Suh J, Kohara K, Yoshiki A, Abe K, Tonegawa S: Island cells control temporal association memory. Science 2014, 343:896-901. 41. Royer S, Zemelman BV, Losonczy A, Kim J, Chance F, Magee JC, Buzsa´ki G: Control of timing, rate and bursts of hippocampal place cells by dendritic and somatic inhibition. Nat Neurosci 2012, 15:769-775. A study of PV and SOM IN recruitment during one-dimensional treadmill running in head-fixed mice. Somatic inhibition through PV neurons has strongest impact during the rising phase of theta, whereas dendritic inhibition through SOM INs mostly affects firing during the descending phase of theta. SOM neurons control pyramidal neuron bursting activity but not theta phase locking, whereas PV neurons affect theta phase timing but not firing rates.
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44. Katona L, Lapray D, Viney TJ, Oulhaj A, Borhegyi Z, Micklem BR, Klausberger T, Somogyi P: Sleep and movement differentiates actions of two types of somatostatin-expressing GABAergic interneuron in rat hippocampus. Neuron 2014, 82:872-886. 45. Hasselmo ME, Bodelo´n C, Wyble BP: A proposed function for hippocampal theta rhythm: separate phases of encoding and retrieval enhance reversal of prior learning. Neural Comput 2002, 14:793-817. 46. Losonczy A1, Zemelman BV, Vaziri A, Magee JC: Network mechanisms of theta related neuronal activity in hippocampal CA1 pyramidal neurons. Nat Neurosci 2010, 13:967-972. 47. Xue M, Atallah BV, Scanziani M: Equalizing excitation-inhibition ratios across visual cortical neurons. Nature 2014, 511: 596-600.
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