An Approach for Reliably Investigating Hippocampal Sharp Wave-Ripples In Vitro

Among the various hippocampal network patterns, sharp wave-ripples (SPW-R) are currently the mechanistically least understood. Although accurate information on synaptic interactions between the participating neurons is essential for comprehensive understanding of the network function during complex activities like SPW-R, such knowledge is currently notably scarce. counterpart. We show that slice storage in the interface chamber close to physiological temperature is the required condition to preserve network integrity that is necessary for the generation of SPW-R. Moreover, we demonstrate the utility of our method for studying synaptic and network properties of SPW-R, using electrophysiological and imaging methods that can only be applied in the submerged system.The approach presented here demonstrates a reliable and experimentally simple strategy for studying hippocampal sharp wave-ripples. Given its utility and easy application we expect our model to foster the generation of new insight into the network physiology underlying SPW-R

The response of a classical Hodgkin–Huxley neuron to an inhibitory input pulse

A population of uncoupled neurons can often be brought close to synchrony by a single strong inhibitory input pulse affecting all neurons equally. This mechanism is thought to underlie some brain rhythms, in particular gamma frequency (30–80 Hz) oscillations in the hippocampus and neocortex. Here we show that synchronization by an inhibitory input pulse often fails for populations of classical Hodgkin–Huxley neurons. Our reasoning suggests that in general, synchronization by inhibitory input pulses can fail when the transition of the target neurons from rest to spiking involves a Hopf bifurcation, especially when inhibition is shunting, not hyperpolarizing. Surprisingly, synchronization is more likely to fail when the inhibitory pulse is stronger or longer-lasting. These findings have potential implications for the question which neurons participate in brain rhythms, in particular in gamma oscillations

Sparse Gamma Rhythms Arising through Clustering in Adapting Neuronal Networks

Gamma rhythms (30–100 Hz) are an extensively studied synchronous brain state responsible for a number of sensory, memory, and motor processes. Experimental evidence suggests that fast-spiking interneurons are responsible for carrying the high frequency components of the rhythm, while regular-spiking pyramidal neurons fire sparsely. We propose that a combination of spike frequency adaptation and global inhibition may be responsible for this behavior. Excitatory neurons form several clusters that fire every few cycles of the fast oscillation. This is first shown in a detailed biophysical network model and then analyzed thoroughly in an idealized model. We exploit the fact that the timescale of adaptation is much slower than that of the other variables. Singular perturbation theory is used to derive an approximate periodic solution for a single spiking unit. This is then used to predict the relationship between the number of clusters arising spontaneously in the network as it relates to the adaptation time constant. We compare this to a complementary analysis that employs a weak coupling assumption to predict the first Fourier mode to destabilize from the incoherent state of an associated phase model as the external noise is reduced. Both approaches predict the same scaling of cluster number with respect to the adaptation time constant, which is corroborated in numerical simulations of the full system. Thus, we develop several testable predictions regarding the formation and characteristics of gamma rhythms with sparsely firing excitatory neurons

Membrane Properties and the Balance between Excitation and Inhibition Control Gamma-Frequency Oscillations Arising from Feedback Inhibition

Computational studies as well as in vivo and in vitro results have shown that many cortical neurons fire in a highly irregular manner and at low average firing rates. These patterns seem to persist even when highly rhythmic signals are recorded by local field potential electrodes or other methods that quantify the summed behavior of a local population. Models of the 30–80 Hz gamma rhythm in which network oscillations arise through ‘stochastic synchrony’ capture the variability observed in the spike output of single cells while preserving network-level organization. We extend upon these results by constructing model networks constrained by experimental measurements and using them to probe the effect of biophysical parameters on network-level activity. We find in simulations that gamma-frequency oscillations are enabled by a high level of incoherent synaptic conductance input, similar to the barrage of noisy synaptic input that cortical neurons have been shown to receive in vivo. This incoherent synaptic input increases the emergent network frequency by shortening the time scale of the membrane in excitatory neurons and by reducing the temporal separation between excitation and inhibition due to decreased spike latency in inhibitory neurons. These mechanisms are demonstrated in simulations and in vitro current-clamp and dynamic-clamp experiments. Simulation results further indicate that the membrane potential noise amplitude has a large impact on network frequency and that the balance between excitatory and inhibitory currents controls network stability and sensitivity to external inputs

Encoding of Spatio-Temporal Input Characteristics by a CA1 Pyramidal Neuron Model

The in vivo activity of CA1 pyramidal neurons alternates between regular spiking and bursting, but how these changes affect information processing remains unclear. Using a detailed CA1 pyramidal neuron model, we investigate how timing and spatial arrangement variations in synaptic inputs to the distal and proximal dendritic layers influence the information content of model responses. We find that the temporal delay between activation of the two layers acts as a switch between excitability modes: short delays induce bursting while long delays decrease firing. For long delays, the average firing frequency of the model response discriminates spatially clustered from diffused inputs to the distal dendritic tree. For short delays, the onset latency and inter-spike-interval succession of model responses can accurately classify input signals as temporally close or distant and spatially clustered or diffused across different stimulation protocols. These findings suggest that a CA1 pyramidal neuron may be capable of encoding and transmitting presynaptic spatiotemporal information about the activity of the entorhinal cortex-hippocampal network to higher brain regions via the selective use of either a temporal or a rate code

The molecular logic of endocannabinoid signalling

The endocannabinoids are a family of lipid messengers that engage the cell surface receptors that are targeted by Δ9-tetrahydrocannabinol, the active principle in marijuana (Cannabis). They are made on demand through cleavage of membrane precursors and are involved in various short-range signalling processes. In the brain, they combine with CB1 cannabinoid receptors on axon terminals to regulate ion channel activity and neurotransmitter release. Their ability to modulate synaptic efficacy has a wide range of functional consequences and provides unique therapeutic possibilities. © 2003, Nature Publishing Group. All rights reserved

Comparison of single NMDA receptor channels recorded on hippocampal principal cells and oriens/alveus interneurons projecting to stratum lacunosum-moleculare (O-LM cells)

NMDA receptors participate in the glutamatergic excitation of both principal cells and GABAergic interneurons. The features of NMDA channels on specific interneurons, however, are not known. Therefore, we obtained direct measurements of single NMDA receptor channels on anatomically identified oriens/alveus interneurons projecting to stratum lacunosum-moleculare (O-LM cells) and compared them to those found on hippocampal principal cells using cell-attached recordings in in vitro slice preparations. The recorded channels could be blocked by ketamine, a membrane-permeable NMDA channel inhibitor. In the absence of Mg2+, all O-LM cells had NMDA channels with a comparable slope conductance (~60pS) to those measured on CA1 pyramidal cells or dentate granule cells. In addition, NMDA channels with smaller conductance (43-45 pS) were also found on two O-LM cells but not on principal cells. These results suggest that at least two types of NMDA channels are expressed on O-LM cells likely reflecting distinct subunit composition

Synaptic currents in anatomically identified CA3 neurons during hippocampal gamma oscillations in vitro.

Gamma-frequency oscillations are prominent during active network states in the hippocampus. An intrahippocampal gamma generator has been identified in the CA3 region. To better understand the synaptic mechanisms involved in gamma oscillogenesis, we recorded action potentials and synaptic currents in distinct types of anatomically identified CA3 neurons during carbachol-induced (20-25 microM) gamma oscillations in rat hippocampal slices. We wanted to compare and contrast the relationship between excitatory and inhibitory postsynaptic currents in pyramidal cells and perisomatic-targeting interneurons, cell types implicated in gamma oscillogenesis, as well as in other interneuron subtypes, and to relate synaptic currents to the firing properties of the cells. We found that phasic synaptic input differed between cell classes. Most strikingly, the dominant phasic input to pyramidal neurons was inhibitory, whereas phase-coupled perisomatic-targeting interneurons often received a strong phasic excitatory input. Differences in synaptic input could account for some of the differences in firing rate, action potential phase precision, and mean action potential phase angle, both between individual cells and between cell types. There was a strong positive correlation between the ratio of phasic synaptic excitation to inhibition and firing rate over all neurons and between the phase precision of excitation and action potentials in interneurons. Moreover, mean action potential phase angle correlated with the phase of the peak of the net-estimated synaptic reversal potential in all phase-coupled neurons. The data support a recurrent mechanism of gamma oscillations, whereby spike timing is controlled primarily by inhibition in pyramidal cells and by excitation in interneurons