Direct synaptic excitation between hilar mossy cells revealed with a targeted voltage sensor

Intrinsic and Synaptic Contributions to Repetitive Spiking in Dentate Granule Cells

Repetitive firing of granule cells (GCs) in the dentate gyrus (DG) facilitates synaptic transmission to the CA3 region. This facilitation can gate and amplify the flow of information through the hippocampus. High-frequency bursts in the DG are linked to behavior and plasticity, but GCs do not readily burst. Under normal conditions, a single shock to the perforant path in a hippocampal slice typically drives a GC to fire a single spike, and only occasionally more than one spike is seen. Repetitive spiking in GCs is not robust, and the mechanisms are poorly understood. Here, we used a hybrid genetically encoded voltage sensor to image voltage changes evoked by cortical inputs in many mature GCs simultaneously in hippocampal slices from male and female mice. This enabled us to study relatively infrequent double and triple spikes. We found GCs are relatively homogeneous and their double spiking behavior is cell autonomous. Blockade of GABA type A receptors increased multiple spikes and prolonged the interspike interval, indicating inhibitory interneurons limit repetitive spiking and set the time window for successive spikes. Inhibiting synaptic glutamate release showed that recurrent excitation mediated by hilar mossy cells contributes to, but is not necessary for, multiple spiking. Blockade of T-type Ca2+ channels did not reduce multiple spiking but prolonged interspike intervals. Imaging voltage changes in different GC compartments revealed that second spikes can be initiated in either dendrites or somata. Thus, pharmacological and biophysical experiments reveal roles for both synaptic circuitry and intrinsic excitability in GC repetitive spiking.

Adaptive spike threshold dynamics associated with sparse spiking of hilar mossy cells are captured by a simple model

Hilar mossy cells (hMCs) in the dentate gyrus (DG) receive inputs from DG granule cells (GCs), CA3 pyramidal cells and inhibitory interneurons, and provide feedback input to GCs. Behavioural and in vivo recording experiments implicate hMCs in pattern separation, navigation and spatial learning. Our experiments link hMC intrinsic excitability to their synaptically evoked in vivo spiking outputs. We performed electrophysiological recordings from DG neurons and found that hMCs displayed an adaptative spike threshold that increased both in proportion to the intensity of injected currents, and in response to spiking itself, returning to baseline over a long time scale, thereby instantaneously limiting their firing rate responses. The hMC activity is additionally limited by a prominent medium after-hyperpolarizing potential (AHP) generated by small conductance K+ channels. We hypothesize that these intrinsic hMC properties are responsible for their low in vivo firing rates. Our findings extend previous studies that compare hMCs, CA3 pyramidal cells and hilar inhibitory cells and provide novel quantitative data that contrast the intrinsic properties of these cell types. We developed a phenomenological exponential integrate-and-fire model that closely reproduces the hMC adaptive threshold nonlinearities with respect to their threshold dependence on input current intensity, evoked spike latency and long-lasting spike-induced increase in spike threshold. Our robust and computationally efficient model is amenable to incorporation into large network models of the DG that will deepen our understanding of the neural bases of pattern separation, spatial navigation and learning. KEY POINTS: Previous studies have shown that hilar mossy cells (hMCs) are implicated in pattern separation and the formation of spatial memory, but how their intrinsic properties relate to their in vivo spiking patterns is still unknown. Here we show that the hMCs display electrophysiological properties that distinguish them from the other hilar cell types including a highly adaptive spike threshold that decays slowly. The spike-dependent increase in threshold combined with an after-hyperpolarizing potential mediated by a slow K+ conductance is hypothesized to be responsible for the low-firing rate of the hMC observed in vivo. The hMC's features are well captured by a modified stochastic exponential integrate-and-fire model that has the unique feature of a threshold intrinsically dependant on both the stimulus intensity and the spiking history. This computational model will allow future work to study how the hMCs can contribute to spatial memory formation and navigation.

Unitary synaptic responses of parvalbumin interneurons evoked by excitatory neurons in the mouse barrel cortex

The mammalian cortex integrates and processes information to transform sensory inputs into perceptions and motor outputs. These operations are performed by networks of excitatory and inhibitory neurons distributed through the cortical layers. Parvalbumin interneurons (PVIs) are the most abundant type of inhibitory cortical neuron. With axons projecting within and between layers, PVIs supply feedforward and feedback inhibition to control and modulate circuit function. Distinct populations of excitatory neurons recruit different PVI populations, but the specializations of these synapses are poorly understood. Here, we targeted a genetically encoded hybrid voltage sensor to PVIs and used fluorescence imaging in mouse somatosensory cortex slices to record their voltage changes. Stimulating a single visually identified excitatory neuron with small-tipped theta-glass electrodes depolarized multiple PVIs, and a common threshold suggested that stimulation elicited unitary synaptic potentials in response to a single excitatory neuron. Excitatory neurons depolarized PVIs in multiple layers, with the most residing in the layer of the stimulated neuron. Spiny stellate cells depolarized PVIs more strongly than pyramidal cells by up to 77%, suggesting a greater role for stellate cells in recruiting PVI inhibition and controlling cortical computations. Response half-width also varied between different excitatory inputs. These results demonstrate functional differences between excitatory synapses on PVIs.

Imaging Voltage Globally and in Isofrequency Lamina in Slices of Mouse Ventral Cochlear Nucleus

The cochlear nuclei (CNs) receive sensory information from the ear and perform fundamental computations before relaying this information to higher processing centers. These computations are performed by distinct types of neurons interconnected in circuits dedicated to the specialized roles of the auditory system. In the present study, we explored the use of voltage imaging to investigate CN circuitry. We tested two approaches based on fundamentally different voltage sensing technologies. Using a voltage-sensitive dye we recorded glutamate receptor-independent signals arising predominantly from axons. The mean conduction velocity of these fibers of 0.27 m/s was rapid but in range with other unmyelinated axons. We then used a genetically-encoded hybrid voltage sensor (hVOS) to image voltage from a specific population of neurons. Probe expression was controlled using Cre recombinase linked to c-fos activation. This activity-induced gene enabled targeting of neurons that are activated when a mouse hears a pure 15-kHz tone. In CN slices from these animals auditory nerve fiber stimulation elicited a glutamate receptor-dependent depolarization in hVOS probe-labeled neurons. These cells resided within a band corresponding to an isofrequency lamina, and responded with a high degree of synchrony. In contrast to the axonal origin of voltage-sensitive dye signals, hVOS signals represent predominantly postsynaptic responses. The introduction of voltage imaging to the CN creates the opportunity to investigate auditory processing circuitry in populations of neurons targeted on the basis of their genetic identity and their roles in sensory processing.

Recurrent Excitatory Feedback From Mossy Cells Enhances Sparsity and Pattern Separation in the Dentate Gyrus via Indirect Feedback Inhibition

It is generally appreciated that storing memories of specific events in the mammalian brain, and associating features of the environment with behavioral outcomes requires fine-tuning of the strengths of connections between neurons through synaptic plasticity. It is less understood whether the organization of neuronal circuits comprised of multiple distinct neuronal cell types provides an architectural prior that facilitates learning and memory by generating unique patterns of neuronal activity in response to different stimuli in the environment, even before plasticity and learning occur. Here we simulated a neuronal network responding to sensory stimuli, and systematically determined the effects of specific neuronal cell types and connections on three key metrics of neuronal sensory representations: sparsity, selectivity, and discriminability. We found that when the total amount of input varied considerably across stimuli, standard feedforward and feedback inhibitory circuit motifs failed to discriminate all stimuli without sacrificing sparsity or selectivity. Interestingly, networks that included dedicated excitatory feedback interneurons based on the mossy cells of the hippocampal dentate gyrus exhibited improved pattern separation, a result that depended on the indirect recruitment of feedback inhibition. These results elucidate the roles of cellular diversity and neural circuit architecture on generating neuronal representations with properties advantageous for memory storage and recall.