A wavelet-based method for local phase extraction from a multi-frequency oscillatory signal

Cell and circuit origins of fast network oscillations in the mammalian main olfactory bulb

Neural synchrony generates fast network oscillations throughout the brain, including the main olfactory bulb (MOB), the first processing station of the olfactory system. Identifying the mechanisms synchronizing neurons in the MOB will be key to understanding how network oscillations support the coding of a high-dimensional sensory space. Here, using paired recordings and optogenetic activation of glomerular sensory inputs in MOB slices, we uncovered profound differences in principal mitral cell (MC) vs. tufted cell (TC) spike-time synchrony: TCs robustly synchronized across fast- and slow-gamma frequencies, while MC synchrony was weaker and concentrated in slow-gamma frequencies. Synchrony among both cell types was enhanced by shared glomerular input but was independent of intraglomerular lateral excitation. Cell-type differences in synchrony could also not be traced to any difference in the synchronization of synaptic inhibition. Instead, greater TC than MC synchrony paralleled the more periodic firing among resonant TCs than MCs and emerged in patterns consistent with densely synchronous network oscillations. Collectively, our results thus reveal a mechanism for parallel processing of sensory information in the MOB via differential TC vs. MC synchrony, and further contrast mechanisms driving fast network oscillations in the MOB from those driving the sparse synchronization of irregularly firing principal cells throughout cortex.

Real-Time Implementation of EEG Oscillatory Phase-Informed Visual Stimulation Using a Least Mean Square-Based AR Model

It is a technically challenging problem to assess the instantaneous brain state using electroencephalography (EEG) in a real-time closed-loop setup because the prediction of future signals is required to define the current state, such as the instantaneous phase and amplitude. To accomplish this in real-time, a conventional Yule–Walker (YW)-based autoregressive (AR) model has been used. However, the brain state-dependent real-time implementation of a closed-loop system employing an adaptive method has not yet been explored. Our primary purpose was to investigate whether time-series forward prediction using an adaptive least mean square (LMS)-based AR model would be implementable in a real-time closed-loop system or not. EEG state-dependent triggers synchronized with the EEG peaks and troughs of alpha oscillations in both an open-eyes resting state and a visual task. For the resting and visual conditions, statistical results showed that the proposed method succeeded in giving triggers at a specific phase of EEG oscillations for all participants. These individual results showed that the LMS-based AR model was successfully implemented in a real-time closed-loop system targeting specific phases of alpha oscillations and can be used as an adaptive alternative to the conventional and machine-learning approaches with a low computational load.

Time-Series Prediction of the Oscillatory Phase of EEG Signals Using the Least Mean Square Algorithm-Based AR Model

Neural oscillations are vital for the functioning of a central nervous system because they assist in brain communication across a huge network of neurons. Alpha frequency oscillations are believed to depict idling or inhibition of task-irrelevant cortical activities. However, recent studies on alpha oscillations (particularly alpha phase) hypothesize that they have an active and direct role in the mechanisms of attention and working memory. To understand the role of alpha oscillations in several cognitive processes, accurate estimations of phase, amplitude, and frequency are required. Herein, we propose an approach for time-series forward prediction by comparing an autoregressive (AR) model and an adaptive method (least mean square (LMS)-based AR model). This study tested both methods for two prediction lengths of data. Our results indicate that for shorter data segments (prediction of 128 ms), the AR model outperforms the LMS-based AR model, while for longer prediction lengths (256 ms), the LMS- based AR model surpasses the AR model. LMS with low computational cost can aid in electroencephalography (EEG) phase prediction (alpha oscillations) in basic research to reveal the functional role of the oscillatory phase as well as for applications for brain-computer interfaces.

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.

New Insights from 22-kHz Ultrasonic Vocalizations to Characterize Fear Responses: Relationship with Respiration and Brain Oscillatory Dynamics

Fear behavior depends on interactions between the medial prefrontal cortex (mPFC) and the basolateral amygdala (BLA), and the expression of fear involves synchronized activity in θ and γ oscillatory activities. In addition, freezing, the most classical measure of fear response in rodents, temporally coincides with the development of sustained 4-Hz oscillations in prefrontal-amygdala circuits. Interestingly, these oscillations were recently shown to depend on the animal’s respiratory rhythm, supporting the growing body of evidence pinpointing the influence of nasal breathing on brain rhythms. During fearful states, rats also emit 22-kHz ultrasonic vocalizations (USVs) which drastically affect respiratory rhythm. However, the relationship between 22-kHz USV, respiration, and brain oscillatory activities is still unknown. Yet such information is crucial for a comprehensive understanding of how the different components of fear response collectively modulate rat’s brain neural dynamics. Here, we trained male rats in an odor fear conditioning task, while recording simultaneously local field potentials (LFPs) in BLA, mPFC, and olfactory piriform cortex (PIR), together with USV calls and respiration. We show that USV calls coincide with an increase in delta and gamma power and a decrease in theta power. In addition, during USV emission in contrast to silent freezing, there is no coupling between respiratory rate and delta frequency, and the modulation of fast oscillations amplitude relative to the phase of respiration is modified. We propose that sequences of USV calls could result in a differential gating of information within the network of structures sustaining fear behavior, thus potentially modulating fear expression/memory.

Odorant features differentially modulate beta/gamma oscillatory patterns in anterior versus posterior piriform cortex

Oscillatory activity is a prominent characteristic of the olfactory system. We previously demonstrated that beta and gamma oscillations occurrence in the olfactory bulb (OB) is modulated by the physical properties of the odorant. However, it remains unknown whether such odor-related modulation of oscillatory patterns is maintained in the piriform cortex (PC) and whether those patterns are similar between the anterior PC (aPC) and posterior PC (pPC). The present study was designed to analyze how different odorant molecular features can affect the local field potential (LFP) oscillatory signals in both the aPC and the pPC in anesthetized rats. As reported in the OB, three oscillatory patterns were observed: standard pattern (gamma + beta), gamma-only and beta-only patterns. These patterns occurred with significantly different probabilities in the two PC areas. We observed that odor identity has a strong influence on the probability of occurrence of LFP beta and gamma oscillatory activity in the aPC. Thus, some odor coding mechanisms observed in the OB are retained in the aPC. By contrast, probability of occurrence of different oscillatory patterns is homogeneous in the pPC with beta-only pattern being the most prevalent one for all the different odor families. Overall, our results confirmed the functional heterogeneity of the PC with its anterior part tightly coupled with the OB and mainly encoding odorant features whereas its posterior part activity is not correlated with odorant features but probably more involved in associative and multi-sensory encoding functions.

Noise-Assisted Multivariate EMD-Based Mean-Phase Coherence Analysis to Evaluate Phase-Synchrony Dynamics in Epilepsy Patients

Spatiotemporal evolution of synchrony dynamics among neuronal populations plays an important role in decoding complicated brain function in normal cognitive processing as well as during pathological conditions such as epileptic seizures. In this paper, a non-linear analytical methodology is proposed to quantitatively evaluate the phase-synchrony dynamics in epilepsy patients. A set of finite neuronal oscillators was adaptively extracted from a multi-channel electrocorticographic (ECoG) dataset utilizing noise-assisted multivariate empirical mode de-composition (NA-MEMD). Next, the instantaneous phases of the oscillatory functions were extracted using the Hilbert transform in order to be utilized in the mean-phase coherence analysis. The phase-synchrony dynamics were then assessed using eigenvalue decomposition. The extracted neuronal oscillators were grouped with respect to their frequency range into wideband (1-600 Hz), ripple (80-250 Hz), and fast-ripple (250-600 Hz) bands in order to investigate the dynamics of ECoG activity in these frequency ranges as seizures evolve. Drug-refractory patients with frontal and temporal lobe epilepsy demonstrated a reduction in phase-synchrony around seizure onset. However, the network phase-synchrony started to increase toward seizure end and achieved its maximum level at seizure offset for both types of epilepsy. This result suggests that hyper-synchronization of the epileptic network may be an essential self-regulatory mechanism by which the brain terminates seizures.

Current Source Density Analysis of Electroantennogram Recordings: A Tool for Mapping the Olfactory Response in an Insect Antenna

The set of chemosensory receptors expressed by the olfactory receptor neurons lying in an insect's antennae and maxillary palps define the ability of this insect to perceive the volatile chemicals of its environment. The main two electrophysiological methods of antennal recordings for studying the range of chemicals that activate chemosensory receptors have limitations. Single-sensillum recording (SSR) samples a subset of olfactory receptor neurons and therefore does not reveal the full capacity of an insect to perceive an odor. Electroantennography (EAG), even if less resolutive than SSRs, is sometimes preferred since it samples the activity of a large number of the olfactory receptor neurons. But, at least in flies, the amplitude of the EAG signal is not directly correlated with the degree of sensitivity of the insect to the olfactory compound. Such dual methodology was also used to study mammalian brains, and the current source density (CSD) analysis was developed to bridge the gap between the cellular and the population recordings. This paper details the use of a similar approach adapted to the study of olfactory responses within insects with bulbous antennae. The EAG was recorded at multiple antennal positions and the CSD that generates the EAG potentials were estimated. The method measures the activation of olfactory receptor neurons (ORNs) across the antennae and thus it quantifies the olfactory sensitivity of the insect. It allows a rapid mapping of olfactory responses and thus can be used to guide further SSRs or to determine that two chemicals are detected by independent ORNs. This study further explored biases resulting from a limited number of recording positions or from an approximation of the antennal geometry that should be considered for interpreting the CSD maps. It also shows that the CSD analysis of EAGs is compatible with a gas chromatograph stimulator for analyzing the response to complex odors. Finally, I discuss the origin of the EAG signal in light of the CSD theory.

Assessment of Multivariate Neural Time Series by Phase Synchrony Clustering in a Time-Frequency-Topography Representation

Most EEG phase synchrony measures are of bivariate nature. Those that are multivariate focus on producing global indices of the synchronization state of the system. Thus, better descriptions of spatial and temporal local interactions are still in demand. A framework for characterization of phase synchrony relationships between multivariate neural time series is presented, applied either in a single epoch or over an intertrial assessment, relying on a proposed clustering algorithm, termed Multivariate Time Series Clustering by Phase Synchrony, which generates fuzzy clusters for each multivalued time sample and thereupon obtains hard clusters according to a circular variance threshold; such cluster modes are then depicted in Time-Frequency-Topography representations of synchrony state beyond mere global indices. EEG signals from P300 Speller sessions of four subjects were analyzed, obtaining useful insights of synchrony patterns related to the ERP and even revealing steady-state artifacts at 7.6 Hz. Further, contrast maps of Levenshtein Distance highlight synchrony differences between ERP and no-ERP epochs, mainly at delta and theta bands. The framework, which is not limited to one synchrony measure, allows observing dynamics of phase changes and interactions among channels and can be applied to analyze other cognitive states rather than ERP versus no ERP.

Neuronal dynamics supporting formation and recombination of cross-modal olfactory-tactile association in the rat hippocampal formation

The present study is aimed at describing some aspects of the neural dynamics supporting discrimination of olfactory-tactile paired-associated stimuli during acquisition of new pairs and during recombination of previously learned pairs in the rat. To solve the task, animals have to identify one odor-texture (OT) combination associated with a food reward among three cups with overlapping elements. Previous experiments demonstrated that the lateral entorhinal cortex (LEC) is involved in the processes underlying OT acquisition, whereas the dorsal hippocampus (DH) is selectively involved in the recombination processes. In the present study, local field potentials were recorded form the anterior piriform cortex (aPC), LEC, and DH in freely moving rats performing these tasks. Signal analysis focused on theta (5-12 Hz)- and beta-band (15-40 Hz) oscillatory activities in terms of both amplitude and synchrony. The results show that cue sampling was associated with a significant increase in the beta-band activity during the choice period in both the aPC and the LEC, and is modulated by level of expertise and the animal's decision. In addition, this increase was significantly higher during the recombination compared with the acquisition of the OT task, specifically when animals had to neglect the odor previously associated with the reward. Finally, a significant decrease in coherence in the theta band between LEC and DH was observed in the recombination but not in the acquisition task. These data point to specific neural signatures of simple and complex cross-modal sensory processing in the LEC-DH complex. NEW & NOTEWORTHY This study is the first to describe electrophysiological correlates of cross-modal olfactory-tactile integration in rats. Recordings were sought from the lateral entorhinal cortex and the dorsal hippocampus because previous studies have shown their role in the formation and in the recombination of previously learned associations. We identified specific oscillatory-evoked neural responses in these structures in the theta and beta bands, which characterize acquisition and recombination of cross-modal olfactory-tactile pairs.

Duration analysis using matching pursuit algorithm reveals longer bouts of gamma rhythm

The gamma rhythm (30–80 Hz), often associated with high-level cortical functions, is believed to provide a temporal reference frame for spiking activity, for which it should have a stable center frequency and linear phase for an extended duration. However, recent studies that have estimated the power and phase of gamma as a function of time suggest that gamma occurs in short bursts and lacks the temporal structure required to act as a reference frame. Here, we show that the bursty appearance of gamma arises from the variability in the spectral estimator used in these studies. To overcome this problem, we use another duration estimator based on a matching pursuit algorithm that robustly estimates the duration of gamma in simulated data. Applying this algorithm to gamma oscillations recorded from implanted microelectrodes in the primary visual cortex of awake monkeys, we show that the median gamma duration is greater than 300 ms, which is three times longer than previously reported values.

NEW & NOTEWORTHY Gamma oscillations (30–80 Hz) have been hypothesized to provide a temporal reference frame for coordination of spiking activity, but recent studies have shown that gamma occurs in very short bursts. We show that existing techniques have severely underestimated the rhythm duration, use a technique based on the Matching Pursuit algorithm, which provides a robust estimate of the duration, and show that the median duration of gamma is greater than 300 ms, much longer than previous estimates.

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.

Odor-Induced Neuronal Rhythms in the Olfactory Bulb Are Profoundly Modified in ob/ob Obese Mice

Leptin, the product of the Ob(Lep) gene, is a peptide hormone that plays a major role in maintaining the balance between food intake and energy expenditure. In the brain, leptin receptors are expressed by hypothalamic cells but also in the olfactory bulb, the first central structure coding for odors, suggesting a precise function of this hormone in odor-evoked activities. Although olfaction plays a key role in feeding behavior, the ability of the olfactory bulb to integrate the energy-related signal leptin is still missing. Therefore, we studied the fate of odor-induced activity in the olfactory bulb in the genetic context of leptin deficiency using the obese ob/ob mice. By means of an odor discrimination task with concomitant local field potential recordings, we showed that ob/ob mice perform better than wild-type (WT) mice in the early stage of the task. This behavioral gain of function was associated in parallel with profound changes in neuronal oscillations in the olfactory bulb. The distribution of the peaks in the gamma frequency range was shifted toward higher frequencies in ob/ob mice compared to WT mice before learning. More notably, beta oscillatory activity, which has been shown previously to be correlated with olfactory discrimination learning, was longer and stronger in expert ob/ob mice after learning. Since oscillations in the olfactory bulb emerge from mitral to granule cell interactions, our results suggest that cellular dynamics in the olfactory bulb are deeply modified in ob/ob mice in the context of olfactory learning.

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.

Regular theta-firing neurons in the nucleus incertus during sustained hippocampal activation

This paper describes the existence of theta-coupled neuronal activity in the nucleus incertus (NI). Theta rhythm is relevant for cognitive processes such as spatial navigation and memory processing, and can be recorded in a number of structures related to the hippocampal activation including the NI. Strong evidence supports the role of this tegmental nucleus in neural circuits integrating behavioural activation with the hippocampal theta rhythm. Theta oscillations have been recorded in the local field potential of the NI, highly coupled to the hippocampal waves, although no rhythmical activity has been reported in neurons of this nucleus. The present work analyses the neuronal activity in the NI in conditions leading to sustained hippocampal theta in the urethane-anaesthetised rat, in order to test whether such activation elicits a differential firing pattern. Wavelet analysis has been used to better define the neuronal activity already described in the nucleus, i.e., non-rhythmical neurons firing at theta frequency (type I neurons) and fast-firing rhythmical neurons (type II). However, the most remarkable finding was that sustained stimulation activated regular-theta neurons (type III), which were almost silent in baseline conditions and have not previously been reported. Thus, we describe the electrophysiological properties of type III neurons, focusing on their coupling to the hippocampal theta. Their spike rate, regularity and phase locking to the oscillations increased at the beginning of the stimulation, suggesting a role in the activation or reset of the oscillation. Further research is needed to address the specific contribution of these neurons to the entire circuit.

Large-scale, high-resolution multielectrode-array recording depicts functional network differences of cortical and hippocampal cultures

Understanding the detailed circuitry of functioning neuronal networks is one of the major goals of neuroscience. Recent improvements in neuronal recording techniques have made it possible to record the spiking activity from hundreds of neurons simultaneously with sub-millisecond temporal resolution. Here we used a 512-channel multielectrode array system to record the activity from hundreds of neurons in organotypic cultures of cortico-hippocampal brain slices from mice. To probe the network structure, we employed a wavelet transform of the cross-correlogram to categorize the functional connectivity in different frequency ranges. With this method we directly compare, for the first time, in any preparation, the neuronal network structures of cortex and hippocampus, on the scale of hundreds of neurons, with sub-millisecond time resolution. Among the three frequency ranges that we investigated, the lower two frequency ranges (gamma (30–80 Hz) and beta (12–30 Hz) range) showed similar network structure between cortex and hippocampus, but there were many significant differences between these structures in the high frequency range (100–1000 Hz). The high frequency networks in cortex showed short tailed degree-distributions, shorter decay length of connectivity density, smaller clustering coefficients, and positive assortativity. Our results suggest that our method can characterize frequency dependent differences of network architecture from different brain regions. Crucially, because these differences between brain regions require millisecond temporal scales to be observed and characterized, these results underscore the importance of high temporal resolution recordings for the understanding of functional networks in neuronal systems.

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.

Investigating local and long-range neuronal network dynamics by simultaneous optogenetics, reverse microdialysis and silicon probe recordings in vivo

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Optogenetics and microdialysis can be successfully combined.

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How to manipulate circuits of spontaneous and evoked activities with drugs and lights?

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Thalamic control of delta waves and sleep spindles.

Background

The advent of optogenetics has given neuroscientists the opportunity to excite or inhibit neuronal population activity with high temporal resolution and cellular selectivity. Thus, when combined with recordings of neuronal ensemble activity in freely moving animals optogenetics can provide an unprecedented snapshot of the contribution of neuronal assemblies to (patho)physiological conditions in vivo. Still, the combination of optogenetic and silicone probe (or tetrode) recordings does not allow investigation of the role played by voltage- and transmitter-gated channels of the opsin-transfected neurons and/or other adjacent neurons in controlling neuronal activity.

New method and results

We demonstrate that optogenetics and silicone probe recordings can be combined with intracerebral reverse microdialysis for the long-term delivery of neuroactive drugs around the optic fiber and silicone probe. In particular, we show the effect of antagonists of T-type Ca²⁺ channels, hyperpolarization-activated cyclic nucleotide-gated channels and metabotropic glutamate receptors on silicone probe-recorded activity of the local opsin-transfected neurons in the ventrobasal thalamus, and demonstrate the changes that the block of these thalamic channels/receptors brings about in the network dynamics of distant somatotopic cortical neuronal ensembles.

Comparison with existing methods

This is the first demonstration of successfully combining optogenetics and neuronal ensemble recordings with reverse microdialysis. This combination of techniques overcomes some of the disadvantages that are associated with the use of intracerebral injection of a drug-containing solution at the site of laser activation.

Conclusions

The combination of reverse microdialysis, silicone probe recordings and optogenetics can unravel the short and long-term effects of specific transmitter- and voltage-gated channels on laser-modulated firing at the site of optogenetic stimulation and the actions that these manipulations exert on distant neuronal populations.

Quantifying spatiotemporal properties of vocal fold dynamics based on a multiscale analysis of phonovibrograms

In order to objectively assess the laryngeal vibratory behavior, endoscopic high-speed cameras capture several thousand frames per second of the vocal folds during phonation. However, judging all inherent clinically relevant features is a challenging task and requires well-founded expert knowledge. In this study, an automated wavelet-based analysis of laryngeal high-speed videos based on phonovibrograms is presented. The phonovibrogram is an image representation of the spatiotemporal pattern of vocal fold vibration and constitutes the basis for a computer-based analysis of laryngeal dynamics. The features extracted from the wavelet transform are shown to be closely related to a basic set of video-based measurements categorized by the European Laryngological Society for a subjective assessment of pathologic voices. The wavelet-based analysis further offers information about irregularity and lateral asymmetry and asynchrony. It is demonstrated in healthy and pathologic subjects as well as for a surgical group that was examined before and after the removal of a vocal fold polyp. The features were found to not only classify glottal closure characteristics but also quantify the impact of pathologies on the vibratory behavior. The interpretability and the discriminative power of the proposed feature set show promising relevance for a computer-assisted diagnosis and classification of voice disorders.

Odor- and state-dependent olfactory tubercle local field potential dynamics in awake rats

The olfactory tubercle (OT), a trilaminar structure located in the basal forebrain of mammals, is thought to play an important role in olfaction. While evidence has accumulated regarding the contributions of the OT to odor information processing, studies exploring the role of the OT in olfaction in awake animals remain unavailable. In the present study, we begin to address this void through multiday recordings of local field potential (LFP) activity within the OT of awake, freely exploring Long-Evans rats. We observed spontaneous OT LFP activity consisting of theta- (2-12 Hz), beta- (15-35 Hz) and gamma- (40-80 Hz) band activity, characteristic of previous reports of LFPs in other principle olfactory structures. Beta- and gamma-band powers were enhanced upon odor presentation. Simultaneous recordings of OT and upstream olfactory bulb (OB) LFPs revealed odor-evoked LFP power at statistically similar levels in both structures. Strong spectral coherence was observed between the OT and OB during both spontaneous and odor-evoked states. Furthermore, the OB theta rhythm more strongly cohered with the respiratory rhythm, and respiratory-coupled theta cycles in the OT occurred following theta cycles in the OB. Finally, we found that the animal's internal state modulated LFP activity in the OT. Together, these data provide initial insights into the network activity of the OT in the awake rat, including spontaneous rhythmicity, odor-evoked modulation, connectivity with upstream sensory input, and state-dependent modulation.

Essential thalamic contribution to slow waves of natural sleep

Slow waves represent one of the prominent EEG signatures of non-rapid eye movement (non-REM) sleep and are thought to play an important role in the cellular and network plasticity that occurs during this behavioral state. These slow waves of natural sleep are currently considered to be exclusively generated by intrinsic and synaptic mechanisms within neocortical territories, although a role for the thalamus in this key physiological rhythm has been suggested but never demonstrated. Combining neuronal ensemble recordings, microdialysis, and optogenetics, here we show that the block of the thalamic output to the neocortex markedly (up to 50%) decreases the frequency of slow waves recorded during non-REM sleep in freely moving, naturally sleeping-waking rats. A smaller volume of thalamic inactivation than during sleep is required for observing similar effects on EEG slow waves recorded during anesthesia, a condition in which both bursts and single action potentials of thalamocortical neurons are almost exclusively dependent on T-type calcium channels. Thalamic inactivation more strongly reduces spindles than slow waves during both anesthesia and natural sleep. Moreover, selective excitation of thalamocortical neurons strongly entrains EEG slow waves in a narrow frequency band (0.75-1.5 Hz) only when thalamic T-type calcium channels are functionally active. These results demonstrate that the thalamus finely tunes the frequency of slow waves during non-REM sleep and anesthesia, and thus provide the first conclusive evidence that a dynamic interplay of the neocortical and thalamic oscillators of slow waves is required for the full expression of this key physiological EEG rhythm.

Anesthetic regimes modulate the temporal dynamics of local field potential in the mouse olfactory bulb

Anesthetized preparations have been widely used to study odor-induced temporal dynamics in the olfactory bulb. Although numerous recent data of single-cell recording or imaging in the olfactory bulb have employed ketamine cocktails, their effects on networks activities are still poorly understood, and odor-induced oscillations of the local field potential have not been characterized under these anesthetics. Our study aimed at describing the impact of two ketamine cocktails on oscillations and comparing them to awake condition. Anesthesia was induced by injection of a cocktail of ketamine, an antagonist of the N-methyl-d-aspartate receptors, combined with one agonist of α2-adrenergic receptors, xylazine (low affinity) or medetomidine (high affinity). Spontaneous and odor-induced activities were examined in anesthetized and awake conditions, in the same mice chronically implanted with an electrode in the main olfactory bulb. The overall dynamic pattern of oscillations under the two ketamine cocktails resembles that of the awake state. Ongoing activity is characterized by gamma bursts (>60 Hz) locked on respiration and beta (15-40 Hz) power increases during odor stimulation. However, anesthesia decreases local field potential power and leads to a strong frequency shift of gamma oscillations from 60-90 Hz to 100-130 Hz. We conclude that similarities between oscillations in anesthetized and awake states make cocktails of ketamine with one α2-agonist suitable for the recordings of local field potential to study processing in the early stages of the olfactory system.

Modulations of EEG beta power during planning and execution of grasping movements

Although beta oscillations (≈ 13–35 Hz) are often considered as a sensorimotor rhythm, their functional role remains debated. In particular, the modulations of beta power during preparation and execution of complex movements in different contexts were barely investigated. Here, we analysed the beta oscillations recorded with electroencephalography (EEG) in a precued grasping task in which we manipulated two critical parameters: the grip type (precision vs. side grip) and the force (high vs. low force) required to pull an object along a horizontal axis. A cue was presented 3 s before a GO signal and provided full, partial or no information about the two movement parameters. We measured beta power over the centro-parietal areas during movement preparation and execution as well as during object hold. We explored the modulations of power in relation to the amount and type of prior information provided by the cue. We also investigated how beta power was affected by the grip and force parameters.

We observed an increase in beta power around the cue onset followed by a decrease during movement preparation and execution. These modulations were followed by a transient power increase during object hold. This pattern of modulations did not differ between the 4 movement types (2 grips ×2 forces). However, the amount and type of prior information provided by the cue had a significant effect on the beta power during the preparatory delay. We discuss how these results fit with current hypotheses on the functional role of beta oscillations.

Phase geometries of two-dimensional excitable waves govern self-organized morphodynamics of amoeboid cells

In both randomly moving Dictyostelium and mammalian cells, phosphatidylinositol (3,4,5)-trisphosphate and F-actin are known to propagate as waves at the membrane and act to push out the protruding edge. To date, however, the relationship between the wave geometry and the patterns of amoeboid shape change remains elusive. Here, by using phase map analysis, we show that morphology dynamics of randomly moving Dictyostelium discoideum cells can be characterized by the number, topology, and position of spatial phase singularities, i.e., points that represent organizing centers of rotating waves. A single isolated singularity near the cellular edge induced a rotational protrusion, whereas a pair of singularities supported a symmetric extension. These singularities appeared by strong phase resetting due to de novo nucleation at the back of preexisting waves. Analysis of a theoretical model indicated excitability of the system that is governed by positive feedback from phosphatidylinositol (3,4,5)-trisphosphate to PI3-kinase activation, and we showed experimentally that this requires F-actin. Furthermore, by incorporating membrane deformation into the model, we demonstrated that geometries of competing waves explain most of the observed semiperiodic changes in amoeboid morphology.

Alteration of sensory-evoked metabolic and oscillatory activities in the olfactory bulb of GLAST-deficient mice

Astrocytes are key cellular elements in both the tripartite synapse and the neurovascular unit. To fulfill this dual role in synaptic activity and metabolism, they express a panel of receptors and transporters that sense glutamate. Among them, the GLT-1 and GLAST transporters are known to regulate extracellular glutamate concentrations at excitatory synapses and consequently modulate glutamate receptor signaling. These major uptake systems are also involved in energy supply to neurons. However, the functional role of GLAST in concurrent regulation of metabolic and neuronal activity is currently unknown. We took advantage of the attractive structural and functional features of the main olfactory bulb to explore the impact of GLAST on sensory information processing while probing both glutamate uptake and neuronal activity in glomeruli and deeper cellular layers, respectively. Using odor-evoked 2-deoxyglucose imaging and local field potential recordings in GLAST knockout mice, we show in vivo that deletion of GLAST alters both glucose uptake and neuronal oscillations in olfactory bulb networks.

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.

Real-time brain oscillation detection and phase-locked stimulation using autoregressive spectral estimation and time-series forward prediction

Neural oscillations are important features in a working central nervous system, facilitating efficient communication across large networks of neurons. They are implicated in a diverse range of processes such as synchronization and synaptic plasticity, and can be seen in a variety of cognitive processes. For example, hippocampal theta oscillations are thought to be a crucial component of memory encoding and retrieval. To better study the role of these oscillations in various cognitive processes, and to be able to build clinical applications around them, accurate and precise estimations of the instantaneous frequency and phase are required. Here, we present methodology based on autoregressive modeling to accomplish this in real time. This allows the targeting of stimulation to a specific phase of a detected oscillation. We first assess performance of the algorithm on two signals where the exact phase and frequency are known. Then, using intracranial EEG recorded from two patients performing a Sternberg memory task, we characterize our algorithm's phase-locking performance on physiologic theta oscillations: optimizing algorithm parameters on the first patient using a genetic algorithm, we carried out cross-validation procedures on subsequent trials and electrodes within the same patient, as well as on data recorded from the second patient.

Reshaping of bulbar odor response by nasal flow rate in the rat

Background

The impact of respiratory dynamics on odor response has been poorly studied at the olfactory bulb level. However, it has been shown that sniffing in the behaving rodent is highly dynamic and varies both in frequency and flow rate. Bulbar odor response could vary with these sniffing parameter variations. Consequently, it is necessary to understand how nasal airflow can modify and shape odor response at the olfactory bulb level.

Methodology and Principal Findings

To assess this question, we used a double cannulation and simulated nasal airflow protocol on anesthetized rats to uncouple nasal airflow from animal respiration. Both mitral/tufted cell extracellular unit activity and local field potentials (LFPs) were recorded. We found that airflow changes in the normal range were sufficient to substantially reorganize the response of the olfactory bulb. In particular, cellular odor-evoked activities, LFP oscillations and spike phase-locking to LFPs were strongly modified by nasal flow rate.

Conclusion

Our results indicate the importance of reconsidering the notion of odor coding as odor response at the bulbar level is ceaselessly modified by respiratory dynamics.

Assessing instantaneous synchrony of nonlinear nonstationary oscillators in the brain

Neuronal populations throughout the brain achieve levels of synchronous electrophysiological activity as a consequence of both normal brain function as well as during pathological states such as in epileptic seizures. Understanding this synchrony and being able to quantitatively assess the dynamics with which neuronal oscillators across the brain couple their activity is a critical component toward decoding such complex behavior. Commonly applied techniques to resolve relationships between oscillators typically make assumptions of linearity and stationarity that are likely not to be valid for complex neural signals. In this study, intracranial electroencephalographic activity was recorded bilaterally in both hippocampi and in anteromedial thalamus of rat under normal conditions and during hypersynchronous seizure activity induced by focal injection of the epileptogenic agent kainic acid. Nonlinear oscillators were first extracted using empirical mode decomposition. The technique of eigenvalue decomposition was used to assess global phase synchrony of the highest energy oscillators. The Hilbert analytical technique was then used to measure instantaneous phase synchrony of these oscillators as they evolved in time. To test the reliability of this method, we first applied it to a system of two coupled Rössler attractors under varying levels of coupling with small frequency mismatch. The application of these analytical techniques to intracranially recorded brain signals provides a means for assessing how complex oscillatory behavior in the brain evolves and changes during both normal activity and as a consequence of diseased states without making restrictive and possibly erroneous assumptions of the linearity and stationarity of the underlying oscillatory activity.

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.

Olfactory function relies on a chain of neural relays that extends from the periphery to the central nervous system and implies neural activity with various timescales. A central question in neuroscience is how information is encoded by the neural activity. In the mammalian olfactory bulb, local neural activity oscillations in the 40–80 Hz range (gamma) may influence the timing of individual neuron activities such that olfactory information may be encoded in this way. In this study, we first characterize in vivo the detailed activity of individual neurons relative to the oscillation and find that, depending on their state, neurons can exhibit periodic activity patterns. We also find, at least qualitatively, a relation between this activity and a particular odor. This is reminiscent of general physical phenomena—the entrainment by an oscillation—and to verify this hypothesis, in a second phase, we build a biologically realistic model mimicking these in vivo conditions. Our model confirms quantitatively this hypothesis and reveals that entrainment is maximal in the gamma range. Taken together, our results suggest that the neuronal activity may be specifically formatted in time during the gamma oscillation in such a way that it could, at this stage, encode the odor.

The way an odor is experienced during aversive conditioning determines the extent of the network recruited during retrieval: a multisite electrophysiological study in rats

Recent findings have revealed the importance of orthonasal and retronasal olfaction in food memory, especially in conditioned odor aversion (COA); however, little is known about the dynamics of the cerebral circuit involved in the recognition of an odor as a toxic food signal and whether the activated network depends on the way (orthonasal vs retronasal) the odor was first experienced. In this study, we mapped the modulations of odor-induced oscillatory activities through COA learning using multisite recordings of local field potentials in behaving rats. During conditioning, orthonasal odor alone or associated with ingested odor was paired with immediate illness. For all animals, COA retrieval was assessed by orthonasal smelling only. Both types of conditioning induced similarly strong COA. Results pointed out (1) a predictive correlation between the emergence of powerful beta (15-40 Hz) activity and the behavioral expression of COA and (2) a differential network distribution of this beta activity according to the way the animals were exposed to the odor during conditioning. Indeed, for both types of conditioning, the aversive behavior was predicted by the emergence of a strong beta oscillatory activity in response to the odor in the olfactory bulb, piriform cortex, orbitofrontal cortex, and basolateral amygdala. This network was selectively extended to the infralimbic and insular cortices when the odor was ingested during acquisition. These differential networks could participate in different food odor memory; these results are discussed in line with recent behavioral results that indicate that COA can be formed over long odor-illness delays only if the odor is ingested.

Respiration-gated formation of gamma and beta neural assemblies in the mammalian olfactory bulb

A growing body of data suggests that information coding can be achieved not only by varying neuronal firing rate, but also by varying spike timing relative to network oscillations. In the olfactory bulb (OB) of a freely breathing anaesthetized mammal, odorant stimulation induces prominent oscillatory local field potential (LFP) activity in the beta (10-35 Hz) and gamma (40-80 Hz) ranges, which alternate during a respiratory cycle. At the same time, mitral/tufted (M/T) cells display respiration-modulated spiking patterns. Using simultaneous recordings of M/T unitary activities and LFP activity, we conducted an analysis of the temporal relationships between M/T cell spiking activity and both OB beta and gamma oscillations. We observed that M/T cells display a respiratory pattern that pre-tunes instantaneous frequencies to a gamma or beta regime. Consequently, M/T cell spikes become phase-locked to either gamma or beta LFP oscillations according to their frequency range and respiratory pattern. Our results suggest that slow respiratory dynamics pre-tune M/T cells to a preferential fast rhythm (beta or gamma) such that a spike-LFP coupling might occur when units and oscillation frequencies are in a compatible range. This double-coupling process might define two complementary beta- and gamma-neuronal assemblies along the course of a respiratory cycle.

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.

Efficient wavelet ridge extraction method for asymptotic signal analysis

A wavelet ridge extraction method is proposed for efficient estimation of instantaneous frequency and amplitude of the asymptotic signal. Inequalities are derived to provide limitations on scale interval and sampling frequency. The evaluation of optimal scale interval and sampling frequency at any given accuracy can be done by solving these inequalities and minimizing the computational complexity of continuous wavelet transform. After the continuous wavelet transform of the signal is completed with these optimal parameters, a more reliable ridge can be formed using only the discontinuity points on the ridge extracted using the conventional method. The results of a system identification simulation test performed to verify the efficiency of the proposed method indicate that the computational load of the proposed method is about 1/6 of that of the conventional method. When the system identification method is used to measure samples with known moment of inertia, the relative error below 0.08% is achieved.

Strong coupling between pyramidal cell activity and network oscillations in the olfactory cortex

Oscillatory activity is a prominent characteristic of electrophysiological recordings in the olfactory system and has been proposed to play a key role in encoding olfactory representations. Studies in several systems have shown that some aspects of information coding involve characteristics that intertwine spikes and fast oscillations (in the beta and gamma range) of local field potentials (LFP). In the insect olfactory system, it has been proposed that oscillatory activity could provide a temporal link between cells. Following previous data, we have proposed that gamma band oscillations in mammals could subserve a gating function for the transfer of information between the olfactory bulb (OB) and the anterior piriform cortex (aPC), which are functionally coupled. In this study, we used an electrophysiological approach to investigate the temporal relationship between LFP gamma oscillations and single-unit activity by simultaneously recording LFP and single unit discharges in the rat aPC during odor evoked activity. Our data showed that mean spike discharges and gamma oscillatory bursts were synchronized with the same respiratory cycle epoch (around the inspiration/expiration transition). Temporal correlations between spikes and LFP revealed that cortical cell spikes were tightly phase-coupled with the peak of gamma oscillations and that this phase-coupling was not odor-dependent. Our results suggest that gamma oscillation may act as a temporal filter. Oscillatory phase-coupled spikes in the OB could act in increasing the probability of spike emission in the aPC cell during a narrow time-window, explaining the tight phase-coupling observed in the aPC. The role of spike-LFP phase-coupling as a binding function between odor features is discussed.

The presence of pacemaker HCN channels identifies theta rhythmic GABAergic neurons in the medial septum

The medial septum (MS) is an indispensable component of the subcortical network which synchronizes the hippocampus at theta frequency during specific stages of information processing. GABAergic neurons exhibiting highly regular firing coupled to the hippocampal theta rhythm are thought to form the core of the MS rhythm-generating network. In recent studies the hyperpolarization-activated, cyclic nucleotide-gated non-selective cation (HCN) channel was shown to participate in theta synchronization of the medial septum. Here, we tested the hypothesis that HCN channel expression correlates with theta modulated firing behaviour of MS neurons by a combined anatomical and electrophysiological approach. HCN-expressing neurons represented a subpopulation of GABAergic cells in the MS partly overlapping with parvalbumin (PV)-containing neurons. Rhythmic firing in the theta frequency range was characteristic of all HCN-expressing neurons. In contrast, only a minority of HCN-negative cells displayed theta related activity. All HCN cells had tight phase coupling to hippocampal theta waves. As a group, PV-expressing HCN neurons had a marked bimodal phase distribution, whereas PV-immunonegative HCN neurons did not show group-level phase preference despite significant individual phase coupling. Microiontophoretic blockade of HCN channels resulted in the reduction of discharge frequency, but theta rhythmic firing was perturbed only in a few cases. Our data imply that HCN-expressing GABAergic neurons provide rhythmic drive in all phases of the hippocampal theta activity. In most MS theta cells rhythm genesis is apparently determined by interactions at the level of the network rather than by the pacemaking property of HCN channels alone.