Gamma frequency oscillations are thought to provide a temporal structure for information processing in the brain. They contribute to cognitive functions, such as memory formation and sensory processing, and are disturbed in some psychiatric disorders. Fast-spiking, parvalbumin-expressing, soma-inhibiting interneurons have a key role in the generation of these oscillations. Experimental analysis in the hippocampus and the neocortex reveals that synapses among these interneurons are highly specialized. Computational analysis further suggests that synaptic specialization turns interneuron networks into robust gamma frequency oscillators.

Networks of GABAergic interneurons are of critical importance for the generation of gamma frequency oscillations in the brain. To examine the underlying synaptic mechanisms, we made paired recordings from ''basket cells'' (BCs) in different subfields of hippocampal slices, using transgenic mice that express enhanced green fluorescent protein (EGFP) under the control of the parvalbumin promoter. Unitary inhibitory postsynaptic currents (IPSCs) showed large amplitude and fast time course with mean amplitudeweighted decay time constants of 2.5, 1.2, and 1.8 ms in the dentate gyrus, and the cornu ammonis area 3 (CA3) and 1 (CA1), respectively (33-34°C). The decay of unitary IPSCs at BC-BC synapses was significantly faster than that at BC-principal cell synapses, indicating target cell-specific differences in IPSC kinetics. In addition, electrical coupling was found in a subset of BC-BC pairs. To examine whether an interneuron network with fast inhibitory synapses can act as a gamma frequency oscillator, we developed an interneuron network model based on experimentally determined properties. In comparison to previous interneuron network models, our model was able to generate oscillatory activity with higher coherence over a broad range of frequencies (20 -110 Hz). In this model, high coherence and flexibility in frequency control emerge from the combination of synaptic properties, network structure, and electrical coupling.G amma frequency oscillations are thought to be of key importance for higher brain functions, such as feature binding and temporal encoding of information (1-5). Experimental and theoretical evidence suggests that local networks of synaptically connected GABAergic interneurons are critically involved in the generation of these oscillations (6-19). First, perisomatic inhibitory interneurons (basket cells) fire action potentials at high frequency during gamma activity in vivo, with single spikes phase-locked to the oscillations of the field potential (6, 7). Second, pharmacologically isolated networks of inhibitory interneurons in vitro can oscillate at gamma frequency in response to metabotropic glutamate receptor activation (8). Finally, models of mutually connected interneurons generate coherent action potential activity in the gamma frequency range in the presence of a tonic excitatory drive (9-19).The mechanisms leading to the generation of coherent gamma oscillations in interneuron networks, however, have remained unclear. Although gamma frequency oscillations can be generated in interneuron network models, coherence is fragile against variation in amplitude and time course of the inhibitory postsynaptic conductance, against heterogeneity of the tonic excitatory drive, and against sparseness of connectivity (11-14). The mechanisms contributing to the control of network frequency are also poorly understood. It is thought that the time course of the inhibitory synaptic conductance change is a major factor (8-14), but the significance of other parameters remains undetermined. Some models suggest t...

During our daily life, we depend on memories of past experiences to plan future behaviour. These memories are represented by the activity of specific neuronal groups or 'engrams'. Neuronal engrams are assembled during learning by synaptic modification, and engram reactivation represents the memorized experience . Engrams of conscious memories are initially stored in the hippocampus for several days and then transferred to cortical areas . In the dentate gyrus of the hippocampus, granule cells transform rich inputs from the entorhinal cortex into a sparse output, which is forwarded to the highly interconnected pyramidal cell network in hippocampal area CA3 . This process is thought to support pattern separation (but see refs. ). CA3 pyramidal neurons project to CA1, the hippocampal output region. Consistent with the idea of transient memory storage in the hippocampus, engrams in CA1 and CA2 do not stabilize over time. Nevertheless, reactivation of engrams in the dentate gyrus can induce recall of artificial memories even after weeks . Reconciliation of this apparent paradox will require recordings from dentate gyrus granule cells throughout learning, which has so far not been performed for more than a single day. Here, we use chronic two-photon calcium imaging in head-fixed mice performing a multiple-day spatial memory task in a virtual environment to record neuronal activity in all major hippocampal subfields. Whereas pyramidal neurons in CA1-CA3 show precise and highly context-specific, but continuously changing, representations of the learned spatial sceneries in our behavioural paradigm, granule cells in the dentate gyrus have a spatial code that is stable over many days, with low place- or context-specificity. Our results suggest that synaptic weights along the hippocampal trisynaptic loop are constantly reassigned to support the formation of dynamic representations in downstream hippocampal areas based on a stable code provided by the dentate gyrus.

Networks of GABAergic neurons are key elements in the generation of gamma oscillations in the brain. Computational studies suggested that the emergence of coherent oscillations requires hyperpolarizing inhibition. Here, we show that GABA(A) receptor-mediated inhibition in mature interneurons of the hippocampal dentate gyrus is shunting rather than hyperpolarizing. Unexpectedly, when shunting inhibition is incorporated into a structured interneuron network model with fast and strong synapses, coherent oscillations emerge. In comparison to hyperpolarizing inhibition, networks with shunting inhibition show several advantages. First, oscillations are generated with smaller tonic excitatory drive. Second, network frequencies are tuned to the gamma band. Finally, robustness against heterogeneity in the excitatory drive is markedly improved. In single interneurons, shunting inhibition shortens the interspike interval for low levels of drive but prolongs it for high levels, leading to homogenization of neuronal firing rates. Thus, shunting inhibition may confer increased robustness to gamma oscillations in the brain.

Interactions among rhythmically active neuronal circuits that oscillate at different frequencies are important for generating complex behaviors, yet little is known about the underlying cellular mechanisms. We addressed this issue in the crab stomatogastric ganglion (STG), which contains two distinct but interacting circuits. These circuits generate the gastric mill rhythm (cycle period, approximately 10 sec) and the pyloric rhythm (cycle period, approximately 1 sec). When the identified modulatory projection neuron named modulatory commissural neuron 1 (MCN1) is activated, the gastric mill motor pattern is generated by interactions among MCN1 and two STG neurons [the lateral gastric (LG) neuron and interneuron 1]. We show that, during MCN1 stimulation, an identified synapse from the pyloric circuit onto the gastric mill circuit is pivotal for determining the gastric mill cycle period and the gastric-pyloric rhythm coordination. To examine the role of this intercircuit synapse, we replaced it with a computational equivalent via the dynamic-clamp technique. This enabled us to manipulate better the timing and strength of this synapse. We found this synapse to be necessary for production of the normal gastric mill cycle period. The synapse acts, during each LG neuron interburst, to boost rhythmically the influence of the modulatory input from MCN1 to LG and thereby to hasten LG neuron burst onset. The two rhythms become coordinated because LG burst onset occurs with a constant latency after the onset of the triggering pyloric input. These results indicate that intercircuit synapses can enable an oscillatory circuit to control the speed of a slower oscillatory circuit, as well as provide a mechanism for intercircuit coordination.

Hippocampal theta (5-10 Hz) and gamma (35-85 Hz) oscillations depend on an inhibitory network of GABAergic interneurons. However, the lack of methods for direct and cell-type-specific interference with inhibition has prevented better insights that help link synaptic and cellular properties with network function. Here, we generated genetically modified mice (PV-⌬␥ 2) in which synaptic inhibition was ablated in parvalbumin-positive (PV؉) interneurons. Hippocampal local field potential and unit recordings in the CA1 area of freely behaving mice revealed that theta rhythm was strongly reduced in these mice. The characteristic coupling of theta and gamma oscillations was strongly altered in PV-⌬␥ 2 mice more than could be accounted for by the reduction in theta rhythm only. Surprisingly, gamma oscillations were not altered. These data indicate that synaptic inhibition onto PV؉ interneurons is indispensable for theta-and its coupling to gamma oscillations but not for rhythmic gammaactivity in the hippocampus. Similar alterations in rhythmic activity were obtained in a computational hippocampal network model mimicking the genetic modification, suggesting that intrahippocampal networks might contribute to these effects.compartmental model ͉ GABA ͉ GABAA receptor ͉ knockout ͉ network synchrony

Mutual synaptic interactions between GABAergic interneurons are thought to be of critical importance for the generation of network oscillations and for temporal encoding of information in the hippocampus. However, the functional properties of synaptic transmission between hippocampal interneurons are largely unknown. We have made paired recordings from basket cells (BCs) in the dentate gyrus of rat hippocampal slices, followed by correlated light and electron microscopical analysis. Unitary GABA A receptor-mediated IPSCs at BC-BC synapses recorded at the soma showed a fast rise and decay, with a mean decay time constant of 2.5 Ϯ 0.2 msec (32°C). Synaptic transmission at BC-BC synapses showed paired-pulse depression (PPD) (32 Ϯ 5% for 10 msec interpulse intervals) and multiple-pulse depression during repetitive stimulation. Detailed passive cable model simulations based on somatodendritic morphology and localization of synaptic contacts further indicated that the conductance change at the postsynaptic site was even faster, decaying with a mean time constant of 1.8 Ϯ 0.6 msec. Sequential triple recordings revealed that the decay time course of IPSCs at BC-BC synapses was approximately twofold faster than that at BC-granule cell synapses, whereas the extent of PPD was comparable. To examine the consequences of the fast postsynaptic conductance change for the generation of oscillatory activity, we developed a computational model of an interneuron network. The model showed robust oscillations at frequencies Ͼ60 Hz if the excitatory drive was sufficiently large. Thus the fast conductance change at interneuron-interneuron synapses may promote the generation of high-frequency oscillations observed in the dentate gyrus in vivo.

Gamma frequency (30 -100 Hz) oscillations in the mature cortex underlie higher cognitive functions. Fast signaling in GABAergic interneuron networks plays a key role in the generation of these oscillations. During development of the rodent brain, gamma activity appears at the end of the first postnatal week, but frequency and synchrony reach adult levels only by the fourth week. However, the mechanisms underlying the maturation of gamma activity are unclear. Here we demonstrate that hippocampal basket cells (BCs), the proposed cellular substrate of gamma oscillations, undergo marked changes in their morphological, intrinsic, and synaptic properties between postnatal day 6 (P6) and P25. During maturation, action potential duration, propagation time, duration of the release period, and decay time constant of IPSCs decreases by ϳ30 -60%. Thus, postnatal development converts BCs from slow into fast signaling devices. Computational analysis reveals that BC networks with young intrinsic and synaptic properties as well as reduced connectivity generate oscillations with moderate coherence in the lower gamma frequency range. In contrast, BC networks with mature properties and increased connectivity generate highly coherent activity in the upper gamma frequency band. Thus, late postnatal maturation of BCs enhances coherence in neuronal networks and will thereby contribute to the development of cognitive brain functions.