Respiratory rhythm modulates membrane potential and spiking of nonolfactory neurons.

In recent years, several studies have shown a respiratory drive of the local field potential (LFP) in numerous brain areas so that the respiratory rhythm could be considered as a master clock promoting communication between distant brain locations. However, outside of the olfactory system, it remains unknown whether the respiratory rhythm could shape membrane potential (MP) oscillations. To fill this gap, we co-recorded MP and LFP activities in different nonolfactory brain areas, medial prefrontal cortex (mPFC), primary somatosensory cortex (S1), primary visual cortex (V1), and hippocampus (HPC), in urethane-anesthetized rats. Using respiratory cycle-by-cycle analysis, we observed that respiration could modulate both MP and spiking discharges in all recorded areas during episodes that we called respiration-related oscillations (RRo). Further quantifications revealed that RRo episodes were transient in most neurons (5 consecutive respiratory cycles in average). RRo development in MP was largely correlated with the presence of respiratory modulation in the LFP. By showing that the respiratory rhythm influenced brain activities deep to the MP of nonolfactory neurons, our data support the idea that respiratory rhythm could mediate long-range communication between brain areas.NEW & NOTEWORTHY In this study, we evidenced strong respiratory-driven oscillations of neuronal membrane potential and spiking discharge in various nonolfactory areas of the mammal brain. These oscillations were found in the medial prefrontal cortex, primary somatosensory cortex, primary visual cortex, and hippocampus. These findings support the idea that respiratory rhythm could be used as a common clock to set the dynamics of large-scale neuronal networks on the same slow rhythm.

Distinct brain networks for remote episodic memory depending on content and emotional experience.

Memories of life episodes are the heart of individual stories. However, modelling episodic memory is a major challenge in both humans and animals when considering all its characteristics. As a consequence, the mechanisms that underlie the storage of old nontraumatic episodic memories remain enigmatic. Here, using a new task in rodents that models human episodic memory including odour/place/context components and applying advances behavioural and computational analyses, we show that rats form and recollect integrated remote episodic memories of two occasionally encountered complex episodes occurring in their daily life. Similar to humans, the information content and accuracy of memories vary across individuals and depend on the emotional relationship with odours experienced during the very first episode. We used cellular brain imaging and functional connectivity analyses, to find out the engrams of remote episodic memories for the first time. Activated brain networks completely reflect the nature and content of episodic memories, with a larger cortico-hippocampal network when the recollection is complete and with an emotional brain network related to odours that is critical in maintaining accurate and vivid memories. The engrams of remote episodic memories remain highly dynamic since synaptic plasticity processes occur during recall related to memory updates and reinforcement.

Afterhyperpolarization Promotes the Firing of Mitral Cells through a Voltage-Dependent Modification of Action Potential Threshold.

In the olfactory bulb, mitral cells (MCs) display a spontaneous firing that is characterized by bursts of action potentials (APs) intermixed with silent periods. Intraburst firing frequency and duration are heterogeneous among MCs and increase with membrane depolarization. By using patch-clamp recording on rat slices, we dissected out the intrinsic properties responsible for this bursting activity. We showed that the threshold of AP generation dynamically changes as a function of the preceding trajectory of the membrane potential. In fact, the AP threshold became more negative when the membrane was hyperpolarized and had a recovery rate inversely proportional to the membrane repolarization rate. Such variations appeared to be produced by changes in the inactivation state of voltage-dependent Na+ channels. Thus, AP initiation was favored by hyperpolarizing events, such as negative membrane oscillations or inhibitory synaptic input. After the first AP, the following fast afterhyperpolarization (AHP) brought the threshold to more negative values and then promoted the emission of the following AP. This phenomenon was repeated for each AP of the burst making the fast AHP a regenerative mechanism that sustained the firing, AHP with larger amplitudes and faster repolarizations being associated with larger and higher-frequency bursts. Burst termination was found to be because of the development of a slow repolarization component of the AHP (slow AHP). Overall, the AHP characteristics appeared as a major determinant of the bursting properties.

The deep and slow breathing characterizing rest favors brain respiratory-drive.

A respiration-locked activity in the olfactory brain, mainly originating in the mechano-sensitivity of olfactory sensory neurons to air pressure, propagates from the olfactory bulb to the rest of the brain. Interestingly, changes in nasal airflow rate result in reorganization of olfactory bulb response. By leveraging spontaneous variations of respiratory dynamics during natural conditions, we investigated whether respiratory drive also varies with nasal airflow movements. We analyzed local field potential activity relative to respiratory signal in various brain regions during waking and sleep states. We found that respiration regime was state-specific, and that quiet waking was the only vigilance state during which all the recorded structures can be respiration-driven whatever the respiratory frequency. Using CO2-enriched air to alter respiratory regime associated to each state and a respiratory cycle based analysis, we evidenced that the large and strong brain drive observed during quiet waking was related to an optimal trade-off between depth and duration of inspiration in the respiratory pattern, characterizing this specific state. These results show for the first time that changes in respiration regime affect cortical dynamics and that the respiratory regime associated with rest is optimal for respiration to drive the brain.

Brain-State-Dependent Modulation of Neuronal Firing and Membrane Potential Dynamics in the Somatosensory Thalamus during Natural Sleep.

The thalamus plays a central role in sleep rhythms in the mammalian brain and, yet, surprisingly little is known about its function and interaction with local cortical oscillations during NREM sleep (NREM). We investigated the neuronal correlates of cortical barrel activity in the two corresponding thalamic nuclei, the ventral posterior medial (VPM), and the posterior medial (Pom) nuclei during natural NREM in mice. Our data reveal (1) distinct modulations of VPM and Pom activity throughout NREM episodes, (2) a thalamic nucleus-specific phase-locking to cortical slow and spindle waves, (3) cell-specific subthreshold spindle oscillations in VPM neurons that only partially overlap with cortical spindles, and (4) that spindle features evolve throughout NREM episodes and vary according to the post-NREM state. Taken together, our results suggest that, during natural sleep, the barrel cortex exerts a leading role in the generation and transfer of slow rhythms to the somatosensory thalamus and reciprocally for spindle oscillations.

High beta rhythm amplitude in olfactory learning signs a well-consolidated and non-flexible behavioral state.

Beta rhythm (15-30 Hz) is a major candidate underlying long-range communication in the brain. In olfactory tasks, beta activity is strongly modulated by learning but its condition of expression and the network(s) responsible for its generation are unclear. Here we analyzed the emergence of beta activity in local field potentials recorded from olfactory, sensorimotor and limbic structures of rats performing an olfactory task. Rats performed successively simple discrimination, rule transfer, memory recall tests and contingency reversal. Beta rhythm amplitude progressively increased over learning in most recorded areas. Beta amplitude reduced to baseline when new odors were introduced, but remained high during memory recall. Intra-session analysis showed that even expert rats required several trials to reach a good performance level, with beta rhythm amplitude increasing in parallel. Notably, at the beginning of the reversal task, beta amplitude remained high while performance was low and, in all tested animals, beta amplitude decreased before rats were able to learn the new contingencies. Connectivity analysis showed that beta activity was highly coherent between all structures where it was expressed. Overall, our results suggest that beta rhythm is expressed in a highly coherent network when context learning - including both odors and reward - is consolidated and signals behavioral inflexibility.

In vivo beta and gamma subthreshold oscillations in rat mitral cells: origin and gating by respiratory dynamics.

In mammals, olfactory bulb (OB) dynamics are paced by slow and fast oscillatory rhythms at multiple levels: local field potential, spike discharge, and/or membrane potential oscillations. Interactions between these levels have been well studied for the slow rhythm linked to animal respiration. However, less is known regarding rhythms in the fast beta (10-35 Hz) and gamma (35-100 Hz) frequency ranges, particularly at the membrane potential level. Using a combination of intracellular and extracellular recordings in the OB of freely breathing rats, we show that beta and gamma subthreshold oscillations (STOs) coexist intracellularly and are related to extracellular local field potential (LFP) oscillations in the same frequency range. However, they are differentially affected by changes in cell excitability and by odor stimulation. This leads us to suggest that beta and gamma STOs may rely on distinct mechanisms: gamma STOs would mainly depend on mitral cell intrinsic resonance, while beta STOs could be mainly driven by synaptic activity. In a second study, we find that STO occurrence and timing are constrained by the influence of the slow respiratory rhythm on mitral and tufted cells. First, respiratory-driven excitation seems to favor gamma STOs, while respiratory-driven inhibition favors beta STOs. Second, the respiratory rhythm is needed at the subthreshold level to lock gamma and beta STOs in similar phases as their LFP counterparts and to favor the correlation between STO frequency and spike discharge. Overall, this study helps us to understand how the interaction between slow and fast rhythms at all levels of OB dynamics shapes its functional output. NEW & NOTEWORTHY In the mammalian olfactory bulb of a freely breathing anesthetized rat, we show that both beta and gamma membrane potential fast oscillation ranges exist in the same mitral and tufted (M/T) cell. Importantly, our results suggest they have different origins and that their interaction with the slow subthreshold oscillation (respiratory rhythm) is a key mechanism to organize their dynamics, favoring their functional implication in olfactory bulb information processing.

Competing Mechanisms of Gamma and Beta Oscillations in the Olfactory Bulb Based on Multimodal Inhibition of Mitral Cells Over a Respiratory Cycle.

Gamma (∼40-90 Hz) and beta (∼15-40 Hz) oscillations and their associated neuronal assemblies are key features of neuronal sensory processing. However, the mechanisms involved in either their interaction and/or the switch between these different regimes in most sensory systems remain misunderstood. Based on in vivo recordings and biophysical modeling of the mammalian olfactory bulb (OB), we propose a general scheme where OB internal dynamics can sustain two distinct dynamic states, each dominated by either a gamma or a beta regime. The occurrence of each regime depends on the excitability level of granule cells, the main OB interneurons. Using this model framework, we demonstrate how the balance between sensory and centrifugal input can control the switch between the two oscillatory dynamic states. In parallel, we experimentally observed that sensory and centrifugal inputs to the rat OB could both be modulated by the respiration of the animal (2-12 Hz) and each one phase shifted with the other. Implementing this phase shift in our model resulted in the appearance of the alternation between gamma and beta rhythms within a single respiratory cycle, as in our experimental results under urethane anesthesia. Our theoretical framework can also account for the oscillatory frequency response, depending on the odor intensity, the odor valence, and the animal sniffing strategy observed under various conditions including animal freely-moving. Importantly, the results of the present model can form a basis to understand how fast rhythms could be controlled by the slower sensory and centrifugal modulations linked to the respiration. Visual Abstract: See Abstract.

Afterhyperpolarization (AHP) regulates the frequency and timing of action potentials in the mitral cells of the olfactory bulb: role of olfactory experience.

Afterhyperpolarization (AHP) is a principal feedback mechanism in the control of the frequency and patterning of neuronal firing. In principal projection neurons of the olfactory bulb, the mitral cells (MCs), the AHP is produced by three separate components: classical potassium-mediated hyperpolarization, and the excitatory and inhibitory components, which are generated by the recurrent dendrodendritic synaptic transmission. Precise spike timing is involved in olfactory coding and learning, as well as in the appearance of population oscillatory activity. However, the contribution of the AHP and its components to these processes remains unknown. In this study, we demonstrate that the AHP is developed with the MC firing frequency and is dominated by the potassium component. We also show that recurrent synaptic transmission significantly modifies MC AHP and that the strength of the hyperpolarization produced by the AHP in the few milliseconds preceding the action potential (AP) emission determines MC firing frequency and AP timing. Moreover, we show that the AHP area is larger in younger animals, possibly owing to increased Ca(2+) influx during MC firing. Finally, we show that olfactory experience selectively reduces the early component of the MC AHP (under 25 msec), thus producing a modification of the AP timing limited to the higher firing frequency. On the basis of these results, we propose that the AHP, and its susceptibility to be selectively modulated by the recurrent synaptic transmission and olfactory experience, participate in odor coding and learning by modifying the frequency and pattern of MC firing.

Two distinct olfactory bulb sublaminar networks involved in gamma and beta oscillation generation: a CSD study in the anesthetized rat.

A prominent feature of olfactory bulb (OB) dynamics is the expression of characteristic local field potential (LFP) rhythms, including a slow respiration-related rhythm and two fast alternating oscillatory rhythms, beta (15-30 Hz) and gamma (40-90 Hz). All of these rhythms are implicated in olfactory coding. Fast oscillatory rhythms are known to involve the mitral-granule cell loop. Although the underlying mechanisms of gamma oscillation have been studied, the origin of beta oscillation remains poorly understood. Whether these two different rhythms share the same underlying mechanism is unknown. This study uses a quantitative and detailed current-source density (CSD) analysis combined with multi-unit activity (MUA) recordings to shed light on this question in freely breathing anesthetized rats. In particular, we show that gamma oscillation generation involves mainly the upper half of the external plexiform layer (EPL) and superficial areas of granule cell layer (GRL). In contrast, the generation of beta oscillation involves the lower part of the EPL and deep granule cells. This differential involvement of sublaminar networks is neither dependent on odor quality nor on the precise frequency of the fast oscillation under study. Overall, this study demonstrates a functional sublaminar organization of the rat OB, which is supported by previous anatomical findings.

Insulin modulates network activity in olfactory bulb slices: impact on odour processing.

Odour perception depends closely on nutritional status, in animals as in humans. Insulin, the principal anorectic hormone, appears to be one of the major candidates for ensuring the link between olfactory abilities and nutritional status, by modifying processing in the olfactory bulb (OB), one of its main central targets. The present study investigates whether and how insulin can act in OB, by evaluating its action on the main output neurons activities, mitral cells (MCs), in acute rat OB slices. Insulin was found to act at two OB network levels: (1) on MCs, by increasing their excitability, probably by inhibiting two voltage-gated potassium (K(+)) channels; (2) on interneurons by modifying the GABAergic and on glutamatergic synaptic activity impinging on MCs, mainly reducing them. Insulin also altered the olfactory nerve (ON)-evoked excitatory postsynaptic currents in 60% of MCs. Insulin decreased or increased the ON-evoked responses in equal proportion and the direction of its effect depended on the initial neuron ON-evoked firing rate. Indeed, insulin tended to decrease the high and to increase the low ON-evoked firing rates, thereby reducing inter-MC response firing variability. Therefore, the effects of insulin on the evoked firing rates were not carried out indiscriminately in the MC population. By constructing a mathematical model, the impact of insulin complex effects on OB was assessed at the population activity level. The model shows that the reduction of variability across cells could affect MC detection and discrimination abilities, mainly by decreasing and, less frequently, increasing them, depending on odour quality. Thus, as previously proposed, this differential action of insulin on MCs across odours would allow this hormone to put the olfactory function under feeding signal control, given the discerning valence of an odour as a function of nutritional status.

The relationship between respiration-related membrane potential slow oscillations and discharge patterns in mitral/tufted cells: what are the rules?

BACKGROUND: A slow respiration-related rhythm strongly shapes the activity of the olfactory bulb. This rhythm appears as a slow oscillation that is detectable in the membrane potential, the respiration-related spike discharge of the mitral/tufted cells and the bulbar local field potential. Here, we investigated the rules that govern the manifestation of membrane potential slow oscillations (MPSOs) and respiration-related discharge activities under various afferent input conditions and cellular excitability states. METHODOLOGY AND PRINCIPAL FINDINGS: We recorded the intracellular membrane potential signals in the mitral/tufted cells of freely breathing anesthetized rats. We first demonstrated the existence of multiple types of MPSOs, which were influenced by odor stimulation and discharge activity patterns. Complementary studies using changes in the intracellular excitability state and a computational model of the mitral cell demonstrated that slow oscillations in the mitral/tufted cell membrane potential were also modulated by the intracellular excitability state, whereas the respiration-related spike activity primarily reflected the afferent input. Based on our data regarding MPSOs and spike patterns, we found that cells exhibiting an unsynchronized discharge pattern never exhibited an MPSO. In contrast, cells with a respiration-synchronized discharge pattern always exhibited an MPSO. In addition, we demonstrated that the association between spike patterns and MPSO types appeared complex. CONCLUSION: We propose that both the intracellular excitability state and input strength underlie specific MPSOs, which, in turn, constrain the types of spike patterns exhibited.

Individual and synergistic effects of sniffing frequency and flow rate on olfactory bulb activity.

Is faster or stronger sniffing important for the olfactory system? Odorant molecules are captured by sniffing. The features of sniffing constrain both the temporality and intensity of the input to the olfactory structures. In this context, it is clear that variations in both the sniff frequency and flow rate have a major impact on the activation of olfactory structures. However, the question of how frequency and flow rate individually or synergistically impact bulbar output has not been answered. We have addressed this question using multiple experimental approaches. In double-tracheotomized, anesthetized rats, we recorded both the bulbar local field potential (LFP) and mitral/tufted cells' activities when the sampling flow rate and frequency were controlled independently. We found that a tradeoff between the sampling frequency and the flow rate could maintain olfactory bulb sampling-related rhythmicity and that only an increase in flow rate could induce a faster, odor-evoked response. LFP and sniffing were recorded in awake rats. We found that sampling-related rhythmicity was maintained during high-frequency sniffing. Furthermore, we observed that the covariation between the frequency and flow rate, which was necessary for the tradeoff seen in the anesthetized preparations, also occurred in awake animals. Our study shows that the sampling frequency and flow rate can act either independently or synergistically on bulbar output to shape the neuronal message. The system likely takes advantage of this flexibility to adapt sniffing strategies to animal behavior. Our study provides additional support for the idea that sniffing and olfaction function in an integrated manner.

Stability of fast oscillations in the mammalian olfactory bulb: experiments and modeling.

In the rat olfactory bulb (OB), fast oscillations of the local field potential (LFP) are observed during the respiratory cycle. Gamma-range oscillations (40-90 Hz) occur at the end of inspiration, followed by beta-range oscillations (15-30 Hz) during exhalation. These oscillations are highly stereotypical, and their frequencies are stable under various conditions. In this study, we investigate the effect of stimulus intensity on activity in the OB. Using a double-cannulation protocol, we showed that although the frequency of the LFP oscillation does depend on the respiratory cycle phase, it is relatively independent of the intensity of odorant stimulation. In contrast, we found that the individual firing rate of mitral OB cells dramatically changed with the intensity of the stimulation. This suggests that OB fast oscillation parameters, particularly frequency, are fully determined by intrinsic OB network parameters. To test this hypothesis, we explored a model of the OB where fast oscillations are generated by the interplay between excitatory mitral/tufted cells and inhibitory granule cells with graded inhibition. We found that our model has two distinct activity regimes depending on the amount of noise. In a low-noise regime, the model displays oscillation in the beta range with a stable frequency across a wide range of excitatory inputs. In a high-noise regime, the model displays oscillatory dynamics with irregular cell discharges and fast oscillations, similar to what is observed during gamma oscillations but without stability of the oscillation frequency with respect to the network external input. Simulations of the full model and theoretical studies of the network's linear response show that the characteristics of the low-noise regime are induced by non-linearities in the model, notably, the saturation of graded inhibition. Finally, we discuss how this model can account for the experimentally observed stability of the oscillatory regimes.

Specific entrainment of mitral cells during gamma oscillation in the rat olfactory bulb.

Local field potential (LFP) oscillations are often accompanied by synchronization of activity within a widespread cerebral area. Thus, the LFP and neuronal coherence appear to be the result of a common mechanism that underlies neuronal assembly formation. We used the olfactory bulb as a model to investigate: (1) the extent to which unitary dynamics and LFP oscillations can be correlated and (2) the precision with which a model of the hypothesized underlying mechanisms can accurately explain the experimental data. For this purpose, we analyzed simultaneous recordings of mitral cell (MC) activity and LFPs in anesthetized and freely breathing rats in response to odorant stimulation. Spike trains were found to be phase-locked to the gamma oscillation at specific firing rates and to form odor-specific temporal patterns. The use of a conductance-based MC model driven by an approximately balanced excitatory-inhibitory input conductance and a relatively small inhibitory conductance that oscillated at the gamma frequency allowed us to provide one explanation of the experimental data via a mode-locking mechanism. This work sheds light on the way network and intrinsic MC properties participate in the locking of MCs to the gamma oscillation in a realistic physiological context and may result in a particular time-locked assembly. Finally, we discuss how a self-synchronization process with such entrainment properties can explain, under experimental conditions: (1) why the gamma bursts emerge transiently with a maximal amplitude position relative to the stimulus time course; (2) why the oscillations are prominent at a specific gamma frequency; and (3) why the oscillation amplitude depends on specific stimulus properties. We also discuss information processing and functional consequences derived from this mechanism.

OpenElectrophy: An Electrophysiological Data- and Analysis-Sharing Framework.

Progress in experimental tools and design is allowing the acquisition of increasingly large datasets. Storage, manipulation and efficient analyses of such large amounts of data is now a primary issue. We present OpenElectrophy, an electrophysiological data- and analysis-sharing framework developed to fill this niche. It stores all experiment data and meta-data in a single central MySQL database, and provides a graphic user interface to visualize and explore the data, and a library of functions for user analysis scripting in Python. It implements multiple spike-sorting methods, and oscillation detection based on the ridge extraction methods due to Roux et al. (2007). OpenElectrophy is open source and is freely available for download at http://neuralensemble.org/trac/OpenElectrophy.

Correlation-induced synchronization of oscillations in olfactory bulb neurons.

Oscillations are a common feature of odor-evoked and spontaneous activity in the olfactory system in vivo and in vitro and are thought to play an important role in information processing and memory in a variety of brain areas. Theoretical and experimental studies have described several mechanisms by which oscillations can be generated and synchronized. Here, we investigate the hypothesis that correlated noisy inputs are able to generate synchronous oscillations in olfactory bulb mitral cells in vitro. We consider several alternative mechanisms and conclude that olfactory bulb synchronous oscillations are likely to arise because of the response of uncoupled oscillating neurons to aperiodic but correlated inputs. This mechanism has been described theoretically, but we provide the first experimental evidence that such a mechanism may underlie synchronization in real neurons. In physiological experiments, we show that this mechanism can generate gamma-band oscillations in populations of olfactory bulb mitral cells. This mechanism synchronizes oscillatory firing by using shared fast fluctuations in stochastic inputs across neurons, without requiring any synaptic or electrical coupling. We discuss the properties and limitations of synchronization by this mechanism and suggest that it may underlie fast oscillations in many brain areas.

Dynamics of the instantaneous firing rate in response to changes in input statistics.

We review and extend recent results on the instantaneous firing rate dynamics of simplified models of spiking neurons in response to noisy current inputs. It has been shown recently that the response of the instantaneous firing rate to small amplitude oscillations in the mean inputs depends in the large frequency limit f on the spike initiation dynamics. A particular simplified model, the exponential integrate-and-fire (EIF) model, has a response that decays as 1/f in the large frequency limit and describes very well the response of conductance-based models with a Hodgkin-Huxley type fast sodium current. Here, we show that the response of the EIF instantaneous firing rate also decays as 1/f in the case of an oscillation in the variance of the inputs for both white and colored noise. We then compute the initial transient response of the firing rate of the EIF model to a step change in its mean inputs and/or in the variance of its inputs. We show that in both cases the response speed is proportional to the neuron stationary firing rate and inversely proportional to a 'spike slope factor' Delta(T) that controls the sharpness of spike initiation: as 1/Delta(T) for a step change in mean inputs, and as 1/Delta(T) (2) for a step change in the variance in the inputs.

How spike generation mechanisms determine the neuronal response to fluctuating inputs.

This study examines the ability of neurons to track temporally varying inputs, namely by investigating how the instantaneous firing rate of a neuron is modulated by a noisy input with a small sinusoidal component with frequency (f). Using numerical simulations of conductance-based neurons and analytical calculations of one-variable nonlinear integrate-and-fire neurons, we characterized the dependence of this modulation on f. For sufficiently high noise, the neuron acts as a low-pass filter. The modulation amplitude is approximately constant for frequencies up to a cutoff frequency, fc, after which it decays. The cutoff frequency increases almost linearly with the firing rate. For higher frequencies, the modulation amplitude decays as C/falpha, where the power alpha depends on the spike initiation mechanism. For conductance-based models, alpha = 1, and the prefactor C depends solely on the average firing rate and a spike "slope factor," which determines the sharpness of the spike initiation. These results are attributable to the fact that near threshold, the sodium activation variable can be approximated by an exponential function. Using this feature, we propose a simplified one-variable model, the "exponential integrate-and-fire neuron," as an approximation of a conductance-based model. We show that this model reproduces the dynamics of a simple conductance-based model extremely well. Our study shows how an intrinsic neuronal property (the characteristics of fast sodium channels) determines the speed with which neurons can track changes in input.